METHODS: A total of 2406 Malaysian children aged 5 to 12 years, who had participated in the South East Asian Nutrition Surveys (SEANUTS), were included in this study. Cognitive performance [non-verbal intelligence quotient (IQ)] was measured using Raven's Progressive Matrices, while socioeconomic characteristics were determined using parent-report questionnaires. Body mass index (BMI) was calculated using measured weight and height, while BMI-for-age Z-score (BAZ) and height-for-age Z-score (HAZ) were determined using WHO 2007 growth reference.
RESULTS: Overall, about a third (35.0%) of the children had above average non-verbal IQ (high average: 110-119; superior: ≥120 and above), while only 12.2% were categorized as having low/borderline IQ ( 3SD), children from very low household income families and children whose parents had only up to primary level education had the highest prevalence of low/borderline non-verbal IQ, compared to their non-obese and higher socioeconomic counterparts. Parental lack of education was associated with low/borderline/below average IQ [paternal, OR = 2.38 (95%CI 1.22, 4.62); maternal, OR = 2.64 (95%CI 1.32, 5.30)]. Children from the lowest income group were twice as likely to have low/borderline/below average IQ [OR = 2.01 (95%CI 1.16, 3.49)]. Children with severe obesity were twice as likely to have poor non-verbal IQ than children with normal BMI [OR = 2.28 (95%CI 1.23, 4.24)].
CONCLUSIONS: Children from disadvantaged backgrounds (that is those from very low income families and those whose parents had primary education or lower) and children with severe obesity are more likely to have poor non-verbal IQ. Further studies to investigate the social and environmental factors linked to cognitive performance will provide deeper insights into the measures that can be taken to improve the cognitive performance of Malaysian children.
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).
METHODS: The Prospective Urban Rural Epidemiology (PURE) study is a large, epidemiological cohort study of individuals aged 35-70 years (enrolled between Jan 1, 2003, and March 31, 2013) in 18 countries with a median follow-up of 7·4 years (IQR 5·3-9·3). Dietary intake of 135 335 individuals was recorded using validated food frequency questionnaires. The primary outcomes were total mortality and major cardiovascular events (fatal cardiovascular disease, non-fatal myocardial infarction, stroke, and heart failure). Secondary outcomes were all myocardial infarctions, stroke, cardiovascular disease mortality, and non-cardiovascular disease mortality. Participants were categorised into quintiles of nutrient intake (carbohydrate, fats, and protein) based on percentage of energy provided by nutrients. We assessed the associations between consumption of carbohydrate, total fat, and each type of fat with cardiovascular disease and total mortality. We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random intercepts to account for centre clustering.
FINDINGS: During follow-up, we documented 5796 deaths and 4784 major cardiovascular disease events. Higher carbohydrate intake was associated with an increased risk of total mortality (highest [quintile 5] vs lowest quintile [quintile 1] category, HR 1·28 [95% CI 1·12-1·46], ptrend=0·0001) but not with the risk of cardiovascular disease or cardiovascular disease mortality. Intake of total fat and each type of fat was associated with lower risk of total mortality (quintile 5 vs quintile 1, total fat: HR 0·77 [95% CI 0·67-0·87], ptrend<0·0001; saturated fat, HR 0·86 [0·76-0·99], ptrend=0·0088; monounsaturated fat: HR 0·81 [0·71-0·92], ptrend<0·0001; and polyunsaturated fat: HR 0·80 [0·71-0·89], ptrend<0·0001). Higher saturated fat intake was associated with lower risk of stroke (quintile 5 vs quintile 1, HR 0·79 [95% CI 0·64-0·98], ptrend=0·0498). Total fat and saturated and unsaturated fats were not significantly associated with risk of myocardial infarction or cardiovascular disease mortality.
INTERPRETATION: High carbohydrate intake was associated with higher risk of total mortality, whereas total fat and individual types of fat were related to lower total mortality. Total fat and types of fat were not associated with cardiovascular disease, myocardial infarction, or cardiovascular disease mortality, whereas saturated fat had an inverse association with stroke. Global dietary guidelines should be reconsidered in light of these findings.
FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).
DESIGN: DP were derived from the MANS FFQ using principal component analysis. The cross-sectional association of the derived DP with prevalence of overweight was analysed.
SETTING: Malaysia.
PARTICIPANTS: Nationally representative sample of Malaysian adults from MANS (2003, n 6928; 2014, n 3000).
RESULTS: Three major DP were identified for both years. These were 'Traditional' (fish, eggs, local cakes), 'Western' (fast foods, meat, carbonated beverages) and 'Mixed' (ready-to-eat cereals, bread, vegetables). A fourth DP was generated in 2003, 'Flatbread & Beverages' (flatbread, creamer, malted beverages), and 2014, 'Noodles & Meat' (noodles, meat, eggs). These DP accounted for 25·6 and 26·6 % of DP variations in 2003 and 2014, respectively. For both years, Traditional DP was significantly associated with rural households, lower income, men and Malay ethnicity, while Western DP was associated with younger age and higher income. Mixed DP was positively associated with women and higher income. None of the DP showed positive association with overweight risk, except for reduced adjusted odds of overweight with adherence to Traditional DP in 2003.
CONCLUSIONS: Overweight could not be attributed to adherence to a single dietary pattern among Malaysian adults. This may be due to the constantly morphing dietary landscape in Malaysia, especially in urban areas, given the ease of availability and relative affordability of multi-ethnic and international foods. Timely surveys are recommended to monitor implications of these changes.
DESIGN: Use of the International Tobacco Control Policy Evaluation Project surveys of smokers, using the 2007 survey wave (or later, where necessary).
SETTINGS: Australia, Canada, China, France, Germany, Ireland, Malaysia, Mexico, the Netherlands, New Zealand, South Korea, Thailand, United Kingdom, Uruguay and United States.
PARTICIPANTS: Samples of smokers from 15 countries.
MEASUREMENTS: Self-report on use of cessation aids and on visits to health professionals and provision of cessation advice during the visits.
FINDINGS: Prevalence of quit attempts in the last year varied from less than 20% to more than 50% across countries. Similarly, smokers varied greatly in reporting visiting health professionals in the last year (<20% to over 70%), and among those who did, provision of advice to quit also varied greatly. There was also marked variability in the levels and types of help reported. Use of medication was generally more common than use of behavioural support, except where medications are not readily available.
CONCLUSIONS: There is wide variation across countries in rates of attempts to stop smoking and use of assistance with higher overall use of medication than behavioural support. There is also wide variation in the provision of brief advice to stop by health professionals.
MATERIALS AND METHODS: We analysed internationally comparable representative household survey data from 33,482 respondents aged ≥ 15 years in Indonesia, Malaysia, Romania, Argentina and Nigeria for determinants of tobacco use within each country. Socio-demographic variables analysed included gender, age, residency, education, wealth index and awareness of smoking health consequences. Current tobacco use was defined as smoking or use of smokeless tobacco daily or occasionally.
RESULTS: The overall prevalence of tobacco use varied from 5.5% in Nigeria to 35.7% in Indonesia and was significantly higher among males than females in all five countries. Odds ratios for current tobacco use were significantly higher among males for all countries [with the greatest odds among Indonesian men (OR=67.4, 95% CI: 51.2-88.7)] and among urban dwellers in Romania. The odds of current tobacco use decreased as age increased for all countries except Nigeria where. The reverse was true for Argentina and Nigeria. Significant trends for decreasing tobacco use with increasing educational levels and wealth index were seen in Indonesia, Malaysia and Romania. Significant negative associations between current tobacco use and awareness of adverse health consequences of smoking were found in all countries except Argentina.
CONCLUSIONS: Males and the socially and economically disadvantaged populations are at the greatest risk of tobacco use. Tobacco control interventions maybe tailored to this segment of population and incorporate educational interventions to increase knowledge of adverse health consequences of smoking.
METHODS: In this multinational, prospective cohort study, we examined associations for 14 potentially modifiable risk factors with mortality and cardiovascular disease in 155 722 participants without a prior history of cardiovascular disease from 21 high-income, middle-income, or low-income countries (HICs, MICs, or LICs). The primary outcomes for this paper were composites of cardiovascular disease events (defined as cardiovascular death, myocardial infarction, stroke, and heart failure) and mortality. We describe the prevalence, hazard ratios (HRs), and population-attributable fractions (PAFs) for cardiovascular disease and mortality associated with a cluster of behavioural factors (ie, tobacco use, alcohol, diet, physical activity, and sodium intake), metabolic factors (ie, lipids, blood pressure, diabetes, obesity), socioeconomic and psychosocial factors (ie, education, symptoms of depression), grip strength, and household and ambient pollution. Associations between risk factors and the outcomes were established using multivariable Cox frailty models and using PAFs for the entire cohort, and also by countries grouped by income level. Associations are presented as HRs and PAFs with 95% CIs.
FINDINGS: Between Jan 6, 2005, and Dec 4, 2016, 155 722 participants were enrolled and followed up for measurement of risk factors. 17 249 (11·1%) participants were from HICs, 102 680 (65·9%) were from MICs, and 35 793 (23·0%) from LICs. Approximately 70% of cardiovascular disease cases and deaths in the overall study population were attributed to modifiable risk factors. Metabolic factors were the predominant risk factors for cardiovascular disease (41·2% of the PAF), with hypertension being the largest (22·3% of the PAF). As a cluster, behavioural risk factors contributed most to deaths (26·3% of the PAF), although the single largest risk factor was a low education level (12·5% of the PAF). Ambient air pollution was associated with 13·9% of the PAF for cardiovascular disease, although different statistical methods were used for this analysis. In MICs and LICs, household air pollution, poor diet, low education, and low grip strength had stronger effects on cardiovascular disease or mortality than in HICs.
INTERPRETATION: Most cardiovascular disease cases and deaths can be attributed to a small number of common, modifiable risk factors. While some factors have extensive global effects (eg, hypertension and education), others (eg, household air pollution and poor diet) vary by a country's economic level. Health policies should focus on risk factors that have the greatest effects on averting cardiovascular disease and death globally, with additional emphasis on risk factors of greatest importance in specific groups of countries.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).