Association between alcohol intake and overweight and obesity: a systematic review and dose-response meta-analysis of 127 observational studies

How do lifestyle factors modify the association between genetic predisposition and obesity-related phenotypes? A 4-way decomposition analysis using UK Biobank

BACKGROUND

Obesity and central obesity are multifactorial conditions with genetic and non-genetic (lifestyle and environmental) contributions. There is incomplete understanding of whether lifestyle modifies the translation from respective genetic risks into phenotypic obesity and central obesity, and to what extent genetic predisposition to obesity and central obesity is mediated via lifestyle factors.

METHODS

This is a cross-sectional study of 201,466 (out of approximately 502,000) European participants from UK Biobank and tested for interactions and mediation role of lifestyle factors (diet quality; physical activity levels; total energy intake; sleep duration, and smoking and alcohol intake) between genetic risk for obesity and central obesity. BMI-PRS and WHR-PRS are exposures and obesity and central obesity are outcomes.

RESULTS

Overall, 42.8% of the association between genetic predisposition to obesity and phenotypic obesity was explained by lifestyle: 0.9% by mediation and 41.9% by effect modification. A significant difference between men and women was found in central obesity; the figures were 42.1% (association explained by lifestyle), 1.4% (by mediation), and 40.7% (by modification) in women and 69.6% (association explained by lifestyle), 3.0% (by mediation), and 66.6% (by modification) in men.

CONCLUSIONS

A substantial proportion of the association between genetic predisposition to obesity/central obesity and phenotypic obesity/central obesity was explained by lifestyles. Future studies with repeated measures of obesity and lifestyle would be needed to clarify causation.

Normal-weight visceral obesity promotes a higher 10-year atherosclerotic cardiovascular disease risk in patients with type 2 diabetes mellitus-a multicenter study in China

BACKGROUND

Visceral obesity is associated with high cardiovascular events risk in type 2 diabetes mellitus (T2DM). Whether normal-weight visceral obesity will pose a higher atherosclerotic cardiovascular disease (ASCVD) risk than body mass index (BMI)-defined overweight or obese counterparts with or without visceral obesity remains unclear. We aimed to explore the relationship between general obesity and visceral obesity and 10-year ASCVD risk in patients with T2DM.

METHODS

Patients with T2DM (6997) who satisfied the requirements for inclusion were enrolled. Patients were considered to have normal weight when 18.5 kg/m² ≤ BMI < 24 kg/m²; overweight when 24 kg/m² ≤ BMI < 28 kg/m²; and obesity when BMI ≥ 28 kg/m². Visceral obesity was defined as a visceral fat area (VFA) ≥ 100 cm². Patients were separated into six groups based on BMI and VFA. The odd ratios (OR) for a high 10-year ASCVD risk for different combinations of BMI and VFA were analysed using stepwise logistic regression. Receiver operating characteristic (ROC) curves for diagnosing the high 10-year ASCVD risk were constructed, and areas under the ROC curves were estimated. Potential non-linear relationships between VFA levels and high 10-year ASCVD risk were examined using restricted cubic splines (knot = 4). Multilinear regression was used to identify factors affecting VFA in patients with T2DM.

RESULTS

In patients with T2DM, subjects with normal-weight visceral obesity had the highest 10-year ASCVD risk among the six groups, which had more than a 2-fold or 3-fold higher OR than those who were overweight or obese according to BMI but did not have visceral obesity (all P < 0.05). The VFA threshold for high 10-year ASCVD risk was 90 cm². Multilinear regression showed significant differences in the effect of age, hypertension, drinking, fasting serum insulin, fasting plasma glucose, 2 h postprandial C-peptide, triglyceride, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol on VFA in patients with T2DM (all P < 0.05).

CONCLUSIONS

T2DM patients with normal-weight visceral obesity had a higher 10-year ASCVD risk than BMI-defined overweight or obese counterparts with or without visceral obesity, which should initiate standardised management for ASCVD primary prevention.

Evaluation and Treatment of Obesity and Its Comorbidities: 2022 Update of Clinical Practice Guidelines for Obesity by the Korean Society for the Study of Obesity

The goal of the 8th edition of the Clinical Practice Guidelines for Obesity is to help primary care physician provide safe, effective care to patients with obesity by offering evidence-based recommendations to improve the quality of treatment. The Committee for Clinical Practice Guidelines comprised individuals with multidisciplinary expertise in obesity management. A steering board of seven experts oversaw the entire project. Recommendations were developed as the answers to key questions formulated in patient/problem, intervention, comparison, outcomes (PICO) format. Guidelines underwent multi-level review and cross-checking and received endorsement from relevant scientific societies. This edition of the guidelines includes criteria for diagnosing obesity, abdominal obesity, and metabolic syndrome; evaluation of obesity and its complications; weight loss goals; and treatment options such as diet, exercise, behavioral therapy, pharmacotherapy, and bariatric and metabolic surgery for Korean people with obesity. Compared to the previous edition of the guidelines, the current edition includes five new topics to keep up with the constantly evolving field of obesity: diagnosis of obesity, obesity in women, obesity in patients with mental illness, weight maintenance after weight loss, and the use of information and communication technology-based interventions for obesity treatment. This edition of the guidelines features has improved organization, more clearly linking key questions in PICO format to recommendations and key references. We are confident that these new Clinical Practice Guidelines for Obesity will be a valuable resource for all healthcare professionals as they describe the most current and evidence-based treatment options for obesity in a well-organized format.

Genetic and Environmental Factors Underlying Parallel Changes in Body Mass Index and Alcohol Consumption: A 36-Year Longitudinal Study of Adult Twins

INTRODUCTION

While the genetic and environmental underpinnings of body weight and alcohol use are fairly well-known, determinants of simultaneous changes in these traits are still poorly known. We sought to quantify the environmental and genetic components underlying parallel changes in weight and alcohol consumption and to investigate potential covariation between them.

METHODS

The analysis comprised 4,461 adult participants (58% women) from the Finnish Twin Cohort with four measures of alcohol consumption and body mass index (BMI) over a 36-year follow-up. Trajectories of each trait were described by growth factors, defined as intercepts (i.e., baseline) and slopes (i.e., change over follow-up), using latent growth curve modeling. Growth values were used for male (190 monozygotic pairs, 293 dizygotic pairs) and female (316 monozygotic pairs, 487 dizygotic pairs) same-sex complete twin pairs in multivariate twin modeling. The variances and covariances of growth factors were then decomposed into genetic and environmental components.

RESULTS

The baseline heritabilities were similar in men (BMI: h2 = 79% [95% confidence interval: 74, 83]; alcohol consumption: h2 = 49% [32, 67]) and women (h2 = 77% [73, 81]; h2 = 45% [29, 61]). Heritabilities of BMI change were similar in men (h2 = 52% [42, 61]) and women (h2 = 57% [50, 63]), but the heritability of change in alcohol consumption was significantly higher (p = 0.03) in men (h2 = 45% [34, 54]) than in women (h2 = 31% [22, 38]). Significant additive genetic correlations between BMI at baseline and change in alcohol consumption were observed in both men (rA = -0.17 [-0.29, -0.04]) and women (rA = -0.18 [-0.31, -0.06]). Non-shared environmental factors affecting changes in alcohol consumption and BMI were correlated in men (rE = 0.18 [0.06, 0.30]). Among women, non-shared environmental factors affecting baseline alcohol consumption and the change in BMI were inversely correlated (rE = -0.11 [-0.20, -0.01]).

CONCLUSIONS

Based on genetic correlations, genetic variation underlying BMI may affect changes in alcohol consumption. Independent of genetic effects, change in BMI correlates with change in alcohol consumption in men, suggesting direct effects between them.

Meta-analytic evidence for a sex-diverging association between alcohol use and body mass index

Alcohol use is an important health issue and has been suggested to contribute to the burden produced by obesity. Both alcohol use and obesity are subject to sex differences. The available studies on the relationship between alcohol use and body mass index (BMI) report inconsistent results with positive, negative, and null findings which requests a meta-analytic approach. Therefore, we conducted a meta-analysis of case-control, cohort, and cross-sectional studies. The systematic literature search and data extraction was performed by 3 independent raters. We conducted sex-separated meta-analyses and -regressions to investigate how alcohol consumption associates with BMI. Our systematic literature search resulted in 36 studies with 48 data sets (N_men = 172,254; k_men = 30; N_women = 24,164; k_women = 18; N_{unknown sex} = 672,344; k_{unknown sex} = 24). Alcohol use was associated with higher BMI in men (g = 0.08 [0.07; 0.09]) and lower BMI in women (g = - 0.26 [- 0.29; - 0.22]). Moreover, we found the amount of daily alcohol intake in men (β = 0.001 [0.0008; 0.0014]) and ethnicity in women (g[Caucasians] = - 0.45 versus g[Asians] = - 0.05; z = 11.5, p < 0.0001) to moderate these effects. We here identified sex-diverging relationships between alcohol use and BMI, found daily alcohol intake and ethnicity to sex-specifically moderate these effects, and argue that sex-specific choice of beverage type and higher amount of daily alcohol use in men than in women account for these observations. Future research is needed to provide empirical evidence for the underlying mechanisms.

White rice, brown rice and the risk of type 2 diabetes: a systematic review and meta-analysis

OBJECTIVE

Intake of white rice has been associated with elevated risk for type 2 diabetes (T2D), while studies on brown rice are conflicting. To inform dietary guidance, we synthesised the evidence on white rice and brown rice with T2D risk.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, EMBASE and Cochrane databases were searched through November 2021.

ELIGIBILITY CRITERIA

Prospective cohort studies of white and brown rice intake on T2D risk (≥1 year), and randomised controlled trials (RCTs) comparing brown rice with white rice on cardiometabolic risk factors (≥2 weeks).

DATA EXTRACTION AND SYNTHESIS

Data were extracted by the primary reviewer and two additional reviewers. Meta-analyses were conducted using random-effects models and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed using the Newcastle Ottawa Scale for prospective cohort studies and the Cochrane Risk of Bias Tool for RCTs. Strength of the meta-evidence was assessed using NutriGrade.

RESULTS

Nineteen articles were included: 8 cohort studies providing 18 estimates (white rice: 15 estimates, 25 956 cases, n=5 77 426; brown rice: 3 estimates, 10 507 cases, n=1 97 228) and 11 RCTs (n=1034). In cohort studies, white rice was associated with higher risk of T2D (pooled RR, 1.16; 95% CI: 1.02 to 1.32) comparing extreme categories. At intakes above ~300 g/day, a dose-response was observed (each 158 g/day serving was associated with 13% (11%-15%) higher risk of T2D). Intake of brown rice was associated with lower risk of T2D (pooled RR, 0.89; 95% CI: 0.81 to 0.97) comparing extreme categories. Each 50 g/day serving of brown rice was associated with 13% (6%-20%) lower risk of T2D. Cohort studies were considered to be of good or fair quality. RCTs showed an increase in high-density lipoprotein-cholesterol (0.06 mmol/L; 0.00 to 0.11 mmol/L) in the brown compared with white rice group. No other significant differences in risk factors were observed. The majority of RCTs were found to have some concern for risk of bias. Overall strength of the meta-evidence was moderate for cohort studies and moderate and low for RCTs.

CONCLUSION

Intake of white rice was associated with higher risk of T2D, while intake of brown rice was associated with lower risk. Findings from substitution trials on cardiometabolic risk factors were inconsistent.

PROSPERO REGISTRATION NUMBER

CRD42020158466.

Which drinkers have changed their alcohol consumption due to energy content concerns? An Australian survey

Background

Alcohol is a discretionary, energy dense, dietary component. Compared to non-drinkers, people who consume alcohol report higher total energy intake and may be at increased risk of weight gain, overweight, and obesity, which are key preventable risk factors for illness. However, accurate consumer knowledge of the energy content in alcohol is low. To inform future behaviour change interventions among drinkers, this study investigated individual characteristics associated with changing alcohol consumption due to energy-related concerns.

Methods

An online survey was undertaken with 801 Australian adult drinkers (18–59 years, 50.2% female), i.e. who consumed alcohol at least monthly. In addition to demographic and health-related characteristics, participants reported past-year alcohol consumption, past-year reductions in alcohol consumption, frequency of harm minimisation strategy use (when consuming alcohol), and frequency of changing alcohol consumption behaviours because of energy-related concerns.

Results

When prompted, 62.5% of participants reported changing alcohol consumption for energy-related reasons at least ‘sometimes’. Women, those aged 30–44 years, metropolitan residents, those with household income $80,001–120,000, and risky/more frequent drinkers had increased odds of changing consumption because of energy-related concerns, and unemployed respondents had reduced odds.

Conclusions

Results indicate that some sociodemographic groups are changing alcohol consumption for energy-related reasons, but others are not, representing an underutilised opportunity for health promotion communication. Further research should investigate whether messaging to increase awareness of alcohol energy content, including through systems-based policy actions such as nutritional/energy product labelling, would motivate reduced consumption across a broader range of drinkers.

Energy labelling of alcoholic drinks: An important or inconsequential obesity policy?

Alcohol is calorie dense, but unlike food products, alcoholic drinks tend to be exempt from nutritional labelling laws that require energy content information to be displayed on packaging or at point of purchase. This review provides a perspective on the likely efficacy of alcoholic drink energy labelling as a public health policy to reduce obesity and discusses key questions to be addressed by future research. First, the contribution that alcohol makes to population level daily energy intake and obesity is outlined. Next, consumer need for alcohol energy labelling and the potential impacts on both consumer and industry behavior are discussed. Pathways and mechanisms by which energy labelling of alcoholic drinks could reduce obesity are considered, as well as possible unintended consequences of alcoholic drink energy labelling. Would widespread energy labelling of alcoholic drinks reduce obesity? The unclear effect that alcohol has on population level obesity, the modest contribution calories from alcohol make to daily energy intake and limited impact nutritional labelling policies tend to have on behavior, suggest alcohol energy labelling may have limited impact on population obesity prevalence as a standalone policy. However, there are a number of questions that will need to be answered by future research to make definitive conclusions on the potential for alcohol energy labelling policies to reduce obesity.

'Joining the Dots': Individual, Sociocultural and Environmental Links between Alcohol Consumption, Dietary Intake and Body Weight-A Narrative Review

Alcohol is energy-dense, elicits weak satiety responses relative to solid food, inhibits dietary fat oxidation, and may stimulate food intake. It has, therefore, been proposed as a contributor to weight gain and obesity. The aim of this narrative review was to consolidate and critically appraise the evidence on the relationship of alcohol consumption with dietary intake and body weight, within mainstream (non-treatment) populations. Publications were identified from a PubMed keyword search using the terms 'alcohol', 'food', 'eating', 'weight', 'body mass index', 'obesity', 'food reward', 'inhibition', 'attentional bias', 'appetite', 'culture', 'social'. A snowball method and citation searches were used to identify additional relevant publications. Reference lists of relevant publications were also consulted. While limited by statistical heterogeneity, pooled results of experimental studies showed a relatively robust association between acute alcohol intake and greater food and total energy intake. This appears to occur via metabolic and psychological mechanisms that have not yet been fully elucidated. Evidence on the relationship between alcohol intake and weight is equivocal. Most evidence was derived from cross-sectional survey data which does not allow for a cause-effect relationship to be established. Observational research evidence was limited by heterogeneity and methodological issues, reducing the certainty of the evidence. We found very little qualitative work regarding the social, cultural, and environmental links between concurrent alcohol intake and eating behaviours. That the evidence of alcohol intake and body weight remains uncertain despite no shortage of research over the years, indicates that more innovative research methodologies and nuanced analyses are needed to capture what is clearly a complex and dynamic relationship. Also, given synergies between 'Big Food' and 'Big Alcohol' industries, effective policy solutions are likely to overlap and a unified approach to policy change may be more effective than isolated efforts. However, joint action may not occur until stronger evidence on the relationship between alcohol intake, food intake and weight is established.