shiree

Final Report

Socio-Economic & Nutrition Survey carried out in October

2009

July 2010

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Executive Summary

1. Male and Female Headed Households: 401 randomly selected households took part in the survey with approximately equal numbers from each of the 6 NGOs. Nearly half (45.9%) were female headed, much higher than the most recent national figure (10.2%, Household Income and Expenditure Survey, (HIES) of 2005). The number of female headed households varied significantly between NGOs from a low of 26.5% in NETZ to a high of 77.3% in SCF. Female heads were primarily widowed (64.7%) or divorced/abandoned (26.6%) while nearly all male heads were married (98.6%). Of the 184 female headed households, 76 (41.3%) lived alone compared with only 2 out of 217 male headed households. Mean family size was 2.96, much lower than the HIES (4.85) and female headed households were smaller by, on average 1.5 family members (2.14 versus 3.65, female versus male, respectively). Female headed households had fewer adults, 5 to 15 year olds and under 5 year olds compared with male headed households.

2. Education: Overall 84.8% of the sample had not been to school compared with 50.3% nationally. 1 in 5 of male headed households had attended school compared with only 1 in 12 of female headed households. There was considerable variation between NGOs with the highest school attendance for males in CARE (32.4%) and females in UTTARAN (21.9%) and the lowest attendance in NETZ for males (12.0%) and no females attended school in the PAB sample.

3. Chronic illness and disability: Chronic illness/disability was reported by just under 1 in 5 households, more so in SCF (27.3%) and UTTARAN (25.7%) households and less so in NETZ (10.3%) and CARE (12.1%) households.

4. Employment: Overall 5.2% of heads did not work (7.4% men, 2.7%, women). Women tended to work as domestic maids (27.2%), beggars (24.5%) or as day labourers (25.5%), while over half the men were employed as day labourers (56.2%), 9.7% were rickshaw pullers, or drove vans and carts, 6% were beggars and 4.6% were engaged in fishing/ aquaculture. 92.6% of all adult family members were reported to work. 10.4% of 5-15 year olds were employed in full time work and a further 7.6% part time and significantly more worked fom female (28%) than male (12.7%) headed households.

5. Land ownership: About 1 in 10 households owned some homestead land compared with the national figure of over 50%. Significantly more male headed households owned land (13.4%) than female headed households (5.4%) but the amount owned was small and only 4 households owned more than 4 decimals.

6. Household ownership, size and structure: Just under half of the households (47.4%) reported owning their own house, 17.5% rented, nearly 13% lived rent free and 11% lived on khas land. Female headed households were less likely to own a house and tended to live rent free. Total house size averaged 11.75 sq metres, female headed houses were significantly smaller (10.84 sq m) than male headed houses (12.51

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sq m). Urban dwellers, on average, had the smallest houses (9.95 sq m) and there was no significant variation in household size across rural NGOs. Houses were mainly constructed of tin/corrugated iron sheet in urban areas and grass etc or mud in rural areas whereas nationally cement/brick was used in 50% of urban households and 10% of rural households. Nearly all floors in rural areas were made of mud and cement brick in urban areas.

7. Water supply and defecation practices: The main source of drinking water in rural areas was a tube well and 10% used pond/river compared with 5% nationally. Only 8.9% of households owned a tube well and a further 8.9% shared ownership. In rural areas only 2 households (0.06%) had an electricity supply compared with 31.2% nationally whereas 88.9% of urban dwellers had access to electricity in keeping with national data. Urban dwellers used sanitary or ring/slab latrines whereas 38.9% of rural dwellers used open spaces (14.5% nationally), 38.8% used a ring/slab latrine and 8.5% a pit latrine.

8. Loans: Overall a third of households had some form of loan, mainly an interest free loan (22.2%) averaging 2100 Taka, while 1 in 10 households had an informal interest loan averaging 4110 Taka. Of the 13% of households with cash savings, the average was 190 Taka (range 5-2000).

9. Assets: No urban households owned animals and only five rural households had either a cow, calf or pig. 8.0% of rural households had goats and one fifth of households owned poultry. Working equipment was owned by 142 households (35.4%) more so by male (48.8%) than female (19.6%) headed households and the mean reported cost of purchasing equipment was 191 Taka. Only 8 households had either a TV, radio, bicycle, wardrobe or mobile phone; 6% of households owned a chair, 6.2% a mattress, 11% a table, 19.7% a wooden trunk, 53.4% a bed and 88%, 1 or more blankets. Just over one third of households owned jewellery. Nearly all households reported ownership of other household items e.g. water container, pans and umbrella. The mean cost of household belongings was 733 Taka, more in male than female headed households (788 versus 667 Taka, respectively). Total worth of all assets (animals, equipment and household belongings) averaged 925 Taka while 18 households (4.5%) had reported assets worth greater than 3000 Taka.

10. Income: 62 different income streams were identified of either cash or in-kind income. Overall mean cash income was 1000 Taka but 15% of households reported no cash income more so in female than male headed houses (21.2% versus 9.7%, respectively). Urban dwellers had significantly greater cash and in-kind income. After taking into account the number of adult workers per household no significant differences were found by head of household, but there were highly significant differences between NGOs mainly due to the much higher income in the urban sample. Total in-kind income was 348 Taka and total income from all sources was 1348 Taka/month. Based on regular cash income the mean per household per month was only 776 Taka compared with 7203 Taka nationally. In rural areas the mean income was 565 (6095

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nationally) and 1095 (10463 nationally) in urban areas. 93.8% and 66.7% of rural and urban households respectively were in the lowest income decile based on household income/month. Mean per capita income per day was 9.0 Taka (19.9 urban and 6.9 rural). 93.8% of rural households had an income of <22 Taka per capita/day (2007 prices) increasing to 95.6% with a cut-off of 26 Taka per capita/day (2009 prices). For urban households 76.2% had an income of <26 Taka per capita/day (2007 prices) rising to 81.0% based on 30 Taka per day per capita (2009 prices).

11. Expenditure: 44 household expenditure items were identified; 17 food items, 17 household and 10 work related. Information was provided daily, weekly, monthly or over the past 3 months. Mean overall expenditure was 1296 Taka (compared with 6134 Taka nationally), of which 65% (52.3% nationally) was spent on food over half (56.4%) on rice. Household expenditure accounted for nearly one third of all expenditure (30.5%) and work related items cost only 4.7% of total expenditure. Based on regular expenditure per household per month, the mean was only 1162 Taka compared with 6134 Taka nationally. In rural areas the mean expenditure was 870 (5319 nationally) and 2730 (8533 nationally) in urban areas. Expenditure on food increased to 74.7% of total expenditure. 98.5% and 76.2% of rural and urban households respectively were in the lowest expenditure decile based on household expenditure/month. Mean per capita expenditure per day was 13.7 Taka (28.9 urban and 10.8 rural). 91% of rural households had an expenditure of <22 Taka per capita/day (2007 prices) increasing to 96% with a cut-off of 26 Taka per capita/day (2009 prices). For urban households 46% had an expenditure of <26 Taka per capita/day (2007 prices) rising to 60% based on 30 Taka per day per capita (2009 prices).

12. Difference between income and expenditure: The difference between household income and expenditure (credit/debit balance) was calculated for each household and the overall mean was +45 Taka with 52.9% of households in credit. Credit/debit balance ranged from -6758 to +5184 Taka. When analyses were restricted to regular monthly income and expenditure 76% of households were in debit with an overall mean of -386 Taka. Significant heterogeneity existed between NGOs and male headed households were more in debit than female headed households(-449 and -313 Taka, respectively).

13. Food intake and security: Food diversity was poor especially in rural areas and very few families consumed any meat, poultry, fruits or milk. Urban families were more likely to consume rice every day than rural families (88.9% versus 76.3%, respectively). Households had poor food security. Over a quarter of adults (but not children) had not eaten all day at least once in the last week. Eating less than three meals a day was more common in rural than urban dwellers (48.5% versus 30.2%) as was lower quality of food (62.7% versus 46.0%, in rural and urban, respectively) while food gathering was undertaken by 59.2% of rural households but only by 9.5% of urban families. Female headed households were much more likely to buy food on credit (30.0% versus 16.8% female and male headed households, respectively).

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14. Medical treatment: Just over a quarter (26.2%) of household members did not require medical treatment, but 15.7% who reported sick did not seek treatment. Of those seeking treatment (n=233) over 70% relied on the pharmacy or pharmacy in combination with another service(s).

15. Adult nutritional status: Mean Body Mass Index (BMI) was similar in male and female headed households (BMI mean=18.2) but there was evidence of severe chronic energy deficiency (CED); nearly 60% showed some CED (compared with 30% in the Bangladesh Demographic Health Survey, BDHS, 2007) of whom 15.1% were in the very severe CED category, 13.6% severe and 30.6% moderately severe category. 54.0% of female headed households were anaemic (32.4% in males). Overall 75.2% of head of households had CED or were anaemic (69.3% in males and 79.9% in females). There was a significant positive relationship between BMI and haemoglobin level and each 1 unit increase in BMI was associated with a 1.3 g/l rise in haemoglobin. Defecating in open spaces was associated with worse adult nutritional status; CED III (20.9% versus 10.9%, open spaces versus latrine use, respectively) and anaemia (52.9% versus 37.8%). There was also a positive association between food expenditure and haemoglobin level; for each 100 Taka spent on food haemoglobin increased by 0.8 g/l.

16. Child nutritional status: Just over half of the under 5 year old children were stunted (52.2%) or underweight (50.4%) and nearly a quarter (23.7%) were wasted. These percentages are worse than the BDHS, 2007 survey which found only 42% stunted, 42% underweight and 17% stunted. Overall 62.5% of children were either wasted, stunted or underweight. Over a quarter of children were stunted and underweight and 22.3% of children suffered from both acute and chronic undernutrition. 59.4% of girls and 53.7% of boys were anaemic. Of those children not stunted, underweight or wasted, 64.3% were anaemic. Overall 86.7% of children were either stunted, wasted, underweight or anaemic and 10% were suffering from all 4 conditions. There were positive associations between parental BMI and child height-for-age and weight-for-age z-scores.

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1. SOCIO-DEMOGRAPHIC CHARACTERISTICS OF THE SAMPLE

1.1 Background

64 representative households were selected from each of the 6 NGOs on the basis of the variables provided by the NGOs, usually the reported monthly income, educational level of the head of household, presence of under five year old in the household, age of the household head, household size and sex of household head. A representative back-up list was also generated in case households were absent on the day of the survey. 1.2 Age and marital status of household head In total 401 households took part in the survey, with approximately equal numbers of households from each of the six NGOs (Table 1). Table 1 Basic socio-demographic characteristics of head of house and households by NGO

NGO N Male Headed Houses

Mean Age of head of house

(years)

Family Size Education (yes, %)

Disability/ chronic illness

% Male Female Male Female Male Female Overall % CARE 66 56.1 45.9 46.5 3.51 2.21 32.4 6.9 12.1DSK 63 52.4 42.3 40.5 4.18 2.67 15.2 10.0 20.6NETZ 68 73.5 42.6 50.9 3.24 1.89 12.0 5.6 10.3PAB 64 62.5 38.6 56.5 3.83 2.00 17.6 0.0 12.5SCF 66 22.7 57.9 50.7 3.87 1.86 20.0 5.9 27.3UTTARAN 74 56.8 45.3 42.8 3.62 2.28 28.6 21.9 25.7Total 401 54.1 43.9 47.8 3.65 2.14 20.7 8.7 18.2 Nearly half the households had a female head (45.9%) compared with 10.2% nationally (Household Income and Expenditure Survey, HIES, 2005). However the number of male and female headed households differed significantly between NGOs primarily due to an excess of female headed households in the SCF sample and male excess in the NETZ sample (χ2=38.71, p<0.001). Overall female heads were significantly older by about 4 years, on average, than male heads (t=2.40, p=0.017) and there was significant variation in mean ages between NGOs (Table 1) even after taking into account differences between male and female headed households (F=2.65, p=0.023). Female heads were primarily widowed (64.7%) or divorced/abandoned (26.6%) while nearly all male heads were married (98.6%).

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1.3 Family size and families with under 5 year-old children The overall mean family size was 2.96 (range 1-8) which is much lower than the national figure of 4.85 (HIES, 2005). Female headed households were significantly smaller than male headed households by, on average, 1.5 family members (2.14 versus 3.65 family members, t=11.44, p<0.001). The lower mean family size in female headed households was apparent in all NGOs (Table 1) and the largest mean family size was in the urban slums in both male and female headed households. Female headed households had significantly fewer adults, 5 to 15 year olds, as well as under 5 year-olds compared with male headed households. Of the 184 female headed households, 76 women were living alone compared with only 2 out of 217 male headed households. Households with under 5 year-old children made up 31.4% of the sample but only 14.1% of female headed households had an under 5 year-old child compared with 46.1% in male headed households (χ2=47.18, p<0.001). There was no significant heterogeneity in the distribution of under 5 year-old children in NGOs after taking into account the numbers of male and female headed households in each NGO. 1.4 Schooling Only 14.8% of the heads of households had attended school compared with nearly 50% nationally, (49.7%, HIES, 2005) and there were significant differences in school attendance between male and female headed households. Overall 20.7% (45 of 217) of males had been to school compared with only 8.7% (16 of 184) of females. Males were more likely to have attended school across all NGOs but there was considerable heterogeneity between NGOs (Table 1) with the highest male school attendance in CARE and female in UTTARAN and lowest attendance in the NETZ sample for males, while no females attended school in the PAB sample. Of the other adult household members overall, 27.4% had attended school, more so in female headed households (41.7%) than male headed households (24.1%). Significantly more adult males (58.7%) attended school than adult females (22.1%, χ2=26.39, p<0.001) and these percentages were similar in both male and female headed households. Overall 50.6% of the 5 to 15 years of age attended school, slightly more girls attend (54.5%) than boys (46.9%) and these percentages were similar in both male and female headed households. 1.5 Disability within the household Overall 18.2% of heads of household reported having either disability (3.2%) or chronic illness (15.0%) but no significant differences were found in the extent of

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disability and chronic illness (combined) between male and female headed households. There was considerable heterogeneity between NGOs with low disability in NETZ (10.3%) and over 25% disability in SCF (27.3%) and UTTARAN (25.7%). When all adult data were combined 14.8% had some disability or chronic illness, but this did not vary between male and female headed households. However among adults other than the head, there was significantly more disability and chronic illness in female (21.7%) than male (8.4%) headed households (χ2=10.06, p=0.002). Among the under 5 year-olds and 5 to 15 year-olds, 5.2% and 3.2%, respectively were reported to have disability or chronic illness and no differences were found by the sex of the household head. 1.6 Employment of household members Overall 21 household heads did not work (5.2%; 7.4% male, 2.7% female) of whom 14 were disabled or chronically ill. About a quarter of women worked as either domestic maids (27.2%), beggars (24.5%) or as day labourers (25.5%) while over half of the men were employed as day labourers (56.2%), 9.7% were riding rickshaws, driving vans, carts or boats, 6.0% were beggars and 4.6% were engaged in fishing/aquaculture. Of all the adult family members (n=718), 92.6% were reported as working and this percentage was similar in male (92.2%) and female (91.8%) headed households. Of the children between 5 and 15 years of age, 58 of them (18.5%) were employed either full time (n=34, 10.8%) or part time (n=24, 7.6%). There was a significant disparity in working practices of 5 to 15 year olds living in male and female head households; 28% of 5 to 15 year olds worked full or part time in female headed households compared with only 12.7% in male headed households (χ2=12.47, p=0.002). 2. HOUSEHOLD LAND OWNERSHIP Overall only 9.7% of households owned some homestead land compared with 94.7% nationally (HIES, 2005). Male headed households were significantly more likely to own homestead land (13.4%) than female headed households (5.4%, χ2=7.13, p=0.008). The amount owned was small and only 4 households had more than 4 decimals. Only two households owned, shared or rented free of charge, cultivatable land. It is not possible to test for differences between rural NGOs because of the small sample sizes of those with land.

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Table 2 Household land ownership by head of household Variable Male (%, n= 217) Female (%, n= 184) Homestead land owned (decimal) 0

0.1 – 1.0 1.1 – 2.0

2.1+

86.64.16.03.2

94.6

1.6 3.3 0.5

Cultivatable land owned No Yes

99.10.9

100.0

0.0 Cultivatable land share cropped No Yes

99.10.9

100.0

0.0 Cultivatable land used free of charge No Yes

99.5

0.5

100.0

0.0

3. HOUSING, WATER ACCESS, SANITATION AND ELECTRICITY 3.1 Home ownership Overall just under half of households (47.4%) reported owning their house, while 17.5% rented, 12.7% lived rent free and 11% lived on khas land. There was a highly significant difference (χ2=22.86, p=0.001) in ownership between male and female headed households (Table 3). Female headed households were less likely to own a house, and tended to live rent free, either with family or non-family, than male headed households. Table 3 House ownership by head of household House Ownership Male (%) Female (%) Own 53.5 40.2Rent 17.5 17.4Live with parent 4.1 6.5Rent free with family 3.7 14.7Rent free non-family 2.3 6.0Live on khas land 12.4 9.2Other 6.5 6.0 3.2 Size of house Each household specified the length and width of their house in hath (0.46m) and from this the total area of the house was determined in square metres (sq m). The overall mean was 11.75sq m (SD=5.94) but female headed households lived, on

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average, in smaller dwellings (10.84sq m) compared with male headed households (12.51sq m, F=7.06, p=0.008) and there was also significant variation between NGOs (F=2.95, p=0.013) with the largest mean household size in PAB (13.67sq m) and the smallest in the urban slum (9.95sq m). Restricting analysis to rural areas revealed that mean household size did not vary significantly across rural NGO although the smaller average household size of female headed households remained significant. 3.3 House construction The material for wall construction was primarily from grass/straw/jute sticks/plastic (grass etc., 31.2%), mud (29.4%), tin/corrugated iron sheet (18.5%) or bamboo (13.2%) and much worse than national data where 50% of urban and 10% of rural households walls were constructed of cement/brick. As expected there were highly significant differences in wall construction between urban and rural areas; in urban areas walls were mainly constructed of tin/corrugated iron sheet (84.1%) or cement/brick (9.5%) whereas in rural areas they were mainly made of grass etc (37.2%) or mud (35.1%) and to a lesser extent by bamboo (14.6%) and tin/corrugated iron sheet (6.3%, χ2=242.03, p<0.001 There was also significant variation between rural NGOs with CARE and PAB having the highest usage of grass etc., NETZ and UTTARAN primarily mud, and SCF equal usage of grass etc, bamboo and mud. In addition there was a significant effect of head of household after taking NGO differences into account, with female headed households more likely to use bamboo and less likely to use mud (χ2=13.33, p=0.021). The material for roof construction was primarily tin/corrugated iron sheet (58.6%) or grass/straw/jute stick/plastic (35.4%) whereas nationally corrugated tin was used in 82.3% of households, brick/cement in 7.7% and grass/straw etc. only accounted for 10%. Significant heterogeneity was found between material used for roofing construction between NGOs (χ2=156.52, p<0.001). All urban slum dwellers (100%) used tin/corrugated iron sheet for roofing as did nearly all households in PAB (95.1%). Just over three-quarters of the roofs of CARE households were made of tin/corrugated sheet while over 76% of SCF and UTTARAN households were constructed with grass etc. Households in NETZ used more or less equally grass etc. or tin/corrugated iron sheet. No significant differences were found in material for roof construction by head of household. Nearly all floors were made of mud (83.5%) or cement/brick (10.7%). Only 3 rural households (0.9%) used cement/ brick compared with 81.6% in urban slums (χ2=275.64, p<0.001). No significant differences were found in material for floor construction by head of household.

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3.4 Source of drinking water The main sources of drinking water were tube well (71.6%), pond/river etc. (10.0%) and pipe/supply (8.7%) whereas the corresponding national figures were 89%, 3% and 8% respectively. Highly significant differences (χ2=378.17, p<0.001) were found between NGOs source of drinking water reflecting both urban-rural differences (urban dwellers did not use open wells, ponds etc.) but also differences between rural NGOs. For example, usage of pond/river as a source of drinking water was primarily by SCF and UTTARAN households and open wells entirely by NETZ households. Female headed households were more likely to use pond/river than male headed households as their source of drinking water. Only 8.9% of households owned a tube well and a further 8.9% shared tube well ownership. There was significant variation between NGOs (χ2=62.50, p<0.001) mainly because 28.8% of CARE households owned a tube well with a further 16.7% with shared ownership. No significant differences in tube well ownership were found between male or female headed households. 3.5 Electricity supply Nearly all rural households (99.9%) had no electricity supply (nationally 68% of rural households do not have electricity) whereas 88.9% of urban dwellers (comparable with national data) had an electrical supply (χ2=307.50, p<<0.001) and no significant differences in electricity supply were apparent between male or female headed households. 3.6 Defecation practices Place of defecation was primarily, but not entirely, related to location. Urban dwellers tended to defecate using either a sanitary or ring/slab latrine (87.3%) compared with only 38.8% of rural dwellers (χ2=190.41, p<0.001). Overall in rural areas 38.9% used open spaces (compared with 11.3%, nationally), particularly so in NETZ (85.3% of all households), PAB (60.9%) and SCF (48.5%) households. Pit latrines were used by 8.5% of rural inhabitants mainly in CARE and UTTARAN. No significant differences in defecation practices were found between male or female headed households.

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4. CASH LOANS AND SAVINGS Five sources of cash loan were identified (i) free informal (ii) informal loans with interest (iii) interest loans from shomiti (iv) interest loans from microfinance institutions and (v) interest loans from bank or Government of Bangladesh. A total of 89 households (22.2%) had interest free loans (range 1 to 8 loans) of whom just over half (11.7%) had only 1 loan (Table 4). The percentage of households taking up an interest free loan was very similar in urban and rural areas (26.9% and 21.3%, respectively). The mean amount of Taka borrowed did not significantly increase with the number of loans because of the large variability in the amount borrowed and the overall average loan was 2101 Taka. The number of loans did not vary by NGO or by head of household. However female headed households borrowed significantly less Taka (1180 Taka), on average, than male headed households (2788 Taka, t=2.74, p=0.008), a difference of 1608 Taka, on average, and this difference remained significant after taking into account the number of loans and NGOs. A total of 42 households (10.5%) had an informal interest loan (range 1 to 4) and the mean amount of the loan was 4110 Taka. Although there were no significant differences in the number or amount of loan by NGO or head of household, urban households were much more likely to take out an informal interest loan than a rural household (23.8% versus 9.8%, respectively, χ2=9.94, p=0.002). The urban mean informal interest loan was significantly greater than the rural mean (6508 versus 2778 Taka, t=2.17, p=0.036). The mean informal interest loan was significantly higher than the interest free loan (4110 versus 2101 Taka, t=2.18, p=0.031). The number of households taking out any other form of interest loan was only 2.7% (Table 4) and the average bank loan was much higher than any other form of loan. Overall 31.2% of households had some form of loan. The total loan number of loans did not vary by NGO or head of household. The overall mean loan was 3254 Taka and the mean loan was significantly lower if from a single source. There was significant heterogeneity in mean loans between NGOs primarily due to an urban-rural difference and on average, urban households borrowed more than rural households (6410 versus 2692 Taka, respectively), a difference of 3718 Taka (t=3.54, p=0.001). There were no significant differences in mean loans amongst rural NGOs. Male headed households borrowed more than female headed households (4228 versus 2358 Taka, respectively) a difference of 1870 Taka (t=2.26, p=0.026) and this difference remained significant after taking into account variation between NGOs. Overall 11.9% of households had some form of interest loan, mainly informal (Table 4). Those with a single loan source tend to borrow less than those with multiple sources. Urban households (n=15), on average, took out much larger

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loans than rural households (n=33, 9725 versus 3265 Taka, respectively). No significant heterogeneity was found between rural means nor was there any head of household effect. In total 13.0% (n=52) had some cash savings, mean 190 Taka (range 5 – 2000 Taka) and there were no significant differences in the extent of savings between NGOs, urban-rural households or by household head. Households with savings were more likely to take out a loan than households without any savings (46.2% versus 28.9%, χ2=6.25, p=0.012). Table 4 Number of loans, average amount of loan (Taka) and range Type of Loan Number of

Loans N Mean (Taka) Range (Taka)

Free informal 1 2 3+ Total

47132989

1614248327192101

25 – 2000020 – 12000

150 – 1000020 – 20000

Interest informal 1 2 3+ Total

19121142

2474338394254110

450 – 110001000 – 7900

1000 – 35000450 – 35000

Shomiti 1+ 4 3238 600 – 7000Microfinance 1 5 4812 2560 – 8500Bank 1 3 14667 12000 –

20000Total loans 1

2 3 4+ Total

55272221

125

20324276541744873524

25 – 2000020 – 26000

150 – 35000200 – 1900020 – 35000

Total interest only loans 1 2 3 4+ Total

2016

66

48

28685579

1140064335284

450 – 120001000 – 260002400 – 350001000 – 19000

450 – 35000 5. HOUSEHOLD ASSETS 5.1 Animals No urban households owned any animals and only two rural households owned adult cattle, two households had calves and only 1 household had a pig. Twenty seven households (6.7% of all households, 8.0% of rural households) had goats and there was no significant heterogeneity in pig ownership between rural NGOs or by head of household. One fifth, 21.4% of all households (25.4% of rural

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households) owned poultry. There was significant variation in poultry ownership between NGOs. About one third or more of households in CARE, SCF and UTTARAN owned poultry compared with 1 in 5 in PAB and 1 in 10 in NETZ (χ2=33.67, p=0.001). In total 101 rural households had animals, 29.9% of the rural NGO households. The amount spent on animals ranged from 25 to 6000 Taka and the mean was 454 Taka. There was no significant variation between NGOs or by head of household, although male headed households spent more, on average, than female headed households but not consistently across all rural NGO (Table 5). Table 5 Mean amount spent on animals by NGO and head of household NGO Male Female Total n Mean n Mean n MeanCARE 16 645 13 228 29 457NETZ 5 552 2 475 7 530PAB 12 425 2 105 14 379SCF 4 188 20 637 24 562UTTARAN 19 441 8 213 27 374Total 56 488 48 412 101 454 5.2 Working equipment Nobody owned a boat or sewing machine, only 2 households reported having cottage industry equipment, 4 households reported owning a rickshaw (2 in CARE and 2 in PAB), 32 rural households (8%, 9.5% of rural households) owned a net. Net ownership varied significantly between rural NGOs (χ2=11.82, p=0.019); 12 households (18.2%) in the SCF sample owned a net compared with only 1 household (1.5%) in the NETZ sample. Male headed households were more likely to own a net than female headed households (13.0% versus 5.2%, χ2=6.02, p=0.014). Equipment was owned by 142 households (35.4%) and female headed households were much less likely than male headed households to own any equipment (48.8% versus 19.6%, respectively (χ2=35.41, p<0.001). Male headed households also owned more equipment (1 piece, 26.3% versus 13.6%, 2 pieces, 12.9% versus 3.3% and 3+ pieces, 9.7% versus 2.7% for male and female headed households, respectively). There was also significant heterogeneity between NGOs (χ2 =63.31, p<0.001) which was mainly due to the low ownership in CARE (18.2%) while 54.4% of NETZ householders owned equipment and 20.6% of NETZ households had 3+ pieces of equipment. Households with more adult members tended to have more equipment (χ2=38.23, p<0.001).

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The mean (geometric) reported amount spent purchasing equipment was 191 Taka (Table 6, range 5 – 4000 Taka) and male headed households spent nearly 3.5 times (234 Taka) on agricultural equipment compared female headed households (68 Taka, F=4.57, p=0.034). There was also significant heterogeneity in amount spent between rural NGOs (F=3.42, p=0.006) with least spending in NETZ and UTTARAN and greatest in CARE. Spending on equipment did not associate with the number of adult family members. Table 6 Mean amount spent on equipment by NGO and head of household NGO Male Female Total n Mean n Mean n Mean CARE 15 634 5 152 20 514DSK 11 115 4 114 15 115NETZ 32 80 5 102 37 83PAB 25 331 4 18 29 288SCF 12 278 17 49 29 144UTTARAN 22 109 6 28 28 91Total 117 234 41 68 158 191 5.3 Household belongings Only 1 household owned a television, 3 households each owned a radio, bicycle or wardrobe, 4 households owned a mobile phone, 24 households (6%) owned a chair, 25 households (6.2%) owned a mattress, 38 households (9.4%) had a fan (all living in the urban slums), 44 households (11%) had a table, 79 households (19.7%) had a wooden trunk 151 household members (38.7%) owned some jewellery, 214 households (53.4%) owned a bed and 353 (88%) owned 1 or more blankets. Jewellery ownership varied significantly between NGOs with the highest ownership in DSK (61.9%) and UTTARAN (59.5%) and lowest in NETZ (11.8%, χ2=55.28, p=0.001). More jewellery was owned in households with a male head (46.1%) than a female head (27.7%, χ2=14.31, p=0.001) Ownership of a wooden box/trunk varied significantly between NGOs. No household in NETZ owned a trunk whereas 46.9% of PAB households owned a trunk (χ2=68.39, p=0.001). Ownership of blankets varied between NGOs (χ2=153.62, p<0.001). Just over one third (36.5%) of urban households did not own a blanket compared with 7.4% in the rural NGOs. SCF and UTTARAN had the highest blanket ownership (98.5% and 97.3%, respectively). Table ownership varied significantly between NGOs, from a low of 2.7% (UTTARAN) to a high of 28.8% (CARE, χ2=34.34, p=0.001). No head of household effect was found. Mattress ownership varied significantly between NGOs (χ2=32.07,

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p<0.001) and was highest in PAB (17.2%) and DSK (14.3%) while no households in SCF or UTTARAN owned a mattress. Mattress ownership was significantly higher in male (8.8%) than female headed households (3.3%, χ2=5.14, p=0.023). Bed ownership also varied between NGOs with lower ownership in NETZ (26.5%), SCF (28.8%) and UTTARAN (27.0%) and high ownership in DSK (73.0%), PAB (84.4%) and CARE (86.4%). Male headed households were more likely to own a bed (59.0%) than female headed households (46.7%, χ2=6.00, p=0.014). Nearly all households (97.7%) cited ownership of other household items (e.g. water container pots, pans, umbrella etc) and 40.1% specified ownership of other items. The mean amount spent on household goods was 733 Taka (Table 7) and male headed households spent just significantly more than female headed households (788 versus 667, respectively, F=4.07, p=0.044). There was also very significant variation between NGOs (F=18.36, p<0.001) with the greatest mean household expenditure by DSK, followed by CARE, and PAB with the lowest expenditure in NETZ. Table 7 Mean amount spent on household belongings by NGO and head of household NGO Male Female Total n Mean n Mean n Mean CARE 37 1081 29 629 66 882DSK 33 1340 30 1426 63 1381NETZ 49 323 18 177 67 284PAB 40 937 23 494 63 775SCF 15 599 49 470 64 500UTTARAN 42 563 31 692 73 618Total 216 788 180 667 396 733 5.4 Total household assets The worth of animals, equipment and household belongings were summed and the mean worth of all (total) assets was 925 Taka and 18 households (4.5%) had reported assets > 3000 Taka. Although separate analyses revealed that male headed households had more assets than female headed households (1041 versus 786 Taka, respectively, t=2.53, p=0.012) and there was an increase in assets with increasing number of adult members (1 adult, mean 760 Taka, 2 adults mean 948 Taka and 3 adults mean 1276 Taka, F=5.13, p=0.006) these differences become insignificant in an analysis of variance (ANOVA) which took into account head of household, number of adults and NGOs. The ANOVA showed a very large NGO effect (F=10.23, p<0.001), a marginal head of household effect (F=3.33, p=0.06) and no effect of number of adult members (p ns). The NGO with the highest mean assets was DSK (Table 8) and the lowest mean was NETZ.

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Table 8 Mean total assets by NGO and head of household NGO Male Female Total N Mean N Mean n Mean CARE 37 1617 29 758 66 1239DSK 33 2378 30 1441 30 1932NETZ 49 432 18 258 67 443PAB 40 1271 23 507 63 992SCF 15 871 49 746 64 776UTTARAN 42 1041 31 752 73 791Total 216 1040 180 786 396 925 6. HOUSEHOLD INCOME Sixty two different income streams were identified, of either cash or in-kind income (Table 9). The main cash income sources were daily labour, agricultural labour, domestic work, Fetra/Zakat, other sources, donations from relatives, rickshaw etc. puller and taking a loan, while for in-kind income the main sources were domestic work, followed by Fetra/Zakat, donation from relatives, other sources, daily labour and loan taken. Cash income was usually reported as higher than in-kind income with the main exceptions of child labour and begging. There was no significant variation in mean cash income or in-kind income by head of household. Overall mean total cash income was 1000 Taka and 15% of households reported no cash income, significantly more so in female headed households (21.2% versus 9.7%, female and male, respectively (χ2=10.38, p=0.001). Mean cash income did not vary significantly by head of household, but income in households with 1 or 2 adults were significantly lower than in households with 3 adults by 906 and 627 Taka, respectively (F=5.08, p=0.007. There was also significant variation between mean cash income of NGOs which was accounted for by the much higher urban mean (2318 versus 928 Taka, urban and rural, respectively, F=47.95, p<0.001). Overall mean total cash income was 1000 Taka and 15% of households reported no cash income, significantly more so in female headed households (21.2% versus 9.7%, female and male, respectively (χ2=10.38, p=0.001). Mean cash income did not vary significantly by head of household, but income in households with 1 or 2 adults were significantly lower than in households with 3 adults by 906 and 627 Taka, respectively (F=5.08, p=0.007. There was also significant variation between mean cash income of NGOs which was accounted for by the much higher urban mean (2318 versus 928 Taka, urban and rural, respectively, F=47.95, p<0.001).

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Table 9 Household income in the last month Income Source Cash income In-kind income % Mean % Mean Agricultural day labourer 15.5 851 3.5 293 Other daily labour 30.2 654 9.2 278 Domestic work 11.7 670 20.9 447 Rickshaw etc 7.2 1611 0 0 Skilled labour 0.7 1050 0 0 Own agricultural produce 0.2 250 0.2 30 Fishing 6.2 713 2.0 346 Livestock 0.2 800 0.2 150 Industrial/garment labour 2.0 1358 0.2 300 Petty trade 4.0 755 0 0 Cottage industry 2.7 819 0 0 Service 3.0 1525 1.0 850 Transport 0 0 0 0 Begging 5.7 380 0 366 Rag picking/scavenger 1.0 665 0.5 365 Motorised van 0 0 0 0 Fuel sales 1.5 165 1.5 195 Child labour 3.2 416 2.5 600 Rural maintenance programme 0.7 973 0 0 100 day cash-for-work 0.2 3000 0 0 Foreign remittance 0 0 0 0 Donation from relatives 7.7 497 12.0 193 Fetra/Zakat 9.2 202 14.5 247 Government allowance 3.0 414 2.0 420 Training allowance 2.2 378 2.7 207 Shiree relief 0 0 0 0 Other NGO relief 0 0 0 0 Loan Taken 6.7 1870 7.0 243 Savings withdrawal 0 0 0 0 Other 9.0 372 10.7 289 Total 85.0 1177 68.1 511 Total regular income 78.3 991 51 460 Overall mean total in-kind income was 348 Taka and 31.9% of households reported no in-kind income. There was significant heterogeneity between NGO means (Table 10, F=4.97, p<0.001) with most of the heterogeneity due to urban-rural differences; the urban in-kind mean income was significantly higher than rural income (448 versus 329 Taka, respectively, (F=14.51, p<0.001). There was no significant difference between male and female headed households for in-kind income nor were there any significant differences by number of adults in the household.

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Combining cash and in-kind income revealed that only three households reported no income (2 male headed), and the mean total income was 1358 Taka (Table 10) much lower than the 7203 Taka/month national average income in 2005. Variation in mean total income was mainly due to the number of adults in the household and NGOs, but there was no significant head of household effect. Households with 1 or 2 adults had, on average 1019 and 693 Taka respectively, less income than households with 3 adults (F=7.77, p<0.001). The higher total income in DSK was the main reason for NGO heterogeneity (F=16.00, p<0.001). HIES calculated income based on regular cash income only. In shiree the mean regular cash income per household per month was only 776 Taka compared with 7203 Taka nationally (Table 10). In rural areas the mean income was 565 (6095 nationally) and 1095 (10463 nationally) in urban areas. 93.8% and 66.7% of rural and urban households respectively were in the lowest income decile based on household income/month. Mean per capita income per day was 9.0 Taka (19.9 urban and 6.9 rural). 93.8% of rural households had an income of <22 Taka per capita/day (2007 prices) increasing to 95.6% with a cut-off of 26 Taka per capita/day (2009 prices). For urban households 76.2% had an income of <26 Taka per capita/day (2007 prices) rising to 81.0% based on 30 Taka per day per capita (2009 prices). Table 10 Regular cash income by NGO Household cash

income/month Mean cash income per

earner/month

Mean cash income per capita/month

Mean cash income per capita/day

NGO shiree HIES shiree HIES shiree HIES CARE 768 382 276 9.2DSK (urban)

1905 10463 1209 6975 595 2217 19.9

NETZ 423 243 154 5.1PAB 770 433 243 8.1SCF 352 245 167 5.6UTTARAN 527 330 201 6.7Total Rural 565 6095 326 4449 208 1246 6.9Total 776 7203 464 5145 268 1485 9.0 7. HOUSEHOLD EXPENDITURE Forty four household expenditure items were identified, 17 involving food items, 17 primarily concerning the house and 10 were work related. Information was provided either daily, weekly, monthly or over the past 3 months depending on the purchasing. For each household expenditure item a mean monthly amount was computed (Table 11).

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The mean expenditure on food varied significantly by NGO (F=27.25, p<0.001), head of household (F=7.81, p=0.005) and adult family members (F=13.22, p<0.001); male headed households spent more on food that female headed households (+253 Taka) and households with only 1 or 2 adults spent less (1 adult -572 Taka, 2 adults -203 Taka) than households with 3 adults. DSK spent the most on food (Table 12) and there was significant heterogeneity between rural NGOs (F=5.78, p<0.001). The mean expenditure on household items was 408 Taka. There was no significant effect of number of adult household members on household items expenditure but male headed households spent, on average, 231 Taka more than female headed households (F=11.45, p=0.001). DSK spent the most and NETZ the least (F=33.07, p<0.001), but there was no significant heterogeneity in mean household expenditure among the rural NGOs. The mean expenditure on work-related items was 155 Taka and there was no significant variation by head of household or number of adult family members. The significant NGO effect (F=5.22, p<0.001) was due to higher DSK mean and no significant differences were found between rural NGOs. The mean total expenditure was 1315 Taka. On average male headed households spent 459 Taka more than female headed households (F=9.04, p=0.003); households with 1 adult or 2 adults spent 870 and 452 Taka, respectively, less than households with 3 adult members (F=10.54, p<0.001). Total expenditure varied between NGOs, DSK, on average, spending the most and SCF the least (F=58.39, p<0.001). Expenditure varied significantly between rural NGOs (F=4.37, p=0.002). The mean overall expenditure was 1296 Taka (Table 11) compared with 6134 Taka nationally, of which 65% was spent on food (52.3% nationally) with expenditure on rice being over half (56.4%). Household expenditure accounted for nearly one third of all expenditure (30.5%) and work related items cost only 4.7% of the total expenditure. 91.3% of households were in the lowest expenditure decile, based on the HIES 2005 report. The mean overall expenditure was 1296 Taka (Table 11) compared with 6134 Taka nationally, of which 65% was spent on food (52.3% nationally) with expenditure on rice being over half (56.4%). Household expenditure accounted for nearly one third of all expenditure (30.5%) and work related items cost only 4.7% of the total expenditure.

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Table 11 Household expenditure per month Expenditure Source % who purchased

source Mean of those who

purchased Overall Mean

Rice 84.5 560 473 Paddy 0.7 318 2 Wheat 22.2 67 14 Potato 44.6 97 43 Pulses 53.9 55 30 Fish 38.4 98 38 Meat 10.5 63 7 Eggs 14.7 54 8 Milk 6.2 61 4 Green vegetables 52.9 89 47 Other vegetables 38.2 118 45 Fruit 6.5 41 3 Sugar 20.7 36 7 Salt 91.5 17 16 Spices 83.0 58 48 Cooking oil 90.3 51 47 Other food items 9.0 68 6 Total food 96.5 868 838Kerosene 87.8 48 42 Soap 84.8 26 22 Other toiletries 23.9 22 5 Education 12.5 45 6 Transport costs 10.7 126 14 Health care 55.6 137 76 Clothing/footwear 24.2 111 27 House rent 14.5 835 121 Household furniture 0.5 440 2 Household repair 3.0 43 18 Electricity 3.0 142 4 Mobile phone 7.7 43 3 Wedding expenses 0.5 5000 25 Religious event 18.5 44 8 Interest payments 4.2 534 23 Loan given 0.2 3 0 Other household costs 1.2 43 1 Total house 97.0 408 395Work related 3.2 261 8 Agriculture 0 0 0 Livestock inputs 1.0 33 0 Livestock purchase 0.7 28 0 Land/pond lease 0 0 0 Business 1.2 869 11 Rickshaw rent 3.5 866 30 Fishing inputs 1.2 400 0 Other costs 7.2 158 11 Total work 16.0 386 62Total expenditure 98.5 1315 1296Total regular expenditure 98.5 1179 1162 HIES calculated regular expenditure. In shiree the mean regular expenditure per household per month was only 1162 Taka compared with 6134 Taka nationally

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(Table 12). In rural areas the mean expenditure was 870 (5319 nationally) and 2730 (8533 nationally) in urban areas. Expenditure on food increased to 74.7% of total expenditure. 98.5% and 76.2% of rural and urban households respectively were in the lowest expenditure decile based on household expenditure/month. Mean per capita expenditure per day was 13.7 Taka (28.9 urban and 10.8 rural). 91% of rural households had an expenditure of <22 Taka per capita/day (2007 prices) increasing to 96% with a cut-off of 26 Taka per capita/day (2009 prices). For urban households 46% had an expenditure of <26 Taka per capita/day (2007 prices) rising to 60% based on 30 Taka per day per capita (2009 prices). Table 12 Mean expenditure on food, house, work-related and total by NGO NGO Food Household Work-

relatedTotal Household

regular expenditure/month

Mean regular expenditure per

capita/day shiree HIES CARE 943 276 225 1240 1160 14.4DSK 1551 1340 826 3160 2730 8533 28.9NETZ 685 119 85 793 762 9.3PAB 868 225 141 1074 948 10.3SCF 562 188 89 737 698 10.5UTTARAN 633 331 172 982 9.8Total rural 870 5319 10.8Total 868 408 386 1315 1162 6134 13.7 8. DIFFERENCE BETWEEN HOUSEHOLD INCOME AND EXPENDITURE The difference between household income and expenditure (credit/debit balance) was calculated for each household and the overall mean was +45 Taka (credit), of whom 52.9% of households were in credit. Credit/debit balance was very large ranging from -6758 to +13700 Taka (due to a loan of 20000 Taka, if excluded, the upper value would fall to +5184). There was no relationship between credit/debit balance and head of household or number of adult members. Significant variation was found between NGOs which was mainly accounted for by the greater debt of DSK (F=3.78, p=0.002), and no significant variation was found between rural NGOs although CARE and NETZ were, on average, in debit and PAB, SCF and UTTARAN, in credit (Table 13). However when the analyses were restricted to regular monthly income and expenditure 76% of households were in debit with an overall mean of -386 Taka. Significant heterogeneity existed between NGOs and male headed households

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were more in debit than female headed households(-449 and -313, respectively, F+4.91, p=0.027). Table 13 Difference between reported household income and expenditure by NGO NGO Total Income – Total Expenditure Regular Income – Regular Expenditure CARE -51 -391 DSK -467 -824 NETZ -85 -340 PAB +142 -177 SCF +338 -345 UTTARAN +348 -268 Total +45 -386

9. HOUSEHOLD FOOD INTAKE Very few families consumed cassava or meat and over 90% of households did not consume any poultry, fruits or milk (Table 14). There were significant urban/rural differences with urban dwellers more likely to consume rice every day (88.9% versus 76.3%, χ2=4.93, p=0.026), and more likely to consume all other foods except for ‘other vegetables’ than rural dwellers (the numbers consuming meat and cassava were too small to draw any conclusions). Rural NGOs were similar in days of rice, pulse, fruits, milk and eggs consumption but over three-quarters of NETZ and UTTARAN households did not consume potatoes (χ2=29.76, p=0.003) and all households in PAB consumed green vegetables compared with only 60.6% in CARE (χ2=61.56, p<0.001); other vegetables were consumed by only 30% of NETZ households compared with about 70% in the other rural NGOs (χ2=52.69, p<0.001). Fresh fish was consumed least in NETZ (29.4%) and most in SCF (74.2%, χ2=52.95, p<0.001) while dried fish was mainly consumed in CARE (18.2%) and by only 1 household in each of the SCF and UTTARAN samples (χ2=20.05, p<0.001). There were no significant differences between the number of days any food was consumed by male and female headed households.

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Table 14 Number of days in the last week that household members consumed foodstuffs Food Number of days food consumed 0 (%) 1 (%) 2 (%) 3+ (%) Rice 0.2 - - 99.8 (7

days) Flour 82.0 6.2 6.5 5.2 Pulse 48.6 20.2 17.2 14.0 Potato 57.4 12.7 13.0 17.0 Cassava 98.8 0.7 0.5 - Green vegetables

10.0 11.0 24.9 54.1

Other vegetables

41.9 17.7 13.5 26.9

Fruits 91.5 3.7 2.5 2.2 Milk 95.3 2.0 1.0 1.7 Eggs 89.8 5.7 2.0 2.5 Fresh fish 42.4 21.9 15.7 8.7 Dried fish 88.3 6.0 3.2 2.5 Poultry 95.0 4.2 0.7 - Meat 98.8 1.2 - - 10. HOUSEHOLD FOOD SECURITY Households had poor food security (Table 15) and during the week prior to the survey they had eaten smaller portions of food, lower quality food and less than three meals a day. Over a quarter of adults (but not children) had not eaten all day at least once in the last week. Eating less than three meals a day was more common in rural than urban dwellers (48.5% versus 30.2%, χ2=7.22, p=0.007) as was less quality of food (62.7% versus 46.0%, in rural and urban, respectively χ2=6.17, p=0.013) while food gathering was undertaken by 59.2% of rural households but only 9.5% of urban dwellers (χ2=52.40, p<0.001). Female headed households were much more likely to buy food on credit (30.0% versus 16.8% for female and male headed households, respectively, χ2=9.39, p =0.002) while male headed households were much more likely to give more food to an earning member (35.0% versus 4.3%, male and female headed households, respectively, χ2=56.58, p<0.001).

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Table 15 Food strategy Food Strategy Yes (%) 3+ days (%) Eat smaller portion 84.3 76.4Eat < 3 times a day 45.6 31.6Eat food of less quality 60.1 47.2Eat gathered food 51.4 29.2Eat no food in 24 hours adult 27.2 0.7Eat no food in 24 hours child 2.7 0.4Borrow money to buy food 17.5 2.7Bought food on credit 23.9 4.7Send family member elsewhere for food 19.7 4.2Give more food to earning household members 20.9 14.0 11. HEALTH TREATMENT SERVICES Just over a quarter (26.2%) of the household members did not require medical treatment, but 15.7% were sick but did not seek treatment. Of those seeking treatment (n=233) over 70% relied on the pharmacy or pharmacy in combination with another service(s). When the data were grouped into 5 categories (not sick, sick but did not seek medical treatment, quack and others, pharmacy and clinic/hospital/medical doctor) there was no significant difference between male and female headed households. Table 16 Health Treatment Services Treatment Service Overall % %, those seeking

treatment Not sick 26.2 -Sick but did not seek medical treatment 15.7 -Relative/neighbour 0.7 1.3Quack/traditional healer 4.5 7.7Pharmacy 29.4 50.6Government clinic 1.0 1.7NGO clinic 0.2 0.4Private clinic 0.2 0.4Medical doctor 1.2 2.1Government hospital 5.5 9.4NGO hospital - -Private Hospital - -Homeopathic doctor 3.0 5.2Other 0.2 0.4Pharmacy with others 11.7 20.2

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12 NUTRITIONAL STATUS 12.1 Head of Household 12.1.1 BMI (Body Mass Index) In total 143 male and 174 female heads of household had their weight and height measured from which the Body Mass Index (weight (kg)/height (m)2) was calculated. There was no significant difference in mean BMI between male and females (Table 17) and the overall mean BMI was 18.3 and there was a highly significant negative association between BMI and age (b=-0.032, t=3.77, p< 0.001) and BMI declined by 0.32 kgm-2 for each 10 year increase in age. In all subsequent analyses the effect of age was taken into account. There was a just significant difference in mean BMIs between NGOs (F=2.42, p=0.036) after correcting for age, with the lowest mean in NETZ in both males and females and the highest mean in UTTARAN in females and DSK in males. There were no significant differences in means by marital status. BMI was categorised into the three levels of Chronic Energy Deficiency (CED) <16.0 (CED III), 16 - 16.9 (CED II) and 17 – 18.49 (CED I) and normal (18.5+). There was no significant difference in the distribution of BMI categories by NGO and overall 59.3% of the heads of household were suffering from some degree of undernutrition (compared with 30% in the Bangladesh Demographic Survey, 2007), rising to nearly three-quarters (73.7%) in NETZ. Table 17 Mean BMI and levels of chronic energy deficiency by NGO and head of household NGO Mean BMI BMI categories (%) Male Female <16 16 – 16.9 17 – 18.49 18.5+ CARE 18.4 18.5 12.3 12.3 29.8 45.6DSK 18.1 18.8 8.7 17.4 32.6 41.3NETZ 17.7 16.7 22.8 19.3 31.6 26.3PAB 17.6 18.4 19.6 8.7 37.0 34.8SCF 18.7 18.4 19.3 12.3 24.6 43.9UTTARAN 19.5 18.4 7.4 11.1 29.6 51.9Total 18.3 18.2 15.1 13.6 30.6 40.7 12.1.2 Haemoglobin level Haemoglobin (Hb) level was obtained from a finger prick of blood using a portable haemoglobin analyser (HemoCue, HomoCue Ltd., Sweden). There was a significant negative relationship between haemoglobin and age (b=-0.38, F=23.85, p< 0.001) and a 10 year age difference was associated with a mean haemoglobin

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difference of 3.8 g/l. Mean haemoglobin levels varied by head of household and also by NGO (Table 18); males had significantly higher average haemoglobin than females by 17.6 g/l after age correction (F=71.70, p< 0.001). There were significant differences in mean haemoglobin levels between NGOs after correcting for age and sex (F=7.54, p< 0.001) and in both males and females CARE had the highest mean and NETZ the lowest. Haemoglobin levels are categorised as severe anaemia <70 (g/l), anaemia 70 - 129.9 in males and 70 – 119.9 in females and normal as ≥130 in males and ≥120 in females. Only two males had severe anaemia (Hb levels of 40 and 56 g/l), one each in CARE and DSK. There was considerable variation in the extent of anaemia by NGO and head of household; 54.0% of female headed households were anaemic compared with 32.4% in male headed households (χ2=18.56, p<0.001). The highest levels of anaemia were found in NETZ and SCF and the lowest in CARE (χ2=43.09, p<0.001). Table 18 Mean haemoglobin and anaemic status by NGO and head of household NGO Mean Hb Hb category (%)

Anaemic Normal Male Female Male Female Male Female CARE 143.1 126.9 9.7 25.9 90.3 74.1 DSK 141.3 116.5 23.5 51.7 76.5 48.3 NETZ 125.3 105.9 57.9 82.4 42.1 17.6 PAB 142.5 117.3 16.7 54.2 83.3 45.8 SCF 127.1 115.6 62.5 63.3 37.5 36.7 UTTARAN 136.3 118.3 33.3 50.0 66.7 50.0 Total 136.0 117.2 32.4 54.0 67.6 46.0 12.1.3 BMI and haemoglobin level There was a significant positive relationship between haemoglobin level and BMI, such that for each 1 unit increase in BMI, haemoglobin level increased by 1.3 g/l (Figure 1).

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Figure 1 Relationship between adult haemoglobin level (g/l) and BMI

The relationship between haemoglobin and BMI categories is presented in Table 19 by head of household. There were significant differences (χ2=15.12, p=0.002) and just under 80% of female headed households were either anaemic only, CED only, or both anaemic and CED compared with only 70% of male headed households. Table 19 Relationship between haemoglobin and BMI categories Hb category BMI category Male (%) Female (%) Total (%) Normal Normal 30.7 20.1 24.8Normal CED 37.1 25.8 30.9Anaemic Normal 12.1 19.5 16.2Anaemic CED 20.0 34.4 28.0 The association between haemoglobin and BMI categories by NGO is presented in Table 20 and it reveals very significant heterogeneity between NGOs (χ2=47.03, p<0.001) with only 10.9% of NETZ heads of households having BMI in the normal range and without anaemia, compared with 38.6% in CARE.

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Table 20 Haemoglobin and BMI categories by NGO NGO Haemoglobin and BMI categories Anaemic/CED Anaemic/Normal Normal/CED Normal/Normal CARE 10.5 7.0 43.9 38.6DSK 26.1 15.2 32.6 26.1NETZ 49.1 16.4 23.6 10.9PAB 21.7 13.0 43.5 21.7SCF 40.4 22.8 15.8 21.1UTTARAN 18.9 22.6 28.3 30.2Total 28.0 16.2 30.9 24.8 12.2 Association between head of household nutritional status and socio-economic variables 12.2.1 Health, working status, land and house ownership, household size and defecation practices No significant differences in mean BMI were found in relation to health, working status, land and home ownership. There was a just significant positive association, after correcting for age, between household size and BMI (b=+0.047, t=2.04, p=0.042) and an increase in household size by 10 sq metres was associated with an increase in nearly ½ BMI unit. There was a highly significant association between defecation practice and BMI (F=11.71 p<0.001) with those not using a latrine having, on average, a lower BMI of nearly 1 unit (0.96kgm-2); 20.9% of CEDIII (BMI < 16) used open defecation compared with only 10.9% who used a latrine (Table 21, χ2=8.56, p=0.036). Table 21 BMI categories and place of defecation Defecation BMI CED III (%) Anaemic (%) Open 20.9 52.9 Latrine 10.9 37.8 No significant differences in mean Hb level were found in relation to health, land or home ownership, household size after taking into account age and sex. Those not working had a mean haemoglobin level 10.44 g/l lower than workers (F=4.71, p=0.031). Those not using a latrine had, on average, a 5.1 g/l lower haemoglobin level than latrine users (F=6.11, p=0.014) and were more likely to be anaemic (Table 21). Adults who were anaemic and CED were more likely to defecate in open spaces (χ2=15.67, p=0.001). 12.2.2 Income and expenditure

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There was a highly significant positive linear association between the haemoglobin level and expenditure on food (Figure 2, b=0.008, t=5.11, p<0.001) and haemoglobin level increased by 0.8 g/l, on average, for each additional 100 Taka spent on food. Expenditure on food explained just over 8% of the variation in haemoglobin level. Figure 2 Relationship between adult haemoglobin level (g/l) and expenditure on food

The mean expenditure on food by anaemic heads of households was significantly lower in both male and female headed households (Table 22, F=6.51, p=0.01). Table 22 Expenditure on food by head of household and anaemic status Anaemic status Male Female Normal 1221 614Anaemic 843 552 There was also a significant positive association between haemoglobin level and total cash income (b=0.005, t=4.07, p=0.001) and each additional 200 Taka of cash income associated with a rise in haemoglobin of 1 g/l. There was no association between haemoglobin and in-kind income. No significant association was found between BMI and expenditure on food or cash income. 12.3 Under 5 year-old children 12.3.1 Anthropometry From the measured height and weight of each child, the z-scores of height-for-age (HAZ), weight-for-age (WAZ) and weight-for-height (WHZ) were computed using the WHO (2006) standards. For example,

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z-score for height =(observed height-median reference height) standard deviation of height Low height-for-age (or length-for-age for children below 2 years of age) is a measure of past (chronic) undernutrition. Infants and children with z-scores <-2.00 are said to be stunted and those <-3.00 severely stunted. Low weight-for-age reflects both past (chronic) and present (acute) undernutrition but is unable to distinguish between them. Infants and children with z-scores <-2.00 are said to be underweight and <-3.00 severely underweight. Low weight-for-height is a measure of current or acute undernutrition and infants and children with z-scores <-2.00 are said to be wasted and <-3.00 severely wasted. There was no significant change in any of the z-scores in relation to the age of the child. Table 23 presents a breakdown of the sample of 113 children by mean z-scores as well as the percentage who were wasted, stunted and underweight. There were no significant differences in mean HAZ or WAZ between boys and girls, but girls had a significantly worse mean WHZ than boys (-1.5 versus -1.0, respectively, F=6.11, p=0.015). Only HAZ showed just significant heterogeneity (F=2.45, p=0.038) between NGOs with the worst means in DSK (-2.5) and PAB (-2.2) and the best mean in UTTARAN (-1.3). Over half the children were stunted (one fifth severely) or underweight and nearly a quarter were wasted. Table 23 Mean z-scores and severity of child undernutrition Nutritional status Mean % Very severe

(<-3) % Severe

(-2.99 - -2.00) % Normal (≥-1. 99+)

Height-for-age -2.0 19.5 32.7 47.8 Weight-for-age -2.0 16.8 33.6 49.6 Weight-for-height -1.3 5.3 18.4 76.3 The shiree child nutrition data were compared with 3 recent surveys (Table 24), two conducted in the Chars and with the most recent national survey. The shiree data are comparable with the Char surveys which also involving the poor, but much worse than the national data. Table 24 Extent of < 5 year old stunting, wasting and underweight in recent Bangladesh surveys Nutritional status

Shire 2009 CDSP IV 2009 CLP 2009 BDHS 2007

Stunting 52.2 52.0 54.0 43.0Underweight 50.4 57.0 49.0 41.0Wasted 23.7 18.0 14.0 17.0

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Only 37.5% of children had a normal HAZ, WAZ and WHZ (Table 25) and over 15% were stunted, underweight and wasted. Three-quarters of the wasted children (acute undernutrition) also had chronic undernutrition. Table 25 Percentage of children stunted, underweight and wasted Nutritional status % Normal 37.5Stunted only 9.8Underweight only 1.8Wasted only 1.8Stunted and underweight 26.8Stunted and wasted 0Underweight and wasted 7.1Stunted, underweight and wasted 15.2 12.3.2 Haemoglobin level Haemoglobin level was also determined in under 5 year-old children. The threshold for severe anaemia is 70 g/l and for anaemia 110 g/l. Only two children had severe anaemia, one each in NETZ and PAB. There was a significant positive linear relationship between haemoglobin level and child’s age (Figure 3, b=0.26, t=3.36, p=0.001) and haemoglobin increased, on average, by 0.26 g/l for each monthly increment. Figure 3 Relationship between child’s haemoglobin level (g/l) and age

There were significant mean differences in haemoglobin by sex (F=4.23, p=0.042) of the child and NGO (F=2.89, p=0.017) after correcting for the age of the child (Table 26). Boys had a higher mean than girls and PAB had the highest mean in boys and CARE in girls. Overall 59.4% of girls and 53.7% of boys were anaemic.

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Table 26 Mean haemoglobin and anaemic status by NGO and sex of the child NGO Mean Hb Hb category (%)

Anaemia Normal Boy Girl Boy Girl Boy Girl CARE 108.1 114.6 42.9 36.4 57.1 63.6 DSK 112.9 103.5 50.0 64.7 50.0 35.3 NETZ 104.6 94.0 64.3 100.0 35.7 0 PAB 113.2 108.2 40.0 38.5 60.0 61.5 SCF 106.0 90.0 100.0 100 0 0 UTTARAN 111.9 112.1 50.0 58.3 50.0 41.7 Total 109.8 106.1 53.7 59.4 46.3 40.6 12.3.3 Anthropometry and Haemoglobin level The inter-relationship between anaemic status and stunting, wasting and underweight are presented separately in Table 27. For HAZ and Hb, only 18.6% of children were normal, for WAZ and Hb 23.0% were normal and for WHZ and Hb, 34.5% were normal. Table 27 Anaemic status with stunting, underweight and wasting separately Z-score Z-score category Hb category % HAZ Normal Normal 18.6 Stunted Normal 25.7 Normal Anaemic 29.2 Stunted Anaemic 26.5WAZ Normal Normal 23.0 Underweight Normal 22.1 Normal Anaemic 26.5 Underweight Anaemic 28.3WHZ Normal Normal 34.5 Wasted Normal 9.5 Normal Anaemic 41.4 Wasted Anaemic 14.7 When anaemia and extent of stunting, underweight and wasting were combined together (Table 28) only 13.4% of the under 5 year-old children had a normal nutritional status as defined by z-scores and haemoglobin levels and 9.8% of children were anaemic, stunted, underweight and wasted. Of the children with normal anthropometry 64.3% were anaemic.

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Table 28 Anaemia and extent of stunting, underweight and wasting combined Anthropometry Anaemic

(%) Non-anaemic

(%) Normal 24.1 13.4 Stunted only 2.7 0.8 Underweight only 0.9 0.9 Wasted only 0 1.8 Stunted and underweight 13.4 13.4 Stunted and wasted 0 0 Underweight and wasted 4.5 2.7 Stunted, underweight and wasted 9.8 5.4 12.4 Association between child’s nutritional status and income and expenditure No significant associations were found between any of the child’s nutritional status variables (z-scores and haemoglobin level) and the socio-economic variables including income, expenditure or with head of household. 12.5 Association between head of household and child’s nutritional status There were significant positive associations between parental BMI and child’s stunting and underweight (Figures 4 and 5 respectively). Figure 4 Association between child’s height-for-age and adult BMI

Figure 5 Association between child’s weight-for-age and adult BMI

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For every 1 unit increase in adult BMI, the child’s z-score of height-for age increased by 0.21SD (t=2.66, p=0.009) and weight-for-age by 0.14SD (t=2.36, p=0.021). No significant relationships were found between adult and child haemoglobin levels or with wasting.