Consistent but indirect evidence has implicated genetic factors in smoking behavior1,2. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], β = 1.03, standard error (s.e.) = 0.053, P = 2.8 × 10−73). Two 10q25 SNPs (rs1329650[G], β = 0.367, s.e. = 0.059, P = 5.7 × 10−10; and rs1028936[A], β = 0.446, s.e. = 0.074, P = 1.3 × 10−9) and one 9q13 SNP in EGLN2 (rs3733829[G], β = 0.333, s.e. = 0.058, P = 1.0 × 10−8) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04–1.08, P = 1.8 × 10−8). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08–1.18, P = 3.6 × 10−8) was significantly associated with smoking cessation.

In epidemiological studies it is often necessary to disentangle the pathways that link an exposure to an outcome. Typically the aim is to identify the total effect of the exposure on the outcome, the effect of the exposure that acts through a given set of mediators of interest (indirect effect) and the effect of the exposure unexplained by those same mediators (direct effect). The traditional approach to mediation analysis is based on adjusting for the mediator in standard regression models to estimate the direct effect. However, several methodological papers have shown that under a number of circumstances this traditional approach may produce flawed conclusions. Through a better understanding of the causal structure of the variables involved in the analysis, with a formal definition of direct and indirect effects in a counterfactual framework, alternative analytical methods have been introduced to improve the validity and interpretation of mediation analysis. In this paper, we review and discuss the impact of the three main sources of potential bias in the traditional approach to mediation analyses: (i) mediator-outcome confounding;(ii) exposure-mediator interaction and (iii) mediator-outcome confounding affected by the exposure. We provide examples and discuss the impact these sources have in terms of bias.

Lung cancer is mainly caused by smoking, but the quantitative relations between smoking and histologic subtypes of lung cancer remain inconclusive. Using one of the largest lung cancer datasets ever assembled, we explored the impact of smoking on risks of the major cell types of lung cancer. This pooled analysis included 13,169 cases and 16,010 controls from Europe and Canada. Studies with population controls comprised 66.5% of the subjects. Adenocarcinoma (AdCa) was the most prevalent subtype in never smokers and in women. Squamous cell carcinoma (SqCC) predominated in male smokers. Age-adjusted odds ratios (ORs) were estimated with logistic regression. ORs were elevated for all metrics of exposure to cigarette smoke and were higher for SqCC and small cell lung cancer (SCLC) than for AdCa. Current male smokers with an average daily dose of >30 cigarettes had ORs of 103.5 (95% CI 74.8-143.2) for SqCC, 111.3 (95% CI 69.8-177.5) for SCLC, and 21.9 (95% CI 16.6-29.0) for AdCa. In women, the corresponding ORs were 62.7 (95% CI 31.5-124.6), 108.6 (95% CI 50.7-232.8), and 16.8 (95% CI 9.2-30.6), respectively. Whereas ORs started to decline soon after quitting, they did not fully return to the baseline risk of never smokers even 35 years after cessation. The major result that smoking exerted a steeper risk gradient on SqCC and SCLC than on AdCa is in line with previous population data and biological understanding of lung cancer development.

Obesity is one of the biggest challenges facing global reproductive health. Women in the UK and USA are today more likely to be obese or overweight at booking than normal weight, and many low-and middle-income countries (LMICs) seem destined to follow suit (Poston et al. Lancet Diabetes Endocrinol 2016;4:1025-36). Understanding how, and to what extent, maternal body mass index (BMI) and weight gain during pregnancy contribute to adverse outcomes for mothers and their offspring is therefore vital to informing future health policy.In an individual participant data meta-analysis of over 265 000 births, Santos et al. (BJOG 2019;126:984-95) confirm strong correlations between pre-pregnancy maternal BMI and the risks of gestational hypertension, preeclampsia and gestational diabetes. Over one-third of such complications in the study population were considered attributable to maternal overweight and obesity. The risk of large size for gestational age (LGA) at birth increased similarly across all categories of pre-pregnancy BMI and gestational weight gain, although these data should be interpreted in the context of a continuing debate regarding the customisation of fetal growth charts. It remains uncertain how maternal height and weight influence fetal growth potential, and whether LGA babies born to mothers who are obese or mothers with excessive weight gain carry the same short-and long-term health risks as LGA babies born to mothers who are normal weight. Preterm birth was also more common among women who are obese and past literature has suggested that this association is strongest for extremely preterm delivery (Cnattingius et al. JAMA 2013;309:2362-70), whether spontaneous or iatrogenic.Whereas women who are obese or have high weight gain are consistently shown to be at greatest risk, there is clear evidence of a continuum of risk across the full BMI range, which is emphasised by the authors' use of population attributable risk (PAR). Notably, the overall burden of pregnancy complications is similar in overweight and obese groups (PAR 11.4 and 12.5%, respectively). This calls into question traditional models of care targeting women with a booking BMI above 30 kg/m 2 or even higher thresholds. Minimising gestational weight gain in these women ameliorates but does not remove the excess risk, and ultimately may have less impact on outcomes at a population level than previously hoped.The authors acknowledge that the data were derived from cohorts who were largely white; however, comparable findings have been reported in LMICs with varied ethnic populations (Rahman et al. Obes Rev 2015;16:758-70).Being healthy entails more than just not being obese, and the study also draws important attention to the risks of small size for gestational age and preterm birth, particularly amongst underweight women with inadequate weight gain during pregnancy. These findings strengthen the argument for novel public health approaches to optimise maternal health with a shift in focus towards pre-conception and interpregnancy intervent...

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BackgroundMaternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these effects differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact.Methods and findingsWe conducted an individual participant data meta-analysis of data from 162,129 mothers and their children from 37 pregnancy and birth cohort studies from Europe, North America, and Australia. We assessed the individual and combined associations of maternal pre-pregnancy BMI and gestational weight gain, both in clinical categories and across their full ranges, with the risks of overweight/obesity in early (2.0–5.0 years), mid (5.0–10.0 years) and late childhood (10.0–18.0 years), using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal sociodemographic and lifestyle-related characteristics. We observed that higher maternal pre-pregnancy BMI and gestational weight gain both in clinical categories and across their full ranges were associated with higher risks of childhood overweight/obesity, with the strongest effects in late childhood (odds ratios [ORs] for overweight/obesity in early, mid, and late childhood, respectively: OR 1.66 [95% CI: 1.56, 1.78], OR 1.91 [95% CI: 1.85, 1.98], and OR 2.28 [95% CI: 2.08, 2.50] for maternal overweight; OR 2.43 [95% CI: 2.24, 2.64], OR 3.12 [95% CI: 2.98, 3.27], and OR 4.47 [95% CI: 3.99, 5.23] for maternal obesity; and OR 1.39 [95% CI: 1.30, 1.49], OR 1.55 [95% CI: 1.49, 1.60], and OR 1.72 [95% CI: 1.56, 1.91] for excessive gestational weight gain). The proportions of childhood overweight/obesity prevalence attributable to maternal overweight, maternal obesity, and excessive gestational weight gain ranged from 10.2% to 21.6%. Relative to the effect of maternal BMI, excessive gestational weight gain only slightly increased the risk of childhood overweight/obesity within each clinical BMI category (p-values for interactions of maternal BMI with gestational weight gain: p = 0.038, p < 0.001, and p = 0.637 in early, mid, and late childhood, respectively). Limitations of this study include the self-report of maternal BMI and gestational weight gain for some of the cohorts, and the potential of residual confounding. Also, as this study only included participants from Europe, North America, and Australia, results need to be interpreted with caution with respect to other populations.ConclusionsIn this study, higher maternal pre-pregnancy BMI and gestational weight gain were associated with an increased risk of childhood overweight/obesity, with the strongest effects at later ages. The additional effect of gestational weight gain in women who are overweight or obese before pregnancy is small. Given the large po...

Background Undescended testis, which is a risk factor for testicular cancer, is usually treated surgically, but whether the age at treatment has any effect on the risk is unclear. We studied the relation between the age at treatment for undescended testis and the risk of testicular cancer. Methods We identified men who underwent orchiopexy for undescended testis in Sweden between 1964 and 1999. Cohort subjects were identified in the Swedish Hospital Discharge Register and followed for the occurrence of testicular cancer through the Swedish Cancer Registry. Vital statistics and data on migration status were taken from the Register of Population and Population Changes for the years 1965 through 2000. We estimated the relative risk of testicular cancer using Poisson regression of standardized incidence ratios, comparing the risk in the cohort with that in the general population. We also analyzed the data by means of Cox regression, using internal comparison groups. Results The cohort consisted of 16,983 men who were surgically treated for undescended testis and followed for a total of 209,984 person-years. We identified 56 cases of testicular cancer during follow-up. The relative risk of testicular cancer among those who underwent orchiopexy before reaching 13 years of age was 2.23 (95% confidence interval [CI], 1.58 to 3.06), as compared with the Swedish general population; for those treated at 13 years of age or older, the relative risk was 5.40 (95% CI, 3.20 to 8.53). The effect of age at orchiopexy on the risk of testicular cancer was similar in comparisons within the cohort. Conclusions Treatment for undescended testis before puberty decreases the risk of testicular cancer.

BackgroundPreterm birth, low birth weight, and infant catch-up growth seem associated with an increased risk of respiratory diseases in later life, but individual studies showed conflicting results.ObjectivesWe performed an individual participant data meta-analysis for 147,252 children of 31 birth cohort studies to determine the associations of birth and infant growth characteristics with the risks of preschool wheezing (1-4 years) and school-age asthma (5-10 years).MethodsFirst, we performed an adjusted 1-stage random-effect meta-analysis to assess the combined associations of gestational age, birth weight, and infant weight gain with childhood asthma. Second, we performed an adjusted 2-stage random-effect meta-analysis to assess the associations of preterm birth (gestational age <37 weeks) and low birth weight (<2500 g) with childhood asthma outcomes.ResultsYounger gestational age at birth and higher infant weight gain were independently associated with higher risks of preschool wheezing and school-age asthma (P < .05). The inverse associations of birth weight with childhood asthma were explained by gestational age at birth. Compared with term-born children with normal infant weight gain, we observed the highest risks of school-age asthma in children born preterm with high infant weight gain (odds ratio [OR], 4.47; 95% CI, 2.58-7.76). Preterm birth was positively associated with an increased risk of preschool wheezing (pooled odds ratio [pOR], 1.34; 95% CI, 1.25-1.43) and school-age asthma (pOR, 1.40; 95% CI, 1.18-1.67) independent of birth weight. Weaker effect estimates were observed for the associations of low birth weight adjusted for gestational age at birth with preschool wheezing (pOR, 1.10; 95% CI, 1.00-1.21) and school-age asthma (pOR, 1.13; 95% CI, 1.01-1.27).ConclusionYounger gestational age at birth and higher infant weight gain were associated with childhood asthma outcomes. The associations of lower birth weight with childhood asthma were largely explained by gestational age at birth.