Summary 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/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. 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.
Although several clinical trials are now underway to test possible therapies, the worldwide response to the COVID-19 outbreak has been largely limited to monitoring/containment. We report here that ...Ivermectin, an FDA-approved anti-parasitic previously shown to have broad-spectrum anti-viral activity in vitro, is an inhibitor of the causative virus (SARS-CoV-2), with a single addition to Vero-hSLAM cells 2 h post infection with SARS-CoV-2 able to effect ~5000-fold reduction in viral RNA at 48 h. Ivermectin therefore warrants further investigation for possible benefits in humans.
•Ivermectin is an inhibitor of the COVID-19 causative virus (SARS-CoV-2) in vitro.•A single treatment able to effect ~5000-fold reduction in virus at 48 h in cell culture.•Ivermectin is FDA-approved for parasitic infections, and therefore has a potential for repurposing.•Ivermectin is widely available, due to its inclusion on the WHO model list of essential medicines.
BMI 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.
In 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.
3 632 674 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.
BMI 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.
Wellcome Trust.
Self-reported health (SRH) is widely used as an epidemiological instrument given the changes in public health since its introduction in the 1980s. We examined the association between SRH and ...mortality and how this is affected by time and health measurements in a prospective cohort study using repeated measurements and physical examinations of 11652 men and 12684 women in Tromsø, Norway. We used Cox proportional hazard regression to estimate hazard ratios (HRs) of death for SRH, controlling for pathology, biometrics, smoking, sex and age. SRH predicted mortality independently of other, more objective health measures. Higher SRH was strongly associated with lower mortality risk. Poor SRH had HR 2.51 (CI: 2.19, 2.88). SRH is affected by disease, mental health and other risk factors, but these factors had little impact on HRs (Poor SRH: HR 1.99; CI: 1.72, 2.31). SRH predicted mortality, but with a time-dependent effect. Time strongly affected the hazard ratio for mortality, especially after ten-year follow-up (Poor SRH HR 3.63 at 0-5 years decreased to HR 1.58 at 15-21 years). SRH has both methodological and clinical value. It should not be uncritically utilised as a replacement instrument when measures of physical illness and other objective health measures are lacking.
Ischaemic heart disease, stroke, and other cardiovascular diseases (CVDs) lead to 17.5 million deaths worldwide per year. Taking into account population ageing, CVD death rates are decreasing ...steadily both in regions with reliable trend data and globally. The declines in high-income countries and some Latin American countries have been ongoing for decades without slowing. These positive trends have broadly coincided with, and benefited from, declines in smoking and physiological risk factors, such as blood pressure and serum cholesterol levels. These declines have also coincided with, and benefited from, improvements in medical care, including primary prevention, diagnosis, and treatment of acute CVDs, as well as post-hospital care, especially in the past 40 years. These variables, however, explain neither why the decline began when it did, nor the similarities and differences in the start time and rate of the decline between countries and sexes. In Russia and some other former Soviet countries, changes in volume and patterns of alcohol consumption have caused sharp rises in CVD mortality since the early 1990s. An important challenge in reaching firm conclusions about the drivers of these remarkable international trends is the paucity of time-trend data on CVD incidence, risk factors throughout the life-course, and clinical care.
Hypertension is an important public health challenge worldwide. Information on the burden of disease from hypertension is essential in developing effective prevention and control strategies. An ...up-to-date and comprehensive assessment of the evidence concerning hypertension in sub-Saharan Africa is lacking. A literature search of the PUBMED database was conducted and supplemented by a manual search of bibliographies of retrieved articles. The search was restricted to population based studies on hypertension in sub-Saharan Africa published between January 1975 and May 2006. Data were extracted after a standard protocol and using standard data collection forms. Thirty-seven publications met the inclusion criteria. The prevalence of hypertension varied extensively between and within studies. Prevalence of hypertension was higher in urban than rural studies in all studies that covered both types of area, and also increased with increasing age in most studies. In most studies less than 40% of people with blood pressure above the defined normal range had been previously detected as hypertensive. Of people with previously diagnosed hypertension, less than 30% were on drug treatment in most studies, and less than 20% had blood pressure within the defined normal range. Hypertension is of public health importance in sub-Saharan Africa, particularly in urban areas, with evidence of considerable under-diagnosis, treatment, and control. There is an urgent need to develop strategies to prevent, detect, treat, and control hypertension effectively in the African region.
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