Methods: A cross-sectional survey included 3353 university students from Indonesia, Malaysia, Myanmar, Thailand and Vietnam, median age 20 years (interquartile range 3 years).
Results: In all five ASEAN countries, the study found a prevalence no soft drink consumption in the past 30 days of 20.3%, less than one time a day 44.7%, once a day 25.4% and two or more times a day 9.6%. In the adjusted logistic regression analysis, higher frequency of soft drink consumption (one and/or two or more times a day) was associated with externalizing behaviour (in physical fight, injury, current tobacco use, problem drinking, drug use, pathological internet use and gambling behaviour), and higher frequency of soft drink consumption (two or more times a day) was associated with depression in females, but no association was found for the general student population in relation to internalizing behaviour (depression, posttraumatic stress disorder, suicidal ideation, suicide plan, suicide attempt and sleeping problem).
Conclusions: Findings suggest that carbonated soft drink consumption is associated with a number of externalizing but not internalizing health risk behaviours.
METHODS: A cross-sectional questionnaire survey and anthropometric measurement were conducted with undergraduate university students that were randomly recruited. The Eating Attitudes Test (EAT-26) was utilized to determine the prevalence of disordered eating attitudes. The sample included 3148 university students, with a mean age of 20.5 years, SD = 1.6.
RESULTS: Using the EAT-26, 11.5% of the students across all countries were classified as being at risk for an eating disorder, ranging from below 10% in Indonesia, Thailand and Vietnam to 13.8% in Malaysia and 20.6% in Myanmar. In multivariable logistic regression analysis, sociodemographic factors (wealthier subjective economic status, and living in a lower middle income country), underweight and overweight body weight perception, psychological factors (depression symptoms and pathological internet use), and being obese were associated with eating disorder risk.
CONCLUSIONS: Relatively high rates of eating disorder risk were found. This result calls for increased awareness, understanding of eating disorders and related risk factors and interventions in university students in ASEAN.
LEVEL OF EVIDENCE: Level V, descriptive cross-sectional survey.
METHODS: This cross-sectional study was conducted in 2015 among 8809 undergraduate university students from 13 universities in Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam using self-administered questionnaire. Multivariate logistic regression analyses were conducted to explore the associated factors.
RESULTS: More than half (62.3%) of the study sample were female with a mean age of 20.5 (SD = 2.0) years. Of total, 12.8% were infrequent (
METHODS: This multi-country cross-sectional study was conducted in 2015 in Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam. A multi-stage cluster sampling was used to select undergraduate students from one or two universities in each country for self-administered questionnaire survey. Multivariate logistic regression analyses was performed to explore risk factors related to illicit drug use.
RESULTS: Participants included 7,923 students with a mean age of 20.6 years (SD = 2.8), ranging from 18-30 years. The overall prevalence of frequent (≥10 times), infrequent (1-9 times) and ever (at least once) illicit drug use in the past 12 months was 2.2, 14.7, and 16.9%, respectively. After adjustment, male students were significantly less likely to be infrequent (1-9 times vs. never), but significantly more likely to be ever users compared to females. Compared to those living with parents/guardians, students living away from parents/guardians were significantly less likely to be frequent (≥10 times vs. never) and infrequent users. Students from lower-middle-income countries were significantly more likely to be frequent and infrequent users, but significantly less likely to be ever users compared to those from upper-middle or high-income countries. Students with poor subjective health status were significantly more likely to be frequent users compared to those who reported good subjective health status. Students who reported binge drinking in the past month were significantly more likely to be infrequent users, but significantly less likely to be ever users.
CONCLUSIONS: Our findings indicate that prevalence of illicit drug use among university students in the ASEAN region varied by country. Concerted social intervention programs should be designed to address related health and behavioral problems such as illicit drug use and alcohol drinking with particular emphasis on at-risk subgroups of this young population.
Methods: This cross-sectional study was conducted July-August 2018 in three regions in Indonesia. Adults aged 60 years and above (n=427) were recruited via random sampling from community clinics and public and private elderly homes. They responded to interview-administered questions and provided measurements on sociodemographics and various health variables, including falls and fall risk. Fall risk was assessed with the STEADI (Stopping Elderly Accidents, Deaths, & Injuries) screen. Multivariable logistic regression was conducted to estimate associations with fall and fall risk.
Results: In the year immediately preceding the study, 29.0% of participants had suffered a fall. Approximately one-third of women (31.1%) and one-fifth of men (20.4%) reported a fall in the past year, and 25.4% of community dwellers and 32.7% of institutionalized older adults had fallen. The overall proportion of fall risk was 45.4%, 49.0% among women, 38.0% among men, 50.5% in the institutionalized setting, and 40.4% in the community setting. In adjusted logistic regression analysis, older age (OR: 1.89, CI: 1.06, 3.37), private elderly home setting (OR:2.04, CI: 1.10, 3.78), and being female (OR: 0.49, CI: 0.30, 0.82) were associated with falls in the preceding 12 months. Older age (80-102 years) (OR: 2.55, CI: 1.46, 4.46), private elderly home residence (OR: 2.24, CI: 1.19, 4.21), lack of education (OR: 0.51, CI: 0.28, 0.93), memory problems (OR: 1.81, CI: 1.09, 2.99), and arthritis (OR: 2.97, CI: 1.26, 7.00) were associated with fall risk by the STEADI screen. In stratified analysis by setting, being female (OR: 0.49, CI: 0.25, 0.95) and living in urban areas (OR: 1.97, CI: 1.03, 3.76) were associated with falls in the institutionalized setting, and having near vision problems (OR: 2.32, CI: 1.09, 4.93) was associated with falls in the community setting. Older age (OR: 2.87, CI: 1.36, 6.07) was associated with fall risk in the institutionalized setting, and rural residence (OR: 0.37, CI: 0.15, 0.93) and having a joint disorder or arthritis (OR: 4.82, CI: 1.28, 16.61) were associated with fall risk in the community setting.
Conclusion: A high proportion of older adults in community and institutional care in Indonesia have fallen or were at risk of falling in the preceding 12 months. Health variables for fall and fall risk were identified for the population overall and for specific populations in the home care and community setting that could help in designing fall-prevention strategies.
METHODS: As data on policy indicators were straightforward and fully available, we focused on studying 25 non-policy indicators: 23 GMFs and 2 PMIs. Gathering data availability of the target indicators was conducted among NCD surveillance experts from the six selected countries during May-June 2020. Our research team found information regarding whether the country had no data at all, was using WHO estimates, was providing 'expert judgement' for the data, or had actual data available for each target indicator. We triangulated their answers with several WHO data sources, including the WHO Health Observatory Database and various WHO Global Reports on health behaviours (tobacco, alcohol, diet, and physical activity) and NCDs. We calculated the percentages of the indicators that need improvement by both indicator category and country.
RESULTS: For all six studied countries, the health-service indicators, based on responses to the facility survey, are the most lacking in data availability (100% of this category's indicators), followed by the health-service indicators, based on the population survey responses (57%), the mortality and morbidity indicators (50%), the behavioural risk indicators (30%), and the biological risk indicators (7%). The countries that need to improve their NCD surveillance data availability the most are Cambodia (56% of all indicators) and Lao PDR (56%), followed by Malaysia (36%), Vietnam (36%), Myanmar (32%), and Thailand (28%).
CONCLUSION: Some of the non-policy GMF and PMI indicators lacked data among the six studied countries. To achieve the global NCDs targets, in the long run, the six countries should collect their own data for all indicators and begin to invest in and implement the facility survey and the population survey to track NCDs-related health services improvements once they have implemented the behavioural and biological Health Risks Population Survey in their countries.