Additional file 1: of Measuring spatial equity and access to maternal health services using enhanced two step floating catchment area method (E2SFCA) – a case study of the Indian Sundarbans

Parameter estimation. (DOCX 42 kb

Significance of Multiple Shocks on Individual Items of Welfare, Sundarbans, West Bengal, India.

<p>Significance of Multiple Shocks on Individual Items of Welfare, Sundarbans, West Bengal, India.</p

Proportion of households incurring sacrifices of different items according to self-assessed intensity of climatic shock, Sundarbans, West Bengal, India.

#<p>building embankments, dwelling repairs etc.</p><p>*p<0.1,</p><p>** p<0.05,</p><p>*** p<0.001.</p><p>Proportion of households incurring sacrifices of different items according to self-assessed intensity of climatic shock, Sundarbans, West Bengal, India.</p

Effect of climate shock intensity on use of different coping strategies, Sundarbans, West Bengal, India.

<p>Note: ^#Includes both ‘moneylenders’ and ‘mortgage etc.’ as coping strategies.</p><p>Second column values are odds ratios from logit regressions on the predictor variable denoting whether the household had suffered relatively greater impact from Aila. The indicator variable is based on a self-rating question on impact of <i>Aila</i> on eight categories of household assets and means of livelihood with a household reporting ‘devastating’ for more than half the categories classified as of suffering a greater impact – termed as ‘high impact’ households. The logit model additionally controls for <i>pre-shock</i> vulnerabilities (see text) and village-level fixed effects. The t-statistic tests for the hypothesis that the variable is not different from zero. * p<0.1, ** p<0.05.</p><p>Effect of climate shock intensity on use of different coping strategies, Sundarbans, West Bengal, India.</p

Percentage distribution of coping strategies against shock inflinted by cyclone <i>Aila</i>, according to perceived severity of the shock, Sundarbans, West Bengal, India.

<p>Percentage distribution of coping strategies against shock inflinted by cyclone <i>Aila</i>, according to perceived severity of the shock, Sundarbans, West Bengal, India.</p

Percentage of households with members in different age-sex groups reporting a deterioration of self-assessed health in the one year following <i>Aila</i>, Sundarbans, West Bengal, India.

<p>*p<0.1,</p><p>** p<0.05,</p><p>*** p<0.001.</p><p>Percentage of households with members in different age-sex groups reporting a deterioration of self-assessed health in the one year following <i>Aila</i>, Sundarbans, West Bengal, India.</p

Multiple Shocks and Aggregate Welfare Losses due to cyclone <i>Aila</i>, Sundarbans, West Bengal, India.

<p>*p<0.1,</p><p>** p<0.05,</p><p>*** p<0.001.</p><p>Multiple Shocks and Aggregate Welfare Losses due to cyclone <i>Aila</i>, Sundarbans, West Bengal, India.</p

Joint effect of climate and health shocks on coping strategies against expenditure following health shock, Sundarbans, West Bengal, India.

<p>Note: ^#Expenditure items include direct costs of treatment, expenses on drugs and medicines, transport, and related expense such as those incurred on food or lodging for patients and accompanying person(s).</p><p>@ denotes that the testing of hypotheses for difference of means (results in column B-F) was carried out only for the households reporting an incidence of health shock (n = 94).</p>∧<p>The coefficients in column G are odds-ratios on the ‘multiple-shock’ variable – households experiencing both the health shock as well as high-impact due to climatic shock – from logit regressions with the dependent variable in the corresponding row of the first column. Health shock variable is for illness of household head and/or spouse. The comparison group for column G coefficients is households with health shock alone (with a less-impact of Climatic shock). Models additionally control for (log) total health expenses, <i>pre-shock</i> vulnerabilities (see text) and village-level fixed effects. Coping models (items B and C, in column A) also controls for the self-assessed ‘difficulty in financing’ variable.</p><p>Figures in parentheses are t-statistics testing for the hypothesis that the variable is not different from zero.</p><p>* *p<0.05, *** p<0.01.</p><p>Joint effect of climate and health shocks on coping strategies against expenditure following health shock, Sundarbans, West Bengal, India.</p