Research Article: Relative Contributions of Geographic, Socioeconomic, and Lifestyle Factors to Quality of Life, Frailty, and Mortality in Elderly

Date Published: January 19, 2010

Publisher: Public Library of Science

Author(s): Jean Woo, Ruth Chan, Jason Leung, Moses Wong, Abdisalan M. Noor.

Abstract: To date, few studies address disparities in older populations specifically using frailty as one of the health outcomes and examining the relative contributions of individual and environmental factors to health outcomes.

Partial Text: With the ageing of populations worldwide, the major users of health services are older people. Increasing emphasis has been placed on the collection of data documenting variations or disparities in health outcomes, with a view to minimizing these disparities as part of public health improvement [1]. However collection of outcomes at the macro level has limitations, in that it is difficult to have a clear understanding of contributory factors from only ecological data. Furthermore, the fact that more resources tend to be direct at areas with poorer outcomes gives rise to cross-sectional associations linking increase spending with poor outcomes [2]. For any country or city, while it is important to document regional variations in health outcomes, in depth studies using primary data are needed to identify possible contributory factors in order to minimize disparities. Different strategies are required for different contributory factors. Provision and accessibility of health services, particularly of primary care [3], represent only one of many external factors. Others include social and psychological factors [4], [5], [6], [7], [8], the physical environment such as air pollution [9], [10], open spaces [11] and perhaps population density, noise and constant bright light constituting some of the neighbourhood factors. Individual factors include socioeconomic status [4], [8], [12], [13], [14], [15], lifestyle [16] and the life course influence in terms of early life environment [17] and life events [6], [13].

The total number of subjects from 11/18 districts with > = 100 participants was 3611 (90.3% of the original sample). After four years of follow up, 233 participants had died [Fig 1]. Variations in lifestyle (DQI, PASE, smoking habit and alcohol use) with age, gender, socioeconomic status and district is shown in Table 1. Increasing age was associated with lower PASE score, less use of tobacco and alcohol. Being female was associated with better dietary quality, lower PASE score, less use of tobacco and alcohol, and higher socioeconomic position. Higher socioeconomic position was associated with lower PASE score and less use of tobacco. Using Shatin as the reference district, district variations in different components of lifestyle are observed, but do not fall into any consistent ‘healthy’ or ‘unhealthy’ pattern.

Analysis of this dataset shows that even within a city of 1050 km2 with a population of 6.7 million people, small area variations in health outcomes exist among the elderly aged 65 years and over. District of residence, socioeconomic position and lifestyle factors directly as well as indirectly affect self-rated physical and mental health, frailty and four year mortality in a complex manner.



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