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Theory and methods
Validity of rapid estimates of household wealth and income for health surveys in rural Africa
  1. Saul S Morrisa,
  2. Calogero Carlettoa,
  3. John Hoddinotta,
  4. Luc J M Christiaensenb
  1. aFood Consumption and Nutrition Division, International Food Policy Research Institute, 2033 K St NW, Washington DC 20006, USA, bDepartment of Agricultural, Resource and Managerial Economics, Cornell University, Ithaca NY, USA
  1. Dr Morris (e-mail: s.morris{at}cgiar.org)

Abstract

STUDY OBJECTIVE To test the validity of proxy measures of household wealth and income that can be readily implemented in health surveys in rural Africa.

DESIGN Data are drawn from four different integrated household surveys. The assumptions underlying the choice of wealth proxy are described, and correlations with the true value are assessed in two different settings. The expenditure proxy is developed and then tested for replicability in two independent datasets representing the same population.

SETTING Rural areas of Mali, Malawi, and Côte d'Ivoire (two national surveys).

PARTICIPANTS Random sample of rural households in each setting (n=275, 707, 910, and 856, respectively).

MAIN RESULTS In both Mali and Malawi, the wealth proxy correlated highly (r⩾0.74) with the more complex monetary value method. For rural areas of Côte d'Ivoire, it was possible to generate a list of just 10 expenditure items, the values of which when summed correlated highly with expenditures on all items combined (r=0.74, development dataset,r=0.72, validation dataset). Total household expenditure is an accepted alternative to household income in developing country settings.

CONCLUSIONS It is feasible to approximate both household wealth and expenditures in rural African settings without dramatically lengthening questionnaires that have a primary focus on health outcomes.

  • socioeconomic status
  • indicators
  • Africa

https://doi.org/10.1136/jech.54.5.381

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    Footnotes

    • Funding: funding for data collection and analysis of the Mali and Malawi data has been supported by the International Fund for Agricultural Development (TA Grant No. 301-IFPRI). We gratefully acknowledge this funding, but emphasise that ideas and opinions presented here are the responsibility of the authors and should in no way be attributed to IFAD.