Socioeconomic status and health among older population

The study examines how health outcomes at older ages are associated with socioeconomic status (SES) in rural and urban Vietnam and how such patterns of health inequality have changed over the last 10 years (2001-2011). Vietnam has witnessed rapid economic development, a significant increase in income inequality, and major health-sector reforms. These factors may have implications for older adults’ health. Research related to the wellbeing of older adults is becoming more important as Vietnam begins a period of rapid population aging. The share of Vietnam’s population age 60 and older is estimated to grow from 8% in 2010 to 31% in 2050 and by then, the number of Vietnamese older adults will increase by 335%. Analyzing nationally representative data from the 2011 Vietnam National Aging Survey (the country’s first national survey of older persons) in conjunction with the 2001 Vietnam National Health Survey (the country’s most comprehensive health survey), this study addresses three specific research questions including: Are there socioeconomic gradients of self-rated health among older persons in rural and urban Vietnam in 2001 and 2011? Did inequality pattern that existed in 2001 remain consistent or altered across the two time periods? Were consistencies or alterations uniform across rural and urban locations?

The proportion of adults reaching 60 in Latin America is expected to grow quickly. Cuba and Puerto Rico are good examples. San Juan and Havana have a substantial fraction of people above age 60. The objective of this paper is to study inequalities in health in two cities: San Juan, Puerto Rico and Havana, Cuba. This research is based on data from PREHCO (Puerto Rican Elderly Health Conditions) and SABE (Health, Well-being and Aging in Latin America) . A socioeconomic index was calculated for Puerto Rico based on six dimensions: assets, household equipment, household ownership, per capita income, financial debts and health insurance; the index for Cuba was based on five dimensions per capita income, household infrastructure, household equipment, education and neighborhood environment. Using k-medians clustering the elderly population was grouped in three clusters: low, medium and high. Important differences by sex, age and certain health conditions were found between older adults in San Juan and Havana.

Objectives: To examine age pattern of socioeconomic gradients across various reported and measured health indicators for Indian adults.
Methods: Cross-sectional data on 11,230 Indian adults aged 18-plus from the Study of Global Ageing and Adult Health, India (SAGE, 2007) is used. Bivariate analysis and logit models with interactions of age and socioeconomic status are applied to examine effects of socioeconomic status on health of Indian adults across ages.
Results: Results reveal a more dynamic pattern of age vis-à-vis socioeconomic gradients on the health of Indian older adults. Negative age gradient prevailed on key indicators of adult health across socioeconomic spectrum. However, age gradient was stronger for the poor and less educated adults. Concurrently, key measures of socioeconomic status: years of schooling and wealth quintile indicated an overwhelming positive gradient on health but with considerable heterogeneity across ages and on different domains of health.
Discussion: Overall, results demonstrate a non-static and counteracting pattern of age vis-à-vis socioeconomic gradients on adult health. Results suggest that the trajectories of age and social determinants interactively determine the health of Indian older adult.

It is widely believed that family background has a significant influence on children’s life. The vast majority of the existent literature has focused on the relationship between parents’ education and income and the education and income of their children. Surprisingly, much less work has been done on the intergenerational transmission of health. The main objective of this paper is to examine the correlations of health across generations using the Indonesia Family Life Survey (IFLS). We take advantage of the richness of IFLS and examine several health measures of respondents, including self-reports and biomarkers. As measures of health of both parents, IFLS has information on whether they are dead at the time of the last wave in 2007, their general health status and whether they have difficulties with any ADLs at the time of the survey or just before death. The findings suggest strong intergenerational correlations between the measures of parental health, schooling, and the health of their adult children. We also examine how these intergenerational correlations might differ for respondents born in the more developed parts of Indonesia compared to the less developed areas. Interestingly, these health associations are much lower for respondents who were born in Java or Bali.