Analyzing Health Equity Using Household Survey Data

1. Analyzing Health Equity Using Household Survey Data Lecture 2 Data for Health Equity Analysis: Requirements, Sources and Sample Design “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

2. Data requirements: Health outcomes Murray and Chen (1992) classification of morbidity measures “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

3. Data requirements: Health-related behavior • Health care utilization • Payments for health care • Smoking, drinking, diet • Sexual practices • Household-level behavior (cooking, sanititation, etc.) “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

4. Data requirements: Living standards or socioeconomic status • Living standards: • Direct approaches e.g., income, expenditure • Cardinal – can compare magnitudes of differences • Proxy measures e.g., assets index • Ordinal – provide rankings • Socioeconomic status: • Education (level or years) • Occupational class “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

5. Data requirements for health equity analysis

6. Data sources • Household surveys and non-routine data • Large-scale, multi-purpose surveys e.g., LSMS (World Bank), MICS (UNICEF) • Health / demographic surveys e.g., DHS (ORC Macro), WHS (WHO) • Household budget surveys • Facility-based surveys (exit polls) • Routine data • Administrative data from HIS, vital registration, etc. • Census data “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

7. Pros and cons of household survey data “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

8. Pros and cons of user exit poll data “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

9. Pros and cons of administrative data “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

10. Pros and cons of census data “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

11. Sample design and the analysis of survey data • Multi-purpose and health surveys often have a complex design • Stratification – separate sampling from population sub-groups e.g., urban / rural • Cluster sampling – clusters of observations not sampled independently e.g., villages • Unequal selection probabilities – e.g. oversampling of the poor, uninsured “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

12. Standard stratified sampling • Population categorised by relatively few strata e.g. urban/rural, regions • Separate random sample of pre-defined size selected from each strata • Sample strata proportions need not correspond to population proportions  sample weights (separate issue) “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

13. Stratification and descriptive analysis • If pop. mean differs by strata, stratification reduces sample variance of its estimator • Standard errors for means and other descriptive stats. should be adjusted down • If regression used to estimate conditional means, then adjust the standard errors “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

14. Cluster sampling • Two (or more) stage sampling process • Clusters sampled from pop./strata • Households sampled from clusters • Observations are not independent within clusters and likely correlated through unobservables • Standard errors of parameter estimates should be adjusted to take account of the within cluster correlation “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

15. Sample weights • Stratification, over-sampling, non-response and attrition can all lead to a sample that is not representative of the population • Sample weights are the inverse of the probability that an observation is a sample member • Sample weights must be applied to get unbiased estimates of population means, etc. and correct standard errors • Should also be applied in “descriptive regressions” “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

16. Stata computation Set the sample design parameters svyset locality [pw=wgt], strata(strata) Estimate the mean and get the correct SE svy: mean vacc, over(quint) “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

17. Child Immunization Rates by Household Consumption Quintile, Mozambique 1997 No allowance for sample design With sample weights “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity

18. Child Immunization Rates by Household Consumption Quintile, Mozambique 1997 With stratification and clustering With stratification “Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity