Nutrition Sector SMART Survey Report Pakistan, November… · Nutrition Sector SMART Survey Report...

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SMART Survey Report

Kohat District of Khyber Pakhtunkhwa (KP) Province, Pakistan

Hailu Wondim, ACF-International

Nutrition Sector SMART Survey Report Pakistan, November, 2013

Kohat SMART Survey Report, November 2013 ii

ACKNOWLEDGEMENT

We greatly appreciated the support of KP province department of health nutrition cell and Kohat district health office in leading the survey.

We highly appreciate the technical input of Maureen Gallagher (Senior Nutrition Advisor and Cecile Basquin (Nutrition Advisor). This survey could not have been completed without the commitment and hard work of ACF International capital office management team, logistics team, administration and finance team. A special thanks goes to ACF Kohat field team for the proactive support during preparation and implementation of the survey.

Our heartfelt appreciation goes to the survey team (supervisor, data analyst, team leaders and enumerators) who put all their efforts to produce a quality data. We are also thankful to the mothers/caretakers of children who give their time to this survey by responding to the questions raised by the survey team. Last but not least we pass our gratitude to the children who took part in the anthropometric assessment.

This survey and the survey report have been produced with the financial assistance of the UNICEF and WFP. The views expressed herein should not be taken, in any way, to reflect the official opinion of UNICEF or WFP Statement on Copyright © Action Against Hunger | ACF-International Unless otherwise indicated, reproduction is authorised on condition that the source is credited. If reproduction or use of texts and visual materials (sound, images, software, etc.) is subject to prior authorization, such authorization will render null and void the above-mentioned general authorization and will clearly indicate any restrictions on use.

Kohat SMART Survey Report, November 2013 iii

TABLE OF CONTENTS

ACKNOWLEDGEMENT ............................................................................................... ii

ABBREVIATIONS .................................................................................................... iii

1. EXECUTIVE SUMMARY ........................................................................................ 1

2. INTRODUCTION ................................................................................................ 2

3. OBJECTIVES .................................................................................................... 3

4. METHODOLOGY ............................................................................................... 4

5. RESULTS ........................................................................................................ 7

6. CONCLUSIONS ............................................................................................... 12

7. RECOMMENDATIONS ........................................................................................ 13

8. ANNEXES ..................................................................................................... 14

LIST OF TABLES

Table 1: Summary of Nutrition and Health indicator results, Kohat District, Oct 2013 ............... 1

Table 2: Sample size calculation for nutrition status using ENA for SMART software (June 27th, 2013 version) ................................................................................................. 5

Table 3: Distribution of age and sex of sample ............................................................... 7

Table 4: Summary of prevalence of acute malnutrition by Z-score (N=640) ............................ 8

Table 5: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema ........................................................................................................ 8

Table 6: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex . 8

Table 7: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema ....... 9

Table 8: Prevalence of acute malnutrition based on the percentage of the median and/or oedema .................................................................................................................. 9

Table 9: Prevalence of underweight based on weight-for-age z-scores by sex ......................... 9

Table 10: Prevalence of stunting based on height-for-age z-scores and by sex ...................... 10

Table 11: Point Prevalence of child morbidity in children 6-59 months in the two weeks prior to the survey (n=648) ......................................................................................... 10

Table 12: Percentage distribution of children 6-59 months by illness in the 2 weeks prior to the survey ........................................................................................................ 10

Table 13: BCG and measles vaccination and Vitamin A supplementation coverage ................. 10

Table 14: Households water source, child excreta disposal and toilet availability .................. 11

LIST OF FIGURES

Figure 1: Map of Kohat District, October 2013 ............................................................... 2

Kohat SMART Survey Report, November 2013 iv

ABBREVIATIONS

BCG Bacillus Calmette–Guérin

CMAM Community Based Management of Acute Malnutrition

DHO District Health Office

DoH Department of Health

ENA Emergency Nutrition Assessment

ECHO European Commission Humanitarian Office

FSL Food Security and Livelihood

GAM Global Acute Malnutrition

IDP Internally Displaced People

IYCF Infant and Young Child Feeding

IVAP Internally Vulnerability Assessment & Profiling

KP Khyber Pakhtunkhwa

MUAC Mid Upper Arm Circumference

PDAR Person Days At Risk

UC Union Council

SMART Standard Monitoring and Assessment of Relief and Transition

WHO World Health Organization

WASH Water Sanitation and Hygiene

Kohat SMART Survey Report, November 2013 1

1. EXECUTIVE SUMMARY

Kohat district is located in Khyber Pakhtunkhwa (KP) province, 180km from Islamabad and 65km from Peshawar (the provincial capital). It is sub-divided into 33 Union Councils (UCs). It is bordered by Peshawar district in the north, Hangu and Kurak in the south, Nowshera in the east, and Oarkzai Agency in the west. Military operation in Bajur district and insurgency activity throughout 2011 caused a significant number of displaced persons to Kohat District. The majority of Internally Displaced People (IDP) stay with host communities, stretching the capacity of households who employ distress mechanisms to overcome the additional strain. During 2012, Kohat has received part of the newly displaced population from Khyber Agency, thus the pressure on traditional livelihoods in combination with structural vulnerabilities has had the effect of reducing the overall quality of life and resilience for the region.

The overall objective of the nutrition survey was to measure the extent and severity of acute malnutrition in children aged 6 to 59 months and their caregivers (pregnant and lactating women).

The survey was conducted in 26 IDP affected union councils1 of Kohat District of KP Province. The study was conducted from 1st through 7th of October, 2013. Across sectional study with two-stage cluster sampling using Standardized Monitoring of Relief and Transition (SMART) methodology was used.

A total of 640 children aged 6-59 months were assessed for their nutritional status through anthropometric measurements from 506 sampled households. The data quality analysis is presented in annex1 (plausibility check on anthropometric results). Table 1: Summary of Nutrition and Health indicator results, Kohat District, Oct 2013

2

Index Indicators Results

WHO 2006

WHZ- scores

Global Acute Malnutrition Weight for height< -2 z and/or oedema

8.0% (6.1 - 10.3)

Severe Acute Malnutrition Weight for height < -3 z and/or oedema

1.3% (0.7 - 2.3)

HAZ- scores

Stunting Height for age <-2 z-score

28.9% (24.7 - 33.4)

WAZ-scores

Underweight Weight for age <-2 z-score

18.2% (15.6 - 21.0)

MUAC

Global Acute Malnutrition MUAC <125 mm or oedema

2.8% (1.6 - 4.6)

Severe Acute Malnutrition MUAC <115 mm or oedema (<115mm)

0.3% (0.0 - 2.3)

1IDP affected union councils are those councils which have at least ten IDP households (as agreed in the cluster meeting) as per the IVAP 2011 assessment report 2Figures in brackets are 95% confidence intervals (C.I.)


2. INTRODUCTION

The 24 districts making up the KP province are: Chitral, Upper Dir, Lower Dir, Swat, Kohistan, Shangla, Batagram, Buner, Manshera, Malakand, Maradan, Swabi, Haripur, Abottabad, Charasadda, Peshawar, Nowshera, Kohat, Hangu, Karak, Bannu, LakkiMarawat, Tank, and DI Khan.

Kohat district is located 180km from Islamabad and 65km from Peshawar (the provincial capital). It is sub-divided into 33 UCs. It is bordered by Peshawar district in the north, Hangu and Kurak in the south, Nowshera in the east, and Oarkzai Agency in the west (Figure 1).

Figure 1: Map of Kohat District, October 2013

Kohat is the 14th most highly populated district of KP. It has a total population of 1,043,850 and under five population of 177,455 (17%)3. Military operation in Bajur district and insurgency activity throughout 2011 caused a significant number of displaced people to Kohat District. The majority of Internally Displaced Persons (IDPs) stay with host communities, stretching the capacity of households who employ distress mechanisms to overcome the additional strain. During 2012 Kohat has received part of the newly displaced population from Khyber Agency, thus the pressure on traditional livelihoods in combination with structural vulnerabilities has had the effect of reducing the overall quality of life and resilience for the region. Kohat has very little Water Sanitation and Hygiene (WASH) infrastructure/services. Based on the Internally Vulnerability Assessment and Profiling (IVAP) Report in July 2011, Kohat hosts the third largest population of IDPs in KP, with almost 18,111 families and the second largest population of unregistered IDPs4.

3 District Health Office 4 Integrated Rapid Needs Assessment, Food Security and Livelihoods (FSL), Water, Sanitation and


ACF International supports the Department of Health (DoH) in Community Management of Acute Malnutrition (CMAM) in 5 UCs with funds from the Humanitarian Aid and Civil Protection department of the European Commission (ECHO). This one year ECHO project integrates Food Security and Livelihoods (FSL), Water Sanitation and Hygiene (WASH) and nutrition.

The proposed strategy for nutrition is designed to ensure the provision of lifesaving nutrition services for acutely malnourished children, pregnant and lactating women in camps and off-camp; to prevent poor nutritional outcome through rigorous promotion of optimal infant feeding practices, proper hygiene/sanitation and improved maternal nutrition; micronutrient supplementation and nutrition education on locally available foods; setting up of a robust reporting and information system and monitoring mechanism; and an emphasis on capacity development of health care providers for all target areas to be implemented in partnership with the DoH and provincial nutrition cells in KP & FATA.

In the back drop of this and as a follow-up of the efforts that is going to be implemented in Kohat district, there was a need to establish baseline information through an assessment of nutritional status of children.

3. OBJECTIVES

3.1 General Objective The overall objective of the proposed nutrition surveys was to measure the extent and severity of acute malnutrition in children aged 6 to 59 months and among pregnant and lactating women.

3.2 Specific Objectives

To estimate the prevalence of acute and chronic malnutrition among children 6-

59 months of age;

To estimate the prevalence of maternal malnutrition among pregnant and

lactating women;

To assess the IYCF practices among children aged 0-23 months;

To assess morbidity and immunization coverage among children aged 6- 59

months

To assess access to food;

To examine the population’s access to, and use of, improved water, sanitation

and hygiene;

To examine the progress of establishment of feeding programs for treatment of

malnourished children

Hygiene (WASH) and Nutrition in Hangu and Kohat Districts, KP Province


4. METHODOLOGY

4.1 Study area

The survey was conducted in IDP affected 26 union councils5 of KohatDistrict of KP Province (annex 2).

4.2 Study period

The study was conducted from October 1 - 7, 2013. 4.3 Study design

The survey was a cross sectional study with two-stage cluster sampling using SMART methodology. Villages are considered as the smallest geographical unit (clusters).

4.4 Study population

4.4.1 Children 6 – 59 months old: Anthropometric measurements and oedema was

measured from children 6-59 months old (65 – 110 cm long/tall when age is not

known) in the sampled household in all selected villages.

4.4.2 Mothers of children under two years of age: To estimate the infant and young

child feeding practice relevant information was gathered from mothers of

children who are under two years of age in all selected villages.PLW MUAC

measurement was taken to estimate the malnutrition prevalence of PLW

4.4.3 Households: Household (HH) food security and WASH information was

collected from subsamples of selected households in all selected villages. This

will be supplemented by village level focus group discussion with key informants.

4.5 Sample size

4.5.1 Sample size for nutritional status

ENA for SMART software delta version (June 27th, 2013 version) was used for sample size calculation. Sample sizes for nutritional status have been calculated as described below.

Estimated Global Acute Malnutrition (GAM): standard nutrition survey has not

been conducted recently in the districts to estimate the prevalence of

malnutrition. The 2011 national nutrition survey estimated GAM prevalence of

17.9% in the province (KP)6. The recent survey conducted in the area was in

20127. GAM levels were estimated between 10-13% in this survey. GAM estimate

of 12% was taken to estimate the sample size.

Precision: A precision of 4% was used. This level of precision is enough to give

accurate information to meet the objective of the survey.

5IDP affected union councils are those councils which have at least ten IDP households (as agreed in the cluster meeting) as per the IVEP 2011 assessment report 6National nutrition survey, Pakistan, 2011 7AUSAID supported nutrition survey report , 2012


Design effect: The population in KP province is heterogeneous with host and

IDPs. Among the IDP some of them arrived the period they have arrived varies

greatly8. Nutritional status is considered to have variations within the districts.

A design effect of 1.5 was used to plan this survey.

Table 2: Sample size calculation for nutrition status using ENA for SMART software (June 27th, 2013 version)

GAM

9

Pre

cis

ion

Desi

gn

eff

ect1

0

Sam

ple

si

ze

Childre

n

U5

Popula

tion

(%)1

1

Av.

HH

siz

e

Conti

ngency

Sam

ple

size H

H

Clu

sters

(15hh/

clu

ster)

12 4 1.5 414 12.5 7.5 3% 506 34

4.5.2 Food Security, WASH and IYCF data collection methodology

The survey assessed the potential underlying factors causing malnutrition, mainly FSL, WASH and IYCF situations. For this reason, the survey collected food security, WASH and IYCF information from all households included for the anthropometry component.

Additionally, three focus group discussions were conducted to better understand the infant and young child feeding practice of children with 8–12 key informants.

4.6 Procedures (recommended in KP province context)

The following steps were taken in field work:

a) Inception meetings conducted with District administration, DOH & key

stakeholders. The objective and timing of the survey were also discussed and

agreed during those meetings.

b) Support was requested from community leaders in the selected clusters.

c) Local events calendar was finalized with community leaders.

d) Team leaders and enumerators were informed about routes, number of HHs,

number of children <5, addresses & other relevant information’s by ACF nutrition

supervisors and local EPI teams

e) One cluster/team/day was surveyed to avoid fatigue and team work overload

f) Every morning the team leaders calibrated their uni-scales and height

measurement.

g) In each village before the team starts assessment of the community, consentwas

asked from gate keepers of the village.

h) Three lady enumerators enter into the village with a local guide and conduct all

the interviews and measurements while one male enumerator stays at the

"Hugira" (guest reception).

i) The enumerators selected 15 HHs from thevillage by simple random sampling

method.

8Humanitarian operation plan 2013 9As per agreement with UNICEF nutrition experts 10As per the agreement with UNICEF nutrition experts 11 UNICEF's data base


j) Children with acute malnutrition were referred to the nearest CMAM centre.

k) Data was entered in to ENA for SMART and Epi info on daily basis & every morning

feedback was given to each team before departure to the next day data

collection.

4.7 Data collection methods

Age: Children’s age was recorded in months using a local events calendar.

Height/Length- Lengths was taken for children below two years of age (below

85 cm12 when age is not known). They were measured lying horizontally on the

length measuring board. Height was taken for children two years and above (or

85 cm and above when age is not known). Their height was taken while

standing. Height and length was measured using standard 130 cm long

height/length board.

Before taking the height/length, subjects were requested to take off their shoes (if wearing them) and stand in a position against the height board, which has been placed on a flat level surface. Trained data collectors took height measurements, with acceptable accuracy and precision. Height was recorded to the nearest 0.1cm.

Weight was measured by using a calibrated Uni-scale and recorded to the

nearest 0.1Kg.

Nutritional Oedema was diagnosed by applying a normal thumb pressure to the

top of the foot for three seconds. If there is oedema, an impression remains for

some time (at least a few seconds) where the oedema fluid has been pressed

out of the tissue. Any suspected oedema case were reported and rechecked by

supervisors.

MUAC (Mid Upper Arm Circumference) will be measured using a three colour

coded (red, yellow, green) flexible, non-elastic 26.5cm long tape, graduated

with 1 mm precision. MUAC will be measured at the mid-point of the left upper

arm of all children 6-59 months old and PLW. The reading of the measurement

will be recorded to the nearest 1mm.

4.8 Organization of the survey

4.8.1 Meeting with the Province and District authorities

Before the survey was conducted relevant Provincial and District sector offices were briefed about the background, purpose, objectives and methods for the survey and their cooperation secured. The authorities were requested to officially inform the communities (villages) where the assessment took place. Relevant sectors were invited to supervise the training and data collection and recruit additional data collectors needed.

4.8.2 Data Quality

Each questionnaire and data sheet was checked each night prior to the data entry. The

12www.SMARTmethodology.com


data was entered on daily basis and missing or flag data identified. Based on the results supervisors gave feedback to enumerators every morning. On the last day of the survey the anthropometric data was of an excellent quality (Annex 1: plausibility report).

4.8.3 Ethical Considerations

All relevant Provincial and District stakeholders were informed of the study objectives, methods and their roles and their permission sought. Verbal consent was sought from gate keepers of each village and care takers of the children and household heads for voluntary participation in the survey.

The identities of the participants were kept anonymous. Those who do not wish to participate in the survey were respected for their self-determination / decisions.

4.8.4 Data Entry and analysis

The anthropometric data entry and analysis was done using ENA for SMART software (September 1st, 2013). EPI info 3.5.3 was used for entry and analysis of IYCF, FSL and WASH component. ENA for SMART program data analysis was automatic and a results summary is generated instantly.

4.8.5 Preliminary result and final report

An executive summary was shared two weeks after the data collection and this is the final report.

5. RESULTS

Percentage of values flagged with SMART flags: WHZ: 1.1 %,

Table 3 shows the distribution of children sampled in the survey.

Table 3: Distribution of age and sex of sample

Boys Girls Total Ratio

AGE (mo) no. % no. % no. % Boy: girl

6-17 91 52.3 83 47.7 174 26.9 1.1

18-29 69 47.3 77 52.7 146 22.5 0.9

30-41 81 49.7 82 50.3 163 25.2 1.0

42-53 69 59.0 48 41.0 117 18.1 1.4

54-59 26 54.2 22 45.8 48 7.4 1.2

Total 336 51.9 312 48.1 648 100.0 1.1

The age groups 54-59 were slightly under represented and the remaining age groups were well represented as compared to the normal age distribution advised by WHO (2000)13. The main reason behind this under representation is older age children in some households were in school during the time of the survey.

The overall sex ratio was 1.08 (with a p value of 0.346) which is within the acceptable range (0.9 - 1.1). In this survey boys and girls were equally represented. 1. Anthropometry results (based on WHO 2006 reference)

13WHO reference population


Using the WHO 2006 reference standards and WFH z-scores, the prevalence of GAM in Kohat District was 8.0 %( 6.1- 10.3, 95% CI) and SAM was 1.3 %( 0.7- 2.3, 95% CI). Boys are more affected than girls.

Table 4: Summary of prevalence of acute malnutrition by Z-score (N=640)14

All n = 640

Boys n = 332

Girls n = 308

Prevalence of global acute malnutrition (<-2 z-score and/or oedema)

(51) 8.0 % (6.1 - 10.3 )

(29) 8.7 % (6.2 - 12.2 )

(22) 7.1 % (4.8 - 10.6

)

Prevalence of moderate acute malnutrition (<-2 z-score and >=-3 z-score, no oedema)

(43) 6.7 % (5.0 - 8.9 )

(25) 7.5 % (5.3 - 10.6 )

(18) 5.8 % (3.6 - 9.3 )

Prevalence of severe acute malnutrition (<-3 z-score and/or oedema)

(8) 1.3 % (0.7 - 2.3)

(4) 1.2 % (0.5 - 3.2)

(4) 1.3 % (0.5 - 3.4)

*The prevalence of oedema was 0.0%.

With regards to prevalence of malnutrition in different age groups, younger (6-17 months) and older children (54-59 months) are more affected than any other age groups, the prevalence of GAM being 9.5 % and 8.3% respectively.(table 5)

Table 5: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting (<-3 z-score)

Moderate wasting (>= -3 and <-2 z-score )

Normal (> = -2 z score)

Oedema

Age (mo)

Total no.

No. % No. % No. % No.

%

6-17 168 0 0.0 16 9.5 152 90.5 0 0.0

18-29 145 1 0.7 10 6.9 134 92.4 0 0.0

30-41 163 5 3.1 6 3.7 152 93.3 0 0.0

42-53 116 1 0.9 7 6.0 108 93.1 0 0.0

54-59 48 1 2.1 4 8.3 43 89.6 0 0.0

Total 640 8 1.3 43 6.7 589 92.0 0 0.0

Based on MUAC international cut – off (Table 5), GAM was 2.8% (1.6- 4.6, 95% CI)and SAM 0.3% (0.0- 2.3, 95% CI). These GAM and SAM prevalence calculated by MUAC international cut off are much lower than the prevalence obtained by z scores (GAM 8.0% and SAM 1.3%).

Table 6: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex

15

All n = 648

Boys n = 336

Girls n = 312

Prevalence of global malnutrition (< 125 mm and/or oedema)

(18) 2.8 % (1.6 - 4.6 )

(5) 1.5 % (0.6 - 3.5 )

(13) 4.2 % (2.4 - 7.2 )

Prevalence of moderate malnutrition (< 125 mm and >= 115 mm, no

(16) 2.5 % (1.5 - 4.0 )

(4) 1.2 % (0.4 - 3.1 )

(12) 3.8 % (2.2 - 6.6 )

14figures indicated in brackets are 95% confidence interval (CI) 15

The figures in bracket indicates 95% CI


oedema)

Prevalence of severe malnutrition (< 115 mm and/or oedema)

(2) 0.3 % (0.0 - 2.3 )

(1) 0.3 % (0.0 - 2.2 )

(1) 0.3 % (0.0 - 2.4 )

The younger age groups were more affected than any other age groups with a prevalence of MAM 5.7% in children 6-17 months of age and 2.1% in 18-29 months (Table 6).

Table 7: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema

Severe wasting

(< 115 mm)

Moderate wasting

(>= 115 mm and < 125

mm)

Normal (> = 125 mm )

Oedema

Age (mo)

Total no.

No % No % No. % No %

6-17 174 1 0.6 10 5.7 163 93.7 0 0.0

18-29 146 1 0.7 3 2.1 142 97.3 0 0.0

30-41 163 0 0.0 3 1.8 160 98.2 0 0.0

42-53 117 0 0.0 0 0.0 117 100.0 0 0.0

54-59 48 0 0.0 0 0.0 48 100.0 0 0.0

Total 648 2 0.3 16 2.5 630 97.2 0 0.0

When using Weight for Height Median, children (4.5% of the total population under five) moderately malnourished (Table 7).

Table 8: Prevalence of acute malnutrition based on the percentage of the median and/or

oedema16

n = 643

Prevalence of global acute malnutrition (<80% and/or oedema)

(29) 4.5 % (3.2 - 6.3 )

Prevalence of moderate acute malnutrition (<80% and >= 70%, no oedema)

(29) 4.5 % (3.2 - 6.3 )

Prevalence of severe acute malnutrition (<70% and/or oedema)

(0) 0.0 % (0.0 - 0.0 )

The prevalence of underweight in the surveyed community was 18.2% (15.6 - 21.0 95% C.I.). Boys were affected more than girls, with a prevalence of 20.4% and 15.8% respectively.

Table 9: Prevalence of underweight based on weight-for-age z-scores by sex

17

All n = 644

Boys n = 333

Girls n = 311

Prevalence of underweight (<-2 z-score)

(117) 18.2 % (15.6 - 21.0 )

(68) 20.4 % (16.7 - 24.7 )

(49) 15.8 % (12.1 - 20.2

)

Prevalence of moderate underweight (<-2 z-score and >=-3 z-score)

(89) 13.8 % (11.7 - 16.3 )

(53) 15.9 % (12.2 - 20.5 )

(36) 11.6 % (8.6 - 15.4 )

Prevalence of severe underweight (<-3 z-score)

(28) 4.3 % (2.8 - 6.8 )

(15) 4.5 % (2.6 - 7.6 )

(13) 4.2 % (2.2 - 7.8 )

16The figures indicated in brackets are 95% CI. 17The figures indicated in brackets are 95% CI


Nearly one third (28.9%) of children were affected by stunting, which is lower than the national average (43.7%)18 . Table 10: Prevalence of stunting based on height-for-age z-scores and by sex

19

All n = 630

Boys n = 325

Girls n = 305

Prevalence of stunting (<-2 z-score)

(182) 28.9 % (24.7 - 33.4 )

(99) 30.5 % (25.4 - 36.1 )

(83) 27.2 % (21.7 - 33.5 )

Prevalence of moderate stunting (<-2 z-score and >=-3 z-score)

(127) 20.2 % (17.0 - 23.7 )

(66) 20.3 % (16.3 - 25.0 )

(61) 20.0 % (15.4 - 25.6 )

Prevalence of severe stunting (<-3 z-score)

(55) 8.7 % (6.0 - 12.5 )

(33) 10.2 % (6.9 - 14.7 )

(22) 7.2 % (4.2 - 12.2 )

2. Child Morbidity

The survey found that among children aged 6-59 months, 43.7% reportedly suffered from some types of illness during the previous 2 week period (table 11).

Table 11: Point Prevalence of child morbidity in children 6-59 months in the two weeks prior to the survey (n=648)

6-59 months No. of cases from sample %

Prevalence of reported illness 648 43.7

Of all children that had been sick, the most common sickness reported was fever 37.8% (n=107), followed by diarrhoea, 27.2% (n=77) and Acute Respiratory Infection (ARI) 22.6% (n=64, Table 12).

Table 12: Percentage distribution of children 6-59 months by illness in the 2 weeks prior to the survey

Illness/symptom No of cases % from the total sample (n=648)

% among sick children (n=283)

Fever Diarrhoea ARI Other

107 77 64 35

17.2 11.4 10.3 5.6

37.8 27.2 22.6 12.4

Total 283 43.7 100

3. Vaccination and Vitamin A Supplementation

Based on vaccination card records, measles vaccination for children aged 9-59 months was only 39.7%. However including recall, this increased to 74.3%. BCG vaccination coverage as observed by a scar was higher compared to other vaccination coverage, which is 75.5%. However, the vaccination coverage is lower than the national target (>90%). The proportion of all children aged 6-59 months who had received vitamin A in the last 6 months was 70.5% (Table 13).

Table 13: BCG and measles vaccination and Vitamin A supplementation coverage

20

18NNS Pakistan, 2011 19Figures in brackets are 95% confidence intervals (C.I.) 20

Figures in bracket are 95% CI

Vaccination / Supplementation Type (No) % (95% C.I.)


4. Maternal nutrition Maternal malnutrition was assessed using MUAC. A total of 229 pregnant and lactating women (PLW) were measured. Around two percent (2.2%, n=5 PLW) of these mothers were malnourished (with a MUAC less than 210mm). 5. IYCF The results of the survey indicate that most of the IYCF indicators are below the national average.

Proportion of children 0 to 23 months who were put to the breast within one hour

of birth was 55.0%. Whereas 77.9% of children were put in to their mothers breast

within 12 hours of being born.

Breastfeeding is nearly universal; almost all (99.6%) children 0-23 months are

breast fed at some point in their development.

Three quarter (76.3%) of them were still being breast fed at the time of the

survey.

Complementary foods are introduced in a timely fashion for nearly half of the children of children (56.1%). This indicates children aged 6 to 9 months are given complementary feeding as per WHO recommendation. Only 3% of children are fed with the recommended four or more food groups the day preceding the survey. 6. Food consumption and WASH 500households were included in the survey, 94% of them are residents of the district whereas 6% of them are IDPs (n=29). Among the IDPs nearly half of them (48.2%) arrived at the district from 2012 to 2013 and 31% of them before 2009. On food consumption, more than 90% of households reported to have eaten three or more meals the day prior the survey. The most common food type consumed during the week before the survey was cereals, oil and milk. There was no significant difference with regards to food consumed and number of food consumed between residents of the district and IDPs (p=0.067). The result shows that 90.6% of the households get water from improved sources21 (piped water, protected spring, protected dug well). The main sources of water are public tabs/boreholes with hand pumps. Ninety two percent of households have soap available at household level. However, of the households who have soap, only 89% of households have used it recently. Sanitary latrine coverage in the district is nearly 94%. Table 14: Households water source, child excreta disposal and toilet availability

n %

21The survey did not examine the quality of water and cannot determine, if there is likelihood of contamination

Measles by card (9-59 months) (n=608) (241) 39.7% (35.8 –43.7)

Measles by card and recall (9-59 months) (n=637) (454) 74.3% (71.0 – 78.0)

BCG scar (6-59 months) (n=648) (491) 75.5% (72.2 – 79.0)

Vitamin A in last 6 months (6-59 months) (n=648) (457) 70.5% (66.8 – 74.0)


Source of drinking water (N=500)

Public tap/hand pump 211 42.2

Protected dug well 123 24.6

Piped water 119 23.8

Unprotected dug well 28 5.6

Surface water 17 3.4

Other 2 0.4

Child excreta disposal (N=500 )

Connected to open drainage 253 50.6

Other 123 24.6

Left open 104 20.8

Buried 20 4.0

Toilet/latrine facility (N=500)

Flush toilet 247 49.4

Pit latrine 219 43.8

No facility/bush/field 30 6.0

Other 4 0.8

6. CONCLUSIONS

The prevalence of global acute malnutrition (GAM) among the surveyed

population using weight for height z-score was estimated at 8.0% (6.1- 10.3 95%

CI) and the prevalence of severe acute malnutrition (SAM) was 1.3% ( 0.7- 2.3

95% CI).Therefore, with this level of GAM and SAM in the presence of aggravating

factors (indicated below, e.g. high under five morbidity) the situation of the

district is considered as "ALERT", according to the WHO 2006 standards.

Prevalence of GAM using WHZ was 8.0% whereas using MUAC cut off point was

2.8%. This might be because weight for height criteria is not used/rarely used to

admit children to acute malnutrition treatment programs.

The occurrence of illnesses in children was 43.7% with fever being the major

illness (37.8%) followed by diarrhoea (27.2%).

This survey found relatively good BCG, Measles and Vitamin A vaccination

coverage which reflects the effort made by routine immunization service.

However, the vaccination coverage is lower compared with the national target

(>90%).In addition measles vaccination coverage verified by card was estimated

at 39.7% which is low which indicates low immunization card retention.

The IYCF practices among mother of children under two years of age was found to

be suboptimal

The information on WASH & FSL was not comprehensive to allow for major

conclusions.


7. RECOMMENDATIONS

There is a need to strengthen the Community based Management of Acute

Malnutrition (CMAM) in the district. A regular community outreach activity will

help in capturing children early.

The food security situation of the district needs close monitoring and follow up in

the coming months

Admission criteria in CMAM program need a high attention at this point. GAM

prevalence based on MUAC was found significantly lower than prevalence of GAM

based on WHZ. The CMAM program may need to use both MUAC and WHZ criteria

as admission rather than using MUAC only.

The WASH indicators, i.e., high latrine coverage and high improved water

sources should not be taken as a conclusive finding since there was no test done

on the water. The high diarrheal rates reported among children warrants

further investigation of the problem (in-depth investigation of the problem

including water testing).

IEC/BCC materials which address IYCF practices should be developed or adapted

and used to create awareness about appropriate breast feeding and

complementary feeding practice.

The District Health Office should further improve the routine vaccination

coverage, measles, BCG vaccination and card retention.

Immediate and collaborative effort by the district health office is required in

order to tackle the current wide spread febrile and diarrhoeal diseases in the

community.


8. ANNEXES

Annex 1: Plausibility check summary

Criteria Score Interpretation

Missing/ flagged data 0 (1.1%) Excellent

Overall sex ration 0 (p=0.346) Excellent

Overall age distribution 4 (p=0.002) Acceptable

Digit pref. score weight 0 (3) Excellent

Digit pref. score height 0 (5) Excellent

Digit pref. score height 0 (2) Excellent

Standard deviation whz 0 (1.06) Excellent

Skewnesswhz 0 (-0.03) Excellent

Kurtosis whz 0 (-0.09) Excellent

Poisson distribution whz 0 (p=0.76) Excellent

Overall score whz 4% Excellent

General Information

District:

Tehsil: Union Council:

Name of Village/Block: Cluster Number:

Household Number: Date of interview

Name of Interviewer: Signature:


Annex 2: Survey tools

Anthropometry Format,September 2013

1 2 3 4 5 6 7 8 9 10 11 12 13

CH ID

HHID

Child Full

Name

Sex

(M/F)

Date of

Birth (Date/Month/Year)

Age in Month

s

Weig

ht (kg)

Height(cm)

Oedema

(Y/N)

MUAC(mm)

BCG scar (Y/N)

Measles Vaccination (9-59 months) 0=Not vac 1=on card 2=Recall

VIT A in the last 6 months since March 13 (Y/N)

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

28

29

30

31

1 2 14 15 16 17 18 19 20

CH ID.

HH. ID.

Child registered? 0= No, 1= SFP, 2= OTP, 3= SC (Choose

Was the Child Ill during last 2

weeks?*

If child was ill last two weeks, Has the child

been taken to a health facility?**

N/A= not ill

Mother MUAC (mm)

Is the Mother Pregnant or Lactating?*** P=Pregnant, L=Lactating, No= Not P,

Is the Mother

registered in SFP?

0 = Not reg. 1=

Remarks


one option) Not L, A= Absent

registered

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

* Case definition for sickness **Where was the child taken

for treatment? ***Definition of PLW

1. Not sick 2. Diarrhoea (3 loose stools per day) 3. ARI 4. Fever 5. Other (specify)

(You can choose more than one option)

1. Child not taken for treatment

2. General practitioner 3. Hospital 4. Traditional healer 5. Other (specify) (You can choose more than one option)

Pregnant and lactating woman. Pregnant = Pregnant in third trimester (≥ 6months pregnant/visible pregnancy). Lactating = Lactating with a baby <6months


FSL and WASH questionnaires

SECTION 1: HOUSEHOLD CIRCUMSTANCES (ONLY FOR THE HOUSEHOLD)

1.1 What is the status of the household?

1 Resident

2 IDP

3 Returnee

1.2 How many people live in this household?

1 Total │____│

2 Under five years│____│

1.3 What is the main source of livelihood/income in this household?

1. Farming/ own land 2. Farming/share cropping 3. Income support 4. Fishing 5. Livestock/ Poultry 6. Remittances 7. Services (Govt. or private employee) 8. Shopkeeper/ trader 9. Skilled wage labor 10. Unskilled wage labor 11. Humanitarian assistance 12. Trade 13. Others

1.4 Since when have you been displaced?

Since when have you returned?

___/____ (MM/YYYY) ___/____( MM/YYYY)

1.5 What type of material is your house made of? (Major portion)

1 Mud/mud brick/

2 Stone/concrete/brick

3 Thatch

4 Plastic shelter

5 Other (specify)


SECTION 2 COPING MECHANISMS

2.1 Yesterday, how many meals were eaten in this household ( adults and children >2 years old)

2.2 Is this number different from usual?

1= Less,

2= Same, 3=More

2.3 On how many days was the food item eaten in previous 7 days?

(Choose one Option)

What was the main source of the food in the past 7 days?

(Choose one Option

2.3

a

0= Zero, 1=one day 2= 2 days 3= 3 day 4= 4 days 5= 5 days

6= 6 days 7= 7 days

1= Own crop/garden, production, 2= Market/shop purchase, 3= Work for food, 4= Borrowing/debts, 5= Gifts from neighbours/relatives,

6 = Food aid,

B Cereals (Wheat, bread, rice, maize

│____│ │____│

C Pulses (Dhal, beans, Lentils,peas, nuts

│____│ │____│

D Vegetables │____│ │____│

E Fruits │____│ │____│

F Meat, and poultry, eggs and fish

│____│ │____│

I Milk, cheese, yogurt │____│ │____│

J Sugar, honey │____│ │____│

K Oil, ghee, butter │____│ │____│

L Root and tubers │____│ │____│

2.4

During the PAST MONTH, had there been times when you had problems to fulfil the household’s basic needs?

Codes: 1. Yes, 2. No

(If ‘No’, go to Q3.1.)

│____│

2.5

During the PAST MONTH, has anyone in your household done the following:

Fill in frequency of coping strategy

Codes: 1. Every day, 2.1-2 days/week, 3. More than 3 days/week, 4. 1-2 times a month, 5. Hardly ever, 6. Not used

a. Skipped meals │____│ b. Skipped meals for entire day │____│

c. Relied on less preferred and less expensive food

│____│ d. Limited portion size at meals │____│

e.

Restricted consumption by adults in order for small children to eat

│____│ f. Consumed seed stocks held for the next season

│____│


g. Sold domestic assets (radio, furniture, fridge, TV, carpet…)

│____│ h. Sold productive assets (farm implements, sewing machine, motorbike, land, trees, livestock etc.

│____│

I. Removed children from school

│____│ J. Sought alternative or additional jobs │____│

SECTION 3 : Water and Sanitation Facilities

3.1 What is the main source of drinking water for their household

1 Piped water – piped into dwelling

2 public tap stand

3 Hand pump

4 Tube well / turbine

5 Covered (protected) well

6 Uncovered (unprotected) well

7 Protected spring

8 Unprotected spring

9 Surface water (river, canal, stream, pond, irrigation channel)

10 Buy water from vendor: truck/tanker/cart

3.2 What kind of toilet facility does your HH use?

1 Flush / Pour flush toilet

2 Pit Latrine 3 No facilities, bush or field 4 Other (specify)

3.3 How are child excreta disposed?

1 Left open

2 Buried

3 Sewer connected

4 Other (specify)

3.4 Soap available at household for hand washing

0 No (If no go to 4.1)

1 Yes

3.5 If Yes, Can you please show us the soap which you are using? (it is an observation question to see their hand washing practices).

0 No

1 Yes (Please check the condition of the soap)


Section 4: Breast / Complementary Feeding Practices of the Youngest Child (0 – 23 months of age) ask for the youngest child. Childs name: Childs age (in Months):

S. No.

Questions Responses and Codes

4.1 Have you ever breastfed your child? If No, go to Q 5.6

No 0

yes 1

Don’t know 8

4.2 After delivery when did you first put the child to the breast?

Immediately after birth (within 1hour)

1

Hours

Days

Don’t know 8

4.3 At what age the child was given liquids (water, tea etc.) other than breast milk?

Days

Months

Don’t know 8

4.4 Is the child still being breastfed? No 0

yes 1

4.5 How old was the child when other milk was introduced?

Days

Months

Don’t know 8

4.6 At what age the child was given first semisolid / solid food? (If not given yet, go to next section)

Months

Not yet given 1

Don’t know 8

4.7 Since yesterday morning, did the child receive any of the following?

A Breast milk No 0

yes 1

Don’t know 8

B Vitamin, mineral supplements or medicine

No 0

yes 1

Don’t know 8

C Plain water No 0

yes 1

Don’t know 8

D Sweetened, flavoured water or fruit juice or tea or infusion

No 0

yes 1

Don’t know 8

E Oral Rehydration Solution (ORS)

No 0

yes 1

Don’t know 8

F Infant formula No 0

yes 1

8

G Tinned, powdered or fresh animal milk

No 0

yes 1

Don’t know 8

H Any other liquids No 0

yes 1

Don’t know 8

I Solid or semi-solid or soft food? If No, or Don’t know , go to Section 3

No 0

yes 1

Don’t know 8

4.8 Since yesterday morning, how many times did the Number of Times


child eat solid, semisolid, or soft foods other than liquids?

Don’t know 8

4.9 Could you please tell which of the following foods you have fed to your youngest child in the last 24 hours? (Encircle the items eaten)

Cereals (roti, nan, bread, wheat, rice, maize)

A Vitamin A rich vegetables and fruits (yellow)

G

Legumes (dhal, beans, groundnut) B Other fruits and Vegetables H

Meat/chicken C Milk, yoghurt, cheese, etc I

Fish/sea food D Sugar in tea J

Egg E Including leaves K

Cooking oil/fats/butter F

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