George Davey Smith

Bio: George Davey Smith is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Mendelian randomization. The author has an hindex of 224, co-authored 2540 publications receiving 248373 citations. Previous affiliations of George Davey Smith include Keele University & Western Infirmary.

Is the Association Between Parity and Coronary Heart Disease Due to Biological Effects of Pregnancy or Adverse Lifestyle Risk Factors Associated With Child-Rearing? Findings From the British Women’s Heart and Health Study and the British Regional Heart Study

Abstract: Background— Parity is associated with coronary heart disease (CHD) risk. In the present study, we assessed the associations between number of children and CHD in both women and men. Methods and Results— A total of 4286 women and 4252 men aged 60 to 79 years from 24 British towns were studied. Number of children was positively associated with body mass index and waist-hip ratio in both sexes. In women but not in men, number of children was inversely associated with high-density lipoprotein cholesterol and was positively associated with triglycerides and diabetes. For both sexes, similar “J” shaped associations between number of children and CHD were observed, with the prevalence lowest among those with 2 children and increasing linearly with each additional child beyond 2. For those with at least 2 children, each additional child increased the age-adjusted odds of CHD by 30% (odds ratio, 1.30; 95% confidence interval, 1.17 to 1.44) for women and by 12% for men (odds ratio, 1.12; 95% confidence interval, 1....

Association between general and central adiposity in childhood, and change in these, with cardiovascular risk factors in adolescence: prospective cohort study

Abstract: Objectives To examine the prospective associations between body mass index (BMI), waist circumference, and fat mass in childhood and cardiovascular risk factors at age 15-16. Design Prospective cohort study. Setting Avon Longitudinal Study of Parents and Children. Participants 5235 children aged 9-12 at start of study. Main exposures BMI, waist circumference, and fat mass determined by dual energy x ray absorptiometry, assessed at age 9-12 and at age 15-16. Main outcome measures Systolic and diastolic blood pressure and concentrations of fasting glucose, insulin, triglycerides, low density lipoprotein cholesterol, and high density lipoprotein cholesterol assessed at age 15-16. Results In girls a 1 SD greater BMI at age 9-12 was associated with cardiovascular risk factors at age 15-16 in fully adjusted models: odds ratio 1.23 (95% confidence interval 1.10 to 1.38) for high systolic blood pressure (≥130 mm Hg); 1.19 (1.03 to 1.38) for high concentration of low density lipoprotein cholesterol (≥2.79 mmol/l); 1.43 (1.06 to 1.92) for high concentration of triglycerides (≥1.7 mmol/l); 1.25 (1.08 to 1.46) for low concentration of high density lipoprotein cholesterol ( 0.2 for heterogeneity). When waist circumference or fat mass or both were added to models including BMI they did not increase the variation in cardiovascular risk factors already explained by BMI and confounders alone. Girls who were overweight/obese at age 9-12 but were normal weight by 15-16 had similar odds of adverse levels of risk factors to those who were normal weight at both ages. In boys odds of high systolic blood pressure, high concentrations of triglycerides and insulin, and low concentrations of high density lipoprotein cholesterol remained higher in this group compared with those who were normal weight at both ages but were lower than in those who remained overweight/obese at both ages. Conclusions Measurements of waist circumference or directly assessed fat mass in childhood do not seem to be associated with cardiovascular risk factors in adolescence any more strongly than BMI. Girls who favourably alter their overweight status between childhood and adolescence have cardiovascular risk profiles broadly similar to those who were normal weight at both time points, but boys who change from overweight to normal show risk factor profiles intermediate between those seen in boys who are normal weight at both ages or overweight at both ages.

Obtaining sub-grid-scale information from coarse-resolution general circulation model output

Abstract: The relationships between local temperature and precipitation and large-scale climate are explored using regression analysis. The motivation for this study is the need of the impact analyst for small-scale information given only coarser resolution General Circulation Model output. The predictor variables employed are area averages (over ∼2.5 × 106 km2) of temperature and precipitation and propinquitous grid point values of mean sea level pressure and 700 mbar height, together with the zonal and meridional gradients of these two variables. Regression analyses are performed using monthly-mean data from Oregon, with separate analyses for each month. In independent verification, spatial-mean explained variances range from 58 to 87% for temperature and from 39 to 76% for precipitation. Most of the variance explained arises from the area average of the variable which is the predictand: in other words, if the temperature, say, at point x is to be estimated, the best predictor is generally the area average temperature. There are large spatial differences in the amount of local climate variance that can be explained by large-scale data. Examples are given which show how site-specific changes can differ markedly from those at the grid point scale.

Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults

Abstract: Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Alcohol consumption and mortality from all causes, coronary heart disease, and stroke: results from a prospective cohort study of Scottish men with 21 years of follow up

Abstract: Objectives: To relate alcohol consumption to mortality. Design: Prospective cohort study. Setting: 27 workplaces in the west of Scotland. Participants: 5766 men aged 35-64 when screened in 1970-3 who answered questions on their usual weekly alcohol consumption. Main outcome measures: Mortality from all causes, coronary heart disease, stroke, and alcohol related causes over 21 years of follow up related to units of alcohol consumed per week. Results: Risk for all cause mortality was similar for non-drinkers and men drinking up to 14 units a week. Mortality risk then showed a graded association with alcohol consumption (relative rate compared with non-drinkers 1.34 (95% confidence interval 1.14 to 1.58) for 15-21 units a week, 1.49 (1.27 to 1.75) for 22-34 units, 1.74 (1.47 to 2.06) for 35 or more units). Adjustment for risk factors attenuated the increased relative risks, but they remained significantly above 1 for men drinking 22 or more units a week. There was no strong relation between alcohol consumption and mortality from coronary heart disease after adjustment. A strong positive relation was seen between alcohol consumption and risk of mortality from stroke, with men drinking 35 or more units having double the risk of non-drinkers, even after adjustment. Conclusions: The overall association between alcohol consumption and mortality is unfavourable for men drinking over 22 units a week, and there is no clear evidence of any protective effect for men drinking less than this.

Measuring inconsistency in meta-analyses

Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

Bias in meta-analysis detected by a simple, graphical test

Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

Abstract: Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

Abstract: Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate