Assessing the health of the poor: towards a pro-poor measurement strategy.

The problems of measuring the health of the poor are now becoming a priority area for development agencies. This is not only because of the consensus on equitable health status as a worthy and agreed goal in itself, but also because of the emerging understanding of the crucial role that health plays in the production of poverty. Furthermore, the current impetus for preparing Poverty Reduction Strategy Papers (PRSPs) requires an effective monitoring and evaluation process to be planned as part of each country’s strategy. Much data on the health of the world’s poor is already collected on a regular basis in developing countries by the Demographic and Health Survey (DHS) programme. More information on the economic status of individuals in developing countries is also collected, less frequently and with less standardised questionnaires, by the World Bank under the Living Standards Measurement Survey (LSMS) programme. Other data on both health and income or wealth is also available from a range of uncoordinated sources. So far, the only focused attempt to measure the health of the poor uses DHS data to track health indicators for different ‘wealth’ groups, where wealth is measured by calculating household assets and amenities. Using DHS data as the main strategy for measuring health is the best way forward, given that it is the highest quality and most standardised scheme of data collection. The DHS is very unlikely, however, to include income in its questionnaire schedule, so that general agreement needs to be reached on the asset approach as an appropriate way forward, the alternative being a consistent set of health questions being included in LSMS surveys. Apart from undertaking analyses of data which has already been collected, there should also be supplementary data collection undertaken to cover the shortcomings of the DHS in any given setting. According to the country characteristics in any given setting, the following range of techniques should be considered to supplement DHS and LSMS monitoring: poverty mapping from the most recent census; piggybacking poverty studies on already functioning population ‘laboratories’; and undertaking new cluster surveys in new poor areas. It is also advisable to engage in a dialogue for undertaking new standardised surveys in-country such as DHS and LSMS. The latter is particularly amenable to flexibility of subject matter to be included in the questionnaire.