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Combining health and social protection measures to reach the ultra ...

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Access <strong>to</strong> <strong>health</strong>2002 2005 Diff.SUP NSUP Difference SUP NSUP Difference in diff(1) (2) (3=1-2) (4) (5) (6=4-5) (7=6-3)Prevalence of illness 15.21 14.17 1.04* 14.17 14.45 -0.28 -1.32*(% people sick in last 15 days)Workdays lost due <strong>to</strong> 1.28 1.47 -0.19 2.96 2.66 0.31 0.50*illness (mean)Average expenditure 76.26 148.10 -71.84** 127.47 112.64 14.83 86.67**on illness (doc<strong>to</strong>rs’fees+medicine)Average expenditure 25.34 52.42 -27.08 27.08 22.48 4.60 31.68*on transport for medicalattention*, ** denote significance at less than 5 <strong>and</strong> 1% level respectivelyTable 1: Fac<strong>to</strong>rs affecting <strong>health</strong>(Rabbani et al. 2006)that with a lower borrower-member ratio <strong>and</strong> relativelysmaller sized credit taken by <strong>the</strong>se “graduated” <strong>ultra</strong> poormembers, microcredit/microfinance for <strong>the</strong> poorest may takea longer time <strong>to</strong> achieve sustainability.In <strong>the</strong> CFPR/TUP model, a declining trend in <strong>the</strong> <strong>to</strong>tal cos<strong>to</strong>f intervention per <strong>ultra</strong> poor household was seen with time(from US$ 344 in 2002 <strong>to</strong> US$ 287 in 2004) which isexpected <strong>to</strong> go down fur<strong>the</strong>r <strong>to</strong> US$ 278 in 2006 43 . Themodel was concluded as cost-effective considering <strong>the</strong>impacts on livelihood which were found <strong>to</strong> be positive(improved income <strong>and</strong> asset base), comprehensive(economic, <strong>social</strong> <strong>and</strong> <strong>health</strong> changes) <strong>and</strong> apparentlysustainable (maintenance of asset growth after “graduation”<strong>and</strong> joining regular microcredit/microfinance programme).ConclusionsMitigation of <strong>the</strong> income-erosion effect of illness is anessential pre-requisite for alleviation of poverty, especially for<strong>the</strong> poorest households in low-income countries likeBangladesh 44 . The findings of this study support <strong>the</strong>TUP Beneficiaries(Sulaiman et al. 2006)Borrower(49%)Non-Borrower(51%)Repaying withoutany difficulty (37%)Faced trouble inrepaying loan (12%)Applied for loan(14%)Have not applied(37%)Willing <strong>to</strong> take fur<strong>the</strong>rcredit (30%)Willing <strong>to</strong> take fur<strong>the</strong>rcredit (6%)Application onprocess (5%)Will apply (14%)Uncertain about fur<strong>the</strong>rcredit (5%)Uncertain about fur<strong>the</strong>rcredit (3%)Application rejected(9%)Uncertain aboutapplying (9%)Unwilling <strong>to</strong> take fur<strong>the</strong>rcredit (3%)Unwilling <strong>to</strong> take fur<strong>the</strong>rcredit (3%)Will not apply (14%)Figure 5: Status of beneficiary households of 2002 (baseline) in February 2005 (one year after completion of intervention cycle)Global Forum Update on Research for Health Volume 4 ✜ 037

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