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.
Objective: To investigate the association of a composite measure of psychosocial stress and the development of CVD events and mortality in a large prospective study involving populations from 21 high-, middle-, and low-income countries across 5 continents.
Design, Setting, and Participants: This population-based cohort study used data from the Prospective Urban Rural Epidemiology study, collected between January 2003 and March 2021. Participants included individuals aged 35 to 70 years living in 21 low-, middle-, and high-income countries. Data were analyzed from April 8 to June 15, 2021.
Exposures: All participants were assessed on a composite measure of psychosocial stress assessed at study entry using brief questionnaires concerning stress at work and home, major life events, and financial stress.
Main Outcomes and Measures: The outcomes of interest were stroke, major coronary heart disease (CHD), CVD, and all-cause mortality.
Results: A total of 118 706 participants (mean [SD] age 50.4 [9.6] years; 69 842 [58.8%] women and 48 864 [41.2%] men) without prior CVD and with complete baseline and follow-up data were included. Of these, 8699 participants (7.3%) reported high stress, 21 797 participants (18.4%) reported moderate stress, 34 958 participants (29.4%) reported low stress, and 53 252 participants (44.8%) reported no stress. High stress, compared with no stress, was more likely with younger age (mean [SD] age, 48.9 [8.9] years vs 51.1 [9.8] years), abdominal obesity (2981 participants [34.3%] vs 10 599 participants [19.9%]), current smoking (2319 participants [26.7%] vs 10 477 participants [19.7%]) and former smoking (1571 participants [18.1%] vs 3978 participants [7.5%]), alcohol use (4222 participants [48.5%] vs 13 222 participants [24.8%]), and family history of CVD (5435 participants [62.5%] vs 20 255 participants [38.0%]). During a median (IQR) follow-up of 10.2 (8.6-11.9) years, a total of 7248 deaths occurred. During the course of follow-up, there were 5934 CVD events, 4107 CHD events, and 2880 stroke events. Compared with no stress and after adjustment for age, sex, education, marital status, location, abdominal obesity, hypertension, smoking, diabetes, and family history of CVD, as the level of stress increased, there were increases in risk of death (low stress: hazard ratio [HR], 1.09 [95% CI, 1.03-1.16]; high stress: 1.17 [95% CI, 1.06-1.29]) and CHD (low stress: HR, 1.09 [95% CI, 1.01-1.18]; high stress: HR, 1.24 [95% CI, 1.08-1.42]). High stress, but not low or moderate stress, was associated with CVD (HR, 1.22 [95% CI, 1.08-1.37]) and stroke (HR, 1.30 [95% CI, 1.09-1.56]) after adjustment.
Conclusions and Relevance: This cohort study found that higher psychosocial stress, measured as a composite score of self-perceived stress, life events, and financial stress, was significantly associated with mortality as well as with CVD, CHD, and stroke events.
METHODS: We studied 125 287 participants from 18 countries in North America, South America, Europe, Africa, and Asia in the Prospective Urban Rural Epidemiology (PURE) study. Habitual food intake was measured with validated food frequency questionnaires. We assessed the associations between nutrients (total fats, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, carbohydrates, protein, and dietary cholesterol) and cardiovascular disease risk markers using multilevel modelling. The effect of isocaloric replacement of saturated fatty acids with other fats and carbohydrates was determined overall and by levels of intakes by use of nutrient density models. We did simulation modelling in which we assumed that the effects of saturated fatty acids on cardiovascular disease events was solely related to their association through an individual risk marker, and then compared these simulated risk marker-based estimates with directly observed associations of saturated fatty acids with cardiovascular disease events.
FINDINGS: Participants were enrolled into the study from Jan 1, 2003, to March 31, 2013. Intake of total fat and each type of fat was associated with higher concentrations of total cholesterol and LDL cholesterol, but also with higher HDL cholesterol and apolipoprotein A1 (ApoA1), and lower triglycerides, ratio of total cholesterol to HDL cholesterol, ratio of triglycerides to HDL cholesterol, and ratio of apolipoprotein B (ApoB) to ApoA1 (all ptrend<0·0001). Higher carbohydrate intake was associated with lower total cholesterol, LDL cholesterol, and ApoB, but also with lower HDL cholesterol and ApoA1, and higher triglycerides, ratio of total cholesterol to HDL cholesterol, ratio of triglycerides to HDL cholesterol, and ApoB-to-ApoA1 ratio (all ptrend<0·0001, apart from ApoB [ptrend=0·0014]). Higher intakes of total fat, saturated fatty acids, and carbohydrates were associated with higher blood pressure, whereas higher protein intake was associated with lower blood pressure. Replacement of saturated fatty acids with carbohydrates was associated with the most adverse effects on lipids, whereas replacement of saturated fatty acids with unsaturated fats improved some risk markers (LDL cholesterol and blood pressure), but seemed to worsen others (HDL cholesterol and triglycerides). The observed associations between saturated fatty acids and cardiovascular disease events were approximated by the simulated associations mediated through the effects on the ApoB-to-ApoA1 ratio, but not with other lipid markers including LDL cholesterol.
INTERPRETATION: Our data are at odds with current recommendations to reduce total fat and saturated fats. Reducing saturated fatty acid intake and replacing it with carbohydrate has an adverse effect on blood lipids. Substituting saturated fatty acids with unsaturated fats might improve some risk markers, but might worsen others. Simulations suggest that ApoB-to-ApoA1 ratio probably provides the best overall indication of the effect of saturated fatty acids on cardiovascular disease risk among the markers tested. Focusing on a single lipid marker such as LDL cholesterol alone does not capture the net clinical effects of nutrients on cardiovascular risk.
FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).
METHODS: We used the TyG index as a surrogate measure for insulin resistance. Fasting triglycerides and fasting plasma glucose were measured at the baseline visit in 141 243 individuals aged 35-70 years from 22 countries in the Prospective Urban Rural Epidemiology (PURE) study. The TyG index was calculated as Ln (fasting triglycerides [mg/dL] x fasting plasma glucose [mg/dL]/2). We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random effects to test the associations between the TyG index and risk of cardiovascular diseases and mortality. The primary outcome of this analysis was the composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, and non-fatal myocardial infarction, or stroke). Secondary outcomes were non-cardiovascular mortality, cardiovascular mortality, all myocardial infarctions, stroke, and incident diabetes. We also did subgroup analyses to examine the magnitude of associations between insulin resistance (ie, the TyG index) and outcome events according to the income level of the countries.
FINDINGS: During a median follow-up of 13·2 years (IQR 11·9-14·6), we recorded 6345 composite cardiovascular diseases events, 2030 cardiovascular deaths, 3038 cases of myocardial infarction, 3291 cases of stroke, and 5191 incident cases of type 2 diabetes. After adjusting for all other variables, the risk of developing cardiovascular diseases increased across tertiles of the baseline TyG index. Compared with the lowest tertile of the TyG index, the highest tertile (tertile 3) was associated with a greater incidence of the composite outcome (HR 1·21; 95% CI 1·13-1·30), myocardial infarction (1·24; 1·12-1·38), stroke (1·16; 1·05-1·28), and incident type 2 diabetes (1·99; 1·82-2·16). No significant association of the TyG index was seen with non-cardiovascular mortality. In low-income countries (LICs) and middle-income countries (MICs), the highest tertile of the TyG index was associated with increased hazards for the composite outcome (LICs: HR 1·31; 95% CI 1·12-1·54; MICs: 1·20; 1·11-1·31; pinteraction=0·01), cardiovascular mortality (LICs: 1·44; 1·15-1·80; pinteraction=0·01), myocardial infarction (LICs: 1·29; 1·06-1·56; MICs: 1·26; 1·10-1·45; pinteraction=0·08), stroke (LICs: 1·35; 1·02-1·78; MICs: 1·17; 1·05-1·30; pinteraction=0·19), and incident diabetes (LICs: 1·64; 1·38-1·94; MICs: 2·68; 2·40-2·99; pinteraction <0·0001). In contrast, in high-income countries, higher TyG index tertiles were only associated with an increased hazard of incident diabetes (2·95; 2·25-3·87; pinteraction <0·0001), but not of cardiovascular diseases or mortality.
INTERPRETATION: The TyG index is significantly associated with future cardiovascular mortality, myocardial infarction, stroke, and type 2 diabetes, suggesting that insulin resistance plays a promoting role in the pathogenesis of cardiovascular and metabolic diseases. Potentially, the association between the TyG index and the higher risk of cardiovascular diseases and type 2 diabetes in LICs and MICs might be explained by an increased vulnerability of these populations to the presence of insulin resistance.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
OBJECTIVE: The study aimed to assess the association of unprocessed red meat, poultry, and processed meat intake with mortality and major CVD.
METHODS: The Prospective Urban Rural Epidemiology (PURE) Study is a cohort of 134,297 individuals enrolled from 21 low-, middle-, and high-income countries. Food intake was recorded using country-specific validated FFQs. The primary outcomes were total mortality and major CVD. HRs were estimated using multivariable Cox frailty models with random intercepts.
RESULTS: In the PURE study, during 9.5 y of follow-up, we recorded 7789 deaths and 6976 CVD events. Higher unprocessed red meat intake (≥250 g/wk vs. <50 g/wk) was not significantly associated with total mortality (HR: 0.93; 95% CI: 0.85, 1.02; P-trend = 0.14) or major CVD (HR: 1.01; 95% CI: 0.92, 1.11; P-trend = 0.72). Similarly, no association was observed between poultry intake and health outcomes. Higher intake of processed meat (≥150 g/wk vs. 0 g/wk) was associated with higher risk of total mortality (HR: 1.51; 95% CI: 1.08, 2.10; P-trend = 0.009) and major CVD (HR: 1.46; 95% CI: 1.08, 1.98; P-trend = 0.004).
CONCLUSIONS: In a large multinational prospective study, we did not find significant associations between unprocessed red meat and poultry intake and mortality or major CVD. Conversely, a higher intake of processed meat was associated with a higher risk of mortality and major CVD.
OBJECTIVES: We aimed to assess the association between consumption of UPFs and risk of mortality and major CVD in a cohort from multiple world regions.
DESIGN: This analysis includes 138,076 participants without a history of CVD between the ages of 35 and 70 y living on 5 continents, with a median follow-up of 10.2 y. We used country-specific validated food-frequency questionnaires to determine individuals' food intake. We classified foods and beverages based on the NOVA classification into UPFs. The primary outcome was total mortality (CV and non-CV mortality) and secondary outcomes were incident major cardiovascular events. We calculated hazard ratios using multivariable Cox frailty models and evaluated the association of UPFs with total mortality, CV mortality, non-CV mortality, and major CVD events.
RESULTS: In this study, 9227 deaths and 7934 major cardiovascular events were recorded during the follow-up period. We found a diet high in UPFs (≥2 servings/d compared with 0 intake) was associated with higher risk of mortality (HR: 1.28; 95% CI: 1.15, 1.42; P-trend < 0.001), CV mortality (HR: 1.17; 95% CI: 0.98, 1.41; P-trend = 0.04), and non-CV mortality (HR: 1.32; 95% CI 1.17, 1.50; P-trend < 0.001). We did not find a significant association between UPF intake and risk of major CVD.
CONCLUSIONS: A diet with a high intake of UPFs was associated with a higher risk of mortality in a diverse multinational study. Globally, limiting the consumption of UPFs should be encouraged.
OBJECTIVES: Our aim was to assess the association of egg consumption with blood lipids, cardiovascular disease (CVD), and mortality in large global studies involving populations from low-, middle-, and high-income countries.
METHODS: We studied 146,011 individuals from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study. Egg consumption was recorded using country-specific validated FFQs. We also studied 31,544 patients with vascular disease in 2 multinational prospective studies: ONTARGET (Ongoing Telmisartan Alone and in Combination with Ramipril Global End Point Trial) and TRANSCEND (Telmisartan Randomized Assessment Study in ACEI Intolerant Subjects with Cardiovascular Disease). We calculated HRs using multivariable Cox frailty models with random intercepts to account for clustering by study center separately within each study.
RESULTS: In the PURE study, we recorded 14,700 composite events (8932 deaths and 8477 CVD events). In the PURE study, after excluding those with history of CVD, higher intake of egg (≥7 egg/wk compared with <1 egg/wk intake) was not significantly associated with blood lipids, composite outcome (HR: 0.96; 95% CI: 0.89, 1.04; P-trend = 0.74), total mortality (HR: 1.04; 95% CI: 0.94, 1.15; P-trend = 0.38), or major CVD (HR: 0.92; 95% CI: 0.83, 1.01; P-trend = 0.20). Similar results were observed in ONTARGET/TRANSCEND studies for composite outcome (HR 0.97; 95% CI: 0.76, 1.25; P-trend = 0.09), total mortality (HR: 0.88; 95% CI: 0.62, 1.24; P-trend = 0.55), and major CVD (HR: 0.97; 95% CI: 0.73, 1.29; P-trend = 0.12).
CONCLUSIONS: In 3 large international prospective studies including ∼177,000 individuals, 12,701 deaths, and 13,658 CVD events from 50 countries in 6 continents, we did not find significant associations between egg intake and blood lipids, mortality, or major CVD events. The ONTARGET and TRANSCEND trials were registered at clinicaltrials.gov as NCT00153101. The PURE trial was registered at clinicaltrials.gov as NCT03225586.
METHODS: Weekly influenza surveillance data for 2006 to 2011 were obtained from Bangladesh, Cambodia, India, Indonesia, the Lao People's Democratic Republic, Malaysia, the Philippines, Singapore, Thailand and Viet Nam. Weekly rates of influenza activity were based on the percentage of all nasopharyngeal samples collected during the year that tested positive for influenza virus or viral nucleic acid on any given week. Monthly positivity rates were then calculated to define annual peaks of influenza activity in each country and across countries.
FINDINGS: Influenza activity peaked between June/July and October in seven countries, three of which showed a second peak in December to February. Countries closer to the equator had year-round circulation without discrete peaks. Viral types and subtypes varied from year to year but not across countries in a given year. The cumulative proportion of specimens that tested positive from June to November was > 60% in Bangladesh, Cambodia, India, the Lao People's Democratic Republic, the Philippines, Thailand and Viet Nam. Thus, these tropical and subtropical countries exhibited earlier influenza activity peaks than temperate climate countries north of the equator.
CONCLUSION: Most southern and south-eastern Asian countries lying north of the equator should consider vaccinating against influenza from April to June; countries near the equator without a distinct peak in influenza activity can base vaccination timing on local factors.
METHODS AND ANALYSIS: This is a 3-year project in which a survey of 100 000 workers from all 13 states in Malaysia will be conducted using a web-based screening tool that is comprised of two parts: occupational disease screening tool and hazard identification, risk assessment and risk control method. Data will be collected using a multistage stratified sampling method from 500 companies, including seven critical industrial sectors. The independent variables will be sociodemographic characteristics, comorbidities, previous medical history, high-risk behaviour and workplace profile. The dependent variable will be the types of occupational diseases (noise-induced hearing loss, respiratory, musculoskeletal, neurotoxic, skin and mental disorders). Subsequently, suggestions of referral for medium and high-risk workers to occupational health clinics will be attained. The approved occupational health service clinics/providers will make a confirmatory diagnosis of each case as deemed necessary. Subsequently, a walk-through survey to identify workplace hazards and recommend workplace improvement measures to prevent these occupational diseases will be achieved. Both descriptive and inferential statistics will be used in this study. Simple and adjusted binary regression will be used to find the determinants of occupational diseases.
ETHICS AND DISSEMINATION: This study has been approved by the MARA University of Technology Research Ethics Board. Informed, written consent will be obtained from all study participants. Findings will be disseminated to the Department of Occupational Health and Safety, involved industries, and through peer-reviewed publications.
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: The Prospective Urban Rural Epidemiology (PURE) study is a prospective epidemiological study of individuals aged 35 and 70 years from 21 countries on five continents, with a median follow-up of 9.1 years. In the cross-sectional analyses, we assessed the association of dairy intake with prevalent MetS and its components among individuals with information on the five MetS components (n=112 922). For the prospective analyses, we examined the association of dairy with incident hypertension (in 57 547 individuals free of hypertension) and diabetes (in 131 481 individuals free of diabetes).
RESULTS: In cross-sectional analysis, higher intake of total dairy (at least two servings/day compared with zero intake; OR 0.76, 95% CI 0.71 to 0.80, p-trend<0.0001) was associated with a lower prevalence of MetS after multivariable adjustment. Higher intakes of whole fat dairy consumed alone (OR 0.72, 95% CI 0.66 to 0.78, p-trend<0.0001), or consumed jointly with low fat dairy (OR 0.89, 95% CI 0.80 to 0.98, p-trend=0.0005), were associated with a lower MetS prevalence. Low fat dairy consumed alone was not associated with MetS (OR 1.03, 95% CI 0.77 to 1.38, p-trend=0.13). In prospective analysis, 13 640 people with incident hypertension and 5351 people with incident diabetes were recorded. Higher intake of total dairy (at least two servings/day vs zero serving/day) was associated with a lower incidence of hypertension (HR 0.89, 95% CI 0.82 to 0.97, p-trend=0.02) and diabetes (HR 0.88, 95% CI 0.76 to 1.02, p-trend=0.01). Directionally similar associations were found for whole fat dairy versus each outcome.
CONCLUSIONS: Higher intake of whole fat (but not low fat) dairy was associated with a lower prevalence of MetS and most of its component factors, and with a lower incidence of hypertension and diabetes. Our findings should be evaluated in large randomized trials of the effects of whole fat dairy on the risks of MetS, hypertension, and diabetes.
METHODS: We assessed fruit and vegetable consumption using data from country-specific, validated semi-quantitative food frequency questionnaires in the Prospective Urban Rural Epidemiology (PURE) study, which enrolled participants from communities in 18 countries between Jan 1, 2003, and Dec 31, 2013. We documented household income data from participants in these communities; we also recorded the diversity and non-sale prices of fruits and vegetables from grocery stores and market places between Jan 1, 2009, and Dec 31, 2013. We determined the cost of fruits and vegetables relative to income per household member. Linear random effects models, adjusting for the clustering of households within communities, were used to assess mean fruit and vegetable intake by their relative cost.
FINDINGS: Of 143 305 participants who reported plausible energy intake in the food frequency questionnaire, mean fruit and vegetable intake was 3·76 servings (95% CI 3·66-3·86) per day. Mean daily consumption was 2·14 servings (1·93-2·36) in low-income countries (LICs), 3·17 servings (2·99-3·35) in lower-middle-income countries (LMICs), 4·31 servings (4·09-4·53) in upper-middle-income countries (UMICs), and 5·42 servings (5·13-5·71) in high-income countries (HICs). In 130 402 participants who had household income data available, the cost of two servings of fruits and three servings of vegetables per day per individual accounted for 51·97% (95% CI 46·06-57·88) of household income in LICs, 18·10% (14·53-21·68) in LMICs, 15·87% (11·51-20·23) in UMICs, and 1·85% (-3·90 to 7·59) in HICs (ptrend=0·0001). In all regions, a higher percentage of income to meet the guidelines was required in rural areas than in urban areas (p<0·0001 for each pairwise comparison). Fruit and vegetable consumption among individuals decreased as the relative cost increased (ptrend=0·00040).
INTERPRETATION: The consumption of fruit and vegetables is low worldwide, particularly in LICs, and this is associated with low affordability. Policies worldwide should enhance the availability and affordability of fruits and vegetables.
FUNDING: Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, AstraZeneca (Canada), Sanofi-Aventis (France and Canada), Boehringer Ingelheim (Germany and Canada), Servier, GlaxoSmithKline, Novartis, King Pharma, and national or local organisations in participating countries.
METHODS: In the Prospective Urban Rural Epidemiology (PURE) study, participants aged 35-70 years (n=156 625) were recruited from 110 803 households, in 604 communities and 22 countries; availability (presence of any dose of medication in the pharmacy on the day of audit) and medicine cost data were collected from pharmacies with the Environmental Profile of a Community's Health audit tool. Our primary analysis was to describe the availability and affordability of metformin and insulin and also commonly used and prescribed combinations of two medicines for diabetes management (two oral drugs, metformin plus a sulphonylurea [either glibenclamide (also known as glyburide) or gliclazide] and one oral drug plus insulin [metformin plus insulin]). Medicines were defined as affordable if the cost of medicines was less than 20% of capacity-to-pay (the household income minus food expenditure). Our analyses included data collected in pharmacies and data from representative samples of households. Data on availability were ascertained during the pharmacy audit, as were data on cost of medications. These cost data were used to estimate the cost of a month's supply of essential medicines for diabetes. We estimated affordability of medicines using income data from household surveys.
FINDINGS: Metformin was available in 113 (100%) of 113 pharmacies from high-income countries, 112 (88·2%) of 127 pharmacies in upper-middle-income countries, 179 (86·1%) of 208 pharmacies in lower-middle-income countries, 44 (64·7%) of 68 pharmacies in low-income countries (excluding India), and 88 (100%) of 88 pharmacies in India. Insulin was available in 106 (93·8%) pharmacies in high-income countries, 51 (40·2%) pharmacies in upper-middle-income countries, 61 (29·3%) pharmacies in lower-middle-income countries, seven (10·3%) pharmacies in lower-income countries, and 67 (76·1%) of 88 pharmacies in India. We estimated 0·7% of households in high-income countries and 26·9% of households in low-income countries could not afford metformin and 2·8% of households in high-income countries and 63·0% of households in low-income countries could not afford insulin. Among the 13 569 (8·6% of PURE participants) that reported a diagnosis of diabetes, 1222 (74·0%) participants reported diabetes medicine use in high-income countries compared with 143 (29·6%) participants in low-income countries. In multilevel models, availability and affordability were significantly associated with use of diabetes medicines.
INTERPRETATION: Availability and affordability of essential diabetes medicines are poor in low-income and middle-income countries. Awareness of these global differences might importantly drive change in access for patients with diabetes.
FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).
METHODS: The Prospective Urban Rural Epidemiology (PURE) study is a large multinational cohort study of individuals aged 35-70 years enrolled from 21 countries in five continents. Dietary intakes of dairy products for 136 384 individuals were recorded using country-specific validated food frequency questionnaires. Dairy products comprised milk, yoghurt, and cheese. We further grouped these foods into whole-fat and low-fat dairy. The primary outcome was the composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, non-fatal myocardial infarction, stroke, or heart failure). Hazard ratios (HRs) were calculated using multivariable Cox frailty models with random intercepts to account for clustering of participants by centre.
FINDINGS: Between Jan 1, 2003, and July 14, 2018, we recorded 10 567 composite events (deaths [n=6796] or major cardiovascular events [n=5855]) during the 9·1 years of follow-up. Higher intake of total dairy (>2 servings per day compared with no intake) was associated with a lower risk of the composite outcome (HR 0·84, 95% CI 0·75-0·94; ptrend=0·0004), total mortality (0·83, 0·72-0·96; ptrend=0·0052), non-cardiovascular mortality (0·86, 0·72-1·02; ptrend=0·046), cardiovascular mortality (0·77, 0·58-1·01; ptrend=0·029), major cardiovascular disease (0·78, 0·67-0·90; ptrend=0·0001), and stroke (0·66, 0·53-0·82; ptrend=0·0003). No significant association with myocardial infarction was observed (HR 0·89, 95% CI 0·71-1·11; ptrend=0·163). Higher intake (>1 serving vs no intake) of milk (HR 0·90, 95% CI 0·82-0·99; ptrend=0·0529) and yogurt (0·86, 0·75-0·99; ptrend=0·0051) was associated with lower risk of the composite outcome, whereas cheese intake was not significantly associated with the composite outcome (0·88, 0·76-1·02; ptrend=0·1399). Butter intake was low and was not significantly associated with clinical outcomes (HR 1·09, 95% CI 0·90-1·33; ptrend=0·4113).
INTERPRETATION: Dairy consumption was associated with lower risk of mortality and major cardiovascular disease events in a diverse multinational cohort.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
METHODS: We did a prospective cohort study (Prospective Urban Rural Epidemiology [PURE] in 135 335 individuals aged 35 to 70 years without cardiovascular disease from 613 communities in 18 low-income, middle-income, and high-income countries in seven geographical regions: North America and Europe, South America, the Middle East, south Asia, China, southeast Asia, and Africa. We documented their diet using country-specific food frequency questionnaires at baseline. Standardised questionnaires were used to collect information about demographic factors, socioeconomic status (education, income, and employment), lifestyle (smoking, physical activity, and alcohol intake), health history and medication use, and family history of cardiovascular disease. The follow-up period varied based on the date when recruitment began at each site or country. The main clinical outcomes were major cardiovascular disease (defined as death from cardiovascular causes and non-fatal myocardial infarction, stroke, and heart failure), fatal and non-fatal myocardial infarction, fatal and non-fatal strokes, cardiovascular mortality, non-cardiovascular mortality, and total mortality. Cox frailty models with random effects were used to assess associations between fruit, vegetable, and legume consumption with risk of cardiovascular disease events and mortality.
FINDINGS: Participants were enrolled into the study between Jan 1, 2003, and March 31, 2013. For the current analysis, we included all unrefuted outcome events in the PURE study database through March 31, 2017. Overall, combined mean fruit, vegetable and legume intake was 3·91 (SD 2·77) servings per day. During a median 7·4 years (5·5-9·3) of follow-up, 4784 major cardiovascular disease events, 1649 cardiovascular deaths, and 5796 total deaths were documented. Higher total fruit, vegetable, and legume intake was inversely associated with major cardiovascular disease, myocardial infarction, cardiovascular mortality, non-cardiovascular mortality, and total mortality in the models adjusted for age, sex, and centre (random effect). The estimates were substantially attenuated in the multivariable adjusted models for major cardiovascular disease (hazard ratio [HR] 0·90, 95% CI 0·74-1·10, ptrend=0·1301), myocardial infarction (0·99, 0·74-1·31; ptrend=0·2033), stroke (0·92, 0·67-1·25; ptrend=0·7092), cardiovascular mortality (0·73, 0·53-1·02; ptrend=0·0568), non-cardiovascular mortality (0·84, 0·68-1·04; ptrend =0·0038), and total mortality (0·81, 0·68-0·96; ptrend<0·0001). The HR for total mortality was lowest for three to four servings per day (0·78, 95% CI 0·69-0·88) compared with the reference group, with no further apparent decrease in HR with higher consumption. When examined separately, fruit intake was associated with lower risk of cardiovascular, non-cardiovascular, and total mortality, while legume intake was inversely associated with non-cardiovascular death and total mortality (in fully adjusted models). For vegetables, raw vegetable intake was strongly associated with a lower risk of total mortality, whereas cooked vegetable intake showed a modest benefit against mortality.
INTERPRETATION: Higher fruit, vegetable, and legume consumption was associated with a lower risk of non-cardiovascular, and total mortality. Benefits appear to be maximum for both non-cardiovascular mortality and total mortality at three to four servings per day (equivalent to 375-500 g/day).
FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).
METHODS: A cross-section of 163,397 adults aged 35 to 70 years were recruited from 661 urban and rural communities in selected low-, middle- and high-income countries (complete data for this analysis from 151,619 participants). Using blood pressure measurements, self-reported health and household data, concentration indices adjusted for age, sex and urban-rural location, we estimate the magnitude of wealth-related inequalities in the levels of hypertension awareness, treatment, and control in each of the 21 country samples.
RESULTS: Overall, the magnitude of wealth-related inequalities in hypertension awareness, treatment, and control was observed to be higher in poorer than in richer countries. In poorer countries, levels of hypertension awareness and treatment tended to be higher among wealthier households; while a similar pro-rich distribution was observed for hypertension control in countries at all levels of economic development. In some countries, hypertension awareness was greater among the poor (Sweden, Argentina, Poland), as was treatment (Sweden, Poland) and control (Sweden).
CONCLUSION: Inequality in hypertension management outcomes decreased as countries became richer, but the considerable variation in patterns of wealth-related inequality - even among countries at similar levels of economic development - underscores the importance of health systems in improving hypertension management for all. These findings show that some, but not all, countries, including those with limited resources, have been able to achieve more equitable management of hypertension; and strategies must be tailored to national contexts to achieve optimal impact at population level.
Methods: Cross-sectional data from 21 countries in the Prospective Urban and Rural Epidemiology study were collected covering 61 229 hypertensive individuals aged 35-70 years, their households and the 656 communities in which they live. Outcomes include whether hypertensive participants have their condition detected, treated and/or controlled. Multivariate statistical models adjusting for community fixed effects were used to assess the associations of three social capital measures: (1) membership of any social organisation, (2) trust in other people and (3) trust in organisations, stratified into high-income and low-income country samples.
Results: In low-income countries, membership of any social organisation was associated with a 3% greater likelihood of having one's hypertension detected and controlled, while greater trust in organisations significantly increased the likelihood of detection by 4%. These associations were not observed among participants in high-income countries.
Conclusion: Although the observed associations are modest, some aspects of social capital are associated with better management of hypertension in low-income countries where health systems are often weak. Given that hypertension affects millions in these countries, even modest gains at all points along the treatment pathway could improve management for many, and translate into the prevention of thousands of cardiovascular events each year.