Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5·24 million UK adults

Abstract

SummaryBackgroundHigh 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.MethodsWith 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.Findings5·24 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/m2 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/m2 population-wide increase in BMI would result in 3790 additional annual UK patients developing one of the ten cancers positively associated with BMI.InterpretationBMI 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.FundingNational Institute for Health Research, Wellcome Trust, and Medical Research Council.

Acute Pericarditis and Cancer Risk: A Matched Cohort Study Using Linked UK Primary and Secondary Care Data

“…We identified all cancers through medical codes from the CPRD medical dictionary related to cancer (mapped to ICD‐10 chapter 2 headings in a previous study8), and through ICD‐10 codes in the HES, and restricted to first occurrence of cancer. We estimated risk for any cancer combined and for 14 individual cancers; the site‐specific cancer outcomes chosen for analysis included the most common cancers and was further informed by findings from previously published data on pericarditis and cancer risk 4, 9, 10…”

“…We used body mass index (BMI) calculated directly from weight and height records (weight/height2) and created 4 categories: underweight (BMI <18.5), normal weight (BMI=18.5–24.9), overweight (BMI=25.0–29.9), and obesity (BMI >30), using World Health Organization (WHO) grouping of overweight and obesity. Details on processing, cleaning, and representativeness of CPRD BMI data have been previously described 8, 11. We categorized smoking status into never‐smoker, current smoker, and ex‐smoker, and similarly alcohol use into never‐use, current use, and ex‐use.…”

Insulin resistance and endometrial cancer risk: A systematic review and meta-analysis

“…Numerous epidemiological studies confirm an association between obesity and various cancer forms, including EC [9]. This malignancy has also been associated with sedentarism, type II diabetes mellitus, and polycystic ovary syndrome [10e14].…”

Association of Body Mass Index in Early Pregnancy and Perinatal Outcome among Mothers Attending a Maternity (Christian) Hospital in Berhampur, Odisha: A Hospital Based Prospective Study

“…Han et al in a systematic review and meta-analyses observed that that singletons born to underweight women have higher risks of preterm birth (overall, spontaneous and induced) and LBW than those born to women with normal weight (9) BMI provides a reliable indicator of body fat for most people and is used to screen for weight categories that may lead to problems (7) . It is an inexpensive and easy-to-perform method of screening for weight category, for example underweight, normal or healthy weight, overweight, and obesity (10) . The critical relevance of mothers nutritional status was emphasized by the fact that in all the EAG including Assam state, mothers who were underweight were more likely to have LBW babies than normal weight (11) .…”