METHODS: The Prospective Urban Rural Epidemiology study is ongoing in 21 countries. Here we report an analysis done in 18 countries with data on clinical outcomes. Eligible participants were adults aged 35-70 years without cardiovascular disease, sampled from the general population. We used morning fasting urine to estimate 24 h sodium and potassium excretion as a surrogate for intake. We assessed community-level associations between sodium and potassium intake and BP in 369 communities (all >50 participants) and cardiovascular disease and mortality in 255 communities (all >100 participants), and used individual-level data to adjust for known confounders.

FINDINGS: 95 767 participants in 369 communities were assessed for BP and 82 544 in 255 communities for cardiovascular outcomes with follow-up for a median of 8·1 years. 82 (80%) of 103 communities in China had a mean sodium intake greater than 5 g/day, whereas in other countries 224 (84%) of 266 communities had a mean intake of 3-5 g/day. Overall, mean systolic BP increased by 2·86 mm Hg per 1 g increase in mean sodium intake, but positive associations were only seen among the communities in the highest tertile of sodium intake (p<0·0001 for heterogeneity). The association between mean sodium intake and major cardiovascular events showed significant deviations from linearity (p=0·043) due to a significant inverse association in the lowest tertile of sodium intake (lowest tertile <4·43 g/day, mean intake 4·04 g/day, range 3·42-4·43; change -1·00 events per 1000 years, 95% CI -2·00 to -0·01, p=0·0497), no association in the middle tertile (middle tertile 4·43-5·08 g/day, mean intake 4·70 g/day, 4·44-5.05; change 0·24 events per 1000 years, -2·12 to 2·61, p=0·8391), and a positive but non-significant association in the highest tertile (highest tertile >5·08 g/day, mean intake 5·75 g/day, >5·08-7·49; change 0·37 events per 1000 years, -0·03 to 0·78, p=0·0712). A strong association was seen with stroke in China (mean sodium intake 5·58 g/day, 0·42 events per 1000 years, 95% CI 0·16 to 0·67, p=0·0020) compared with in other countries (4·49 g/day, -0·26 events, -0·46 to -0·06, p=0·0124; p<0·0001 for heterogeneity). All major cardiovascular outcomes decreased with increasing potassium intake in all countries.

INTERPRETATION: Sodium intake was associated with cardiovascular disease and strokes only in communities where mean intake was greater than 5 g/day. A strategy of sodium reduction in these communities and countries but not in others might be appropriate.

DESIGN: International prospective cohort study.

SETTING: 18 high, middle, and low income countries, sampled from urban and rural communities.

PARTICIPANTS: 103 570 people who provided morning fasting urine samples.

MAIN OUTCOME MEASURES: Association of estimated 24 hour urinary sodium and potassium excretion (surrogates for intake) with all cause mortality and major cardiovascular events, using multivariable Cox regression. A six category variable for joint sodium and potassium was generated: sodium excretion (low (<3 g/day), moderate (3-5 g/day), and high (>5 g/day) sodium intakes) by potassium excretion (greater/equal or less than median 2.1 g/day).

RESULTS: Mean estimated sodium and potassium urinary excretion were 4.93 g/day and 2.12 g/day, respectively. After a median follow-up of 8.2 years, 7884 (6.1%) participants had died or experienced a major cardiovascular event. Increasing urinary sodium excretion was positively associated with increasing potassium excretion (unadjusted r=0.34), and only 0.002% had a concomitant urinary excretion of <2.0 g/day of sodium and >3.5 g/day of potassium. A J-shaped association was observed of sodium excretion and inverse association of potassium excretion with death and cardiovascular events. For joint sodium and potassium excretion categories, the lowest risk of death and cardiovascular events occurred in the group with moderate sodium excretion (3-5 g/day) and higher potassium excretion (21.9% of cohort). Compared with this reference group, the combinations of low potassium with low sodium excretion (hazard ratio 1.23, 1.11 to 1.37; 7.4% of cohort) and low potassium with high sodium excretion (1.21, 1.11 to 1.32; 13.8% of cohort) were associated with the highest risk, followed by low sodium excretion (1.19, 1.02 to 1.38; 3.3% of cohort) and high sodium excretion (1.10, 1.02 to 1.18; 29.6% of cohort) among those with potassium excretion greater than the median. Higher potassium excretion attenuated the increased cardiovascular risk associated with high sodium excretion (P for interaction=0.007).

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.

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.

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.

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.

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).

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.

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).

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.

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.

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.

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.