Nutritional Assessment on Flood-Affected Populations Kamber-Shahdadkot and Dadu Districts, Sindh Province

FINAL REPORT

Nutritional Assessment on Flood-Affected Populations Kamber-Shahdadkot and Dadu Districts, Sindh Province,

Pakistan

November 2007

Anna Bosch i Masgrau Nutritionist Action Against Hunger (ACF-USA) Table of contents

Acknowledgments 3 List of acronyms 4 Executive summary 5 1. Introduction 9 1.1 Floods and massive population displacement 10 1.2 Health 10 1.3 Food security 11 1.4 Water and Sanitation 12 1.5 Nutrition 12 1.6 Aid response 13 1.7 Programs initiated by ACF in floods affected areas 13 2. Objectives of the survey 14 3. Methodology 14 3.1 Population Data 14 3.2 Sample size and cluster selection 15 3.3 Households and children selection 15 3.4 Data collection and measurement techniques 16 3.4.1 Anthropometric data 16 3.4.2 Household and Mortality Data 17 3.5 Indicators and Formulas used 17 3.5.1 Acute Malnutrition 17 3.5.2 Mortality 18 3.5.3 Measles Vaccination Coverage 18 3.6 Training and supervision 19 3.7 Data analysis 19 4. Results 19 4.1 Kamber-Shahdadkot survey 19 4.1.1 Anthropometric results 19 4.1.2 Mortality 22 4.1.3 Immunization coverage 22 4.2 Dadu survey 23 4.2.1 Anthropometric results 23 4.2.2 Mortality 26 4.2.3 Vaccination Results 26 5. Discussion 26 6. Recommendations 27 Appendixes 28

2/32 Acknowledgments

Action Against Hunger thanks the Health Executive District Officer of Dadu and Kamber-Shahdadkot, as well as the Nazims of the Union Councils surveyed, for their assistance and collaboration.

Action Against Hunger would like to thank Action Aid, HOPE, as well as the local NGO Pirbhat Women Development Society, NDS and YST for their assistance in conducting the survey and gathering information.

Action Against Hunger is also extremely grateful to the community members for their cooperation and hospitality.

Final thanks go to Thamina Laghari and Sajjad Hussain and the whole Nutrition Team, as well as all the members of Action Against Hunger’s Larkana base, especially to Faisal.

3/32 List of acronyms

ACF Action Contre la Faim / Action Against Hunger ARI Acute respiratory infection BCG Bacillus Calmette-Guérin, a vaccine for tuberculosis BHC Basic Health Centers CI Confidence interval CDR Crude death rate CTC Community-based therapeutic care DHQ District Head Quarter Hospitals DTP Diphtheria, Tetanus, and Pertussis EDO Executive District Officer GAM Global acute malnutrition GD Government Dispensaries HepA Hepatitis A HepB Hepatitis B IDP Internally displaced person Kcal Kilocalories LHW Lady Health worker MHC Mother and Child Health MoH Minister of Health MUAC Mid upper arm circumference NDS NGO Development Society NCHS National Centre of Health Statistics NGO Non governmental organization OPD Out door patient department OTP Outpatient Therapeutic Programme PKR Pakistani rupees Pol Poliomyelitis RHC Rural Health Centre RUTF Ready-to-use therapeutic food SAM Severe acute malnutrition SC Stabilization centre SD Standard deviation SFP Supplementary Feeding Programme SMART Standardized Monitoring and Assessment of Relief and Transitions TFC Therapeutic feeding center THQ Taluka Headquarters Hospital UC Union Council YST Young Samaji Tanzeem

4/32 Executive summary

Context

The Sindh is one of the four provinces of Pakistan, located on the Southeastern corner of the country. Its capital is Karachi. The Sindh is bounded by the Thar Desert to the East, the Kirthar Mountains to the West, and the Arabian Sea in the South. Its center is crossed by the Indus River, around which the soil is fertile. It is the third largest Province of Pakistan, stretching about 579 km from north to south, and 442 km (extreme) or 281 km (average) from east to west, with a total acreage of 140,915 km².The province is subdivided into 23 districts, further subdivided into numerous Talukas and local governments. The total population of the Province is estimated between 50 to 54 millions inhabitants (1.1 million in Kamber-Shahdadkot and 1.7 million on Dadu)1. According to Pakistan Demographics 2003, 48.7% of the population lives in urban context. The Sindh Province is a major centre of economic activity in Pakistan and has a highly diversified economy, ranging from heavy industry and finance centered in and around Karachi, to a substantial agricultural base along the Indus. The main crops are cotton, rice, wheat, sugar cane, bananas, and mangoes. Land ownership is very uneven in the area: most of the land is owned by a small number of important landlords.

Floods

In 2007, heavy monsoon rains coupled with the landfall of Cyclone Yemyin on 26th June led to extensive flooding in Northern Sindh. Although the cyclone-associated rainfalls affected first the Balochistan Province, they drained then through the Indus River, and ultimately the Arabian Sea. Kamber-Shahdadkot and Dadu Districts were the most acutely affected. Because the floods were the result of breaches on the FPB rather than direct flows, water levels rose relatively slowly in the two districts, and the local population had time to escape from their villages and seek shelter on higher ground (frequently along elevated roadways) or in nearby towns. More than 100,0002 people were displaced by the floods in Kamber-Shahdadkot and Dadu or stranded in villages built on the tops of hills and completely surrounded by water.

Rationale of the surveys

The nutrition situation of the affected population was not documented. The only data available come from a countrywide nutrition survey, the MICS, implemented by UNICEF in 2001-2002, and targeting children from 0 to 59 months.The results for global acute malnutrition rates were 38% weight-for-age, 36.8% height-for-age and 13.1% weight-for-height in Z-score analysis (reference NCHS).

Nevertheless, it can be expected that the nutritional status of the target population has deteriorated due to agriculture is the main resource of this people and the fields have been widely destroyed by the floods. Humanitarian assistance started one week after the floods by the Government, international and local NGO: food and tent distributions were implemented, water and sanitation programs and distribution of money. During the month of August, flood waters started to recede, allowing some of the displaced people to return home. Most of the aid stopped by September/October, at the end of the emergency phase. However, the flood crisis is not over: households will continue to face difficulties in the coming months, as their principal livelihood source – agriculture production– was destroyed during the floods.

Flood affected population of Kamber-Shahdadkot and Dadu districts were chosen for a joint nutritional and food security survey. The Food Security Assessment was conducted in September 2007 and the results show that the food security situation of flood-affected households is precarious at best and is expected to deteriorate further in the coming months.

1 Population as per census of 1998 2 Approximately 10% of the total population of Kamber-Shahdadkot and 20% of the total population of Dadu

5/32 This Nutrition Assessment is the second part of this project that will provide a better understanding of the current food security and nutrition situation of these areas in order to make recommendations about potential interventions.

Methodology

To ensure the validity of the results, after analysis of both districts, it was decided to conduct 2 nutrition surveys (one in each district), to ensure the principle of homogeneity in each of the areas surveyed. Indeed, the Food security assessment carried out in September revealed that Kamber-Shahdadkot is more vulnerable than Dadu3. For both surveys, a cluster sampling was chosen. The SMART protocol was applied in the training, planning, collection and analysis of both anthropometric and mortality data. 4 teams composed of 3 members each, completed the field work. There was a least a female surveyor in each team. They attended theoretical and practical training, from October 25th to 29th, 2007.

Kamber-Shahdadkot

The survey was conducted from October 31st to November 9th, 2007. 805 children between 6 and 59 months were measured. After cleaning, the data of 27 of them were discarded of the analysis. The following results are based on the data of 778 children. Table 1: Results summary, Kamber-Shahdadkot survey, November 2007 INDEX INDICATOR RESULTS4 Global Acute Malnutrition 16.7% W/H< -2 z and/or oedema (12.9% - 20.5%) Z- scores Severe Acute Malnutrition 2.2% W/H < -3 z and/or oedema (1.2% - 3.2%) NCHS Global Acute Malnutrition 9.5% W/H < 80% and/or oedema (6.9% - 12.2%) % Median Severe Acute Malnutrition 0.4% W/H < 70% and/or oedema (0.0% - 0.8%) Global Acute Malnutrition 18.7% W/H< -2 z and/or oedema (15.0% - 22.3%) Z-scores Severe Acute Malnutrition 4.1% W/H < -3 z and/or oedema (2.6% - 5.6%) WHO Global Acute Malnutrition 6.0% W/H < 80% and/or oedema (4.3% - 7.8%) % Median Severe Acute Malnutrition 0.3% W/H < 70% and/or oedema (0.0% - 0.6%) Total crude retrospective mortality (last 3 months) /10,000/day 0.37 (0.11-0.63) Under five crude retrospective mortality /10,000/day 1.27 (0.35-2.19) By card 2.0% Measles immunization coverage According to caretaker5 73.3% (children ≥ 9months old) Not immunized 16.1% Do not know 8.6%

3 “Villages in Dadu District tend to be built on higher ground, and fewer were completely destroyed by the floods. As a result, in most cases food stocks were saved and fewer livestock lost. In addition, income sources tend to be more diverse in Dadu District, with a higher percentage of households involved in handicrafts and casual labor. While a majority of households in both districts will not be able to plant in the next planting for 2007, more households will be able to plant in Dadu District (37%) than in Kamber-Shahdadkot District (28%). Finally, perhaps because they are more accessible from Karachi and Hyderabad, villages in Dadu District seem to have received more aid, particularly from local and national NGOs” in A Food Security Assessment of Flood-Affected Populations in Kamber-Shahdadkot and Dadu Districts, Sindh Province, Pakistan, ACF USA, 2007. 4 Results in bracket are at 95% confidence intervals. 5 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker

6/32 Dadu

The survey was conducted from November 20th to 27th, 2007. 822 children between 6 and 59 months were measured. After cleaning, the data of 32 of them were discarded of the analysis. The following results are based on the data of 790 children. Table 2: Results summary, Dadu survey, November 2007 INDEX INDICATOR RESULTS6 Global Acute Malnutrition 15.6% W/H< -2 z and/or oedema (12.8% - 18.3%) Z- scores Severe Acute Malnutrition 0.9% W/H < -3 z and/or oedema (0.1% - 1.7%) NCHS Global Acute Malnutrition 9.1% W/H < 80% and/or oedema (6.9% - 11.4%) % Median Severe Acute Malnutrition 0.3% W/H < 70% and/or oedema (0.0% - 0.8%) Global Acute Malnutrition 17.8% W/H< -2 z and/or oedema (14.8% - 20.9%) Z-scores Severe Acute Malnutrition 3.2% W/H < -3 z and/or oedema (1.9% - 4.5%) WHO Global Acute Malnutrition 5.2% W/H < 80% and/or oedema (3.5% - 6.9%) % Median Severe Acute Malnutrition 0.3% W/H < 70% and/or oedema (0.0% - 0.8%) Total crude retrospective mortality (last 3 months) /10,000/day 0.11 (0.00 – 0.22) Under five crude retrospective mortality /10,000/day 0.08 (0.00 – 0.23) By card 6.5% Measles immunization coverage According to caretaker7 76.1% (children ≥ 9months old) Not immunized 17.4% Do not know 0.0%

Discussion

The prevalence of Global Acute Malnutrition rates found in both surveys reveals an alarm situation, while the Severe Acute Malnutrition rates are very low. The results describe in both surveys a situation that is alarming, but not severe. This is confirmed by the retrospective mortality rates, that all are below the alert level. Higher rates are noted in the Kamber-Shahdadkot survey as compared with the Dadu survey, both for malnutrition and for mortality: nevertheless, the difference found is not significant, when considering confidence interval, and does not lead to a different interpretation.

Therefore, the malnutrition found in the flood affected areas of Kamber-Shahdadkot and Dadu can be described as of a high magnitude, as it affects a high percentage of the under-five, but of low intensity, as malnutrition cases are almost exclusively moderate.

The immunization status of the surveyed children cannot be known with certainty, as around 75% of them are supposed to be vaccinated, but have no card to prove it. Nevertheless, the high number of negative answers show that access to vaccination, and by extension to basic health care, is not sufficient.

6 Results in bracket are at 95% confidence intervals. 7 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker

7/32 inducing an unusually long hunger gap until the next harvests. As a result, families are decreasing their food consumption. Other sources of income, like casual labor and selling livestock, have not been enough to sustain food security8.

The evolution of the nutrition situation cannot be predicted from a nutrition survey; close monitoring of the direct causes of malnutrition, such a food, water and health access, are necessary.

Recommendations

The results presented in this report show that the nutrition situation of flood-affected population is of concern. The following recommendations are made for donors, agencies, and organizations interested in intervening in the recovery phase of the flood crisis:

Nutrition treatment and monitoring:

Continue the existing nutrition program, and extend the coverage of supplementary feeding activities, to prevent the deterioration of moderately malnourished children,

Set up a nutritional surveillance system with existing health and nutrition structures,

Involve the Ministry of Health for activities such as the detection, prevention and treatment of acute malnutrition being implemented routinely in public structures,

Coordination of the different actors working in health and nutrition, to monitor the nutrition situation.

Factors leading to malnutrition:

Improvement of the food security situation, according to the recommendations given in the Food Security Assessment report (ACF, September 2007)

Improvement of the clean water access

Improvement of the health access in general (rehabilitation of the structures damaged by the floods, number of medical staff in the structures, availability of drugs and vaccines)

8 A Food Security Assessment of Flood-Affected Populations in Kamber-Shahdadkot and Dadu Districts, Sindh Province, Pakistan, ACF USA, 2007

8/32 1. Introduction The Islamic Republic of Pakistan is a country in South Asia, marking the region where South Asia converges with Central Asia and the Middle East. It has a 1,046 km coastline along the Arabian Sea in the south, and is bordered by Afghanistan and Iran in the west, India in the east and China in the far northeast.

Statistics:

Total population: 157,935,000

Gross national income per capita (PPP international $): 2,350

Life expectancy at birth m/f (years): 61/62

Healthy life expectancy at birth m/f (years, 2002): 54/52

Probability of dying under five (per 1 000 live births): 100

Total expenditure on health per capita (Intl $, 2004): 48

Total expenditure on health as % of GDP (2004): 2.2

Percentage people living below 1 $ a day: 23%

Pakistan is a federation of four provinces, a capital territory and federally administered tribal areas. The Sindh is one of the four provinces of Pakistan, located on the Southeastern corner of the country. Its capital is Karachi. The Sindh is bounded by the Thar Desert to the East, the Kirthar Mountains to the West, and the Arabian Sea in the South. Its center is crossed by the Indus River, around which the soil is fertile. It is the third largest Province of Pakistan, stretching about 579 km from north to south, and 442 km (extreme) or 281 km (average) from east to west, with a total acreage of 140,915 km². The province is subdivided into 23 districts, further subdivided into numerous talukas and local governments.

The total population of the Province is estimated between 50 to 54 millions inhabitants. According to Pakistan Demographics 2003, 48.7% of the population lives in urban context. Sindh's population is predominantly Muslim, but Sindh is also home to nearly all of Pakistan's Hindus,

9/32 numbering roughly 1.8 million. Smaller groups of Christians, Parsis or Zoroastrians, Ahmadis, and a tiny Jewish community can also be found in the province.

The Sindh Province is a major centre of economic activity in Pakistan and has a highly diversified economy, ranging from heavy industry and finance centered in and around Karachi, to a substantial agricultural base along the Indus. The main crops are cotton, rice, wheat, sugar cane, bananas, and mangoes. Agriculture is clearly the most important source of income on Kamber-Shahdadkot and Dadu districts. Land ownership is very uneven in the area: most of the land is owned by a small number of important landlords. There are two main agricultural seasons each year: the kharif season, from June to November, is timed around the monsoon rains, which fall from mid-June to mid-August, and includes the cultivation of water-intensive crops like rice; and the rabi season, from October to April, during which are grown crops that require less water (wheat, barley, legumes, mustard/oil seed, and animal fodder).

1.1 Floods and massive population displacement

Flooding is a chronic issue in the Indus Valley. Minor flooding in the irrigated regions of Sindh occurs on an annual basis during the summer monsoon rains in July and August. Major floods induced by unusually heavy monsoon patterns occur roughly once a decade. The current system of barrages, bunds, canals, and drains was developed in the 1930’s under the British colonial administration, which expanded on a network built in the 18th century. People complain about the insufficient maintenance of these structures. The question is that this system is not sufficient to control important floods, and their devastating effects on areas around the Indus River. In 2007, heavy monsoon rains coupled with the landfall of Cyclone Yemyin on 26th June led to extensive flooding in Northern Sindh. Although the cyclone-associated rainfalls affected first the Balochistan Province, they drained then through the Indus River, and ultimately the Arabian Sea. Kamber-Shahdadkot and Dadu Districts were the most acutely affected. Because the floods were the result of breaches rather than direct flows, water levels rose relatively slowly in the two districts, and the local population had time to escape from their villages and seek shelter on higher ground (frequently along elevated roadways) or in nearby towns. More than 100,000 people were displaced by the floods in Kamber-Shahdadkot and Dadu or stranded in villages built on the tops of hills and completely surrounded by water. It is reported that approximately 10% of the total population9 of Kamber-Shahdadkot has been affected comprising 25% of the total district area10 and 20%11 of the total population of Dadu District12.

1.2 Health

In Pakistan attempts have been made to improve the health conditions of the people through availability of trained personnel, adequate supply of medicines and establishment of health services. Yet the health care system as a whole is not encouraging. The main health problems are preventable communicable diseases, malnutrition and high incident of birth resulting of high proportion of infant and maternal mortality. There are also clear differentials in health conditions by rural and urban areas and socio- economic groups. Malaria, tuberculosis and wide variety of childhood diseases such as diarrhea, measles and tetanus etc. still continue to pose potential threat to the health of millions of people in the country. Unsanitary condition, polluted water and illiteracy among rural mother, urban slum and high fertility, small budgetary allocation and inadequate administrative structure have been identified as the main hurdles in the progress of health conditions13.

9 The total population of Kamber-Shahdadkot District is 1.2 million persons, according to Pakistan Demographics 2003. 10 Source: WHO Pakistan floods Situation report 7 July. And Rapid Assessment Report Floods Pakistan ACF. 11 Source: Revenue Department Dadu 12 The total population of Dadu District is 1.7 million persons, Population as per census of 1998. 13 Source: Federal Bureau Statistics. Government Pakistan, 2007

10/32 Health structures in the Sindh Province Public and private health care systems are operating in the region. The public health care system operates on a four-tier system: Government Dispensaries (GD), Basic Health Centers (BHC), Rural Health Centers (RHC) and Mother and Child Health (MHC), Taluka Headquarters Hospitals (THQ) and District Headquarters Hospitals (DHQ). Within the public health system, there is a charge for a consultation (2 to 5 Pakistani Rupees14). There are also number of ‘health houses’ operated by lady health workers, providing primary health care, family planning, growth monitoring, immunizations and antenatal care. Table 3: List of Public Health facilities in Kamber-Shahdadkot and Dadu districts, before the floods

Health Facilities Kamber-Shahdadkot Dadu District Headquarters Hospitals 0 1 Taluka Headquarters Hospitals 4 3 Rural Health Centers 4 3 Basic Health Centers 27 44 Government Dispensaries 25 2415 Mother and Child Health centers 2 3 Total doctors 95 100 Total population 1.2 million 1.7 million

The facilities have been heavily affected by the floods, and some of them are still not functional, more than 3 months later. Increasing cases of ARI, diarrhea, malaria, skin diseases, eye infections, heat stroke, snake bites and viral infection have been reported during the floods. Immunization coverage In Dadu an immunization campaign (BCG, DTP, typhoid, HepA, Pol, measles and vit-A) has been done in the affected area after the floods. In Kamber-Shahdadkot an immunization campaign (BCG, tetanus and diphtheria and typhoid, HepB, Pol, measles and vit-A) has taken place during the month of July16.

1.3 Food security

This year’s floods arrived shortly after households had finished transplanting their rice crop from the nursery beds and sowing it in their main fields. Almost all the rice crop in flood-affected areas was destroyed. As a result of the loss of the rice crop, the annual hunger gap is expected to continue this year until the first post-flood harvest17. According to the ACF food security assessment (September 2007):

14 1 USD = 60 PKR 15 In Dadu District are Government Dispensaries and Experimental Dispensaries. Experimental Dispensaries are health centers that MoH has integrated from the local government on the Health Public system after 2001 (LGO 2001) when the Health System was transferred to the Districts. 16 This information was obtained from interviews at the EDOs of Health of both districts. Dadu coverage measles campaign: 103% (590,587 total vaccinated/572,934 total targeted). Kamber-Shahdadkot : 64,085 children vaccinated. 17 “The harvests of rice in November and wheat in April give households an increase in food and income that lasts them for 4-5 months, depending on the year. The most difficult times during the year are just before the harvests, when the food and income from the previous harvest has run out. Of these two periods, the one just before the rice harvest (August and September) is generally considered to be the more difficult. This is the “hunger gap,” or time during the year when people have the most difficulty getting food.” in A Food Security Assessment of Flood-Affected Populations in Kamber-Shahdadkot and Dadu Districts, Sindh Province, Pakistan, ACF USA, 2007

11/32 71% of households displaced by the floods are already back or plan to return to their villages by the end of October. In isolated areas, displacement will continue for several more months due to a lack of drainage possibilities for standing water.

89% of interviewed households ranked agriculture as their most important source of income. The rice crop was almost completely destroyed by the floods, which will prolong the annual “hunger gap” until the first post-floods harvest. Only 32% of households expect to plant for the upcoming wheat season, while the remainder will have to wait until next year’s rice harvest in October 2008.

70% of interviewed households report that they are consuming less food than a normal year. Daily food intake is estimated at 1350 kcal, or 64% of daily requirements.

Flood-affected households are currently relying on three main coping strategies: casual labor, the sale of livestock, and the taking of credit. These coping strategies are used in a normal year to bridge the “hunger gap” period but are unsustainable for periods of longer than six months.

The main needs identified by interviewed households include food, shelter, household items, and seeds/fertilizer. With limited cash available, households are having to choose between competing daily expenses and are unable to save up for the larger investments that are needed for them to fully recover.

1.4 Water and Sanitation

In the new system of local government (LGO 2001), provision of water and sanitation facilities is responsibility of the taluka administration. In small towns and cities, these facilities exist, and are more or less functional. In the rural areas and villages they are hardly found; shallow wells with hand pumps and water from irrigation channels are common sources of water for drinking purposes. Private water trucking and donkey carts are used by some water providers in cities and towns. In the rural areas, to fulfill the needs of water for drinking and domestic use purposes is mainly responsibility of women and young girls. Majority of rural population has to walk 200 meters to 2 km to the nearest water point. Due to the nature of soil aquifer, topographical features and salinity, the underground water is mostly brackish, except for a narrow stripe along irrigation channels and canals. In rural areas the vast majority of population does not have proper sanitation facilities. Common habit is to use open space or houses backyard for defecation.

During the monsoon and post monsoon seasons, flies and mosquitoes are very common in the country side. This situation contributes to various diseases. Water and sanitation infrastructures have been seriously damaged in the flood affected areas. Some water schemes operating in the countryside before the floods have been literally wiped away. Some wells have been plugged or the hand pump machine irreversibly damaged becoming useless. Some others are still flooded today.

1.5 Nutrition

The nutrition situation of the affected population was not documented. The only data available come from a countrywide nutrition survey, the MICS, implemented by UNICEF in 2001-2002, and targeting children from 0 to 59 months.The results for global acute malnutrition rates at country level were 38% weight-for- age, 36.8% height-for-age and 13.1% weight-for-height in Z-score analysis (reference NCHS).

Nevertheless, it is expected that the nutritional status of the flood affected population has deteriorated, and is of concern: indeed, the population could move with part of their food stocks but they are quickly depleting, the agriculture is the main resource of this people and the fields have been widely destroyed, compromising the production of the next harvests, and water filtration systems have been destroyed, limiting access to safe water, and increasing the risk of waterborne diseases.

12/32 In Dadu, a nutritional program conducted by UNICEF trough a local NGO called HOPE, has been initiated after the floods. The program counts several components: Detection of the cases, through screening by community or self-referral. SFP program for the cases of moderate acute malnutrition Outpatient Therapeutic Program for the cases of severe malnutrition with no medical complications Inpatient treatment in a Stabilization Centre (SC) for the cases of severe malnutrition presenting medical complications

In the period from August 28th to October 27th 2007, the program statistics are: Among 13,354 children screened: 6,596 children detected with moderate malnutrition and 575 children detected with severe malnutrition Admissions to TFC: 119 (56 sent by mobile units and 63 sent by THQ)

In Kamber-Shahdadkot a program has been implemented as from October 2007. Results are not yet available.

1.6 Aid response

Humanitarian assistance started one week after the floods: food and tent distributions were implemented by the Government and local NGOs. International NGOs focused on water and sanitation programs. On the other hand, the Government distributed checks worth 15.000 PKR to flood-affected households. However, the data collected during the Food security assessment carried out by ACF-USA show that less than half of the households actually received this support. During the month of August, flood waters started to recede, allowing some of the displaced people to return home. It has to be noticed that food aid was not provided to people who had staid in their village, or who had returned. Most of the aid stopped by September/October, at the end of the emergency phase. However, the flood crisis is not over: households will continue to face difficulties in the coming months, as their principal livelihood source – agriculture production– was destroyed during the floods. While most of the water has meanwhile receded, there are still wide areas remaining under water and not targeted by humanitarian relief operations.

1.7 Programs initiated by ACF in floods affected areas

ACF initiated a water/sanitation emergency response in the flood-affected areas of Kamber-Shahdadkot and Dadu Districts on July 17th. ACF partnered with two local NGOs to implement a project financed by UNICEF involving water trucking, latrines construction, shallow wells, hygiene promotion, distribution of hygiene kits and water purification tablets, and storage containers in selected settlements of internally displaced persons (IDPs) in both districts. It has finished on October 22nd. A second water/sanitation project involving water trucking, shallow wells, hygiene promotion and distribution of hygiene kits is running on Kamber-Shahdadkot until December 2007.

A Food Security Assessment was conducted in September 2007 and the results show that the food security situation of flood-affected households is precarious at best and is expected to deteriorate further in the coming months. This Nutrition Assessment is the second part of a project that will provide a better understanding of the current food security and nutrition situation of these areas in order to make recommendations about potential interventions.

13/32 2. Objectives of the survey

To assess the nutritional status of children aged 6 to 59 months in the floods affected area of Kamber-Shahdadkot and Dadu Districts. To assess the retrospective death rate among children less than 5 years of age, and the crude death rate of the total population living in the area covered by the surveys. To assess the measles immunization coverage among children ages 9–59 months

3. Methodology

These assessments target both populations of the Kamber-Shahdadkot and Dadu Districts, which represents around 200.000 people. To ensure the validity of the results, after analysis of both districts18, it was decided to conduct 2 nutrition surveys (one in each district), to ensure the principle of homogeneity in each of the areas surveyed.

For both surveys, a cluster sampling was chosen. The SMART protocol was applied in the training, planning, collection and analysis of both anthropometric and mortality data.

3.1 Population Data

In Pakistan, provinces are subdivided into districts, subdivided into numerous talukas which are further divided into Union Councils (UC). A Union Council consists of several villages.

In Kamber-Shahdadkot, 5 UC were selected for the survey. They were all part of the Food Security assessment, and were amongst the most affected by the floods.

In Dadu, 6 UC were selected for the survey. They were also covered by the Food Security assessment, were affected by the floods, and benefited from a nutrition program.

The list of villages and the number of population from the selected UC were obtained from the Government department, local Government and local NGOs. Villages under less than 100 people were merged with the closest ones.

Despite the population movement during the floods, more than 70%19 of displaced households had returned to their villages at the time of the surveys. Therefore, the official population figures were used for the calculation of the sampling size.

18 “Villages in Dadu District tend to be built on higher ground, and fewer were completely destroyed by the floods. As a result, in most cases food stocks were saved and fewer livestock lost. In addition, income sources tend to be more diverse in Dadu District, with a higher percentage of households involved in handicrafts and casual labor. While a majority of households in both districts will not be able to plant in the next planting for 2007, more households will be able to plant in Dadu District (37%) than in Kamber-Shahdadkot District (28%). Finally, perhaps because they are more accessible from Karachi and Hyderabad, villages in Dadu District seem to have received more aid, particularly from local and national NGOs” in A Food Security Assessment of Flood-Affected Populations in Kamber-Shahdadkot and Dadu Districts, Sindh Province, Pakistan, ACF USA, 2007. 19 A Food Security Assessment of Flood-Affected Populations in Kamber-Shahdadkot and Dadu Districts, Sindh Province, Pakistan, ACF USA, 2007

14/32 Table 4: Population estimates in selected Talukas and Union Councils

DISTRICT TALUKA UC Population Warah Mirpur 12,230 Qubo Saeed Bago Dero 11,185 Khan Hazar Wah 11,346 KAMBER- Miro khan Khaber 14,820 SHAHDADKOT Qamber Ghaibi Dero 49,982 TOTAL 99,563 Children < 5years old (17%) 16,926 Khan Jo Goth 12,750 Mehar Fareedabad 17,910 Gozo 28,000 K.N. Shah Chhor Qamber 13,050 DADU Sawro 9,915 Johi Kamal Khan 9,100 TOTAL 90,725 Children < 5years old (17%) 15,423

3.2 Sample size and cluster selection

Kamber-Shahdadkot: An expected prevalence of 10% was used for the sample calculation. A precision of 3 and a design effect of 2 were chosen. After calculation with ENA (SMART associated software), the required sample size would be 751 children.

Dadu: The second survey was done after the results of the first one were released. Therefore, the results obtained were used to fine-tune the results expected in Dadu. A prevalence of 20% was used for the sample calculation. A precision of 4 and design effect of 2 were chosen. After calculation, the required sample size would be 750 children.

For both survey, the number of children to be assessed daily was 25. 30 clusters of 25 children had then to be assessed to provide the desired number of children for both surveys. The clusters were assigned to the villages according to their respective size with the ENA software. Thirty-six clusters were selected (6 extra clusters were selected in case on inaccessibility to the villages because of the flood affectation).

3.3 Households and children selection

At cluster level, households were randomly selected. The team would first go to the centre of the village and spin a bottle to determine a direction. The team then moved along this direction to the periphery of the village. There, the bottle was spun again and thereafter all the houses along this second line were counted. The first household to be surveyed was selected using a random number. Every child between 6 and 59 months present in the household was measured. A household was defined as a group of people who regularly eat together from the same cooking pot and sleep in the same compound. In the case that two families were on the same household, each family’s name had written on a piece of paper and a separate member of the team selected one. Polygamous families living together were considerate as a unique family.

15/32 In case of temporary absence of children the household was not omitted, a second visit was paid to the household later. If the child was still not available then, s/he was replaced by a child selected according to the methodology.

The subsequent households were chosen by moving to the right until the cluster was completed. In case that the village was bigger than 1,000 thousands people, the closer second house on the right was surveyed, in order to increase the coverage of the surveyed area. In some cases, the displaced population was settled alongside the road; a systematic sampling was used to select households.

Retrospective mortality data and migration information was collected alongside the anthropometric data and in every household selected by the methodology whether or not they counted eligible children for the anthropometric survey.

3.4 Data collection and measurement techniques

3.4.1 Anthropometric data

The following was collected for children 6 months of age to 59 months of age. (See appendix 1 for the questionnaire): Age: The age (in months) of the children was, in the first instance, established by asking the mother for the birth date of the child. If the mother did not know the birth date, the member of the team asked for birth cards or vaccination cards. If the information could not be found by the mother or the vaccination card, the age was evaluated according to several criteria: the estimation of the period of births by the mother by using a local calendar of events, the age of the siblings (brothers and sisters), the number of teeth and the height of the child. Sex: Male children were recorded as ‘M’ and females as ‘F’. Weight: Children were weighed in kilograms, to the nearest 0.1kg, using 25kg hanging sprint Salter scales. The scale was hung from a stick held by two measurers, and recalibrated to zero before the child was put into the weighing pants/basket. Although the teams attempted to weigh all children without clothing, in some areas this was not culturally acceptable. For children who were weighed with clothing 0.1kg was subtracted if they were half dressed (trousers or top). It must be say that it has rarely occurred. Each morning the scales were checked by the Nutrition Assistant using a standard weight of 2kg. Height: The height of the children was recorded in centimeters, to the nearest 0.1cm, using a 1,30m height board with a movable block. Children less than 85cm were measured lying down and those more than 85cm standing up. All children were measured barefoot. For children measured while standing up, the measurers were trained to ensure that the child’s head, shoulder blades, buttocks, calves and heels were touching the board and that they were looking straight ahead. Children measured while lying down were placed in the middle of the board with the head touching the fixed end, the knees pressed down and the heels touching the movable base of the board. Mid upper arm circumference (MUAC): MUAC was measured in centimeters, to the nearest 0.1cm, using a MUAC tape. The measurers were trained to locate the mid-point between the shoulder and the tip of the elbow on the left arm with the arm bent at a right angle. The measurement was taken at this mid-point with the arm extended and relaxed. Edema: was measured by applying normal thumb pressure to the anterior surface of both feet for three seconds. If an indentation remained after the pressure was removed, presence of edema was considered positive and a “Y” was entered on the data collection form. If the thumb imprint did not persist, or if the edema was not bilateral, the child was recorded as not having edema and an “N” was entered on the data collection form. The supervisor tried to check all positive or questionable cases of edema. Measles immunization status: The mother/caretaker was asked whether the children have been vaccinated against measles. If an immunization card was available confirming that a

16/32 measles vaccination had been given, the date was checked and the child recorded as having received the vaccination (1=yes). If the caretaker stated that the child was vaccinated, but they did not have an immunization card, the child was recorded as having a history of measles vaccination (2=history). If the caretaker stated that the child had not been vaccinated, the child was recorded as not having had the measles vaccine (3=no). If the caretakers does not know about the immunization status of the child, then “does not know” was recorded (4).

3.4.2 Household and Mortality Data

The following information was recorded for each household selected (regardless of whether there were any children ages 6 to 59 months living in the house) in order to establish the under 5 years and crude mortality rate. To ensure accuracy of the data collected, a household tally sheet was completed for each household visited and the information transferred to the household and mortality questionnaire (see Appendix). The start of the recall period chosen was the beginning of the floods, on June 26th.

The head of each household was asked: To list all the household members that are present now, or were present at any time of the recall period; How many people were currently living in the house (total and under five), How many of the current household members arrived since the beginning of the recall period, (excluding births), How many former household members left since the beginning of the recall period (excluding deaths), The number of births since the beginning of the recall period, The number of deaths since the beginning of the recall period.

3.5 Indicators and Formulas used

3.5.1 Acute Malnutrition

¾ Weight for Height Index

For the children, acute malnutrition rates were estimated from the weight for height (WFH) index values combined with the presence of edema. The WFH indices are compared with the NCHS20 and the 2005 WHO references. The indexes are presented in both NCHS and WHO references, but currently, only the NCHS reference is used at field level for identification of malnourished cases. The WHO reference indexes are mentioned for information.

WFH indices are expressed in both Z-score and percentage of the median. The expression in Z-score has true statistical meaning, and allows inter-study comparison. The percentage of the median on the other hand is commonly used to identify eligible children for feeding programs.

Guidelines for the results expressed in Z-score: • Severe malnutrition is defined by WFH < -3 SD and/or existing bilateral edema on the lower limbs of the child. • Moderate malnutrition is defined by WFH < -2 SD and ≥ -3 SD and no edema. • Global acute malnutrition is defined by WFH < -2 SD and/or existing bilateral edema.

Guidelines for the results expressed in percentage of median: • Severe malnutrition is defined by WFH < 70 % and/or existing bilateral edema on the lower limbs

20 NCHS: National Center for Health Statistics (1977) NCHS growth curves for children birth-18 years. United States. Vital Health Statistics. 165, 11-74.

17/32 • Moderate malnutrition is defined by WFH < 80 % and ≥ 70 % and no edema. • Global acute malnutrition is defined by WFH <80% and/or existing bilateral edema

¾ Children’s Mid-Upper Arm Circumference (MUAC)

The weight for height index is the most appropriate index to quantify wasting in a population in emergency situations where acute forms of malnutrition are the predominant pattern. However the mid-upper arm circumference (MUAC) is a useful tool for rapid screening of children at a higher risk of mortality. MUAC measurements are presented for all children form 6 to 59 months, divided by height groups, as MUAC is a malnutrition indicator in children taller that 65 cm in some protocols, and children taller than 75 cm in others. The guidelines are as follows:

MUAC < 110 mm severe malnutrition and high risk of mortality MUAC ≥ 110 mm and <120 mm moderate malnutrition and moderate risk of mortality MUAC ≥ 120 mm and <125 mm high risk of malnutrition MUAC ≥ 125 mm and <135 mm moderate risk of malnutrition MUAC ≥ 135 mm adequate nutritional status

3.5.2 Mortality

The crude mortality rate (CMR) is determined for the entire population surveyed for a given period. The CMR is calculated using the ENA software.

The formula below is applied: Crude Mortality Rate (CMR) = 10,000/a*f/ (b+f/2-e/2+d/2-c/2), where: a = Number of recall days (90) b = Number of current household residents c = Number of people who joined household d = Number of people who left household e = Number of births during recall f = Number of deaths during recall period

The result is expressed per 10,000 people / day. The thresholds are defined as follows:

Total CMR: Alert level: 1/10,000 people/day Emergency level: 2/10,000 people/day

Under five CMR: Alert level: 2/10,000 people/day Emergency level: 4/10,000 people/day

3.5.3 Measles Vaccination Coverage

Because measles vaccinations should be given to children at 9 months of age immunization history will only be analyzed for children ≥9 months of age. In these surveys, coverage was calculated as follows:

Measles coverage = (Number of children ages 9–59 months reported to have been vaccinated) / (Total number of children ages 9–59 months in the sample population) × 100

18/32 3.6 Training and supervision

Four survey teams were used for the survey, each comprising three people (one team leader and two measurers). Teams consisted in 6 men and 6 female. Due to the cultural context, each team comprised at least one female member. To ensure that the teams had a good knowledge of the survey area, the measurers were recruited locally. Ideally, the same teams should have been used for both surveys to ensure that data collection was consistent, unfortunately, 3 team members left after the first survey and were replaced.

The nutritional team members attended a four day training (two theory days and two practical ones) conducted by the two Nutritionist Assistants supervised and trained for the Nutritionist Officer. The training covered: basic introduction to nutrition and malnutrition, rationale of the surveys, sampling methodology, interview skills, and criteria of malnutrition, anthropometric measurements, and household/mortality questionnaires. Finally, a pilot survey took place in one village. All the training was conducted in Sindhi and the surveyor’s manual was translated in Sindhi and given to each team member.

During the survey, a debriefing session was conducted with all team members at the end of every day. At village level, the purpose and the running of the survey were explained to the local authorities. A facilitator was identified among the local community, and guided the teams around. The facilitators did not measure or interview any household.

3.7 Data analysis

The team leaders returned their completed questionnaires at the end of each day. All the data collected that day was reviewed, and necessary corrections were made immediately, when possible. Data were entered and analyzed with the ENA software and Excel.

4. Results

4.1 Kamber-Shahdadkot survey The field work for the survey was done from November 20th to 27th, 2007.

4.1.1 Anthropometric results

The data of 805 children between 6 and 59 months were collected. The data of 27 children were discarded of the analysis as they were incoherent or incomplete. The following analysis is based on data from 778 children.

a. Age and sex distribution of the sample population Table 4: Distribution of age and sex of sample, Kamber-Shahdadkot survey, November 2007 Age groups Boys Girls Total Sex Ratio (months) no. % no. % no. % 6-17 88 49.7 89 50.3 177 22.8 1.0 18-29 62 46.6 71 53.4 133 17.1 0.9 30-41 91 51.1 87 48.9 178 22.9 1.0 42-53 92 52.6 83 47.4 175 22.5 1.1 54-59 71 61.7 44 38.3 115 14.8 1.6 Total 404 51.9 374 48.1 778 100.0 1.1

The sex ratio is close to one, showing no significant unbalance in the number of boys and girls included in the survey.

19/32 Figure 1: Age and gender distribution, Kamber-Shahdadkot survey, November 2007

Age and gender distibution

54-59 months

42-53 months

30-41 months Boys Girls 18-29 months

6-17 months

-60 -40 -20 0 20 40 60 80

b. Anthropometric analysis in Z-scores

Table 5: Prevalence of acute malnutrition by age expressed in weight-for-height in z-scores and/or edema, Kamber-Shahdadkot survey, November 2007 Age Moderate wasting Severe wasting Normal groups (>= -3 and <-2 z- Edema Total (<-3 z-score) (> = -2 z scores) (in scores ) months) No. % No. % No. % No. % 6-17 177 10 5.6 28 15.8 139 78.5 0 0.0 18-29 133 2 1.5 24 18.0 106 79.7 1 0.8 30-41 177 2 1.1 29 16.4 145 81.9 1 0.6 42-53 175 1 0.6 18 10.3 156 89.1 0 0.0 54-59 115 0 0.0 14 12.2 101 87.8 0 0.0 Total 777 15 1.9 113 14.5 647 83.3 2 0.3

Table 6: Prevalence of acute malnutrition in NCHS and WHO indexes, in Z-scores, Kamber-Shahdadkot survey, November 2007

NCHS WHO Prevalence of global malnutrition 16.7 % 18.7% (<-2 z-scores and/or oedema) (12.9% - 20.5%) (15.0% - 22.3%) Prevalence of severe malnutrition 2.2 % 4.1% (<-3 z-scores and/or oedema) (1.2% - 3.2%) (2.6% - 5.6%)

Table 7: Distribution of acute malnutrition and edema based on weight-for-height z-scores, Kamber- Shahdadkot survey, November 2007 <-3 z-scores >=-3 z-scores Marasmic kwashiorkor Kwashiorkor Edema present No. 0 (0.0%) No. 2 (0.3 %) Marasmic Normal Edema absent No. 15 (1.9%) No. 760 (97.8%)

20/32 Figure 2: Weight for Height distribution in Z-scores, Kamber-Shahdadkot survey, November 2007

Weight for height Z-score distribution curve shows marked displacement to the left of the reference curve indicating a critical nutrition situation. The mean Z-score is -1.20, while the standard deviation is equal to 0.85 and lies within the normal range of 0.8 – 1.2. The assessed sample can be conclusively said to be representative of the surveyed population. Both the skewness (0.076) and kurtosis (0.069) are within the moment range of +1 and -1 and consequently the degree of asymmetry around the mean and the relative flatness compared with normal distribution are satisfactory.

c. Anthropometric analysis in percentage of the median

Table 8: Prevalence of malnutrition by age expressed weight-for-height in % of the median and/or edema, Kamber-Shahdadkot survey, November 2007 Age Moderate wasting Severe wasting Normal groups (>=70% and <80% Edema Total (<70% median) (> =80% median) (in median) months) No. % No. % No. % No. % 6-17 177 0 0.0 27 15.3 150 84.7 0 0.0 18-29 133 1 0.8 14 10.5 117 88.0 1 0.8 30-41 177 0 0.0 16 9.0 160 90.4 1 0.6 42-53 175 0 0.0 9 5.1 166 94.9 0 0.0 54-59 115 0 0.0 5 4.3 110 95.7 0 0.0 Total 777 1 0.1 71 9.1 703 90.5 2 0.3

Table 9: Prevalence of acute malnutrition in NCHS and WHO indexes, in % of the median, Kamber- Shahdadkot survey, November 2007

NCHS WHO Prevalence of global malnutrition 9.5% 6.0% (<80% of the median and/or edema) (6.9% - 12.2%) (4.3% - 7.8%) Prevalence of severe malnutrition 0.4% 0.3% (<70% of the median and/or edema) (0.0% - 0.8%) (0.1% - 0.6%)

21/32 d. Anthropometric analysis in MUAC Table 10: Distribution of MUAC in height groups, Kamber-Shahdadkot survey, November 2007

>=65 – < 75 cm >=75 – < 90 cm ≥ 90 cm height Total MUAC (mm) height height N % N % N % N % < 110 3 2.2% 0 0.0% 0 0.0% 3 0.4% 110≥ MUAC<120 22 16.2% 8 2.9% 0 0.0% 30 4.0% 120≥ MUAC<125 15 11.0% 22 7.9% 3 0.9% 40 5.3% 125 ≥ MUAC <135 42 30.9% 58 20.7% 21 6.3% 121 16.2% MUAC ≥ 135 54 39.7% 192 68.6% 309 92.8% 555 74.1% TOTAL 136 100.0% 280 100.0% 333 100.0% 749 100.0%

According to MUAC criteria, 0.4% of the children surveyed are severely malnourished and 4.4% are moderately malnourished.

4.1.2 Mortality 512 households were surveyed for the retrospective mortality survey. The results collected are presented as follow: 3,490 people were present the day of the survey. 931 of them were children below 5 years of age (26.6%). 0 people have joined the household during the past 120 days. 268 people have left the household during the past 120 days. 46 of them were children below 5 years of age. 84 births occurred during the past 120 days. 16 deaths occurred. 14 of them affected children below 5 years of age.

Thus the retrospective mortality rates are:

♦ Crude mortality rate is 0.37 [0.11- 1.63] /10,000/day. ♦ Under five mortality is 1.27 [0.35-2.19] /10,000/day.

Displacement due to the floods:

64% of the households interviewed declared to have been displaced and to have returned. 11% % of the households interviewed declared to have been displaced, but that part of the family has still not returned.

4.1.3 Immunization coverage

Measles vaccination coverage was measured for children 9 months or more of age. The results are displayed in the following table: Table 11: Measles vaccination coverage, Kamber-Shahdadkot survey, November 2007 Vaccination proved by card 2.0% Vaccination declared by the caretaker21 73.3% Not immunized 16.1% Do not know 8.6%

21 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker

22/32 4.2 Dadu survey

The field work for the survey was done from October 31st to November 9th, 2007.

4.2.1 Anthropometric results

The data of 822 children between 6 and 59 months were collected. The data of 32 children were discarded of the analysis as they were incoherent or incomplete. The following analysis is based on data from 790 children.

a. Age and sex distribution of the sample population Table 12: Distribution of age and sex of sample, Dadu survey, November 2007 Age groups Boys Girls Total Sex Ratio (months) no. % no. % no. % 6-17 89 51.4 84 48.6 173 21.9 1.1 18-29 73 47.4 81 52.6 154 19.5 0.9 30-41 92 50.8 89 49.2 181 22.9 1.0 42-53 84 51.5 79 48.5 163 20.6 1.1 54-59 60 50.4 59 49.6 119 15.1 1.0 Total 398 50.4 392 49.6 790 100.0 1.0

The sex ratio is equal to one, showing no significant unbalance in the number of boys and girls included in the survey. Figure 3: Age and gender distribution, Dadu survey, November 2007

Age and gender distibution

54-59 months

42-53 months

30-41 months Boys Girls 18-29 months

6-17 months

-60 -40 -20 0 20 40 60

23/32 b. Anthropometric analysis in Z-scores

Table 13: Prevalence of acute malnutrition by age expressed in weight-for-height in z-scores and/or edema, Dadu survey, November 2007 Age Moderate wasting Severe wasting Normal groups (>= -3 and <-2 z- Edema Total (<-3 z-score) (> = -2 z scores) (in scores ) months) No. % No. % No. % No. % 6-17 173 3 1.7 26 15.0 143 82.7 1 0.6 18-29 154 0 0.0 29 18.8 124 80.5 1 0.6 30-41 181 0 0.0 23 12.7 158 87.3 0 0.0 42-53 163 2 1.2 20 12.3 141 86.5 0 0.0 54-59 119 0 0.0 18 15.1 101 84.9 0 0.0 Total 790 5 0.6 116 14.7 667 84.4 2 0.3

Table 14: Prevalence of acute malnutrition in NCHS and WHO indexes, in Z-scores, Dadu survey, November 2007

NCHS WHO Prevalence of global malnutrition 15.6% 17.8% (<-2 z-scores and/or edema) (12.8% - 18.3%) (14.8% - 20.9%) Prevalence of severe malnutrition 0.9% 3.2% (<-3 z-scores and/or edema) (0.1% - 1.7%) (1.9% - 4.5%)

Table 15: Distribution of acute malnutrition and edema based on weight-for-height z-scores, Dadu survey, November 2007 <-3 z-scores >=-3 z-scores Marasmic kwashiorkor Kwashiorkor Edema present No. 1 (0.1%) No. 1 (0.1%) Marasmic Normal Edema absent No. 5 (0.6%) No. 783 (99.1%)

Figure 4: Weight for Height distribution in Z-scores, Dadu survey, November 2007

24/32 Weight for height Z-score distribution curve shows marked displacement to the left of the reference curve indicating a critical nutrition situation. The mean Z-score is -1.17, while the standard deviation is equal to 0.81 and lies within the normal range of 0.8 – 1.2. The assessed sample can be conclusively said to be representative of the surveyed population. Both the skewness (0.132) and kurtosis (-0.447) are within the moment range of +1 and -1 and consequently the degree of asymmetry around the mean and the relative flatness compared with normal distribution are satisfactory.

c. Anthropometric analysis in percentage of the median Table 16: Prevalence of malnutrition by age expressed weight-for-height in % of the median and/or edema, Dadu survey, November 2007 Age Moderate wasting Severe wasting Normal groups (>=70% and <80% Edema Total (<70% median) (> =80% median) (in median) months) No. % No. % No. % No. % 6-17 173 0 0.0 19 11.0 153 88.4 1 0.6 18-29 154 0 0.0 14 9.1 139 90.3 1 0.6 30-41 181 0 0.0 16 8.8 165 91.2 0 0.0 42-53 163 0 0.0 11 6.7 152 93.3 0 0.0 54-59 119 0 0.0 10 8.4 109 91.6 0 0.0 Total 790 0 0.0 70 8.9 718 90.9 2 0.3

Table 17: Prevalence of acute malnutrition in NCHS and WHO indexes, in % of the median, Dadu survey, November 2007

NCHS WHO Prevalence of global malnutrition 9.1% 5.2% (<80% of the median and/or edema) (6.9% - 11.4%) (3.5% - 6.9%) Prevalence of severe malnutrition 0.3% 0.3% (<70% of the median and/or edema) (0.0% - 0.8%) (0.0% - 0.8%)

d. Anthropometric analysis in MUAC Table 18: Distribution of MUAC in height groups, Dadu survey, November 2007

>=65 – < 75 cm >=75 – < 90 cm ≥ 90 cm height Total MUAC (mm) height height N % N % N % N % < 110 4 2.6% 0 0.0% 0 0.0% 4 0.5% 110≥ MUAC<120 24 15.9% 15 5.0% 0 0.0% 39 5.0% 120≥ MUAC<125 13 8.6% 24 8.0% 4 1.2% 41 5.3% 125 ≥ MUAC <135 47 31.1% 73 24.3% 29 8.9% 149 19.1% MUAC ≥ 135 63 41.7% 189 62.8% 294 89.9% 546 70.1% TOTAL 151 100.0% 301 100.0% 327 100.0% 779 100.0%

According to MUAC criteria, 0.5% of the children surveyed are severely malnourished, and 5.5% are moderately malnourished.

25/32 4.2.2 Mortality

512 households were surveyed for the retrospective mortality survey. The results collected are presented as follow: 3,726 people were present the day of the survey. 931 of them were children below 5 years of age (25.0%). 0 people have joined the household during the past 120 days. 137 people have left the household during the past 120 days. 22 of them were children below 5 years of age. 94 births occurred during the past 120 days. 6 deaths occurred. 1 of them affected a child below 5 years of age.

Thus the retrospective mortality rates are:

♦ Crude mortality rate is 0.11 [0.00- 0.22] /10,000/day. ♦ Under five mortality is 0.08 [0.00-0.23] /10,000/day.

Displacement due to the floods:

39% of the households interviewed declared to have been displaced and to have returned. 8.5% of the households interviewed declared to have been displaced, but that part of the family has still not returned.

4.2.3 Vaccination Results

Measles vaccination coverage was measured for children 9 months or more of age. The results are displayed in the following table: Table 19: Measles vaccination coverage, Dadu survey, November 2007 Vaccination proved by card 6.5% Vaccination declared by the caretaker22 76.1% Not immunized 17.4% Do not know 0.0%

5. Discussion

22 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker

26/32 The immunization status of the surveyed children cannot be known with certainty, as around 75% of them are supposed to be vaccinated, but have no card to prove it. Nevertheless, the high number of negative answers show that access to vaccination, and by extension to basic health care, is not sufficient.

There is no baseline regarding the nutrition situation in the target areas, which could inform on the impact of the floods and their consequences on those rates. It is nevertheless very probable that the later led to a deterioration of the nutritional status of the affected population: the agricultural production -their principal livelihood source- was ruined during the floods, inducing an unusually long hunger gap until the next harvests. As a result, families are decreasing their food consumption. Other sources of income, like casual labor and selling livestock, have not been enough to sustain food security23.

The evolution of the nutrition situation cannot be predicted from a nutrition survey; close monitoring of the direct causes of malnutrition, such a food, water and health access, are necessary.

6. Recommendations

Nutrition treatment and monitoring:

Continue the existing nutrition program, and extend the coverage of supplementary feeding activities, to prevent the deterioration of moderately malnourished children,

Set up a nutritional surveillance system with existing health and nutrition structures,

Involve the Ministry of Health for activities such as the detection, prevention and treatment of acute malnutrition being implemented routinely in public structures,

Coordination of the different actors working in health and nutrition, to monitor the nutrition situation.

Factors leading to malnutrition:

Improvement of the food security situation, according to the recommendations given in the Food Security Assessment report (ACF, September 2007)

Improvement of the clean water access

Improvement of the health access in general (rehabilitation of the structures damaged by the floods, number of medical staff in the structures, availability of drugs and vaccines)

23 A Food Security Assessment of Flood-Affected Populations in Kamber-Shahdadkot and Dadu Districts, Sindh Province, Pakistan, ACF USA, 2007

27/32 Appendixes

Appendix 1: ANTHROPOMETRIC survey data form

Village: Date: Cluster number: Team number:

Chil HH Weight Height Sex Age in Oedema comment MUA d . Birthday (kg) (cm) MEASLES (F/M) months (Y/N) s C no. no. ±100g ±0.1cm 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

Immunization 1: Yes, proved by a card, 2: Yes, according to caretaker, 3: No, 4: Don’t know

28/32 Appendix 2: MORTALITY, Household data collection form (one sheet for every household)

UC : Village: Cluster number: HH number: Date: Team number:

1 2 3 4 5 6 7 Present in the household at the time of flood Died Date of Born during HH Present (include those not present now and indicate during ID Sex birth/or age recall member now which members were not present at the start of the recall in years period? the recall period) period? 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Current HH members – total Current HH members - < 5 Current HH members who arrived during recall (exclude births) Current HH members who arrived during recall - <5 (exclude births) Past HH members who left during recall (exclude deaths) Past HH members who left during recall - < 5 (exclude deaths) Births during recall Total deaths Deaths < 5

29/32 Appendix 3: Cluster selection, Kamber Shahdadkot survey

Estimated Cluster Taluka Uc Village under five assignment Pholirro 660 1 Qazi 900 3 Illahi Bux Khoso 150 4 Miro Korray Ji Wandh 360 5 Khabar Khan Moli Dino Khoso 1050 Mohd Bux Brohi 300 Fazul Chandio And Shahan Chandio 1320 12 Khalifo Kalhoro 210 Mir Pur Buriro 800 24 Bago Mohd Hassan Mugheri 200 25 Dero Mir Gh Umar Khoso And Darya Khan Mastoi 248 26 Qubo Haiabat Khan Magsi And Qalandar Bux Khoso 320 27 Saed Mohd Ibrahim Patujo And Sikander Magsi And Abdul Khali Mastoi 105 Khan Faiz Mohd Khaskheli, Haji Jan Mohd Khaskheli, Mohd Punhal, Abdul 300 29 Hazar Hamid Chandio Wah Liagat Ali Magsi 150 30 Ali Bux Magsi 90 31 Allah Bachyo And Din Muhammad Gadhi 550 Tewana And Karmullah Machi 150 Karyo Sabar 2000 Juma Khan Gebyani 100 Warah Mirpur Muhammad Salah Cholyani 200 32 Muhammad Ibrahim Sakhni 500 Ado Lashari 1500 34 Muhammad Khan Cholyani, Samano Khan Cholyani 300 36 Ghabidero 2800 8 Gul Burio, Abdul Rasool Buhio, Umeed Ali Fakirani 376 9 Mahboob Bujirani, Kareem Dino Chandio 110 19 Gabi Sona Khan Chandio 328 Qamber Dero Yaktar Burio, Buthi Lashkar Khan Chandio 518 15 Razi Khan Bujerani 528 16 Shakar Ji Wahi 461 17 Soomar Jo Goth, Fiaque Chandio 515 18

30/32 Appendix 4: Cluster selection, Dadu survey

Estimated Cluster Taluka Uc Village under five assignment Syeed Pur/Sayedpur 2000 1 Machhi House 150 2 Khan Jo Goth Qaim Jatoi 3500 3 Ghari Jager 3000 4 Khushal Machi 300 5 Mathien Akh Kadhai 500 6 Mehar Shoaib Colony 300 7 Faridabad 4000 8 Fareedabad Chhutto Meerwani 750 9 Charo 600 10 Mathien Aliwal 1000 11 Qadir Bux(Khan) Rind 700 12 Gozo 6000 13 Panjani Chandio 1500 15 Haji Jan Korijo/Jan Mohammad Korejo 3000 16 Jaro Khan Panhwar 800 17 Gozo Ibrahim Chandio 2500 18 K.N. Shah Bhangar 600 19 Wah Sobdar 2500 20 Sattani Chandia 4000 21 House Of Nallah 1500 23 Chor Qamber Mado 7500 24,25 Allah Dino Khoso 2000 27 Razi Khan Rodnani 200 Shahak Rodnani 1785 29 Sawro M. Hassan Rodnani 350 Abdul Rehmani Rodnani/Dhani Bux 280 31 Johi Rodnani Chapper Khan Jamali 2000 32 Dur Mohd Rodnani 600 33 Kamal Khan Sahib Khan Solangi 1500 34 Malto Jamali 200 35

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Appendix 5: MAP of the affected flood area

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