METHODS: Behavioural Risk Factors Surveillance System data were used to estimate the weight the US population needed to lose to achieve a BMI
METHODS: Data are obtained from the Malaysia Non-Communicable Disease Surveillance-1. Logistic regressions are conducted using a multiracial (Malay, Chinese, Indian and other ethnic groups) sample of 2,447 observations to examine the factors affecting individual decisions to consume FV on a daily basis.
RESULTS: Based on the binary outcomes of whether individuals consumed FV daily, results indicate that work hours, education, age ethnicity, income, gender, smoking status, and location of residence are significantly correlated with daily fruit consumption. Daily vegetable consumption is significantly correlated with income, gender, health condition, and location of residence.
CONCLUSIONS: Our results imply the need for programs to educate and motivate consumers to make healthier dietary choices. Interventions to increase FV consumption by changing behaviors should be considered, as should those that increase public awareness of the dietary benefits of FV. These intervention programs should be targeted at and tailored toward individuals who are less educated, younger, less affluent, males, smokers, and metropolitan dwellers.
METHODS: Data are obtained from 2,436 observations from the Malaysia Non-Communicable Disease Surveillance-1. The multi-ethnic sample is segmented into Malay, Chinese, and Indian/other ethnicities. Ordered probit analysis is conducted and marginal effects of sociodemographic and health lifestyle variables on BMI calculated.
RESULTS: Malays between 41 and 58 years are more likely to be overweight or obese than their 31-40 years counterparts, while the opposite is true among Chinese. Retirees of Chinese and Indian/other ethnicities are less likely to be obese and more likely to have normal BMI than those between 31 and 40 years. Primary educated Chinese are more likely to be overweight or obese, while tertiary-educated Malays are less likely to suffer from similar weight issues as compared to those with only junior high school education. Affluent Malays and Chinese are more likely to be overweight than their low-middle income cohorts. Family illness history is likely to cause overweightness or obesity, irrespective of ethnicity. Malay cigarette smokers have lower overweight and obesity probabilities than non-cigarette smokers.
CONCLUSIONS: There exists a need for flexible policies to address cross-ethnic differences in the sociodemographic and health-lifestyle covariates of BMI.
METHODS: We employed a five-stage scoping review framework, to systematically identify and review eligible articles. Eligibility criteria included a focus on bed bug infestations and reference to mental health impacts. Descriptive information was then extracted from each article, including the specific mental health effects cited.
RESULTS: An initial search yielded 920 unique articles on the topic of bed bugs. Of these, 261 underwent abstract review, and 167 underwent full-text review. Full-text review and subsequent review of reference lists yielded a final sample of 51 articles. Numerous mental health effects were linked to bed bug infestations, including severe psychiatric symptoms. However, the majority (n = 31) of the articles were commentary papers; only five original research articles were identified.
CONCLUSIONS: Although significant mental health effects are often linked to bed bugs, such discussions remain largely anecdotal. Despite recognition that the impact of bed bugs constitutes an important public health concern, little empirical evidence currently exists on this topic.
METHODS: A first round of data collection was conducted in 2014 including interviews with a probability sample of 1102 households and individual interviews with 2058 males and females aged 18-59. In 2016, a second round of data collection was conducted. A fixed effects model was used in the analysis.
RESULTS: The perceived effect of the unrest on the household was associated with an increased reporting of psychiatric symptoms. Furthermore, the migration of a household member for work and the presence of children left behind were related to an increased reporting of psychiatric symptoms among adults, especially among females.
CONCLUSIONS: The unrest and its associated migration was related to an increased reporting of psychiatric symptoms among working age adults in the study population.
METHODS: A population-based cross-sectional study was conducted in Singapore. Participants wore an accelerometer for 7 days to measure physical activity (PA). Demographic, anthropometric and psychological data were also collected. Psychological variables included PA guideline knowledge, motivational profile for PA self-regulation (5 subscales), perceived barriers to PA (4 subscales) and perceived social support for PA. Regression models with adjustment for socio-demographic variables were fitted.
RESULTS: External regulation (b = - 13.03, 95% CI - 34.55; - 1.50) and perceived daily life barriers (b = - 12.63, 95% CI - 24.95; - 0.32) were significantly associated with fewer weekly MVPA minutes. A significant interaction between perceived social support and age (p = 0.046) was found. Social support was significantly negative associated with MVPA minutes in younger (
METHODS: A total of 1844 (780 males and 1064 females) known diabetics aged ≥ 35 years were identified from the South East Asia Community Observatory (SEACO) health and demographic surveillance site database.
RESULTS: 41.3% of the sample had poor glycaemic control. Poor glycaemic control was associated with age and ethnicity, with older participants (65+) better controlled than younger adults (45-54), and Malaysian Indians most poorly controlled, followed by Malay and then Chinese participants. Metabolic risk factors were also highly associated with poor glycaemic control.
CONCLUSIONS: There is a critical need for evidence for a better understanding of the mechanisms of the associations between risk factors and glycaemic control.
METHODS: Data were from the Global Burden of Disease Study 2019. We analysed data from Southeast Asia, including Cambodia, Indonesia, Laos, Malaysia, Maldives, Mauritius, Myanmar, Philippines, Seychelles, Sri Lanka, Thailand, Timor-Leste, and Vietnam.
RESULTS: In 2019, there were 728,500 deaths attributable to tobacco in Southeast Asia, with 128,200 deaths attributed to SHS exposure. The leading causes of preventable deaths were ischemic heart disease, stroke, diabetes mellitus, lower respiratory infections, chronic obstructive pulmonary disease, tracheal, bronchus, and lung cancer. Among deaths attributable to tobacco, females had higher proportions of deaths attributable to SHS exposure than males in Southeast Asia.
CONCLUSION: The burden of preventable deaths in a year due to SHS exposure in Southeast Asia is substantial. The implementation and enforcement of smoke-free policies should be prioritized to reduce the disease burden attributed to passive smoking in Southeast Asia.