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Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability. Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity. Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses. Conclusions: The re

Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability. Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity. Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses. Conclusions: The re

Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability. Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity. Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses. Conclusions: The re

Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability. Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity. Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses. Conclusions: The re

Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability. Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity. Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses. Conclusions: The re

Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability. Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity. Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses. Conclusions: The re

BackgroundArsenic exposure via drinking water increases the risk of chronic respiratory disease in adults. However, information on pulmonary health effects in children after early life exposure is limited.MethodsThis population-based cohort study set in rural Matlab, Bangladesh, assessed lung function and respiratory symptoms of 650 children aged 7-17 years. Children with in utero and early life arsenic exposure were compared with children exposed to less than 10 µg/l in utero and throughout childhood. Because most children drank the same water as their mother had drunk during pregnancy, we could not assess only in utero or only childhood exposure.ResultsChildren exposed in utero to more than 500 µg/l of arsenic were more than eight times more likely to report wheezing when not having a cold [odds ratio (OR) = 8.41, 95% confidence interval (CI): 1.66-42.6, P < 0.01] and more than three times more likely to report shortness of breath when walking on level ground (OR = 3.86, 95% CI: 1.09-13.7, P = 0.02) and when walking fast or climbing (OR = 3.19, 95% CI: 1.22-8.32, P < 0.01]. However, there was little evidence of reduced lung function in either exposure category.ConclusionsChildren with high in utero and early life arsenic exposure had marked increases in several chronic respiratory symptoms, which could be due to in utero exposure or to early life exposure, or to both. Our findings suggest that arsenic in water has early pulmonary effects and that respiratory symptoms are a better marker of early life arsenic toxicity than changes in lung function measured by spirometry.

In Bangladesh, being active and able to participate in productive activities is often essential to ensure ongoing health and survival. This study aims to describe and explore the patterns of participation in productive activities by older people in Matlab, a rural area of Bangladesh. Data from a cross sectional survey of people over 60 years of age was utilised. Six hundred and twenty five men and women participated in home based interviews providing information about their participation in productive activities including work, domestic activities and community groups. Overall, 94.4% of subjects reported participation in at least one productive activity. Men were the main participants in paid work and community groups, with 62% reporting engagement in paid work and 44% contributing to community groups. Both men (95.4%) and women (91.9%) reported performing at least one domestic activity. Performance of higher numbers of domestic tasks was associated with being younger, female, not requiring any assistance with self care, not married, not living with any children and earning between 100–999 Bangladesh Taka in the past month. Participation in community groups was low with only 26% of the sample reporting any involvement. This study indicates a high level of productivity in the older population in Matlab which benefits the individual, the family and the wider community. The safety and suitability of typical productive activities needs further investigation, in order to inform strategies protecting the older population from the effects of over work and harmful activities., At the time of this research, Lisa Cameron was a visiting research fellow at ICDDR,B. The authors gratefully acknowledge the assistance and dedication of the field staff of Matlab Health and Demographic Surveillance System (ICDDR,B) and the expertise of the Karolinska Institutet staff in the development and implementation of this project. We are grateful to the participants for their time and involvement in this research and acknowledge the Department for International Development (DFID—United Kingdom) in providing funding for this project.

In this paper, we present an international network of researchers from projects examining the human aging process and its consequences. It is both vital and urgent to include aging and a life course perspective on the public health agenda, particularly in low-income countries. By announcing the network in a publication, we wish not just to position the network but, more importantly, to attract the attention of other potential collaborators either at the project, institutional, decision making, or applied level.