METHODS: In the Prospective Urban Rural Epidemiological study (PURE), individuals aged 35-70 years from urban and rural communities in 27 countries were considered for inclusion. We recorded information on participants' sociodemographic characteristics, risk factors, medication use, cardiac investigations, and interventions. 168 490 participants who enrolled in the first two of the three phases of PURE were followed up prospectively for incident cardiovascular disease and death.
FINDINGS: From Jan 6, 2005 to May 6, 2019, 202 072 individuals were recruited to the study. The mean age of women included in the study was 50·8 (SD 9·9) years compared with 51·7 (10) years for men. Participants were followed up for a median of 9·5 (IQR 8·5-10·9) years. Women had a lower cardiovascular disease risk factor burden using two different risk scores (INTERHEART and Framingham). Primary prevention strategies, such as adoption of several healthy lifestyle behaviours and use of proven medicines, were more frequent in women than men. Incidence of cardiovascular disease (4·1 [95% CI 4·0-4·2] for women vs 6·4 [6·2-6·6] for men per 1000 person-years; adjusted hazard ratio [aHR] 0·75 [95% CI 0·72-0·79]) and all-cause death (4·5 [95% CI 4·4-4·7] for women vs 7·4 [7·2-7·7] for men per 1000 person-years; aHR 0·62 [95% CI 0·60-0·65]) were also lower in women. By contrast, secondary prevention treatments, cardiac investigations, and coronary revascularisation were less frequent in women than men with coronary artery disease in all groups of countries. Despite this, women had lower risk of recurrent cardiovascular disease events (20·0 [95% CI 18·2-21·7] versus 27·7 [95% CI 25·6-29·8] per 1000 person-years in men, adjusted hazard ratio 0·73 [95% CI 0·64-0·83]) and women had lower 30-day mortality after a new cardiovascular disease event compared with men (22% in women versus 28% in men; p<0·0001). Differences between women and men in treatments and outcomes were more marked in LMICs with little differences in HICs in those with or without previous cardiovascular disease.
INTERPRETATION: Treatments for cardiovascular disease are more common in women than men in primary prevention, but the reverse is seen in secondary prevention. However, consistently better outcomes are observed in women than in men, both in those with and without previous cardiovascular disease. Improving cardiovascular disease prevention and treatment, especially in LMICs, should be vigorously pursued in both women and men.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
Objective: To assess whether sleep timing and napping behavior are associated with increased obesity, independent of nocturnal sleep length.
Design, Setting, and Participants: This large, multinational, population-based cross-sectional study used data of participants from 60 study centers in 26 countries with varying income levels as part of the Prospective Urban Rural Epidemiology study. Participants were aged 35 to 70 years and were mainly recruited during 2005 and 2009. Data analysis occurred from October 2020 through March 2021.
Exposures: Sleep timing (ie, bedtime and wake-up time), nocturnal sleep duration, daytime napping.
Main Outcomes and Measures: The primary outcomes were prevalence of obesity, specified as general obesity, defined as body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 or greater, and abdominal obesity, defined as waist circumference greater than 102 cm for men or greater than 88 cm for women. Multilevel logistic regression models with random effects for study centers were performed to calculate adjusted odds ratios (AORs) and 95% CIs.
Results: Overall, 136 652 participants (81 652 [59.8%] women; mean [SD] age, 51.0 [9.8] years) were included in analysis. A total of 27 195 participants (19.9%) had general obesity, and 37 024 participants (27.1%) had abdominal obesity. The mean (SD) nocturnal sleep duration was 7.8 (1.4) hours, and the median (interquartile range) midsleep time was 2:15 am (1:30 am-3:00 am). A total of 19 660 participants (14.4%) had late bedtime behavior (ie, midnight or later). Compared with bedtime between 8 pm and 10 pm, late bedtime was associated with general obesity (AOR, 1.20; 95% CI, 1.12-1.29) and abdominal obesity (AOR, 1.20; 95% CI, 1.12-1.28), particularly among participants who went to bed between 2 am and 6 am (general obesity: AOR, 1.35; 95% CI, 1.18-1.54; abdominal obesity: AOR, 1.38; 95% CI, 1.21-1.58). Short nocturnal sleep of less than 6 hours was associated with general obesity (eg, <5 hours: AOR, 1.27; 95% CI, 1.13-1.43), but longer napping was associated with higher abdominal obesity prevalence (eg, ≥1 hours: AOR, 1.39; 95% CI, 1.31-1.47). Neither going to bed during the day (ie, before 8pm) nor wake-up time was associated with obesity.
Conclusions and Relevance: This cross-sectional study found that late nocturnal bedtime and short nocturnal sleep were associated with increased risk of obesity prevalence, while longer daytime napping did not reduce the risk but was associated with higher risk of abdominal obesity. Strategic weight control programs should also encourage earlier bedtime and avoid short nocturnal sleep to mitigate obesity epidemic.
METHODS: We conducted a community-based cross-sectional study in 15 sub-districts of Kuantan Singingi regency from May-June 2017. We selected 320 mothers from 15 sub-districts who delivered in the last 3 months (February-April 2017). Trained data enumerators collected the relevant data by using a pre-tested semi-structured questionnaire. We used Cox regression analysis to determine the factors associated with delivery at healthcare facilities. Prevalence Ratio (PR) with a 95% confidence interval (CI) for childbirth at healthcare facilities was the key outcome measure.
RESULTS: Only 54.4% (174) of the 320 mothers delivered at healthcare facilities. Knowledge about pregnancy danger signs (PR = 1.59, 95%CI:1.15-2.2), attitude towards healthcare services (PR = 0.79, 95%CI:0.33-1.89), and access to health care services (PR = 0.39, 95%CI:0.18-0.84) were the dominant factors of childbirth at healthcare facilities. There was an interaction between attitude and access to healthcare influencing delivery at healthcare facilities.
CONCLUSIONS: Utilization of healthcare facilities for childbirth was low in Kuantan Singingi regency. Knowledge of pregnancy danger signs was an independent correlate of childbirth at healthcare facilities. Also, the interaction between attitude and access to healthcare showed a significant influence on childbirth at healthcare facilities. We recommend strengthening of existing maternal and child health program with a particular emphasis on complete and quality antenatal care, health education on danger signs of pregnancy and childbirth, and promoting positive attitudes towards healthcare facilities.
METHODS: We analyzed aggregate data from Demographic and Health Surveys and Multiple Indicator Cluster Surveys done from 1986 to 2012 in low-and-middle-income countries. Two-week prevalence rates of diarrhea, caregiver's care seeking behavior and three case management indicators were analyzed. We assessed overall time trends across the countries using panel data analyses and country-level changes between two sequential surveys.
RESULTS: Overall, yearly increase in case management indicators ranged from 1 · 3 to 2 · 5%. In the year 2012, <50% of the children were given correct treatment (received oral rehydration and increased fluids) for diarrhea. Annually, an estimated 300 to 350 million children were not given oral rehydration solutions, or recommended home fluids or 'increased fluids' and 304 million children not taken to a healthcare provider during an episode of diarrhea. Overall, care seeking for diarrhea, increased from pre-2000 to post-2000, i.e. from 35 to 45%; oral rehydration rates increased by about 7% but the rate of 'increased fluids' decreased by 14%. Country-level trends showed that care seeking had decreased in 15 countries but increased in 33 countries. Care seeking from a healthcare provider increased by ≥10% in about 23 countries. Oral rehydration rates had increased by ≥10% in 15 countries and in 30 countries oral rehydration rates increased by <10%.
CONCLUSIONS: Very limited progress has been made in the case management of childhood diarrhea. A better understanding of caregiver's care seeking behavior and health care provider's case management practices is needed to improve diarrhea case management in low- and-middle-income countries.
Objective: To estimate changes in the prevalence of current tobacco use and socioeconomic inequalities among male and female participants from 22 sub-Saharan African countries from 2003 to 2019.
Design, Setting, and Participants: Secondary data analyses were conducted of sequential Demographic and Health Surveys in 22 sub-Saharan African countries including male and female participants aged 15 to 49 years. The baseline surveys (2003-2011) and the most recent surveys (2011-2019) were pooled.
Exposures: Household wealth index and highest educational level were the markers of inequality.
Main Outcomes and Measures: Sex-specific absolute and relative changes in age-standardized prevalence of current tobacco use in each country and absolute and relative measures of inequality using pooled data.
Results: The survey samples included 428 197 individuals (303 232 female participants [70.8%]; mean [SD] age, 28.6 [9.8] years) in the baseline surveys and 493 032 participants (348 490 female participants [70.7%]; mean [SD] age, 28.5 [9.4] years) in the most recent surveys. Both sexes were educated up to primary (35.7%) or secondary school (40.0%). The prevalence of current tobacco use among male participants ranged from 6.1% (95% CI, 5.2%-6.9%) in Ghana to 38.3% (95% CI, 35.8%-40.8%) in Lesotho in the baseline surveys and from 4.5% (95% CI, 3.7%-5.3%) in Ghana to 46.0% (95% CI, 43.2%-48.9%) in Lesotho during the most recent surveys. The decrease in prevalence ranged from 1.5% (Ghana) to 9.6% (Sierra Leone). The World Health Organization target of a 30% decrease in smoking was achieved among male participants in 8 countries: Rwanda, Nigeria, Ethiopia, Benin, Liberia, Tanzania, Burundi, and Cameroon. For female participants, the number of countries having a prevalence of smoking less than 1% increased from 9 in baseline surveys to 16 in the most recent surveys. The World Health Organization target of a 30% decrease in smoking was achieved among female participants in 15 countries: Cameroon, Namibia, Mozambique, Mali, Liberia, Nigeria, Burundi, Tanzania, Malawi, Kenya, Rwanda, Zimbabwe, Ethiopia, Burkina Faso, and Zambia. For both sexes, the prevalence of tobacco use and the decrease in prevalence of tobacco use were higher among less-educated individuals and individuals with low income. In both groups, the magnitude of inequalities consistently decreased, and its direction remained the same. Absolute inequalities were 3-fold higher among male participants, while relative inequalities were nearly 2-fold higher among female participants.
Conclusions and Relevance: Contrary to a projected increase, tobacco use decreased in most sub-Saharan African countries. Persisting socioeconomic inequalities warrant the stricter implementation of tobacco control measures to reach less-educated individuals and individuals with low income.
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).
METHODS: Optimal RTU (oRTU) rates were determined for nine middle-income countries, following the epidemiological evidence-based method. The actual RTU (aRTU) rates were calculated dividing the total number of new notifiable cancer patients treated with radiotherapy in 2012 by the total number of cancer patients diagnosed in the same year in each country. An analysis of the characteristics of patients and treatments in a series of 300 consecutive radiotherapy patients shed light on the particular patient and treatments profile in the participating countries.
RESULTS: The median oRTU rate for the group of nine countries was 52% (47-56%). The median aRTU rate for the nine countries was 28% (9-46%). These results show that the real proportion of cancer patients receiving RT is lower than the optimal RTU with a rate difference between 10-42.7%. The median percent-unmet need was 47% (18-82.3%).
CONCLUSIONS: The optimal RTU rate in middle-income countries did not differ significantly from that previously found in high-income countries. The actual RTU rates were consistently lower than the optimal, in particular in countries with limited resources and a large population.
DESIGN: Cross-sectional observational study.
SETTING: Twenty-three Asian countries and regions, covering 92.1% of the continent's population.
PARTICIPANTS: Ten low-income and lower-middle-income economies, five upper-middle-income economies, and eight high-income economies according to the World Bank classification.
INTERVENTIONS: Data closest to 2017 on critical care beds, including ICU and intermediate care unit beds, were obtained through multiple means, including government sources, national critical care societies, colleges, or registries, personal contacts, and extrapolation of data.
MEASUREMENTS AND MAIN RESULTS: Cumulatively, there were 3.6 critical care beds per 100,000 population. The median number of critical care beds per 100,000 population per country and region was significantly lower in low- and lower-middle-income economies (2.3; interquartile range, 1.4-2.7) than in upper-middle-income economies (4.6; interquartile range, 3.5-15.9) and high-income economies (12.3; interquartile range, 8.1-20.8) (p = 0.001), with a large variation even across countries and regions of the same World Bank income classification. This number was independently predicted by the World Bank income classification on multivariable analysis, and significantly correlated with the number of acute hospital beds per 100,000 population (r = 0.19; p = 0.047), the universal health coverage service coverage index (r = 0.35; p = 0.003), and the Human Development Index (r = 0.40; p = 0.001) on univariable analysis.
CONCLUSIONS: Critical care bed capacity varies widely across Asia and is significantly lower in low- and lower-middle-income than in upper-middle-income and high-income countries and regions.