Dr Rie Goto from Cambridge gave a presentation based on the outputs of Survey 7 and she has enhanced the powerpoint used on the basis of feedback from Shiree.

1. 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

2. shiree Change Monitoring System (CMS)
Shiree has robust survey, monitoring and evaluation structure
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 To provide in depth socio-economic and nutritional
Anthropometric data allowing an assessment of longer term change
Surveys and the impact of project interventions
– random sample in Scale Fund NGO beneficiaries
CMS 4 Participatory Review To provide a forum for beneficiaries to explain changes
and Project Analysis 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
+ CMS6

3. shiree Change Monitoring System (CMS)
Shiree has robust survey, monitoring and evaluation structure
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 To provide in depth socio-economic and nutritional
Anthropometric data allowing an assessment of longer term change
Surveys and the impact of project interventions
– random sample in Scale Fund NGO beneficiaries
CMS 4 Participatory Review To provide a forum for beneficiaries to explain changes
and Project Analysis 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

4. 6 NGOs in Round One Phase One Scale Fund
CARE ‘Community Led, Voice and Value Chain’ 20,000
Community-led development, Social economic HHs
empowerment, Increased wider policy-making process
Uttaran ‘Khas Land Transfar and Income Generation’ 12,000
Khas land (public land) transfer to the landless people,
Reduced corruption, Building income and livelihood capacity
NETZ ‘Asset Transfer and Land’ 9,000
Targeting women and ethnic minority (Adibashi), Asset
transfer and increased income, Reduced vulnerability
Practical Action ‘Technology Transfer, Skills Development and Market’ 16,850
Bangladesh Technology and skill development of sandbar cropping in
(PAB) char lands (riverine islands), Secured market access
Save the ‘Social Entitlements, Asset Transfer and Market’ 15,000
Children (SCF) Enhanced capacity to access to safety-net, Assets and
livelihood transfer, Access to health, education water facility
Dushtha ‘Social Mobilisation, Asset Transfer and Small Business’ 10,000
Shasthya Develop technical skill and business capacities, Improve
Kendra (DSK) water and health using common assets and services
Three additional Round 2 Scale Fund NGOs (Concern, Oxfam, Caritas) commenced
work in 2012 and will be analysed in future reports.

5. CARE:
Gaibandha,
PAB:
Nilphamari,
Gaibandha,
Rangpur,
Nilphamari,
Lalmonirhat
Rangpur,
Lalmonirhat
NETZ:
Rajshahi, Naogaon, DSK:
Chapai-Nawabgonj Dhaka slums
(Karail, Kamrangichar)
Uttaran:
Satkira, Khulna SCF:
Khulna, Bagerhat

6. Design of annual panel nutrition surveys
Cohort 1 - 384 households (64 HHs from Phase One 6 NGOs)
Cohort 2 - additional cohort from urban slum (DSK) and Adivashi (NETZ) in 2011
Cohort 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 384 473 617 555 499 449
Within subject change Comparing with additional cohort
Testing for recruitment homogeneity 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.

7. 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

8. Total 45 research members
including international nutrition
advisor (Cambridge University),
shiree staff, NGO Research
Assistants, enumerators and
measurers
Training of enumerating and
anthropometric measurement
and performing careful
quality control

9. 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)

10. Socio-economic
questionnaire
Socio-demographic characteristics of the household (including age, marital
status, household/family size, education, disability, and occupation)
Morbidity report
Household and homestead land ownership
House condition (size, structure, source of drinking water, electricity and toilet
facilities)
Cash loans and savings
Assets – animals, working equipment and belongings
Income – cash and in-kind
Expenditure – covering food, household and work related
Food intake and food security

11. Results
Sample attrition for analyses
Number of households which completed information all through surveys from
March 2010
March July October March July November March
2010 2010 2010 2011 2011 2011 2012
Cohort Survey Survey Survey Survey Survey Survey Survey
1 2 3 4 5 6 7
1 384 376 352 336 329 316 303
2 128 (128) (128) (128)
3 192
Nutrition Yes - - Yes - - Yes
SES Yes Yes Yes Yes Yes Yes Yes

12. 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.
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.

13. Male and female headed households and family size
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).
Schooling
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.

14. Chronic illness
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%).
% 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

15. 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 All adults: fever, cough, eye and skin
infections fell between surveys 1, 4
and 7 while passing of worms fell
1&7 All <0.001 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.

16. Employment
(%) 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
MHHs - Petty trading increased
FHHs - Decreased unemployment and domestic maid, but begging still
remained an important source of income (9.6%).

17. 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.
Mean number of days and hours worked by head of household
(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 6.36 5.84 6.95 6.49 6.00 6.17 6.20 5.58
7 days
NB: Red shows significant difference (at least <0.01) between survey 4 and 7

18. Land ownership
Households owning land increased significantly from 15.2% in survey 1 to
31.4% in survey 7
MHHs - The increase in ownership occurred between surveys 1 and 4
FHHs - ownership increased across all surveys.
Land ownership by head of household
(%) MHHs FHHs
Survey 1 4 7 1 4 7
Land owned
0 81.2 64.6 65.2 90.2 82.0 73.8
0.1-2.49 7.7 15.5 14.4 4.1 8.2 4.1
2.50-4.99 5.0 8.8 7.2 4.1 5.7 12.3
5.0+ 6.1 11.0 13.3 1.6 4.1 9.8
- yes total 18.8 35.4 34.8 9.8 18.0 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

19. Household ownership, size and structure
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

20. 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).
By male and female headed household By NGOs
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.

21. Electricity, water supply and defecation practices
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: 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.
Defecation Urban Rural Total
practice
Survey Survey Survey
1 4 7 1 4 7 1 4 7
Open 2.9 0 0 36.9 19.8 15.3 33.0 17.5 13.5
Hanging 11.4 5.7 8.6 2.2 0.4 1.9 3.3 1.0 2.6
Pit 14.3 2.9 8.6 11.2 9.0 4.5 11.6 8.3 5.0
Ring/slab 31.4 42.9 40.0 48.5 69.0 75.0 46.5 65.7 70.9
Sanitary 40.0 48.6 42.9 1.1 1.9 3.4 5.6 7.3 7.9

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

23. 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.
By male and female headed HH By NGOs
Urban DSK
UTTARAN
after Survey 5

24. Assets
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%).
Significant
increases
in 1&4
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

25. Ownership of any animal by NGO (%)
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

26. 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.
The value of animals increased significantly between surveys 1, 4 and 7.
Mean value of animals by head of Mean value of animals by NGO
household

27. 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.
Mean value of equipment by head of Mean value of equipment by NGO
household

28. Working equipment 1 4 7 p (1&4) p (1&7) p (4&7)
ownership
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 1 4 7 p (1&4) p (1&7) p (4&7)
working equipment
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

29. 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 number of household goods Mean number of household goods
owned by head of household owned by NGO

30. The value of household equipment increased significantly between
surveys 1, 4 and 7.
Mean value of household goods by Mean value of household goods by
head of household NGO

31. 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 1 4 7 p (1&4) p (1&7) p (4&7)
assets
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

32. Mean value of total assets by head Mean value of total assets by NGO
of household

33. 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.
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)
Mean income in household per month by Mean income in household per month by NGO
MHHs and FHHs

34. 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.
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).
Mean income pppd by MHHs and FHHs Mean income pppd by NGO

35. Mean income per household *Red shows significant difference between MHHs and FHHs
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
Mean income per capita
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

36. In-kind income
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.

37. 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.

38. Expenditure *Red shows significant difference between MHHs and FHHs
Monthly mean expenditure (HIES, Taka per month)
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 per capita (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

39. 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 total expenditure pppd by head Mean total expenditure pppd by NGO
of household

40. Food expenditure
Mean food expenditure pppd by MHHs Mean food expenditure pppd by NGO
and FHHs
MHHs spent more on food, on average, than FHHs (17.5 vs 15.5 Taka pppd),
although the difference appeared to be decreasing
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

41. Household expenditure
Mean household expenditure pppd by Mean household expenditure pppd by
MHHs and FHHs 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

42. Work-related expenditure
Mean work-related expenditure pppd by Mean work-related expenditure pppd by
MHHs and FHHs 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

43. Difference between income and expenditure (net income)
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).
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.
Mean monthly net income by MHHs and FHHs Mean monthly net income by NGOs

44. 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 Survey p
food consumed
1 2 3 4 5 6 7
Rice -
0 0 0 0.3 0 0.3 0 0
1 0 0 0.3 0 0.3 0 0
2 0 0.3 0 0 0 0 0
3+ 100 99.7 98.3 100 99.3 100 100
Flour <0.001
0 71.6 63.7 67.0 78.2 68.3 63.4 77.6
1 11.6 17.3 16.2 7.9 10.9 14.5 8.9
2 8.3 11.7 10.9 6.9 10.6 10.2 6.3
3+ 8.6 7.3 5.9 6.9 10.2 11.9 7.3
Pulse <0.001
0 62.0 38.0 36.6 55.4 36.6 46.5 43.6
1 23.8 33.0 26.4 24.1 21.8 15.5 21.5
2 9.2 21.0 23.4 14.2 23.4 21.1 20.5
3+ 5.0 8.0 13.5 6.3 18.2 16.8 14.5

45. Number of days Survey p
food consumed
1 2 3 4 5 6 7
Potato <0.001
0 1.7 3.0 8.6 0.7 1.7 4.6 0.7
1 1,3 3.0 8.3 0 2.0 1.7 1.0
2 5.9 10.7 13.9 0.3 5.9 6.6 2.0
3+ 91.1 83.3 69.2 99.0 90.4 87.1 96.4
Green vegetables <0.001
0 17.8 6.7 5.6 14.2 4.0 4.6 7.3
1 16.8 11.3 14.6 22.8 10.2 14.5 16.2
2 29.7 26.3 28.8 31.7 29.7 27.7 37.0
3+ 35.6 55.7 51.0 31.4 56.1 53.1 39.6
Other vegetables <0.001
0 5.3 5.7 17.2 9.6 5.6 1.7 3.0
1 4.0 6.7 8.3 10.6 10.6 3.6 5.3
2 23.4 22.3 19.9 18.8 17.2 8.9 20.1
3+ 67.3 65.3 54.6 61.1 66.7 85.8 71.6
Fruits <0.001
0 92.1 57.0 56.6 74.3 33.7 57.4 70.0
1 5.6 27.3 17.5 8.9 24.4 16.5 12.2
2 1.0 7.7 14.6 11.2 21.1 12.9 9.9
3+ 1.3 8.0 11.3 5.6 20.8 13.2 7.9

46. Number of days Survey p
food consumed
1 2 3 4 5 6 7
Milk 0.007
0 92.4 85.3 86.8 85.5 77.2 75.9 81.5
1 5.0 7.7 5.0 8.6 8.9 10.9 5.6
2 1.0 4.0 4.3 1.7 3.6 4.6 4.3
3+ 1.7 3.0 4.0 4.3 10.2 8.6 8.6
Eggs <0.001
0 70.6 54.0 57.0 42.2 38.9 36.3 35.0
1 23.1 31.0 21.2 24.8 28.7 22.8 28.4
2 3.6 10.7 16.9 18.5 16.8 21.1 22.1
3+ 2.6 4.3 5.0 14.5 15.5 19.8 14.5
Fresh fish <0.001
0 38.0 20.7 9.9 24.8 17.8 12.5 16.2
1 35.0 34.0 24.5 27.1 23.1 14.5 21.1
2 16.5 21.7 28.1 21.5 18.8 21.5 19.5
3+ 10.6 23.7 37.4 26.7 40.3 51.5 43.2
Dried fish ns
0 74.3 80.7 81.1 79.9 76.6 76.2 77.2
1 9.9 9.3 6.3 7.6 5.3 8.3 6.9
2 9.2 5.0 4.3 5.9 7.3 7.9 8.3
3+ 6.6 5.0 8.3 6.6 10.9 7.6 7.6

47. Number of days Survey p
food consumed
1 2 3 4 5 6 7
Poultry <0.001
0 96.0 92.3 91.1 84.8 84.8 80.9 79.2
1 3.0 6.7 7.9 11.2 10.6 13.9 13.2
2 0.3 0.3 0.7 3.3 3.6 4.3 5.3
3+ 0.7 0.7 0.3 0.7 1.0 1.0 2.3
Meat <0.001
0 90.1 92.7 97.7 92.4 88.4 84.5 82.8
1 7.6 5.0 1.0 6.6 9.2 9.9 11.9
2 1.7 0.7 0.3 0.7 2.0 2.0 4.3
3+ 0.7 1.7 1.0 0.3 0.3 3.6 1.0
Mean foods eaten 5.9 7.1 7.0 6.7 7.7 7.6 7.3 <0.001
Mean food 4.3 5.0 4.9 4.8 5.3 5.3 5.2 <0.001
diversity

48. 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 Mean number of food types consumed by NGO
by MHHs and FHHs
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.

49. 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.
Mean food coping strategy by MHHs and Mean food coping strategy by NGO
FHHs

50. Social empowerment
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 1 97.6 2.4 - 97.6 2.4 -
education is the best use of 4 85.7 10.7 3.6 85.7 10.7 3.6
my scarce resources 7 95.2 2.4 2.4 95.2 2.4 2.4
If you earn money or 1 73.8 2.4 23.8 73.8 2.4 23.8
receive a loan, you decide 4 79.5 4.8 15.7 79.5 4.8 15.7
how to use the money 7 66.7 1.2 32.1 66.7 1.2 32.1
You feel confident that you 1 73.8 3.6 22.6 73.8 3.6 22.6
can face whatever the 4 78.6 6.0 15.5 78.6 6.0 15.5
future brings/holds 7 66.7 1.2 17.9 66.7 1.2 17.9
What you say matters in 1 98.8 - 1.2 98.8 - 1.2
decisions in your 4 98.8 - 1.2 98.8 - 1.2
household 7 97.6 - 2.4 97.6 - 2.4
There are people outside 1 54.8 6.0 39.3 54.8 6.0 39.3
your family you can rely on 4 57.1 2.4 40.5 57.1 2.4 40.5
for help 7 57.1 4.8 38.1 57.1 4.8 38.1

51. Adult nutritional status
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.
Weight BMI Haemoglobin
Average Average
+ 0.7kg + 0.4 kgm-2

52. Decreased
total 5.3%
Decreased in
Male 7.7%
(Female ns)
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

53. 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 1 32.2 22.4 17.6 27.8
4 27.3 24.9 20.0 27.8
7 27.3 22.0 20.0 30.7

54. Child nutritional status
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.
Average
+ 8.0 g/L

55. The percentage of children who were
Anaemia
stunted fell significantly between
-24.8%
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 Stunting
survey 7. -9.3%
The prevalence of childhood anaemia
fell significantly over the surveys.
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

56. 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 ✔✔ ✔✔ ✔✔

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

58. 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?

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

60. 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).

61. Three measures of income poverty;
(1) Poor or not poor (yes or no, Headcount index)
All indicators use
(2) Depth of poverty (Poverty Gap Index, PGI)
‘poverty line’
(3) Inequality of poverty (Squared Poverty Gap Index, SPGI)
Poverty Gap
= How much would have to be
transferred to bring their expenditure
(or income) up to the poverty line
Poverty line
Population ranked by consumption

62. Poverty Gap and Poverty Gap Index
e.g. Poverty line is 125
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 = 25 / 125 = 0 0 0.20 + 0.40 / 4 =
0.20 0.20 0.20 = 0.10
0.40 (10%)
Income 80 120 150 150
Poverty Gap 45 5 0 0
PG / Poverty line 45 / 125 = 5 / 125 = 0 0 0.36 + 0.40 / 4 =
0.36 0.04 0.04 = 0.10
0.40 (10%)

63. Squared Poverty Gap Index Poverty line is 125
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 = 25 / 125 = 0 0
0.20 0.20
Squared Poverty 0.202 0.202 0 0 0.08 0.08 / 4
Gap =0.04 =0.04 =0.02
(2%)
Income 80 120 150 150
Poverty Gap 45 5 0 0
PG / Poverty line 45 / 125 = 5 / 125 = 0 0
0.36 0.04
Squared Poverty 0.362 0.042 0 0 0.1312 0.1312 / 4
Gap =0.1296 =0.0016 =0.0328
(3.28%)

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