(e.g., Filmer and Pritchett 1998; Gakidou and King 2000).<sup>4</sup> Although both composite asset indices and money-metric measures such as income or consumption have merit as indicators of welfare or living standard, the different approaches raise questions about comparability.

The purpose of this paper is to illustrate how the analysis of health-related inequalities can be sensitive to measures of socioeconomic status. Using data from Mozambique, the paper focuses on five key health service indicators: hospital visits, health facility visits, child immunizations, ante-natal care visits, and medically supervised deliveries. Evidence from the 1996/1997 living standards survey suggests that the incidence of public spending is equally distributed (Heltberg, Simler, and Tarp. 2001) and that income is not an important determinant of the utilization of health services (Lindelöw 2000). In contrast, however, descriptive statistics from a Demographic and Health Survey (DHS) implemented in the same year point at notable inequalities across asset index quintiles in both health outcomes and health service indicators (Gwatkin and others 2000). On the surface, these findings are difficult to reconcile. The paper exploits the considerable overlap in the list of assets covered by the two surveys, and uses the living standards survey to test whether measured inequality in the five health service variables is different depending on the choice of welfare indicator. The results indicate that, with the exception of curative visits to primary-level facilities, measured inequality in the utilization of health services is greater when individuals are ranked according to an asset index rather than consumption. This difference, which is shown to be the product of spatial differences in the respective measure of SES, makes it clear that, at least in some contexts, the choice of welfare indicator can drive conclusions about income-related health inequalities in important ways.

The paper is organized as follows. Section 2 discusses the methods for measuring inequality and for comparing distributions of health service use. It also provides an overview of approaches to the measurement of living standards or socioeconomic status. Section 3 presents the data and the variables used in the analysis. Section 4 reports on the findings of the analysis. Section 5 concludes.

# **2. Methods**

# **2.1 Measurement of Socioeconomic Inequalities in Health Variables**

The questions posed in this paper concern (i) whether the utilization of a particular health service, _h_ , differs in “important” ways depending on the socioeconomic status, _x_ , of individuals; and, (ii), whether the degree to which _h_ differs with _x_ depends on how socioeconomic status is measured. There are different approaches to addressing these questions. A common starting point for looking at the distribution of health-related variables by a continuous measure of SES is to compare the means of different welfare

> 4 This approach is becoming increasingly important as the sometimes-prohibitive costs of collecting income or consumption data is leading to increased reliance on alternative welfare measures. This is the case, for example, with recent efforts to collect “cheap and quick” data for poverty monitoring purposes, such as the Core Welfare Indicator Questionnaire Surveys (CWIQ) of the World Bank.

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