David A. Leon

BACKGROUND: High body-mass index (BMI) predisposes to several site-specific cancers, but a large-scale systematic and detailed characterisation of patterns of risk across all common cancers adjusted for potential confounders has not previously been undertaken. We aimed to investigate the links between BMI and the most common site-specific cancers. METHODS: With primary care data from individuals in the Clinical Practice Research Datalink with BMI data, we fitted Cox models to investigate associations between BMI and 22 of the most common cancers, adjusting for potential confounders. We fitted linear then non-linear (spline) models; investigated effect modification by sex, menopausal status, smoking, and age; and calculated population effects. FINDINGS: 5·24 million individuals were included; 166,955 developed cancers of interest. BMI was associated with 17 of 22 cancers, but effects varied substantially by site. Each 5 kg/m(2) increase in BMI was roughly linearly associated with cancers of the uterus (hazard ratio [HR] 1·62, 99% CI 1·56-1·69; p<0·0001), gallbladder (1·31, 1·12-1·52; p<0·0001), kidney (1·25, 1·17-1·33; p<0·0001), cervix (1·10, 1·03-1·17; p=0·00035), thyroid (1·09, 1·00-1·19; p=0·0088), and leukaemia (1·09, 1·05-1·13; p≤0·0001). BMI was positively associated with liver (1·19, 1·12-1·27), colon (1·10, 1·07-1·13), ovarian (1·09, 1.04-1.14), and postmenopausal breast cancers (1·05, 1·03-1·07) overall (all p<0·0001), but these effects varied by underlying BMI or individual-level characteristics. We estimated inverse associations with prostate and premenopausal breast cancer risk, both overall (prostate 0·98, 0·95-1·00; premenopausal breast cancer 0·89, 0·86-0·92) and in never-smokers (prostate 0·96, 0·93-0·99; premenopausal breast cancer 0·89, 0·85-0·94). By contrast, for lung and oral cavity cancer, we observed no association in never smokers (lung 0·99, 0·93-1·05; oral cavity 1·07, 0·91-1·26): inverse associations overall were driven by current smokers and ex-smokers, probably because of residual confounding by smoking amount. Assuming causality, 41% of uterine and 10% or more of gallbladder, kidney, liver, and colon cancers could be attributable to excess weight. We estimated that a 1 kg/m(2) population-wide increase in BMI would result in 3790 additional annual UK patients developing one of the ten cancers positively associated with BMI. INTERPRETATION: BMI is associated with cancer risk, with substantial population-level effects. The heterogeneity in the effects suggests that different mechanisms are associated with different cancer sites and different patient subgroups. FUNDING: National Institute for Health Research, Wellcome Trust, and Medical Research Council.

BackgroundBMI is known to be strongly associated with all-cause mortality, but few studies have been large enough to reliably examine associations between BMI and a comprehensive range of cause-specific mortality outcomes.MethodsIn this population-based cohort study, we used UK primary care data from the Clinical Practice Research Datalink (CPRD) linked to national mortality registration data and fitted adjusted Cox regression models to examine associations between BMI and all-cause mortality, and between BMI and a comprehensive range of cause-specific mortality outcomes (recorded by International Classification of Diseases, 10th revision [ICD-10] codes). We included all individuals with BMI data collected at age 16 years and older and with subsequent follow-up time available. Follow-up began at whichever was the latest of: start of CPRD research-standard follow up, the 5-year anniversary of the first BMI record, or on Jan 1, 1998 (start date for death registration data); follow-up ended at death or on March 8, 2016. Fully adjusted models were stratified by sex and adjusted for baseline age, smoking, alcohol use, diabetes, index of multiple deprivation, and calendar period. Models were fitted in both never-smokers only and the full study population. We also did an extensive range of sensitivity analyses. The expected age of death for men and women aged 40 years at baseline, by BMI category, was estimated from a Poisson model including BMI, age, and sex.Findings3 632 674 people were included in the full study population; the following results are from the analysis of never-smokers, which comprised 1 969 648 people and 188 057 deaths. BMI had a J-shaped association with overall mortality; the estimated hazard ratio per 5 kg/m2 increase in BMI was 0·81 (95% CI 0·80–0·82) below 25 kg/m2 and 1·21 (1·20–1·22) above this point. BMI was associated with all cause of death categories except for transport-related accidents, but the shape of the association varied. Most causes, including cancer, cardiovascular diseases, and respiratory diseases, had a J-shaped association with BMI, with lowest risk occurring in the range 21–25 kg/m2. For mental and behavioural, neurological, and accidental (non-transport-related) causes, BMI was inversely associated with mortality up to 24–27 kg/m2, with little association at higher BMIs; for deaths from self-harm or interpersonal violence, an inverse linear association was observed. Associations between BMI and mortality were stronger at younger ages than at older ages, and the BMI associated with lowest mortality risk was higher in older individuals than in younger individuals. Compared with individuals of healthy weight (BMI 18·5–24·9 kg/m2), life expectancy from age 40 years was 4·2 years shorter in obese (BMI ≥30·0 kg/m2) men and 3·5 years shorter in obese women, and 4·3 years shorter in underweight (BMI <18·5 kg/m2) men and 4·5 years shorter in underweight women. When smokers were included in analyses, results for most causes of death were broadly similar, although marginally stronger associations were seen among people with lower BMI, suggesting slight residual confounding by smoking.InterpretationBMI had J-shaped associations with overall mortality and most specific causes of death; for mental and behavioural, neurological, and external causes, lower BMI was associated with increased mortality risk.FundingWellcome Trust.

CONTEXT: Low birth weight is implicated as a risk factor for type 2 diabetes. However, the strength, consistency, independence, and shape of the association have not been systematically examined. OBJECTIVE: To conduct a quantitative systematic review examining published evidence on the association of birth weight and type 2 diabetes in adults. DATA SOURCES AND STUDY SELECTION: Relevant studies published by June 2008 were identified through literature searches using EMBASE (from 1980), MEDLINE (from 1950), and Web of Science (from 1980), with a combination of text words and Medical Subject Headings. Studies with either quantitative or qualitative estimates of the association between birth weight and type 2 diabetes were included. DATA EXTRACTION: Estimates of association (odds ratio [OR] per kilogram of increase in birth weight) were obtained from authors or from published reports in models that allowed the effects of adjustment (for body mass index and socioeconomic status) and the effects of exclusion (for macrosomia and maternal diabetes) to be examined. Estimates were pooled using random-effects models, allowing for the possibility that true associations differed between populations. DATA SYNTHESIS: Of 327 reports identified, 31 were found to be relevant. Data were obtained from 30 of these reports (31 populations; 6090 diabetes cases; 152 084 individuals). Inverse birth weight-type 2 diabetes associations were observed in 23 populations (9 of which were statistically significant) and positive associations were found in 8 (2 of which were statistically significant). Appreciable heterogeneity between populations (I(2) = 66%; 95% confidence interval [CI], 51%-77%) was largely explained by positive associations in 2 native North American populations with high prevalences of maternal diabetes and in 1 other population of young adults. In the remaining 28 populations, the pooled OR of type 2 diabetes, adjusted for age and sex, was 0.75 (95% CI, 0.70-0.81) per kilogram. The shape of the birth weight-type 2 diabetes association was strongly graded, particularly at birth weights of 3 kg or less. Adjustment for current body mass index slightly strengthened the association (OR, 0.76 [95% CI, 0.70-0.82] before adjustment and 0.70 [95% CI, 0.65-0.76] after adjustment). Adjustment for socioeconomic status did not materially affect the association (OR, 0.77 [95% CI, 0.70-0.84] before adjustment and 0.78 [95% CI, 0.72-0.84] after adjustment). There was no strong evidence of publication or small study bias. CONCLUSION: In most populations studied, birth weight was inversely related to type 2 diabetes risk.

OBJECTIVE: To establish whether fetal growth rate (as distinct from size at birth) is associated with mortality from ischaemic heart disease. DESIGN: Cohort study based on uniquely detailed obstetric records with 97% follow up over the entire life course and linkage to census data in adult life. SUBJECTS: All 14 611 babies delivered at the Uppsala Academic Hospital, Sweden, during 1915-29 followed up to end of 1995. MAIN OUTCOME MEASURES: Mortality from ischaemic heart disease and other causes. RESULTS: Cardiovascular disease showed an inverse association with birth weight for both men and women, although this was significant only for men. In men a 1000 g increase in birth weight was associated with a proportional reduction in the rate of ischaemic heart disease of 0.77 (95% confidence interval 0.67 to 0.90). Adjustment for socioeconomic circumstances at birth and in adult life led to slight attenuation of this effect. Relative to the lowest fourth of birth weight for gestational age, mortality from ischaemic heart disease in men in the second, third, and fourth fourths was 0.81 (0.66 to 0.98), 0.63 (0.50 to 0.78), and 0.67 (0.54 to 0.82), respectively. The inclusion of birth weight per se and birth weight for gestational age in the same model strengthened the association with birth weight for gestational age but removed the association with birth weight. CONCLUSION: This study provides by far the most persuasive evidence of a real association between size at birth and mortality from ischaemic heart disease in men, which cannot be explained by methodological artefact or socioeconomic confounding. It strongly suggests that it is variation in fetal growth rate rather than size at birth that is aetiologically important.