RESEARCH DESIGN AND METHODS: The prevalence of diabetes, defined as self-reported or fasting glycemia ≥7 mmol/L, was documented in 119,666 adults from three high-income (HIC), seven upper-middle-income (UMIC), four lower-middle-income (LMIC), and four low-income (LIC) countries. Relationships between diabetes and its risk factors within these country groupings were assessed using multivariable analyses.

RESULTS: Age- and sex-adjusted diabetes prevalences were highest in the poorer countries and lowest in the wealthiest countries (LIC 12.3%, UMIC 11.1%, LMIC 8.7%, and HIC 6.6%; P < 0.0001). In the overall population, diabetes risk was higher with a 5-year increase in age (odds ratio 1.29 [95% CI 1.28-1.31]), male sex (1.19 [1.13-1.25]), urban residency (1.24 [1.11-1.38]), low versus high education level (1.10 [1.02-1.19]), low versus high physical activity (1.28 [1.20-1.38]), family history of diabetes (3.15 [3.00-3.31]), higher waist-to-hip ratio (highest vs. lowest quartile; 3.63 [3.33-3.96]), and BMI (≥35 vs. <25 kg/m(2); 2.76 [2.52-3.03]). The relationship between diabetes prevalence and both BMI and family history of diabetes differed in higher- versus lower-income country groups (P for interaction < 0.0001). After adjustment for all risk factors and ethnicity, diabetes prevalences continued to show a gradient (LIC 14.0%, LMIC 10.1%, UMIC 10.9%, and HIC 5.6%).

METHODS: Two cross-sectional studies were conducted in urban and rural areas of Yangon Region in 2013 and 2014 respectively, using the WHO STEPwise approach to surveillance of risk factors of NCDs. Through a multi-stage cluster sampling method, 1486 participants were recruited.

RESULTS: Age-standardized prevalence of the behavioral risk factors tended to be higher in the rural than urban areas for all included factors and significantly higher for alcohol drinking (19.9% vs. 13.9%; p = 0.040) and low fruit & vegetable consumption (96.7% vs. 85.1%; p = 0.001). For the metabolic risk factors, the tendency was opposite, with higher age-standardized prevalence estimates in urban than rural areas, significantly for overweight and obesity combined (40.9% vs. 31.2%; p = 0.023), obesity (12.3% vs.7.7%; p = 0.019) and diabetes (17.2% vs. 9.2%; p = 0.024). In sub-group analysis by gender, the prevalence of hypercholesterolemia and hypertriglyceridemia were significantly higher in urban than rural areas among males, 61.8% vs. 40.4%; p = 0.002 and 31.4% vs. 20.7%; p = 0.009, respectively. Mean values of age-standardized metabolic parameters showed higher values in urban than rural areas for both male and female. Based on WHO age-standardized Framingham risk scores, 33.0% (95% CI = 31.7-34.4) of urban dwellers and 27.0% (95% CI = 23.5-30.8) of rural dwellers had a moderate to high risk of developing CHD in the next 10 years.

METHODS: A total of 176 adolescents in selected urban areas in the states of Wilayah Persekutuan and Selangor were selected. The Suicide Ideation Scale (SIS) was used to measure the level of severity or tendency of suicidal ideation. The Multidimensional Scale of Perceived Social Support (MSPSS) was used to measure the perceived social support received by the respondent while the Spiritual Wellbeing Scale (SWBS) was used to measure the religious wellbeing (RWB), the existential wellbeing (EWB) and the overall score of spiritual wellbeing (SWB).

RESULTS: The study found that both RWB and EWB showed significant negative correlation with suicidal ideation. Similarly, support from family and friends also showed a negative correlation with suicidal ideation. Further analysis using multiple regressions showed that RWB and SWB, and family support predict suicidal ideation in adolescents.

METHODS: Between 2009 and 2012, a kilometre-long walk was completed by trained investigators in 462 communities across 16 countries to collect data on tobacco marketing. We interviewed community members about their exposure to traditional and non-traditional marketing in the previous six months. To examine differences in marketing between urban and rural communities and between high-, middle- and low-income countries, we used multilevel regression models controlling for potential confounders.

FINDINGS: Compared with high-income countries, the number of tobacco advertisements observed was 81 times higher in low-income countries (incidence rate ratio, IRR: 80.98; 95% confidence interval, CI: 4.15-1578.42) and the number of tobacco outlets was 2.5 times higher in both low- and lower-middle-income countries (IRR: 2.58; 95% CI: 1.17-5.67 and IRR: 2.52; CI: 1.23-5.17, respectively). Of the 11,842 interviewees, 1184 (10%) reported seeing at least five types of tobacco marketing. Self-reported exposure to at least one type of traditional marketing was 10 times higher in low-income countries than in high-income countries (odds ratio, OR: 9.77; 95% CI: 1.24-76.77). For almost all measures, marketing exposure was significantly lower in the rural communities than in the urban communities.

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.

SETTING: The study was carried out in Kuala Lumpur, the capital of Malaysia.

METHODS: A cross-sectional study using a self administered questionnaire including adults above 21 years old as an exit survey was conducted in Kuala Lumpur.

MAIN OUTCOME MEASURES: Number of medications taken in a day by participants, source of medication for the treatment of minor illnesses among participants, common illnesses chosen for self-medication by participants, and the sources of information of participants.

RESULTS: Of 314 participants, 62.7% had taken at least one medication in the past week without prescription and 62.7% believed that over the counter medicines were just as effective as those prescribed by doctors. 69.4% would seek a healthcare professional's advice before purchasing any medication and 86.9% would consult a pharmacist prior to buying medication from the pharmacy. Only 86% checked the expiry dates on medications and 54.5% reported keeping leftover medication.

METHODS: We undertook analysis on 11,821 subjects from six seroprevalence surveys conducted in Malaysia between 2001 and 2013, which composed of five urban and two rural series.

RESULTS: Prevalence of dengue increased with age in both urban and rural locations in Malaysia, which exceeded 90 % among those aged 70 years or beyond. The age-specific rates of the 5 urban surveys overlapped without clear separation among them, while prevalence was lower in younger subjects in rural series than in urban series, the trend reversed in older subjects. There were no differences in the seroprevalence by gender, ethnicity or region. Poisson regression model confirmed the prevalence have not changed in urban areas since 2001 but in rural areas, there was a significant positive time trend such that by year 2008, rural prevalence was as high as in urban areas.

METHODS: This prospective cross-sectional study aimed to identify rural-urban differences in risk factors for low birth weight among women in Malaysia. Pregnant women at ≥20 weeks of gestation in urban and rural Malaysia (n = 437) completed questionnaires on sociodemographic characteristics and physical activity. Weight and middle-upper arm circumference were measured. Infant birth outcomes were extracted from medical records.

RESULTS: The overall prevalence of low birth weight infants was 6.38%. Rural women had more low birth weight infants than urban women (9.8% vs 2.0%, p = 0.03). Findings showed rural women were less sedentary (p = 0.003) and participated in more household/caregiving activities (p = 0.036), sports activities (p = 0.01) and less occupational activity (p urban women. Logistic regression revealed that older age (OR = 1.395, 95% Cl = 1.053 to 1.846), low parity (OR = 0.256, 95% Cl = 0.088-0.747) and low middle-upper arm circumference (OR = 0.738, 95% Cl = 0.552 to 0.987) increased the risk of low birth weight infants in rural, but not in urban women.