RESEARCH DESIGN AND METHODS: The prevalence of diabetes, defined as self-reported or fasting glycemia ≥7 mmol/L, was documented in 119,666 adults from three high-income (HIC), seven upper-middle-income (UMIC), four lower-middle-income (LMIC), and four low-income (LIC) countries. Relationships between diabetes and its risk factors within these country groupings were assessed using multivariable analyses.
RESULTS: Age- and sex-adjusted diabetes prevalences were highest in the poorer countries and lowest in the wealthiest countries (LIC 12.3%, UMIC 11.1%, LMIC 8.7%, and HIC 6.6%; P < 0.0001). In the overall population, diabetes risk was higher with a 5-year increase in age (odds ratio 1.29 [95% CI 1.28-1.31]), male sex (1.19 [1.13-1.25]), urban residency (1.24 [1.11-1.38]), low versus high education level (1.10 [1.02-1.19]), low versus high physical activity (1.28 [1.20-1.38]), family history of diabetes (3.15 [3.00-3.31]), higher waist-to-hip ratio (highest vs. lowest quartile; 3.63 [3.33-3.96]), and BMI (≥35 vs. <25 kg/m(2); 2.76 [2.52-3.03]). The relationship between diabetes prevalence and both BMI and family history of diabetes differed in higher- versus lower-income country groups (P for interaction < 0.0001). After adjustment for all risk factors and ethnicity, diabetes prevalences continued to show a gradient (LIC 14.0%, LMIC 10.1%, UMIC 10.9%, and HIC 5.6%).
CONCLUSIONS: Conventional risk factors do not fully account for the higher prevalence of diabetes in LIC countries. These findings suggest that other factors are responsible for the higher prevalence of diabetes in LIC countries.
METHODS: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family.
FINDINGS: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (pinteraction<0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (pinteraction<0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (pinteraction<0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries.
INTERPRETATION: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
RESEARCH DESIGN AND METHODS: The Prospective Urban Rural Epidemiology (PURE) study enrolled 143,567 adults aged 35-70 years from 4 high-income countries (HIC), 12 middle-income countries (MIC), and 5 low-income countries (LIC). The mean follow-up was 9.0 ± 3.0 years.
RESULTS: Among those with diabetes, CVD rates (LIC 10.3, MIC 9.2, HIC 8.3 per 1,000 person-years, P < 0.001), all-cause mortality (LIC 13.8, MIC 7.2, HIC 4.2 per 1,000 person-years, P < 0.001), and CV mortality (LIC 5.7, MIC 2.2, HIC 1.0 per 1,000 person-years, P < 0.001) were considerably higher in LIC compared with MIC and HIC. Within LIC, mortality was higher in those in the lowest tertile of wealth index (low 14.7%, middle 10.8%, and high 6.5%). In contrast to HIC and MIC, the increased CV mortality in those with diabetes in LIC remained unchanged even after adjustment for behavioral risk factors and treatments (hazard ratio [95% CI] 1.89 [1.58-2.27] to 1.78 [1.36-2.34]).
CONCLUSIONS: CVD rates, all-cause mortality, and CV mortality were markedly higher among those with diabetes in LIC compared with MIC and HIC with mortality risk remaining unchanged even after adjustment for risk factors and treatments. There is an urgent need to improve access to care to those with diabetes in LIC to reduce the excess mortality rates, particularly among those in the poorer strata of society.
METHOD: In this cross-sectional study, 9432 community-dwelling elderly people aged 60 years and older living in rural or urban areas in Haikou were investigated. The interviews collected self-reported information on the presence of four major chronic diseases, as well as socio-demographic characteristics, lifestyle factors and self-reported height and weight.
FINDINGS: Overall, 31.7% (2961/9344) reported at least one of the four chronic diseases. The prevalence of hypertension, diabetes mellitus, COPD, and stroke was 26.0% (2449/9407), 8.0% (749/9371), 1.0% (95/9360), and 1.9% (175/9382), respectively. Common correlates of the four major chronic diseases were older age, being engaged in intellectual work, currently being a smoker and obesity. Gender, locality of residence, and alcohol consumptions were also found to be associated to some of the chronic conditions.
CONCLUSION: This finding indicates that multiple chronic conditions among elderly people in Haikou are prevalent and warrant special attention to reduce diseases burden and align health care services to cater the holistic elderly patients' need.
DESIGN: Two-stage stratified sample.
SETTING: Nationally representative of rural Bangladesh.
SUBJECTS: Households (n 5503) and individuals (n 24 198).
RESULTS: Fish consumption in poor households was almost half that in wealthiest households; and lower in females than males in all groups, except the wealthiest, and for those aged ≥15 years (P<0·01). In infants of complementary feeding age, 56 % did not consume ASF on the survey day, despite 78 % of mothers knowing this was recommended. Non-farmed fish made a larger contribution to Fe, Zn, Ca, vitamin A and vitamin B12 intakes than farmed fish (P<0·0001).
CONCLUSIONS: Policies and programmes aimed to increase fish consumption as a means to improve nutrition in rural Bangladesh should focus on women and young children, and on the poorest households. Aquaculture plays an important role in increasing availability and affordability of fish; however, non-farmed fish species are better placed to contribute to greater micronutrient intakes. This presents an opportunity for aquaculture to contribute to improved nutrition, utilising diverse production technologies and fish species, including small fish.
METHODS: This study was conducted based on secondary data analysed from the third phase of the longitudinal study "Neuroprotective Model for Health Longevity among Malaysian Elderly" (LRGS TUA). Stratification of urban and rural study areas were in accordance to that determined by the Department of Statistics. A total of 814 community dwelling older women (53% urban, 47% rural), aged 60 years and above, across four states within Peninsular Malaysia were included in this analysis. Interview-based questionnaires were used to obtain respondents' sociodemographic details and clinical characteristics. The Timed Up and Go test and Handgrip Strength tests were used to assess physical function. Urinary incontinence was self-reported, and quality of life of those with incontinence was assessed using the King's Health Questionnaire (KHQ).
RESULTS: Prevalence of urinary incontinence was 16% and 23% among older women living in urban and rural areas, respectively. Ethnicity was significantly associated with incontinence among older women in both urban and rural population (p rural setting (p rural population, respondents with chronic constipation [OR: 3.384, 95% C.I: 1.556-7.360, p = 0.002] were found to be at a higher risk of UI. In terms of quality of life, respondents in rural areas experienced more role, physical, social, emotional limitations and sleep disturbance as compared to their urban counterparts (p rural setting. The risk factors of UI were ethnicity and chronic constipation among urban and rural older women respectively. It is important to provide holistic strategies in the prevention and management of UI among older women especially within the rural population.