1
NUTRITIONAL STATUS OF ADOLESCENT
SCHOOL GIRLS AND ITS DETERMINANTS IN A
RURAL AREA OF IMO STATE
A DISSERTATION SUBMITTED TO
THE NATIONAL POSTGRADUATE MEDICAL COLLEGE OF
NIGERIA IN PART FULFILLMENT OF THE REQUIREMENTS
FOR THE FELLOWSHIP OF THE COLLEGE.
BY
DR FRANCIS UCHECHI IREGBU,
MB,BS (NIGERIA) 1999
2
DECLARATION
It is hereby declared that this work is original unless otherwise acknowledged.
The work has not been presented to any other College for a Fellowship nor, has it
been submitted elsewhere for publication
..............................................................................
DR. FRANCIS UCHECHI IREGBU
Date: .........................
3
CERTIFICATE PAGE
The study reported in this dissertation was done by the candidate under our
supervision. We have also supervised the writing of the dissertation.
Signature: ..................................................................
Name of Supervisor: TC Okeahialam, FMC Paed, FWACP
Status of supervisor: Professor of Paediatrics
Date .......................................
Signature: .......................................
Name of supervisor: Dr. ARC Nwokocha, FMCPaed
Status of supervisor: Consultant Paediatrician
Date: ........................................
4
TABLE OF CONTENTS
PAGE
Declaration i
Certificate page ii
Table of contents iii
Abbreviations v
List of tables vi
List of figures viii
Definition of terms ix
Dedication xi
Acknowledgements xii
Summary xiii
Introduction 1
Literature review 4
Aims and objectives 44
Justification 45
Methodology 46
Results 61
5
Discussion 89
Conclusions 99
Recommendations 100
Limitations of the study 101
Future research 102
References 103
Appendices 121
6
ABBREVIATIONS
BMI: Body mass index
cm: centimetre
EDTA: Ethylenediaminetetraacetic acid
FAO: Food and Agriculture Organisation
FMC: Federal Medical Centre
Hb: haemoglobin
Kg: kilogramme
NCHS: National Centre for Health Statistics
SPSS: Statistical Package for the Social Sciences
TIBC: Total iron binding capacity
WHO: World Health Organisation
7
LIST OF TABLES
Page
Table I: Means of some population indices ………… 62
Table II: Population characteristics of the students …………. 64
Table III: Distribution of subjects by parental occupation and educational
attainment …………………….. 65
Table IV: Prevalence of underweight, overweight and obesity by age groups …67
Table V: Prevalence of stunting by age …………………………. 68
Table VI: Nutritional status(BMI category) by family size and income ……. 69
Table VIIA: Nutritional status(BMI category) by mother’s educational attainment
…………………… 71
Table VIIB: Nutritional status(BMI category) by father’s educational attainment
…………………… 72
Table VIIIA: Nutritional status by father’s occupation ……………….. 74
Table VIIIB: Nutritional status by mother’s occupation ………………. 75
Table IX: Nutritional status by social class …………………… 76
Table X: Distribution of stunting by social class …………………… 77
Table XIA: Distribution of stunting by paternal education ………………. 78
Table XIB: Distribution of stunting by maternal education ……………… 78
Table XII: Nutritional status by sexual maturity(menarcheal status) …….. 79
8
Table XIII: Menarcheal status by social class ……………….. 80
Table XIV: Results of logistic regression analysis ……………….. 82
Table XV: Summary of iron status results ………………… 83
Table XVI: Prevalence of iron deficiency by age ………………… 84
Table XVII: Prevalence of anaemia and and iron deficiency anaemia …….. 84
Table XVIII: Iron deficiency by maternal education ………………… 87
9
LIST OF FIGURES
Page
Figure I : Summary of clinical examination findings .................................. 66
Figure II: Distribution of iron status in different income categories …… 85
Figure III: Iron status in the different social classes ……………………. 86
Figure IV : Distribution of helminths in the student population ................. 88
10
DEFINITION OF TERMS
Nutrition
The process of taking in and metabolising food whereby tissue is built up and
energy is liberated.1
Malnutrition:
A condition of impairment of health caused by deficiency, excess or imbalance
of nutrients(calories, protein, vitamins, and minerals) in the body. It does not
simply denote undernourishment.2
Adolescent: an individual who is in the transition period from childhood to
adulthood. It commonly refers to someone between the ages of ten and nineteen
years.3
Early adolescence: this is the beginning of adolescence and is defined as the
period between 10 and 13 years.4
Mid adolescence: this refers to the age group of between 14 and 16 years.4
Late adolescence: this is the period that marks the end of adolescence and it refers
to the ages of 17 to 19 years.4
Body mass index( BMI):
A statistical calculation used to estimate a healthy body weight based on how tall a
person is. It is calculated as weight in kilograms divided by height in metres
11
squared, expressed in kg/m2. BMI can also be measured using the BMI chart which
has colours for the different BMI categories.5
Underweight:
BMI less than18.5kg/m2 or BMI less than the 5th percentile of age- and sex-
specific values of a reference, usually the WHO/NCHS. It can also be described as
low weight-for-age.3
Stunting:
Height less than 5th percentile of the reference or height-for-age z-scores less
than 2 standard deviations below the mean of a reference population.3 It is
indicative of long term malnutrition.
Overweight:
BMI between 25 and 29.9kg/m2 or BMI greater than the 85th percentile of age-
and sex-specific values.3
Obesity:
BMI greater than or equal to 30kg/m2 or BMI greater than or equal to
the 95th percentile of age- and sex-specific values.3
Transferrin Saturation:
This is the ratio of serum iron to total iron binding capacity (TIBC). Iron
deficiency results in a net reduction of transferrin saturation.6
12
DEDICATION
This work is dedicated to my wife Chinwe who has been a solid rock through the
period of training and to our children Chukwuka, Chiamaka and Olaedo.
13
ACKNOWLEDGEMENT
My gratitude goes to the school girls, parents and guardians as well as the teachers
who participated in this study.
I am grateful to my supervisors- Professor T.C. Okeahialam and Dr. A.R.C.
Nwokocha for their support, encouragement and invaluable guidance in the course
of this study. I am also grateful to Dr. K. Achigbu for his painstaking review of the
drafts of this work, and to Dr. T.C. Ezeofor for pointing me in this direction and
for assisting with some key materials.
Profound appreciation goes to members of the field team- Dr. I. Ahuche, Dr. K.
Aguh, and Dr. P. Anyaji who proved ever so adept at blood collection. I am also
grateful to Mr. J. Okwara, Mr. G. Nwanguma, Mr. O. Chijioke and Ms. C. Okoro
who assisted me in the analysis of the specimens. I appreciate Mr C. Ebirim for his
assistance with data management.
I eternally appreciate my wife, Chinwe whose soothing presence during the field
work provided a calming effect on the girls. I am also grateful to my sister, Mrs
M.C. Asodike and her husband, Dr. V.C. Asodike who together have been great
stabilising forces during the residency training.
Finally, I thank God Almighty who made everything possible.
14
SUMMARY
The study is a descriptive cross-sectional survey of the nutritional status of
adolescent school girls in Ogbaku, a rural community near Owerri, the Imo State
capital in the South East zone of Nigeria. The survey was conducted over the
period of October to November 2009. A total of 229 girls between 11 and 19 years
resident in the community were studied. These were drawn from the only public
girls’ school and one of the private co-educational schools in the town.
Clinical assessment and anthropometric measurements were done. In addition,
blood samples for haemoglobin, serum iron, total iron binding capacity(TIBC), and
serum ferritin were collected. Stool samples were taken for analysis for helminths.
Socio-economic data were also obtained from the girls. Body mass index
percentiles and height-for-age z-scores of the WHO reference113 were used to
determine the nutritional status. A combination of low serum ferritin and low
transferrin saturation were used to determine iron deficiency. Social classification
was done using the Olusanya criteria.57
The mean age of the girls was 15.8 ± 1.8 years while the means for height, weight
and BMI were 157.66± 7.6 cm, 49.1± 7.8 kg, and 19.73 ± 2.5kg/m2 , respectively.
15
Average age at menarche was 13.39 ± 1.1 years. Haemoglobin ranged from 8.9 to
16.1g/dl with a mean of 11.0 ± 1.1g/dl. The mean serum iron, TIBC and ferritin
values were 71.5µg/dl, 371.5µg/dl and 37.4µg/ml, respectively.
The study showed a prevalence of underweight, overweight and stunting of 16.6%,
6.1% and 7.0%, respectively. None of the subjects was obese. There was a direct
relationship between the BMI status and age, one increasing with the other. The
prevalence of underweight was significantly increased by younger age(p=0.001)
and low social class(p=0.001). Similarly, the prevalence of stunting was increased
by younger age(p=0.022) and by low social class(p=0.026). Greater household size
also led to significantly higher prevalence of underweight (p= 0.020).
On logistic regression analysis, the factors that significantly influenced the
nutritional status of the girls were early adolescence(age 11 to 13 years), family
size 10 or greater, and social classes III and V. Students who were in early
adolescence had 8.3 times higher likelihood of being underweight than those in late
adolescence(CI= 2.716-25.3). Girls whose family sizes were 10 or greater were 3
times as likely to be underweight as those with family sizes 1 to 3(CI=1.130-
8.210). The risk of undernutrition in adolescents belonging to social III was 6.8
times more than those in social class I (CI=1.28-36.6), while girls in social class V
had 6.6 times (CI= 1.836-23.79) more risk of underweight than their counterparts
in social class I.
16
Anaemia was widely prevalent at 77.8 percent while the prevalence of iron
deficiency was 13.9 percent. Iron deficiency anemia was seen in 12.5 percent of
the girls. Of the socio-economic parameters, only maternal education significantly
affected iron status(P=0.019). Among the girls who had attained menarche, 16.3%
were underweight compared with 83.7% who were of normal weight and above.
Additionally, 100 percent of girls in social class I had attained menarche compared
with 89.2 percent in class V. Hookworm was the most common intestinal parasite
identified with a prevalence of 13 percent.
The findings in this study indicate that the current state of nutrition in this
community is poor, especially in the lower socio-economic strata. Hence deliberate
actions aimed at ameliorating the heightened effects of the currrent economic
downturn on poor families are needed. Also desirable is periodic nutritional
survey of the children in order to detect areas of need for specific intervention.
17
INTRODUCTION
Adolescence is a period of maturation from childhood to adulthood. According to
the World Health Organisation, WHO, it is the period between the ages of 10 and
19 years.3 It is estimated that 1.2 billion individuals, about 20% of the global
population, are adolescents.7 Of this number, 85% live in the developing world.3
The adolescent period is characterised by rapid growth. About 25% of an
adolescent girl’s final adult height and 50% of her adult weight are achieved during
this period.8 As a result, nutritional requirements are high and malnutrition can
easily result.
Adolescent girl malnutrition is important as it not only affects the girl child but
also influences her future reproductive role. A number of factors are considered
important determinants of nutritional status in an adolescent. Poverty is a
significant factor, especially in the rural areas where food intake is frequently less
than optimal.9-11 Negative cultural practices especially gender-based discrimination
in food intake and health care provisions can also affect girl child nutrition.12,13 In
addition is the physical stress which may come from hard manual work in farming
communities leading to increased nutritional requirements.11,14 This increased
needs may not be fully met by the limited resources available. Traditional
18
household chores often undertaken by girls may also involve considerable
expenditure of energy. Emotional and psychological challenges are common in this
period and may manifest in eating disorders and poor eating habits.15,16 At this age
also, menarche sets in and the demands of menstruation imposes an extra
nutritional burden on the child.2,3,17,18
Micronutrient deficiencies especially iron, folic acid and vitamin A are common in
many parts of the world among adolescents.2 Maternal anaemia, which usually has
its roots within adolescence, is known to increase the risk of preterm delivery and
low birth weight.l9,20 The negative impact of iron deficiency on cognitive function
and consequent academic performance is well recognised.17,21,22 It is also known
that poor nutrition in this period is a precursor of chronic diseases in adulthood.23,24
It is in this light that the interest in adolescent nutrition can be appreciated.
Nutritional anthropometry is regarded as an important preliminary tool in
evaluating adolescent nutrition.3,25,26 Concerns exist as to the standards of
measurement across diverse populations and ethnicities27,28 However, the WHO
recommends the WHO/NCHS reference for uniformity.3 Overweight and obesity
are common problems in Europe and North America29,30 while stunting and
underweight are more prevalent in South East Asia and sub-Saharan Africa.9,12,31-33
Interest in adolescent nutrition in developing countries is a relatively recent
phenomenon as previous efforts had mostly focused on the pre-school child.3 As a
19
result, scanty information exists on the nutritional status of adolescent girls in
Nigeria generally and Imo state in particular, especially in the rural setting.
Adolescence is also considered the last window of opportunity for nutritional
interventions.3,31,34,35 It is therefore desirable to have a better understanding of
adolescent nutritional status and its associated factors in our environment.
20
REVIEW OF LITERATURE
An individual’s nutritional status is essentially determined by intake of an adequate
diet.26 Adequacy of diet is in turn known to be influenced by several factors among
which are cultural traditions, and the socio-economic conditions in the family.36
Another important determinant of nutritional status is the nature of the health
environment. This is defined by factors such as sanitation and access to safe water,
the absence of which can lead to infection.36,37 Lucas38 recognises the role of
infection on the nutritional status of a community; malnutrition is known to
predispose to infections while infections can make malnutrition worse.
Additionally, variables such as women’s education and women’s status in the
society are also considered important.37,39-42 It is believed that women who are
empowered by education are more able to deliver quality care to their children.
According to Neumark-Sztainer et al,15 there is a high incidence of inadequate
intake and disordered eating habits in adolescents. Low levels of consumption of
fruits and vegetables were reported. This study also documented chronic dieting
and binge eating, especially among the overweight group of adolescents. However,
the body mass index(BMI ) of the survey population were derived from self-
21
reported heights and weights. This represents a potential for error in the
classification of nutritional status.
The rate of growth substantially influences a child’s nutritional requirements.27
Since adolescents grow faster during this period than at any other period after the
first year of life, their nutritional requirements at this time are correspondingly
high.2 Woodruff and Duffield27 documented an energy requirement of 2420kcal per
day for adolescents to be the highest of any age group. In the presence of these
high nutrient requirements, the adolescent is easily vulnerable to undernutrition.
Availability of food in terms of quantity and quality determines the dietary intake
of adolescent girls which in turn is closely allied to their physical growth.
Adolescents are recognised as a diverse group with significant differences
manifesting between age-groups, in gender and social class.43 The adolescent
period is commonly classified into early(10-14) and late adolescence(15-19).7
Other classifications recognise early(10-13), middle(14-16) and late(17 and older)
adolescence.4,44 This division recognises different stages of development which is
physical, social and emotional as well as cognitive. In the developmental pathway
from childhood to adulthood, the individual goes through the steps of completing
puberty and somatic growth. This is followed by social, emotional and cognitive
development, moving from concrete to abstract thinking. In the later years, an
independent identity is established and preparation for a career or vocation ensues.4
22
OVERVIEW OF ESSENTIAL NUTRIENTS
The three basic needs for health and growth are energy, water and protein with
vitamins, minerals and specific fatty acids added in smaller amounts.45 Energy
needs are met mostly from carbohydrate and fats.
Protein and Energy
Protein provides about 4 calories per kilogram.45 The human diet requires a
specific group of proteins, the essential amino acids, for optimal nutrition. Animal
protein from muscle tissue, eggs and milk supply these requirements in appropriate
proportion. Requirements increase with conditions like burns, trauma and severe
sepsis, while deficiencies easily affect tissues with rapid turnover rates, such as the
immune system and the gastrointestinal mucosa.46
Fats are an important provider of energy, yielding about 9 calories per gram.45
They are required for the absorption of fat soluble vitamins and for the myelination
of the central nervous sysytem. Due to concerns about heart disease, it is
recommended that fat intake not exceed 30% of total calories after 2 years of age.45
Deficiency of essential fatty acids result in growth failure, abnormal scaliness,
thrombocytopaenia and increased susceptibility to infections.46
The energy density of carbohydrates is 4kcal/g. They are required in relatively high
amounts as energy source; this is to limit the amount of protein and fats ingested
23
both of which are potentially toxic in excess amounts.45 Carbohydrates are
recommended to make up 55% to 60% of calories, including not more than 10%
from simple sugars, after the first two years of life.46 Adolescents are however
known to consume a lot of these simple sugars. According to Frary et al,47 teens
consume more added sugars as a percentage of total energy intake than any other
group, with these sugars constituting about 20% of their total energy intake. It was
also discovered that as the intake of these sugar-sweetened beverages increased,
the overall quality of diet declined, including the consumption of fruits, vegetables
and calcium.
Iron
Iron is an essential constituent of the red blood cell with which oxygen is carried
around the body. It is also useful in energy metabolism and for the normal function
of the immune system.48 Iron needs increase during adolescence due to the growth
spurt, with expanding blood volume and increasing muscle mass.18 Rich sources of
iron include red meat, egg yolk, and fish. Iron from haem sources such as red meat
is absorbed best while non-haem iron(from grains and vegetables) is not so well
absorbed.49 Generally, nutritional factors such as poor intake, low bioavailability of
dietary iron, gastrointestinal loss, and increased requirements for growth are
considered the most frequent causes of anaemia and iron deficiency in
childhoodand in reproductive-age women especially in developing countries.2,50
24
Across all ages in sub-Saharan Africa, malaria is also a very important cause of
anaemia.
Clinical features of anaemia and iron deficiency include pallor, lassitude and
general feelings of lack of energy. Other manifestations include glossitis, angular
stomatitis and koilonychia. There may also be behavioural disturbances such as
pica- the eating of non food materials.48 In advanced cases of iron deficiency
anaemia, anorexia and irritability may be evident, reflecting tissue iron
deficiency.51
Calcium
Calcium is the primary mineral in the bone. The major dietary sources are milk and
other dairy products. Rapid growth creates a higher calcium requirement in
adolescents than any other group outside pregnant women.27 In the adolescent peak
years of skeletal growth, over 25% of adult bone are accumulated.52 Deficiency in
dietary calcium results in failure to achieve peak bone density in the adolescent
period, increasing the risk for the development of postmenopausal osteoporosis.35,
52
Vitamin A, C, the B-vitamins, and minerals are required in relatively small
amounts but are no less important for optimal nutrition. Vitamin A is important for
25
vision while the B vitamins are important constituents of several enzyme
systems.53
Folic acid
Folic acid or folate is a cofactor for many important cellular reactions in the body
including cell division.19 It is found in leafy green vegetables and dried beans. Low
folate intake is known to be common in many reproductive age women, and neural
tube defects have been described in children born to folate-deficient mothers.19
Those who overcook their food and individuals who do not eat fresh fruits and
vegetables are also at risk of folate deficiency.54
DETERMINANTS OF NUTRITIONAL STATUS
Political, socio-economic, psychological and livelihood factors such as sedentary
lifestyle, heavy physical work, smoking and alcohol are known to influence
nutrition.3 Socio-economic factors determine access to food and food supplies.
These factors include income available to the family or community, maternal
education and the quality of the health environment.37 Political factors include
instability, wars and inter-tribal upheavals which affect the economy negatively.27
Among the psychological factors are the eating habits of adolescents and the
presence of eating disorders.3 Cultural factors such as food taboos may adversely
26
affect nutrition. Vagaries of nature such as floods and earthquakes that affect food
production may also influence nutrition periodically.
Socio-economic factors
A cycle has been described linking poverty with malnutrition and disease.36,55
Income poverty is associated with low food intake, frequent infections and
eventually malnutrition and poverty. On a larger scale, malnutrition takes a great
toll on the economy of the country. It was estimated that the annual economic loss
to Nigeria from childhood malnutrition stood at $489 million or about 1.5% of the
Gross Domestic Product,GDP.56
Social Class and Family Income
Indices commonly used to measure socio-economic status include parental
education and occupation, especially maternal education and father’s occupation.
This is the method described by Olusanya et al57 and frequently applied in
paediatric surveys10,26,39, Information on family size and financial holdings
including tangible assests have also been used to classify the socio-economic
class.11,58,59. While asset proxy measurements are becoming popular, there are still
controversies surrounding the reliability of its use and the common standards of
stratification59,60 There is as yet no agreement on the choice of assets to include and
the implications of having particular assets.61
27
Nwokocha,62 in an article on adolescent growth and development, identified the
socio-economic class as having the most important and significant effect on
puberty, with nutrition being most affected.
Using data from the 2003 Nigeria Demographic and Health Survey(NDHS),
Uthman42 showed a high level of stunting and underweight in the poorest
households among under-five children. About 44% of the children from the
poorest homes were stunted compared to 18.4% from the richest homes.
Underweight prevalence followed a similar trend being 26.8% and 10.3% in the
poorest and richest households, respectively. In addition, wide geographical
variations were documented, with stunting being most prevalent in the North East
and North West regions, areas known to have high levels of household poverty.
In India where the caste system operates, Venkaiah et al63 in a cross-sectional
randomised study found that in a population of rural adolescents, stunting was
significantly higher among the caste community. The prevalence of underweight
was also significantly associated with this group of underpriviledged adolescents.
Additionally, families of labourers and those living in houses made of mud walls
and thatched roof had high levels of both underweight and stunting, indicating the
role of the social class in nutrition. Conversely however, Choudhary et al36 also in
India found that neither the caste nor the type of house, both indicators of social
class, had significant association with the nutritional status of rural adolescent girls
28
in Varanasi, India. With respect to the type of house, there was not a clear
description of the nature of the structures by the authors. Besides, residents were
said to live in mixed dwellings, making it difficult to appreciate clear lines of
demarcation and the basis for social stratification.
Poor societies with scarce resources always grapple with the problem of food.
Cleaver et al56 acknowledged food availability as a burning issue in the resource-
poor setting of sub-Saharan Africa. While noting its unenviable position globally,
they recognized the challenges posed by lack of purchasing power in accessing
food. Senbanjo et al39 identified significantly higher levels of wasting in children
whose mothers earned less than ten thousand naira per month than in children
whose mothers earned more. Interestingly, no such difference was observed with
respect to paternal income. This may be due to the fact that fathers applied a
substantial part of their income to uses which may not directly influence a child’s
nutritional status such as paying of bills and meeting of social obligations.
Choudhary et al36 noted that adolescent undernutrition was higher in subjects
whose families’ main occupation was in labour compared to others in the service
class, business and agriculture. In this study, the difference between these two
main groups was statistically significant, whereas there was statistical similarity
among the business, service and agriculture groups. Since occupation is considered
an important determinant of social classification,57 it could be assumed that
29
adolescents whose families were in the latter occupations enjoyed a higher social
standing than the former. Although agriculture is not considered a high class
occupation in most developing countries, the relatively lower levels of
undernutrition observed may be as a result of such families feeding directly from
the proceeds of their work.
In Cameroun, Kurz and Som10 also showed household low socio-economic status
to be the best indicator of poor nutritional status in adolescents, being predictive of
underweight. In that study, low socio-economic status correlated with low intakes
of energy, protein, iron-rich foods and vitamin A. However, contrary to
expectations, similar average socio-economic status existed between those who
were anaemic and those who were not using a minimum haemoglobin cut-off of
11.5g/dl. In their summary of the Minnesota Adolescent Health Survey, MAHS,
Neumark-Sztainer et al15 identified low socio-economic status as a risk factor for
inadequate food intake, with its attendant risk for malnutrition.
Family Size
Larger family size is frequently seen among the poor. Gopalan64 identified large
family size as part of poverty syndrome that also includes poor education and
environment as a key cause of undernutrition. Evidence exists to the effect that in
homes where the family size is large, the frequency of malnutrition is
30
correspondingly high. Uthman42 revealed such findings in his review of the
Nigerian National Health data showing higher rates of malnutrition with increasing
family size. The family sizes were however not recorded.
Venkaiah et al63 found a higher risk of undernutrition in adolescents who belong to
family size greater than 4. This higher risk was however slight and not statistically
significant. While comparing the burden of undernutrition in different family sizes,
Choudhary et al36 observed that as the family size increased from 6 to 7-12, there
was a corresponding increase in the prevalence of undernutrition from 71.83% to
72.14%. However, as the family size increased to above 12, there was a reverse in
the progression, reducing instead to 55.93%. Although no reason was put forward
by the researchers to explain this trend, the reversal in the prevalence of
undernutrition in families which sizes exceeded 12 may point to the protective
effect of the extended family.
Place of dwelling
Urban dwelling is associated with better indices of nutrition.9 The widespread
public services in the urban centres increases the availability of health care. There
are also opportunities for better sanitation and potable water, both markers of
improved living conditions.40 However, problems associated with urban growth
31
such as overcrowding, especially in poor areas, may mean that sometimes this
advantage is not fully felt.65
In Rivers State, Nigeria, Brabin et al33 demonstrated higher prevalence of
underweight among rural girls than in their urban counterparts. Of the rural
adolescents, 15.6% were underweight while 8.0% of an urban population of similar
age resident in Port Harcourt were classified as underweight. Stunting also affected
more rural girls(10.4%) than urban(4.7%). Oninla et al66 in a comparative study of
the nutritional status of urban and rural school children in Ife, South-West Nigeria
showed better nutritional indices for the urban children. The prevalent rates of
underweight and stunting for the rural population were 70.5% and 35.8%, while in
the urban area they were 52.2 and 19.8%, respectively. Similar findings were
reported by Olumakaiye in which a higher prevalence of undernutrition was found
in rural adolescents relative to their urban counterparts.9
In a cross-sectional study of the food habits of urban and rural adolescents in
Cameroun, a clear difference was demonstrated in the consumption of certain types
of food by Dapi et al.11 It was also determined that meat, fish and eggs were more
available and affordable in the urban areas and therefore were consumed more.
Consumption of these food items in the rural areas was only on special occassions
as a result of high prices and low availabilty. This study had a sample size of only
fifty two and this may not be adequately representative of the population. Thus,
32
certain conclusions drawn from it may be incomplete. Furthermore, the sample
population was limited to the ages of twelve and fifteen; it is possible that older
adolescents might have more say in what they eat. Kurz and Som10 reported lower
energy intakes in adolescent girls who resided in rural areas than in their urban
counterparts. This trend was also replicated for protein intake.
Maternal Education
In a study of the influence of socio-economic factors on nutritional status of
children in a rural community in Osun state, Nigeria, Senbanjo, Adeodu and
Adejuyigbe39 determined that lower maternal education had a positive relationship
with rates of underweight. The prevalence of underweight was three times as high
in children whose mothers had secondary school education or lower as in children
whose mothers had post secondary education. Additionally, the prevalence of
stunting was one and a half to two times in children of mothers who were not
educated beyond the secondary school level compared with those whose mothers
had post secondary education. However, these observed differences were not
statistically significant. This may be due to the generally low prevalence of
malnutrition found in this community. Another factor may be the composition of
the community. It has a largely homogenous nature which resulted in most of the
families belonging to roughly the same socio-economic class.
33
Uthman42 determined that children of illiterate mothers had higher prevalence of
malnutrition. This is similar to findings from Cameroun40 and Peru.41 Using pooled
cross-sectional data from health surveys in Cameroun, Pongou, Salomon and
Ezzati40 determined that low maternal education negatively affected the nutritional
status of children of the survey population. Children whose mothers had secondary
education or higher were found to be better protected from malnutrition. This
relatively better protection may be as a result of these mothers being more capable
of using cost-effective alternative nutrient sources in times of lack.
The positive relationship between parental education and better nutrition was again
demonstrated by Choudhary et al.36 The extent of undernutrition was 86.1% in
subjects with illiterate or just literate parents compared to 64.04% and 45.0%
where the highest educational attainment was secondary school or above,
respectively. However, contrary to previous observations,39-42 these differences
stemmed not from the influence of maternal education but from paternal
educational attainment. With varying levels of paternal education, there existed
significant differences in nutritional status( p<0.001). There was no significant
association of maternal education with nutritional status of the adolescent girls(
p>0.05). The traditional nature of this society in which women’s role vary little or
not at all with education may account for maternal education not playing a
significant part in determining adolescents’ nutritional status.
34
Studying a periurban population of greater Lima in Peru, Wachs et al41
demonstrated a significantly positive relationship between maternal education and
child’s weight and length. In addition, children of more educated women were
found to be taller than those of less educated women. The effect of genes however
was not assessed as parental anthropometry was not done. Furthermore, less than
half of the initial subjects finished the study as the investigators’ finances
dwindled.
Reed, Habicht and Niameogo67 also documented better nutritional status with
improved maternal education. In this study conducted in rural Benin Republic, it
was shown that weight-for-age improved with maternal education. This
improvement was only for up to four years of education, and in the middle socio-
economic stratum. However, above four years of education and in the high and low
socio-economic groups, this relationship did not hold. A reason adduced for this is
that the better educated women of this community engaged more in economic
activities which put pressure on their time to the detriment of childcare. This study
used weight-for-age as the only index of nutritional status and findings using other
indices might have led to different outcomes.
35
Cultural factors
In parts of Africa and Asia, some cultural practices play a negative role in the
health and well being of the female adolescent. Choudhary et al12 recognized
gender-based discrimnations in the areas of educational opportunities, expenditure
on health care, and nutrition. Apart from reasons of physiology, women are
known to be more likely than men to suffer nutritional deficiences on account of
several cultural factors. These include low social status and cultural norms about
eating.2,68
In many societies, the adolescent female spends many hours and expends
considerable energy in daily tasks of the household.55 In some communities, the
culture forbids females the eating of certain meat such as rabbits, snails, and edible
insects, and these may be the major available sources of protein68
In rural poor households, there is frequently an uneven distribution of food intake,
with men and boys being favoured.12 This has been recognised as an important
cause of inadequate intake for females. In some communities, women and girls eat
only the food that is left after the male members of the family have eaten.This still
obtains even when females do the heavy work.69
36
Psychological factors
As social interactions increase from primary school to adolescence, so does the
tendency for dietary habits to change in a substantial manner. Naturally,
adolescents are prone to unhealthy eating habits. Some of the unwholesome dietary
patterns observed in adolescents include snacking, usually on nutrient-poor items,
meal skipping and irregular eating patterns.43,70,71 A review of adolescent food
intake trends in the US from 1965 to 1996 by Cavadini et al72 showed an
increasing tendency to the consumption of simple carbohydrates and a reduction of
fruit and vegetable intake.
Another common habit identified with adolescents is meal skipping, with females
more at risk. Kehski-Rahkonen et al,70 in a study of adolescent and adult eating
patterns in Finland associated breakfast skipping with health compromising
behaviours such as smoking, frequent drinking of alcohol, and not exercising. It is
thought that these breakfast skippers are in the habit of making unhealthy food
choices in order to make up for the missed breakfast. Hence they tended to have a
higher BMI. Adolescents who skipped breakfast were also more likely to use
coffee and decaffeinated sodas than regular breakfast eaters. On the reverse side,
better education and higher socio-economic status were positively correlated with
breakfast eating.
37
Food choices reflect diverse influences ranging from parents and peers to
television. The role of television is deemed crucial as adolescents are always
attracted to it. Instructively, Powell, Szczypka and Chaloupka73 in a sample of top-
rated television shows, recognised that the majority(up to 89.4%) of the food
product adverts viewed by adolescents were of poor nutritional content, being high
in either fat, sugar or salt. In the sample, the largest food category of adverts seen
was for sweet products most of which were also high in saturated fat.
Adolescent girls are particularly concerned about body image.35,71,74 Tiggemann et
al75 identified pressures from models and the media, as well as the desire for
attractiveness and attention as driving adolescent girls. Also identified were the
desire to fit into clothes, and to achieve a feeling of control. Even individuals
whose BMI fell in the normal range see themselves as overweight. They have also
frequently expressed the wish to be thinner, reflecting the influence of models and
celebrities which they so often encounter in the media.43,71
Political factors
Politics may influence the availability of important agricultural inputs such as
irrigation, fertilizer and seeds. This could in turn affect food production with its
consequent effect on food intake and nutritional status.56 Furthermore, political
instability tends to shift attention away from agriculture.
38
Often, in developing countries like Nigeria, political considerations at the national
level determine food security at the household levels. It is also at this level that the
effect of food insecurity is most felt.56 In periods of food insecurity, quality and
variety are first sacrificed to quantity.With worsening conditions, even quantity
eventually declines.76
Presence of support services including a strong primary health care is associated
with better nutritional indices. Senbanjo et al39 reported a low prevalence of
malnutrition in a rural community, Ifewara in Osun state, which had adequate
social amenities, access to basic health care, and nutritional interventions.
MAIN NUTRITIONAL PROBLEMS OF ADOLESCENCE
Micronutrient Deficiencies
Iron deficiency is the consequence of long-term negative iron balance in which
stores no longer meet the needs of normal iron turnover. In this condition, the
supply of iron to the tissues is compromised.6 The development of iron deficiency
anaemia begins with a series of steps in which, first, the iron stores are depleted.
Then there is a loss of transport iron reflected by reduced serum iron levels, and
finally overt anaemia.50,77 Hence the more severe stages of iron deficiency are
associated with anaemia.
39
Anaemia and iron deficiency have been described as pervasive nutritional
deficiencies globally.2,3 They have also been identified as being most common
among groups of low socio-economic status.6 According to Lawson et al,78 fast-
growing children are at risk of iron deficiency. Poor diet, rapid growth and
menstruation are prominent occurences in the female adolescent, and combination
of these events leads to a greater iron requirement.49,51 If these needs are not duly
met, the adolescent is liable to grow up having less than enough iron stores before
the first pregnancy.
Iron deficiency anaemia may occur in obese or underweight children.51 Despite
being a widespread deficiency, Sharma, Prasad and Rao79 in their studies suggested
that prevalence of anaemia was lower in those who were taller or heavier than
those who were shorter or lower in weight for a given age. Additionally, greater
rural than urban prevalence has been found for anaemia and iron deficiency in line
with overall nutrition profile.79,80 Brabin et al33 found that low BMI was
significantly corelated with lower haemoglobin status, also implying an association
of general malnutrition with anaemia.
Choudhary et al12 reported a prevalence of anaemia(Hb<12g/dl) of 30.74% among
rural adolescent girls in the Varanasi district of India, with 2.2% having marked
anaemia(Hb<10g/dl). The study also revealed that in areas where open field
defecation was the practice, a statistically significant difference in
40
anaemia(p<0.001) existed between the group which wore footwear to defecate and
that which did not. This implies that the effect of hookworm infestation leading to
anaemia was considerable among the population which did not wear footwear.
However, the contribution of other factors to anaemia was not assessed and these
could be significant while at the same time being prevalent in the same individuals
in whom hookworm infestations were found.
Using the ELISA technique to measure serum ferritin levels, Vasanthi et al80 in
rural India reported a prevalence of 16% of iron deficiency among the adolescent
girls. With a cut-off of 12g/dl, a higher prevalence of anaemia was reported in girls
who had attained menarche than in those who had not(27% vs 24.2%).
In Akwa-Ibom state, Nigeria, Ekpo and Jimmy49 reported a 4% prevalence of
anaemia with haemoglobin levels less than 10g/dl and haematocrit of less than
30%. This was in a study of adolescent females aged between 12 and 18 years
from secondary schools across the state. This prevalence is lower than values
reported from India12,34 and reflects the lower cut-off used in the Nigerian study.
Using the HemoCue method, Brabin et al33 documented anaemia prevalence of
59.1%(Hb<12g/dl) in an adolescent population in Rivers state, with 0.7% classified
as having severe anaemia(Hb<8g/dl).
41
Beard48 described an increased risk of infection during iron deficiency, with
cellular immunity being particularly affected. Anaemia also affects pregnancy
outcomes, leading to increased risk of low birth weight, prematurity, and IUD.17
Up to 35% of preventable LBW has been attributable to iron deficiency.2
Iron deficiency is known to affect cognition. In a blinded, placebo-controlled
intervention study, Murray-Kolb and Beard21 determined that the cognitive
domains of attention, memory and learning improved 5- to 7-folds after treatment
with ferrous sulphate for 16 weeks. In the study, the subjects went through tasks
such as tests of speed and accuracy. Significantly, findings were neither affected
by age nor by menstrual cycle.
In a national sample of children aged between 6 and 16 years in the United States,
Halterman et al22 demonstrated lower scores in mathematics in iron deficient
children compared with those who had normal iron status. Additionally, the risk of
scoring low in mathematics was determined by logistic regression to be greater
than twice in children with iron deficiency than in children with normal iron status.
Vitamin A deficiency causes growth retardation, impaired vision and immunity,
while deficiencies of iodine hinders physical development, causes mental
impairment and reduces school performance.2
42
Undernutrition and stunting
Adolescence is an important time for gains in weight and height with increases in
both muscle and fat.81 Stunting is commonly seen among adolescents in
undernourished populations, and it is accepted that short stature owes its origin
mainly to inadequate dietary intake and infection in the pre-school years.3 Stunting
has been described as a pointer to the living standards and nutritional status of a
community.55 It is considered important in adolescence because that is when the
final adult height is attained. Furthermore, a stunted woman is believed to be likely
to have a short pelvis predisposing her to obstructed labour during childbirth.81
Using a British reference standard, Brabin et al33 demonstrated a prevalence of
thinness or underweight of 15.6% in a group of rural adolescent girls aged 14-19
years in Ogoni, Rivers State, Nigeria. In her own study in Osun State, South West
Nigeria, Olumakaiye9 showed a prevalence of 20.1 for underweight. A cross-
sectional study in Western Kenya by Leenstra et al31 revealed underweight or
thinness of 15.6% and stunting of 12.1%. Among the subjects, 3.9% were both thin
and stunted and only about 0.64% were considered overweight.
In rural north India, Anand, Kant and Kapoor34 in a school based study reported
high prevalence of stunting in adolescent girls. This was 61.4% at 12 years,
increasing further to 70.4% at 13 years. However, by 14 years, a sharp drop to
43
22.7% was recorded, coinciding with puberty onset. In the survey, BMI also
increased with age, similar to the trend from Kenya31 and Osun State, Nigeria.9 In a
survey of rural communities across nine states in India, Venkaiah et al63 also
documented a decline in stunting as age increased. After an initial rise between the
ages of ten and thirteen, the percentage of stunting decreased from 46.7 at 13 years
to 37.2% at 17 years. This reversal coincides with the onset of puberty and may
thus be explained. Furthermore, it may be partly reflective of the catch-up in
growth which is believed to be possible in late adolescence.82 In a study of
adolescents from rural West Bengal, India, Bose and Bisai83 recorded a consistent
decreasing trend in the rate of undernutrition as age increased. Here, undernutrition
decreased from 42.4% at 11 years to 6.5% at 18 years in keeping with the above
trends9,31
Using a previous WHO criteria, Choudhary et al12 determined that 68.52% and
0.74% of the rural girls studied were underweight and overweight, respectively and
none was obese. However, with the proposed Asia criteria, more girls were
classified as overweight(2.2%), and up to 0.7% were considered obese. This
suggested ethnic differences in morphology which tended to over-classify Asians
as being underweight using Western references.
Underweight is associated with some negative health indices. Weaver et al35
contend that excessive thinness compromise bone health by not providing adequate
44
weight-bearing load on the skeleton. When this exists with menstrual dysfunction
and oestrogen deficiency, further skeletal growth is jeopardised.
Undernutrition has also been linked with late age of onset of menarche. Leenstra et
al31 determined that thinness and underweight were of significant occurrence in
girls who were late to start menstruating, reflecting a possible hormonal input to
weight status. Similar findings were made with regard to stunting. In Senegal,
Simondon et al82 noted significant differences in the age of menarche for three
groups of girls which were categorised as non stunted, mildly stunted and severely
stunted. This classification was however based on preschool height even though
the authors concluded that the mean height increment varied significantly only for
those aged 16 or 17 years.
Underweight and stunting are far more common in developing countries than in
more affluent societies. In Nigeria, relatively higher prevalences of underweight
than overweight and obesity have been reported similar to findings from Kenya31
and Asia.12,26,63,84 Findings from the richer countries show more cases of
overweight and obesity than underweight.3,29,30 This has been attributed to high
calorie diet and a sedentary lifestyle.29
45
Overnutrition
Adolescent obesity is known to persist in adult life, with its clear association with
risk for cardiovascular disease.3 Incidentally, many developing countries are
undergoing a nutrition transition in which there is an increase in obesity and a
reduction in the prevalence of undernutrition.11,30 These countries have increasing
rates of overweight and obesity, mostly due to change in diet to a more westernised
form. Wang et al30 reported such trend in Brazil and China, lately affluent
countries where obesity increased from 4.1 to 13.9%, and from 6.4 to 7.7%,
respectively.
Overweight and obesity result from a positive energy balance, when intake exceeds
expenditure.85 Consumption of energy dense foods high in saturated fats and sugars
and poor physical activity are key causes of obesity.56 Adolescents who skip meals
may try to make up with unhealthy alternatives resulting in overweight and
obesity.70 Increased rates of diabetes, coronary heart disease, and hip fracture have
been recognized in individuals who were overweight as adolescents.23
Obesity also has enormous social implications. A national cohort study in the US
by Gortmaker et al86 showed that obese individuals were less likely to get married,
completed fewer years of education, had lower household incomes, lower self
46
esteem, and higher rates of poverty than those who had not been overweight. These
findings followed reassessment after a period of 7 years.
A multi-country study across Europe showed overweight and obesity ranging from
5 to 35% among 13 and 15 year-olds.29 This study drew data from 35 countries in
the WHO European region and showed that girls in the UK countries of England,
Scotland and Wales had about the highest prevalence. It also showed a male
preponderance of obesity, except in Ireland where girls had a higher prevalence.
Wang, Monteiro and Popkin30 compiled national data from the US, Brazil, China
and Russia. In it, underweight and overweight in the US were 3.3% and 26.6%,
respectively. In Brazil, prevalences were 8.6% for underweight and 13.9% for
overweight. Values from China and Russia, respectively showed 13.1%
underweight and 7.7% overweight, and 8.1% underweight and 9.0% overweight.
The main variables studied were height, weight, age, sex, residence and socio-
economic status. Overall, higher prevalences for obesity and overweight than
underweight prevailed even in Russia where there was an increase in underweight.
In Nigeria, overweight is considered an evolving problem. A cross-sectional study
of adolescents aged 10 to 19 years in public schools in Lagos by Ben-Bassey et al87
showed prevalence of overweight of 3.7% and 3.0% in urban and rural settings,
respectively. Corresponding data for obesity showed prevalence of 0.4% and 0%,
47
respectively. These values closely match Olumakaiye’s findings in Osun.9
Although the prevalence of overweight/obesity increased with higher socio-
economic class, these differences were not statistically significant. Additionally,
there was no significant rural-urban disparity for overweight and obesity.
METHODS OF NUTRITIONAL STATUS ASSESSMENT
Nutritional status can be assessed by anthropometry, clinical examination and by
biochemical parameters.88 These constitute the traditional approach which give an
indication of the magnitude of the problem.76 In order to assess the broader
nutrition situation and determine relative importance of the causes, use is made of
the evaluation of dietary intake, determination of health conditions such as
sanitation and access to water, evaluation of dietary knowledge, and socio-
economic profile of the family.12,26,76
Anthropometric Assessment
The internationally recognised way of assessing malnutrition at the population
level is the measurement of anthropometry.28 Following the puberty spurt, rapid
changes occur in the body form of the adolescent. These changes have substantial
impact on the weight as well as height, but in unequal degrees; gains in weight
continue after height growth has stopped.89 This makes the adolescent
48
anthropometry different from that of childhood. Indices that involve height and
weight are the most frequently used tools to assess adolescent nutrition and they
are also known to be the most precisely measured.90 BMI which is generally
recommended by the WHO determines the appropriateness of an individual’s
weight with respect to his or her height.3,91 To this end, the use of an internationally
applicable cut-off for BMI, the WHO/NCHS reference has been endorsed to make
for uniformity of reporting and classification.3,92 In using BMI-for-age in
adolescent nutritional status assessment, consideration is given to the maturational
or physiological age of the individual since a good correlation exists between
them.31,92
Anthropometric measurements reflect both short- and long-term nutritional status.
They have the advantage of being non invasive, universally applicable, cheap and
relatively easy to obtain.88,91 The accuracy of the measurements is recognised as a
key part of the assessment. To a large extent, the utility of anthropometry rests on
comparison of the values across individuals or populations against a set of
reference values.93 However, the WHO still recommends the measurement of
anthropometry without necessarily waiting for more specific reference data.3 The
relevance of these reference values and of a consistent, well defined cut-offs is
demonstrated by the findings of an analysis of a household survey in Rio de
Janeiro, Brazil. Here, a simple change in cut-off values from different
49
references(WHO-1995;WHO-2000;International Obesity task Force, IOTF)
resulted in significant modification of the nutritional profile of the adolescent
population. For instance, changing the cut-off from the WHO-1995 to the
WHO2007 led to 23% increase in the overweight prevalence of the female
adolescent population.92 Therefore, a reference which is consistent and similar to
the study population may be considered ideal.
Although anthropometric indices are sensitive measures of the immediate and
underlying causes of malnutrition, they lack specificity for any particular cause.
Anthropometry alone would not reveal the relative importance of factors such as
dietary intake, poor environmental health, infectious diseases and food insecurity76
BMI is an index of weight-for-height which use was first suggested by a Belgian
statistician, Adolphe Quetelet as a predictor of health.5 Using the BMI, a
classification of the weight categories has been done. Normal weight is classified
as BMI of 18.5-24.9kg/m2, overweight as 25-29.9kg/m2 and obesity as BMI more
than or equal to 30kg/m2.29,89,94 To use BMI however, knowing an adolescent’s age
as exactly as possible is considered important.25,91 Available studies in adolescents
consistently show changes in BMI with age.9,31,34
BMI may not always present the entire picture of individuals’ health profile. In a
study of Fulani children and adolescents in the Jos Plateau of Northern Nigeria,
50
Glew et al32 documented average BMI of 14.9% and 15.0%, respectively for boys
and girls, indicating a high level of malnutrition. About 42% and 46% of the girls
were stunted and underweight, respectively when compared to WHO standards.
However, advanced studies of their body composition using electrical impedance
techniques showed overall health comparable to healthy age-matched children in
the United States.
Furthermore, changes in weight which would otherwise have been deemed
significant in terms of risk for mortality may not be so apparent if only the BMI is
used as a measure.5
Sexual Maturity
Another important consideration in adolescents is sexual maturation. Age at
menarche can be influenced by genetic, environmental, socio-economic, and
psychological factors. Studies have shown strong associations between sexual
maturation and BMI.31,36,82,84 This results in people of similar sexual maturity score
having comparable BMI inspite of differences in age. Agarwal et al95 suggested
that in adolescent growth assessment, anthropometric indices should be calculated
in relation to sexual maturity rather than age. A common practice is to adjust for
chronological age with maturation age especially when using references from a
population in which early onset of sexual maturity takes place such as the US.31,33
51
Ofuya96 in Rivers state, Nigeria documented a statistically significant difference in
the age of menarche between two groups of girls from different socio-economic
classes. Girls from middle class homes, associated with higher family income and
better nutrition, were noted to reach menarche earlier(12.2 years) than those from
low socio-economic class(13.0 years). This association of better nutritional state
with higher family income is an indirect one since the anthropometric parameters
of those girls were not documented.
In a community-based cross-sectional study, Acharya and colleagues84 showed
that age at menarche was lowered as nutritional status improved. It was shown that
as BMI increased, there was a concomittant significant increase in the number of
girls attaining menarche. They also reported a statistically significant difference
between the mean BMI of those who had attained menarche and those who had
not. The mean age at menarche was 14.42 years which is considerably higher than
that from girls in similar socio-economic circumstances in Nigeria,31 but lower
than figures from Kenya31 and Senegal.82
On the reverse side, it has been shown that when menarche is delayed long enough
to allow for a prolonged period of growth, there may exist the possibility of
compensatory growth. This was the finding of Simondon et al82 in a longitudinal
study carried out in rural Senegal. Girls who were stunted during the preschool
years, and who also had delayed menarche, had a significantly greater height
52
increment in the second half of adolescence than girls whose preschool heights
were normal. This study did not take into account the possible change in the family
circumstances of the affected girls in mid adolescence or later. This is because
better nutrition per se may account for some of the positive results obtained.
Clinical Assessment
This involves examination for changes that may be seen on the superficial
epithelial tissues such as the skin, eyes, buccal mucosa and hair. A rapid clinical
assessment schedule exists which cuts across the examination of these organs.26
Biochemical Analysis
Indices such as haemoglobin, tests for iron status, serum proteins such as albumin
and prealbumin are some of the biochemical tests used in nutritional assessment.97
Laboratory assessment of Iron status
The WHO encourages a definition of iron deficiency based on multiple indices for
a population-based assessment. An ideal combination would reflect functional
impairment, iron storage and tissue avidity for iron.6 The essence of this
combination is to offset the effect of the limitations of each of the tests when used
alone. In resource-poor settings however, cost may be an important constraint to
using this approach.
53
It is generally agreed that the basic standard for the evaluation of iron stores is the
staining of aspirated bone marrow.6,98,99 However; for the purposes of field work,
this may not always be possible.98,100 Ferritin is adjudged to be the most accurate
biochemical marker for the body’s iron stores.6 Oluboyede101 in a study of women
in Ibadan found that higher serum ferritin correlated positively with increasing
amounts of haemosiderin in the bone marrow. Such strong correlation was
however lacking in a study of nutritional anaemia at the Ahmadu Bello University
Teaching Hospital, Zaria by Leyland et al.102 Here, the serum ferritin of 93% of the
‘non-elite’ subjects who had no stainable iron in their bone marrow still fell within
a range considered as normal. It is recognised that inflammatory states and
infections, liver damage and malignancies lead to an elevation of the serum ferritin
levels.98,103 Since no exclusion criteria were put forward, it is likely that the
presence of chronic infections such as hepatitis or malaria may have spuriously
raised the level of ferritin in this study group. This is because infections are
common in many developing countries, especially among the low socio-economic
group. Mild infections can significantly elevate the serum ferritin levels and this
can persist for 2-3 weeks after the appearance of fever.50
Prevalence of iron deficiency may rest on the diagnostic criteria used for the
diagnosis. The serum markers of iron deficiency are low ferritin, low iron, raised
total iron binding capacity, raised red cell protoporphyrin and increased transferrin
54
binding receptors. Classically, an abnormality in at least two independent
indicators of iron status establishes the diagnosis of iron deficiency.6,22,104 In a
study of the relationship between iron deficiency and cognitive achievement in a
group of adolescent girls, Halterman et al22 defined iron deficiency on the basis of
abnormal values in two out of three parameters. The indices used were serum
ferritin, transferrin saturation and free erythrocyte protoporphyrin. Additionally, an
appropriate response to a therapeutic iron trial is considered sufficient evidence of
iron deficiency.6,18,77,98 However, this depends on compliance with the therapeutic
regimen.
Ferritin levels is a frequently used criterion as a sole marker of iron
deficiency.18,58,105 It is thought to be the best single test when account is taken of its
capacity to rise in the presence of inflammation.6,50,98 Other parameters such as
serum iron and TIBC have qualified usefulness as screening tests for iron
deficiency.6,77,98
Using more than one parameter, Leyland et al102 in Zaria, Northern Nigeria
determined that a combination of serum ferritin and transferrin saturation was the
best method of assessing iron deficiency. In this study, the mean transferrin
saturation was expectedly reduced in a ‘non-elite’ group and in the group with
anaemia, even in the presence of ferritin levels that are above the threshold for iron
55
deficiency. Thus, the effect of inflammation on ferritin levels can be clearly
identified.
Dietary Assessment
Dietary assessment is an important aspect of nutritional surveys and has been used
in a number of studies. There are three methods used to collect dietary
information:26
i. Log Book or inventory method
ii. Oral questionnaire method
iii. Weighing method
Log Book or Inventory method
Here, a book containing the relevant questions is kept with the housewife or the
head of the household who must then enter all the purchases in the book. This
method may only be used with literate groups. In addition, full co-operation of the
householder is vital since the data is only as reliable as the entries made.
Oral Questionnaire method
This is the most common among the methods of dietary survey. The interviewer
prepares a diet survey questionnaire tailored to the needs of the survey.
56
Information on types and qualities of the food consumed is usually obtained. It has
the advantages of not being time consuming and of having the capacity to cover
large number of households within a short period of time. However, data obtained
may not be accurate, giving only approximate information. Therefore, this method
may only be suitable for collecting information on general dietary patterns or on
dietary habits of large sections of population.21 Dapi et al11 employed a form of the
oral questionnaire, the Food Frequency Questionnaire,FFQ, in which the frequency
of consumption of various food items were determined. Frequencies of breakfast,
lunch, dinner and in-between meals were also collected. In keeping with the design
of this dietary evaluation method, no specified quantities of food were recorded.
Weighing method
In this method, items of food are weighed before and after cooking. By weighing
the leftovers after consumption, the amount of food may be determined. This is the
considered the most reliable method of dietary assessment. It has the drawback of
being time consuming as the researcher has to be physically present to record the
food items before and after cooking. This method was used by Beegum26 in Kerala,
India who applied it in a subsample of the survey group. Cole et al106 in Ibadan,
Nigeria also adopted this method coupled with chemical analysis of the food
samples.
57
STRATEGIES OF IMPROVING ADOLESCENT NUTRITION
An integrated plan combining educational and environmental approaches which
include nutrition in the overall adolescent health scheme is advocated.15 Such
programmes include those that target reproductive health, infections, violence, and
youth accidents.3 The role of the school in fostering knowledge and changing
behaviours has been acknowleged,3,86 making it an important factor in this process.
This composite approach involves the use of promotive and preventive tools.3
Promotive strategies
Lack of adequate physical activity has been described as a precursor of obesity and
overweight alongside unhealthy eating habits.56 In order to combat these situations,
it is advocated that physical activity be promoted while discouraging a sedentary
lifestyle.72 To this end,Neumark-Sztainer et al15 suggested neighbourhood
facilities for physical activity. Gortmaker and colleagues86 documented a positive
effect of physical activity on the BMI profile of some adolescent school girls. In
this school-based interventional study, change in behaviour as measured by
television viewing, and dietary practices improved with increased physical
exercise.
Healthy eating is crucial to normal growth and development. It is known that such
habits can be learned by example from parents and even by their mere presence at
58
meal times.107 Healthy eating involves eating a variety of meals, including fruits
and vegetables. It has been suggested that parents provide the opportunity for
healthy eating by making available wholesome foods and by serving as role
models of healthy eating.108
Strenghtening of self esteem is another means of achieving a healthy and balanced
individual. Neumark-stzainer et al15 in their adolescent health survey, reported that
having a positive body image was a strong protective factor against the
development of poor eating habits and unhealthy weight loss practices. It is also
thought to insulate the adolescent against adverse external influences which might
prey on her poor self image.3
Preventive strategies
Nutritional assessment including dietary assessment is regarded as an initial
important measure in influencing nutritional status.2 Dietary inquiry helps in the
identification of dietary inadequacies and in detecting potential eating disorders.3
This would then form the basis for nutritional counselling. It has been suggested
that information and nutrition-related services should be made accessible to
adolescent girls. These can be done through a number of means which include
schools and youth-oriented health programmes.2 Furthermore, it has been shown
that interventions that reach adolescents help in fostering life-long positive habits.
59
Self administered questionnaires and dietary recall have been used to review eating
paterns and food habits.72 Determination of the level of physical activity
irrespective of BMI is also advocated. It is thought that this would give an insight
into the underlying factors of malnutrition3
Dietz23 recognises the tendency of obesity to persist through adolescence to
adulthood. Since treatment of established obesity is difficult and expensive,
prevention and early intervention is vital. Eating, rather than skipping meals helps
to prevent obesity.70 Also considered important is parental influence and decisions
concerning meals.107,108 Suggestions are that programmes to prevent eating
disturbances should be female-oriented since they are more prone, and should
target reducing body dissatisfaction, understanding physical development and
improving knowledge about nutrition and weight control3
60
AIM AND OBJECTIVES
AIM: To determine the nutritional status of adolescent school girls in a rural
community, Ogbaku in Imo state.
OBJECTIVES OF THE STUDY:
(1) To determine the prevalence of underweight, stunting and
obesity in the study population.
(2) To ascertain the prevalence of iron deficiency anaemia among
the study subjects.
(3) To determine the relationships between BMI and socio-
demographic factors within the community.
(4) To determine possible associations between socio-economic
factors and iron deficiency.
61
JUSTIFICATION FOR THE STUDY
A child’s nutrition will affect its future health; this is known to be true of the girl
child in her reproductive role as an adult. In many developing countries including
Nigeria, decreasing food production and economic hardship has constrained the
diet of many people, especially in the rural areas. In addition to this is inadequate
knowledge of the nutritive value of food. As a result, the right balance in calorie,
protein and micronutrients is often not attained.
Previous workers have documented regional differences in nutritional status
among adolescent girls, even within the same country.42 In Nigeria however,
information is still limited and few studies have been carried out in South-East
Nigeria. The proposed area of study in Imo state is mostly agricultural and is
within the oil-producing zone. It is believed that exploration and exploitation
activities may worsen the food situation in the future through degradation of
farmland.
Since the adolescent period is regarded as the last window of opportunity for
nutritional interventions,31 the present study is therefore undertaken to obtain data
about nutritional status of rural female adolescents and the determinant factors. It is
hoped that data thus obtained will fill the knowledge gap as well as form the basis
for appropriate interventions in the future.
62
METHODOLOGY
STUDY AREA
The study was conducted in Ogbaku community in Mbaitoli LGA of Imo State of
South Eastern Nigeria. It is located about eight kilometers from Owerri, the state
capital and lies west of the city along the Owerri-Onitsha expressway. The
projected population for the year 2006 was 23,005 (12,212 females and 10,793
males).109 It is a predominantly agrarian community with a mixture of traders,
artisans and civil servants. The inhabitants are mainly Igbo speaking and are
indigenes, with a very small contribution from other ethnic groups. For
admininstrative purposes Ogbaku comprises four autonomous communities which
constitute two political wards spread over eighteen villages.
There are four government approved post primary schools, two public and two
private schools. The public schools are one male-only and one female-only
schools, while the private schools are of mixed sex or coeducational. All the
schools are non residential.
STUDY POPULATION
This comprised post- primary school girls from JS1 to SS3 within the ages of 10 to
19 years.
63
PERIOD OF STUDY
The study was carried out between October and November 2009. This period was
used for administering questionnaires, selection of subjects, clinical examination,
anthropometric measurements, collection of blood and stool samples and their
analyses. The survey was preceded by a pilot study in Orogwe, a neighbouring
community in late September 2009.
INCLUSION CRITERIA
1. Age 10 years to 19 years at last birthday
2. Verbal consent by the girls
3. Informed consent by parent/ guardian.
4. Students who have continously lived in the community for at least 6 months.
EXCLUSION CRITERIA
1. Students whose known haemoglobin genotype is SS or whose clinical history
and habitus suggest sickle cell anaemia.
2. Students with known chronic illnesses such as nephrotic syndrome, and
bronchial asthma as can be deduced from the medical history.
3. Students on iron supplements.
4. Students who had fever in the previous three weeks up to the time of the
study.50
64
5. Students with skeletal deformities such as scoliosis and kyphosis.
6. Age below 10 and above 19 years as at last birthday.
7. Non consent by the subject, parent/ guardian.
SAMPLE SIZE
A minimum sample size of 202 was calculated using the formula110 n= z2pq/d2
Where: n = desired sample size.
z = the standard normal deviation, usually set at 1.96.
p = the proportion in the population with attribute to a previous study
q = 1.0−p
d = degree of accuracy desired, set at 0.05.
If d = 0.05,
p = prevalence of underweight in rural adolescent girls in Ogoni, Rivers
state(15.6%)33
q = 0.844, then
n = (1.96)(1.96) X 0.156 X 0.844 / 0.05 X 0.05 = 202.
65
This was adjusted to 242 in order to accomodate an attrition rate of 20%, which
was the attrition rate in the pilot study.
APPROVAL
Official approval to carry out the study was obtained from the Ethical Committee
of the Federal Medical Centre Owerri, the Imo State Universal Basic Education
Board(IMSUBEB) and the Secondary Education Management Board(SEMB)
under the Imo State Ministry of Education(Appendices III-V) . The principals of
the selected schools were officially informed and details of the study was
explained to the teachers and students. A written approval was also obtained from
the Parents Teachers Association, PTA of the public school(Appendix VI). There
was however no functional PTA for the private school. Completion and return of
the first part of the questionnaire, and endorsement of the consent form (Appendix
I) by the parent or guardian served as consent.
STUDY DESIGN
This study was a descriptive cross-sectional survey in which the adolescent girls
who met the inclusion criteria were enrolled. Pre-tested questionnaires from a pilot
study was administered to the study population.
66
SAMPLING PROCEDURE
All the three schools with females in the study area were first stratified into public
and private schools. Since there is only one public school with females in its
population, that was chosen. For the two private schools, selection was by simple
ballot. The names of the two schools were written on a piece of paper, folded and
placed in a non transparent bag. This was presented to a child to pick one school by
chance, without looking.
The public school had a student population of 459 while the private school had 322
females giving a combined population of 781. From this combined population, 280
girls were recruited on the basis of the respective population of each school as
follows:
Public school: 459 x 280/781= 165
Private school: 322 x 280/781= 115
Within the schools, a two-stage sampling design was employed to select
participants.
First Stage: stratification of the students according to their year of study into J.S.I,
J.S. II, J.S. III, SS I, SS.II and SS. III.
67
Second Stage: selection of study participants from the different years of study and
subsequently the various classes.
In each each year of study(JSS 1 to SS3), proportional allocation was again
applied. Subjects were recruited in line with the relative proportion of students in
each year of study against the number allocated to the particular school(165 for the
public and 115 for the private).
Subject selection from the classes(A, B, C) was done by the lottery method. Pieces
of paper which had been marked ‘Yes’ were folded and placed on a desk in front
of the class. These were mixed with blank pieces of paper which were similarly
folded. The number of papers marked ‘Yes’ was of the calculated number for that
class. Using the class register and starting from the first name, students were then
called out to pick. Those who picked the papers marked ‘Yes’ were selected.
Where there was more than one class in a year of study, the calculated number for
that year of study was divided equally among the classes.
COLLECTION OF DATA
Each selected school was visited prior to commencement of the study, to
familiarise the investigator with the schools, inform the principal of the study date
and conclude arrangements for a smooth conduct of the study. Direct contact was
also made with some of the parents of the public school at a PTA meeting.
68
The investigator was introduced to the teachers and students during an assembly
and the purpose of his visit explained in both English and Igbo languages.
Recruited students were then given questionnaires which were in two parts, A and
B to take home for completion. Part A, which includes the consent form, was
completed at home with the help of the parents and guardians. Students whose
parents are illiterate were encouraged to use literate older relatives or neighbours to
explain the contents of the form.
The next day, the students returned with the questionnaires. Part B of the
questionnaire was administered to the students personally by the researcher in each
class. This was to ensure confidentiality and encourage truthful answers. At the
end, the questionnaires were retrieved from the students and reviewed. Students
who met the inclusion criteria after the review were then slated for further study.
Data from recruited participants were collected in two batches for the private
school and in three batches for the public school. Information obtained were on
clinical findings, anthropometry, blood and stool profile, starting with the private
school.
A screened classroom in the private school and a section of the school hall in the
public school were used for this purpose. This was to ensure privacy and co-
operation. In both cases, a female teacher served as chaperone.
69
Data collection was done in three stations with clinical examination first, followed
by anthropometry and finally blood collection. This was done between 10 am and
1pm with a thirty minute break in-between. Anthropometry and clinical
examination were done exclusively by the investigator while his assistants, two
House Officers from the Federal Medical Centre, carried out venepuncture,
assisted by a nurse. The investigator visited the schools a day before each round of
data collection to drop labelled specimen bottles for stool samples with the
students which they returned the next day.
A total of 280 copies of the questionnaire were distributed out of which 253 were
returned with parental consent. Of this number, 231 girls met the inclusion criteria
after review of the responses and these were slated for further study.
Clinical Examination
A general clinical examination was carrried out by the investigator on each of the
remaining 229 students(2 students were further excluded as a result of sudden
illness on the days of study). Changes in the skin, eyes, hair, buccal mucosa and
tongue were noted and recorded, in addition to other obvious abnormalities. With
the standard protocol,111 axillary temperatures were taken using mercury-in glass
thermometres.
70
Anthropometric Measurements
The following anthropometric indices were assessed in the subjects using standard
protocol112
Weight: the weights of the subjects were measured using a a standard standing
weighing scale (Camry digital electronic scale, model ED 307). Each student was
weighed in the school uniform made of light cotton fabric without shoes and socks.
Those who wore berets and cardigans were asked to remove them before each
weighing. The scale was standardised every morning prior to commencement of
weighing using a standard weight of 0.5kg. The digital display registered 0.00
before each measurement. The weight was then recorded to the nearest 0.5 kg.
Height: this was measured using a well-calibrated RGZ-160 model stadiometer
with a movable headpiece. Subjects were made to stand erect with feet placed
together, and back and heels in firm contact with the upright bar of the scale. With
the head aligned in a horizontal plane, the headpiece was then brought onto the top
of the head. Hairstyle did not affect the measurements as all the subjects wore their
hair short in line with the schools’ regulations. The height was recorded to the
nearest 0.1centimetre.
The measurements were carried out by the investigator alone to minimise observer
bias, and the same set of equipment was used throughout the study. The indices of
weight and height were converted to the body mass index, BMI using the formular
71
weight(kg)/height(m2). Subsequently, underweight, stunting, overweight and
obesity were determined in line with the outlined definitions, and with the WHO
reference.113
Age was calculated from the reported date of birth and verified with the school
register. Age at menarche was by recall.
Laboratory Assessment
The subjects’ haemoglobin, serum ferritin, Total iron binding capacity, TIBC and
serum iron were analysed. Stool examinations were also done. TIBC and serum
iron were used to calculate the transferrin saturation. Transferrin saturation is the
ratio of serum iron to TIBC.6 For the purpose of this study, anaemia was defined
based on the WHO gender- and age-specific cut-offs;6 iron deficiency was defined
as serum ferritin <15µg/l and transferrin saturation less than 16%.6 Iron deficiency
anaemia is a combination of iron deficiency and anaemia. The laboratory
investigations were carried out under initial guidance with results matched with
those of the laboratory scientists. Subsequent analyses were done by the principal
investigator assisted by the medical laboratory scientists.
72
Biochemical tests
Subjects were comfortably seated and the skin of the cubital fossa cleaned with
alcohol. With the aid of a Vacutainer device, five milliliters of venous blood was
collected into a plain vacuum tube and two millilitres into an EDTA vacuum tube
from the antecubital vein. These were then labeled. Samples were left in an ice box
awaiting transport to the hospital laboratory at the end of each day’s exercise. On
arrival at the hospital, blood in the plain tube was centrifuged and the serum
collected. This was then stored in the laboratory freezer from where samples were
taken and analysed in batches for serum iron, TIBC and ferritin.
Haemoglobin estimation was done using an automated Coulter counter MD-II
series analyser.
Ferritin Assay:
Biotec ELISA kits(Suffolk, UK) were used for the procedure with the following
materials: Microtitre plate; anti-Ferritin conjugate; wash buffer; chromogen;
substrate; stop solution; zero Standard; standards; plate sealers.
Procedure: reagents were first allowed to stand and equilibrate to room
temperature. Then the desired number of strips were placed in the holder. Twenty
microlitres of subjects’ sample, standard and blank and 100 microlitre of enzyme
conjugate were drawn and added to each well. Automatic pipettes with disposable
73
tips were used in order to avoid contamination between serum specimens. The
wells were covered with the plated sealers and placed in Equitron(England)
Incubator at 370C for 30 minutes. After this time, the sealer was discarded and the
liquid aspirated. The wells were then filled with wash buffer. Five cycles of
washing were done using Acurex(USA) automatic Microplate Washer with a soak
time of 10 sec between cycles. Thereafter, the strips were overturned on blotting
paper to dry. Then 200 microlitre of chromogen/substrate were added to all the
wells and another incubation done but this time for 10 minutes in the dark at room
temperature. At the end of this incubation, 100 microlitres of stop solution was
added to the wells and gently shaken to mix the solution. An automatic
Acurex(USA) Microplate Reader was then used to read the absorbance at 450nm.
The result was derived from a callibration curve from which the ferritin
concentration of the sample was read.
Serum iron/ TIBC : this was determined using Teco Diagnostics iron/TIBC
reagent sets(USA). A standard photometric method was used.114 First serum iron
and UIBC were determined independently. Then TIBC was calculated from the
formular: TIBC(Total Iron Binding Capacity):
Iron level + UIBC = TIBC.
74
Stool Examination
Subjects to be analysed were given clean, labelled plastic containers a day before
the day of collection. Morning samples were collected and transported to the
parasitology laboratory where testing was done in batches. Sample not ready for
immediate analysis were refrigerated.
Method:
Macroscopy: samples were first subjected to macroscopic examination, checking
for colour, consistency, blood and adult worms. This was followed by a wet
preparation of the stool sample.
Wet Preparation: first, one drop of saline was placed on a clean slide.Then with an
applicator, about 1g of the sample was picked and emulsified with the saline. Care
was taken to collect stool from the surface and other parts of the specimen
container. This was to get a sample representative of all parts of the specimen. The
emulsified stool on the slide was then covered with a cover slip and examined
through the microscope with 40X Objective.
Concentration(sedimentation): negative samples(on wet preparation) were re-
examined after concentration with the sedimentation method. About 4g of the stool
sample was collected from the specimen container, again taking care to include
stool from all surfaces of the container. This was placed in a centrifuge tube. Then
75
about 4ml of 10% formal saline was added, and the specimen emulsified with a
glass rod. This mixture was then centrifuged using a 12-bucket centrifuge Model
80-2(Techmel & Techmel, Texas, USA) for 5 minutes at 3000rpm.
Thereafter, the supernatant was discarded, and the sediment retained. To this
sediment were added 7ml of 10% formal saline and 3ml of ethyl acetate. This was
centrifuged again for 5 minutes at 3000rpm. At the end of this process, four layers
were visible in the centrifuge tube; the top layer is ether and dissolved fat, followed
by faecal debris, then formal water, and lastly sediment containing parasites.
The sediment was then placed on slide, covered with a cover slip and examined
with 40X objective lens. Eggs were identified, counted and recorded.
SOCIAL CLASSIFICATION
The subjects were stratified using their mothers’ level of education and their
fathers’ occupation as described by Olusanya et al.57 Social class for each student
was determined from the sum of the father’s and mother’s scores(Appendix VIII).
Based on this information, five social classes were assigned to the subjects.
76
DATA ANALYSIS
The data collected were analysed using the SPSS version 15.0 statistical package.
Frequency tables were generated for relevant variables. Descriptive statistics such
as means and standard deviation of the quantitative variables such as age, height,
weight were determined. Using the chi-square test, the significance of the
association between socio-demographic variables and anthropometric indices, and
between socio-demographic variables and iron status were determined. Logistic
regression was used to ascertain the determinants of nutritional status. A p-value
less than 0.05 was considered statistically significant.
77
RESULTS
A total of two hundred and twenty-nine adolescent girls who met the inclusion
criteria were recruited into the study, with 134 and 95 from the public and private
schools, respectively. Blood samples were collected from 221 students out of 229
giving a response rate of 96.5%. Eight students who had previously given consent
later withdrew from venepuncture for fear of the procedure. Out of the 221 blood
samples, 216 were analysed. Five samples were not analysed owing to mislabelling
and spillage. Stool samples were obtained and analysed in 205 girls.
One hundred and eighteen(51.5%) were in the junior classes while one hundred
and eleven(48.5%) were in the senior classes. The age range of the study
population was 11 to 19 years with a mean of 15.8 ±1.7 years. There was no ten-
year old among the survey population. The means for height, weight and BMI were
157.6± 7.6 cm, 49.1± 7.8 kg, and 19.7 ± 2.5kg/m2 , respectively. Average age at
menarche was 13.39 ± 1.1 years while the mean haemoglobin was 11.0 ±
1.1g/dl(Table I).
78
Table I. Means of some population indices
Variable Range Mean ± SD
Age(years) 11-19 15.8 ± 1.8
Height(cm) 134.0-175.0 157.6 ± 7.6
Weight(kg) 25.5-73.0 49.1 ± 7.8
BMI(kg/m2) 14.2-27.0 19.7 ± 2.5
Menarcheal age(years) 11-17 13.3 ± 1.1
Haemoglobin(g/dl) 8.9-16.1 11.0 ± 1.1
Socio-economic profile
Table II shows a summary of the population characteristics of the girls with respect
to age, class, family size, parental income and marital status, social class,
anthropometry and haemoglobin status.
Households with 7-9 individuals accounted for the highest number of students at
94(42.5%), followed by those with 4-6 family size with 60(27.2%) individuals.
Next are families with more than 10 people which have 52(23.5%) students
belonging to them. The least number of students- 15(6.8%) belonged to family size
of 1-3.
79
Girls whose parents earned between N7,500 and N15,000 accounted for the highest
number of 75(36.4%). Forty six(22.3%) students had parental income of less than
N7,500(Table II). Girls with parental income of above N30, 000 were 45 (21.9%)
in number. Students with parents earning between N15,500 and N30,000 were the
least in number at 40 (19.4%).
Of the parents, 194 (85.1%) were married while twenty-nine (12.7%) were
widowed. Five(2.2%) were separated or divorced. The highest number of
individuals, 72 (33.3%) and 70 (32.4%) belonged to social classes III and IV,
respectively. There were 37(17.2%) students in social class V, and 35(16.2%) in
social class II. Only 2(0.9%) students belonged to social class I.
Table III shows that 32(14.5%) and 9(4.0%) fathers and mothers, respectively had
university education. One hundred and thirty one (59.5%) of the fathers and 146
(64.6%) of the mothers had post-primary education while 89(40.5%) fathers and
80(35.4%) mothers had no schooling or primary education at the most. With
respect to parental occupation, 15(6.9%) fathers were in the professional cadre or
engaged as top businessmen. One hundred and eleven (50.9%) were middle level
manpower while 92 (42.2%) were unskilled labourers. Majority of the mothers,
189 (83.3%) were employed in unskilled work.
80
Table II. Population characteristics of the students
Age group Number Percentage(%)
11-13 24 10.5
14-16 101 44.1
17-19 104 45.4
Class
J.S 1 20 8.7
J.S 11 35 15.3
J.S 111 63 27.5
S.S 1 33 14.4
S.S 11 59 25.8
S.S 111 19 8.3
Family size
1-3 15 6.8
4-6 60 27.2
7-9 94 42.5
>10 52 23.5
Parental income per month
<N7,500 46 22.3
N7,500-15,000 75 36.4
N15,001-30,000 40 19.4
>N30,000 45 21.9
Marital status of parents
Married 194 85.1
Divorced 5 2.2
Widowed 29 12.7
Social class
I 2 0.9
II 35 16.2
III 70 32.4
IV 72 33.3
V 37 17.2
Nutritional status
Underweight 38 16.6
Normal 177 77.3
Overweight 14 6.1
Stunted 16 7.0
Normal 213 93.0
Haemoglobin Status
Anaemia present(Hb<12g/dl) 168 77.8
No anaemia 48 22.2
81
Table III. Distribution of subjects by parental occupation and educational
attainment
Father(%) Mother(%)
Educational status
No schooling or up to
primary education
89(40.5) 80(35.4)
Secondary or tertiary
education below
university
99(45) 137(60.6)
University education 32(14.5) 9(4.0)
Total 220(100) 226(100)
Occupation
Professionals, top civil
servants,politicians, top
businessmen
15(6.9)
10(4.4)
Middle level bureaucrats,
technicians, skilled
artisans
111(50.9) 28(12.3)
Unskilled workers, those
with income below the
minimum wage(N7,500)
92(42.2) 189(83.3)
Total 218(100) 227(100)
82
Nutritional status
The predominant clinical abnormality was pallor in 58 cases. Other findings
include thin build, dark discolouration of the tongue, dental caries and fungal nail
infections. One hundred and fifty (150) girls did not have any abnormalities on
clinical examination(Figure I).
Figure I. Summary of clinical examination findings
Key
Others:
Thin build: 24
Dark discolouration of the tongue: 2
Dental caries:4
Fungal nail infection:2
83
Table IV shows the prevalence of underweight, overweight and obesity across the
age groups of the survey population. Overall, 38 (16.6%) and 14 (6.1%) girls were
underweight and overweight, respectively. No individual was obese. From early
adolescence, the prevalence of underweight decreased from 29.2% through 24.8%
in mid adolescence to 5.8% in late adolescence(p=0.001).
The prevalence of stunting decreased steadily with age(Table V). The overall
prevalence was 7.0%. Three (12.5%), 11(10.9) and 2(1.9%) girls were stunted in
early, middle and late adolescence, respectively(p=0.022).
Table IV. Prevalence of underweight, overweight and obesity by age groups
Age
groups
No Nutritional status ᵪ2 p-
value
df
underweight normal overweight obese
11-13 24 7(29.2) 15(62.5) 2(8.3) 0 17.987 0.001* 4
14-16 101 25(24.8) 69(68.3) 7(6.9) 0
17-19 104 6(5.8) 93(89.4) 5(4.8) 0
Total 229 38(16.6) 177(77.3) 14(6.1) 0
*statistically significant
84
Table V. Prevalence of stunting by age groups
Age
groups
No Stunted(%) Not
stunted(%)
ᵪ2 p-value df
11-13 24 3(12.5) 21(87.5) 7.595 0.022* 2
14-16 101 11(10.9) 90(89.1)
17-19 104 2(1.9) 102(98.1)
Total 229(100) 16(7.0) 213(93.0)
*statistically significant
From Table VI, underweight was most prevalent in family size 10 and above,
affecting 15(28.8%) girls. This is followed by family size 7-9 and 4-6 with
13(13.8%) and 10(16.7%), respectively. None of the girls in family size 1-3 was
underweight. Overweight was present only in family size 4-6 and 7-9.
Underweight was more prevalent amongst girls in the lower income groups, being
present in 10(21.7%) and 12(16.0%) girls of the less than N7,500 and N7,500-
N15,000 income groups, respectively(Table VI). The corresponding prevalence for
the higher income categories of N15,001-N30,000 and above N30,000 was
7(17.5%) and 2(4.4%), respectively. These differences are however not statistically
significant(p= 0.077).
85
Table VI. Nutritional status(BMI category) by family size and family income
Number BMI Category ᵪ2 p-
value
df
Underweight Normal Overweight
Family
Size
1-3 15 0 15(100) 0 14.789 0.022* 6
4-6 60 10(16.7) 45(75.0) 5(8.3)
7-9 94 13(13.8) 72(76.6) 9(9.6)
≥10 52 15(28.8) 37(71.2) 0
Total 221 38(17.2) 169(76.5) 14(6.3)
Family
Income
<N7,500 46 10(21.7) 31(67.4) 5(10.9) 11.383 0.077 6
N7,500-
N15,000
75 12(16.0) 56(74.7) 7(9.3)
N15,001-
N30,000
40 7(17.5) 32(80.0) 1((2.5)
>N30,000 45 2(4.4) 42(93.3) 1(2.2)
Total 206(100) 31(15.0) 161(78.2) 14(6.8)
*statistically significant
86
Table VII(A & B) show that for all levels of maternal education, normal BMI was
the highest category. Eighteen girls were underweight at low and middle level
maternal education each compared with only 2 girls from families with the highest
level of maternal educational attainment . The prevalence of underweight
decreased as paternal education increased from primary(20.2%) through secondary
(16.2%) to university (12.5%). A similar relationship existed between overweight
prevalence and paternal education. However, these differences were not
statistically significant(p=0.266).
87
Table VII(A & B). Nutritional status(BMI Category) by parental educational
attainment
Table VIIA: mother’s education n=226
Number BMI Category(%) χ2 p-
value
df
underweight normal Overweight
No
schooling
or up to
primary
education
80 18(22.5) 56(70.0) 6(7.5) 4.399 0.355 4
Secondary
or tertiary
education
below
university
137 18(13.1) 111(81.0) 8(5.8)
University
education
9 2(22.2) 7(77.8) 0
Total 226(100) 38(16.8) 174(77.0) 14(6.2)
88
TableVIIB: Father’s education n=220
Number BMI Category(%) χ2 p-
value
df
underweight normal overweight
No
schooling
or up to
primary
education
89 18(20.2) 62(69.7) 9(10.1) 5.219 0.266 4
Secondary
or tertiary
education
below
university
99 16(16.2) 79(79.8) 4(4.0)
University
education
32 4(12.5) 27(84.4) 1(3.1)
Total 220 38(17.3) 168(76.4) 14(6.4)
89
From Table VIII(A & B), the prevalence of underweight increased as paternal
occupation moved from highly skilled to unskilled. Underweight was most
prevalent amongst girls whose fathers were unskilled workers at 20(21.7%).
Eighteen(16.2%) of the girls whose fathers were middle level bureaucrats,
technicians or skilled artisans were underweight. This is in contrast to the category
comprising professionals, top civil servants and top businessmen in which none of
the girls was underweight.
A similar trend was seen with maternal occupation in which the prevalence of
underweight was highest in girls whose mothers were unskilled, and declined as
level of skills improved. Thirty four(18.0%) of the girls whose mothers were
unskilled workers were underweight compared with 2(7.1%) and none,
respectively from the middle and highly skilled mothers.
However, neither paternal(p= 0.173) nor maternal occupation(p= 0.092) had a
statistically significant relationship with BMI status[Table VIII(A & B)].
90
Table VIII(A & B). Nutritional status by parental occupation
Table VIIIA: Father’s occupation n=218
Number Nutritional status(%) χ2 p-
value
df
underweight normal overweight
Professionals, top civil
servants, elected
politicians, top
businessmen
15
0 15(100) 0 6.367 0.173 4
Middle level
bureaucrats,
technicians, skilled
artisans
111 18(16.2) 86(77.5) 7(6.3)
Unskilled workers,
those with income
below the minimum
wage
92 20(21.7) 65(70.7) 7(7.6)
Total 218(100) 38(17.4) 166(76.1)
91
TableVIIIB: Mother’s occupation n= 227
Number Nutritional status(%) χ2 p-
value
df
underweight normal overweight
Professionals, top civil
servants, elected
politicians, top
businessmen
10 0 10(100) 0 7.976 0.092 4
Middle level
bureaucrats,
technicians, skilled
artisans
28 2(7.1) 26(92.9) 0
Unskilled workers,
those with income
below the minimum
wage
189 34(18.0) 141(74.6) 14(7.4)
Total 227(100) 36(15.9) 171(78.0) 14(6.2)
92
Social class V with 14(37.8%) girls had significantly higher prevalence of
underweight than social class IV(5.6%), III(25.7%) and II(5.7%)(p=0.001). There
was no underweight girl in social class I(Table IX).
From Table X, 7(18.9%) students in social class V were stunted representing the
highest prevalence. Five girls were stunted in social class IV, 1(1.4%) in social
class III and none in social class I(p= 0.026).
Table IX. Nutritional status by social class
Social
class
No BMI category(%) ᵪ2 p-
value
df
underweight normal overweight
I 2 0 2(100) 0 25.896 0.001* 8
II 35 2(5.7) 32(91.4) 1(2.9)
III 70 18(25.7) 48(68.6) 4(5.7)
IV 72 4(5.6) 63(87.5) 5(6.9)
V 37 14(37.8) 21(56.8) 2(5.4)
Total 216(100) 38(17.6) 166(76.9) 12(5.6)
*statistically significant
93
Table X. Distribution of stunting by social class
Social
class
Number Stunted Not
stunted
ᵪ2 p-value df
I 2 0 2(100) 11.049 0.026* 4
II 35 3(8.6) 32(91.4)
III 70 1(1.4) 69(98.6)
IV 72 5(6.9) 67(93.1)
V 37 7(18.9) 30(81.1)
Total 216(100) 16(7.4) 200(92.6)
*statistically significant
Table XI shows that of the girls studied, only those whose fathers had primary
education or less were stunted(p= 0.000). Stunting was found among 10(12.5%)
and 6(4.4%) girls whose mothers’ highest educational attainment was primary and
post-secondary(not university) education, respectively. There was no case of
stunting among children of university graduates. An inverse relationship existed
between maternal education and the prevalence of stunting. This is however not
statistically significant(p= 0.056).
94
Table XI(A & B). Distribution of stunting by parental education
Table XIA: paternal education n=220
Paternal education Number Stunted Not
stunted
χ2 p-
value
df
No schooling or up to
primary education
89 13(14.6) 76(85.4) 20.337 0.000* 2
Secondary or tertiary
education below
university
99 0 99(100)
University education 32 0 32(100)
Total 220(100) 13(5.9) 207(94.1)
*statistically significant
Table XIB: maternal education n=226
Number Stunted Not
stunted
χ2 p-
value
df
No schooling or up to
primary education
80 10(12.5) 70(87.5) 5.777 0.056 2
Secondary or tertiary
education below university
137 6(4.4) 131(95.6)
University education 9 0 9(100)
Total 226(100) 16(7.1) 210(92.9)
95
Menarcheal status
Table XII shows that the proportion of girls who had attained menarche were
more in the higher weight categories than those who had not. Eighty nine and a
half percent of underweight girls had attained menarche compared with 91.0% and
92.9% of the normal weight and overweight girls, respectively. This difference was
however not statistically significant(p=0.925).
Table XII. Nutritional status by sexual maturity(menarcheal status)
Nutritional
status
Number Menarcheal status ᵪ2 p-value df
AM NAM 0.157 0.925 2
Underweight 38 34(89.5) 4(10.5)
Normal 177 161(91.0) 16(9.0)
Overweight 14 13(92.9) 1(7.1)
Total 229(100) 208(90.8) 21(9.2)
AM= Attained menarche
NAM= Not attained menarche
96
Table XIII shows the effect of social class on menarcheal status. All the girls in
social class I had attained menarche. By proportion, more girls had attained
menarche in social classes II(91.4%) and III(95.7%) compared to social classes
IV(90.3%) and V(89.2%). However, this difference is not statistically
significant(p=0.471).
Table XIII. Menarcheal status by social class
Social
class
Number Menarcheal status ᵪ2 p-value df
AM NAM 3.547 0.471 4
I 2 2(100) 0
II 35 32(91.4) 3(8.6)
III 70 67(95.7) 3(4.3)
IV 72 65(90.3) 7(9.7)
V 37 33(89.2) 4(10.8)
Total 216(100) 199(92.1) 17(7.9)
AM= Attained menarche
NAM= Not attained menarche
97
Table XIV shows that among the factors analysed, age, family size and social class
had statistically significant relationships with the nutritional status of the
population. Of these, early adolescence, family size greater than 10, and social
classes III and V contributed significantly to the nutritional status of the adolescent
girls(Table XIV). Compared to girls in late adolescence, those in early adolescence
had 8.3 times higher risk of being underweight (p= 0.000, CI= 2.716-25.3).
Adolescents whose family sizes were greater than 10 were 3 times as likely to be
underweight as those with family sizes 1-3(p=0.028, CI=1.130-8.210). The risk of
undernutrition in adolescents belonging to social III was 6.9 times more than those
in social class I (p= 0.025, CI=1.28-36.6) while girls in social class V were 6.7
times (p= 0.004, CI= 1.836-23.79) more at risk of underweight than their
counterparts in social class I.
98
Table XIV. Results of logistic regression analysis
variables Regression
coefficient(B)
Odds
ratio(OR)
95% confidence
interval
p-
value
Age groups
Early
adolescence
2.115 8.291 2.716-25.3 0.000*
Mid adolescence 0.049 1.050 0.303-3.64 0.939
Late adolescence Ref
Family size
4-6 20.727 1003 0.000-0.000 0.998
7-9 0.561 1.75 0.507-5.422 0.330
>10 1.114 3.04 1.130-8.210 0.028*
1-3 Ref
Social class
II 21.726 2725 0.000-0.000 0.99
III 1.925 6.852 1.28-36.6 0.025*
IV -0.192 1.21 0.291-2.29 0.712
V 1.888 6.608 1.836-23.79 0.004*
I Ref
*statistically significant
Ref= Reference category against which the other categories are matched.
99
Iron status
Table XV. Summary of iron status results
Number Range Minimum Maximum Mean
Haemoglobin(g/dl) 216 7.2 8.9 16.1 11.0
Serum iron(µg/dl) 216 197 3 200 71.5
TIBC(µg/dl) 216 637 15 652 371.5
Serum ferritin(µg/ml) 216 331.3 0.7 332 37.4
Table XVI shows that iron deficiency was present in 30 girls giving an overall
prevalence of 13.9%. Iron deficiency was present in 16(16.7%) girls of the 14 to
16-year age group, representing the highest prevalence. Eleven(11.5%) students in
the 17 to 19-year group were iron deficient compared with 3(12.5%) students in
the 11to13- year age group.
Iron deficiency anaemia was present in 27 girls(12.5%). Three(1.4%) students
had iron deficiency without anaemia. Overall, anaemia was present in 168(77.8%)
of the girls(Table XVII).
100
Table XVI. Prevalence of iron deficiency by age groups
Age
groups
Number Iron status ᵪ2 p-value df
deficient non
deficient
11-13 24 3(12.5) 21(87.5) 1.132 0.568 2
14-16 96 16(16.7) 80(83.3)
17-19 96 11(11.5) 85(88.5)
Total 216(100) 30(13.9) 186(86.1)
Table XVII. Prevalence of anaemia and iron deficiency anaemia
Anaemia status Iron status Total
deficient Non deficient
Anaemia(Hb<12g/dl) 27(12.5) 141(65.3) 168(77.8)
No anaemia 3(1.4) 45(20.8) 48(22.2)
Total 30(13.9) 186(86.1) 216(100)
101
Figure II shows that iron deficiency was observed more in the lower income
groups. Eleven(25.0%) and 10(14.3%) girls from the less than N7,500 and N7,500-
N15,000 income groups, respectively were iron deficient. On the other hand,
3(8.3%) in the N15,001-N30,000 and 6(13.6%) in the >N30,000 income groups
had iron deficiency.
Figure II. Distribution of iron status in different income categories
102
Most cases of iron deficiency were seen in 10(15.4%) and 8(11.8%) students
belonging to social class III and IV, respectively. No student in social class I had
iron deficiency(Figure III).
Figure III. Iron status in the different social classes
103
Table XVIII shows that 5(6.7%) girls whose mothers had primary education or less
and 25(19.4%) with maternal post-primary education( but not up to university) had
iron deficiency, respectively. There was no case of iron deficiency in girls whose
mothers had university education(p= 0.019).
Table XVIII. Iron deficiency by maternal education
Mother’s
educational
attainment
Number Iron status χ2 p-
value
df
Deficient(%) Non
deficient(%)
No schooling or up
to primary
education
75 5(6.7) 70(93.3) 7.875 0.019* 2
Secondary or
tertiary education
below university
129 25(19.4) 104(80.6)
University
education
9 0 9(100)
Total 213(100) 30(14.1) 183(85.9)
*statistically significant
104
Figure IV. Distribution of helminthic infestation
Of the 205 stool samples analysed, helminths were seen in 60 samples. There were
three cases of mixed infection. The frequency of hookworm infestation was 27
while E. histolytica and ascaris were found 16 and 10 times, respectively. G.
lamblia and trichuris had the lowest frequency of 7 and 3, respectively.
105
DISCUSSION
Nutritional assessment of the adolescent girl is considered an important tool in the
overall evaluation of the present and future health of a community.3 This study
reveals a high level of malnutrition in a rural community in Imo State. There was a
high prevalence of underweight among the adolescent girls. Iron deficiency and
iron deficiency anaemia were common while anaemia was pervasive. However, the
prevalence of stunting was relatively low.
In this study, there was a clear pattern of increase in the BMI with increasing age.
Conversely, lower BMI values were found in the younger age groups. As girls got
older, the prevalence of underweight steadily declined. This observation of
increasing BMI with age is similar to those of Anand et al34 and others.9,10,31,83 The
increase of BMI with age in adolescent girls is thought to be from the addition of
fat stores and muscle mass, as well as from accelerated skeletal growth with the
onset of puberty.3,8,10 This continues throughout the period of physical maturation
from early to late adolescence hence weight tends to increase with age.
Furthermore, as older adolescents have more say in their diet and even sometimes
cook the food themselves, it is possible that they are more likely to eat to repletion
than their younger counterparts. However, Mukopadhay et al115 in West Bengal
106
India documented an increase of undernutrition with advancing age in a study of
11 to 14 year-old adolescents. This age range which falls predominantly within
early adolescence may have affected the outcome of that study since that is around
the onset of physical maturity. While the prevalence of underweight in rural Imo
state (16.6%) is similar to that recorded in Rivers(15.6%)33 and Osun(15.1%)9
States both in Nigeria, and in Kenya(15.6%),31 it is considerably lower than the
prevalence of 68.5% and 53% in rural India.12,26 This is consistent with reports that
South East Asia bears a heavier burden of malnutrition than Africa.3,9,56
The emergence of overweight and obesity as risk factors for the future
development of chronic diseases such as diabetes and hypertension has been
noted.3,23,29 The prevalence of overweight from this study was 6.1%. This is
relatively higher than that found among the rural girls by Olumakaiye9 in
Osun(1.5%) and Ben-Bassey et al87 in Lagos state(3.0%). However, all three
studies recorded no case of obesity among the rural girls. This picture contrasts
with ranges of 5% to 28% for obesity and overweight, respectively across Europe.
Studies in the United States, Russia and China show similar higher values for
overweight and obesity.30 As diets change to unhealthy forms and inactivity
increases, the burden of excess body weight rises.29 Reports indicate an increase in
the prevalence of overweight and obesity from all regions across the
world.3,11,29,30,56
107
Stunting as determined by height less than −2 z-scores for age was most prevalent
at early(12.5%) adolescence, with the least prevalence in late adolescence(1.9%).
The overall prevalence(7.0%) is much lower than reported by Venkaiah et al63 and
by Mulugeta et al116 (26.5%) in rural Ethiopia. It is also remarkably lower than the
prevalence in rural Kenya(12.2%).31 However, it is higher than the prevalence of
4.7% determined by Brabin et al33 in rural Rivers state, Nigeria. Although the same
definition(height-for-age z-scores less than 2 standard deviation below the median
of a reference population) for stunting was applied in this study as in the above
studies, different reference populations were used. Brabin et al33 used the British
1990 reference values. The 1995 NCHS reference and a normalised version of the
1977 NCHS reference curve were used for the Indian63 study and the Kenyan31
study, respectively. This present study and that from Ethiopia116 employed the
2007 WHO reference population113. Hence direct comparison can only be made
with caution. The observation of a decline in the prevalence of stunting after the
age of 13 years is similar to findings by Venkaiah et al.63 In that study, the decline
in the prevalence of stunting was sustained into late adolescence as in the present
study. This may be explained by some catch-up growth which is believed to be
possible in late adolescence.82
In the present study, the reduction in the prevalence of stunting coincides with
average age of menarche which is 13.39 years. Age at menarche is known to
108
coincide with the last part of the adolescent growth spurt.31 This may then partly
explain the reduction in the prevalence of stunting at this age. However, stunting
is essentialy an indicator of undernutrition in the early years and may be reflective
of inadequate intake or infections which happened in the past and caused slowness
of growth.3,10 This combination of a relatively high prevalence of underweight and
a low prevalence of stunting in rural Imo state indicate a possible adequacy of diet
in the younger years. This implies problems with the recent and current nutrition.
Social class is defined on the basis of maternal education and paternal occupation
after the method developed by Olusanya et al.57 A significant relationship existed
between social class and the weight categories. The prevalence of underweight is
remarkably low in the upper class(social class I and II), and generally increased
down the social scale. This is similar to findings by Kurz and Som10 and
Choudhary et al.12 In the review of the Nigeria Demographic and Health Survey,
Uthman42 showed a wide variation in the prevalence of both underweight and
stunting between the privileged and non privileged homes. Social class is regarded
as a window into the economic capacity of a family.11 Therefore, individuals in the
higher social classes are more enabled to provide food and health care, factors
which are likely to result in less cases of undernutrition. Although stunting was
most prevalent in social class V and did not exist in social class I, there was no
gradual progression down the social scale. This was contrary to previous
109
observations of progressively higher prevalence of stunting with the lower
classes.42,63 However, the indices of social classification used by these workers are
different from that which was employed in the present study. Additionally, the
social class at the time of this study may not strictly reflect the social stratum in the
pre-school years which is the critical period for stunting.
In the present study, there was no underweight individual in family size 1-3. At the
same time, all individuals belonging to this group were of normal weight category.
This suggests that 1-3 is the ideal family size in the community and may reflect the
tendency of resources to be sufficient when fewer people are available to share
them. It has been noted that overall, food availabilty, access and intake, is strongly
influenced by family structure.36,56 In the current study, the largest family size
holds the highest number of underweight individuals. This is in keeping with
observations by Uthman42 that large household size is associated with higher
prevalence of underweight.
Underweight prevalence increased with increasing family size only to decrease by
family size 7-9. Choudhary et al36 documented a similar trend. However, for this
study, there was another rise in the prevalence of underweight with the largest
family size of 10 individuals or greater following the initial decline. The extended
family system which is still operational in many societies in the developing world
is capable of mitigating the effects of poverty. This is through the pooling of
110
resources and through assistance in child care and may explain the decrease in
undernutrition even with increasing family size. However, this benefit can be
overwhelmed when householders exceed a certain limit, especially when they are
mostly non income generating.
From the current study, about half of the families earned N15,000 or less.
Remarkably, this group accounted for about 70% of underweight persons. In
addition, the highest income group had by far the least prevalence of underweight.
This is similar to the observation by Senbanjo et al39 that significantly higher levels
of wasting existed in the children whose parents earned little than in children
whose parents earned more. Uthman42 also documented vast differences in the
likelihood of underweight between the richest and poorest households. Senbanjo et
al’s observations were with maternal income. However, this study evaluated joint
parental income and so could not assess the impact of maternal income on
nutritional status.
Although this finding was not statistically significant, underweight prevalence was
highest at the lowest level of maternal education, being least with tertiary level of
education in this rural community in Imo state. This is corroborated by Senbanjo et
al39 and Uthman42 in Nigeria, and by Pongou and colleagues40 in Cameroun.
Educated mothers are believed to be more capable of generating extra income
through higher paid jobs. They are also thought to be more adaptable in the use of
111
available food in a nutritious manner. Wachs et al41 and Reed et al67 documented
similar findings of improved nutritional status with better maternal education. By
contrast however, Choudhary et al36 in India noted that while overall nutritonal
status improved with parental education, maternal education did not play any
meaningful role. Rather, this was only significantly influenced by the literacy
status of the father.
Daughters of professionals and individuals in the highest occupational echelon had
zero prevalence of underweight. Underweight prevalence increased steadily as
occupational status moved from highly skilled to unskilled. This pattern held for
both maternal and paternal occupation. Choudhary et al36 documented statistically
significant association between malnutrition and the occupation of labourer. This is
in keeping with the lower income which unskilled labour usually attracts, and
which would in turn result in poverty and limited availability of food and hence
malnutrition.56
The prevalence of iron deficiency in the current study was 13.9%. This was lower
than the prevalence of 16% reported in a group of rural adolescents in India.80
However, it is much higher than the 3.5% reported in Canadian adolescent girls.117
Although multiple indices were used only in the current and Canadian studies, the
trend still shows highest levels of malnutrition in South East Asia, and corroborates
previous observations by the WHO3 and World Bank.56 This study also
112
documented highest prevalence of iron deficiency in the 14 to 16 year age group.
Similar findings were reported by Vasanthi et al80 in which girls older than 14
years were documented to have higher levels of iron deficiency. Apart from the
effects of intake, the twin factors of rapid growth and menstrual loss would
account for the relatively higher levels of iron deficiency around this age.49,51
The present study also documented a significantly higher level of iron deficiency
in the lowest income groups. In addition, there was a direct relationship between
the highest social class and the lowest prevalence of iron deficiency. Although
these findings are not statistically significant, they reflect the overall poorer
nutritional profile of the underclass.10,42
In this community, the prevalence of anaemia using the WHO cut-off of 12g/dl
across the adolescent age group is 77.8%. By this, anaemia was the principal
nutritional problem identified in the survey population. According to the WHO,6
this degree of anaemia is of significant public health importance, with serious
implications for the health of the adolescent girl and that of her unborn child. The
prevalence of anaemia of 77.8% in the present study is considerablly higher than
the 30.4% reported by Choudhary et al in India.12 Although this value is
comparable to that of girls of similar social circumstances in nearby Rivers
state(59.1%),33 it is still higher. This highlights the severity of anaemia from the
113
current study. Of the girls who had anaemia, only 12.5% were iron deficient
indicating other causes of anaemia than iron deficiency.
Average age at menarche which is 13.39 ± 1.1 years is similar to 13.01± 1.44 years
which was found in a group of girls from low income families in Rivers state but
higher than 12.22 ± 1.19 years in girls from middle class families in the same
locality.96 It is also similar to 13.70 ± 0.03 years obtained in a group of urban girls
by Oduntan et al in Ibadan in 1974.118 However, the mean age of menarche of the
rural girls in the same study was considerably higher at 14.50± 0.09 years.
Although the localities differ, these findings suggest a secular trend towards earlier
menarcheal age over the three decades. The mean menarcheal age of the present
study also compared favourably with the mean value of 13.34 ± 1.26 years
obtained in India84. However, it is lower than 15.6 years obtained in Senegal.82 The
nutritional status of these populations with similar age at menarche may have
important similarities as menarcheal age is said to mirror the prevailing nutritional
condition.31
Menarcheal status was significantly correlated with BMI category in the present
study. The greatest proportion of individuals who had attained menarche(93%)
belonged to the highest BMI category. Furthermore, most of the girls who had not
attained menarche were in the underweight category. This is similar to findings by
Leenstra et al31 who documented significant occurence of undernutrition in girls
114
who menstruated late. Other workers82,84 have made similar observations. It is
postulated that increase in body fat serves as a trigger for the onset of menstuation.
Thus menstuation begins earlier in better nourished populations such as in
developed countries.8
In this present study, all the girls who belonged to social class I had attained
menarche compared to 89.2% in social class V. There was however no statistically
significant association between age at menarche and social class. This is contrary
to Ofuya’s findings in which statistically significant differrences existed between
the mean age of menarche and social class(Z score= −11.32).96
. The present study shows a high prevalence of intestinal parasites of 31.1% among
the survey population. This is much lower than the prevalence of 59.5% found by
Rao at al119 in a group of adolescents in India. In both studies however, hookworm
was the most common parasite isolated. Hookworm was found in 13% of the total
stool samples in this study. This closely matches the prevalence of iron deficiency
of 13.9%, indicating a likely important contribution of hookworms to iron
deficiency in the community. This high prevalence may be indicative of poor
disposal of human waste and consequent percutaneous entry where individuals
move about barefoot. This situation is frequently found in rural communities.12
However, the current study did not assess the habits of the girls with respect to the
use of footwear.
115
CONCLUSIONS
1. There was a high prevalence of underweight, and a relatively low prevalence
of stunting among the adolescent girls of the community.
2. Anaemia was the major nutritional problem, being prevalent in 77.8% of the
subjects.
3. There was a high prevalence of iron deficiency and iron deficiency anaemia
in the survey population.
4. Young age, low social class and large family size were the key determinants
of the nutritional status of the girls. These factors caused significant increase
in the prevalence of underweight among the girls.
5. Maternal education and occupation had no significant effect on the
prevalence of underweight in this community.
6. Hookworm was the most common intestinal helminth and had a high
prevalence among the adolescent girls.
116
RECOMMENDATIONS
1. School meals should be initiated so as to mitigate the effects of the high
prevalence of anaemia and underweight in the community.
2. There should be a strengthening of the socio-economic capacity of the
family through poverty alleviation schemes as well as renewed emphasis on
family planning as a child survival strategy. It is hoped that these measures
would address the preponderance of undernutrition among the lower social
classes and large families.
3. Regular deworming of the student population is encouraged.
4. It is recommended that periodic nutritional assessment should be embarked
upon in order to ascertain the trends and areas for nutritional intervention.
117
LIMITATIONS
1. This study included only adolescent girls who were enrolled in school and may
not be wholly reflective of the nutritional status of the community. Fees are
charged in the schools so girls who attend school are the ones who can afford
these fees thereby excluding the poorer ones who may potentially be less well
nourished.
2. A study of the pattern of food intake over a period of time would have been
desirable but not feasible due to the cross-sectional nature of the study.
118
FURTHER RESEARCH
1. To conduct a community-based household survey to enable girls who are not
in school to be studied and actual dietary intake ascertained.
2. To develop local anthropometric references for adolescent girls.
119
REFERENCES
1. “Nutrition.” Stedman’s medical dictionary[e version1.5] Williams and Wilkins,
1994.
2. Ransom EI, Elder LK. Nutrition of women and adolescent girls: why it matters.
PRB, Population Reference Bureau Brief, Washington, D.C.; 2008.
3. WHO. Nutrition in adolescence: issues and challenges for the health sector:
issues in adolescent health and development. WHO Discussion papers on
adolescence. Geneva; 2005.
4. Kaplan DW, Love-Osborne KA. Adolescence In: Hay WW, Levin MJ,
Sondheimer JM, Deterding RR, editors. Current diagnosis & treatment: pediatrics.
19th ed. New York: McGraw-Hill Companies; 2009. p.101-12.
5. Cook Z, Kirk S, Lawrenson S, Sandford S. Use of BMI in the assessment of
undernutrition in older subjects: reflecting on practice. Proc Nut Soc 2005; 64:
313-7.
6. World Health Organization (WHO). Iron deficiency anaemia- assessment,
prevention and control. A guide for programme managers. WHO/NHD/01.3.
Geneva: WHO, 2001.
7. United Nations Population Fund (UNFPA). State of world population 2003:
120
making one billion count: investing in adolescents’ health and rights. New York:
UNFPA; 2003.
8. Joffe A. Introduction to adolescent medicine In: Mcmillan JA, Deangelis CD,
Feigin RD, Warshaw JB, Oski FA, editors. Oski’s pediatrics: principles and
practice[iSilo book, version 4.01, 2004]. 3rd ed. New York: Lippincott Williams &
Wilkins Publishers; 1999. p. 119.
9. Olumakaiye MF. Prevalence of underweight: a matter of concern among
adolescents in Osun State, Nigeria. Pakistan J Nutr 2008; 7: 503-08.
10. Kurz K, Som JN. Study of the factors that influence the nutritional status of
adolescent girls in Cameroon. ICRW Nutrition of adolescent girls research
programme, Research Report Series No. 10; 1994.
11. Dapi LN, Nouedoui C, Janlert U, Haglin L. Adolescents’food habits and
nutritional status in urban and rural areas in Cameroon, Africa. Scand J Nutr 2005;
49: 151-58.
12. Choudhary S, Mishra CP, Shukla KP. Nutritional status of adolescent girls in
rural area of Varanasi. J Prev Soc Med 2003; 34: 54-61.
13. Craft N. Women’s health: Life span: conception to adolescence. BMJ 1997;
315:1227-30.
121
14. Cooper SR, Cooper SP, Felknor SS, Santana VS, Fischer FM, Shipp EM, et al.
Non traditional work factors in farmworker adolescent populations: implications
for health research and interventions. Public Health Rep 2005; 120: 622-29.
15. Neumark-Sztainer D, Story M, Resnick M, Blum R. Lessons learned about
adolescent nutrition from the Minnesota Adolescent Health Survey. J Am Diet
Assoc 1998; 98: 1449-56.
16. Krowchuk DP, Kreiter SR, Woods CR, Sinal SH, DuRant RH. Problem dieting
behaviours among young adolescents. Pediatr Arch Adolesc Med 1998; 152: 884-
88.
17. Nelson M. Anaemia in adolescent girls: effects on cognitive function and
activity. Proc Nut Soc 1996; 55: 359-67.
18. Eskeland B, Hunskaar S. Anaemia and iron deficiency screening in
adolescence: a pilot study of iron stores and haemoglobin response to iron
treatment in a population of 14–15-year-olds in Norway. Acta Paediatr 1999; 88:
815-21.
19. Scholl TO, Johnson WG. Folic acid: influence on the outcome of pregnancy.
Am J Clin Nutr 2000; 71: 1295S-1303S.
20. Lone FW, Qureshi RN, Emanuel F. Maternal anaemia and its impact on
perinatal outcome. Trop Med & Int Health 2004; 9: 486-90.
122
21. Murray-Kolb LE, Beard JL. Iron treatment normalises cognitive functioning
in young women. Am J Clin Nutr 2007; 85: 778-87.
22. Halterman JS, Kaczorowski JM, Aligne CA, Auinger P, Szilagyi PG. Iron
deficiency and cognitive achievement among school-aged children and
adolescents in the United States. Pediatrics 2001; 107: 1381-6.
23. Dietz W. Childhood weight affects adult morbidity and mortality. J Nutr
1998; 128: 411S-14S.
24. De Henauw S, Gottrand F, De Bourdeaudhuij I,Gonzalez-Gross M, Leclercq
C, Kafatos A, et al. Nutritional status and lifestyles of adolescents from a public
health perspective. The HELENA Project—Healthy lifestyle in Europe by
nutrition in adolescence. J Public Health 2007; 15: 187-97.
25. Food and Agriculture Organisation, FAO. Nutritional Status Assessment and
Analyses: nutritional status indicators- FAO Learner Notes, Rome; 2007.
26. Beegum MR. Prevalence of malnutrition among adolescent girls: a case study
in Kalliyoor Panchayat, Thiruvananthapuram. Kerala Research Programme on
local level development Discussion papers No.35, 2001.
123
27. Woodruff BA, Duffield A. Anthropometric assessment of nutritional status in
adolescent populations in humanitarian emergencies. Eur Clin Nutr 2002; 56:
1108-18.
28. De Onis and Blossner M. The World Health Organisation global database on
child growth and malnutrition: methodology and applications. Int J Epidemiol
2003; 32: 518-26.
29. WHO. Prevalence of excess body weight and obesity in children. European
Environment and Health Information System, ENHIS Factsheet no. 2.3,
Copenhagen, 2007.
30. Wang Y, Monteiro C, Popkin BM. Trends of obesity and underweight in older
children and adolescents in the United States, Brazil, China and Russia. Am J Clin
Nutr 2002; 75: 971-77.
31. Leenstra T, Petersen LT, Kariuki SK, Oloo AJ, Kager PA, ter Kuile FO.
Prevalence and severity of malnutrition and age at menarche; cross-sectional
studies in adolescent schoolgirls in Western Kenya. Eur J Clin Nutr 2005; 59: 41-
8.
32. Glew RH, Conn CA, Bhanji R, Calderon P, Barnes C, VanderJagt DJ. Survey
of the growth characteristics and body composition of Fulani children in a rural
hamlet in northern Nigeria. Afr J Biomed Res 2003; 6: 123-7.
124
33. Brabin L, Ikimalo J, Dollimore N, Kemp J, Ikokwu-Wonodi C, Babatunde S,
Obunge O, Briggs N. How do they grow? A study of south-eastern Nigerian
adolescent girls. Acta Paediatr 1997; 86: 1114-20.
34. Anand K, Kant S, Kapoor SK, Nutritional status of adolescent school children
in rural North India. Indian Pediatr 1999; 36: 810-6.
35. Weaver MC, Peacock M, Johnston CC Jr. Adolescent nutrition in the
prevention of postmenopausal osteoporosis. J Clin Endocrinol Metab 1999; 84:
1839-43.
36. Choudhary S, Mishra C & Shukla K. Correlates Of Nutritional Status Of
Adolescent Girls In The Rural Area Of Varanasi. The Internet Journal of Nutrition
and Wellness [electronic resource] 2009 [accessed 2009 Dec 30] vol 7, no 2.
Available from:URL:
http://www.ispub.com/ostia/index.php?xmlFilePath=journals/ijnw/front.xml
37. Smith LC, Haddad L. Overcoming child malnutrition in developing countries:
past achievement and future choices. IFPRI Research Brief 64. Washington:
International Food Policy Research Institute, 2000.
38. Lucas AO. Nutrition and infection. Am J Trop Med Hyg 1992; 47(1): 36-8.
39. Senbanjo IO, Adeodu OO, Adejuyigbe EA. Influence of socio-economic
factors on nutritional status of children in a rural community of Osun State,
125
Nigeria. Accessed 2009 Dec 11. Available from : URL:
http://www.uib.es/congres/ecopub/ecineq/papers/235senbanjo.pdf
40. Pongou R, Salomon JA, Ezzati M. Health impact of macro-economic crises
and policies: determinants of variation in childhood malnutrition trends in
Cameroon. Int J Epidemiol 2006; 35: 648-56.
41. Wachs TD, Creed-Kanashiro H, Cueto S, Jacoby E. Maternal education and
intelligence predict offspring diet and nutritional status. J Nutr 2005; 135: 2179-86.
42. Uthman OA. A multilevel analysis of individual and community effect on
chronic childhood malnutrition in rural Nigeria. The Internet Journal of Nutrition
and Wellness [electronic resource] 2008 [accessed 2008 Dec 28]; vol 6, no 2.
Available from:URL: http://www.ispub.com/ostia/index.php
43. Shepherd R, Dennison CM. Influences on adolescent food choice. Proc Nut
Soc 1996; 55: 345-57.
44. Needlman RD. Adolescence In: Behrman RE, Kliegman RM, Jensen HB,
editors. Nelson textbook of pediatrics. 17th ed. Philadelphia: WB Saunders; 2003.
p.53-58.
45. Finberg L. Feeding the healthy child- nutritional needs and dietary analysis In:
Mcmillan JA, Deangelis CD, Feigin RD, Warshaw JB, Oski FA, editors. Oski’s
126
pediatrics: principles and practice. [iSilo book, version 4.01, 2004] 3rd ed. New
York: Lippincott Williams & Wilkins Publishers; 1999. p. 114.
46. Krebs NF, Primak LE. Normal childhood nutrition and its disorders In: Hay
WW, Levin MJ, Sondheimer JM, Deterding RR, editors. Current diagnosis &
treatment: pediatrics. 19th ed. New York: McGraw-Hill Companies; 2009. p. 268-
71.
47. Frary CD, Johnson RK, Wang MQ. Children and adolescents’ choices of foods
and beverages high in added sugars are associated with intakes of key nutrients and
food groups. J Adolesc Health 2004; 34: 56-63.
48. Beard JL. Iron biology in immune function, muscle metabolism and neuronal
functioning. J Nutr 2001; 131: 568S-80S.
49. Ekpo AJ, Jimmy EO. Dietary and haematological evaluation of adolescence
females in Nigeria. Pakistan J Nutr 2008; 7: 503-08.
50. Olivares M, Walter T, Hertrampf E and Pizarro F. Anaemia and iron deficiency
disease in children. Br Med Bull 1999; 55: 534-43.
51. Glader B. Iron deficiency anaemia In: Behrman RE, Kliegman RM, Jensen HB,
editors. Nelson textbook of pediatrics. 17th ed. Philadelphia: WB Saunders; 2003.
p.1614-16.
127
52. Whiting SJ, Vatanparast H, Baxter-Jones A, Faulkner RA, Mirwald R and
Bailey DA. Supplement: nutritional influences on bone growth in children. Factors
that affect bone mineral accrual in the adolescent growth spurt. J Nutr 2004;134:
696S-700S.
53. Poskitt EME. Nutrition in childhood In: Hendrickse RG, editor. Paediatrics in
the tropics. London: Blackwell Scientific Publications; 1991. p. 90-118.
54. Solanzo FG. Folic acid deficiency causes birth defects. Food and Nutrition
Research Institute, FNRI online newsletter [accessed 2008 Nov 14]. Available
from: URL: www.fnri.gov.ph
55. Benefice E, Garnier D, Ndiaye G. High levels of habitual physical activity in
west African adolescent girls and relationship to maturation, growth and nutritional
status: results from a 3-year prospective study. Am J Hum Biol 2001; 13: 808-20.
56. Cleaver K, Okidegbe N, De Nys E. Agriculture and rural development: hunger
and malnutrition. World Bank Seminar Series, Jan. 2006.
57. Olusanya O, Okpere E, Ezimokhai M. The importance of social class in
voluntary fertility control in a devloping country. W Afr Med J 1985; 4: 205-12.
128
58. Walker SP, Grantham-McGregor S,Himes JH and Williams S. Adolescent
Kingston girls’ school achievement: nutrition, health and social factors. Proc Nut
Soc 1996; 55: 333-43.
59. Vyas S and Kumaranayake L. How to do (or not to do) . . .constructing socio-
economic status indices: how to use principal components analysis. Advance
publication London School of Hygiene and Tropical Medicine. Oxford: OUP; Oct
2006.
60. Onwujekwe O, Hanson K, Fox-Rushby J. Some indicators of socio-economic
status may not be reliable and use of indices with these data could worsen equity.
Health Econ 2006;15: 639–44.
61. Houweling TAJ, Kunst AE, Mackenbach JP. Measuring health inequality
among children in developing countries: does the choice of the indicator of
economic status matter? Int J Equity Health 2003; 2:8.
62. Nwokocha ARC. Adolescence and associated problems In: Azubuike JC,
Nkanginieme KEO, editors. Paediatrics and child health in a tropical region.
Owerri: African Educational Services; 1991. p. 97-109.
63. Venkaiah K, Damayanti K, Nayak MU, Vijayaraghavan K. Diet and
nutritional status of rural adolescents in India. Eur J Clin Nutr 2002; 56: 1119-25.
64. Gopalan S. Malnutrition: causes, consequences and solutions. Nutrition 2000;
16: 556-8.
129
65. Maxwell D, Levin C, Amar-Klemesu M, Ruel M, Morris S, Ahiadeke C. Urban
livelihoods and food and nutrition security in greater Accra, Ghana. IFPRI
Research Report 112; 2000.
66. Oninla SO, Owa JA, Onayade AA and Taiwo O. Comparartive study of
nutritional status of urban and rural Nigerian school children. J TropPaed 2007;
53: 39-43.
67. Reed BA, Habicht J, Niameogo C.The effects of maternal education on child
nutritional status depend on socio-environmental conditions. Int J Epidmiol 1996;
25: 585-92.
68. Akinsola HA. Public health nutrition In: Akinsola HA: A to Z of community
health and social medicine in medical and nursing practice. Ibadan: 3AM
Communications; 1993. p.122-25.
69. Food and Agriculture Organisation, FAO. Corporate document repository-
Gender and Development Plan of Action(Food and Nutrition) accessed from the
FAO website on 6/10/2009.
70. Kehski-Rahkonen A, Kaprio J, Rissanen A, Virkkunen M and Rose RJ.
Breakfast skipping and health-compromising behaviours in adolescents and adults.
Eur J Clin Nutr 2003; 57:842-53.
71. Findlay S. Dieting in adolescence. Paediatr Child Health 2004; 9: 487-91.
130
72. Cavadini C, Siega-Riz AM, Popkin BM. US adolescent food intake trends from
1965 to 1996. Arch Dis Child 2000; 83: 18-24.
73. Powell LM, Szczypka G, Chaloupka FJ. Exposure to food advertising on
television among US children. Arch Pediatr Adolesc Med 2007; 161: 553-60.
74. Hill AJ. Symposium on “Nutrition and health in children and adolescents”
Session 3: Eating behaviour and early indicators of metabolic syndrome.
Motivation for eating behaviour in adolescent girls: the body beautiful. A meeting
of the Nutrition Society hosted by the Irish Section was held on 14–16 June 2006
at University College Cork, Cork, Republic of Ireland. Proc Nut Soc 2006; 65:
376-84.
75. Tiggemann M, Gardiner M, Slater A. “I would rather be size 10 than have
straight A’s” : a focus group study of adolescent girls’ wish to be thinner. J
Adolesc 2000; 23:645-59.
76. Heird WC. Food insecurity, hunger, and undernutrition. In: Behrman RE,
Kliegman RM, Jensen HB, editors. Nelson textbook of pediatrics. 17th ed.
Philadelphia: WB Saunders; 2003. p. 167-72.
77. Oski FA. Iron deficiency in infancy and childhood. N Engl J Med 1993; 329:
190-93.
131
78. Lawson MS, Thomas M, Hardiman A. Iron status of Asian children aged two
years living in England. Arch Dis Child 1998; 78: 420-6.
79. Sharma A, Prasad K, Rao KV. Identification of appropriate strategy to control
anaemia in adolescent girls of poor communities. Indian Pediatr 2000; 37: 261-7.
80. Vasanthi G, Fawashe AB, Susie H, SujathaT, Raman L. Iron nutritional status
of adolescent girls from rural area and urban slum. Indian Pediatr 1994; 31: 127-
32.
81. Kurz KM. Adolescent nutritional status in developing countries. Proc Nut Soc
1996; 55: 321-31.
82. Simondon KB, Simondon F, Simon I, Diallo A, Benefice E, Traissac P, et al.
Preschool stunting, age at menarche and adolescent height: a longitudinal study in
rural Senegal. Eur J Clin Nutr 1998; 52: 412-8.
83. Bose K, Bisai S. Nutritional status of rural adolescent school children in
Paschim Medinipur, West Bengal. Indian Pediatr 2008; 45: 515.
84. Acharya A, Reddaiah VP, Baridalyne N. Nutritional status and menarche in
adolescent girls in an urban resettlement colony of South Delhi. Indian J Comm
Med 2006; 31: 302-3.
132
85. Birch LL, Fisher JO. Development of eating behaviours among children and
adolescents. Pediatrics 1998; 101: 539-49.
86. Gortmaker SL, Must A, Perrin JM, Sobol AM, Dietz WH. Social and economic
consequences of overweight in adolescence and young adulthood. N Engl J Med
1993; 329: 1008-12.
87. Ben-Bassey UP, Oduwole AO, Ogundipe OO. Prevalence of overweight and
obesity in Eti-Osa LGA, Lagos, Nigeria. Obes Res 2007; 8: 475-9.
88. de Onis M. Measuring nutritional status in relation to mortality. Bull World
Health Organ 2000; 78 no. 10.
89. Cole TJ, Flegal KM, Nicholls D, Jackson AA. Body mass index cutoffs to
define thinness in children and adolescents: international survey. BMJ 2007;
335:194.
90. Ulijaszek SJ, Kerr DA. Anthropometric measurement error and the assessment
of nutritional status. British J Nutr 1999; 82: 165-77.
91. World Health Organisation. Physical status: the use and interpretation of
anthropometry. WHO Technical Report Series. 1995; 854: 1-452.
92. Gomes F, dos Anjos LA, de Vasconcellos. Cad Saude Publica 2009; 25: 8.
133
93. De Onis. Measuring nutritional status in relation to mortality. Bull World
Health Organ 2000; vol. 78 no. 10, Geneva.
94. Current WHO recommendations for adolescent anthropometry summarised
from report of a WHO Expert Committee accessed from
www.unsystem.org/SCN/archives/adolescents on 18/11/2008.
95. Agarwal KN, Saxena A, Bansal AK, Agarwal DK. Physical growth assessment
in adolescence. Indian Pediatr 2001; 38: 1217-35
96. Ofuya ZM. The age at menarche in adolescents from two different socio-
economic classes. OJHAS 2007 vol 6 issue 4(3).
97. Jeejeebhoy KN. Nutritional Assessment. Nutrition 2000; 16: 585-90.
98. Witte DA. Laboratory tests to confirm or exclude iron deficiency. Laboratory
Medicine 1985;16: 671-75.
99. Okeahialam TC, Obi GO. Iron deficiency in sickle cell anaemia in Nigerian
children. Ann Trop Paediatr 1982; 2: 89-92.
100. Punnonen K. Laboratory diagnosis of iro deficiency anaemia. Scand J Clin
Lab Invest 2005; 65: 533-34.
101. Oluboyede OA. Iron studies in pregnant and non pregnant women with
haemoglobin SS or SC disease. Br J Obstet Gyneacol 1980; 87: 989-96.
134
102. Leyland MJ, Baski AK, Brown PJ, Kenny TW, Strange CA. Assessment of
nutritional anaemia in Northern Nigeria. Ann Trop Med Parasitol 1979; 73: 63-71.
103. Worwood M. Ferritin. Blood Rev 1990; 4: 259-69.
104. Hereberg S, Galan P, Chauhac M, Zohoun I, Raimbault AMM. Iron status and
inflammatory processes in anaemic children. J Trop Paed 1987; 33: 168-71.
105. Nicklas TA, Kuribidila S, Gatewood LC, Metzinger AB, Frempong KO.
Prevalence of anaemia and iron deficiency in urban Haitian children two to five
years of age. J Trop Paed 1998; 44: 133-38.
106. Cole AH, Taiwo OO, Nwagbara NI, Cornelia CE. Energy intakes,
anthropometry and body composition of Nigerian adolescent girls: a case study of
an institutionalised secondary school in Ibadan. Br J Nutr 1997; 77: 497-509.
107. Videon TM, Manning CK. Influences on adolescent eating patterns: the
importance of family meals. J Adolesc Health 2003; 32: 365-73.
108. Fisher JO, Mitchell DC, Smiciklas-Wright H, Birch LL. Parental influences
on young girls’ fruit and vegetable, micronutrient, and fat intakes. J Am Diet Assoc
2002; 102: 58-64.
135
109. National Population Commission: projections from the final result of the 1991
census.
110. Araoye MO. Subjects selection In: Araoye MO, ed. Research methodology
with statistics for health and social sciences. Ilorin: Nathadex Publishers; 2003.
p.115-29.
111. Osinusi K, Njinyam MN. Comparison of body temperatures taken at different
sites and the reliability of axillary temperature in screening for fever. Afr Med Sci
1997; 26: 163-6.
112. Jelliffe DB. The assessment of the nutritional status of the community, WHO
Monograph Series, no. 53 (Geneva,1966).
113. WHO. Growth reference 5-19 years. From the internet, WHO website:
www.int/growthref/en. accessed on 31/10/08
114. Tietz NW. Fundamentals of clinical chemistry. Philadelphia: W.B. Saunders
1976; pp.923-29.
115. Mukhopadhyay A, Badra M, Bose K. Anthropometric assessment of
nutritional status of adolescents of Kolkata, West Bengal. J Hum Ecol 2005; 18:
213-16.
136
116. Mulugeta A, Hagos F, Stoecker B, Kruseman G, Linderhof V, Abraha Z,
Yohannes M and Samuel GG. Nutritional status of adolescent girls from rural
communities of Tigray, Northern Ethiopia. Ethiop J Health Dev 2009; 23: 5-11.
117. Deegan H, Bates HM, McCargar LJ. Assessment of iron status in adolescents:
dietary, biochemical and lifestyle determinants. J Adolesc Health 2005; 37: 15-21.
118. Oduntan OO, Ayeni O, Kale OO. The age of menarche in Nigerian girls. Ann
Hum Biol 1976; 3: 269-74.
119. Rao VG, Aggrawal MC, Yadav R, Das SK, Sahare LK, Bondley MK et al.
Intestinal parasitic infections, anaemia and undernutrition among tribal adolescents
of Madhya Pradesh. Indian J Com Med 2003; 28(1).
137
APPENDIX 1
CONSENT FORM
Department of Paediatrics
Federal Medical Centre,
Owerri.
Dear parents/guardians,
I am a medical doctor working in the department of paediatrics of the Federal
Medical Centre, Owerri. With the approval of the hospital authorities and the state
school management board, I am conducting a study on the state of nutrition of our
young females. This study will entail height and weight measurements as well as
free blood test. The participants will also benefit from a free clinical examination.
All findings in the study will be strictly confidential and subjects will be treated
free of charge. Results will also be made available on request. This study is safe
and is not harmful to the participants.
I am therefore requesting your permission to include your child in this health
survey. If you accept, kindly sign or thumb print and answer the questions in
Section A. Please be informed that you can withdraw your child/ ward at any stage
of the study if you so desire. Thanks.
..................................................... .....................................
Signature/mark of parent/guardian Dr F.U. Iregbu
..................................
Supervising consultant.
138
APPENDIX 2
QUESTIONNAIRE
Part A:
i. Personal identification data
1. Serial no. ............................. 2. Date of birth: .................................
3. Age(at last birthday): ................... 4. Class:...........................
ii. Family data
5. How long have you lived in Ogbaku? (specify): ....................................
6. Child lives with (tick) : a. Parents ........... b. Other relatives(specify):
........................... c. Guardian(unrelated) ...................................
7. No of persons in household: .................... 8. No of siblings: .................
9. Father’s occupation (specify): ................................................
10. Mother’s occupation (specify): ..................................................
11. Levels of parents’ education – Tick as appropriate
Mother Father
Up to university [ ] [ ]
Polytechnic [ ] [ ]
College of Education/
School of nursing [ ] [ ]
Secondary school
Completed SS3 [ ] [ ]
Completed JS3 [ ] [ ]
Primary school
Completed [ ] [ ]
139
Not completed [ ] [ ]
No schooling [ ] [ ]
12. Parents’ /guardian’s marital status: Married ........, Single...........,
(c.Divorced............., (d. Widowed........
13. Average monthly income of father(specify) : ...................................
14. Average monthly income of mother(specify): ....................................
Part B:
Section A
Personal health information:
15. Are you on any medication? Yes [ ], No [ ]. If Yes, what
medication? .................................. How long have you taken it? ...................
Who prescibed it? ...............................
16.Haemoglobin genotype ....................
17. How many times ill/hospitalised this year ..................
18. Fever in the last three weeks? Yes [ ], No [ ].
Dietary pattern:
19. Usual no. of meals / day: (a. once [ ], (b) 2 times [ ],(c) 3 times [ ]
20. Usual 24-hr dietary intake:
a. Breakfast ................ b. Lunch ...................c. Dinner ................
21. Frequency of meat or fish intake: a. Daily [ ], (b. 3 times/week [ ],
(c. Others [ specify]...............................................................
22. Frequency of consumption of fresh fruits a. Daily [ ], (b. 3
times/week [ ], (c. Others [ specify]...............................................................
23. Are there foods you are forbidden to eat? Yes[ ], No[ ].
If yes, specify ................................................
140
Section B
Nutrition Knowledge:
24. A balanced diet consists of : (a.carbohydrate [ ], (b.carbohydrate +
protein [ ], (c. A+B+ fats [ ], (d. C+ vitamins & minerals [ ].
25. A rich source of iron is: (a. Liver [ ], (b. Garri [ ], c. Rice [ ].
Section C
Hygiene and sanitation:
26. Source of drinking water( specify): .................................................
27. Method of sewage disposal(specify):...............................................
28. Hand washing after defecation: a. Always[ ], b. Often [ ], c.
Sometimes[ ].
Section D
Personal attitudes:
29. How do you regard your body size and shape? (a). Too thin [ ],
(b). Too big [ ], (c). Normal size [ ].
30 . Do you try to control your weight? Yes [ ], No [ ].
If yes, how? a.Exercise [ ], b. Eating less [ ], c.
Others(specify).......................................
Section E
Level of activity:
31. How do you get to school? (a). On foot [ ], (b).By bike [ ], (c).
Other (specify) ..........................................
32. What is the distance between your home and school? a. Far [ ] ,
b. Very far [ ], c. Near [ ].
33. Do you play games in school? Yes [ ], No [ ]. If yes,
specify………………
141
34. Usual activity after school: (a. Farm work [ ], (b. Rest &
relaxation [ ], (c. Household chores [ ].
Section F
Sexual maturation:
35. Have you started seeing your periods? Yes [ ], No [ ].
36. If ‘yes’ to above, a) Age at first menstruation:........................
b) Last menstrual period...............................
c) Duration of menstrual bleed ...................
Section G
Clinical Examination :
...........................................................................................................................
...........................................................................................................................
...........................................................................................................................
Anthropometric parameters:
Weight (kilograms) :....................
Height (centimeters): ....................
Body mass index( kg/m2) ..................
Laboratory tests:
Haemoglobin (g/dl):..................
Serum ferritin (ng/ml)…………
TIBC (microg/dl) .....................
Serum Iron (microg/dl.........................
Stool analysis …………………...............
142
143
144
145
146
147
APPENDIX 8
METHOD USED FOR SOCIAL CLASSIFICATION OF THE SUBJECTS
A
SCORE FATHER’S OCCUPATION
1 Professional, top civil servants, elected
Politicians and top businessmen.
2 Middle level bureaucrats, technician, skilled
Artisans
3 Unskilled worker and those in general
whose incomes are below the minimum
wage.
B
SCORE MOTHER’S LEVEL OF EDUCATION
0 Education up to University
1 Secondary education or tertiary education
below university(e.g. college of educa-
tion, school of nursing)
2 No schooling or up to primary education
Social Class = score from A + score from B
148
APPENDIX 9 :
Equipment used in the study
Digital Scale Stadiometer
149
APPENDIX 10
Results of biochemical analyses :
Hb Serum iron TIBC Ferritin
12.6 129 397.7 4.1
13.5 162.6 412.6 34.7
12 150 386 43
11 114.5 387 21
11 144 446 23
12 181 652 30
11 164 601 31
12 171 439.6 44
10 133 306 4
13 140 593 48
11 126 236 33
10 144 504 2.2
10 81 519 8
11 138 252 19
10 97 403 41
14 103 556 20
10.9 145 314 1.7
10 84 404 2
11 127 435 15
11.6 116 428 16.9
11 83 333 9
11 172 293 35
13 128 283 37
12 121 584 30
. . . .
10 115 604 1.5
10.2 74 541 5.9
10.7 45 353 19
10 31 335 199.5
10 10 327 8
Hb Serum iron TIBC Ferritin
10 85 427 11
9 14 507 16
11 70 513 16
11 38 370 26
11 50 510 70
10 10 399.5 10
11 48 295 12
12 39 389 47
10 39 382 39
11 18 305 22
10 25 450 64
10 50 358 45
11 5 427 15
11 8 288 33
10 45 468 50
. . . .
11 27 492 52
9.5 24 366 106
11 89 404 31
10 24 369 38
9 13 503 47
10 35 455 17
9 52 430 31
10 49 456 127
10 41 386 44
12.1 69 347 197
11 46 529 37
10 37 394 46
12 24 324 90
12.3 18 418 285
11 59 225 27
11 20 502 224
150
Hb Serum iron TIBC Ferritin
11 35 457 114
10 7 15 332
9 6 408 36
12 7 404 36
12 19 487 11
11.1 134 445 32
11 115 388 20
13.4 166.4 414.2 33.4
12.5 128 379 5.4
12 141 390 40
11 125 240 30.3
12.9 142 597 50
12.0 118 463.9 38
11 160 607 43.4
12 170 440 40.6
10 130 310 6
10.1 98 400.3 39
12 150 310 2.1
10 134 507 4
10 80 521 9
11 139 250 20
11 172 291 33.5
13 129 280 38
12 123 580.4 29
10 116 603 1.6
12.2 73 539 6.1
14 104 561 22
11 82 329 7
12 118 427 17.1
. . . .
11.1 127 437 16
10 83 403 3.1
10.5 92.2 418.5 5.3
11.2 36.2 187.7 8.5
10.9 14.2 164.2 12.2
11 42.5 150.9 6.8
11 12.5 330.3 29.3
11.6 92.5 524.7 1.2
10.2 106.3 449.5 29.7
12.2 157.5 369.4 25.9
Hb Serum iron TIBC Ferritin
11 66.3 282.4 93.8
11.3 46.3 415 11.2
. . . .
8.9 5 360.9 283.7
10.6 52.5 69.5 50.1
10.3 32.5 62.2 4.9
. . . .
11.3 60 432.9 71.6
. . . .
11 136.3 449.5 29.7
11.6 112.5 476.9 1.3
11.2 55 334.7 9.9
11.7 151.3 409 25.4
. . . .
10.6 23.8 197.5 8
11.1 18.8 251.9 1
9.8 40 103.6 22
12.0 62.5 198.1 107
. . . .
12.5 70 400.5 54.8
. . . .
10.3 17.5 479 21.9
10 10 374 21.9
11 15 277.7 32
. . . .
10.7 3.8 232.6 1
12.5 63.8 157 229.7
10 23.8 417.9 0.7
16.1 13 347.3 42.6
11 56 217.3 17
11.6 52.5 183.9 44
9.9 62.5 232 17
10 54 494.5 67.7
. . . .
11.8 36 468.5 23
10 19 400 8
12.6 109 473 34
9.5 23 145 1
11 3 44.9 14
11 13 241 38
151
Hb Serum iron TIBC Ferritin
11 46 381 30
11 200 305 38
10 51 306 38
12.4 18 212 132
. . . .
10 14 310 1.2
11.3 43.6 416 11.1
12.1 155.6 370.3 26.2
11.0 66.2 281.3 92.9
10.1 107.2 450.2 27.2
10.5 91.3 417.9 5.2
10.3 31.4 62.4 5.1
10 13 309 1.4
9.0 6 359.7 281.5
11.3 36.2 181.1 8.7
10.9 14.1 162.3 12.4
. . . .
11 43.4 150.8 7.1
11 12.6 327.9 31.2
10.3 93.1 525 1.6
. . . .
10.2 38 466 21
. . . .
12.7 110.1 477 36
10 21 408 9
10.5 26 133 3
12 19.9 223 138
. . . .
10 49.7 301 40
11 198 310 42
11.1 5 43 13
12 45 390 34
. . . .
11 12 244 41
. . . .
9.9 46.7 101 24
13 60 215 20
12.1 67 404 58.3
. . . .
10.5 63 202 110
Hb Serum iron TIBC Ferritin
11.8 19.2 250.2 2
11.6 17.9 500 20.4
10.8 52 496.2 70.2
10.4 20 380 19.7
11.5 21 314 35
10.5 4.1 236.4 2
11.5 53.4 186.6 40
. . . .
10.0 56 499 61.6
10.8 21.5 402 1.1
11.8 12 344 44.2
10.0 65.3 161.1 30
11.3 139.2 454 36.2
11.4 117 480.3 1.8
12.1 58 333.1 30.2
11.2 24.9 199.7 9
10.6 53.2 70.9 50.2
11.6 151.7 418 26.3
. . . .
11.7 61 433 72.3
12.8 129 399.4 4.6
11.3 115.4 392 24
11.5 173 602 35
13.0 144 581 60
10.4 90 529 8
14.0 166 567 22
11.1 136 443 21
11.1 181 305 38
10.2 121 608 2.1
10.2 35 343 200
. . . .
10.3 19 507 14.6
11.1 55 511 77
12.2 52 396 58
. . . .
10.0 50 373 54
. . . .
9.9 45 466 45
11 87 396 29
10 32 405 16.1
152
Hb Serum iron TIBC Ferritin
10.0 66 343 127
. . . .
12.0 20.2 318 81
11.0 18 500 218
9.0 8 21 328
10.2 11 472 12
12 145 372 36
10.8 72 645 27
10.1 27 300 4
10.0 36 500 2.4
10.9 81 396 36
10.1 72 233 3
11.1 80 327 14
12.0 118 572 30
9.5 88.4 417.2 5.8
11 39.2 141.0 6.6
11.8 145.5 356.4 24.4
9.0 6 351.9 273.3
11.3 54 431.8 66.4
i
Top Related