METHODS: Questions about tobacco smoking, smokeless tobacco use, and betel quid chewing were used to create outcome variables such as tobacco smoking, smokeless tobacco use, and 'dual use' (tobacco use and betel quid chewing). Sex-stratified weighted prevalence rates, distribution by socio-demographic factors were presented. Association of demographic factors with tobacco and/or betel quid chewing was assessed by multinomial logistic regression.

OBJECTIVE: Explore the relationship between domestic violence on the decision-making power of married women in Myanmar.

DESIGN: Cross-sectional.

SETTING: National, both urban and rural areas of Myanmar.

PATIENTS AND METHODS: Data from the Myanmar Demographic and Health Survey 2015-16 were used in this analysis. In that survey, married women aged between 15 to 49 years were selected for interview using a multistage cluster sampling technique. The dependent variables were domestic violence and the decision-making power of women. Independent variables were age of the respondents, educational level, place of residence, employment status, number of children younger than 5 years of age and wealth index.

MAIN OUTCOME MEASURES: Domestic violence and decision-making power of women.

SAMPLE SIZE: 7870 currently married women.

RESULTS: About 50% respondents were 35 to 49 years of age and the mean (SD) age was 35 (8.4) years. Women's place of residence and employment status had a significant impact on decision-making power whereas age group and decision-making power of women had a relationship with domestic violence.

CONCLUSION: Giving women decision making power will be indispensable for the achievement of sustainable development goals. Government and other stakeholders should emphasize this to eliminate violence against women.

LIMITATIONS: Use of secondary data analysis of cross-sectional study design and cross-sectional studies are not suitable design to assess this causality. Secondly the self-reported data on violence may be subject to recall bias.

OBJECTIVE: To identify and summarize occupational hazards among oil palm plantation workers.

METHODS: A search was carried out in June 2018 in PubMed, Web of Science, Scopus, and Ovid. Relevant publications were identified by a systematic search of four databases and relevant journals. Publications were included if they examined occupational hazards in oil palm plantation workers.

RESULTS: 941 publications were identified; of these, 25 studies were found eligible to be included in the final review. Of the 25 studies examined, 19 were conducted in Malaysia, 2 in Costa Rica, and one each in Ghana, Indonesia, Myanmar, Papua New Guinea, and Cameroon. Oil palm plantation workers were found to be at risk of musculoskeletal conditions, injuries, psychosocial disorders, and infectious diseases such as malaria and leptospirosis. In addition, they have potential exposure to paraquat and other pesticides.

METHODS: This narrative systematic review addressed MSAs targeted to MMPs in Myanmar for malaria prevention. We searched relevant studies in electronic databases and present the narrative findings in 4 domains: stakeholder groups, net coverage and utilization, social determinates, and facilitators/barriers.

RESULTS: Nine studies were included. The review identified stakeholders involved in intersectoral collaboration. Net ownership was higher than utilization rates in the MARC zones and rates remained below the WHO recommended target of 100%. There was inadequate description of roles and responsibilities for implementation and on channels of communication within the partnerships and with the Government.

DESIGN: Two cross-sectional studies using the WHO STEPS methodology.

SETTING: Both the urban and rural areas of the Yangon Region, Myanmar.

PARTICIPANTS: A total of 1370 men and women aged 25-74 years participated based on a multistage cluster sampling. Physically and mentally ill people, monks, nuns, soldiers and institutionalised people were excluded.

RESULTS: Compared with rural counterparts, urban dwellers had a significantly higher age-standardised prevalence of hypercholesterolaemia (50.7% vs 41.6%; p=0.042) and a low HDL level (60.6% vs 44.4%; p=0.001). No urban-rural differences were found in the prevalence of hypertriglyceridaemia and high LDL. Men had a higher age-standardised prevalence of hypertriglyceridaemia than women (25.1% vs 14.8%; p<0.001), while the opposite pattern was found in the prevalence of a high LDL (11.3% vs 16.3%; p=0.018) and low HDL level (35.3% vs 70.1%; p<0.001).Compared with rural inhabitants, urban dwellers had higher age-standardised mean levels of total cholesterol (5.31 mmol/L, SE: 0.044 vs 5.05 mmol/L, 0.068; p=0.009), triglyceride (1.65 mmol/L, 0.049 vs 1.38 mmol/L, 0.078; p=0.017), LDL (3.44 mmol/L, 0.019 vs 3.16 mmol/L, 0.058; p=0.001) and lower age-standardised mean levels of HDL (1.11 mmol/L, 0.010 vs 1.25 mmol/L, 0.012; p<0.001). In linear regression, the total cholesterol was significantly associated with an urban location among men, but not among women.

METHODS: In 2004 and 2014, household-based cross-sectional studies were conducted in urban and rural areas of Yangon Region using the WHO STEPS protocol. Through a multi-stage cluster sampling method, a total of 4448 and 1486 participated in 2004 and 2014, respectively, with the response rates above 89%.

RESULTS: From 2004 to 2014, there was a significant increase in the age-standardized prevalence of hypertension from 26.7% (95% CI:24.4-29.1) - 34.6% (32.2-37.1), as well as an awareness from 19.4% (17.2-21.9) to 27.8% (24.9-31.0), while treatment and control rates did not change. The age-standardized mean systolic blood pressure increased from 122.8 (SE) ± 0.82 mmHg in 2004 to 128.1 ± 0.53 mmHg in 2014, whereas diastolic blood pressure increased from 76.2 ± 0.35 mmHg to 80.9 ± 0.53 mmHg. In multivariate analyses, hypertension was significantly associated with age, alcohol consumption, overweight and diabetes in both 2004 and 2014, and additionally associated with low physical activity and hypercholesterolemia in 2004. Combining all data, a significant association between study-year and hypertension persisted in different models with an adjustment for socio-demographic variables and behavioural variables, but not when adjusting for a combination of socio-demographic variables, the metabolic variables, BMI and hypercholesterolemia.

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.

METHODOLOGY/PRINCIPAL FINDINGS: A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines).