Estimating inequalities in ownership of insecticide treated nets: does the choice of socio-economic status measure matter?
Research on the impact of socio-economic status (SES) on access to health care services and on health status is important for allocating resources and designing pro-poor policies. Socio-economic differences are increasingly assessed using asset indices as proxy measures for SES. For example, several studies use asset indices to estimate inequities in ownership and use of insecticide treated nets as a way of monitoring progress towards meeting the Abuja targets. The validity of different SES measures has only been tested in a limited number of settings, however, and there is little information on how choice of welfare measure influences study findings, conclusions and policy recommendations. In this paper, we demonstrate that household SES classification can depend on the SES measure selected. Using data from a household survey in coastal Kenya (n = 285 rural and 467 urban households), we first classify households into SES quintiles using both expenditure and asset data. Household SES classification is found to differ when separate rural and urban asset indices, or a combined asset index, are used. We then use data on bednet ownership to compare inequalities in ownership within each setting by the SES measure selected. Results show a weak correlation between asset index and monthly expenditure in both settings: wider inequalities in bednet ownership are observed in the rural sample when expenditure is used as the SES measure [Concentration Index (CI) = 0.1024 expenditure quintiles; 0.005 asset quintiles]; the opposite is observed in the urban sample (CI = 0.0518 expenditure quintiles; 0.126 asset quintiles). We conclude that the choice of SES measure does matter. Given the practical advantages of asset approaches, we recommend continued refinement of these approaches. In the meantime, careful selection of SES measure is required for every study, depending on the health policy issue of interest, the research context and, inevitably, pragmatic considerations.
Chuma
Jane
J
Kenya Medical Research Institute, Kilifi, Kenya. jchuma@kilifi.kemri-wellcome.org
Molyneux
Catherine
C
D001512:Bedding and Linens / Q000191:economics / Q000600:supply & distribution*; D005191:Family Characteristics; D005102:Health Expenditures / Q000706:statistics & numerical data; D006291:Health Policy; D006297:Health Services Accessibility / Q000145:classification / Q000191:economics*; D054625:Healthcare Disparities / Q000145:classification / Q000191:economics*; D006801:Humans; D007306:Insecticides; D007630:Kenya; D008288:Malaria / Q000191:economics / Q000517:prevention & control*; D017059:Models, Econometric; D009032:Mosquito Control / Q000295:instrumentation* / Q000379:methods; D010067:Ownership / Q000191:economics* / Q000706:statistics & numerical data; D012424:Rural Population; D012923:Social Class; D014505:Urban Population
D007306:Insecticides