Monitoring the changes in socio-economic & nutritional

status of extreme poor households

Change Monitoring System (CMS3) - March 2010 to

March 2012

Professor Nick Mascie-Taylor and Dr Rie Goto

University of Cambridge

CMS 1 The Household Profile To provide the baseline from which to monitor change over time – all beneficiaries

CMS 2 Monthly Snapshot To enable an assessment of trends monthly – all beneficiaries

CMS 3 Socio-economic and Anthropometric Surveys

To provide in depth socio-economic and nutritional data allowing an assessment of longer term change and the impact of project interventions – random sample in Scale Fund NGO beneficiaries

CMS 4 Participatory Review and Project Analysis

To provide a forum for beneficiaries to explain changes in their lives and the reasons for these changes, as well as creating a platform for Innovation Fund NGOs to adapt and improve their innovations according to the needs of beneficiaries – group discussion in Innovation Fund NGO beneficiaries

CMS 5 Tracking Studies To provide quality longitudinal tracking studies documenting the dynamics of extreme poverty as it is experienced and changes in beneficiaries’ lives as a result of project interventions – small selection of beneficiaries

shiree Change Monitoring System (CMS)

Shiree has robust survey, monitoring and evaluation structure

+ CMS6

CMS 1 The Household Profile To provide the baseline from which to monitor change over time – all beneficiatries

CMS 2 Monthly Snapshot To enable an assessment of trends monthly – all beneficiaries

CMS 3 Socio-economic and Anthropometric Surveys

To provide in depth socio-economic and nutritional data allowing an assessment of longer term change and the impact of project interventions – random sample in Scale Fund NGO beneficiaries

CMS 4 Participatory Review and Project Analysis

To provide a forum for beneficiaries to explain changes in their lives and the reasons for these changes, as well as creating a platform for Innovation Fund NGOs to adapt and improve their innovations according to the needs of beneficiaries – group discussion in Innovation Fund NGO beneficiaries

CMS 5 Tracking Studies To provide quality longitudinal tracking studies documenting the dynamics of extreme poverty as it is experienced and changes in beneficiaries’ lives as a result of project interventions – small selection of beneficiaries

shiree Change Monitoring System (CMS)

Shiree has robust survey, monitoring and evaluation structure

CARE ‘Community Led, Voice and Value Chain’

Community-led development, Social economic empowerment, Increased wider policy-making process

20,000 HHs

Uttaran ‘Khas Land Transfar and Income Generation’

Khas land (public land) transfer to the landless people, Reduced corruption, Building income and livelihood capacity

12,000

NETZ ‘Asset Transfer and Land’

Targeting women and ethnic minority (Adibashi), Asset transfer and increased income, Reduced vulnerability

9,000

Practical Action Bangladesh (PAB)

‘Technology Transfer, Skills Development and Market’

Technology and skill development of sandbar cropping in char lands (riverine islands), Secured market access

16,850

Save the Children (SCF)

‘Social Entitlements, Asset Transfer and Market’

Enhanced capacity to access to safety-net, Assets and livelihood transfer, Access to health, education water facility

15,000

Dushtha Shasthya Kendra (DSK)

‘Social Mobilisation, Asset Transfer and Small Business’

Develop technical skill and business capacities, Improve water and health using common assets and services

10,000

6 NGOs in Round One Phase One Scale Fund

Three additional Round 2 Scale Fund NGOs (Concern, Oxfam, Caritas) commenced work in 2012 and will be analysed in future reports.

Uttaran:Satkira, Khulna

CARE:Gaibandha, Nilphamari, Rangpur, Lalmonirhat

DSK:Dhaka slums(Karail, Kamrangichar)

NETZ:Rajshahi, Naogaon, Chapai-Nawabgonj

PAB:Gaibandha, Nilphamari, Rangpur, Lalmonirhat

SCF:Khulna, Bagerhat

Cohort 1 - 384 households (64 HHs from Phase One 6 NGOs) Cohort 2 - additional cohort from urban slum (DSK) and Adivashi (NETZ) in 2011Cohort 3 - adding 3 NGOs in Phase Two in 2012 (including 10% estimated attrition each year)

Cohort 2010 2011 2012 2013 2014 2015

1 384 345 310 279 251 226

2 128 115 104 94 85

3 192 172 154 138

Total 384 473 617 555 499 449Within subject change Comparing with additional cohort

Testing for recruitment homogeneity

Design of annual panel nutrition surveys

Follow-up

CMS3 surveys conducted 3 times a year in March, July and October/November between March 2010 and 2012 and annual nutrition survey conducted each year in March.

CMS3 Round 7 - Annual nutrition and socio-economic surveys in 2012

26 February-16 April 2012 (total 50 days including 12 days training)It was a combined survey with Innovation Fund Round 1&2 Endline survey covering 25 Districts in Bangladesh covering 1472 HHs

CMS3 annual nutrition survey covered:

Cohorts 1&2 – 512 HHs

Cohort 3 – 128 HHs

Training of enumerating and anthropometric measurement

Total 45 research members including international nutrition advisor (Cambridge University), shiree staff, NGO Research Assistants, enumerators and measurers

and performing careful quality control

Measurements

Nutritional status

Anthropometric indicators: weight, length/height – BMI (adults) and z-scores (child below 5 years of age) Biochemical indicators: haemoglobin using HemoCue (portable analyser)

Socio-demographic characteristics of the household (including age, marital status, household/family size, education, disability, and occupation)Morbidity reportHousehold and homestead land ownershipHouse condition (size, structure, source of drinking water, electricity and toilet facilities)Cash loans and savingsAssets – animals, working equipment and belongingsIncome – cash and in-kindExpenditure – covering food, household and work relatedFood intake and food security

Socio-economic questionnaire

Results

Sample attrition for analyses

March

2010

July

2010

October

2010

March

2011

July

2011

November

2011

March

2012

Cohort Survey 1

Survey 2

Survey 3

Survey 4

Survey 5

Survey 6

Survey 7

1 384 376 352 336 329 316 303

2 128 (128) (128) (128)

3 192

Number of households which completed information all through surveys from March 2010

Nutrition

SESYes

Yes

-

Yes

-

Yes

Yes

Yes

-

Yes

-

Yes

Yes

Yes

There was greater attrition in the urban sample (45%) than in the rural areas (16%).

In total 303 households, information was collected on 1111 individuals of whom 634 were adults, 315 children aged between 5 and 15 years and 162 children under 5 years of age.

NGO Attrition (%) Female headed households (%)

CARE 25.0 16.7

DSK (Urban) 45.3 62.9

NETZ 14.1 58.2

PAB 10.9 28.1

SCF 17.2 45.3

UTTARAN 14.1 36.4

Total Rural 16.3 37.3

Total 21.1 40.3

In total 303 households participated in the seven surveys from the initial sample of 384 households, an attrition rate of 21% between surveys 1 and 7.

In the total sample 40.3% of households were female headed (FHHs). Mainly widowed (62.3%) and divorced/abandoned (23.0%).

Mean family size increased significantly from 3.35 in survey 1 to 3.67 in survey 7. FHHs were smaller by, on average, 1.3 family members (4.2 vs 2.9).

Male and female headed households and family size

Only 25.0% of heads of households had attended school significantly more so in male (MHHs, 35.3%) than FHHs (12.1%).

Between surveys 1 and 4 school attendance in children increased significantly from about 76% to 86% and rose to 89% in survey 7.

Schooling

Chronic illness fell significantly between surveys 1 (15.6%) and 4 (4.2%) but there was no change between surveys 4 and 7 (4.8%).

Chronic illness

% Survey 1 4 7 p (1&4) p (1&7) p (4&7)

Head 27.7 7.6 8.6 <0.001 <0.001 ns

All adults 23.2 7.3 8.0 <0.001 <0.001 ns

Children 5-15 5.1 1.0 1.0 0.004 0.003 ns

<5 children 3.3 0.8 0 ns 0.035 ns

Total 15.6 4.2 4.8 <0.001 <0.001 ns

Morbidity status

The health status of family members was determined on the day of the survey and over the previous 7 and 30 days.

Morbidity status (%) of all family member in the previous 30 days

1&7 All <0.001

All adults: fever, cough, eye and skin infections fell between surveys 1, 4 and 7 while passing of worms fell between surveys 1 and 4 only.

In children 5 to 15 years of age: the prevalence of fever and cough both fell between surveys 1 and 4 but not between surveys 4 and 7.

Under 5 year old children: there were reductions in fever and cough and passing of worms.

(%) MHHs FHHs

Survey 1 4 7 1 4 7

Unemployment 5.9 4.6 4.2 6.1 2.8 0.9

Agricultural day labourer 36.0 31.8 31.5 16.5 17.4 15.7

Other day labourer 18.8 9.2 13.7 9.6 11.9 4.3

Domestic maid 0.5 2.9 1.8 31.3 21.1 14.8

Rickshaw 16.5 20.2 18.5 0 0 0

Skilled labour 3.8 4.6 2.4 0.9 1.8 2.6

Fishing/aquaculture 4.8 6.4 7.1 2.6 2.8 2.6

Livestock 0 0 1.8 0 2.8 6.1

Cottage/garment 1.1 0.6 1.2 0.9 1.8 2.6

Petty trade 8.6 16.2 15.5 10.4 18.3 11.3

Begging/scavenging 3.8 3.5 1.2 16.5 11.0 9.6

Housework 0 0 1.2 5.2 8.3 25.2

Employment

MHHs - Petty trading increased

FHHs - Decreased unemployment and domestic maid, but begging still remained an important source of income (9.6%).

The number of days worked fell significantly between surveys 4 and 7 while advanced sale of labour generally fell.

Between surveys 4 and 7 self employment increased by 10% and self employed worked, on average, significantly more days.

(days) Overall MHHs Urban Self vs non-self

Survey 4 7 4 7 4 7 4 7

In the last 7 days 4.43 4.32 4.42 4.05 4.97 4.31 4.99 4.90

In the last 14 days 8.84 8.89 8.83 8.58 10.00 8.66 9.80 10.05

In the last 30 days 18.59 18.78 18.55 18.20 20.77 18.37 20.77 21.55

Hours worked in the last 7 days

6.36 5.84 6.95 6.49 6.00 6.17 6.20 5.58

NB: Red shows significant difference (at least <0.01) between survey 4 and 7

Mean number of days and hours worked by head of household

MHHs - The increase in ownership occurred between surveys 1 and 4

FHHs - ownership increased across all surveys.

(%) MHHs FHHs

Survey 1 4 7 1 4 7

Land owned00.1-2.492.50-4.995.0+- yes total

81.27.75.06.1

18.8

64.615.58.8

11.035.4

65.214.47.2

13.334.8

90.24.14.11.69.8

82.08.25.74.1

18.0

73.84.1

12.39.8

26.2

Cultivated – yes 2.2 2.2 7.2 0 0.8 4.1

Share cropped – yes 4.4 9.3 18.2 0 3.3 4.1

Free use – yes 4.4 10.0 16.0 0 4.1 6.6

Land ownership

Land ownership by head of household

Households owning land increased significantly from 15.2% in survey 1 to 31.4% in survey 7

Owning house: The percentage of households owning their own house increased significantly from 72.6% to 80.2% between surveys 1 and 4 and fell slightly to 78.5% in survey 7.

Home ownership Survey

1 4 7

Own 26.7 25.1 26.4

Rent 12.7 11.9 12.2

Live with parent 2.7 1.0 1.7

Live with parent-in-law 1.0 0.7 0.3

Rent free with family 6.0 4.3 5.6

Rent free non-family 5.0 2.0 1.7

Own house on khas land or someone else’s land 46.0 55.1 52.1

Own any house 72.7 80.2 78.5

Household ownership, size and structure

House size: mean reported size of houses increased from 14.0 square metres in survey 1 to 15.5 square metres in survey 4 and to 16.2 square metres in survey 7, but the increase was only significant in MHHs.

The smallest dwellings were in the urban slums (mean 10 square metres).

House material: There was no significant change in materials used in house construction over this time period; walls were primarily made of grass etc, mud or tin sheet, roofs of tin sheet and floors of mud.

By male and female headed household By NGOs

Electricity: There was no significant change in electricity or water supply between surveys. In rural areas about 95% of households had no electricity supply whereas 85% of urban dwellers had access to electricity.

Water: Nearly all urban households obtained their water from a piped supply or tubewell while over 80% of rural households obtained their water from a tubewell.

Defecation practice

Urban Rural Total

Survey Survey Survey

1 4 7 1 4 7 1 4 7

OpenHangingPitRing/slabSanitary

2.911.414.331.440.0

05.72.9

42.948.6

08.68.6

40.042.9

36.92.2

11.248.5

1.1

19.80.49.0

69.01.9

15.31.94.5

75.03.4

33.03.3

11.646.5

5.6

17.51.08.3

65.77.3

13.52.65.0

70.97.9

Electricity, water supply and defecation practices

Defecation: There was a highly significant reduction in open defecation in rural areas down from 36.9% in survey 1, to 19.8% in survey 4 and 15.3% in survey 7 and concomitant increase in use of ring/slab/sanitary latrine up from 49.6% in survey 1 to 78.4% in survey 7.

Loans: There was no consistent pattern to either the number or amount of loans over the seven surveys.

Loans and cash savings

NB: Five sources of cash loan were identified (i) free informal (ii) informal loans with interest (iii) interest loans from samity (iv) interest loans from microfinance institutions and (v) interest loans from a bank or the Government of Bangladesh.

By male and female headed HH By NGOs

Cash savings: In survey 1, 36% of households had some cash savings increasing to 84% in survey 4 and falling to 81% in survey 7.

The mean amount increased significantly from 489 Taka in survey 1 to 4095 Taka in survey 6 and then fell to 3665 Taka in survey 7.

Urban DSK

UTTARAN after Survey 5

Animal ownership: There was a highly significant increase in animal ownership between surveys 1 and 4 (up from 28.4% to 63.9%) followed by a very slight fall in survey 7 (63.4%).

Assets

Survey p (1&4) p (1&7) p (4&7)

Cattle <0.001 <0.001 <0.001

Calf 0.022 <0.001 <0.001

Goat <0.001 <0.001 ns

Poultry <0.001 <0.001 0.042

Pig ns ns ns

Total <0.001 <0.001 ns

Significant increases in 1&4

NGOs Survey 1 4 7 P (1&4) P (1&7) P (4&7)

CARE 39.6 54.2 60.4 ns 0.031 ns

DSK 2.9 2.9 8.6 ns ns ns

NETZ 29.1 94.5 98.2 <0.001 <0.001 ns

PAB 22.8 56.1 64.9 <0.001 <0.001 ns

SCF 30.2 83.0 71.7 <0.001 <0.001 ns

UTTARAN 38.2 65.5 56.4 0.006 <0.001 ns

Total 28.4 63.0 63.4 <0.001 <0.001 ns

Ownership of any animal by NGO (%)

Mean value of animals by head of household

Mean value of animals by NGO

The value of animals increased significantly between surveys 1, 4 and 7.

There were highly significant increases in the amount spent on purchasing animals between the three surveys in both MHHs and FHHs. Overall there was an eightfold increase in spending on animals.

Mean value of equipment by head of household

Mean value of equipment by NGO

Ownership of working equipment: increased from 56.1% in survey 1 to 74.6% in survey 4 and 84.5% in survey 7.

Increases occurred in both MHHs and FHHs and in all three surveys MHHs owned more working equipment (over 90% of MHHs owned working equipment in survey 7 compared with 76% of FHHs).

The value of working equipment only increased significantly between surveys 1 and 4.

Working equipment ownership

1 4 7 p (1&4) p (1&7) p (4&7)

Net 9.9 17.8 18.5 <0.001 <0.001 ns

Rickshaw 4.3 15.8 18.5 <0.001 <0.001 ns

Boat 1.0 2.0 2.6 ns ns ns

Sewing Machine 0.3 4.3 4.6 <0.001 <0.001 ns

Cottage industry 0.3 1.3 - ns - -

Agri equipment (more than 1) 49.5 66.7 79.2 <0.001 <0.001 <0.001

Total ownership 56.1 74.6 84.5 <0.001 <0.001 <0.001

Ownership of any working equipment

1 4 7 p (1&4) p (1&7) p (4&7)

CARE 58.3 81.3 87.5 0.013 <0.001 ns

DSK 20.0 37.1 37.1 ns ns ns

NETZ 70.9 76.4 92.7 ns 0.002 0.022

PAB 59.6 73.6 92.9 ns <0.001 ns

SCF 50.9 75.5 86.8 0.004 <0.001 ns

UTTARAN 63.6 90.9 92.7 0.001 <0.001 ns

Total ownership 56.1 74.6 84.5 <0.001 <0.001 <0.001

Mean number of household goods owned by head of household

Mean number of household goods owned by NGO

Ownership of household belongings: increased significantly (there were large increases in ownership of a mobile phone, wooden box, mattress and chair), more so in MHHs

Overall the number of household goods owned increased from 3.2 (maximum 13) in survey 1 to 4.6 in survey 7.

Mean value of household goods by head of household

Mean value of household goods by NGO

The value of household equipment increased significantly between surveys 1, 4 and 7.

Total assets: Overall the value of assets rose by, on average, 7000 Taka between surveys 1 and 4, and by 3000 Taka between surveys 4 and 7 (Taka 2,311, 9,322 and 12,413 in survey 1, 4 and 7 respectively)

MHHs had significantly higher value of assets in surveys 1 and 7 and the gap was widening.

Average amount spent on assets

1 4 7 p (1&4) p (1&7) p (4&7)

Animals 1293 6899 9201 <0.001 <0.001 <0.001

Equipment 263 2045 2086 <0.001 <0.001 ns

Household belongings 1681 3482 4851 <0.001 <0.001 ns

Household belongings + shop* - 4329 6797 - - <0.001

Total assets 2311 9322 12413 <0.001 <0.001 <0.001

Total assets + shop* - 10166 14360 - - <0.001

*the question conducted only in surveys 4 and 7

Mean value of total assets by head of household

Mean value of total assets by NGO

Overall mean income increased consistently from 1,776 Taka/month in survey 1 to 3,298 Taka/month in survey 7 - there was not consistent improvement within urban and rural areas. (These increased income does not take into account the inflation between March 2010 and March 2012)

Income

The mean income for male and female headed households by survey was calculated based on HIES criteria which do not include in-kind income.

Mean income in household per month by MHHs and FHHs

Mean income in household per month by NGO

Mean income pppd by MHHs and FHHs Mean income pppd by NGO

Over the seven surveys the mean per capita income in the urban area was significantly higher than the rural areas.

Rural MHHs earned on average 5.4 Taka pppd more than FHHs (23.9 versus 18.5 Taka pppd, respectively). Households from CARE and UTTARAN had the highest mean income pppd (24.2 and 26.9, respectively) and SCF the lowest (17.4 Taka pppd).

MHHs per capita income (27.4 Taka pppd) was significantly higher than FHHs (21.4 Taka pppd) and the difference was apparent in all seven surveys.

Urban Rural Total

MHHs FHHs Total MHHs FHHs Total MMHs FHHs Total

1 3428 2514 2853 2093 867 1635 2189 1164 1776

2 4527 3570 3925 2013 900 1603 2193 1390 1873

3 6051 3745 4627 1858 888 1494 2160 1383 1848

4 6439 4531 5240 3130 1454 2505 3368 2009 2821

5 6423 3303 4462 3453 1594 2760 3667 1902 2956

6 5721 2868 3927 3624 1892 2978 3774 2068 3087

7 6595 4701 5405 3698 1888 3023 3906 2396 3298

Urban Rural Total

MHHs FHHs Total MHHs FHHs Total MHHs FHHs Total

1 25.3 25.8 25.6 19.4 12.8 17.0 19.9 15.1 18.0

2 35.9 34.7 35.1 18.3 12.8 16.3 19.6 16.8 18.5

3 46.7 37.1 40.6 16.3 12.9 15.1 18.5 17.2 18.0

4 52.0 45.4 47.9 26.2 19.1 23.6 28.1 23.8 26.4

5 54.2 33.0 40.9 29.9 19.6 26.1 31.6 22.0 27.8

6 46.2 28.0 34.7 30.1 22.4 27.2 31.3 23.4 28.1

7 53.1 45.9 48.6 29.9 25.2 28.2 31.6 28.9 30.5

Mean income per household

Mean income per capita

*Red shows significant difference between MHHs and FHHs

FHHs had significantly greater in-kind income than MHHs for the first three surveys but thereafter MHHs had greater in-kind income.

NETZ had the highest in-kind income in surveys 6 and 7.

In-kind income

The percentage that in-kind income contributed to total income in the total sample and it ranged between 18% and 23% in the total sample.

In FHHs the percentage tended to fall from survey 1 to survey 7 and to rise in MHHs. There was no consistent pattern by NGOs.

Expenditure

Urban Rural Total

Survey MHHs FHHs Total MHHs FHHs Total MHHs FHHs Total

1 4410 4202 4279 2342 1464 2014 2491 1957 2276

2 4136 3277 3592 2037 1179 1717 2168 1520 1909

3 5985 4772 5281 2406 1250 1980 2674 1816 2338

4 6391 4401 5140 2926 1476 2385 3175 2004 2704

5 5562 4343 4796 1376 1444 1503 2943 2098 2601

6 6253 3857 4702 2992 1841 2564 3211 2208 2806

7 7518 4710 5753 2853 1707 2425 3188 2248 2810

Monthly mean expenditure (HIES, Taka per month)

Urban Rural Total

Survey MHHs FHHs Total MHHs FHHs Total MHHs FHHs Total

1 34.2 47.3 42.4 21.6 25.0 22.9 22.5 29.0 25.1

2 31.8 32.0 31.9 18.5 17.3 18.1 19.4 19.6 19.5

3 45.2 46.8 46.1 21.7 18.3 20.4 23.4 22.9 23.2

4 50.8 46.3 48.0 25.7 19.7 23.5 27.5 24.5 26.3

5 45.8 43.9 44.7 23.1 20.6 22.2 24.8 24.8 24.8

6 47.7 38.2 41.5 25.0 22.9 24.2 26.6 25.6 26.2

7 58.3 45.7 50.4 23.4 22.8 23.2 25.9 26.9 26.3

Monthly mean expenditure per capita (HIES, Taka per month)

*Red shows significant difference between MHHs and FHHs

Mean total expenditure pppd by head of household

Mean total expenditure pppd by NGO

Total per capita expenditure increased significantly over the seven surveys from a low in survey 2 of 19.5 Taka pppd to the highest in survey 7 of 26.3 Taka pppd.

There were no significant differences between MHHs and FHHs.

Overall the urban areas had greatest expenditure. The rural analyses indicated no significant differences in overall means, by head of household or between NGOs over the seven surveys.

Mean food expenditure pppd by MHHs and FHHs

Mean food expenditure pppd by NGO

Food expenditure

UTTARAN moved from having the lowest mean of any rural NGO in survey 1 to having the highest mean food expenditure of the rural NGOs in survey 7

MHHs spent more on food, on average, than FHHs (17.5 vs 15.5 Taka pppd), although the difference appeared to be decreasing

Household expenditure

Mean household expenditure pppd by MHHs and FHHs

Mean household expenditure pppd by NGO

There was no significant difference between MHHs and FHHs

Significantly higher spending in the urban area was found, but there were no significant differences between the overall rural means by NGOs

Work-related expenditure

Mean work-related expenditure pppd by MHHs and FHHs

Mean work-related expenditure pppd by NGO

The amount spent on work-related items increased significantly across the surveys from 20 Taka to 106 Taka between surveys 1 and 7

Considerably more spent in the urban areas, on average, than in the rural areas (mean 193 versus 48 Taka, respectively) although the gap appears to be lessening

Households went from a debit in surveys 1 to 3 (-437, -33, -52 Taka/month respectively) to increasing credit in surveys 4 to 7 (+565, +891, +989 and +1076 Taka/month, respectively).

Mean monthly net income by MHHs and FHHs Mean monthly net income by NGOs

Difference between income and expenditure (net income)

MHHs were significantly more in credit than FHHs over the 7 surveys by, on average, 400 Taka/month.

When the average of the seven surveys was calculated all NGOs were in credit ranging from 3 Taka/month to 778 Taka/month.

Household food intake and security

Rice was eaten by nearly all households in all seven surveys. Comparison of March 2011 and March 2013 revealed an increase in fresh fish consumption, pulses, green and other vegetables.

Number of days food consumed

Survey p

1 2 3 4 5 6 7

Rice 0 1 2 3+

000

100

00

0.399.7

0.30.3

098.3

000

100

0.30.3

099.3

000

100

000

100

-

Flour 0 1 2 3+

71.611.6

8.38.6

63.717.311.7

7.3

67.016.210.9

5.9

78.27.96.96.9

68.310.910.610.2

63.414.510.211.9

77.68.96.37.3

<0.001

Pulse 0 1 2 3+

62.023.8

9.25.0

38.033.021.0

8.0

36.626.423.413.5

55.424.114.2

6.3

36.621.823.418.2

46.515.521.116.8

43.621.520.514.5

<0.001

Number of days food consumed

Survey p

1 2 3 4 5 6 7

Potato 0 1 2 3+

1.71,35.9

91.1

3.03.0

10.783.3

8.68.3

13.969.2

0.70

0.399.0

1.72.05.9

90.4

4.61.76.6

87.1

0.71.02.0

96.4

<0.001

Green vegetables 0 1 2 3+

17.816.829.735.6

6.711.326.355.7

5.614.628.851.0

14.222.831.731.4

4.010.229.756.1

4.614.527.753.1

7.316.237.039.6

<0.001

Other vegetables 0 1 2 3+

5.34.0

23.467.3

5.76.7

22.365.3

17.28.3

19.954.6

9.610.618.861.1

5.610.617.266.7

1.73.68.9

85.8

3.05.3

20.171.6

<0.001

Fruits 0 1 2 3+

92.15.61.01.3

57.027.3

7.78.0

56.617.514.611.3

74.38.9

11.25.6

33.724.421.120.8

57.416.512.913.2

70.012.2

9.97.9

<0.001

Number of days food consumed

Survey p

1 2 3 4 5 6 7

Milk 0 1 2 3+

92.45.01.01.7

85.37.74.03.0

86.85.04.34.0

85.58.61.74.3

77.28.93.6

10.2

75.910.9

4.68.6

81.55.64.38.6

0.007

Eggs 0 1 2 3+

70.623.1

3.62.6

54.031.010.7

4.3

57.021.216.9

5.0

42.224.818.514.5

38.928.716.815.5

36.322.821.119.8

35.028.422.114.5

<0.001

Fresh fish 0 1 2 3+

38.035.016.510.6

20.734.021.723.7

9.924.528.137.4

24.827.121.526.7

17.823.118.840.3

12.514.521.551.5

16.221.119.543.2

<0.001

Dried fish 0 1 2 3+

74.39.99.26.6

80.79.35.05.0

81.16.34.38.3

79.97.65.96.6

76.65.37.3

10.9

76.28.37.97.6

77.26.98.37.6

ns

Number of days food consumed

Survey p

1 2 3 4 5 6 7

Poultry 0 1 2 3+

96.03.00.30.7

92.36.70.30.7

91.17.90.70.3

84.811.2

3.30.7

84.810.6

3.61.0

80.913.9

4.31.0

79.213.2

5.32.3

<0.001

Meat 0 1 2 3+

90.17.61.70.7

92.75.00.71.7

97.71.00.31.0

92.46.60.70.3

88.49.22.00.3

84.59.92.03.6

82.811.9

4.31.0

<0.001

Mean foods eaten 5.9 7.1 7.0 6.7 7.7 7.6 7.3 <0.001

Mean food diversity

4.3 5.0 4.9 4.8 5.3 5.3 5.2 <0.001

Overall food diversity rose from 4.3 in survey 1 to 5.3 in surveys 5 and 6 before falling slightly to 5.2 in survey 7.

There was no significant difference between MHHs and FHHs.

Mean number of food types consumed by MHHs and FHHs

Mean number of food types consumed by NGO

NB: The extent of household food diversity was determined in two ways (a) based on the mean of the number of foods eaten (maximum 13) and (b) based on the 7 food groups (grains, roots and tubers, legumes and nuts, dairy products, flesh foods, eggs, vitamin A rich fruits and vegetables and other fruit and vegetables) as defined by WHO and UNICEF.

Mean food coping strategy by MHHs and FHHs

Mean food coping strategy by NGO

The households were asked about the coping strategies they used as a result of financial hardship in the seven days prior to the survey. There were significant improvements in all 10 strategies between surveys 1 and 7.

Overall the responses were quite consistent. More women in survey 7 felt there were people who could be relied upon to help and less women in surveys 4 and 7 felt frightened of moving alone outside their village.

Male Females

Survey Agree Neither Disagree Agree Neither Disagree

Investing in children’s education is the best use of my scarce resources

147

97.685.795.2

2.410.7

2.4

-3.62.4

97.685.795.2

2.410.7

2.4

-3.62.4

If you earn money or receive a loan, you decide how to use the money

147

73.879.566.7

2.44.81.2

23.815.732.1

73.879.566.7

2.44.81.2

23.815.732.1

You feel confident that you can face whatever the future brings/holds

147

73.878.666.7

3.66.01.2

22.615.517.9

73.878.666.7

3.66.01.2

22.615.517.9

What you say matters in decisions in your household

147

98.898.897.6

---

1.21.22.4

98.898.897.6

---

1.21.22.4

There are people outside your family you can rely on for help

147

54.857.157.1

6.02.44.8

39.340.538.1

54.857.157.1

6.02.44.8

39.340.538.1

Social empowerment

The mean weights of head of household increased significantly over the three surveys in both male and female adults and the average weight gain between surveys 1 and 7 was 0.7kg.

Mean BMI also increased significantly across the three surveys by 0.4 kgm-2 and there were concomitant reduction in CED percentages.

Mean haemoglobin did not show any significant change over the surveys but the percentage who were anaemic fell in males but increased slightly in females.

Adult nutritional status

Average + 0.7kg

Average + 0.4 kgm-2

Weight BMI Haemoglobin

Male Female Total

Survey 1 4 7 1 4 7 1 4 7

Mean values

Weight 46.6 46.9 47.7 41.1 41.4 41.6 43.6 43.9 44.3

BMI 18.2 18.2 18.5 18.6 18.8 19.0 18.4 18.5 18.8

Haemoglobin 132.3 134.4 133.7 116.5 115.3 116.5 123.6 123.9 124.2

Categories

BMI <18.5 52.7 49.5 47.3 56.1 54.4 50.9 54.6 52.2 49.3

Anaemic 39.6 33.0 31.9 57.9 58.8 59.6 49.8 47.3 47.3

Decreased total 5.3%

Decreased in Male 7.7%(Female ns)

There were no significant changes between surveys although in the total sample the percentage with CED and anaemia fell by nearly 5%.

Head Survey CED + anaemic CED only Anaemic only Normal

Total 147

32.227.327.3

22.424.922.0

17.620.020.0

27.827.830.7

There was no significant change in mean height-for-age and weight-for-age across the three surveys.

There was a highly significant improvement in haemoglobin concentration with an increase in mean of over 8 g/l.

Child nutritional status

Average + 8.0 g/L

Mean Survey Prevalence Survey

1 4 7 1 4 7

Height-for-age -1.94 -2.02 -1.81 Stunting 52.0 49.3 42.7

Weight-for-age -1.89 -1.95 -1.90 Underweight 44.6 49.3 50.7

Weight-for-height -0.88 -0.96 -1.14 Wasted 20.5 13.3 20.5

Haemoglobin 106.4 111.1 114.7 Anaemic 60.8 45.3 36.0

The percentage of children who were stunted fell significantly between surveys 1 and 7 while the percentage of children who were underweight increased; the prevalence of wasting reduced between surveys 1 and 4 but increased back to baseline level in survey 7.

The prevalence of childhood anaemia fell significantly over the surveys.

Stunting-9.3%

Anaemia -24.8%

Summary ✔✔= significant improvement, ✔ = trend of improvement

1&4 1&7 4&7

Family size ✔ ✔✔ ✔

Illness - ✔✔ ✔✔

Land ✔✔ ✔✔ ✔

House ownership - ✔ -

House material - - -

Loan - - -

Cash savings ✔✔ ✔ ✔

Assets ✔✔ ✔✔ ✔✔

Income ✔✔ ✔✔ ✔✔

Expenditures - - -

Net income ✔✔ ✔✔ ✔✔

Food ✔✔ ✔✔ ✔✔

Adult weight and BMI ✔✔ ✔✔ ✔✔

Adult anaemia - - -

Child z-scores - - -

Child stunting - ✔✔ -

Child anaemia ✔✔ ✔✔ ✔✔

(1) Many indicators of economical situation in households (e.g. land, saving, asset, income, expenditure) showed improvement from 1 year of the intervention and generally keep to show the upward trend after 2 years.

(4) Household food intake and security also improved sharply after 1 year of intervention. BMI and weight in adults showed significant improvement, but not hemoglobin - intervention increased energy intake but still do not improve ‘quality’ of food such as animal protein.

(3) Amount of cash savings, income/expenditure increased, but no change of loans

(2) Number of asset increased from survey 1 to 4 but not in survey 7, but the value increased in survey 7 – how much the assets generate income?

Discussions

(5) After 2 years of intervention, child chronic undernutrition (stunting) showed improvement which may related the reduction of morbidity. However they also showed a sign of acute undernutrition (wasting and underweight) at survey 7 – perhaps other factors such as breastfeeding and weaning practice and poor energy intake may also related.

(6) Child anaemia status improved at surveys 4 and 7 – less than national average (i.e. 68% of under 5 years of age in rural area).

More opinions?

Discussions

Areas worth investigating are:-

1. Do households sustain themselves about the poverty line or does churning poverty occur (which might be seasonal or the result of some health shock or other life event)?

2. Is there any relationship between an absolute measure of poverty (the poverty line) and multidimensional poverty in the ultra poor and is this homogeneous in urban and rural areas?

3. How well does an absolute measure of poverty predict multidimensional poverty in the ultra poor?

How can we know whether there is improvement in the lifestyle of the ultra poor?

How they are close to the above poverty line? – measurement of improvement

Chronic poverty is commonly defined as ‘a state of poverty where individuals, households or regions are trapped in severe and multi-dimensional poverty for an extended period of time, perhaps even across generations’. Duration, multidimensionality and severity are therefore the key characteristics of chronic poverty, and these are mutually reinforcing characteristics (Hulme et al., 2001).

Three measures of income poverty;

Poverty line

Population ranked by consumption

Poverty Gap= How much would have to be transferred to bring their expenditure (or income) up to the poverty line

(1) Poor or not poor (yes or no, Headcount index)(2) Depth of poverty (Poverty Gap Index, PGI)(3) Inequality of poverty (Squared Poverty Gap Index, SPGI)

All indicators use ‘poverty line’

Poverty Gap and Poverty Gap Index

Individual A B C D Sum Poverty Gap

Index

Income 100 100 150 150

Poverty Gap 25 25 0 0

PG / Poverty line 25 / 125 = 0.20

25 / 125 = 0.20

0 0 0.20 + 0.20 =

0.40

0.40 / 4 = 0.10

(10%)

e.g. Poverty line is 125

Income 80 120 150 150

Poverty Gap 45 5 0 0

PG / Poverty line 45 / 125 = 0.36

5 / 125 = 0.04

0 0 0.36 + 0.04 =

0.40

0.40 / 4 = 0.10

(10%)

Squared Poverty Gap Index

Individual A B C D Sum Poverty Gap

Index

Income 100 100 150 150

Poverty Gap 25 25 0 0

PG / Poverty line 25 / 125 = 0.20

25 / 125 = 0.20

0 0

Squared Poverty Gap

0.202 =0.04

0.202 =0.04

0 0 0.08 0.08 / 4 =0.02 (2%)

Poverty line is 125

Income 80 120 150 150

Poverty Gap 45 5 0 0

PG / Poverty line 45 / 125 = 0.36

5 / 125 = 0.04

0 0

Squared Poverty Gap

0.362 =0.1296

0.042 =0.0016

0 0 0.1312 0.1312 / 4 =0.0328 (3.28%)

Thank you to our beneficiaries and all the staff who contributed to making these surveys possible!