Socio-demographic differentials of adult health indicators in Matlab, Bangladesh: self-rated health, health state, quality of life and disability level

• Main Authors: Abdur Razzaque, Lutfun Nahar, Masuma Akter Khanam, Peter Kim Streatfield
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2010-09-01
• Series: Global Health Action
• Subjects: adult health; self-rated health; health state; quality of life; disability; Matlab; Bangladesh; INDEPTH WHO-SAGE
• Online Access: http://www.globalhealthaction.net/index.php/gha/article/view/4618/6065

Background: Mortality has been declining in Bangladesh since the mid- twentieth century, while fertility has been declining since the late 1970s, and the country is now passing through the third stage of demographic transition. This type of demographic transition has produced a huge youthful population with a growing number of older people. For assessing health among older people, this study examines self-rated health, health state, quality of life and disability level in persons aged 50 and over. Data and methods: This is a collaborative study between the World Health Organization Study on global AGEing and adult health and the International Network for the Demographic Evaluation of Populations and Their Health in developing countries which collected data from eight countries. Two sources of data from the Matlab study area were used: health indicator data collected as a part of the study, together with the ongoing Health and Demographic Surveillance System (HDSS) data. For the survey, a total of 4,000 randomly selected people aged 50 and over (HDSS database) were interviewed. The four health indicators derived from these data are self-rated health (five categories), health state (eight domains), quality of life (eight items) and disability level (12 items). Self-rated health was coded as dummy while scores were calculated for the rest of the three health indicators using WHO-tested instruments. Results: After controlling for all the variables in the regression model, all four indicators of health (self-rated health, health state, quality of life and disability level) documented that health was better for males than females, and health deteriorates with increasing age. Those people who were in current partnerships had generally better health than those who were single, and better health was associated with higher levels of education and asset score. Conclusions: To improve the health of the population it is important to know health conditions in advance rather than just before death. This study finds that all four health indicators vary by socio-demographic characteristics. Hence, health intervention programmes should be targeted to those who suffer and are in the most need, the aged, female, single, uneducated and poor.