METHODS: Prostate cancer cases diagnosed between 2003 and 2008 which met with the inclusion criteria were included in the study. One hundred and twelfth (112) pairs of cases and controls matched by age and ethnicity were analysed. McNemar Odds Ratios (OR(M)) were calculated using McNemar Calculator software for univariate analysis while conditional logistic regression was used for multivariate analysis, both using SPSS version 12.0.
RESULTS: Most of the prostate cancer patients (68.8%) that came for treatment in UKMMC were above 70 years old. The majority were Chinese (50.0%) followed by Malay (46.4%) and Indian (3.6%). Multivariate analysis showed cases were more likely to have a first-degree relative with a history of cancer (OR= 3.77, 95% CI= 1.19-11.85), to have been exposed to pesticides (OR= 5.57, 95% CI= 1.75-17.78) and consumed more meat (OR= 12.23, 95% CI= 3.89-39.01). Significantly reduced risks of prostate cancer were noted among those consuming more vegetables (OR= 0.12, 95% CI= 0.02-0.84), more tomatoes (OR= 0.35, 95% CI= 0.13-0.93) and those who had frequent sexual intercourse (OR= 0.44, 95% CI= 0.19-0.96).
CONCLUSION: Some lifestyle and occupation factors are strong predictors of the occurrence of prostate cancer among patients in UKMMC. More importantly, with the identification of the potentially modifiable risk factors, proper public health intervention can be improved.
METHODS AND RESULTS: We estimated the durations of total daily sleep and daytime naps based on the amount of time in bed and self-reported napping time and examined the associations between them and the composite outcome of deaths and major cardiovascular events in 116 632 participants from seven regions. After a median follow-up of 7.8 years, we recorded 4381 deaths and 4365 major cardiovascular events. It showed both shorter (≤6 h/day) and longer (>8 h/day) estimated total sleep durations were associated with an increased risk of the composite outcome when adjusted for age and sex. After adjustment for demographic characteristics, lifestyle behaviours and health status, a J-shaped association was observed. Compared with sleeping 6-8 h/day, those who slept ≤6 h/day had a non-significant trend for increased risk of the composite outcome [hazard ratio (HR), 1.09; 95% confidence interval, 0.99-1.20]. As estimated sleep duration increased, we also noticed a significant trend for a greater risk of the composite outcome [HR of 1.05 (0.99-1.12), 1.17 (1.09-1.25), and 1.41 (1.30-1.53) for 8-9 h/day, 9-10 h/day, and >10 h/day, Ptrend < 0.0001, respectively]. The results were similar for each of all-cause mortality and major cardiovascular events. Daytime nap duration was associated with an increased risk of the composite events in those with over 6 h of nocturnal sleep duration, but not in shorter nocturnal sleepers (≤6 h).
CONCLUSION: Estimated total sleep duration of 6-8 h per day is associated with the lowest risk of deaths and major cardiovascular events. Daytime napping is associated with increased risks of major cardiovascular events and deaths in those with >6 h of nighttime sleep but not in those sleeping ≤6 h/night.
METHODS: REDISCOVER, a prospective study, enrolled 11,288 adults where sociodemographic data, anthropometric and blood pressure measurements, fasting lipid profile and glucose, and history of diabetes, hypertension, and smoking were obtained. The cross-sectional analytic sample presented in this article comprised 10,482 participants from baseline recruitment. The data was analysed by descriptive statistics and multivariable logistic regression.
RESULTS: The overall prevalence of elevated TC, elevated LDL-c, elevated TG, low HDL-c, and elevated non-HDL-c were 64.0% (95% CI 63.0-65.0), 56.7% (CI 55.7-57.7), 37.4% (CI 36.5-38.4), 36.2% (CI 35.2-37.1), and 56.2% (CI 55.3-57.2), respectively. Overweight, obesity, and central obesity were highly prevalent and significantly associated with elevated TC and all dyslipidaemia subtypes. Older age was associated with elevated TC, elevated LDL-c and elevated non-HDL-c. Hypertension was associated with elevated TC, elevated TG, and elevated non-HDL-c, while diabetes was associated with elevated TG and low HDL-c.
CONCLUSIONS: Elevated TC and all dyslipidaemia subtypes are highly prevalent in Malaysia where increased body mass seems the main driver. Differences in the prevalence and associated personal and clinical attributes may facilitate specific preventive and management strategies.
METHODS: We recruited adults in 30 countries covering all World Health Organization (WHO) regions from July 2020 to August 2021. 5 Likert-point scales were used to measure their perceived change in 32 aspects due to COVID-19 (-2 = substantially reduced to 2 = substantially increased) and perceived importance of 13 preparations (1 = not important to 5 = extremely important). Samples were stratified by age and gender in the corresponding countries. Multidimensional preference analysis displays disparities between 30 countries, WHO regions, economic development levels, and COVID-19 severity levels.
RESULTS: 16 512 adults participated, with 10 351 females. Among 32 aspects of impact, the most affected were having a meal at home (mean (m) = 0.84, standard error (SE) = 0.01), cooking at home (m = 0.78, SE = 0.01), social activities (m = -0.68, SE = 0.01), duration of screen time (m = 0.67, SE = 0.01), and duration of sitting (m = 0.59, SE = 0.01). Alcohol (m = -0.36, SE = 0.01) and tobacco (m = -0.38, SE = 0.01) consumption declined moderately. Among 13 preparations, respondents rated medicine delivery (m = 3.50, SE = 0.01), getting prescribed medicine in a hospital visit / follow-up in a community pharmacy (m = 3.37, SE = 0.01), and online shopping (m = 3.33, SE = 0.02) as the most important. The multidimensional preference analysis showed the European Region, Region of the Americas, Western Pacific Region and countries with a high-income level or medium to high COVID-19 severity were more adversely impacted on sitting and screen time duration and social activities, whereas other regions and countries experienced more cooking and eating at home. Countries with a high-income level or medium to high COVID-19 severity reported higher perceived mental burden and emotional distress. Except for low- and lower-middle-income countries, medicine delivery was always prioritised.
CONCLUSIONS: Global increasing sitting and screen time and limiting social activities deserve as much attention as mental health. Besides, the pandemic has ushered in a notable enhancement in lifestyle of home cooking and eating, while simultaneously reducing the consumption of tobacco and alcohol. A health care system and technological infrastructure that facilitate medicine delivery, medicine prescription, and online shopping are priorities for coping with future pandemics.
METHODS: An international cross-sectional study was conducted in 30 countries across six World Health Organization regions from July 2020 to August 2021, with 16 512 adults self-reporting changes in 18 lifestyle factors and 13 interim health outcomes since the pandemic.
RESULTS: Three networks were computed and tested. The central variables decided by the expected influence centrality were consumption of fruits and vegetables (centrality = 0.98) jointly with less sugary drinks (centrality = 0.93) in the lifestyles network; and quality of life (centrality = 1.00) co-dominant (centrality = 1.00) with less emotional distress in the interim health outcomes network. The overall amount of exercise had the highest bridge expected influence centrality in the bridge network (centrality = 0.51). No significant differences were found in the network global strength or the centrality of the aforementioned key variables within each network between males and females or health workers and non-health workers (all P-values >0.05 after Holm-Bonferroni correction).
CONCLUSIONS: Consumption of fruits and vegetables, sugary drinks, quality of life, emotional distress, and the overall amount of exercise are key intervention components for improving overall lifestyle, overall health and overall health via lifestyle in the general population, respectively. Although modifications are needed for all aspects of lifestyle and interim health outcomes, a larger allocation of resources and more intensive interventions were recommended for these key variables to produce the most cost-effective improvements in lifestyles and health, regardless of gender or occupation.
METHODS: We surveyed 16 512 adults from July 2020 to August 2021 in 30 territories. Participants self-reported their medical histories and the perceived impact of COVID-19 on 18 lifestyle factors and 13 health outcomes. For each disease subgroup, we generated lifestyle, health outcome, and bridge networks. Variables with the highest centrality indices in each were identified central or bridge. We validated these networks using nonparametric and case-dropping subset bootstrapping and confirmed central and bridge variables' significantly higher indices through a centrality difference test.
FINDINGS: Among the 48 networks, 44 were validated (all correlation-stability coefficients >0.25). Six central lifestyle factors were identified: less consumption of snacks (for the chronic disease: anxiety), less sugary drinks (cancer, gastric ulcer, hypertension, insomnia, and pre-diabetes), less smoking tobacco (chronic obstructive pulmonary disease), frequency of exercise (depression and fatty liver disease), duration of exercise (irritable bowel syndrome), and overall amount of exercise (autoimmune disease, diabetes, eczema, heart attack, and high cholesterol). Two central health outcomes emerged: less emotional distress (chronic obstructive pulmonary disease, eczema, fatty liver disease, gastric ulcer, heart attack, high cholesterol, hypertension, insomnia, and pre-diabetes) and quality of life (anxiety, autoimmune disease, cancer, depression, diabetes, and irritable bowel syndrome). Four bridge lifestyles were identified: consumption of fruits and vegetables (diabetes, high cholesterol, hypertension, and insomnia), less duration of sitting (eczema, fatty liver disease, and heart attack), frequency of exercise (autoimmune disease, depression, and heart attack), and overall amount of exercise (anxiety, gastric ulcer, and insomnia). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P