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.

Effects of promoting longer-term and exclusive breastfeeding on cardiometabolic risk factors at age 11.5 years: a cluster-randomized, controlled trial.

Abstract: 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...

Risk Factors for Pancreatic Cancer Mortality: Extended Follow-up of the Original Whitehall Study

Abstract: Given the well-established links between diabetes and elevated rates of pancreatic cancer, there are reasons to anticipate that other markers of metabolic abnormality (increased body mass index, plasma cholesterol, and blood pressure) and their correlates (physical activity and socioeconomic status) may also confer increased risk. However, to date, the results of a series of population-based cohort studies are inconclusive. We examined these associations in the original Whitehall cohort study of 17,898 men. A maximum of 38 years of follow-up gave rise to 163 deaths due to carcinoma of the pancreas. Although Poisson regression analyses confirmed established risk factor-disease associations for increasing age, smoking, and type II diabetes, there was essentially no evidence that body mass index (rate ratio, 1.01; 95% confidence interval per 1 SD increase, 0.86-1.18), plasma cholesterol (0.91; 0.78-1.07), diastolic blood pressure (0.93; 0.78-1.09), systolic blood pressure (0.98; 0.83-1.15), physical activity (sedentary versus high: 1.37; 0.89-2.12), or socioeconomic status [clerical (low) versus professional/executive, 0.95; 0.59-1.51] offered any predictive value for pancreatic cancer mortality. These results were unchanged following control for a range of covariates.

Could associations between breastfeeding and insulin-like growth factors underlie associations of breastfeeding with adult chronic disease? The Avon Longitudinal Study of Parents and Children

Abstract: Summary Objective The influence of infant feeding method (breast/formula) on growth factor levels could underlie associations of breastfeeding with childhood growth and risk factors for cardiovascular disease. We investigated associations of having been breastfed with serum IGF-I and IGFBP-3 in childhood. Methods Prospective birth cohort study (subsample of the Avon Longitudinal Study of Parents and Children, UK) based on 871 children born in 1991/1992 who underwent clinical follow-up and blood tests at age 7–8 years. A total of 488 (56%) children had complete data. Results In children with complete data, the age- and sex-standardized IGF-I levels of those who were partially or exclusively breastfed were 6·1 and 13·8 ng/ml higher, respectively, than those who were never breastfed (increase in IGF-I levels per category of breastfeeding exclusivity: 7·1 ng/ml; 95% CI: 0·3–13·9; P = 0·04). In models also controlling for birthweight, gestational age, mother's age, and socioeconomic and dietary factors, the breastfeeding–IGF-I association was attenuated (regression coefficient: 3·3 ng/ml; −4·2–10·7; P = 0·4); further adjustment for IGFBP-3 made little difference (regression coefficient: 4·1 ng/ml; −2·8–10·9; P = 0·2). There was little evidence for an association between breastfeeding and IGFBP-3 or the molar ratio IGF-I/IGFBP-3. Conclusions The positive association between breastfeeding and IGF-I could be due to residual confounding or to chance. Nevertheless, the magnitude of the fully adjusted effect estimate and the novelty of the association suggest that larger studies should now be conducted to confirm or refute the hypothesis that variations in IGF-I by infant feeding mode explain associations of breastfeeding with health in later life.

Osteoarthritis and bone mineral density: are strong bones bad for joints?

Abstract: Osteoarthritis (OA) is a common and disabling joint disorder affecting millions of people worldwide. In OA, pathological changes are seen in all of the joint tissues including bone. Although both cross-sectional and longitudinal epidemiological studies have consistently demonstrated an association between higher bone mineral density (BMD) and OA, suggesting that increased BMD is a risk factor for OA, the mechanisms underlying this observation remain unclear. Recently, novel approaches to examining the BMD-OA relationship have included studying the disease in individuals with extreme high bone mass, and analyses searching for genetic variants associated with both BMD variation and OA, suggesting possible pleiotropic effects on bone mass and OA risk. These studies have yielded valuable insights into potentially relevant pathways that might one day be exploited therapeutically. Although animal models have suggested that drugs reducing bone turnover (antiresorptives) may retard OA progression, it remains to be seen whether this approach will prove to be useful in human OA. Identifying individuals with a phenotype of OA predominantly driven by increased bone formation could help improve the overall response to these treatments. This review aims to summarise current knowledge regarding the complex relationship between BMD and OA.

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