Search

Background: Colorectal cancer (CRC) is the third-most-common cancer worldwide and its rates are increasing. Elevated body mass index (BMI) is an established risk factor for CRC, although the molecular mechanisms behind this association remain unclear. Using the Mendelian randomization (MR) framework, we aimed to investigate the mediating effects of putative biomarkers and other CRC risk factors in the association between BMI and CRC., Methods: We selected as mediators biomarkers of established cancer-related mechanisms and other CRC risk factors for which a plausible association with obesity exists, such as inflammatory biomarkers, glucose homeostasis traits, lipids, adipokines, insulin-like growth factor 1 (IGF1), sex hormones, 25-hydroxy-vitamin D, smoking, physical activity (PA) and alcohol consumption. We used inverse-variance weighted MR in the main univariable analyses and performed sensitivity analyses (weighted-median, MR-Egger, Contamination Mixture). We used multivariable MR for the mediation analyses., Results: Genetically predicted BMI was positively associated with CRC risk [odds ratio per SD (5 kg/m2) = 1.17, 95% CI: 1.08-1.24, P-value = 1.4 × 10-5] and robustly associated with nearly all potential mediators. Genetically predicted IGF1, fasting insulin, low-density lipoprotein cholesterol, smoking, PA and alcohol were associated with CRC risk. Evidence for attenuation was found for IGF1 [explained 7% (95% CI: 2-13%) of the association], smoking (31%, 4-57%) and PA (7%, 2-11%). There was little evidence for pleiotropy, although smoking was bidirectionally associated with BMI and instruments were weak for PA., Conclusions: The effect of BMI on CRC risk is possibly partly mediated through plasma IGF1, whereas the attenuation of the BMI-CRC association by smoking and PA may reflect confounding and shared underlying mechanisms rather than mediation., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: The 5-year mortality rate for pancreatic cancer is among the highest of all cancers. Greater understanding of underlying causes could inform population-wide intervention strategies for prevention. Summary genetic data from genome-wide association studies (GWAS) have become available for thousands of phenotypes. These data can be exploited in Mendelian randomization (MR) phenome-wide association studies (PheWAS) to efficiently screen the phenome for potential determinants of disease risk., Methods: We conducted an MR-PheWAS of pancreatic cancer using 486 phenotypes, proxied by 9,124 genetic variants, and summary genetic data from a GWAS of pancreatic cancer (7,110 cancer cases, 7,264 controls). ORs and 95% confidence intervals per 1 SD increase in each phenotype were generated., Results: We found evidence that previously reported risk factors of body mass index (BMI; 1.46; 1.20-1.78) and hip circumference (1.42; 1.21-1.67) were associated with pancreatic cancer. We also found evidence of novel associations with metabolites that have not previously been implicated in pancreatic cancer: ADpSGEGDFXAEGGGVR *, a fibrinogen-cleavage peptide (1.60; 1.31-1.95), and O-sulfo-l-tyrosine (0.58; 0.46-0.74). An inverse association was also observed with lung adenocarcinoma (0.63; 0.54-0.74)., Conclusions: Markers of adiposity (BMI and hip circumference) are potential intervention targets for pancreatic cancer prevention. Further clarification of the causal relevance of the fibrinogen-cleavage peptides and O-sulfo-l-tyrosine in pancreatic cancer etiology is required, as is the basis of our observed association with lung adenocarcinoma., Impact: For pancreatic cancer, MR-PheWAS can augment existing risk factor knowledge and generate novel hypotheses to investigate., (©2019 American Association for Cancer Research.)

Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation., Methods and Findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44-1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40-1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44-1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30-2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11-1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84-1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose., Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: TE declared employment, research support, and stock in AstraZeneca and research support from Bayer and Pfizer. PCH is a population health fellow of Cancer Research UK. GDS is a member of the Editorial Board of PLOS Medicine.

Background: Risk factors for pancreatic cancer include a cluster of metabolic conditions such as obesity, hypertension, dyslipidemia, insulin resistance, and type 2 diabetes. Given that these risk factors are correlated, separating out causal from confounded effects is challenging. Mendelian randomization (MR), or the use of genetic instrumental variables, may facilitate the identification of the metabolic drivers of pancreatic cancer., Methods: We identified genetic instruments for obesity, body shape, dyslipidemia, insulin resistance, and type 2 diabetes in order to evaluate their causal role in pancreatic cancer etiology. These instruments were analyzed in relation to risk using a likelihood-based MR approach within a series of 7110 pancreatic cancer patients and 7264 control subjects using genome-wide data from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Potential unknown pleiotropic effects were assessed using a weighted median approach and MR-Egger sensitivity analyses., Results: Results indicated a robust causal association of increasing body mass index (BMI) with pancreatic cancer risk (odds ratio [OR] = 1.34, 95% confidence interval [CI] = 1.09 to 1.65, for each standard deviation increase in BMI [4.6 kg/m2]). There was also evidence that genetically increased fasting insulin levels were causally associated with an increased risk of pancreatic cancer (OR = 1.66, 95% CI = 1.05 to 2.63, per SD [44.4 pmol/L]). Notably, no evidence of a causal relationship was observed for type 2 diabetes, nor for dyslipidemia. Sensitivity analyses did not indicate that pleiotropy was an important source of bias., Conclusions: Our results suggest a causal role of BMI and fasting insulin in pancreatic cancer etiology., (© The Author 2017. Published by Oxford University Press.)

Background: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer., Methods and Findings: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results., Conclusions: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.

Background: Previous studies of early life influences on later growth in childhood have varied in their analytical approaches, particularly with respect to 'adjustment' for differences in size at the beginning of the growth period examined., Methods: We compared three commonly used statistical models to assess the effect of maternal body mass index (BMI) on growth between 6.5 and 11.5 years in a large cohort of Belarusian children, as follows: (Model 1) analysis of the difference in anthropometric measurements between the two ages; (Model 2) analysis of the measurement at 11.5 years after adjustment for the same measurement at 6.5 years; and (Model 3) analysis of the difference in measurements after adjustment for the measurement at 6.5 years (mathematically identical to Model 2)., Results: Among PROBIT children of obese mothers (BMI ≥ 30 kg/m 2 ) vs those of mothers with normal BMI (18.5 to < 25 kg/m 2 ), Model 1 yielded larger increases in most weight and adiposity outcomes than did Model 2. We show that these larger effects arise because Model 2 parameterizes the effect of maternal BMI twice in same model: once for its effect on size at 6.5 years, and a second time for its effect on growth over the 5-year period between 6.5 and 11.5 years. Similar results were obtained in analogous analyses from cohorts in Boston, MA, and Singapore., Conclusion: Analysing the effect of exposure on change in outcome between two ages (Model 1) is clearly preferable to 'adjustment' for the outcome at the earlier age whenever the exposure under study affects the outcome at the earlier age., (© The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association)

Importance: Evidence that longer-term and exclusive breastfeeding reduces child obesity risk is based on observational studies that are prone to confounding., Objective: To investigate effects of an intervention to promote increased duration and exclusivity of breastfeeding on child adiposity and circulating insulin-like growth factor (IGF)-I, which regulates growth., Design, Setting, and Participants: Cluster-randomized controlled trial in 31 Belarusian maternity hospitals and their affiliated clinics, randomized into 1 of 2 groups: breastfeeding promotion intervention (n = 16) or usual practices (n = 15). Participants were 17,046 breastfeeding mother-infant pairs enrolled in 1996 and 1997, of whom 13,879 (81.4%) were followed up between January 2008 and December 2010 at a median age of 11.5 years., Intervention: Breastfeeding promotion intervention modeled on the WHO/UNICEF Baby-Friendly Hospital Initiative (World Health Organization/United Nations Children's Fund)., Main Outcome Measures: Body mass index (BMI), fat and fat-free mass indices (FMI and FFMI), percent body fat, waist circumference, triceps and subscapular skinfold thicknesses, overweight and obesity, and whole-blood IGF-I. Primary analysis was based on modified intention-to-treat (without imputation), accounting for clustering within hospitals and clinics., Results: The experimental intervention substantially increased breastfeeding duration and exclusivity when compared with the control (43% vs 6% exclusively breastfed at 3 months and 7.9% vs 0.6% at 6 months). Cluster-adjusted mean differences in outcomes at 11.5 years of age between experimental vs control groups were: 0.19 (95% CI, -0.09 to 0.46) for BMI; 0.12 (-0.03 to 0.28) for FMI; 0.04 (-0.11 to 0.18) for FFMI; 0.47% (-0.11% to 1.05%) for percent body fat; 0.30 cm (-1.41 to 2.01) for waist circumference; -0.07 mm (-1.71 to 1.57) for triceps and -0.02 mm (-0.79 to 0.75) for subscapular skinfold thicknesses; and -0.02 standard deviations (-0.12 to 0.08) for IGF-I. The cluster-adjusted odds ratio for overweight/obesity (BMI ≥ 85th vs <85th percentile) was 1.18 (95% CI, 1.01 to 1.39) and for obesity (BMI ≥ 95th vs <85th percentile) was 1.17 (95% CI, 0.97 to 1.41)., Conclusions: AND RELEVANCE Among healthy term infants in Belarus, an intervention that succeeded in improving the duration and exclusivity of breastfeeding did not prevent overweight or obesity, nor did it affect IGF-I levels at age 11.5 years. Breastfeeding has many advantages but population strategies to increase the duration and exclusivity of breastfeeding are unlikely to curb the obesity epidemic., Trial Registration: isrctn.org: ISRCTN37687716; and clinicaltrials.gov: NCT01561612.

Obese men appear to have an increased risk of being diagnosed with advanced prostate cancer and of dying from the disease. Few studies have examined the impact of weight gain during adulthood on prostate cancer risk and mortality and these have reported conflicting results. We analysed data from 20,991 Norwegian men who participated in two phases of the Nord-Trøndelag Health Study in 1984/1986 (HUNT-1, when aged at least 20 years) and 1995/1997 (HUNT-2). Weight and height were measured at both HUNT-1 and HUNT-2, allowing each man's change in weight and body mass index (BMI) to be computed. During a median of 9.3 years of follow-up after the end of HUNT-2, 649 (3%) men developed prostate cancer. We observed no increase in prostate cancer incidence amongst men who put on weight between HUNT-1 and HUNT-2. In multivariable models, including adjustment for weight at HUNT-2, the hazard ratio (HR) for prostate cancer per one standard deviation, SD (6.2 kg) gain in weight was 0.98 (95% confidence interval [95% CI]=0.87-1.10, p-trend=0.70) and per one SD gain in BMI (1.9 kg/m(2) ) was 0.99 (95% CI=0.90-1.10, p-trend=0.88). Amongst men diagnosed with prostate cancer (any stage), there was no evidence that gain in weight before diagnosis was positively associated with subsequent all-cause mortality (HR per one SD increase in weight=0.98; 95% CI=0.81-1.19, p-trend=0.86). We conclude that weight gain in adulthood had no effect on prostate cancer incidence or survival in this population., (Copyright © 2010 UICC.)

Background: Socio-economic differences in the prevalence of overweight/obesity may be one factor through which health inequalities arise and may vary by the population studied., Methods: Analysing a cohort of 13 889 children born in Belarus between June 1996 and December 1997, the authors investigated associations of parental educational attainment and highest household occupation with: (i) measured body mass index (BMI), waist circumference and skinfold thicknesses at age 6.5 years and (ii) the parents' reported BMI., Results: Overall, 10% of children, 37% of mothers and 53% of fathers were either overweight or obese. Children from non-manual households were 27% [95% confidence interval (CI): 10%, 47%] more likely to be overweight/obese (based on BMI) than those from manual households. They also had larger waist circumferences and higher percentage body fat (calculated from subscapular and triceps skinfolds). Similar associations for being overweight/obese were seen for fathers [odds ratio (OR), 1.10; 95% CI: 1.02, 1.18], but mothers from non-manual households were less likely to be overweight/obese: (OR, 0.84; 95% CI: 0.79, 0. 90). Associations of childhood and parental overweight/obesity with higher educational status of either parent were similar to those observed for non-manual households., Conclusion: We observed socio-economic differentials in overweight/obesity prevalence among children and their parents in Belarus. More affluent children and their fathers were more likely to be overweight/obese but the reverse was found for mothers.

Unlabelled: Observational studies suggest that obese men have a lower risk of incident prostate cancer, but an increased risk of advanced and fatal cancers. These observations could be due to confounding, detection bias, or a biological effect of obesity. Genetic studies are less susceptible to confounding than observational epidemiology and can suggest how associations between phenotypes (such as obesity) and diseases arise. To determine whether the associations between obesity and prostate cancer are causal, we conducted a genetic association study of the relationship between a single nucleotide polymorphism known to be associated with obesity (FTO rs9939609) and prostate cancer. Data are from a population-based sample of 1550 screen-detected prostate cancers, 1815 age- and general practice matched controls with unrestricted prostate specific antigen (PSA) values and 1175 low-PSA controls (PSA <0.5 ng/ml). The rs9939609 A allele, which was associated with higher BMI in the sample, was inversely associated with overall (odds ratio (OR) versus all controls  = 0.93; 95% confidence interval (CI): 0.85-1.02 p = 0.12 per allele) and low-grade (OR = 0.90; 0.81-0.99 p = 0.03 per allele) prostate cancer risk, but positively associated with high-grade cancer among cases (OR high- versus low-grade cancer  = 1.16; 0.99-1.37 p = 0.07 per allele). Although evidence for these effects was weak, they are consistent with observational data based on BMI phenotypes and suggest that the observed association between obesity and prostate cancer is not due to confounding. Further research should confirm these findings, extend them to other BMI-related genetic variants and determine whether they are due to detection bias or obesity-related hormonal changes., Trial Registration: Controlled-Trials.com ISRCTN20141297.

Background: Measures of regional adiposity have been proposed as alternatives to the measurement of body mass index (BMI) for identifying persons at risk of future disease., Objective: The objective was to compare the magnitudes of association of BMI and alternative measurements of adiposity with coronary heart disease, diabetes, and cardiovascular disease risk factors and all-cause mortality., Design: Data from 4 cohorts of adults [3937 women from the British Women's Heart and Health Study (BWHHS); 2367 and 1950 men from phases 1 and 3, respectively, of the Caerphilly Prospective Study (CaPS); 403 men and women from the Boyd Orr Study; and 789 men and women from the Maidstone-Dewsbury Study] were analyzed., Results: The magnitudes of associations of BMI with incident coronary heart disease and cardiovascular disease risk factors were similar to those with measurements of central adiposity [waist circumference (WC), waist-hip ratio (WHR), or waist-height ratio (WHtR)] and more direct measurements of fat mass (bioimpedance/skinfold thickness). In CaPS (men only), there was no strong evidence of differences in the strengths of association with incident diabetes between BMI, WC, WHR, and WHtR (P for heterogeneity > 0.49 for all). In the BWHHS (women only), there was statistical evidence that WC [hazard ratio (HR): 2.35; 95% CI: 2.03, 2.73] and WHtR (HR: 2.29; 95% CI: 1.98, 2.66) were more strongly associated with diabetes than with BMI (HR: 1.80; 95% CI: 1.59, 2.04) (P for heterogeneity < 0.02 for both). Central adiposity measurements were positively associated with all-cause mortality, as was BMI, but only when those with a BMI (in kg/m(2)) <22.5 were removed from the analyses., Conclusion: No strong evidence supports replacing BMI in clinical or public health practice with other adiposity measures.

The evidence that breast-feeding protects against obesity is based on observational studies, with potential for confounding and selection bias. This article summarizes a previously published study in which we assessed whether an intervention designed to promote exclusive and prolonged breast-feeding affects children's height, weight, adiposity, and blood pressure (BP) at age 6.5 y. The Promotion of Breastfeeding Intervention Trial (PROBIT) is a cluster-randomized trial of a breast-feeding promotion intervention based on the WHO/UNICEF Baby-Friendly Hospital Initiative. A total of 17,046 healthy breast-fed infants were enrolled from 31 Belarussian maternity hospitals and affiliated clinics, of whom 13,889 (81.5%) were followed up at 6.5 y with duplicate measurements of height, weight, waist circumference, triceps and subscapular skinfold thicknesses, systolic and diastolic BP. Analysis was based on intention to treat, with statistical adjustment for clustering within hospitals/clinics to permit inferences at the individual level. The experimental intervention led to a large increase in exclusive breast-feeding at 3 mo (43.3% vs. 6.4%, P < 0.001) and a significantly higher prevalence of any breast-feeding throughout infancy. No significant intervention effects were observed on height, BMI, adiposity measures, or BP. The breast-feeding promotion intervention resulted in substantial increases in the duration and exclusivity of breast-feeding yet did not reduce measures of adiposity at age 6.5 y. Previous reports of protective effects against obesity may reflect uncontrolled bias caused by confounding and selection.

Background: Previous studies reported inconsistent associations between breastfeeding and body mass index (BMI; in kg/m2). Associations with body fatness are unknown., Objective: We investigated the association of breastfeeding with fatness measured by dual-energy X-ray absorptiometry., Design: The prospective cohort study involved 4325 singletons with measurements at 9-10 y of age to assess the main outcomes of BMI and total and trunk fat masses., Results: Prevalence of any breastfeeding was 82%. In crude analyses, breastfeeding was inversely associated with total fat mass [% change per category increase (4 categories)] in breastfeeding duration (-4.4%; 95% CI: -3.1%, -5.6%) and trunk fat mass (-0.5%; 95% CI: -1.1%, 0.1%); the odds of adiposity were measured by total [odds ratio (OR): 0.81; 95% CI: 0.75, 0.88] and trunk (OR: 0.78; 95% CI: 0.71, 0.84) fat masses in the top decile. In adjusted models, the inverse association of breastfeeding with mean total fat mass was attenuated by 59% (% change per category increase in breastfeeding duration: -1.8%; 95% CI: -0.5%, -3.1%), but associations with trunk fat mass (% change per category increase in breastfeeding duration: -0.6%; 95% CI: 0.0%, -1.3%) and the ORs for total (0.76; 95% CI: 0.69, 0.84) and trunk (0.74; 95% CI: 0.67, 0.81) fat masses in the top decile were little altered. Children breastfed >or=6 mo had the lowest odds of total fat mass in the top decile (OR: 0.45; 95% CI: 0.33, 0.62). In multivariate models, there was little evidence that breastfeeding was associated with mean or threshold values of BMI., Conclusions: The protective association of breastfeeding with mean total fat mass was attenuated somewhat after adjustment for confounders, which indicated that confounding may explain this association. Breastfeeding may protect against obesity if maintained for >or=6 mo.

Background: It is unclear whether early life body mass index (BMI; in kg/m(2)) is associated with adult cardiovascular disease., Objective: The objective was to assess the association of early life BMI with the risk of ischemic heart disease (IHD) and stroke., Design: The association between early life BMI and risk of adult mortality from IHD and stroke was assessed in 3 historical cohort studies in which height and weight had been assessed by using standard procedures. Participants were traced and linked to national mortality data. Participants in the 3 cohorts were born between 1922 and 1937, 1927 and 1956, and 1928 and 1950 and were aged 2-15, 9-18, and 16-22 y, respectively, at the time of assessment of their height and weight., Results: Participants in all 3 cohorts had mean BMIs similar to those reported for contemporary children and young adults, but fewer of the cohort participants were overweight or obese. BMI was not associated with future risk of IHD or stroke in any cohort. The pooled (all 3 cohorts) adjusted hazard ratio per SD of early life BMI was 1.09 (95% CI: 1.01, 1.19) for IHD and 0.94 (95% CI: 0.82, 1.08) for stroke. The pooled hazard ratio of IHD when participants who were overweight or obese for their age were compared with all other participants was 1.34 (95% CI: 0.95, 1.91), and no association was found between overweight or obesity and stroke risk. The effects of BMI did not vary by cohort or by age., Conclusion: These results do not provide strong evidence that being overweight or obese in childhood is associated with future cardiovascular disease risk.

Background: Evidence from observational studies has suggested that breastfeeding may reduce the prevalence of obesity in later life., Objective: The objective was to examine whether initial breastfeeding is related to lower mean body mass index (BMI; in kg/m(2)) throughout life., Design: The study was a systematic review of published studies investigating the association between infant feeding and a measure of obesity or adiposity in later life, which was supplemented with data from unpublished sources. Analyses were based on the mean differences in BMI between those subjects who were initially breastfed and those who were formula-fed (expressed as breastfed minus bottle-fed), which were pooled by using fixed-effects models throughout., Results: From 70 eligible studies, 36 mean differences in BMI (from 355 301 subjects) between those breastfed and those formula-fed (reported as exclusive feeding in 20 studies) were obtained. Breastfeeding was associated with a slightly lower mean BMI than was formula feeding (-0.04; 95% CI: -0.05, -0.02). The mean difference in BMIs appeared larger in 15 small studies of <1000 subjects (-0.19; 95% CI: -0.31, -0.08) and smaller in larger studies of >or=1000 subjects (-0.03; 95% CI: -0.05, -0.02). An Egger test was statistically significant (P = 0.002). Adjustment for socioeconomic status, maternal smoking in pregnancy, and maternal BMI in 11 studies abolished the effect (-0.10; 95% CI: -0.14, -0.06 before adjustment; -0.01; 95% CI: -0.05, 0.03 after adjustment)., Conclusions: Mean BMI is lower among breastfed subjects. However, the difference is small and is likely to be strongly influenced by publication bias and confounding factors. Promotion of breastfeeding, although important for other reasons, is not likely to reduce mean BMI.

Objective: To examine the influence of initial infant feeding on obesity in later life., Methods: A systematic review of published studies investigating the association between infant feeding and a measure of obesity was performed with Medline (1966 onward) and Embase (1980 onward) databases, supplemented with manual searches. Data extraction was conducted by 2 authors. Analyses were based on odds ratios of obesity among initially breastfed subjects, compared with formula-fed subjects, pooled with fixed-effects models., Results: Sixty-one studies reported on the relationship of infant feeding to a measure of obesity in later life; of these, 28 (298900 subjects) provided odds ratio estimates. In these studies, breastfeeding was associated with a reduced risk of obesity, compared with formula feeding (odds ratio: 0.87; 95% confidence interval [CI]: 0.85-0.89). The inverse association between breastfeeding and obesity was particularly strong in 11 small studies of <500 subjects (odds ratio: 0.43; 95% CI: 0.33-0.55) but was still apparent in larger studies of > or =500 subjects (odds ratio: 0.88; 95% CI: 0.85-0.90). In 6 studies that adjusted for all 3 major potential confounding factors (parental obesity, maternal smoking, and social class), the inverse association was reduced markedly (from an odds ratio of 0.86 to 0.93) but not abolished. A sensitivity analysis examining the potential impact of the results of 33 published studies (12505 subjects) that did not provide odds ratios (mostly reporting no relationship between breastfeeding and obesity) showed little effect on the results., Conclusions: Initial breastfeeding protects against obesity in later life. However, a further review including large unpublished studies exploring the effect of confounding factors in more detail is needed.

Background: The associations of adiposity with aggressive prostate cancer risk are unclear. Using two‐sample Mendelian randomization, we assessed the association of metabolically unfavourable adiposity (UFA), favourable adiposity (FA) and for comparison body mass index (BMI), with prostate cancer, including aggressive prostate cancer. Methods: We examined the association of these genetically predicted adiposity‐related traits with risk of prostate cancer overall, aggressive and early onset disease using outcome summary statistics from the PRACTICAL consortium (including 15,167 aggressive cases). Results: In inverse‐variance weighted models, there was little evidence that genetically predicted one standard deviation higher UFA, FA and BMI were associated with aggressive prostate cancer [OR: 0.85 (95% CI:0.61–1.19), 0.80 (0.53–1.23) and 0.97 (0.88–1.08), respectively]; these associations were largely consistent in sensitivity analyses accounting for horizontal pleiotropy. There was no strong evidence that genetically determined UFA, FA or BMI were associated with overall prostate cancer or early age of onset prostate cancer. Conclusions: We did not find differences in the associations of UFA and FA with prostate cancer risk, which suggest that adiposity is unlikely to influence prostate cancer via the metabolic factors assessed; however, these did not cover some aspects related to metabolic health that may link obesity with aggressive prostate cancer, which should be explored in future studies. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to systematically evaluate the direction of any potential causal effect between sleep and adiposity traits. Methods: Two‐sample Mendelian randomization was used to assess the association of genetically predicted sleep traits with adiposity and vice versa. Using data from UK Biobank and 23andMe, the sleep traits explored were morning preference (chronotype; N = 697,828), insomnia (N = 1,331,010), sleep duration (N = 446,118), napping (N = 452,633), and daytime sleepiness (N = 452,071). Using data from the Genetic Investigation of ANthropometric Traits (GIANT) and Early Growth Genetics (EGG) consortia, the adiposity traits explored were adult BMI, hip circumference (HC), waist circumference (WC), waist‐hip ratio (WHR; N = 322,154), and childhood BMI (N = 35,668). Results: This study found evidence that insomnia symptoms increased mean WC, BMI, and WHR (difference in means, WC = 0.39 SD [95% CI: 0.13‐0.64], BMI = 0.47 SD [95% CI: 0.22‐0.73], and WHR = 0.34 SD [95% CI: 0.16‐0.52]). Napping increased mean WHR (0.23 SD [95% CI: 0.08‐0.39]). Higher HC, WC, and adult BMI increased odds of daytime sleepiness (HC = 0.02 SD [95% CI: 0.01‐0.04], WC = 0.04 SD [95% CI: 0.01‐0.06], and BMI 0.02 SD [95% CI: 0.00‐0.04]). This study also found that higher mean childhood BMI resulted in lower odds of napping (−0.01 SD [95% CI: 0.02‐0.00]). Conclusions: The effects of insomnia on adiposity and of adiposity on daytime sleepiness suggest that poor sleep and weight gain may contribute to a feedback loop that could be detrimental to overall health. [ABSTRACT FROM AUTHOR]

Summary: Background: Caesarean delivery has been associated with later adiposity, perhaps via early programming or perhaps because of residual confounding by maternal or birth characteristics. Objectives: Examine associations of caesarean delivery with adiposity and cardio‐metabolic biomarkers. Methods: Observational analysis of 15 069 children in the PROBIT cohort in Belarus. We examined measures of child anthropometry and blood pressure at 6.5, 11.5 and 16 years and fasting blood (11.5 years). Results: Caesarean‐delivered children were slightly heavier at 6.5 (mean BMI 15.8 vs. 15.6 kg/m2), 11.5 (18.4 vs. 18.2) and 16 years (21.5 vs. 21.3). After adjustment for prenatal characteristics including maternal third trimester BMI, however, we observed no association of caesarean versus vaginal delivery with child BMI (β 0.05 kg/m2; 95%CI: −0.03, 0.14), sum of skinfolds (0.14 mm; −0.13, 0.42), waist circumference (−0.07 cm; −0.23, 0.10), obesity (OR 0.99; 0.76, 1.29), or systolic (−0.20 mmHg; −0.70, 0.30) or diastolic (−0.17 mmHg, −0.60, 0.26) blood pressure at 6.5 years; results were similar at 11.5 and 16 years. At 11.5 years, we observed a modest association of caesarean delivery with fasting insulin (0.33 mU/L; 0.00, 0.65). Conclusions: Caesarean delivery had little or no association with adiposity or related cardio‐metabolic biomarkers in childhood. Adjustment for maternal BMI attenuated all outcome effect estimates. [ABSTRACT FROM AUTHOR]

Purpose: The relationship between body mass index (BMI) and prostate cancer remains unclear. However, there is an inverse association between BMI and prostate-specific antigen (PSA), used for prostate cancer screening. We conducted this review to estimate the associations between BMI and (1) prostate cancer, (2) advanced prostate cancer, and (3) PSA.Methods: We searched PubMed and Embase for studies until 02 October 2017 and obtained individual participant data from four studies. In total, 78 studies were identified for the association between BMI and prostate cancer, 21 for BMI and advanced prostate cancer, and 35 for BMI and PSA. We performed random-effects meta-analysis of linear associations of log-PSA and prostate cancer with BMI and, to examine potential non-linearity, of associations between categories of BMI and each outcome.Results: In the meta-analyses with continuous BMI, a 5 kg/m2 increase in BMI was associated with a percentage change in PSA of - 5.88% (95% CI - 6.87 to - 4.87). Using BMI categories, compared to normal weight men the PSA levels of overweight men were 3.43% lower (95% CI - 5.57 to - 1.23), and obese men were 12.9% lower (95% CI - 15.2 to - 10.7). Prostate cancer and advanced prostate cancer analyses showed little or no evidence associations.Conclusion: There is little or no evidence of an association between BMI and risk of prostate cancer or advanced prostate cancer, and strong evidence of an inverse and non-linear association between BMI and PSA. The association between BMI and prostate cancer is likely biased if missed diagnoses are not considered. [ABSTRACT FROM AUTHOR]

Recent studies finding that small-for-gestational-age (SGA) birth is associated with increased adiposity in childhood and adulthood have been based on analyses "adjusting" for height, weight, or body mass index (BMI; weight (kg)/height (m)²) measured concurrently with the adiposity measurement. To assess the potential for bias due to overadjustment for a causal mediator, we compared 2 approaches to analyzing the association between SGA birth and adiposity outcomes (skinfold thicknesses and bioelectrical impedance measurement of body fat) at age 11.5 years using the same data set in a cohort of Belarusian children followed from birth in 1996-1997 to age 11.5 years in 2008-2010. We 1) studied the association of SGA birth with adiposity, adjusting for baseline covariates only, and 2) made additional regression adjustment for concurrent height, weight, or BMI. The first approach yielded negative associations between SGA birth and all adiposity outcomes. Additional adjustment for concurrent weight or BMI reversed (i.e., to positive) the SGA-adiposity association. To explore the latter anthropometric measures as causal mediators, we also used marginal structural models to estimate the controlled direct effect of SGA birth. That effect was similar to the effect seen with the first approach when modeled on height, was null when modeled on BMI, but was confounded by differences in lean mass versus fat mass when modeled on weight. [ABSTRACT FROM AUTHOR]

Purpose: Previous studies indicate a possible inverse relationship between prostate-specific antigen (PSA) and body mass index (BMI), and a positive relationship between PSA and age. We investigated the associations between age, BMI, PSA, and screen-detected prostate cancer to determine whether an age-BMI-adjusted PSA model would be clinically useful for detecting prostate cancer.Methods: Cross-sectional analysis nested within the UK ProtecT trial of treatments for localized cancer. Of 18,238 men aged 50-69 years, 9,457 men without screen-detected prostate cancer (controls) and 1,836 men with prostate cancer (cases) met inclusion criteria: no history of prostate cancer or diabetes; PSA < 10 ng/ml; BMI between 15 and 50 kg/m2. Multivariable linear regression models were used to investigate the relationship between log-PSA, age, and BMI in all men, controlling for prostate cancer status.Results: In the 11,293 included men, the median PSA was 1.2 ng/ml (IQR: 0.7-2.6); mean age 61.7 years (SD 4.9); and mean BMI 26.8 kg/m2 (SD 3.7). There were a 5.1% decrease in PSA per 5 kg/m2 increase in BMI (95% CI 3.4-6.8) and a 13.6% increase in PSA per 5-year increase in age (95% CI 12.0-15.1). Interaction tests showed no evidence for different associations between age, BMI, and PSA in men above and below 3.0 ng/ml (all p for interaction >0.2). The age-BMI-adjusted PSA model performed as well as an age-adjusted model based on National Institute for Health and Care Excellence (NICE) guidelines at detecting prostate cancer.Conclusions: Age and BMI were associated with small changes in PSA. An age-BMI-adjusted PSA model is no more clinically useful for detecting prostate cancer than current NICE guidelines. Future studies looking at the effect of different variables on PSA, independent of their effect on prostate cancer, may improve the discrimination of PSA for prostate cancer. [ABSTRACT FROM AUTHOR]

Objective: To investigate the associations of body mass index (BMI) and grip strength with objective measures of physical performance (chair rise time, walking speed and balance) including an assessment of sex differences and non-linearity. Methods: Cross-sectional data from eight UK cohort studies (total N = 16 444) participating in the Healthy Ageing across the Life Course (HALCyon) research programme, ranging in age from 50 to 90+ years at the time of physical capability assessment, were used. Regression models were fitted within each study and meta-analysis methods used to pool regression coefficients across studies and to assess the extent of heterogeneity between studies. Results: Higher BMI was associated with poorer performance on chair rise (N = 10 773), walking speed (N = 9 761) and standing balance (N = 13 921) tests. Higher BMI was associated with stronger grip strength in men only. Stronger grip strength was associated with better performance on all tests with a tendency for the associations to be stronger in women than men; for example, walking speed was higher by 0.43 cm/s (0.14, 0.71) more per kg in women than men. Both BMI and grip strength remained independently related with performance after mutual adjustment, but there was no evidence of effect modification. Both BMI and grip strength exhibited non-linear relations with performance; those in the lowest fifth of grip strength and highest fifth of BMI having particularly poor performance. Findings were similar when waist circumference was examined in place of BMI. Conclusion: Older men and women with weak muscle strength and high BMI have considerably poorer performance than others and associations were observed even in the youngest cohort (age 53). Although causality cannot be inferred from observational cross-sectional studies, our findings suggest the likely benefit of early assessment and interventions to reduce fat mass and improve muscle strength in the prevention of future functional limitations. [ABSTRACT FROM AUTHOR]

Background: It is suggested that maternal adiposity has a stronger association with offspring adiposity than does paternal adiposity. Furthermore, a recent small study reported gender assortment in parental-offspring adiposity associations. We aimed to examine these associations in one of the largest studies to date using data from a low-middle income country that has recently undergone a major political and economic transition. Methods and Principal Findings: In a cross-sectional study of 12,181 parental-offspring trios from Belarus (mean age (SD) of mothers 31.7 (4.9), fathers 34.1 (5.1) and children 6.6 (0.3) at time of assessment), we found positive graded associations of mother's and father's BMI with offspring adiposity. There was no evidence that these associations differed between mothers and fathers. For example, the odds ratio of offspring overweight or obesity (based on BMI) comparing obese and overweight mothers to normal weight mothers was 2.03 (95%CI 1.77, 2.31) in fully adjusted models; the equivalent result for father's overweight/obesity was 1.81 (1.58, 2.07). Equivalent results for offspring being in the top 10% waist circumference were 1.91 (1.67, 2.18) comparing obese/overweight to normal weight mothers and 1.72 (1.53, 1.95) comparing obese/ overweight to normal weight fathers. Similarly, results for offspring being in the top 10% of percent fat mass were 1.58 (1.36, 1.84) and 1.76 (1.49, 2.07), for mother's and father's obese/overweight exposures respectively. There was no strong or consistent evidence of gender assortment - i.e. associations of maternal adiposity exposures with offspring outcomes were similar in magnitude for their daughters compared to equivalent associations in their sons and paternal associations were also similar in sons and daughters. Conclusions/Significance: These findings suggest that genetic and/or shared familial environment explain family clustering of adiposity. Interventions aimed at changing overall family lifestyle are likely to be important for population level obesity prevention. [ABSTRACT FROM AUTHOR]

Excess body weight is thought to increase the risk of aggressive prostate cancer (PCa), although the biological mechanism is currently unclear. Body fatness is positively associated with a diminished cellular response to insulin and biomarkers of insulin signalling have been positively associated with PCa risk. We carried out a two-pronged systematic review of (a) the effect of reducing body fatness on insulin biomarker levels and (b) the effect of insulin biomarkers on PCa risk, to determine whether a reduction in body fatness could reduce PCa risk via effects on the insulin signalling pathway. We identified seven eligible randomised controlled trials of interventions designed to reduce body fatness which measured insulin biomarkers as an outcome, and six eligible prospective observational studies of insulin biomarkers and PCa risk. We found some evidence that a reduction in body fatness improved insulin sensitivity although our confidence in this evidence was low based on GRADE (Grading of Recommendations, Assessment, Development and Evaluations). We were unable to reach any conclusions on the effect of insulin sensitivity on PCa risk from the few studies included in our systematic review. A reduction in body fatness may reduce PCa risk via insulin signalling, but more high-quality evidence is needed before any conclusions can be reached regarding PCa. [ABSTRACT FROM AUTHOR]