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Household health surveys are the main data source for health inequality monitoring because they include both data on health indicators and inequality dimensions. Yet, there are sampling design complexities (e.g. clustering, weighting, stratification) that must be taken into consideration when analysing survey data.
The statistical codes shared here demonstrate how complex survey sampling design may be taken into account in the calculation of a) estimates for health indicators disaggregated by inequality dimensions (e.g. economic status, education and urban-rural areas) and b) population subgroup sizes for each inequality dimension. These two pieces of information (a and b), may be used to calculate summary measures of inequality.
Statistical codes are provided for commonly used selected statistical packages using a sample dataset.
Notes:
The health indicator and inequality dimensions are illustrative. Further, the aim here is not to demonstrate how an indicator may be defined or measured, or to advocate for any specific inequality dimension. Rather, the codes demonstrate how for a pre-defined and measured indicator (i.e. births attended by skilled personnel), with pre-selected and measured inequality dimensions, the calculation may be undertaken.
Statistical codes
More Health Equity Monitor data products
- Publications
- Health Equity Assessment Toolkit
- Country profiles
- Statistical codes
- Compendium of indicator definitions (pdf,
550kb)