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Comparative Reports 6 - DHS Wealth Index DHS
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To explore health and population indicators by wealth, select the countries and indicators of interest in STATcompiler, then after the data has loaded, check the boxes for the desired household wealth quintiles under Background Characteristics to display the data for the quintiles.  For an example click here.

Wealth Index resources
The DHS wealth index categorizes households into 5 wealth quintiles, allowing you to see how health differs between the poor and wealthy. (Photo credit: ICF Macro)

What is the wealth index?

The wealth index is a composite measure of a household's cumulative living standard. The wealth index is calculated using easy-to-collect data on a household’s ownership of selected assets, such as televisions and bicycles; materials used for housing construction; and types of water access and sanitation facilities. 

Generated with a statistical procedure known as principal components analysis, the wealth index places individual households on a continuous scale of relative wealth. DHS separates all interviewed households into five wealth quintiles to compare the influence of wealth on various population, health and nutrition indicators. The wealth index is presented in the DHS Final Reports and survey datasets as a background characteristic.

Why is the wealth index important?

Wealth is a household characteristic that often has a large affect on health. The wealth index allows for the identification of problems particular to the poor, such as unequal access to health care, as well as those particular to the wealthy, such as, in Africa, increased risk for infection with HIV. Developed by The DHS Program with partial funding from the World Bank, the DHS wealth index also allows governments to evaluate whether public health services, vaccination campaigns, education, and other essential interventions are reaching the poorest.

The wealth index is particularly valuable in countries that lack reliable data on income and expenditures, which are the traditional indicators used to measure household economic status. 

The wealth index allows researchers to identify how much household economic status affects health outcomes by using both bivariate and more sophisticated multivariate methods. For example, in a study of nine countries, MEASURE DHS researchers have been able to show that economic status is not an important risk factor for domestic violence.

The Wealth-Health Connection: Quick Facts from DHS

  • In Nigeria, children from the wealthiest households are 13 times more likely to be vaccinated than those from the poorest households.
  • In the Philippines, over 90 percent of women in the wealthiest households are assisted by a health professional at delivery, compared to only 25 percent of women in the poorest households.
  • In Tanzania, HIV prevalence is three times higher among women in the wealthiest households (11.4 percent) compared to those in the poorest households (2.8 percent).

For more information about the wealth index and its importance, please see the DHS Comparative Report The DHS Wealth Index.


What is the methodology for wealth indexing?

Information on the wealth index is based on data collected in the Household Questionnaire. This questionnaire includes questions concerning the household’s ownership of a number of consumer items such as a television and car; dwelling characteristics such as flooring material; type of drinking water source; toilet facilities; and other characteristics that are related to wealth status.

Each household asset for which information is collected is assigned a weight or factor score generated through principal components analysis. The resulting asset scores are standardized in relation to a standard normal distribution with a mean of zero and a standard deviation of one. These standardized scores are then used to create the break points that define wealth quintiles as: Lowest, Second, Middle, Fourth, and Highest.

Each household is assigned a standardized score for each asset, where the score differs depending on whether or not the household owned that asset (or, in the case of sleeping arrangements, the number of people per room). These scores are summed by household, and individuals are ranked according to the total score of the household in which they reside. The sample is then divided into population quintiles -- five groups with the same number of individuals in each.

A single asset index is developed on the basis of data from the entire country sample and used in all the tabulations presented. Separate asset indices are not prepared for rural and urban population groups on the basis of rural or urban data, respectively.

Wealth quintiles are expressed in terms of quintiles of individuals in the population, rather than quintiles of individuals at risk for any one health or population indicator. This approach to defining wealth quintiles has the advantage of producing information directly relevant to the principal question of interest, for example, the health status or access to services for the poor in the population as a whole. This choice also facilitates comparisons across indicators for the same quintile, since the quintile denominators remain unchanged across indicators. However, some types of analysis may require data for quintiles of individuals at risk.

All health, nutrition and population indicators are calculated after applying the sampling weights so that the resulting numbers are generalizable to the total population. For each indicator in these tables, the total or population average presented is the weighted sum of the quintile values for that indicator, where the weight assigned to each quintile value is the proportion of the total number of individuals at risk in that quintile. The total value for indicators produced by this weighting scheme are representative of the total population, as they take into account the fact that the numbers of individuals at risk may vary across wealth quintiles. Similarly, each quintile value itself can be reproduced as a weighted average of urban/rural rates (weighted by proportions urban/rural) or the male/female rates (weighted by the proportion male/female). As a result of this weighting scheme, the population average for a given indicator presented in the tables will usually differ from a simple mean of the population subgroups.