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MotivationIn recent years Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods.Implementationmrrobust is freely available as a Stata package.General FeaturesThe package includes inverse variance weighted estimation, as well as a range of median and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualising each estimate either individually or simultaneously. The package also provides statistics such as which are useful in assessing attenuation bias in causal estimates.AvailabilityThe software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].

ObjectivePsoriasis and eczema are common inflammatory skin diseases that have been reported to be associated with obesity. However, causality has not yet been established. We aimed to investigate the possible causal relationship between body mass index (BMI) and psoriasis or eczema.MethodsFollowing a review of published epidemiological evidence of the association between obesity and either psoriasis or eczema, Mendelian Randomization (MR) was used to test for a causal relationship between BMI and these inflammatory skin conditions. We used a genetic instrument comprising 97 single nucleotide polymorphisms (SNPs) associated with BMI. One-sample MR was conducted using individual-level data (401,508 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (731,021 individuals) from published BMI, psoriasis and eczema GWAS. The one-sample and two-sample MR estimates were meta-analysed using a fixed effect model. To explore the reverse causal direction, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis and eczema were used to test if inflammatory skin disease has a causal effect on BMI.ResultsPublished observational data show an association of greater BMI with both psoriasis and eczema case status. The observational associations were confirmed in UK Biobank and HUNT datasets. MR analyses provide evidence that higher BMI causally increases the odds of psoriasis (by 53% per 5 units higher BMI; OR= 1.09 (1.06 to 1.12) per 1 kg/m2; P=4.67×10-9) and eczema (by 8% per 5 units higher BMI; OR=1.02 (1.00 to 1.03) per 1 kg/m2; P=0.09). When investigating causality in the opposite direction, MR estimates provide little evidence for an effect of either psoriasis or eczema influencing BMI.ConclusionOur study, using genetic variants as instrumental variables for BMI, shows that higher BMI leads to a higher risk of inflammatory skin disease. The causal relationship was stronger for psoriasis than eczema. Therapies and life-style interventions aimed at controlling BMI or targeting the mechanisms linking obesity with skin inflammation may offer an opportunity for the prevention or treatment of these common skin diseases.

In this article, we demonstrate how to fit fixed- and random-effects meta-analysis, meta-regression, and multivariate outcome meta-analysis models under the structural equation modeling framework using the sem and gsem commands. While all of these models can be fit using existing user-written commands, formulating the models in the structural equation modeling framework provides deeper insight into how they work. Further, the heterogeneity test for meta-regression and multivariate meta-analysis is readily available from this output.

Essentials Observational data suggest taller people have a higher risk of venous thromboembolism (VTE). We used Mendelian randomization techniques to further explore this association in three studies. Risk of VTE increased by 30-40% for each 10 cm increment in height. Height was more strongly associated with deep vein thrombosis than with pulmonary embolism.Background Taller height is associated with a greater risk of venous thromboembolism (VTE). Objectives To use instrumental variable (IV) techniques (Mendelian randomization) to further explore this relationship. Methods Participants of European ancestry were included from two cohort studies (Atherosclerosis Risk in Communities [ARIC] study and Cardiovascular Health Study [CHS]) and one case-control study (Mayo Clinic VTE Study [Mayo]). We created two weighted genetic risk scores (GRSs) for height; the full GRS included 668 single-nucleotide polymorphisms (SNPs) from a previously published meta-analysis, and the restricted GRS included a subset of 362 SNPs not associated with weight independently of height. Standard logistic regression and IV models were used to estimate odds ratios (ORs) for VTE per 10-cm increment in height. ORs were pooled across the three studies by the use of inverse variance-weighted random effects meta-analysis. Results Among 9143 ARIC and 3180 CHS participants free of VTE at baseline, there were 367 and 109 incident VTE events. There were 1143 VTE cases and 1292 controls included from Mayo. The pooled ORs from non-IV models and models using the full and restricted GRSs as IVs were 1.27 (95% confidence interval [CI] 1.11-1.46), 1.34 (95% CI 1.04-1.73) and 1.45 (95% CI 1.04-2.01) per 10-cm greater height, respectively. Conclusions Taller height is associated with an increased risk of VTE in adults of European ancestry. Possible explanations for this association, including taller people having a greater venous surface area, a higher number of venous valves, or greater hydrostatic pressure, need to be explored further.

Background: The implications of different adiposity measures on cardiovascular disease etiology remain unclear. In this article, we quantify and contrast causal associations of central adiposity (waist-to-hip ratio adjusted for body mass index [WHRadjBMI]) and general adiposity (body mass index [BMI]) with cardiometabolic disease. Methods: Ninety-seven independent single-nucleotide polymorphisms for BMI and 49 single-nucleotide polymorphisms for WHRadjBMI were used to conduct Mendelian randomization analyses in 14 prospective studies supplemented with coronary heart disease (CHD) data from CARDIoGRAMplusC4D (Coronary Artery Disease Genome-wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics; combined total 66 842 cases), stroke from METASTROKE (12 389 ischemic stroke cases), type 2 diabetes mellitus from DIAGRAM (Diabetes Genetics Replication and Meta-analysis; 34 840 cases), and lipids from GLGC (Global Lipids Genetic Consortium; 213 500 participants) consortia. Primary outcomes were CHD, type 2 diabetes mellitus, and major stroke subtypes; secondary analyses included 18 cardiometabolic traits. Results: Each one standard deviation (SD) higher WHRadjBMI (1 SD≈0.08 U) associated with a 48% excess risk of CHD (odds ratio [OR] for CHD, 1.48; 95% confidence interval [CI], 1.28–1.71), similar to findings for BMI (1 SD≈4.6 kg/m 2 ; OR for CHD, 1.36; 95% CI, 1.22–1.52). Only WHRadjBMI increased risk of ischemic stroke (OR, 1.32; 95% CI, 1.03–1.70). For type 2 diabetes mellitus, both measures had large effects: OR, 1.82 (95% CI, 1.38–2.42) and OR, 1.98 (95% CI, 1.41–2.78) per 1 SD higher WHRadjBMI and BMI, respectively. Both WHRadjBMI and BMI were associated with higher left ventricular hypertrophy, glycemic traits, interleukin 6, and circulating lipids. WHRadjBMI was also associated with higher carotid intima-media thickness (39%; 95% CI, 9%–77% per 1 SD). Conclusions: Both general and central adiposity have causal effects on CHD and type 2 diabetes mellitus. Central adiposity may have a stronger effect on stroke risk. Future estimates of the burden of adiposity on health should include measures of central and general adiposity.

ObjectivesTo determine whether educational attainment is a causal risk factor in the development of coronary heart disease.DesignMendelian randomization study, where genetic data are used as proxies for education, in order to minimize confounding. A two-sample design was applied, where summary level genetic data was analysed from two publically available consortia.SettingIn the main analysis, we analysed genetic data from two large consortia (CARDIoGRAM and SSGAC), comprising of 112 cohorts from predominantly high-income countries. In addition, we also analysed genetic data from 7 additional large consortia, in order to identify putative causal mediators.ParticipantsThe main analysis was of 589 377 men and women, predominantly of European origin.ExposureA one standard deviation increase in the genetic predisposition towards higher education (i.e. 3.6 years of additional schooling). This was measured by 162 genetic variants that have been previously associated with education.Main outcomeCombined fatal and nonfatal coronary heart disease (63 746 events).Results3.6 years of additional education lowered the risk of coronary heart disease by a third (odds ratio = 0.67, 95% confidence interval [CI], 0.59 to 0.77, p=0.01). Equivalent increases in education were also causally associated with reductions in smoking, BMI and improvements in blood lipid profiles.ConclusionsMore time spent in education is causally associated with a large reduction in the risk of coronary heart disease. This may be partly explained by changes to smoking, BMI and a blood lipids. These findings offer support for policy interventions that increase education, in order to also reduce the burden of cardiovascular disease.

Background: Mendelian randomization studies have so far restricted attention to linear associations relating the genetic instrument to the exposure, and the exposure to the outcome. In some cases, however, observational data suggest a non-linear association between exposure and outcome. For example, alcohol consumption is consistently reported as having a U-shaped association with cardiovascular events. In principle, Mendelian randomization could address concerns that the apparent protective effect of light-to-moderate drinking might reflect ‘sick-quitters’ and confounding.\ud \ud Methods: The Alcohol-ADH1B Consortium was established to study the causal effects of alcohol consumption on cardiovascular events and biomarkers, using the single nucleotide polymorphism rs1229984 in ADH1B as a genetic instrument. To assess non-linear causal effects in this study, we propose a novel method based on estimating local average treatment effects for discrete levels of the exposure range, then testing for a linear trend in those effects. Our method requires an assumption that the instrument has the same effect on exposure in all individuals. We conduct simulations examining the robustness of the method to violations of this assumption, and apply the method to the Alcohol-ADH1B Consortium data.\ud \ud Results: Our method gave a conservative test for non-linearity under realistic violations of the key assumption. We found evidence for a non-linear causal effect of alcohol intake on several cardiovascular traits.\ud \ud Conclusions: We believe our method is useful for inferring departure from linearity when only a binary instrument is available. We estimated non-linear causal effects of alcohol intake which could not have been estimated through standard instrumental variable approaches.

OBJECTIVES: The purpose of this analysis was to compare the association between variants at the chromosome 9p21 locus (Ch9p21) and risk of first versus subsequent coronary heart disease (CHD) events through systematic review and meta-analysis. BACKGROUND: Ch9p21 is a recognized risk factor for a first CHD event. However, its association with risk of subsequent events in patients with established CHD is less clear. METHODS: We searched PubMed and EMBASE for prospective studies reporting association of Ch9p21 with incident CHD events and extracted information on cohort type (individuals without prior CHD or individuals with established CHD) and effect estimates for risk of events. RESULTS: We identified 31 cohorts reporting on 193,372 individuals. Among the 16 cohorts of individuals without prior CHD (n = 168,209), there were 15,664 first CHD events. Ch9p21 was associated with a pooled hazard ratio (HR) of a first event of 1.19 (95% confidence interval: 1.17 to 1.22) per risk allele. In individuals with established CHD (n = 25,163), there were 4,436 subsequent events providing >99% and 91% power to detect a per-allele HR of 1.19 or 1.10, respectively. The pooled HR for subsequent events was 1.01 (95% confidence interval: 0.97 to 1.06) per risk allele. There was strong evidence of heterogeneity between the effect estimates for first and subsequent events (p value for heterogeneity = 5.6 × 10(-11)). We found no evidence for biases to account for these findings. CONCLUSIONS: Ch9p21 shows differential association with risk of first versus subsequent CHD events. This has implications for genetic risk prediction in patients with established CHD and for mechanistic understanding of how Ch9p21 influences risk of CHD.

We describe a method to estimate associations between random effects from multilevel models. We provide two new postestimation commands, reffadjustsim and reffadjust4nlcom, which are distributed as the reffadjust package. These commands produce the estimates and their associated confidence intervals. The commands are used after official Stata multilevel model estimation commands mixed, meqrlogit, and meqrpoisson (formerly named xtmixed, xtmelogit, and xtmepoisson, respectively, before Stata 13) and with models fit in the MLwiN statistical software package via the runmlwin command. We demonstrate our commands with several simulated datasets and for a bivariate outcome model investigating the relationship between weight and mean arterial pressure in pregnant women using data from the Avon Longitudinal Study of Parents and Children. Our method and commands help to improve the interpretability of estimated random-effects variance components from multilevel models.

Ways to address the increasing healthcare needs of older people are a priority for the National Health Service (NHS) in England. The NHS England Test Bed programme was designed to trial new models of care that are supported by digital health technologies. This paper reports on findings from one Test Bed programme, the Lancashire and Cumbria Innovation Alliance (LCIA) – a partnership between NHS England, industry and Lancaster University, which ran from 2016 to 2018. A key aim of the LCIA Test Bed was to explore the extent to which supported self-care telehealth technology helped older people with long-term conditions to better self-manage their own care, promoting independence and enabling them to remain at home for longer. Each patient received a combination of health technologies over a six-month period. This paper presents results from the qualitative data that formed part of a large-scale mixed-methods evaluation. Specifically it draws on the analysis of 34 observational interviews with 17 participants with chronic obstructive pulmonary disease (COPD) to understand the role of these technologies in the self-management of their care. The data revealed that the majority of participants felt more confident about self-managing COPD as a result of their participation in the programme. These increases in confidence were the result of participants’ increased knowledge and skills in managing their COPD. The paper demonstrates how patients learned to better manage their respiratory condition, the impact of this learning on their daily lives and that of their family carers, and the implications for healthcare practice.

IntroductionA wealth of evidence from a range of country settings indicates that antenatal care, facility delivery and postnatal care can reduce maternal and child mortality and morbidity in high-burden settings. However, the utilisation of these services by pregnant women, particularly in low/middle-income country settings, is well below that recommended by the WHO. The Afya trial aims to assess the impact, cost-effectiveness and scalability of conditional cash transfers to promote increased utilisation of these services in rural Kenya and thus retain women in the continuum of care during pregnancy, birth and the postnatal period. This protocol describes the planned economic evaluation of the Afya trial.Methods and analysisThe economic evaluation will be conducted from the provider perspective as a within-trial analysis to evaluate the incremental costs and health outcomes of the cash transfer programme compared with the status quo. Incremental cost-effectiveness ratios will be presented along with a cost-consequence analysis where the incremental costs and all statistically significant outcomes will be listed separately. Sensitivity analyses will be undertaken to explore uncertainty and to ensure that results are robust. A fiscal space assessment will explore the affordability of the intervention. In addition, an analysis of equity impact of the intervention will be conducted.Ethics and disseminationThe study has received ethics approval from the Maseno University Ethics Review Committee, REF MSU/DRPI/MUERC/00294/16. The results of the economic evaluation will be disseminated in a peer-reviewed journal and presented at a relevant international conference.Trial registration numberNCT03021070

Background Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis. Methods and findings Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02–1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13–1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03–1.04; P = 1.73 × 10−60). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06–1.12) per 1 kg/m2; P = 4.67 × 10−9). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (−0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied. Conclusions Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship., In a mendelian randomization study, Ashley Budu-Aggrey and co-workers study the influence of body mass index on psoriasis., Author summary Why was this study done? Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. However, the direction of causality has not been established. Understanding the causal relationship could inform the management or prevention of disease. What did the researchers do and find? A mendelian randomization (MR) approach was used to investigate the causal relationship between higher body mass index (BMI) and psoriasis. Our analysis included data for a total of 753,421 individuals from two of the largest population-based studies available as well as published genome-wide association studies (GWASs). We found evidence that higher BMI causally increases the risk of psoriasis, supporting observational reports in previous literature. Conversely, there was no evidence to support a causal effect of psoriasis genetic risk upon BMI. What do these findings mean? Our findings suggest that obesity contributes to the pathogenesis of psoriasis, and highlight possible mechanistic relationships. If our findings regarding genetically influenced BMI can be extended to elevated BMI that is amenable to modification by diet or behavior, then they could carry health implications. Further work will be required to determine the effect of a short-term intervention aimed at reducing BMI upon psoriasis patients after disease onset, ideally within a clinical trial setting.

Background: Differences between mothers who do and do not succeed in breastfeeding are likely to confound associations of lactation with later maternal adiposity.Objective: We compared adiposity and blood pressure (BP) in women randomly assigned to an intervention to promote prolonged and exclusive breastfeeding or usual care.Design: We performed a cluster-randomized trial at 31 hospitals in Belarus in 1996–1997.Results: Of 17,046 women enrolled at delivery, we assessed 11,867 women (69.6%) at 11.5 y postpartum. The prevalence of exclusive breastfeeding ≥3 mo was 44.5% in 6321 women in the intervention group and 7.1% in 5546 women in the control group. At 11.5 y postpartum, mean (±SD) body mass index (BMI; in kg/m2) was 26.5 ± 5.5, the percentage of body fat was 33.6% ± 8.3%, and systolic BP was 124.6 ± 14.6 mm Hg. On intention-to-treat analysis (without imputation) with adjustment for clustering by hospital, mean outcomes were lower in intervention compared with control mothers for BMI (mean difference: −0.27; 95% CI: −0.91, 0.37), body fat (−0.49%; 95% CI: −1.25%, 0.27%), and systolic BP (−0.81 mm Hg; 95% CI: −3.33, 1.71 mm Hg), but effect sizes were small, CIs were wide, and results were attenuated further toward the null after adjustment for baseline characteristics. Results were similar in sensitivity analyses [ie, by using conventional observational analyses disregarding treatment assignment, instrumental variable analyses to estimate the causal effect of breastfeeding, and multiple imputation to account for missing outcome measures (n = 17,046)].Conclusion: In women who initiated breastfeeding, an intervention to promote longer breastfeeding duration did not result in an important lowering of adiposity or BP. This trial was registered at clinicaltrials.gov as NCT01561612 and at Current Controlled Trials as ISRCTN37687716.

Objectives\ud \ud To assess associations between the launch of the National Dementia Strategy (NDS) and antipsychotic prescribing in long-term residential care (LTC) in England.\ud \ud Setting and participants \ud \ud Retrospective analysis of prescribing patterns in 616 LTC institutions (31 619 residents) following launch of the NDS, using information from electronic medicines management system.\ud \ud Primary and secondary outcome measures\ud \ud Antipsychotic prescribing point prevalence (PP) for all residents in a cross section of LTC settings over a 4-year period following NDS launch. Secondary outcomes included dosages, length of treatment and use of recommended second-generation antipsychotics (SGAs) versus first-generation antipsychotics (FGAs). Associations between facility-level PP values and institutional characteristics, resident demographics were explored. Variations across geographical areas examined. Prescription net ingredient costs calculated.\ud \ud Results\ud \ud No statistically significant difference was observed in overall prescribing rates over the 4-year period (Kolmogorov-Smirnov (KS) test p=0.60), and there was no significant shift towards newer SGAs (KS test p=0.32). Dosages were above the maximum indicated in only 1.3% of cases, but duration of prescribing was excessive in 69.7% of cases. Care homes in the highest prescribing quintile were more likely to be located in a deprived area (rate ratio (Q5/Q1) RR=5.89, 95% CI 4.35 to 7.99), registered for dementia (RR=3.38, 95% CI 3.06 to 3.73) and those in the lowest quintile were more likely to be served by a single general practitioner (GP) practice (RR=0.48; 95% CI 0.37 to 0.63); p

Background It has been suggested that greater maternal adiposity during pregnancy affects lifelong risk of offspring fatness via intrauterine mechanisms. Our aim was to use Mendelian randomisation (MR) to investigate the causal effect of intrauterine exposure to greater maternal body mass index (BMI) on offspring BMI and fat mass from childhood to early adulthood. Methods and Findings We used maternal genetic variants as instrumental variables (IVs) to test the causal effect of maternal BMI in pregnancy on offspring fatness (BMI and dual-energy X-ray absorptiometry [DXA] determined fat mass index [FMI]) in a MR approach. This was investigated, with repeat measurements, from ages 7 to 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 2,521 to 3,720 for different ages). We then sought to replicate findings with results for BMI at age 6 in Generation R (n = 2,337 for replication sample; n = 6,057 for total pooled sample). In confounder-adjusted multivariable regression in ALSPAC, a 1 standard deviation (SD, equivalent of 3.7 kg/m2) increase in maternal BMI was associated with a 0.25 SD (95% CI 0.21–0.29) increase in offspring BMI at age 7, with similar results at later ages and when FMI was used as the outcome. A weighted genetic risk score was generated from 32 genetic variants robustly associated with BMI (minimum F-statistic = 45 in ALSPAC). The MR results using this genetic risk score as an IV in ALSPAC were close to the null at all ages (e.g., 0.04 SD (95% CI -0.21–0.30) at age 7 and 0.03 SD (95% CI -0.26–0.32) at age 18 per SD increase in maternal BMI), which was similar when a 97 variant generic risk score was used in ALSPAC. When findings from age 7 in ALSPAC were meta-analysed with those from age 6 in Generation R, the pooled confounder-adjusted multivariable regression association was 0.22 SD (95% CI 0.19–0.25) per SD increase in maternal BMI and the pooled MR effect (pooling the 97 variant score results from ALSPAC with the 32 variant score results from Generation R) was 0.05 SD (95%CI -0.11–0.21) per SD increase in maternal BMI (p-value for difference between the two results = 0.05). A number of sensitivity analyses exploring violation of the MR results supported our main findings. However, power was limited for some of the sensitivity tests and further studies with relevant data on maternal, offspring, and paternal genotype are required to obtain more precise (and unbiased) causal estimates. Conclusions Our findings provide little evidence to support a strong causal intrauterine effect of incrementally greater maternal BMI resulting in greater offspring adiposity., Using a Mendelian randomization approach, Rebecca Richmond and colleagues find limited evidence for a causal effect of maternal pregnancy adiposity on future offspring adiposity during childhood and adolescence., Author Summary Why Was This Study Done? Being overweight or obese in pregnancy causes babies to be born larger. Whether these babies go into childhood and adolescence more overweight as a result of their mothers being overweight in pregnancy has not been fully established. We wanted to investigate whether genetically elevated body mass index (BMI) of mothers in pregnancy was causally associated with higher levels of fatness in their offspring in childhood and adolescence, over and above the association expected given genetic transmission of BMI-associated variants. What Did the Researchers Do and Find? We used information on 6,057 mother–child pairs from two prospective birth cohort studies, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Generation R study to assess this. Our findings provide little evidence to support the long-term impact of maternal BMI in pregnancy on the child’s risk of fatness in childhood and adolescence. Rather, most of the association between a mother’s BMI in pregnancy and her child’s fatness is explained by genetic transmission of BMI-associated variants. What Do These Findings Mean? These findings suggest that public health interventions directed at all family members and at different stages of the life course are likely to be important and are potentially more likely to halt the obesity epidemic than a focus on maternal overweight and obesity status in pregnancy. Although we found no large effects of being overweight or obese in pregnancy on offspring’s risk of fatness in later life, further studies with relevant data are required to determine whether there might be smaller effects that our study was unable to detect.

OBJECTIVE The causal nature of associations between circulating triglycerides, insulin resistance, and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes and raise normal fasting glucose levels and hepatic insulin resistance. RESEARCH DESIGN AND METHODS We tested 10 common genetic variants robustly associated with circulating triglyceride levels against the type 2 diabetes status in 5,637 case and 6,860 control subjects and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8,271 nondiabetic individuals from four studies. RESULTS Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (SD 0.59 [95% CI 0.52–0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that the carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio [OR] 0.99 [95% CI 0.97–1.01]; P = 0.26). In nondiabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (SD 0.00 per weighted allele [95% CI −0.01 to 0.02]; P = 0.72) or increased fasting glucose levels (0.00 [−0.01 to 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose, or fasting insulin and, for diabetes, showed a trend toward a protective association (OR per 1-SD increase in log10 triglycerides: 0.61 [95% CI 0.45–0.83]; P = 0.002). CONCLUSIONS Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes or raise fasting glucose or fasting insulin levels in nondiabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

ImportanceNeonates born to overweight or obese women are larger and at higher risk of birth complications. Many maternal obesity-related traits are observationally associated with birth weight, but the causal nature of these associations is uncertain.ObjectiveTo test for genetic evidence of causal associations of maternal body mass index (BMI) and related traits with birth weight.Design, Setting, and ParticipantsMendelian randomization to test whether maternal BMI and obesity-related traits are potentially causally related to offspring birth weight. Data from 30 487 women in 18 studies were analyzed. Participants were of European ancestry from population- or community-based studies in Europe, North America, or Australia and were part of the Early Growth Genetics Consortium. Live, term, singleton offspring born between 1929 and 2013 were included.ExposuresGenetic scores for BMI, fasting glucose level, type 2 diabetes, systolic blood pressure (SBP), triglyceride level, high-density lipoprotein cholesterol (HDL-C) level, vitamin D status, and adiponectin level.Main Outcome and MeasureOffspring birth weight from 18 studies.ResultsAmong the 30 487 newborns the mean birth weight in the various cohorts ranged from 3325 g to 3679 g. The maternal genetic score for BMI was associated with a 2-g (95% CI, 0 to 3 g) higher offspring birth weight per maternal BMI-raising allele (P = .008). The maternal genetic scores for fasting glucose and SBP were also associated with birth weight with effect sizes of 8 g (95% CI, 6 to 10 g) per glucose-raising allele (P = 7 × 10−14) and −4 g (95% CI, −6 to −2g) per SBP-raising allele (P = 1×10−5), respectively. A 1-SD ( ≈ 4 points) genetically higher maternal BMI was associated with a 55-g higher offspring birth weight (95% CI, 17 to 93 g). A 1-SD ( ≈ 7.2 mg/dL) genetically higher maternal fasting glucose concentration was associated with 114-g higher offspring birth weight (95% CI, 80 to 147 g). However, a 1-SD ( ≈ 10 mm Hg) genetically higher maternal SBP was associated with a 208-g lower offspring birth weight (95% CI, −394 to −21 g). For BMI and fasting glucose, genetic associations were consistent with the observational associations, but for systolic blood pressure, the genetic and observational associations were in opposite directions.Conclusions and RelevanceIn this mendelian randomization study, genetically elevated maternal BMI and blood glucose levels were potentially causally associated with higher offspring birth weight, whereas genetically elevated maternal SBP was potentially causally related to lower birth weight. If replicated, these findings may have implications for counseling and managing pregnancies to avoid adverse weight-related birth outcomes.

Recent national surveys suggest that child obesity in the United States may have reached a plateau, but corresponding trends in energy intake have not been examined in depth. This article evaluates medium-term trends in children's reported energy intake by using 4 waves of national dietary surveillance from 2003-2004 to 2009-2010. The analysis uses up to 2 24-h dietary recalls, incorporating methods that address challenges in estimating usual intake, accounting for intraindividual variance and covariates such as the presence of atypical consumption days. Quantile regression was used to assess disparities in intake among sociodemographic subgroups at extremes of the distribution as well as at the median, and the potential influence of misreporting was evaluated. Results indicated that after an initial decline in intakes across all age groups through 2007-2008, there were significant increases of ∼90 kcal/d at the median among adolescents in 2009-2010, whereas intakes in younger children remained steady. Among adolescent boys, the recent increase was larger at the 90th percentile than at the median. Intake trends did not vary by race/ethnic group, among whom intakes were similar at the upper end of the distribution. Misreporting did not influence trends over time, but intakes were lower in younger children and higher in older children after excluding misreporters. Overall, findings suggest that declines in children's energy intake from 2003-2004 through 2007-2008 were consistent with the obesity plateau observed in most age and gender subgroups through 2009-2010. However, there is evidence of increased intakes among adolescents in 2009-2010, which may threaten the earlier abatement in overweight in this older age group.

Mendelian randomization studies estimate causal effects using genetic variants as instruments. Instrumental variable methods are straightforward for linear models, but epidemiologists often use odds ratios to quantify effects. Also, odds ratios are often the quantities reported in meta-analyses. Many applications of Mendelian randomization dichotomize genotype and estimate the population causal log odds ratio for unit increase in exposure by dividing the genotype-disease log odds ratio by the difference in mean exposure between genotypes. This 'Wald-type' estimator is biased even in large samples, but whether the magnitude of bias is of practical importance is unclear. We study the large-sample bias of this estimator in a simple model with a continuous normally distributed exposure, a single unobserved confounder that is not an effect modifier, and interpretable parameters. We focus on parameter values that reflect scenarios in which we apply Mendelian randomization, including realistic values for the degree of confounding and strength of the causal effect. We evaluate this estimator and the causal odds ratio using numerical integration and obtain approximate analytic expressions to check results and gain insight. A small simulation study examines finite sample bias and mild violations of the normality assumption. For our simple data-generating model, we find that the Wald estimator is asymptotically biased with a bias of around 10% in fairly typical Mendelian randomization scenarios but which can be larger in more extreme situations. Recently developed methods such as structural mean models require fewer untestable assumptions and we recommend their use when the individual-level data they require are available. The Wald-type estimator may retain a role as an approximate method for meta-analysis based on summary data.

Instrumental variables can be used to make inferences about causal effects in the presence of unmeasured confounding. For a model in which the instrument, intermediate/treatment, and outcome variables are all binary, Balke and Pearl (1997, Journal of the American Statistical Association 92: 1172–1176) derived nonparametric bounds for the intervention probabilities and the average causal effect. We have implemented these bounds in two commands: bpbounds and bpboundsi. We have also implemented several extensions to these bounds. One of these extensions applies when the instrument and outcome are measured in one sample and the instrument and intermediate are measured in another sample. We have also implemented the bounds for an instrument with three categories, as is common in Mendelian randomization analyses in epidemiology and for the case where a monotonic effect of the instrument on the intermediate can be assumed. In each case, we calculate the instrumental-variable inequality constraints as a check for gross violations of the instrumental-variable conditions. The use of the commands is illustrated with a re-creation of the original Balke and Pearl analysis and with a Mendelian randomization analysis. We also give a simulated example to demonstrate that the instrumental-variable inequality constraints can both detect and fail to detect violations of the instrumental-variable conditions.

BACKGROUND: Gestational weight gain (GWG) is associated with a range of health outcomes, but little is known about the factors that influence it. OBJECTIVE: The objective was to test the hypothesis that maternal and fetal genetic variants that are reliably associated with adiposity are associated with GWG. DESIGN: We examined the association of a risk allele score by using 4 adiposity-related single nucleotide polymorphisms (SNPs; rs9939609 in FTO, rs17782313 near MC4R, rs6548238 near TMEM18, and rs10938397 near GNPDA2) with GWG in a pregnancy cohort in which women had detailed repeated assessment of GWG (median number of weight measurements: 10; interquartile range: 8, 11). The numbers included in our analyses varied between 2324 and 7563 for different variant-outcome analyses. A linear spline random-effects model was used to model weight change with gestational age and to relate genetic variants to this. This modeling confirmed 3 distinct periods of GWG: 0-18, 19-28, and ≥29 wk of gestation. RESULTS: Maternal risk allele score and SNPs in FTO, MC4R, and TMEM18 were positively associated with prepregnancy weight. Maternal allele score was inversely associated with GWG in the first 18 wk of pregnancy (-14.46 g/wk per allele; 95% CI: -24.75, -4.17 g/wk per allele) but was not associated with other periods of GWG. Offspring allele score and maternal and offspring individual SNPs were not associated with GWG in any period or with birth weight or postnatal weight retention. CONCLUSIONS: Our findings suggest that neither maternal nor fetal adiposity-related genetic variants are associated with greater GWG. The inverse association of maternal allele score with GWG in the first 18 wk requires replication.

OBJECTIVE: We used genetic variants that are robustly associated with adiposity to examine the causal association of adiposity with psychological distress. METHODS: We examined the association of adiposity with psychological distress in a large (N = 53,221) general population cohort of 20- to 99-year-old adults from Copenhagen, Denmark. Psychological distress was assessed using four questions that asked about: feeling stressed; not accomplishing very much; wanting to give up; and regular use of antidepressants/sedatives. We used the genetic loci FTO rs9939609 and MC4R rs17782313 as instrumental variables for adiposity quantified by body mass index (BMI) and waist to hip ratio (WHR). RESULTS: In conventional multivariable analyses, BMI and WHR were positively associated with distress. For example, the odds ratio of reporting not accomplishing for each additional standard deviation increase for BMI was 1.11 (95% CI: 1.09, 1.13) and for WHR was 1.10 (95% CI: 1.08, 1.13) in the fully adjusted analyses. In contrast, instrumental variable analyses showed an inverse association of adiposity on distress; corresponding odds ratio in instrumental variable analyses was 0.64 (95% CI: 0.46, 0.89) for BMI and 0.49 (95% CI: 0.25, 0.94) for WHR (P-values for difference between the two approaches both = 0.001). CONCLUSION: The inverse associations of adiposity and psychological distress when genetic variants are used as instrumental variables could be explained by biological pathways linking adiposity and distress. The positive associations of adiposity with distress in multivariable analyses might be explained by residual confounding or reverse causality.

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.

In Mendelian randomization a carefully selected gene is used as an instrumental variable in the estimation of the association between a biological phenotype and a disease. A study using Mendelian randomization will have information on an individual's disease status, the genotype and the phenotype. The phenotype must be on the causal pathway between gene and disease for the instrumental-variable analysis to be valid. For a biallelic polymorphism there are three possible genotypes with which to compare disease risk. Existing methods select two of the three possible genotypes for use in a Mendelian randomization analysis. Multivariate meta-analysis models for Mendelian randomization case-control studies are proposed, which extend previous methods by estimating the pooled phenotype-disease association across both genotype comparisons by using the gene-disease log odds ratios and differences in mean phenotypes. The methods are illustrated using a meta-analysis of the effect of a gene related to collagen production on bone mineral density and osteoporotic fracture.

Funnel plots are commonly used to investigate publication and related biases in meta-analysis. Although asymmetry in the appearance of a funnel plot is often interpreted as being caused by publication bias, in reality the asymmetry could be due to other factors that cause systematic differences in the results of large and small studies, for example, confounding factors such as differential study quality. Funnel plots can be enhanced by adding contours of statistical significance to aid in interpreting the funnel plot. If studies appear to be missing in areas of low statistical significance, then it is possible that the asymmetry is due to publication bias. If studies appear to be missing in areas of high statistical significance, then publication bias is a less likely cause of the funnel asymmetry. It is proposed that this enhancement to funnel plots should be used routinely for meta-analyses where it is possible that results could be suppressed on the basis of their statistical significance.

BACKGROUND: Mendelian randomization uses a carefully selected gene as an instrumental-variable (IV) to test or estimate an association between a phenotype and a disease. Classical IV analysis assumes linear relationships between the variables, but disease status is often binary and modelled by a logistic regression. When the linearity assumption between the variables does not hold the IV estimates will be biased. The extent of this bias in the phenotype-disease log odds ratio of a Mendelian randomization study is investigated. METHODS: Three estimators termed direct, standard IV and adjusted IV, of the phenotype-disease log odds ratio are compared through a simulation study which incorporates unmeasured confounding. The simulations are verified using formulae relating marginal and conditional estimates given in the Appendix. RESULTS: The simulations show that the direct estimator is biased by unmeasured confounding factors and the standard IV estimator is attenuated towards the null. Under most circumstances the adjusted IV estimator has the smallest bias, although it has inflated type I error when the unmeasured confounders have a large effect. CONCLUSIONS: In a Mendelian randomization study with a binary disease outcome the bias associated with estimating the phenotype-disease log odds ratio may be of practical importance and so estimates should be subject to a sensitivity analysis against different amounts of hypothesized confounding.

Leukotrienes are implicated in the pathogenesis of coronary artery disease. Recently two haplotypes (HapA and HapB) in the gene encoding ALOX5AP (arachidonate 5-lipoxygenase-activating protein), the main regulator of 5-lipoxygenase, have been associated with a doubling of the risk of myocardial infarction. Studies have also shown that treatment with a leukotriene inhibitor reduces biomarkers of coronary risk in patients carrying HapA, raising the possibility of developing genotype-specific therapy. In the present study, we examined whether carriage of HapA or HapB is associated with increased LTB(4) (leukotriene B(4)) production in healthy subjects. Age- and gender-matched healthy HapA carriers (n=21), HapB carriers (n=20) and non-A/non-B carriers (n=18), with no reported history of cardiovascular disease, were recruited following DNA screening of 1268 subjects from a population-based study. Blood neutrophils were isolated, and LTB(4) production was measured in response to stimulation with 1 mumol/l of the calcium ionophore A23187. There was no difference in the mean level for LTB(4) production in the three groups (non-A/non-B, 24.9+/-8.3 ng/10(6) cells; HapA, 22.2+/-11.9 ng/10(6) cells; HapB, 19.8+/-4.8 ng/10(6); P=0.14). The findings indicate that if either the HapA or the HapB haplotype of ALOX5AP indeed increases cardiovascular risk, then the mechanism is not simply due to a systematically observable effect of the haplotype on LTB(4) production in response to stimulation. The results suggest that knowledge of a patient's haplotype may not provide useful information on the probable clinical response to ALOX5AP inhibitors.

We aimed to investigate the causal effect of circulating uric acid concentrations on type 2 diabetes risk. A Mendelian randomization study was performed using a genetic score with 24 uric acid–associated loci. We used data of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study, comprising 24,265 individuals of European ancestry from eight European countries. During a mean (SD) follow-up of 10 (4) years, 10,576 verified incident case subjects with type 2 diabetes were ascertained. Higher uric acid was associated with a higher diabetes risk after adjustment for confounders, with a hazard ratio (HR) of 1.20 (95% CI 1.11, 1.30) per 59.48 µmol/L (1 mg/dL) uric acid. The genetic score raised uric acid by 17 µmol/L (95% CI 15, 18) per SD increase and explained 4% of uric acid variation. By using the genetic score to estimate the unconfounded effect, we found that a 59.48 µmol/L higher uric acid concentration did not have a causal effect on diabetes (HR 1.01 [95% CI 0.87, 1.16]). Including data from the Diabetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, increasing our dataset to 41,508 case subjects with diabetes, the summary odds ratio estimate was 0.99 (95% CI 0.92, 1.06). In conclusion, our study does not support a causal effect of circulating uric acid on diabetes risk. Uric acid–lowering therapies may therefore not be beneficial in reducing diabetes risk.

Design of new antenna mount with low effective projected area (EPA) and high load carrying capacity for telecommunication towers is discussed in this paper. The main aim is to reduce the EPA of the mount against the wind pressure direction at the desired elevation from ground by reducing the mount frame structure parts compared to the previous mount designs used in the market. The model in itself has to withstand its dead weight, operator’s weight along with five antenna-radio units. The new model has been designed with a single horizontal frame and four supporting structure for EPA reduction and also the EPA is calculated through Image Processing using MATLAB tool which has not been done previously for mounting structures in the telecommunication field. The preliminary stress and deformation results calculated using ANSYS 15.0 tool and future work that has to be carried out for the design are also discussed in this paper.Copyright © 2015 by ASME

BackgroundYoung people living with long term conditions are vulnerable to health service disengagement. This endangers their long term health. Studies report requests for digital forms of communication – email, text, social media – with their health care team. Digital clinical communication is troublesome for the UK NHS.AimIn this article we aim to present the research protocol for evaluating the impacts and outcomes of digital clinical communications for young people living with long term conditions and provide critical analysis of their use, monitoring and evaluation by NHS providers (LYNC study: Long term conditions, Young people, Networked Communications).MethodsThe research involves: (a) patient and public involvement activities with 16–24 year olds with and without long term health conditions; (b) six literature reviews; (c) case studies – the main empirical part of the study – and (d) synthesis and a consensus meeting. Case studies use a mixed methods design. Interviews and non-participant observation of practitioners and patients communicating in up to 20 specialist clinical settings will be combined with data, aggregated at the case level (non-identifiable patient data) on a range of clinical outcomes meaningful within the case and across cases. We will describe the use of digital clinical communication from the perspective of patients, clinical staff, support staff and managers, interviewing up to 15 young people and 15 staff per case study. Outcome data includes emergency admissions, A&E attendance and DNA (did not attend) rates. Case studies will be analysed to understand impacts of digital clinical communication on patient health outcomes, health care costs and consumption, ethics and patient safety.

Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI).Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis.Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data.Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide confidence intervals.

Background— The duration and exclusivity of breastfeeding in infancy have been inversely associated with future cardiometabolic risk. We investigated the effects of an experimental intervention to promote increased duration of exclusive breastfeeding on cardiometabolic risk factors in childhood. Methods and Results— We followed-up children in the Promotion of Breastfeeding Intervention Trial, a cluster-randomized trial of a breastfeeding promotion intervention based on the World Health Organization/United Nations Children’s Fund Baby-Friendly Hospital Initiative. In 1996 to 1997, 17 046 breastfeeding mother-infant pairs were enrolled from 31 Belarusian maternity hospitals and affiliated polyclinics (16 intervention versus 15 control sites); 13 879 (81.4%) children were followed up at 11.5 years, with 13 616 (79.9%) who had fasted and did not have diabetes mellitus. The outcomes were blood pressure; fasting insulin, adiponectin, glucose, and apolipoprotein A1; and the presence of metabolic syndrome. Analysis was by intention to treat, accounting for clustering within hospitals/clinics. The intervention substantially increased breastfeeding duration and exclusivity in comparison with the control arm (43% versus 6% and 7.9% versus 0.6% exclusively breastfed at 3 and 6 months, respectively). Cluster-adjusted mean differences at 11.5 years between experimental versus control groups were as follows: 1.0 mm Hg (95% confidence interval, −1.1 to 3.1) for systolic and 0.8 mm Hg (−0.6 to 2.3) for diastolic blood pressure; −0.1 mmol/L (−0.2 to 0.1) for glucose; 8% (−3% to 34%) for insulin; −0.3 μg/mL (−1.5 to 0.9) for adiponectin; and 0.0 g/L (−0.1 to 0.1) for apolipoprotein A1. The cluster-adjusted odds ratio for metabolic syndrome, comparing experimental versus control groups, was 1.21 (0.85 to 1.72). Conclusions— An intervention to improve breastfeeding duration and exclusivity among healthy term infants did not influence cardiometabolic risk factors in childhood. Clinical Trial Registration— Current Controlled Trials: ISRCTN37687716 ( http://www.controlled-trials.com/ISRCTN37687716 ). URL: http://clinicaltrials.gov . Unique identifier: NCT01561612.

Although family studies have shown that male lower urinary tract symptoms (LUTS) are highly heritable, no systematic review exists of genetic polymorphisms tested for association with LUTS.To systematically review and meta-analyze studies assessing candidate polymorphisms/genes tested for an association with LUTS, and to assess the strength, consistency, and potential for bias among pooled associations.A systematic search of the PubMed and HuGE databases as well as abstracts of major urologic meetings was performed through to January 2013. Case-control studies reporting genetic associations in men with LUTS were included. Reviewers independently and in duplicate screened titles, abstracts, and full texts to determine eligibility, abstracted data, and assessed the credibility of pooled associations according to the interim Venice criteria. Authors were contacted for clarifications if needed. Meta-analyses were performed for variants assessed in more than two studies.We identified 74 eligible studies containing data on 70 different genes. A total of 35 meta-analyses were performed with statistical significance in five (ACE, ELAC2, GSTM1, TERT, and VDR). The heterogeneity was high in three of these meta-analyses. The rs731236 variant of the vitamin D receptor had a protective effect for LUTS (odds ratio: 0.64; 95% confidence interval, 0.49-0.83) with moderate heterogeneity (I(2)=27.2%). No evidence for publication bias was identified. Limitations include wide-ranging phenotype definitions for LUTS and limited power in most meta-analyses to detect smaller effect sizes.Few putative genetic risk variants have been reliably replicated across populations. We found consistent evidence of a reduced risk of LUTS associated with the common rs731236 variant of the vitamin D receptor gene in our meta-analyses.Combining the results from all previous studies of genetic variants that may cause urinary symptoms in men, we found significant variants in five genes. Only one, a variant of the vitamin D receptor, was consistently protective across different populations.

Objectives:\ud This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease.\ud \ud Background:\ud Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy.\ud \ud Methods:\ud We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable.\ud \ud Results:\ud PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE.\ud \ud Conclusions:\ud Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.

Objectives: To assess the associations between both uric acid levels and hyperuricaemia, with ischaemic heart disease and blood pressure, and to explore the potentially confounding role of body mass index.\ud Design: Mendelian randomisation analysis, using variation at specific genes (SLC2A9 (rs7442295) as an instrument for uric acid; and FTO (rs9939609), MC4R (rs17782313), and TMEM18 (rs6548238) for body mass index).\ud Setting: Two large, prospective cohort studies in Denmark.\ud Participants: We measured levels of uric acid and related covariables in 58 072 participants from the Copenhagen General Population Study and 10 602 from the Copenhagen City Heart Study, comprising 4890 and 2282 cases of ischaemic heart disease, respectively.\ud Main outcome: Blood pressure and prospectively assessed ischaemic heart disease.\ud Results: Estimates confirmed known observational associations between plasma uric acid and hyperuricaemia with risk of ischaemic heart disease and diastolic and systolic blood pressure. However, when using genotypic instruments for uric acid and hyperuricaemia, we saw no evidence for causal associations between uric acid, ischaemic heart disease, and blood pressure. We used genetic instruments to investigate body mass index as a potentially confounding factor in observational associations, and saw a causal effect on uric acid levels. Every four unit increase of body mass index saw a rise in uric acid of 0.03 mmol/L (95% confidence interval 0.02 to 0.04), and an increase in risk of hyperuricaemia of 7.5% (3.9% to 11.1%).\ud Conclusion: By contrast with observational findings, there is no strong evidence for causal associations between uric acid and ischaemic heart disease or blood pressure. However, evidence supports a causal effect between body mass index and uric acid level and hyperuricaemia. This finding strongly suggests body mass index as a confounder in observational associations, and suggests a role for elevated body mass index or obesity in the development of uric acid related conditions.

Kari Tikkinen*, Hamilton, Canada; Rufus Cartwright, London, United Kingdom; Anna Kirby, San Diego, CA; Altaf Mangera, Sheffield, United Kingdom; Gans Thiagamoorthy, London, United Kingdom; Prabhakar Rajan, Glasgow, United Kingdom; Jori Pesonen, Tampere, Finland; Tom Palmer, Bristol, United Kingdom; Chris Ambrose, Vik Khullar, Andrew Walley, Marjo-Riitta Jarvelin, Phillip Bennett, London, United Kingdom; Chris Chapple, Sheffield, United Kingdom

Anna Kirby*, San Diego, CA; Rufus Cartwright, London, United Kingdom; Kari Tikkinen, Hamilton, Canada; Tom Palmer, Bristol, United Kingdom; Gans Thiagamoorthy, London, United Kingdom; Prabhakar Rajan, Glasgow, United Kingdom; Jori Pesonen, Tampere, Finland; Andrew Walley, London, United Kingdom; Altaf Mangera, Sheffield, United Kingdom; Georgios Grigoriadis, Chris Ambrose, Marjo-Riitta Jarvelin, Phillip Bennett, London, United Kingdom; Chris Chapple, Sheffield, United Kingdom; Vik Khullar, London, United Kingdom

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 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

BACKGROUND: Two single-nucleotide polymorphisms, rs1051730 and rs16969968, located within the nicotinic acetylcholine receptor gene cluster on chromosome 15q25 locus, are associated with heaviness of smoking, risk for lung cancer, and other smoking-related health outcomes. Previous studies have typically relied on self-reported smoking behavior, which may not fully capture interindividual variation in tobacco exposure. METHODS: We investigated the association of rs1051730 and rs16969968 genotype (referred to as rs1051730-rs16969968, because these are in perfect linkage disequilibrium and interchangeable) with both self-reported daily cigarette consumption and biochemically measured plasma or serum cotinine levels among cigarette smokers. Summary estimates and descriptive statistical data for 12 364 subjects were obtained from six independent studies, and 2932 smokers were included in the analyses. Linear regression was used to calculate the per-allele association of rs1051730-rs16969968 genotype with cigarette consumption and cotinine levels in current smokers for each study. Meta-analysis of per-allele associations was conducted using a random effects method. The likely resulting association between genotype and lung cancer risk was assessed using published data on the association between cotinine levels and lung cancer risk. All statistical tests were two-sided. RESULTS: Pooled per-allele associations showed that current smokers with one or two copies of the rs1051730-rs16969968 risk allele had increased self-reported cigarette consumption (mean increase in unadjusted number of cigarettes per day per allele = 1.0 cigarette, 95% confidence interval [CI] = 0.57 to 1.43 cigarettes, P = 5.22 × 10(-6)) and cotinine levels (mean increase in unadjusted cotinine levels per allele = 138.72 nmol/L, 95% CI = 97.91 to 179.53 nmol/L, P = 2.71 × 10(-11)). The increase in cotinine levels indicated an increased risk of lung cancer with each additional copy of the rs1051730-rs16969968 risk allele (per-allele odds ratio = 1.31, 95% CI = 1.21 to 1.42). CONCLUSIONS: Our data show a stronger association of rs1051730-rs16969968 genotype with objective measures of tobacco exposure compared with self-reported cigarette consumption. The association of these variants with lung cancer risk is likely to be mediated largely, if not wholly, via tobacco exposure.

Instrumental variables analysis using genetic markers as instruments is now a widely used technique in epidemiology and biostatistics. As single markers tend to explain only a small proportion of phenotypic variation, there is increasing interest in using multiple genetic markers to obtain more precise estimates of causal parameters. Structural mean models (SMMs) are semiparametric models that use instrumental variables to identify causal parameters. Recently, interest has started to focus on using these models with multiple instruments, particularly for multiplicative and logistic SMMs. In this paper we show how additive, multiplicative and logistic SMMs with multiple orthogonal binary instrumental variables can be estimated efficiently in models with no further (continuous) covariates, using the generalised method of moments (GMM) estimator. We discuss how the Hansen J-test can be used to test for model misspecification, and how standard GMM software routines can be used to fit SMMs. We further show that multiplicative SMMs, like the additive SMM, identify a weighted average of local causal effects if selection is monotonic. We use these methods to reanalyse a study of the relationship between adiposity and hypertension using SMMs with two genetic markers as instruments for adiposity. We find strong effects of adiposity on hypertension., Comment: Published at http://dx.doi.org/10.1214/14-STS503 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Vitamin D deficiency has been associated with several common diseases, including cancer and is being investigated as a possible risk factor for these conditions. We reported the striking prevalence of vitamin D deficiency in Scotland. Previous epidemiological studies have reported an association between low dietary vitamin D and colorectal cancer (CRC). Using a case-control study design, we tested the association between plasma 25-hydroxy-vitamin D (25-OHD) and CRC (2,001 cases, 2,237 controls). To determine whether plasma 25-OHD levels are causally linked to CRC risk, we applied the control function instrumental variable (IV) method of the mendelian randomization (MR) approach using four single nucleotide polymorphisms (rs2282679, rs12785878, rs10741657, rs6013897) previously shown to be associated with plasma 25-OHD. Low plasma 25-OHD levels were associated with CRC risk in the crude model (odds ratio (OR): 0.76, 95% Confidence Interval (CI): 0.71, 0.81, p: 1.4×10(-14)) and after adjusting for age, sex and other confounding factors. Using an allele score that combined all four SNPs as the IV, the estimated causal effect was OR 1.16 (95% CI 0.60, 2.23), whilst it was 0.94 (95% CI 0.46, 1.91) and 0.93 (0.53, 1.63) when using an upstream (rs12785878, rs10741657) and a downstream allele score (rs2282679, rs6013897), respectively. 25-OHD levels were inversely associated with CRC risk, in agreement with recent meta-analyses. The fact that this finding was not replicated when the MR approach was employed might be due to weak instruments, giving low power to demonstrate an effect (

In this talk we describe how to fit structural mean models (SMMs), as proposed by Robins, using instrumental variables in the generalized method of moments (GMM) framework using Stata's gmm command. The GMM approach is flexible because it can fit overidentified models in which there are more instruments than endogenous variables. It also allows assessment of the joint validity of the instruments using Hansen's J test through Stata's estat overid gmm postestimation command. In the case of the logistic SMM, the approach also allows different first-stage association models. We show the relationship between the multiplicative SMM and the multiplicative GMM estimator implemented in the ivpois command of Nichols (2007). For the multiplicative SMM, we show—analogously to Imbens and Angrist (1994) for the linear case--that the estimate is a weighted average of local estimates using the instruments separately. To demonstrate the models, we use a Mendelian randomization example, in which genotypes found to be robustly associated with risk factors from genome-wide association studies are used as instrumental variables, thereby investigating the effect of being overweight on the risk of hypertension in the Copenhagen General Population Study.

In this paper, the authors describe different instrumental variable (IV) estimators of causal risk ratios and odds ratios with particular attention to methods that can handle continuously measured exposures. The authors present this discussion in the context of a Mendelian randomization analysis of the effect of body mass index (BMI; weight (kg)/height (m)(2)) on the risk of asthma at age 7 years (Avon Longitudinal Study of Parents and Children, 1991-1992). The authors show that the multiplicative structural mean model (MSMM) and the multiplicative generalized method of moments (MGMM) estimator produce identical estimates of the causal risk ratio. In the example, MSMM and MGMM estimates suggested an inverse relation between BMI and asthma but other IV estimates suggested a positive relation, although all estimates had wide confidence intervals. An interaction between the associations of BMI and fat mass and obesity-associated (FTO) genotype with asthma explained the different directions of the different estimates, and a simulation study supported the observation that MSMM/MGMM estimators are negatively correlated with the other estimators when such an interaction is present. The authors conclude that point estimates from various IV methods can differ in practical applications. Based on the theoretical properties of the estimators, structural mean models make weaker assumptions than other IV estimators and can therefore be expected to be consistent in a wider range of situations.

Growth models are commonly used in life course epidemiology to describe growth trajectories and their determinants or to relate particular patterns of change to later health outcomes. However, methods to analyse relationships between two or more change processes occurring in parallel, in particular to assess evidence for causal influences of change in one variable on subsequent changes in another, are less developed. We discuss linear spline multilevel models with a multivariate response and show how these can be used to relate rates of change in a particular time period in one variable to later rates of change in another variable by using the variances and covariances of individual-level random effects for each of the splines. We describe how regression coefficients can be calculated for these associations and how these can be adjusted for other parameters such as random effect variables relating to baseline values or rates of change in earlier time periods, and compare different methods for calculating the standard errors of these regression coefficients. We also show that these models can equivalently be fitted in the structural equation modelling framework and apply each method to weight and mean arterial pressure changes during pregnancy, obtaining similar results for multilevel and structural equation models. This method improves on the multivariate linear growth models, which have been used previously to model parallel processes because it enables nonlinear patterns of change to be modelled and the temporal sequence of multivariate changes to be determined, with adjustment for change in earlier time periods. Copyright © 2012 John Wiley & Sons, Ltd.

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

Objective To assess the performance of novel contour enhanced funnel plots and a regression based adjustment method to detect and adjust for publication biases. Design Secondary analysis of a published systematic literature review. Data sources Placebo controlled trials of antidepressants previously submitted to the US Food and Drug Administration (FDA) and matching journal publications. Methods Publication biases were identified using novel contour enhanced funnel plots, a regression based adjustment method, Egger’s test, and the trim and fill method. Results were compared with a meta-analysis of the gold standard data submitted to the FDA. Results Severe asymmetry was observed in the contour enhanced funnel plot that appeared to be heavily influenced by the statistical significance of results, suggesting publication biases as the cause of the asymmetry. Applying the regression based adjustment method to the journal data produced a similar pooled effect to that observed by a meta-analysis of the FDA data. Contrasting journal and FDA results suggested that, in addition to other deviations from study protocol, switching from an intention to treat analysis to a per protocol one would contribute to the observed discrepancies between the journal and FDA results. Conclusion Novel contour enhanced funnel plots and a regression based adjustment method worked convincingly and might have an important part to play in combating publication biases.

WNK1 gene variants have been associated with adult blood pressure. We aimed to investigate relationships between WNK1 variants and blood pressure, as well as blood pressure change with age, in a longitudinal childhood study. Associations between single nucleotide polymorphisms in WNK1 and blood pressure and the rate of blood pressure change between 7 and 11 years were examined in the Avon Longitudinal Study of Parent and Children Study (n=5326 for systolic blood pressure at 11 years). We observed associations ( P P =0.0054). No associations were shown with the systolic blood pressure gradient. At age 11 years, 30 polymorphisms showed association ( P P WNK1 variants are associated with diastolic blood pressure gradient from 7 to 11 years and with systolic blood pressure at 11 years. Our study suggests that previously reported effects of WNK1 variants on blood pressure are mediated via effects on the gradient of blood pressure change with age.