Objective To conduct a systematic review and meta-analysis of cohort studies of body mass index (BMI) and the risk of all cause mortality, and to clarify the shape and the nadir of the dose-response curve, and the influence on the results of confounding from smoking, weight loss associated with disease, and preclinical disease.Data sources PubMed and Embase databases searched up to 23 September 2015.Study selection Cohort studies that reported adjusted risk estimates for at least three categories of BMI in relation to all cause mortality.Data synthesis Summary relative risks were calculated with random effects models. Non-linear associations were explored with fractional polynomial models.Results 230 cohort studies (207 publications) were included. The analysis of never smokers included 53 cohort studies (44 risk estimates) with >738 144 deaths and >9 976 077 participants. The analysis of all participants included 228 cohort studies (198 risk estimates) with >3 744 722 deaths among 30 233 329 participants. The summary relative risk for a 5 unit increment in BMI was 1.18 (95% confidence interval 1.15 to 1.21; I2=95%, n=44) among never smokers, 1.21 (1.18 to 1.25; I2=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33; I2=89%, n=11) among healthy never smokers with exclusion of early follow-up, and 1.05 (1.04 to 1.07; I2=97%, n=198) among all participants. There was a J shaped dose-response relation in never smokers (Pnon-linearity <0.001), and the lowest risk was observed at BMI 23-24 in never smokers, 22-23 in healthy never smokers, and 20-22 in studies of never smokers with ≥20 years’ follow-up. In contrast there was a U shaped association between BMI and mortality in analyses with a greater potential for bias including all participants, current, former, or ever smokers, and in studies with a short duration of follow-up (<5 years or <10 years), or with moderate study quality scores.Conclusion Overweight and obesity is associated with increased risk of all cause mortality and the nadir of the curve was observed at BMI 23-24 among never smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of follow-up. The increased risk of mortality observed in underweight people could at least partly be caused by residual confounding from prediagnostic disease. Lack of exclusion of ever smokers, people with prevalent and preclinical disease, and early follow-up could bias the results towards a more U shaped association.

To cite this article: Naess IA, Christiansen SC, Romundstad P, Cannegieter SC, Rosendaal FR, Hammerstrøm J. Incidence and mortality of venous thrombosis: a population-based study. J Thromb Haemost 2007; 5: 692-9.See also Sørensen HT. Venous thromboembolism and the concepts of the incidence and mortality. This issue, pp 690-1.Summary. Background: Estimates of the incidence of venous thrombosis (VT) vary, and data on mortality are limited. Objectives: We estimated the incidence and mortality of a first VT event in a general population. Methods: From the residents of Nord-Trøndelag county in Norway aged 20 years and older (n = 94 194), we identified all cases with an objectively verified diagnosis of VT that occurred between 1995 and 2001. Patients and diagnosis characteristics were retrieved from medical records. Results: Seven hundred and forty patients were identified with a first diagnosis of VT during 516 405 personyears of follow-up. The incidence rate for all first VT events was 1.43 per 1000 person-years [95% confidence interval (CI): 1.33-1.54], that for deep-vein thrombosis (DVT) was 0.93 per 1000 person-years (95% CI: 0.85-1.02), and that for pulmonary embolism (PE) was 0.50 per 1000 person-years (95% CI: 0.44-0.56). The incidence rates increased exponentially with age, and were slightly higher in women than in men. The 30-day casefatality rate was higher in patients with PE than in those with DVT [9.7% vs. 4.6%, risk ratio 2.1 (95% CI: 1.2-3.7)]; it was also higher in patients with cancer than in patients without cancer [19.1% vs. 3.6%, risk ratio 3.8 (95% CI 1.6-9.2)]. The risk of dying was highest in the first months subsequent to the VT, after which it gradually approached the mortality rate in the general population. Conclusions: This study provides estimates of incidence and mortality of a first VT event in the general population.

BackgroundPopulation based studies are important for prevalence, incidence and association studies, but their external validity might be threatened by decreasing participation rates. The 50 807 participants in the third survey of the HUNT Study (HUNT3, 2006-08), represented 54% of the invited, necessitating a nonparticipation study.MethodsQuestionnaire data from HUNT3 were compared with data collected from several sources: a short questionnaire to nonparticipants, anonymous data on specific diagnoses and prescribed medication extracted from randomly selected general practices, registry data from Statistics Norway on socioeconomic factors and mortality, and from the Norwegian Prescription Database on drug consumption.ResultsParticipation rates for HUNT3 depended on age, sex and type of symptoms and diseases, but only small changes were found in the overall prevalence estimates when including data from 6922 nonparticipants. Among nonparticipants, the prevalences of cardiovascular diseases, diabetes mellitus and psychiatric disorders were higher both in nonparticipant data and data extracted from general practice, compared to that reported by participants, whilst the opposite pattern was found, at least among persons younger than 80 years, for urine incontinence, musculoskeletal pain and headache. Registry data showed that the nonparticipants had lower socioeconomic status and a higher mortality than participants.ConclusionNonparticipants had lower socioeconomic status, higher mortality and showed higher prevalences of several chronic diseases, whilst opposite patterns were found for common problems like musculoskeletal pain, urine incontinence and headache. The impact on associations should be analyzed for each diagnosis, and data making such analyses possible are provided in the present paper.

Several studies have suggested a protective effect of intake of whole grains, but not refined grains on type 2 diabetes risk, but the dose-response relationship between different types of grains and type 2 diabetes has not been established. We conducted a systematic review and meta-analysis of prospective studies of grain intake and type 2 diabetes. We searched the PubMed database for studies of grain intake and risk of type 2 diabetes, up to June 5th, 2013. Summary relative risks were calculated using a random effects model. Sixteen cohort studies were included in the analyses. The summary relative risk per 3 servings per day was 0.68 (95% CI 0.58-0.81, I(2) = 82%, n = 10) for whole grains and 0.95 (95% CI 0.88-1.04, I(2) = 53%, n = 6) for refined grains. A nonlinear association was observed for whole grains, p nonlinearity < 0.0001, but not for refined grains, p nonlinearity = 0.10. Inverse associations were observed for subtypes of whole grains including whole grain bread, whole grain cereals, wheat bran and brown rice, but these results were based on few studies, while white rice was associated with increased risk. Our meta-analysis suggests that a high whole grain intake, but not refined grains, is associated with reduced type 2 diabetes risk. However, a positive association with intake of white rice and inverse associations between several specific types of whole grains and type 2 diabetes warrant further investigations. Our results support public health recommendations to replace refined grains with whole grains and suggest that at least two servings of whole grains per day should be consumed to reduce type 2 diabetes risk.

This meta-analysis suggests that there is a significant inverse association between intakes of dairy products, low-fat dairy products, and cheese and risk of type 2 diabetes. Any additional studies should assess the association between other specific types of dairy products and the risk of type 2 diabetes and adjust for more confounding factors.