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

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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

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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

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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.

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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.

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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

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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.

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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

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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

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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