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BackgroundType 2 diabetes mellitus (T2DM) is a global epidemic associated with increased health expenditure, and low quality of life. Many non-genetic risk factors have been suggested, but their overall epidemiological credibility has not been assessed.MethodsWe searched PubMed to capture all meta-analyses and Mendelian randomization studies for risk factors of T2DM. For each association, we estimated the summary effect size, its 95% confidence and prediction interval, and the I2 metric. We examined the presence of small-study effects and excess significance bias. We assessed the epidemiological credibility through a set of predefined criteria.ResultsWe captured 86 eligible papers (142 associations) covering a wide range of biomarkers, medical conditions, and dietary, lifestyle, environmental and psychosocial factors. Adiposity, low hip circumference, serum biomarkers (increased level of alanine aminotransferase, gamma-glutamyl transferase, uric acid and C-reactive protein, and decreased level of adiponectin and vitamin D), an unhealthy dietary pattern (increased consumption of processed meat and sugar-sweetened beverages, decreased intake of whole grains, coffee and heme iron, and low adherence to a healthy dietary pattern), low level of education and conscientiousness, decreased physical activity, high sedentary time and duration of television watching, low alcohol drinking, smoking, air pollution, and some medical conditions (high systolic blood pressure, late menarche age, gestational diabetes, metabolic syndrome, preterm birth) presented robust evidence for increased risk of T2DM.ConclusionsA healthy lifestyle pattern could lead to decreased risk for T2DM. Future randomized clinical trials should focus on identifying efficient strategies to modify harmful daily habits and predisposing dietary patterns.

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Several risk factors present substantial evidence for association with dementia and should be assessed as potential targets for interventions, but these associations may not necessarily be causal.

The development of depression may involve a complex interplay of environmental and genetic risk factors. PubMed and PsycInfo databases were searched from inception through August 3, 2017, to identify meta-analyses and Mendelian randomization (MR) studies of environmental risk factors associated with depression. For each eligible meta-analysis, we estimated the summary effect size and its 95% confidence interval (CI) by random-effects modeling, the 95% prediction interval, heterogeneity with I, and evidence of small-study effects and excess significance bias. Seventy meta-analytic reviews met the eligibility criteria and provided 134 meta-analyses for associations from 1283 primary studies. While 109 associations were nominally significant (P < 0.05), only 8 met the criteria for convincing evidence and, when limited to prospective studies, convincing evidence was found in 6 (widowhood, physical abuse during childhood, obesity, having 4-5 metabolic risk factors, sexual dysfunction, job strain). In studies in which depression was assessed through a structured diagnostic interview, only associations with widowhood, job strain, and being a Gulf War veteran were supported by convincing evidence. Additionally, 8 MR studies were included and provided no consistent evidence for the causal effects of obesity, smoking, and alcohol consumption. The proportion of variance explained by genetic risk factors was extremely small (0.1-0.4%), which limited the evidence provided by the MR studies. Our findings suggest that despite the large number of putative risk factors investigated in the literature, few associations were supported by robust evidence. The current findings may have clinical and research implications for the early identification of individuals at risk for depression.

BackgroundBirth weight, a marker of the intrauterine environment, has been extensively studied in epidemiological research in relation to subsequent health and disease. Although numerous meta-analyses have been published examining the association between birth weight and subsequent health-related outcomes, the epidemiological credibility of these associations has not been thoroughly assessed. The objective of this study is to map the diverse health outcomes associated with birth weight and evaluate the credibility and presence of biases in the reported associations.MethodsAn umbrella review was performed to identify systematic reviews and meta-analyses of observational studies investigating the association between birth weight and subsequent health outcomes and traits. For each association, we estimated the summary effect size by random-effects and fixed-effects models, the 95 % confidence interval, and the 95 % prediction interval. We also assessed the between-study heterogeneity, evidence for small-study effects and excess significance bias. We further applied standardized methodological criteria to evaluate the epidemiological credibility of the statistically significant associations.ResultsThirty-nine articles including 78 associations between birth weight and diverse outcomes met the eligibility criteria. A wide range of health outcomes has been studied, ranging from anthropometry and metabolic diseases, cardiovascular diseases and cardiovascular risk factors, various cancers, respiratory diseases and allergies, musculoskeletal traits and perinatal outcomes. Forty-seven of 78 associations presented a nominally significant summary effect and 21 associations remained statistically significant at P < 1 × 10−6. Thirty associations presented large or very large between-study heterogeneity. Evidence for small-study effects and excess significance bias was present in 13 and 16 associations, respectively. One association with low birth weight (increased risk for all-cause mortality), two dose-response associations with birth weight (higher bone mineral concentration in hip and lower risk for mortality from cardiovascular diseases per 1 kg increase in birth weight) and one association with small-for-gestational age infants with normal birth weight (increased risk for childhood stunting) presented convincing evidence. Eleven additional associations had highly suggestive evidence.ConclusionsThe range of outcomes convincingly associated with birth weight might be narrower than originally described under the “fetal origin hypothesis” of disease. There is weak evidence that birth weight constitutes an effective public health intervention marker.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0692-5) contains supplementary material, which is available to authorized users.

RationaleCOPD has been perceived as being a disease of older men. However, >7 million women are estimated to live with COPD in the USA alone. Despite a growing body of literature suggesting an increasing burden of COPD in women, the evidence is limited.ObjectivesTo assess and synthesize the available evidence among population-based epidemiologic studies and calculate the global prevalence of COPD in men and women.Materials and methodsA systematic review and meta-analysis reporting gender-specific prevalence of COPD was undertaken. Gender-specific prevalence estimates were abstracted from relevant studies. Associated patient characteristics as well as custom variables pertaining to the diagnostic method and other important epidemiologic covariates were also collected. A Bayesian random-effects meta-analysis was performed investigating gender-specific prevalence of COPD stratified by age, geography, calendar time, study setting, diagnostic method, and disease severity.Measurements and main resultsAmong 194 eligible studies, summary prevalence was 9.23% (95% credible interval [CrI]: 8.16%–10.36%) in men and 6.16% (95% CrI: 5.41%–6.95%) in women. Gender prevalences varied widely by the World Health Organization Global Burden of Disease subregions, with the highest female prevalence found in North America (8.07% vs 7.30%) and in participants in urban settings (13.03% vs 8.34%). Meta-regression indicated that age ≥40 and bronchodilator testing contributed most significantly to heterogeneity of prevalence estimates across studies.ConclusionWe conducted the largest ever systematic review and meta-analysis of global prevalence of COPD and the first large gender-specific review. These results will increase awareness of COPD as a critical woman’s health issue.

Objective To map and assess prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease (COPD). Design Systematic review. Data sources PubMed until November 2018 and hand searched references from eligible articles. Eligibility criteria for study selection Studies developing, validating, or updating a prediction model in COPD patients and focusing on any potential clinical outcome. Results The systematic search yielded 228 eligible articles, describing the development of 408 prognostic models, the external validation of 38 models, and the validation of 20 prognostic models derived for diseases other than COPD. The 408 prognostic models were developed in three clinical settings: outpatients (n=239; 59%), patients admitted to hospital (n=155; 38%), and patients attending the emergency department (n=14; 3%). Among the 408 prognostic models, the most prevalent endpoints were mortality (n=209; 51%), risk for acute exacerbation of COPD (n=42; 10%), and risk for readmission after the index hospital admission (n=36; 9%). Overall, the most commonly used predictors were age (n=166; 41%), forced expiratory volume in one second (n=85; 21%), sex (n=74; 18%), body mass index (n=66; 16%), and smoking (n=65; 16%). Of the 408 prognostic models, 100 (25%) were internally validated and 91 (23%) examined the calibration of the developed model. For 286 (70%) models a model presentation was not available, and only 56 (14%) models were presented through the full equation. Model discrimination using the C statistic was available for 311 (76%) models. 38 models were externally validated, but in only 12 of these was the validation performed by a fully independent team. Only seven prognostic models with an overall low risk of bias according to PROBAST were identified. These models were ADO, B-AE-D, B-AE-D-C, extended ADO, updated ADO, updated BODE, and a model developed by Bertens et al. A meta-analysis of C statistics was performed for 12 prognostic models, and the summary estimates ranged from 0.611 to 0.769. Conclusions This study constitutes a detailed mapping and assessment of the prognostic models for outcome prediction in COPD patients. The findings indicate several methodological pitfalls in their development and a low rate of external validation. Future research should focus on the improvement of existing models through update and external validation, as well as the assessment of the safety, clinical effectiveness, and cost effectiveness of the application of these prognostic models in clinical practice through impact studies. Systematic review registration PROSPERO CRD42017069247