METHODS: Data were extracted from a cross-sectional study, the Malaysian Adolescent Health Risk Behaviour (MyAHRB) study, which was conducted from May to September 2013 across 11 states in Peninsular Malaysia. A two-stage proportionate-to-size sampling method was employed to select a total of 3578 school-going adolescents aged 16-17 years from 20 selected schools in urban and rural settlements, respectively. The MyAHRB study adopted a set of self-administered questionnaires adapted from the Global School-based Student's Health Survey (GSHS) and the Youth Risk Behaviour Surveillance.
RESULTS: The results from the analysis of 2991 school-going adolescents aged 16-17 years showed that 16 (in boys) and 15 (in girls) out of 32 combinations of lifestyle risk behaviours clustered. Girls (aOR 2.82, 95% CI: 2.32-3.43) were significantly more likely to have clustered risk behaviours than boys; however, no significant associated factors were observed among girls. In contrast, boys of Malay descent (aOR 0.64, 95% CI: 0.46-0.89) or boys who had at least three friends (aOR 0.65, 95% CI: 0.43-0.99) were less likely to engage in multiple risk behaviours.
CONCLUSION: The present study demonstrated the clustering of multiple risk behaviours that occurred in both genders; these results suggest that multiple behaviour intervention programmes, instead of programmes based on siloed approaches, should be advocated and targeted to the high-risk sub-populations identified in the present study.
METHODS: The MELoR study recruited community-dwelling adults aged 55 years and over, selected through stratified random sampling from three parliamentary constituencies. The baseline data collected during the first wave was obtained through face-to-face interviews in participants' homes using computer-assisted questionnaires. During their baseline assessments, participants were asked whether they had ever experienced a blackout in their lifetime and if they had experienced a blackout in the preceding 12 months.
RESULTS: Information on blackouts and ethnicity were available for 1530 participants. The weight-adjusted lifetime cumulative incidence of syncope for the overall population aged 55 years and above was 27.7%. The estimated lifetime cumulative incidence according to ethnic groups was 34.6% for Malays, 27.8% for Indians and 23.7% for Chinese. The estimated 12-month incidence of syncope was 6.1% overall, equating to 11.7% for Malays, 8.7 % for Indians and 2.3% for Chinese. Both Malay [odds ratio (OR) 1.46; 95% confidence interval (CI) 1.10-1.95 and OR 3.62, 95% CI 1.96-6.68] and Indian (OR 1.34; 95% CI 1.01-1.80 and OR 3.31, 1.78-6.15) ethnicities were independently associated with lifetime and 12-month cumulative incidence of syncope, respectively, together with falls, dizziness and myocardial infarction.
CONCLUSION: Ethnic differences exist for lifetime cumulative incidence of syncope in community-dwelling individuals aged 55 years and over in an urban area in Southeast Asia. Future studies should now seek to determine potential genetic, cultural and lifestyle differences which may predispose to syncope.
Methods: We used information of the EPIC-NL cohort, a prospective cohort of 39 393 men and women, aged 20-70 years at recruitment. A lifestyle questionnaire and a validated food frequency questionnaire were administered at recruitment (1993-97). Low adherence to a Mediterranean-style diet was used to determine an unhealthy dietary pattern. Lifestyle-related factors included body mass index, waist circumference, smoking status, physical activity level, dietary supplement use and daily breakfast consumption. Multivariate logistic regression analyses were performed for the total population and by strata of educational level.
Results: In total 30% of the study population had an unhealthy dietary pattern: 39% in the lowest educated group and 20% in the highest educated group. Physical inactivity, a large waist circumference, no dietary supplement use and skipping breakfast were associated with an unhealthy dietary pattern in both low and high educated participants. Among low educated participants, current smokers had a greater odds of an unhealthy diet compared with never smokers: OR 1.42 (95% CI: 1.25; 1.61). This association was not observed in the high educated group.
Conclusions: Most associations between lifestyle-related factors and unhealthy diet were consistent across educational levels, except for smoking. Only among low educated participants, current smokers reported an unhealthier dietary pattern in comparison to never smokers. These results can be used in the development of targeted health promotion strategies.
Subjects and Methods: In an analytical cross-sectional design, we used simple random sampling technique to select 242 multiracial Malaysian male fishermen aged between 18 and 75 years from five fishing villages located at Gurney Drive, Tanjong Tokong, Tanjong Bungah, Batu Ferringhi, and Teluk Bahang to participate in this study. During four consecutive weekends in January 2017, we conducted face-to-face interviews with participants using a pre-validated, interviewer-administered WHO oral health questionnaire. We categorized participants as having "good" or "poor" oral health based on a mean cutoff score of 14. Multivariate regression models were fitted to assess the oral health status and associated lifestyle factors among the study population, using SPSS version 22.
Results: We achieved a response rate of 97.6%. Overall, the prevalence of poor oral health in this study was 47.5%. "Income" (RM/month), "type of fishing," "additional occupation," "age" (years), "frequency of pies, buns consumed," and "frequency of sweets, soft drinks consumed" were significant predictors of oral health status among the fishermen.
Conclusion: Poor oral health is relatively highly prevalent among the fishermen in our study. The oral health status of fishermen in Teluk Bahang was consistent with the national average and significantly associated with their sociodemographic and lifestyle factors. Targeted interventions are required to arrest and reverse this trend.
METHODS: A total of 50 obese children (7-11 years old) were randomized to the intervention group (IG, n = 25) or the control group (CG, n = 25). Data were collected at baseline, at follow-up (every month) and at six months after the end of the intervention. IG received stage-based lifestyle modification intervention based on the Nutrition Practice Guideline for the Management of Childhood Obesity, while CG received standard treatment. Changes in body composition, physical activity and dietary intake were examined in both the intervention and control groups.
RESULTS: Both groups had significant increases in weight (IG: 1.5 ± 0.5 kg; CG: 3.9 ± 0.6 kg) (p
DESIGN AND MEASURES: Data were analysed from the Global School-Based Student Health Survey Timor-Leste (n = 3455). An ordered probit model was used to assess the effects of demographic, lifestyle, social, and psychological factors on different levels of worry-related sleep problems (i.e., no, mild and severe sleep problems).
RESULTS: School-going adolescents were more likely to face mild or severe worry-related sleep problems if they were older, passive smokers, alcohol drinkers and moderately active. School-going adolescents who sometimes or always went hungry were more likely to experience worry-related sleep problems than those who did not. Involvement in physical fights, being bullied, and loneliness were positively associated with the probability of having modest or severe worry-related sleep problems.
CONCLUSION: Age, exposure to second-hand smoke, alcohol consumption, physical activity, going hungry, physical fights, being bullied and loneliness are the important determining factors of adolescent worry-related sleep problems. Policymakers should pay special attention to these factors when formulating intervention measures.
METHODS: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.
RESULTS: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.
CONCLUSIONS: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.
IMPACT: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
METHODS: The association between the WCRF/AICR score (score range 0-6 in men and 0-7 in women; higher scores indicate greater concordance) assessed on average 6.4 years before diagnosis and CRC-specific (n = 872) and overall mortality (n = 1,113) was prospectively examined among 3,292 participants diagnosed with CRC in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (mean follow-up time after diagnosis 4.2 years). Multivariable Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for mortality.
RESULTS: The HRs (95% CIs) for CRC-specific mortality among participants in the second (score range in men/women: 2.25-2.75/3.25-3.75), third (3-3.75/4-4.75), and fourth (4-6/5-7) categories of the score were 0.87 (0.72-1.06), 0.74 (0.61-0.90), and 0.70 (0.56-0.89), respectively (P for trend <0.0001), compared to participants with the lowest concordance with the recommendations (category 1 of the score: 0-2/0-3). Similar HRs for overall mortality were observed (P for trend 0.004). Meeting the recommendations on body fatness and plant food consumption were associated with improved survival among CRC cases in mutually adjusted models.
CONCLUSIONS: Greater concordance with the WCRF/AICR recommendations on diet, physical activity, and body fatness prior to CRC diagnosis is associated with improved survival among CRC patients.
METHODS: In total, 2,008 Malaysian adults with no previous cancer were surveyed using a 42-item questionnaire adapted from the Awareness Measure and the Cancer Awareness Measure-Mythical Causes Scale. Partial least squares structural equation modeling was used to evaluate measurement models.
RESULTS: Despite high educational attainment, only about half of the respondents believed that 7 of the 21 listed established risk factors caused cancer. Factors associated with accurate beliefs included higher socioeconomic status (SES) and having family or friends with cancer. However, 14 of the 21 listed mythical/unproven factors were correctly believed as not cancer-causing by the majority. Women and those with lower SES were more likely to hold misconceptions. Beliefs on established risk factors were significantly associated with perceived risk of cancer. Individuals with stronger beliefs in established risk factors were less likely to be associated with healthy behaviors. Conversely, stronger beliefs in mythical or unproven factors were more likely to be associated with healthy lifestyles.
CONCLUSION: Findings highlight the importance of prioritizing cancer literacy as a key action area in national cancer control plans. The counterintuitive associations between cancer beliefs and lifestyle emphasize the complexity of this relationship, necessitating nuanced approaches to promote cancer literacy and preventive behaviors.
METHODS: A total of 1319 Malaysian adults participated in this cross-sectional online survey. Information on anthropometric data including body weight and height, and lifestyle behaviours including eating pattern, physical activity, and sleep pattern were self-reported by the respondents. A multivariable generalised linear mixed model was used to assess the associations between lifestyle behaviours and body weight changes with adjustment of confounding factors; namely, age, sex, ethnicity, and body weight status before MCO.
RESULTS: During MCO, 41.2% of the respondents perceived that their eating patterns were healthier, but 36.3% reduced their physical activities, and 25.7% had a poorer sleep quality. Further, the proportion of adults who reported having lose weight (32.2%) was almost similar to those who reported having gained weight (30.7%). Lifestyle behaviours including less frequent practice of healthy cooking methods and lunch skipping were associated with weight gain, while less frequent consumption of high fat foods, more frequent physical activity, and good sleep latency were associated with lower risk of weight gain. In contrast, practicing healthy eating concept, skipped lunch, and more frequent physical activity were significantly associated with weight loss.
CONCLUSION: Lifestyle behaviours were associated with body weight changes during MCO. While the COVID-19 pandemic lockdown is necessary to prevent further spread of the disease, promoting healthy lifestyle practices during lockdown should be implemented for a healthy weight and better health.