Socioeconomic Analysis of the Alameda County Health Department Jurisdiction

Lebowitz, Michael D.; Malcolm, James C.

doi:10.2105/ajph.54.11.1876

Cited by 8 publications

(2 citation statements)

References 6 publications

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“…Socioeconomic position (SEP) has played an important role in many health studies [ 1 - 5 ]. The relationship between SEP and health has been studied in its own right, [ 6 - 8 ] and it has been treated as a potential covariate/confounder in studies of other substantive causes of poor health [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

A novel nonparametric item response theory approach to measuring socioeconomic position: a comparison using household expenditure data from a Vietnam health survey, 2003

Reidpath

Ahmadi

2014

Emerg Themes Epidemiol

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BackgroundMeasures of household socio-economic position (SEP) are widely used in health research. There exist a number of approaches to their measurement, with Principal Components Analysis (PCA) applied to a basket of household assets being one of the most common. PCA, however, carries a number of assumptions about the distribution of the data which may be untenable, and alternative, non-parametric, approaches may be preferred. Mokken scale analysis is a non-parametric, item response theory approach to scale development which appears never to have been applied to household asset data. A Mokken scale can be used to rank order items (measures of wealth) as well as households. Using data on household asset ownership from a national sample of 4,154 consenting households in the World Health Survey from Vietnam, 2003, we construct two measures of household SEP. Seventeen items asking about assets, and utility and infrastructure use were used. Mokken Scaling and PCA were applied to the data. A single item measure of total household expenditure is used as a point of contrast.ResultsAn 11 item scale, out of the 17 items, was identified that conformed to the assumptions of a Mokken Scale. All the items in the scale were identified as strong items (Hi > .5). Two PCA measures of SEP were developed as a point of contrast. One PCA measure was developed using all 17 available asset items, the other used the reduced set of 11 items identified in the Mokken scale analaysis. The Mokken Scale measure of SEP and the 17 item PCA measure had a very high correlation (r = .98), and they both correlated moderately with total household expenditure: r = .59 and r = .57 respectively. In contrast the 11 item PCA measure correlated moderately with the Mokken scale (r = .68), and weakly with the total household expenditure (r = .18).ConclusionThe Mokken scale measure of household SEP performed at least as well as PCA, and outperformed the PCA measure developed with the 11 items used in the Mokken scale. Unlike PCA, Mokken scaling carries no assumptions about the underlying shape of the distribution of the data, and can be used simultaneous to order household SEP and items. The approach, however, has not been tested with data from other countries and remains an interesting, but under researched approach.

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Section: Introductionmentioning

confidence: 99%

A novel nonparametric item response theory approach to measuring socioeconomic position: a comparison using household expenditure data from a Vietnam health survey, 2003

Reidpath

Ahmadi

2014

Emerg Themes Epidemiol

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“…Applications in the field of health care, however, were slow to develop; psychiatry is the sole health care topic in which SAA has been employed in Britain (Philip and McCulloch, 1966;Giggs, 1973;Skrimshire, 1976a). Possible uses in the analysis of health data have been suggested (Craig, 1975), but actual 199 applications have been confined to the United States of America, where the use of SAA has demonstrated social area typologies which identify individual variables associated with certain disease states such as total mortality and cause-specific mortality (Nagi and Stockwell, 1973), tuberculosis (Lebowitz and Malcolm, 1964;Guerrin and Borgatta, 1965), mental illness (Struening and Lehmann, 1969), venereal disease (Lebowitz and Malcolm, 1964;Struening and Lehmann, 1969), uptake of antenatal care (Struening and Lehmann, 1969), low birth weight (Struening et al, 1973), and infant mortality (Lebowitz and Malcolm, 1964;Struening et al, 1973).…”

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Social area analysis in community medicine.

Scott-Samuel¹

1977

Journal of Epidemiology & Community Health

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SUMMARY There is an acknowledged need for better information to guide resource allocation and service planning in the health services. Despite the recognition of the important role of socioeconomic factors, difficulties with the appropriate presentation of data have so far proved insuperable. Social area analysis (SAA), which is a generic name for a number of methods employing census and other data to classify small areas into similar socioeconomic groups, is an approach which quantifies data in a useful fashion and has important applications in medical, epidemiological, and health services research. Most previous British exercises in SAA have been in the field of town planning. The potentialities of the approach for community medicine are evaluated, by the use of information from two existing studies. This is shown to discriminate more effectively than does existing health information between hypotheses concerning geographical variations in mortality, and it provides adequate explanations for urban area differentials in infant mortality, the uptake of vaccination, and the incidence of infectious disease. Specific applications of SAA in health planning and research are discussed.

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