Socioeconomic Status and Morbidity Rate Inequality in China: Based on NHSS and CHARLS Data

Previous studies have shown there are no consistent and robust associations between socioeconomic status and morbidity rates. This study focuses on the relationship between the socioeconomic status and the morbidity rates in China, which helps to add new evidence for the fragmentary relationship between socioeconomic status and morbidity rates. The National Health Services Survey (NHSS) and China Health and Retirement Longitudinal Study (CHARLS) data are used to examine whether the association holds in both all-age cohorts and in older only cohorts. Three morbidity outcomes (two-week incidence rate, the prevalence of chronic diseases, and the number of sick days per thousand people) and two socioeconomic status indicators (income and education) are mainly examined. The results indicate that there are quadratic relationships between income per capita and morbidities. This non-linear correlation is similar to the patterns in European countries. Meanwhile, there is no association between education years and the morbidity in China, i.e., either two-week incidence rate or prevalence rate of chronic diseases has no statistically significant relationship with the education level in China.

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

BACKGROUND

Measures 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.

RESULTS

An 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).

CONCLUSION

The 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.