26 May 2021 In General Health
Little is known about possible changes in alcohol consumption distribution during the COVID-19 pandemic. We estimated how individual changes in alcohol consumption during the pandemic translated into changes in: (i) mean consumption; (ii) dispersion of consumption distribution; and (iii) prevalence of heavy drinkers. We employed data from two independent web-surveys of Norwegian adults collected between April and July 2020 and limited to those reporting past year alcohol consumption (N1 = 15,267, N2 = 1195). Self-reports of changes in drinking behavior were quantified, assuming change being relative to baseline consumption level. During the pandemic, we found a small increase (Survey 1) or no change (Survey 2) in estimated mean alcohol consumption (which parallels to total consumption). However, in both surveys, the dispersion of the distribution increased significantly (p
26 May 2021 In General Health
BACKGROUND: The UK Biobank (UKB) has been used widely to examine associations between lifestyle risk factors and mortality outcomes. It is unknown whether the extremely low UKB response rate (5.5%) and lack of representativeness materially affects the magnitude and direction of effect estimates. METHODS: We used poststratification to match the UKB sample to the target population in terms of sociodemographic characteristics and prevalence of lifestyle risk factors (physical inactivity, alcohol intake, smoking, and poor diet). We compared unweighted and poststratified associations between each lifestyle risk factor and a lifestyle index score with all-cause, cardiovascular disease (CVD), and cancer mortality. We also calculated the unweighted to poststratified ratio of HR (RHR) and 95% confidence interval as a marker of effect-size difference. RESULTS: Of 371,974 UKB participants with no missing data, 302,009 had no history of CVD or cancer, corresponding to 3,298,958 person years of follow-up. Protective associations between alcohol use and CVD mortality observed in the unweighted UKB were substantially altered after poststratification, for example, from a hazard ratio (HR) of 0.63 (0.45-0.87) unweighted to 0.99 (0.65-1.50) poststratified for drinking >/=5 times/week versus never drinking. The magnitude of the poststratified all-cause mortality hazard ratio comparing least healthy with healthiest tertile of lifestyle risk factor index was 9% higher (95% confidence interval: 4%, 14%) than the unweighted estimates. CONCLUSIONS: Lack of representativeness may distort the associations of alcohol with CVD mortality, and may underestimate health hazards among those with cumulatively the least healthy lifestyles.
26 May 2021 In General Health
OBJECTIVES: Previous studies have reported inconsistent results on the relationship between alcohol intake and the risk of systemic lupus erythematosus (SLE). Therefore, we conducted a systematic review and meta-analysis to illustrate the potential role of alcohol intake on the progression of SLE. METHODS: An electronic search of the PubMed, EmBase, and the Cochrane library databases was conducted from their inception up to March 2020. Observational studies that investigated the role of alcohol intake on the risk of SLE were eligible for inclusion in this study. The pooled odds ratio (OR) with 95% confidence interval (CI) was calculated as an effect estimate using the random-effects model. RESULTS: Seven case-control studies (n = 3, 251) and three cohort studies (n = 322, 479) were selected for the final meta-analysis. Mild (OR: 0.85; 95% CI: 0.53-1.38; p = 0.515) or heavy (OR: 0.63; 95% CI: 0.37-1.09; p = 0.102) alcohol intake were not associated with the risk of SLE, while moderate alcohol intake could protect against the risk of SLE (OR: 0.71; 95% CI: 0.55-0.93; p = 0.012). Sensitivity analysis suggested that heavy alcohol intake was associated with a reduced risk of SLE (OR: 0.47; 95% CI: 0.32-0.67; p
26 May 2021 In Drinking Patterns
Objectives: Alcohol consumption and harms among older people are increasing. We examined different demographic characteristics and drinking patterns among an older population. Methods: Secondary analyses of nationally representative Australian data; subjects aged 50+ years (N = 10,856). Two-step cluster analysis was performed to identify demographic groups and alcohol consumption behaviours. Results: Three groups were identified: Group 1 (older, unmarried, and lived alone): >65 years, moderate drinkers, poorest health, psychological distress, social disadvantage, smokers, illicit drug users, and more frequent previous alcohol treatment. Group 3 (older married): >65 years, good health, low psychological distress, less likely to drink at risky levels, and one in five drank daily. Group 2 (younger married): 50-64 years, mostly employed, highest proportion of risky drinkers and of 5+ standard drinks per session, and liberal drinking attitudes with most concern from others about their drinking. Discussion: These demographic typologies can inform targeted prevention efforts for an estimated 1.3 million adults older than 50 years drinking at risky levels.
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