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Causal relationship between obesity, lifestyle factors and risk of benign prostatic hyperplasia: a univariable and multivariable Mendelian randomization study.
Wang, YB, Yang, L, Deng, YQ, Yan, SY, Luo, LS, Chen, P, Zeng, XT
Journal of translational medicine. 2022;20(1):495
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Benign prostatic hyperplasia (BPH) is a common benign disease in middle-aged and elderly men which is often underestimated and underdiagnosed. If patients are not treated in time, it may lead to serious complications, such as urinary retention, renal insufficiency and renal failure. The aim of this study was to evaluate the possible causal associations of abdominal obesity (measured as waist circumference), overall obesity (measured as body mass index), lifestyle factors (dietary habits, smoking, alcohol drinking, and sedentary behaviour) with risk of BPH. This study is a univariable and multivariable mendelian randomised study. Results show that genetic predisposition to higher waist circumference and sedentary behaviour are independently and causally associated with the risk of BPH. However, there isn’t conclusive evidence that genetic predisposition to relative carbohydrate, fat, protein, and sugar intake, smoking and alcohol drinking are causally associated with the risk of BPH. Authors conclude that further studies are needed to identify comprehensive risk factors on BPH and develop freely accessible prediction models for the BPH. These will help to identify individuals at particular risk and provide decision-making supports for individualised intervention.
Abstract
BACKGROUND Obesity (waist circumference, body mass index (BMI)) and lifestyle factors (dietary habits, smoking, alcohol drinking, Sedentary behavior) have been associated with risk of benign prostatic hyperplasia (BPH) in observational studies, but whether these associations are causal is unclear. METHODS We performed a univariable and multivariable Mendelian randomization study to evaluate these associations. Genetic instruments associated with exposures at the genome-wide significance level (P < 5 × 10-8) were selected from corresponding genome-wide associations studies (n = 216,590 to 1,232,091 individuals). Summary-level data for BPH were obtained from the UK Biobank (14,126 cases and 169,762 non-cases) and FinnGen consortium (13,118 cases and 72,799 non-cases). Results from UK Biobank and FinnGen consortium were combined using fixed-effect meta-analysis. RESULTS The combined odds ratios (ORs) of BPH were 1.24 (95% confidence interval (CI), 1.07-1.43, P = 0.0045), 1.08 (95% CI 1.01-1.17, P = 0.0175), 0.94 (95% CI 0.67-1.30, P = 0.6891), 1.29 (95% CI 0.88-1.89, P = 0.1922), 1.23 (95% CI 0.85-1.78, P = 0.2623), and 1.04 (95% CI 0.76-1.42, P = 0.8165) for one standard deviation (SD) increase in waist circumference, BMI, and relative carbohydrate, fat, protein and sugar intake, 1.05 (95% CI 0.92-1.20, P = 0.4581) for one SD increase in prevalence of smoking initiation, 1.10 (95% CI 0.96-1.26, P = 0.1725) and 0.84 (95% CI 0.69-1.02, P = 0.0741) for one SD increase of log-transformed smoking per day and drinks per week, and 1.31 (95% CI 1.08-1.58, P = 0.0051) for one SD increase in sedentary behavior. Genetically predicted waist circumference (OR = 1.26, 95% CI 1.11-1.43, P = 0.0004) and sedentary behavior (OR = 1.14, 95% CI 1.05-1.23, P = 0.0021) were associated with BPH after the adjustment of BMI. CONCLUSION This study supports independent causal roles of high waist circumference, BMI and sedentary behavior in BPH.
2.
Nutritional labelling for healthier food or non-alcoholic drink purchasing and consumption.
Crockett, RA, King, SE, Marteau, TM, Prevost, AT, Bignardi, G, Roberts, NW, Stubbs, B, Hollands, GJ, Jebb, SA
The Cochrane database of systematic reviews. 2018;2:CD009315
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Poor quality diets are a threat to health internationally and a challenge to health services. Implementing methods to change people's choices is difficult; even those who start making healthier choices often find it hard to maintain long-term. There is recognition that our environment has a powerful influence over our food choices and altering this may stimulate behavioural change. Nutritional labels provide information about the nutritional content of a food or drink. The type of information provided varies e.g. what nutrients they describe (e.g. macronutrients like fat or energy content) and the form also varies e.g. as a single number, as a proportion of a guideline for daily consumption, or with colours indicative of relative healthiness. Nutritional labelling has been rolled-out in many forms, across many countries but there is currently no consensus as to the best way of applying this information to products to stimulate healthier food choices. This review explored whether nutritional labels persuade consumers to buy alternative types of food and included 28 articles. Findings from these 28 articles suggest that nutritional labelling specially indicating energy content may cause people to opt to buy foods with a lower energy content in restaurants. This result (only based on 3 studies) suggests that nutritional labelling could be rolled-out on menus in restaurants, but high-quality research is required. Higher-quality research is also needed to explore the impact of nutritional labelling in shops and vending machines.
Abstract
BACKGROUND Nutritional labelling is advocated as a means to promote healthier food purchasing and consumption, including lower energy intake. Internationally, many different nutritional labelling schemes have been introduced. There is no consensus on whether such labelling is effective in promoting healthier behaviour. OBJECTIVES To assess the impact of nutritional labelling for food and non-alcoholic drinks on purchasing and consumption of healthier items. Our secondary objective was to explore possible effect moderators of nutritional labelling on purchasing and consumption. SEARCH METHODS We searched 13 electronic databases including CENTRAL, MEDLINE and Embase to 26 April 2017. We also handsearched references and citations and sought unpublished studies through websites and trials registries. SELECTION CRITERIA Eligible studies: were randomised or quasi-randomised controlled trials (RCTs/Q-RCTs), controlled before-and-after studies, or interrupted time series (ITS) studies; compared a labelled product (with information on nutrients or energy) with the same product without a nutritional label; assessed objectively measured purchasing or consumption of foods or non-alcoholic drinks in real-world or laboratory settings. DATA COLLECTION AND ANALYSIS Two authors independently selected studies for inclusion and extracted study data. We applied the Cochrane 'Risk of bias' tool and GRADE to assess the quality of evidence. We pooled studies that evaluated similar interventions and outcomes using a random-effects meta-analysis, and we synthesised data from other studies in a narrative summary. MAIN RESULTS We included 28 studies, comprising 17 RCTs, 5 Q-RCTs and 6 ITS studies. Most (21/28) took place in the USA, and 19 took place in university settings, 14 of which mainly involved university students or staff. Most (20/28) studies assessed the impact of labelling on menus or menu boards, or nutritional labelling placed on, or adjacent to, a range of foods or drinks from which participants could choose. Eight studies provided participants with only one labelled food or drink option (in which labelling was present on a container or packaging, adjacent to the food or on a display board) and measured the amount consumed. The most frequently assessed labelling type was energy (i.e. calorie) information (12/28).Eleven studies assessed the impact of nutritional labelling on purchasing food or drink options in real-world settings, including purchases from vending machines (one cluster-RCT), grocery stores (one ITS), or restaurants, cafeterias or coffee shops (three RCTs, one Q-RCT and five ITS). Findings on vending machines and grocery stores were not interpretable, and were rated as very low quality. A meta-analysis of the three RCTs, all of which assessed energy labelling on menus in restaurants, demonstrated a statistically significant reduction of 47 kcal in energy purchased (MD -46.72 kcal, 95% CI -78.35, -15.10, N = 1877). Assuming an average meal of 600 kcal, energy labelling on menus would reduce energy purchased per meal by 7.8% (95% CI 2.5% to 13.1%). The quality of the evidence for these three studies was rated as low, so our confidence in the effect estimate is limited and may change with further studies. Of the remaining six studies, only two (both ITS studies involving energy labels on menus or menus boards in a coffee shop or cafeteria) were at low risk of bias, and their results support the meta-analysis. The results of the other four studies which were conducted in a restaurant, cafeterias (2 studies) or a coffee shop, were not clearly reported and were at high risk of bias.Seventeen studies assessed the impact of nutritional labels on consumption in artificial settings or scenarios (henceforth referred to as laboratory studies or settings). Of these, eight (all RCTs) assessed the effect of labels on menus or placed on a range of food options. A meta-analysis of these studies did not conclusively demonstrate a reduction in energy consumed during a meal (MD -50 kcal, 95% CI -104.41, 3.88, N = 1705). We rated the quality of the evidence as low, so our confidence in the effect estimate is limited and may change with further studies.Six laboratory studies (four RCTs and two Q-RCTs) assessed the impact of labelling a single food or drink option (such as chocolate, pasta or soft drinks) on energy consumed during a snack or meal. A meta-analysis of these studies did not demonstrate a statistically significant difference in energy (kcal) consumed (SMD 0.05, 95% CI -0.17 to 0.27, N = 732). However, the confidence intervals were wide, suggesting uncertainty in the true effect size. We rated the quality of the evidence as low, so our confidence in the effect estimate is limited and may change with further studies.There was no evidence that nutritional labelling had the unintended harm of increasing energy purchased or consumed. Indirect evidence came from five laboratory studies that involved mislabelling single nutrient content (i.e. placing low energy or low fat labels on high-energy foods) during a snack or meal. A meta-analysis of these studies did not demonstrate a statistically significant increase in energy (kcal) consumed (SMD 0.19, 95% CI -0.14to 0.51, N = 718). The effect was small and the confidence intervals wide, suggesting uncertainty in the true effect size. We rated the quality of the evidence from these studies as very low, providing very little confidence in the effect estimate. AUTHORS' CONCLUSIONS Findings from a small body of low-quality evidence suggest that nutritional labelling comprising energy information on menus may reduce energy purchased in restaurants. The evidence assessing the impact on consumption of energy information on menus or on a range of food options in laboratory settings suggests a similar effect to that observed for purchasing, although the evidence is less definite and also of low quality.Accordingly, and in the absence of observed harms, we tentatively suggest that nutritional labelling on menus in restaurants could be used as part of a wider set of measures to tackle obesity. Additional high-quality research in real-world settings is needed to enable more certain conclusions.Further high-quality research is also needed to address the dearth of evidence from grocery stores and vending machines and to assess potential moderators of the intervention effect, including socioeconomic status.
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Clinical review: treatment of pediatric obesity: a systematic review and meta-analysis of randomized trials.
McGovern, L, Johnson, JN, Paulo, R, Hettinger, A, Singhal, V, Kamath, C, Erwin, PJ, Montori, VM
The Journal of clinical endocrinology and metabolism. 2008;93(12):4600-5
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Childhood obesity represents a significant problem to society. It is associated with increased incidence of adult obesity and cardiovascular risk factors. This report was commissioned by the Endocrine Society to help them formulate a clinical practice guidance for paediatric obesity. The review completed a meta-analysis and systematic review of randomised controlled trials up until February 2006. It focused on exploring the efficacy of weight loss interventions (diet, lifestyle and pharmacological agents) for overweight children and adolescents (aged 2-18 years). The authors concluded that there was evidence of short-term efficacy of pharmacological interventions (sibutramine and orlistat in adolescents) on body mass index (BMI). The review also reported a moderate effect of physical activity on adiposity but not BMI, and a small to moderate effect of combined lifestyle interventions on BMI. The impact of parental influence on treatment for childhood obesity remain unclear, although the authors suggest it may be of benefit among children aged 8 years and over. Additionally, the long-term efficacy of obesity treatments on the health of children and adolescents remains unclear.
Abstract
CONTEXT The efficacy of treatments for pediatric obesity remains unclear. OBJECTIVE We performed a systematic review of randomized trials to estimate the efficacy of nonsurgical interventions for pediatric obesity. DATA SOURCES Librarian-designed search strategies of nine electronic databases from inception until February 2006, review of reference lists from published reviews, and content expert advice provided potentially eligible studies. STUDY SELECTION Eligible studies were randomized trials of overweight children and adolescents assessing the effect of nonsurgical interventions on obesity outcomes. DATA EXTRACTION Independently and in duplicate, reviewers assessed the quality of each trial and collected data on interventions and outcomes. DATA SYNTHESIS Of 76 eligible trials, 61 had complete data for meta-analysis. Short-term medications were effective, including sibutramine [random-effects pooled estimate of body mass index (BMI) loss of 2.4 kg/m(2) with a 95% confidence interval (CI) of 1.8-3.1; proportion of between-study inconsistency not due to chance (I(2)) = 30%] and orlistat (BMI loss = 0.7 kg/m(2); CI = 0.3-1.2; I(2) = 0%). Trials that measured the effect of physical activity on adiposity (i.e. percent body fat and fat-free mass) found a moderate treatment effect (effect size = -0.52; CI = -0.73 to -0.30; I(2) = 0%), whereas trials measuring the effect on BMI found no significant effect (effect size = -0.02; CI = -0.21 to 0.18; I(2) = 0%), but reporting bias may explain this finding. Combined lifestyle interventions (24 trials) led to small changes in BMI. CONCLUSIONS Limited evidence supports the short-term efficacy of medications and lifestyle interventions. The long-term efficacy and safety of pediatric obesity treatments remain unclear.