A large body of health care literature points to the importance of considering the effects of socioeconomic inequalities on health (Marmot, 2004). The primary aim of the present study is to investigate the role of both objective and subjective indicators of socioeconomic status (SES) in explaining health disparities over time among older adults. Data were drawn from the New Zealand Longitudinal Study of Aging, with complete data available for 1765 participants (Mean age = 61.16 years; SD=4.47). SES and demographic data were taken from 2006 (Time 1) and health data from 2006 and 2008 (Time 2). SES Markers: objective SES was assessed by two proxies - income and education, and subjective SES was measured by economic living standards index. Health Markers: Physical and mental health from Short Form 36, self-rated health and health-risk behaviours were used to assess health status. Various demographic variables were also measured. In comparison to objective SES (assessed by income and education), subjective SES (assessed by perceived economic living standards) came out to be a significant predictor of an array of health outcomes. Hierarchical linear regressions suggested that low subjective SES at Time 1 significantly predicted decrements in health at Time 2, after controlling for sociodemographic characteristics and baseline scores of health outcomes. The concept of economic living standards (as indexed by subjective SES) takes into account the different daily living circumstances and social experience in which people may use income and assets, including different needs and subjective aspirations. Thus, subjective SES is a better longitudinal predictor in explaining the health disparities in older adults than objective SES.

Prior research indicated that restriction of normal activities is an important factor in poorer mental health outcomes (Williamson, 2000). The present study aims to investigate the relationship between ageing-related physical decline in mental health, and how this relationship is mediated by restricted routine activities. Data were drawn from the New Zealand Longitudinal Study of Aging (2006-2008), with complete data available for 2170 participants (Mean age = 61.24 years; SD = 4.56). Self-rated health as compared to last year was used to assess ageing-related physical decline and mental health was measured by the SF 36. Activity restriction was assessed by the 16-items attributed to restricted normal activities adapted from the Physical Component of the SF-36. Several sociodemographic factors were also measured. Mediational analysis using multiple regression equations indicated that ageing-related physical decline was a significant longitudinal predictor of decrements in mental health, after statistically controlling for various sociodemographic factors and baseline scores of the outcome variable. Results also indicated that this relationship was partially mediated by restricted activities (Sobel's test: Z = 8.72, p<.01), suggesting that ageing-related stressors such as physical decline undermines mental health by disrupting routine normal activities. Our findings suggest that activity restriction is a major factor in poorer mental health outcomes in older adults. As ageing-related physical decline increases, so does activity restriction which, in turn, results in decrements in mental health over time. Interventions focusing on promoting manageable activities considering individual differences in psychosocial resources and/or using compensatory control strategies can be developed to reduce activity restriction. For example, programs designed to foster strategies such as social support resources and social integration (e.g., free or low-cost bus service to visit friends and family, more participatory activities arranged in community halls etc.) may improve mental health among the elderly with perceived low social support.