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.

The distribution of substitutional alloying elements during the bainite transformation

Abstract: The behavior of substitutional alloying elements during and after the growth of upper bainite in Fe-Mn-Si-C and Fe-Mn-Si-C-Mo alloy steels has been examined using an atomic resolution microanalysis technique. From the results obtained, and judging from published data, it is concluded that manganese, nickel, silicon, chromium, and molybdenum do not redistribute during the growth of bainitic ferrite. Their concentrations are found to be uniform both at and in the vicinity of the transformation interface, with no indications of any segregation to the transformation interface during growth. However, prolonged annealing at the isothermal transformation temperature, after the formation of bainite has stopped, eventually stimulates the partitioning of substitutional alloying elements as the system tends toward equilibrium. The results demonstrate the existence of an atomic correspondence between the parent and product phases during transformation, the effect of substitutional alloying additions being manifestedvia a modification of the driving force for transformation.

Smoking and health promotion in Nazi Germany.

Abstract: Accepted December 1993 Accepted for publication January 1994 In his recent paper in this journal "A birth cohort analysis of the smoking epidemic in West Germany", Brenner1 presents data showing that smoking rates increased dramatically from the late 1920s onwards and that the reductions now being seen are limited to men with higher education. His conclusions are that intensified education programmes are required among teenagers, together with res trictive smoking policies at the workplace and on transportation systems. Brenner believes that the relatively limited progress made against smoking in Germany is due to the slow adoption of antismoking campaigns compared with other countries such as the USA. In this commentary we show that, contrary to these assertions, energetic antismoking campaigns were adopted in Germany at a very early stage. Indeed, all of the activities Brenner now com mends were vigorously implemented during the Nazi period in Germany, with, as he clearly demonstrates, little effect on stemming the growing tide.

Smoking during pregnancy and components of stature in offspring

Abstract: The objective of this study was to examine the association between maternal smoking during pregnancy and offspring height and its components. The analysis was based on 6,340 white singletons born in 1991-1992 and enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC), who had maternal smoking data recorded for at least one trimester in pregnancy, and who had their height recorded at age 7.5. Smoking at any time in pregnancy was associated with a reduction in offspring height, trunk, and leg length, and the leg-to-trunk ratio, after adjustment for age and sex. After additional adjustment for maternal factors, social factors, and breastfeeding, associations with leg length and leg-to-trunk ratio remained, with reductions of 0.25 cm (95% confidence interval, 0.05-0.46 cm) in leg length and 0.30% (95% confidence interval, 0.03-0.57%) in leg-to-trunk ratio if the mother smoked. Findings were similar when the smoking data were analyzed separately for each trimester. Furthermore, in each trimester, the more a mother smoked, the greater the reduction in offspring height, leg length, and leg-to-trunk ratio. These dose-response relationships remained after adjustment for all potential confounders for leg length and leg-to-trunk ratio. Smoking at any time in pregnancy reduces offspring height and its components, and in particular leg length and leg-to-trunk ratio at age 7.5.

Why do child mortality rates fall ? An analysis of the Nicaraguan experience

Abstract: A comprehensive review of available sources of mortality data was undertaken to document the changes that have occurred in infant mortality in Nicaragua over the last three decades. It was found that a rapid fall in infant mortality commenced in the early 1970s and has continued steadily since. Trends in several different factors which might have led to this breakthrough were examined including: income, nutrition, breastfeeding practices, maternal education, immunizations, access to health services, provision of water supplies and sanitation, and anti-malarial programs. Of these, improved access to health services appears to have been the most important factor. At a time when the number of hospital beds per capita was dropping, increasing numbers of health care professionals, particularly nurses, were becoming available to staff primary health care facilities built in the 1960s. These were provided at least partly in response to the growing political turmoil enveloping the nation at that time. Certain Nicaraguan cultural attributes may have added to the impact of the reforms. Efforts in the field of public health made since the 1979 insurrection appear to have maintained the decline in child mortality.

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