The association between BMI and mortality using offspring BMI as an indicator of own BMI: large intergenerational mortality study

The healthcare costs of increased body mass index-evidence from The Trøndelag Health Study

BACKGROUND

Earlier studies have estimated the impact of increased body mass index (BMI) on healthcare costs. Various methods have been used to avoid potential biases and inconsistencies. Each of these methods measure different local effects and have different strengths and weaknesses.

METHODS

In the current study we estimate the impact of increased BMI on healthcare costs using nine common methods from the literature: multivariable regression analyses (ordinary least squares, generalized linear models, and two-part models), and instrumental variable models (using previously measured BMI, offspring BMI, and three different weighted genetic risk scores as instruments for BMI). We stratified by sex, investigated the implications of confounder adjustment, and modelled both linear and non-linear associations.

RESULTS

There was a positive effect of increased BMI in both males and females in each approach. The cost of elevated BMI was higher in models that, to a greater extent, account for endogenous relations.

CONCLUSION

The study provides solid evidence that there is an association between BMI and healthcare costs, and demonstrates the importance of triangulation.

Life course epidemiology and public health

Life course epidemiology aims to study the effect of exposures on health outcomes across the life course from a social, behavioural, and biological perspective. In this Review, we describe how life course epidemiology changes the way the causes of chronic diseases are understood, with the example of hypertension, breast cancer, and dementia, and how it guides prevention strategies. Life course epidemiology uses complex methods for the analysis of longitudinal, ideally population-based, observational data and takes advantage of new approaches for causal inference. It informs primordial prevention, the prevention of exposure to risk factors, from an eco-social and life course perspective in which health and disease are conceived as the results of complex interactions between biological endowment, health behaviours, social networks, family influences, and socioeconomic conditions across the life course. More broadly, life course epidemiology guides population-based and high-risk prevention strategies for chronic diseases from the prenatal period to old age, contributing to evidence-based and data-informed public health actions. In this Review, we assess the contribution of life course epidemiology to public health and reflect on current and future challenges for this field and its integration into policy making.

Causal models and causal modelling in obesity: foundations, methods and evidence

Discussing causes in science, if we are to do so in a way that is sensible, begins at the root. All too often, we jump to discussing specific postulated causes but do not first consider what we mean by, for example, causes of obesity or how we discern whether something is a cause. In this paper, we address what we mean by a cause, discuss what might and might not constitute a reasonable causal model in the abstract, speculate about what the causal structure of obesity might be like overall and the types of things we should be looking for, and finally, delve into methods for evaluating postulated causes and estimating causal effects. We offer the view that different meanings of the concept of causal factors in obesity research are regularly being conflated, leading to confusion, unclear thinking and sometimes nonsense. We emphasize the idea of different kinds of studies for evaluating various aspects of causal effects and discuss experimental methods, assumptions and evaluations. We use analogies from other areas of research to express the plausibility that only inelegant solutions will be truly informative. Finally, we offer comments on some specific postulated causal factors. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.

Comparison of intergenerational instrumental variable analyses of body mass index and mortality in UK Biobank

BACKGROUND

An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants.

METHODS

In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation.

RESULTS

Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter).

CONCLUSION

Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them.

Mothers of small-bodied children and fathers of vigorous sons live longer

Life-history traits (traits directly related to survival and reproduction) co-evolve and materialize through physiology and behavior. Accordingly, lifespan can be hypothesized as a potentially informative marker of life-history speed that subsumes the impact of diverse morphometric and behavioral traits. We examined associations between parental longevity and various anthropometric traits in a sample of 4,000-11,000 Estonian children in the middle of the 20th century. The offspring phenotype was used as a proxy measure of parental genotype, so that covariation between offspring traits and parental longevity (defined as belonging to the 90th percentile of lifespan) could be used to characterize the aggregation between longevity and anthropometric traits. We predicted that larger linear dimensions of offspring associate with increased parental longevity and that testosterone-dependent traits associate with reduced paternal longevity. Twelve of 16 offspring traits were associated with mothers' longevity, while three traits (rate of sexual maturation of daughters and grip strength and lung capacity of sons) robustly predicted fathers' longevity. Contrary to predictions, mothers of children with small bodily dimensions lived longer, and paternal longevity was not linearly associated with their children's body size (or testosterone-related traits). Our study thus failed to find evidence that high somatic investment into brain and body growth clusters with a long lifespan across generations, and/or that such associations can be detected on the basis of inter-generational phenotypic correlations.

The association between weight-adjusted-waist index and abdominal aortic calcification in adults aged ≥ 40 years: results from NHANES 2013-2014

The negative effects of obesity on the cardiovascular health have drawn much attention. Weight-adjusted-waist index (WWI) has been proved to reflect weight-independent centripetal obesity. However, the association between WWI and abdominal aortic calcification (AAC) has not been reported before. Using data from National Health and Nutrition Examination Survey 2013-2014, we aimed to determine the relationship of WWI and AAC in adults aged ≥ 40 years. WWI was determined by dividing waist circumference by the square root of weight. AAC was measured by dual-energy X-ray absorptiometry and quantified by Kauppila scores. Severe AAC (SAAC) was defined as an AAC score > 6. We utilized weighed multivariable logistic regression and generalized additive model to explore the independent association between WWI and AAC. Threshold effects were further calculated by two-piecewise linear regression model. 3082 participants were enrolled in our analysis, of which 48.2% were male. WWI was positively associated with AAC scores (β = 0.34, 95% CI 0.05-0.63) and exhibited a nonlinear relationship with SAAC. On the left of the breakpoint (WWI = 11.11), WWI and SAAC were positively associated (OR = 2.86, 95% CI 1.40-5.84), while no such relationship was found on the right (OR = 1.07, 95% CI 0.77-1.48). Our findings indicated that WWI may serve as a simple biomarker of AAC in US adults aged ≥ 40 years.

A machine learning-based risk stratification tool for in-hospital mortality of intensive care unit patients with heart failure

BACKGROUND

Predicting hospital mortality risk is essential for the care of heart failure patients, especially for those in intensive care units.

METHODS

Using a novel machine learning algorithm, we constructed a risk stratification tool that correlated patients' clinical features and in-hospital mortality. We used the extreme gradient boosting algorithm to generate a model predicting the mortality risk of heart failure patients in the intensive care unit in the derivation dataset of 5676 patients from the Medical Information Mart for Intensive Care III database. The logistic regression model and a common risk score for mortality were used for comparison. The eICU Collaborative Research Database dataset was used for external validation.

RESULTS

The performance of the machine learning model was superior to that of conventional risk predictive methods, with the area under curve 0.831 (95% CI 0.820-0.843) and acceptable calibration. In external validation, the model had an area under the curve of 0.809 (95% CI 0.805-0.814). Risk stratification through the model was specific when the hospital mortality was very low, low, moderate, high, and very high (2.0%, 10.2%, 11.5%, 21.2% and 56.2%, respectively). The decision curve analysis verified that the machine learning model is the best clinically valuable in predicting mortality risk.

CONCLUSION

Using readily available clinical data in the intensive care unit, we built a machine learning-based mortality risk tool with prediction accuracy superior to that of linear regression model and common risk scores. The risk tool may support clinicians in assessing individual patients and making individualized treatment.

Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable

OBJECTIVE

High body mass index (BMI) is an important predictor of mortality but estimating underlying causality is hampered by confounding and pre-existing disease. Here, we use information from the offspring to approximate parental BMIs, with an aim to avoid biased estimation of mortality risk caused by reverse causality.

METHODS

The analyses were based on information on 9674 offspring-mother and 9096 offspring-father pairs obtained from the 1958 British birth cohort. Parental BMI-mortality associations were analysed using conventional methods and using offspring BMI as a proxy, or instrument, for their parents' BMI.

RESULTS

In the conventional analysis, associations between parental BMI and all-cause mortality were U-shaped (P_curvature < 0.001), while offspring BMI had linear associations with parental mortality (P_trend < 0.001, P_curvature > 0.46). Curvature was particularly pronounced for mortality from respiratory diseases and from lung cancer. Instrumental variable analyses suggested a positive association between BMI and mortality from all causes [mothers: HR per SD of BMI 1.43 (95% CI 1.21-1.69), fathers: HR 1.17 (1.00-1.36)] and from coronary heart disease [mothers: HR 1.65 (1.15-2.36), fathers: HR 1.51 (1.17-1.97)]. These were larger than HR from the equivalent conventional analyses, despite some attenuation by adjustment for social indicators and smoking.

CONCLUSIONS

Analyses using offspring BMI as a proxy for parental BMI suggest that the apparent adverse consequences of low BMI are considerably overestimated and adverse consequences of overweight are underestimated in conventional epidemiological studies.

Instrumental variable analysis using offspring BMI in childhood as an indicator of parental BMI in relation to mortality

Childhood BMI shows associations with adult mortality, but these may be influenced by effects of ill health in childhood on BMI and later mortality. To avoid this, we used offspring childhood BMI as an instrumental variable (IV) for own BMI in relation to mortality and compared it with conventional associations of own childhood BMI and own mortality. We included 36,097 parent–offspring pairs with measured heights and weights from the Copenhagen School Health Records Register and register-based information on death. Hazard ratios (HR) were estimated using adjusted Cox regression models. For all-cause mortality, per zBMI at age 7 the conventional HR = 1.07 (95%CI: 1.04–1.09) in women and 1.02 (95%CI: 0.92–1.14) in men, whereas the IV HR = 1.23 (95%CI: 1.15–1.32) in women and 1.05 (95%CI: 0.94–1.17) in men. Per zBMI at age 13, the conventional HR = 1.11 (95%CI: 1.08–1.15) in women and 1.03 (95%CI: 0.99–1.06) in men, whereas the IV HR = 1.30 (95%CI: 1.19–1.42) in women and 1.15 (95%CI: 1.04–1.29) in men. Only conventional models showed indications of J-shaped associations. Our IV analyses suggest that there is a causal relationship between BMI and mortality that is positive at both high and low BMI values.

The role of family factors in the association between early adulthood BMI and risk of cardiovascular disease. An intergenerational study of BMI in early adulthood and cardiovascular mortality in parents, aunts and uncles

Background

High body mass index (BMI) in childhood and adolescence is related to cardiovascular disease (CVD). Causality is not established because common genetic or early life socioeconomic factors (family factors) may explain this relationship. We aimed to study the role of family factors in the association between BMI and CVD by investigating if early adulthood BMI in conscripts and CVD mortality in their parents/aunts/uncles are related.

Methods

Data from the Armed Forces Personnel Database (including height and weight among conscripts) were linked with data from the Norwegian Population Registry, generational data from the Norwegian Family Based Life Course Study, the National Educational Registry and the Cause of Death Registry using unique personal identification numbers. The study sample (N=369 464) was Norwegian males born 1967-1993, who could be linked to both parents and at least one maternal and one paternal aunt or uncle. Subsamples were identified as conscripts whose parents/aunts/uncles had data on cardiovascular risk factors available from Norwegian health surveys. Cox proportional hazards regression models were used to estimate hazard ratios (HR) of CVD mortality in the parental generation according to BMI categories of conscripts.

Results

Parents of conscripts with obesity or overweight had a higher hazard of CVD death (fathers HR obese: 1.99 (1.79,2.21), overweight: 1.33 (1.24,1.42) mothers HR obese: 1.65 (1.32,2.07), overweight: 1.23 (1.07,1.42)) than parents of normal- or underweight conscripts. Aunts and uncles of conscripts with obesity and overweight had an elevated hazard of CVD death, but less so than parents. Adjustment for CVD risk factors attenuated the results in parents, aunts and uncles.

Conclusions

Family factors may impact the relationship between early adulthood overweight and CVD in parents. These can be genes with impact on BMI over generations and genes with a pleiotropic effect on both obesity and CVD, as well as shared environment over generations.

Inflammatory biomarkers as independent prognosticators of 28-day mortality for COVID-19 patients admitted to general medicine or ICU wards: a retrospective cohort study

Inflammatory biomarkers may be associated with disease severity and increased mortality in COVID-19 patients but have not been studied in North American populations. We sought to determine whether a set of commonly ordered inflammatory biomarkers can predict 28-day mortality. We analyzed a multi-centered (four) COVID-19 registry cohort from March 4th to December 7th, 2020. This cohort included COVID-19-positive patients admitted to medical wards or intensive care units. Patients presenting to the emergency department for COVID-19 symptoms and then subsequently discharged were also included. We performed Cox-regression analysis to measure whether commonly used biomarkers were associated with an increased 28-day mortality. Of 336 COVID-19-positive patients, 267 required hospital admission, and 69 were seen in the emergency room and discharged. The median age was 63 years (IQR 80-50) and the female-to-male ratio was 49:51. Derivation of internally validated cut-offs suggested that C-reactive protein ≥ 78.4 mg/L, neutrophil-to-lymphocyte ratio ≥ 6.1, lymphocyte-to-white blood cell ratio < 0.127, and a modified Glasgow prognostic score equal to 2 vs. 1 or 0 were associated with the highest increased risk of 28-day mortality. We provide early estimates of cut-off values for inflammatory biomarkers and indices measured at the time of admission that may be useful to clinicians for predicting 28-day mortality in North American COVID-19 patients.

A Causal Estimate of Long-Term Health Care Spending Attributable to Body Mass Index Among Adults

While high body mass index (BMI) is believed to be a major driver of poor health, there is little evidence about whether it leads to higher health care spending. Understanding the causal contribution of BMI to health care spending is necessary to estimate the returns to investment in weight loss efforts. We exploit genetic variation in BMI across siblings as a natural experiment to estimate the impact of BMI on cumulative third party and out-of-pocket health care spending among adults using the Panel Study of Income Dynamics data from 1999 through 2011. We estimate a two-stage residual inclusion model with a generalized linear model. We find a $611.60 increase in cumulative insurer spending for each one-unit increase in BMI. This amounts to $130.49 in mean annual spending, and is two times higher than the non-causal estimate. We find no difference in out-of-pocket spending by BMI. These findings suggest that having a higher BMI in young/middle adulthood leads to significantly higher insurer health expenditures over the life course, which can help to inform public and private insurer policies on BMI reduction and control.

Analysis of the association between emergency dialysis start in patients with end-stage kidney disease and non-steroidal anti-inflammatory drugs, proton-pump inhibitors, and iodinated contrast agents

BACKGROUND

The association between the use of potentially nephrotoxic drugs [Non-Steroidal Anti-Inflammatory Drugs (NSAIDs), Iodinated Contrast Agents, Proton Pump Inhibitors (PPIs)] and emergency start of dialysis in patients with chronic kidney disease has not been well explored, although these compounds are commonly prescribed or available without prescription.

METHODS

In this study, the Renal Epidemiology Information Network (REIN) registry data of all patients ≥ 18 years of age who started dialysis in France in 2015 were matched with those in the French National Health Insurance Database. The association between clinical characteristics, nephrotoxic drug exposure and emergency dialysis start was investigated. Patients were categorized into four classes of NSAID and PPI exposure (new, current, past, no user) on the basis of the pre-dialysis exposure period (1-30, 31-90, and 91-365 days). For iodinated contrast agents, exposure in the 72 h and 7 days before dialysis was analyzed.

RESULTS

Among the 8805 matched patients, 30.2% needed to start dialysis in emergency. After adjustment for socio-demographic and clinical variables, new NSAID users were more likely to experience emergency dialysis start [OR = 1.95; 95% CI (1.1-3.4)]. This association was higher for new than for current users [OR: 1.44; 95% CI (1.08-1.92)]. Emergency dialysis start was also associated with iodinated contrast agent exposure in the previous 7 days [OR: 1.44; 95% CI (1.2-1.7)]. No significant relationship was detected between PPIs and emergency dialysis start.

CONCLUSIONS

Using both clinical and healthcare data, this study shows that emergency dialysis start is independently associated with recent exposure to NSAIDs and iodinated contrast agents. This suggests the need to strengthen the information given to healthcare professionals and patients with regard to nephrotoxic drugs.

Association between low prostate-specific antigen levels and greater disease progression in high-grade locally-advanced prostate cancer

PURPOSE

In advanced or high-grade prostate cancer (PCa), prostate-specific antigen (PSA) is usually elevated, however, some patients may present with low initial PSA (iPSA) levels. The objective of this study was to evaluate whether different iPSA levels were associated with dissimilar clinical outcomes among men with high-grade PCa and advanced disease after robot-assisted laparoscopic radical prostatectomy (RaLRP).

METHODS

This study enrolled 69 PCa patients with initial Gleason score ≥8 and pathologic T-stage ≥3a from April 2012 to December 2018. Patients were stratified into 3 groups based on iPSA levels at diagnosis: <5.0, 5.0-9.9, and ≥10.0. The patients' related parameters were compared among these groups.

RESULTS

The median follow-up period was 33.1 months (IQR: 12.1-48.1). There was no difference in biochemical recurrence (BCR) between the 3 groups (Log-rank test, p = 0.484). We found a higher risk of biochemical recurrence in patients with positive surgical margins (HR: 5.04, 95% CI: 1.64-15.50, p = 0.005). In addition, patients with low iPSA levels (<5.0 ng/mL) had poor radiographic progression-free survival (Log-rank test, p = 0.001) and a higher risk of disease progression (HR: 12.2, 95% CI: 1.18-1260.99, p = 0.036) compared with patients with higher iPSA levels (≥10 ng/mL).

CONCLUSION

In patients with high-grade locally-advanced PCa, a low iPSA level was associated with a higher risk of disease progression, but not with biochemical recurrence. In this unique population, serum PSA may not be a reliable marker to detect disease progression. Monitoring of these patients may warrant other biomarkers or imaging.

Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Most estimates of this association are affected by endogeneity bias. We use a novel identification strategy exploiting Mendelian Randomization - random germline genetic variation modelled using instrumental variables - to identify the causal effect of BMI on inpatient hospital costs. Using data on over 300,000 individuals, the effect size per person per marginal unit of BMI per year varied according to specification, including £21.22 (95% confidence interval (CI): £14.35-£28.07) for conventional inverse variance weighted models to £18.85 (95% CI: £9.05-£28.65) for penalized weighted median models. Effect sizes from Mendelian Randomization models were larger in most cases than non-instrumental variable multivariable adjusted estimates (£13.47, 95% CI: £12.51-£14.43). There was little evidence of non-linearity. Within-family estimates, intended to address dynastic biases, were imprecise.

Effect of Obesity and Other Risk Factors on Hypertension among Women of Reproductive Age in Ghana: An Instrumental Variable Probit Model

Background: The growing incidence of mortality as a result cardiovascular diseases (CVDs) is a major public health concern in several developing countries. In Ghana, unhealthy food consumption pattern and sedentary lifestyle are promoting overweight and obesity, with significant consequences on the incidence of CVDs. Specifically, hypertension morbidity is now a public health concern among Ghanaian health policy makers. This paper analysed the effect of body mass index (BMI)/arm circumference and other associated factors on hypertension risk among women of reproductive ages in Ghana. Methods: The data were collected as Demographic and Health Survey (DHS) in 2014. This paper analysed the subset of the data that were collected from eligible women 15-49 years of age. The total sample was 9396, while 9367 gave consents to have their blood pressure measured. Data were analysed with instrumental probit regression model with consideration of potential endogeneity of BMI and arm circumference. Results: The results showed that 25% of the women were either overweight or obese, while 13.28% were hypertensive. Women from the Greater Accra (18.15%), Ashanti (15.53%) and Volta (15.02%) regions had the highest incidences of hypertension. BMI and arm circumferences were truly endogenous and positively associated with the probability of being hypertensive. Other factors that influenced hypertension were age of women, region of residence, urban/rural residence, being pregnant, access to medical insurance, currently working, consumption of broth cubes, processed can meats, salted meat and fruits. Conclusion: It was concluded that hypertension risk was positively associated with being overweight, obesity, age and consumption of salted meat.It was inter aliaemphasized that engagement in healthy eating with less consumption of salted meats, and more consumption of fruits would assist in controlling hypertension among Ghanaian women.

Body Shape and Alzheimer's Disease: A Mendelian Randomization Analysis

Obesity has been reported to be related to memory impairment and decline in cognitive function, possibly further leading to the development of Alzheimer’s disease (AD). However, observational studies revealed both negative and positive associations between body shape (BS) and AD, thereby making it difficult to confirm causality due to residual confounds and reverse causation. Thus, using genome-wide association study summary data, two-sample Mendelian randomization (MR) analyses were applied to identify whether there exists a causal association between BS and AD. BS was measured using anthropometric traits (ATs) in this study, including body mass index (BMI), waist-to-hip ratio (WHR), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), and waist circumference (WC). The associations of single nucleotide polymorphisms (SNP) with each AT and AD were obtained separately from aggregated data from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and International Genomics of Alzheimer’s Project (IGAP) summary data (17,008 cases with AD and 37,154 controls). An inverse-variance weighted method was applied to obtain the overall causal estimate for multiple instrumental SNPs. The odds ratio (OR) [95% confidence interval (CI)] for AD risk per 1-SD difference in BMI was 1.04 (0.88, 1.23), in WHR was 1.01 (0.77, 1.33), in WHRadjBMI was 1.12 (0.89, 1.41), and in WC was 1.02 (0.82, 1.27). Furthermore, simulation analyses of survivor bias indicated the overall causal effect of BMI on risk of AD was not biased. In conclusion, the evidence from MR analyses showed no casual effect of BS on AD risk, which is inconsistent with the results from previous observational studies. The biological mechanism underlying the findings warrants further study.

Variation of all-cause and cause-specific mortality with body mass index in one million Swedish parent-son pairs: An instrumental variable analysis

BACKGROUND

High body mass index (BMI) is associated with mortality, but the pervasive problem of confounding and reverse causality in observational studies limits inference about the direction and magnitude of causal effects. We aimed to obtain estimates of the causal association of BMI with all-cause and cause-specific mortality.

METHODS AND FINDINGS

In a record-linked, intergenerational prospective study from the general population of Sweden, we used two-sample instrumental variable (IV) analysis with data from 996,898 fathers (282,407 deaths) and 1,013,083 mothers (153,043 deaths) and their sons followed up from January 1, 1961, until December 31, 2004. Sons' BMI was used as the instrument for parents' BMI to compute hazard ratios (HRs) for risk of mortality per standard deviation (SD) higher parents' BMI. Using offspring exposure as an instrument for parents' exposure is unlikely to be affected by reverse causality (an important source of bias in this context) and reduces confounding. IV analyses supported causal associations between higher BMI and greater risk of all-cause mortality (HR [95% confidence interval (CI)] per SD higher fathers' BMI: 1.29 [1.26-1.31] and mothers' BMI: 1.39 [1.35-1.42]) and overall cancer mortality (HR per SD higher fathers' BMI: 1.20 [1.16-1.24] and mothers' BMI: 1.29 [1.24-1.34]), including 9 site-specific cancers in men (bladder, colorectum, gallbladder, kidney, liver, lung, lymphatic system, pancreas, and stomach) and 11 site-specific cancers in women (gallbladder, kidney, liver, lung, lymphatic system, ovaries, pancreas, stomach, uterus, cervix, and endometrium). There was evidence supporting causal associations between higher BMI in mothers and greater risk of mortality from kidney disease (HR: 2.17 [1.68-2.81]) and lower risk of mortality from suicide (HR: 0.77 [0.65-0.90]). In both sexes, there was evidence supporting causal associations between higher BMI and mortality from cardiovascular diseases (CVDs), stroke, diabetes, and respiratory diseases. We were unable to test the association between sons' and mothers' BMIs (as mothers' data were unavailable) or whether the instrument was independent of unmeasured or residual confounding; however, the associations between parents' mortality and sons' BMI were negligibly influenced by adjustment for available confounders.

CONCLUSIONS

Consistent with previous large-scale meta-analyses and reviews, results supported the causal role of higher BMI in increasing the risk of several common causes of death, including cancers with increasing global incidence. We also found positive effects of BMI on mortality from respiratory disease, prostate cancer, and lung cancer, which has been inconsistently reported in the literature, suggesting that the causal role of higher BMI in mortality from these diseases may be underestimated. Furthermore, we expect different patterns of bias in the current observational and IV analyses; therefore, the similarities between our findings from both methods increases confidence in the results. These findings support efforts to understand the mechanisms underpinning these effects to inform targeted interventions and develop population-based strategies to reduce rising obesity levels for disease prevention.

Associations of mortality with own blood pressure using son's blood pressure as an instrumental variable

High systolic blood pressure (SBP) causes cardiovascular disease (CVD) and is associated with mortality from other causes, but conventional multivariably-adjusted results may be confounded. Here we used a son’s SBP (>1 million Swedish men) as an instrumental variable for parental SBP and examined associations with parents’ cause-specific mortality, avoiding reverse causation. The hazard ratio for CVD mortality per SD (10.80 mmHg) of SBP was 1.49 (95% CI: 1.43, 1.56); SBP was positively associated with coronary heart disease and stroke. SBP was also associated positively with all-cause, diabetes and kidney cancer mortality, and negatively with external causes. Negative associations with respiratory-related mortality were probably confounded by smoking. Hazard ratios for other causes were imprecise or null. Diastolic blood pressure gave similar results to SBP. CVD hazard ratios were intermediate between those from conventional multivariable studies and Mendelian randomization and stronger than those from clinical trials, approximately consistent with an effect of exposure duration on effect sizes. Plots of parental mortality against offspring SBP were approximately linear, supporting calls for lower SBP targets. Results suggest that conventional multivariable analyses of mortality and SBP are not substantially confounded by reverse causation and confirm positive effects of SBP on all-cause, CVD and diabetes mortality.

Heterogeneous effects of obesity on mental health: Evidence from Mexico

Obesity can spread more easily if it is not perceived negatively. This issue may be more pronounced among the poor, a conjecture that we test in this paper. We start with general evidence on the concave relationship between income and obesity, both across countries and within Mexico, a country characterized by very unequal development levels and the highest obesity rate in the world. We suggest a general model that explains this stylized fact from a simple necessary condition, namely, the complementarity between nonfood consumption and health concerns. Then, we test the direct effect of overweight on mental health among Mexican women. We find a positive effect of obesity in the low consumption group and a depressing effect among the rich. This result is robust to the inclusion of a range of confounders (childhood conditions, lifestyle variables, food expenditure, and household shocks) and after instrumenting individual fatness by the variation in genetic predisposition. The complementarity between living standards and weight concerns may reflect different norms, different labor market penalties, or simply different returns to healthy time across the social spectrum.

Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3·6 million adults in the UK

BACKGROUND

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.

METHODS

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.

FINDINGS

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.

INTERPRETATION

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.

FUNDING

Wellcome Trust.

BMI and Mortality in UK Biobank: Revised Estimates Using Mendelian Randomization

OBJECTIVE

The aim of this study was to obtain estimates of the causal relationship between BMI and mortality.

METHODS

Mendelian randomization (MR) with BMI-associated genotypic variation was used to test the causal effect of BMI on all-cause and cause-specific mortality in UK Biobank participants of White British ancestry.

RESULTS

MR analyses supported a causal association between higher BMI and greater risk of all-cause mortality (hazard ratio [HR] per 1 kg/m2 : 1.03; 95% CI: 0.99-1.07) and mortality from cardiovascular diseases (HR: 1.10; 95% CI: 1.01-1.19), specifically coronary heart disease (HR: 1.12; 95% CI: 1.00-1.25) and those excluding coronary heart disease/stroke/aortic aneurysm (HR: 1.24; 95% CI: 1.03-1.48), stomach cancer (HR: 1.18; 95% CI: 0.87-1.62), and esophageal cancer (HR: 1.22; 95% CI: 0.98-1.53), and a decreased risk of lung cancer mortality (HR: 0.96; 95% CI: 0.85-1.08). Sex stratification supported the causal role of higher BMI increasing bladder cancer mortality risk (males) but decreasing respiratory disease mortality risk (males). The J-shaped observational association between BMI and mortality was visible with MR analyses, but the BMI at which mortality was minimized was lower and the association was flatter over a larger BMI range.

CONCLUSIONS

Results support a causal role of higher BMI in increasing the risk of all-cause mortality and mortality from several specific causes.

Distinguishing genetic correlation from causation across 52 diseases and complex traits

Mendelian randomization, a method to infer causal relationships, is confounded by genetic correlations reflecting shared etiology. We developed a model in which a latent causal variable mediates the genetic correlation; trait 1 is partially genetically causal for trait 2 if it is strongly genetically correlated with the latent causal variable, quantified using the genetic causality proportion. We fit this model using mixed fourth moments [Formula: see text] and [Formula: see text] of marginal effect sizes for each trait; if trait 1 is causal for trait 2, then SNPs affecting trait 1 (large [Formula: see text]) will have correlated effects on trait 2 (large α₁α₂), but not vice versa. In simulations, our method avoided false positives due to genetic correlations, unlike Mendelian randomization. Across 52 traits (average n = 331,000), we identified 30 causal relationships with high genetic causality proportion estimates. Novel findings included a causal effect of low-density lipoprotein on bone mineral density, consistent with clinical trials of statins in osteoporosis.

Influence of puberty timing on adiposity and cardiometabolic traits: A Mendelian randomisation study

BACKGROUND

Earlier puberty is widely linked with future obesity and cardiometabolic disease. We examined whether age at puberty onset likely influences adiposity and cardiometabolic traits independent of childhood adiposity.

METHODS AND FINDINGS

One-sample Mendelian randomisation (MR) analyses were conducted on up to 3,611 white-European female and male offspring from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort recruited at birth via mothers between 1 April 1991 and 31 December 1992. Time-sensitive exposures were age at menarche and age at voice breaking. Outcomes measured at age 18 y were body mass index (BMI), dual-energy X-ray absorptiometry-based fat and lean mass indices, blood pressure, and 230 cardiometabolic traits derived from targeted metabolomics (150 concentrations plus 80 ratios from nuclear magnetic resonance [NMR] spectroscopy covering lipoprotein subclasses of cholesterol and triglycerides, amino acids, inflammatory glycoproteins, and others). Adjustment was made for pre-pubertal BMI measured at age 8 y. For negative control MR analyses, BMI and cardiometabolic trait measures taken at age 8 y (before puberty, and which therefore cannot be an outcome of puberty itself) were used. For replication analyses, 2-sample MR was conducted using summary genome-wide association study data on up to 322,154 adults for post-pubertal BMI, 24,925 adults for post-pubertal NMR cardiometabolic traits, and 13,848 children for pre-pubertal obesity (negative control). Like observational estimates, 1-sample MR estimates in ALSPAC using 351 polymorphisms for age at menarche (explaining 10.6% of variance) among 2,053 females suggested that later age at menarche (per year) was associated with -1.38 kg/m2 of BMI at age 18 y (or -0.34 SD units, 95% CI -0.46, -0.23; P = 9.77 × 10-09). This coefficient attenuated 10-fold upon adjustment for BMI at age 8 y, to -0.12 kg/m2 (or -0.03 SDs, 95% CI -0.13, 0.07; P = 0.55). Associations with blood pressure were similar, but associations across other traits were small and inconsistent. In negative control MR analyses, later age at menarche was associated with -0.77 kg/m2 of pre-pubertal BMI measured at age 8 y (or -0.39 SDs, 95% CI -0.50, -0.29; P = 6.28 × 10-13), indicating that variants influencing menarche also influence BMI before menarche. Cardiometabolic trait associations were weaker and less consistent among males and both sexes combined. Higher BMI at age 8 y (per 1 kg/m2 using 95 polymorphisms for BMI explaining 3.4% of variance) was associated with earlier menarche among 2,648 females (by -0.26 y, 95% CI -0.37, -0.16; P = 1.16 × 10-06), likewise among males and both sexes combined. In 2-sample MR analyses using 234 polymorphisms and inverse variance weighted (IVW) regression, each year later age at menarche was associated with -0.81 kg/m2 of adult BMI (or -0.17 SD units, 95% CI -0.21, -0.12; P = 4.00 × 10-15). Associations were weaker with cardiometabolic traits. Using 202 polymorphisms, later menarche was associated with lower odds of childhood obesity (IVW-based odds ratio = 0.52 per year later, 95% CI 0.48, 0.57; P = 6.64 × 10-15). Study limitations include modest sample sizes for 1-sample MR, lack of inference to non-white-European populations, potential selection bias through modest completion rates of puberty questionnaires, and likely disproportionate measurement error of exposures by sex. The cardiometabolic traits examined were heavily lipid-focused and did not include hormone-related traits such as insulin and insulin-like growth factors.

CONCLUSIONS

Our results suggest that puberty timing has a small influence on adiposity and cardiometabolic traits and that preventive interventions should instead focus on reducing childhood adiposity.

The association between BMI and mortality using early adulthood BMI as an instrumental variable for midlife BMI

The article aims to describe the association between midlife body mass index (BMI) and cardiovascular disease (CVD)- and all-cause mortality, and to use early adulthood BMI as an instrumental variable for midlife BMI, in order to obtain an estimate less distorted by midlife confounders and reverse causality. Data from Norwegian health surveys (1974–2003) (midlife BMI, smoking, blood pressure, total cholesterol, heart rate), Military Conscription Records, National Tuberculosis Screenings (early adulthood BMI), National Educational Registry and Cause of Death Registry were linked. Participants with data on BMI in early adulthood and midlife were included (n = 148.886). Hazard Ratio (HR) for CVD mortality was higher in men with midlife obesity relative to normal weight (HR = 1.46(95% CI 1.25, 1.70). For all-cause mortality, HR was higher in those with obesity or underweight in midlife relative to normal weight (Men:HR = 1.19(95% CI 1.09, 1.29), HR = 2.49(95% CI 1.81, 3.43) Women:HR = 1.33(95% CI 1.13, 1.56), HR = 1.61(95% CI 1.22, 2.13)). In instrumental variable analyses, increased BMI became more strongly associated with CVD and all-cause mortality, and the increased risk of all-cause mortality among the underweight attenuated.

Confounding by ill health in the observed association between BMI and mortality: evidence from the HUNT Study using offspring BMI as an instrument

Background

The observational association between mortality and body mass index (BMI) is U-shaped, leading to highly publicized suggestions that moderate overweight is beneficial to health. However, it is unclear whether elevated mortality is caused by low BMI or if the association is confounded, for example by concurrent ill health.

Methods

Using HUNT, a Norwegian prospective study, 32 452 mother-offspring and 27 747 father-offspring pairs were followed up to 2009. Conventional hazard ratios for parental mortality per standard deviation of BMI were estimated using Cox regression adjusted for behavioural and socioeconomic factors. To estimate hazard ratios with reduced susceptibility to confounding, particularly from concurrent ill health, the BMI of parents’ offspring was used as an instrumental variable for parents’ own BMI. The shape of mortality-BMI associations was assessed using cubic splines.

Results

There were 18 365 parental deaths during follow-up. Conventional associations of mortality from all-causes, cardiovascular disease and cancer with parents’ own BMI were substantially nonlinear, with elevated mortality at both extremes and minima at 21–25 kg m⁻². Equivalent associations with offspring BMI were positive and there was no evidence of elevated parental mortality at low offspring BMI. The linear instrumental variable hazard ratio for all-cause mortality per standard deviation increase in BMI was 1.18 (95% confidence interval: 1.10, 1.26), compared with 1.05 (1.03, 1.06) in the conventional analysis.

Conclusions

Elevated mortality rates at high BMI appear causal, whereas excess mortality at low BMI is likely exaggerated by confounding by factors including concurrent ill health. Conventional studies probably underestimate the adverse population health consequences of overweight.

The impact of childhood overweight and obesity on healthcare utilisation

Rising levels of childhood overweight and obesity represent a major global public health challenge. A number of studies have explored the association between childhood overweight and obesity and healthcare utilisation and costs. This paper adds to the literature by estimating the causal effect of child overweight and obesity status on use of general practitioner (GP) and hospital inpatient stays at two time points using instrumental variable (IV) methods The paper uses data from two waves of the Growing Up in Ireland survey of children when they are 9 and 13 years respectively and uses the biological mother's body mass index (BMI) as an instrument for the child's BMI. Our results demonstrate that child overweight and obesity status do not have a significant effect on healthcare utilisation for children when they are 9 years, but do have a large and significant effect at 13 years. Across all our models, the effects on both GP and hospital inpatient stays are found to be larger when endogeneity in childhood BMI status is addressed. Previous studies that did not address endogeneity concerns are likely to have significantly underestimated the impact of child overweight and obesity status on healthcare utilisation.

Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study

BACKGROUND

Both positive and negative associations between higher body mass index (BMI) and Parkinson disease (PD) have been reported in observational studies, but it has been difficult to establish causality because of the possibility of residual confounding or reverse causation. To our knowledge, Mendelian randomisation (MR)-the use of genetic instrumental variables (IVs) to explore causal effects-has not previously been used to test the effect of BMI on PD.

METHODS AND FINDINGS

Two-sample MR was undertaken using genome-wide association (GWA) study data. The associations between the genetic instruments and BMI were obtained from the GIANT consortium and consisted of the per-allele difference in mean BMI for 77 independent variants that reached genome-wide significance. The per-allele difference in log-odds of PD for each of these variants was estimated from a recent meta-analysis, which included 13,708 cases of PD and 95,282 controls. The inverse-variance weighted method was used to estimate a pooled odds ratio (OR) for the effect of a 5-kg/m2 higher BMI on PD. Evidence of directional pleiotropy averaged across all variants was sought using MR-Egger regression. Frailty simulations were used to assess whether causal associations were affected by mortality selection. A combined genetic IV expected to confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95% CI 0.69-0.98). MR-Egger regression gave similar results, suggesting that directional pleiotropy was unlikely to be biasing the result (intercept 0.002; p = 0.654). However, the apparent protective influence of higher BMI could be at least partially induced by survival bias in the PD GWA study, as demonstrated by frailty simulations. Other important limitations of this application of MR include the inability to analyse non-linear associations, to undertake subgroup analyses, and to gain mechanistic insights.

CONCLUSIONS

In this large study using two-sample MR, we found that variants known to influence BMI had effects on PD in a manner consistent with higher BMI leading to lower risk of PD. The mechanism underlying this apparent protective effect warrants further study.

Cardiovascular mortality - Comparing risk factor associations within couples and in the total population - The HUNT Study

BACKGROUND

To compare associations of conventional risk factors with cardiovascular death within couples and in the population as a whole.

METHODS

We analysed baseline data (1995-97) from the HUNT2 Study in Norway linked to the national Causes of Death Registry. We compared risk within couples using stratified Cox regression.

RESULTS

During 914776 person-years, 3964 cardiovascular deaths occurred, and 1658 of the deaths occurred among 1494 couples. There were consistently stronger associations of serum lipids and blood pressure with cardiovascular mortality within couples compared to the population as a whole. For instance, for systolic blood pressure (per 20mmHg), the hazard ratio (HR) within couples was 1.28 (95% confidence interval: 1.17, 1.40) compared to 1.16 (1.12, 1.20) in the total population, and for diastolic pressure (per 10mmHg), the corresponding HRs were 1.16 (1.07, 1.26) and 1.11 (1.08, 1.13). Anthropometric factors (BMI, waist circumference, waist-hip ratio) as well as diabetes, smoking, physical activity, and education, showed nearly identical positive associations within couples and in the total population.

CONCLUSIONS

Prospective population studies may tend to slightly underestimate associations of these factors with cardiovascular mortality.

Obesity and Physical Activity

Some clinical manifestations of obesity include nonalcoholic fatty liver disease, type 2 diabetes, and cardiovascular disease. Calorie restriction may aid in weight loss in the short term. Exercise and physical activity are other means of weight loss. However, the efficacy of exercise and physical activity in weight reduction in obese populations is still unknown. In this review, we discuss the effects of exercise and physical activity in obese and overweight populations. We also discuss the effects of aerobic exercise and/or resistance training in weight loss and maintenance.

U-shaped association between untreated caries and body mass index in adults at Rabat dental University hospital, Morocco: cross sectional study

Background

Many previous studies estimating the relationship between body mass index (BMI) and dental decay are conflicting. Most studies, however, examine the relationship using BMI as a categorical variable. This study evaluated the non-linear association between body mass index as a continuous variable and untreated dental decay.

Methods

Cross-sectional study of adults free of diseases attending a tertiary dental clinic was conducted. The number of untreated caries at the time of consultation was assessed using the WHO criteria. A multivariable Poisson regression model for severity of untreated dental decay was first established. Restricted cubic spline functions were used to consider potential non-linear associations between BMI and untreated dental caries.

Results

After multivariable adjustment, the prevalence ratios (PR) for the number of dental decay remained significantly associated with the age at beginning tooth brushing (PR = 1.15, 95% CI 1.05–1.25), BMI < normal (PR = 1.66, 95% CI 1.30–2.12), BMI > normal (PR = 1.30, 95% CI 1.03–1.65), SDI (PR = 0.61, 95% CI 0.50–0.75) and GI (PR = 1.59, 95% CI 1.30–1.94). When BMI was evaluated as continuous variable, it exhibited a significant U-shaped pattern with the number of untreated dental decay both in univariable and multivariable analysis.

Conclusion

The rate of untreated tooth decay was associated with both under- and overweight status.

The Curvilinear Effect of BMI on Functional Health - Evidence of the Long-Running German Ageing Survey

AIMS

We aimed at determining the effect of BMI on functional health among older Germans longitudinally.

METHODS

Data from four waves (2002-2014) of the German Ageing Survey ('Deutscher Alterssurvey'; DEAS), a representative sample of community-dwelling individuals aged 40 years and above, were used. Functional health was quantified by the subscale 'physical functioning' of the 36-Item Short Form Health Survey (SF-36). Fixed effects regressions were used to estimate the predictors of functional health. Linear, quadratic, and cubic terms were included for BMI (self-reported).

RESULTS

Fixed effects regressions showed significant linear, quadratic, and cubic effects of BMI on functional health in the total sample and in both sexes. Furthermore, regressions revealed that functional health decreased with increasing age in the total sample and in both sexes. In addition, changes in marital and employment status were significantly associated with changes in functional health in men, but not in women.

CONCLUSION

Our data indicate that the greater the extreme of BMI (either higher or lower), the greater the risk for functional decline. Nutrition programs aimed at preventing changes to extreme BMI might be productive.

The idea of uniform change: is it time to revisit a central tenet of Rose's "Strategy of Preventive Medicine"?

A mean-centric view of populations, whereby a change in the mean of a health variable at the population level is assumed to result in uniform change across the distribution, is a core component of Geoffrey Rose's concept of the "population strategy" to disease prevention. This idea also has a critical role in Rose's observation that individuals who are considered abnormal or sick (the rightward tail of the distribution) and those who are considered normal (the center) are very closely related, and that true preventive medicine must focus on shifting the normal or average. In this Perspective, we revisit these core tenets of Rose's concept of preventive medicine after providing an overview of the key concepts that he developed. We examine whether these assumptions apply to population changes in body mass index (BMI) and show that there is considerable evidence of a widening of the BMI distribution in populations over time. We argue that, with respect to BMI, the idea of using statistical measures of a population solely on the basis of means and the assumption that populations are coherent entities that change uniformly over time may not fully capture the true nature of changes in the population. These issues have important implications for how we assess and interpret the health of populations over time with implications for the balance between universal and targeted strategies aimed at improving health.

Does Overweight and Obesity Impact on Self-Rated Health? Evidence Using Instrumental Variables Ordered Probit Models

This paper, for the first time, presents estimates of the causal impact of overweight and obesity on self-rated health (SRH) using instrumental variables (IV) econometric methods. While a number of previous studies have sought to better understand the determinants of SRH, there is no consensus in relation to the impact of overweight and obesity. Using data from a large nationally representative sample of Irish parents and their children, we estimate a range of ordered probit models to isolate the causal effect of overweight and obesity on SRH. Our data includes independently and objectively recorded weight and height measures for parents and their children and we instrument for parental body mass index (BMI) status using the BMI of a biological child. After controlling for a range of individual, socioeconomic, health and lifestyle related variables, we find that being overweight has a negligible impact on SRH, while being obese has a practically and statistically significant negative impact on SRH, with these effects most pronounced for those who are most obese. We find only minor differences in these effects across gender. Copyright © 2015 John Wiley & Sons, Ltd.

The U-shaped association of body mass index with mortality: Influence of the traits height, intelligence, and education

OBJECTIVE

The U-shaped association between body mass index (BMI) and mortality may depend on other traits with permanent health effects. Whether the association between BMI and mortality depends on levels of health-related traits known to be inversely associated with mortality throughout adult life such as height, intelligence, and education was investigated.

METHODS

The study was based on a cohort of young men with data on weight, height, intelligence test score, and education from the Danish Conscription Database. In total, 346,500 men born 1939 to 1959 were followed until December 2013. The association between BMI and mortality was analyzed using Cox-regression models including interactions between BMI and height, intelligence, and education, respectively.

RESULTS

BMI and mortality showed the U-shaped association from the start of the follow-up period, and it persisted through the subsequent 56 years. As expected, the mortality was inversely associated with height, intelligence, and education, but the U shape of the association between BMI and mortality was unaffected by the levels of these traits except at higher BMI values, where the slopes were steeper for men with higher levels of height, intelligence, and education.

CONCLUSIONS

High and low BMI was associated with higher mortality throughout life regardless of the levels of height, intelligence, and education.

Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents

BACKGROUND

Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up.

METHODS

Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4-14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5-<25·0 kg/m(2).

FINDINGS

All-cause mortality was minimal at 20·0-25·0 kg/m(2) (HR 1·00, 95% CI 0·98-1·02 for BMI 20·0-<22·5 kg/m(2); 1·00, 0·99-1·01 for BMI 22·5-<25·0 kg/m(2)), and increased significantly both just below this range (1·13, 1·09-1·17 for BMI 18·5-<20·0 kg/m(2); 1·51, 1·43-1·59 for BMI 15·0-<18·5) and throughout the overweight range (1·07, 1·07-1·08 for BMI 25·0-<27·5 kg/m(2); 1·20, 1·18-1·22 for BMI 27·5-<30·0 kg/m(2)). The HR for obesity grade 1 (BMI 30·0-<35·0 kg/m(2)) was 1·45, 95% CI 1·41-1·48; the HR for obesity grade 2 (35·0-<40·0 kg/m(2)) was 1·94, 1·87-2·01; and the HR for obesity grade 3 (40·0-<60·0 kg/m(2)) was 2·76, 2·60-2·92. For BMI over 25·0 kg/m(2), mortality increased approximately log-linearly with BMI; the HR per 5 kg/m(2) units higher BMI was 1·39 (1·34-1·43) in Europe, 1·29 (1·26-1·32) in North America, 1·39 (1·34-1·44) in east Asia, and 1·31 (1·27-1·35) in Australia and New Zealand. This HR per 5 kg/m(2) units higher BMI (for BMI over 25 kg/m(2)) was greater in younger than older people (1·52, 95% CI 1·47-1·56, for BMI measured at 35-49 years vs 1·21, 1·17-1·25, for BMI measured at 70-89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46-1·56, vs 1·30, 1·26-1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI.

INTERPRETATION

The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations.

FUNDING

UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.

Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer

BACKGROUND

Adiposity traits have been associated with risk of many cancers in observational studies, but whether these associations are causal is unclear. Mendelian randomization (MR) uses genetic predictors of risk factors as instrumental variables to eliminate reverse causation and reduce confounding bias. We performed MR analyses to assess the possible causal relationship of birthweight, childhood and adult body mass index (BMI), and waist-hip ratio (WHR) on the risks of breast, ovarian, prostate, colorectal and lung cancers.

METHODS

We tested the association between genetic risk scores and each trait using summary statistics from published genome-wide association studies (GWAS) and from 51 537 cancer cases and 61 600 controls in the Genetic Associations and Mechanisms in Oncology (GAME-ON) Consortium.

RESULTS

We found an inverse association between the genetic score for childhood BMI and risk of breast cancer [odds ratio (OR) = 0.71 per standard deviation (s.d.) increase in childhood BMI; 95% confidence interval (CI): 0.60, 0.80; P = 6.5 × 10(-5)). We also found the genetic score for adult BMI to be inversely associated with breast cancer risk (OR = 0.66 per s.d. increase in BMI; 95% CI: 0.57, 0.77; P = 2.5 × 10(-7)), and positively associated with ovarian cancer (OR = 1.35; 95% CI: 1.05, 1.72; P = 0.017), lung cancer (OR = 1.27; 95% CI: 1.09, 1.49; P = 2.9 × 10(-3)) and colorectal cancer (OR = 1.39; 95% CI: 1.06, 1.82, P = 0.016). The inverse association between genetically predicted adult BMI and breast cancer risk remained even after adjusting for directional pleiotropy via MR-Egger regression.

CONCLUSIONS

Findings from this study provide additional understandings of the complex relationship between adiposity and cancer risks. Our results for breast and lung cancer are particularly interesting, given previous reports of effect heterogeneity by menopausal status and smoking status.

BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants

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; I(2)=95%, n=44) among never smokers, 1.21 (1.18 to 1.25; I(2)=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33; I(2)=89%, n=11) among healthy never smokers with exclusion of early follow-up, and 1.05 (1.04 to 1.07; I(2)=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.

The associations between US state and local social spending, income inequality, and individual all-cause and cause-specific mortality: The National Longitudinal Mortality Study

OBJECTIVE

To investigate government state and local spending on public goods and income inequality as predictors of the risks of dying.

METHODS

Data on 431,637 adults aged 30-74 and 375,354 adults aged 20-44 in the 48 contiguous US states were used from the National Longitudinal Mortality Study to estimate the impacts of state and local spending and income inequality on individual risks of all-cause and cause-specific mortality for leading causes of death in younger and middle-aged adults and older adults. To reduce bias, models incorporated state fixed effects and instrumental variables.

RESULTS

Each additional $250 per capita per year spent on welfare predicted a 3-percentage point (-0.031, 95% CI: -0.059, -0.0027) lower probability of dying from any cause. Each additional $250 per capita spent on welfare and education predicted 1.6-percentage point (-0.016, 95% CI: -0.031, -0.0011) and 0.8-percentage point (-0.008, 95% CI: -0.0156, -0.00024) lower probabilities of dying from coronary heart disease (CHD), respectively. No associations were found for colon cancer or chronic obstructive pulmonary disease; for diabetes, external injury, and suicide, estimates were inverse but modest in magnitude. A 0.1 higher Gini coefficient (higher income inequality) predicted 1-percentage point (0.010, 95% CI: 0.0026, 0.0180) and 0.2-percentage point (0.002, 95% CI: 0.001, 0.002) higher probabilities of dying from CHD and suicide, respectively.

CONCLUSIONS

Empirical linkages were identified between state-level spending on welfare and education and lower individual risks of dying, particularly from CHD and all causes combined. State-level income inequality predicted higher risks of dying from CHD and suicide.

The Demand for Cigarettes as Derived from the Demand for Weight Loss: A Theoretical and Empirical Investigation

This paper offers an economic model of smoking and body weight and provides new empirical evidence on the extent to which the demand for cigarettes is derived from the demand for weight loss. In the model, smoking causes weight loss in addition to having direct utility benefits and direct health consequences. It predicts that some individuals smoke for weight loss and that the practice is more common among those who consider themselves overweight and those who experience greater disutility from excess weight. We test these hypotheses using nationally representative data in which adolescents are directly asked whether they smoke to control their weight. We find that, among teenagers who smoke frequently, 46% of girls and 30% of boys are smoking in part to control their weight. As predicted by the model, this practice is significantly more common among those who describe themselves as too fat and among groups that tend to experience greater disutility from obesity. We conclude by discussing the implications of these findings for tax policy; specifically, the demand for cigarettes is less price elastic among those who smoke for weight loss, all else being equal. Public health efforts to reduce smoking initiation and encourage cessation may wish to design campaigns to alter the derived nature of cigarette demand, especially among adolescent girls.

Blood pressure and mortality: using offspring blood pressure as an instrument for own blood pressure in the HUNT study

Given that observational associations may be inaccurate, we used offspring blood pressure (BP) to provide alternative estimates of the associations between own BP and mortality. Observational associations between BP and mortality, estimated as hazard ratios (HRs) from Cox regression, were compared to HRs obtained using offspring BP as an instrumental variable (IV) for own BP (N = 32,227 mother-offspring and 27,535 father-offspring pairs). Observationally, there were positive associations between own BP and mortality from all-causes, cardiovascular disease (CVD), coronary heart disease (CHD), stroke and diabetes. Point estimates of the associations between BP and mortality from all-causes, CVD and CHD were amplified in magnitude when using offspring BP as an IV. For example, the HR for all-cause mortality per standard deviation (SD) increase in own systolic BP (SBP) obtained in conventional observational analyses increased from 1.10 (95% CI: 1.09-1.12; P < 0.0001) to 1.31 (95% CI: 1.19-1.43; P < 0.0001). Additionally, SBP was positively associated with diabetes and cancer mortality (HRs: 2.00; 95% CI: 1.12-3.35; P = 0.02 and 1.20; 95% CI: 1.02-1.42; P = 0.03, respectively), and diastolic BP (DBP) with stroke mortality (HR: 1.30; 95% CI: 1.02-1.66; P = 0.03). Results support positive associations between BP and mortality from all-causes, CVD, and CHD, SBP on cancer mortality, and DBP on stroke mortality.

Association of Body Mass Index with Depression, Anxiety and Suicide-An Instrumental Variable Analysis of the HUNT Study

Objective

While high body mass index is associated with an increased risk of depression and anxiety, cumulative evidence indicates that it is a protective factor for suicide. The associations from conventional observational studies of body mass index with mental health outcomes are likely to be influenced by reverse causality or confounding by ill-health. In the present study, we investigated the associations between offspring body mass index and parental anxiety, depression and suicide in order to avoid problems with reverse causality and confounding by ill-health.

Methods

We used data from 32,457 mother-offspring and 27,753 father-offspring pairs from the Norwegian HUNT-study. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale and suicide death from national registers. Associations between offspring and own body mass index and symptoms of anxiety and depression and suicide mortality were estimated using logistic and Cox regression. Causal effect estimates were estimated with a two sample instrument variable approach using offspring body mass index as an instrument for parental body mass index.

Results

Both own and offspring body mass index were positively associated with depression, while the results did not indicate any substantial association between body mass index and anxiety. Although precision was low, suicide mortality was inversely associated with own body mass index and the results from the analysis using offspring body mass index supported these results. Adjusted odds ratios per standard deviation body mass index from the instrumental variable analysis were 1.22 (95% CI: 1.05, 1.43) for depression, 1.10 (95% CI: 0.95, 1.27) for anxiety, and the instrumental variable estimated hazard ratios for suicide was 0.69 (95% CI: 0.30, 1.63).

Conclusion

The present study’s results indicate that suicide mortality is inversely associated with body mass index. We also found support for a positive association between body mass index and depression, but not for anxiety.

Savings in Medical Expenditures Associated with Reductions in Body Mass Index Among US Adults with Obesity, by Diabetes Status

BACKGROUND

The prevalence of obesity has more than doubled in the USA in the past 30 years. Obesity is a significant risk factor for diabetes, cardiovascular disease, and other clinically significant co-morbidities. This paper estimates the medical care cost savings that can be achieved from a given amount of weight loss by people with different starting values of body mass index (BMI), for those with and without diabetes. This information is an important input into analyses of the cost effectiveness of obesity treatments and prevention programs.

METHODS

Two-part models of instrumental variables were estimated using data from the Medical Expenditure Panel Survey (MEPS) for 2000-2010. Models were estimated for all adults as well as separately for those with and without diabetes. We calculated the causal impact of changes in BMI on medical care expenditures, cost savings for specific changes in BMI (5, 10, 15, and 20 %) from starting BMI levels ranging from 30 to 45 kg/m(2), as well as the total excess medical care expenditures caused by obesity.

RESULTS

In the USA, adult obesity raised annual medical care costs by $US3,508 per obese individual, for a nationwide total of $US315.8 billion (year 2010 values). However, the relationship of medical care costs over BMI is J-shaped; costs rise exponentially in the range of class 2 and 3 obesity (BMI ≥35). The heavier the obese individual, the greater the reduction in medical care costs associated with a given percent reduction in BMI. Medical care expenditures are higher, and rise more with BMI, among individuals with diabetes than among those without diabetes.

CONCLUSIONS

The savings from a given percent reduction in BMI are greater the heavier the obese individual, and are greater for those with diabetes than for those without diabetes. The results provide health insurers, employers, government agencies, and health economists with accurate estimates of the change in medical care expenditures resulting from weight loss, which is important information for calculating the cost effectiveness of interventions to prevent and treat obesity.

Adiposity as a cause of cardiovascular disease: a Mendelian randomization study

BACKGROUND

Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods.

METHODS

The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22,193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes.

RESULTS

There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12-1.28, P = 1.9.10(-7)), heart failure (HR = 1.47, 95% CI, 1.35-1.60, P = 9.10(-19)) and ischaemic stroke (HR = 1.15, 95% CI, 1.06-1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (β = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028-0.033, P = 3.10(-107)). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12-3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05-3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD.

CONCLUSIONS

Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke.

Why do thin people have elevated all-cause mortality? Evidence on confounding and reverse causality in the association of adiposity and COPD from the British Women's Heart and Health Study

Low adiposity has been linked to elevated mortality from several causes including respiratory disease. However, this could arise from confounding or reverse causality. We explore the association between two measures of adiposity (BMI and WHR) with COPD in the British Women’s Heart and Health Study including a detailed assessment of the potential for confounding and reverse causality for each adiposity measure. Low BMI was found to be associated with increased COPD risk while low WHR was not (OR = 2.2; 95% CI 1.3 – 3.1 versus OR = 1.2; 95% CI 0.7 – 1.6). Potential confounding variables (e.g. smoking) and markers of ill-health (e.g. unintentional weight loss) were found to be higher in low BMI but not in low WHR. Women with low BMI have a detrimental profile across a broad range of health markers compared to women with low WHR, and women with low WHR do not appear to have an elevated COPD risk, lending support to the hypothesis that WHR is a less confounded measure of adiposity than BMI. Low adiposity does not in itself appear to increase the risk of respiratory disease, and the apparent adverse consequences of low BMI may be due to reverse causation and confounding.

Is the adiposity-associated FTO gene variant related to all-cause mortality independent of adiposity? Meta-analysis of data from 169,551 Caucasian adults

Previously, a single nucleotide polymorphism (SNP), rs9939609, in the FTO gene showed a much stronger association with all-cause mortality than expected from its association with body mass index (BMI), body fat mass index (FMI) and waist circumference (WC). This finding implies that the SNP has strong pleiotropic effects on adiposity and adiposity-independent pathological pathways that leads to increased mortality. To investigate this further, we conducted a meta-analysis of similar data from 34 longitudinal studies including 169,551 adult Caucasians among whom 27,100 died during follow-up. Linear regression showed that the minor allele of the FTO SNP was associated with greater BMI (n = 169,551; 0.32 kg m(-2) ; 95% CI 0.28-0.32, P < 1 × 10(-32) ), WC (n = 152,631; 0.76 cm; 0.68-0.84, P < 1 × 10(-32) ) and FMI (n = 48,192; 0.17 kg m(-2) ; 0.13-0.22, P = 1.0 × 10(-13) ). Cox proportional hazard regression analyses for mortality showed that the hazards ratio (HR) for the minor allele of the FTO SNPs was 1.02 (1.00-1.04, P = 0.097), but the apparent excess risk was eliminated after adjustment for BMI and WC (HR: 1.00; 0.98-1.03, P = 0.662) and for FMI (HR: 1.00; 0.96-1.04, P = 0.932). In conclusion, this study does not support that the FTO SNP is associated with all-cause mortality independently of the adiposity phenotypes.

The influence of obesity and overweight on medical costs: a panel data perspective

This paper estimates the increase of direct medical costs of both severe and moderate obesity and overweight with respect to a normal-weight individual using a two-part generalised linear model and a longitudinal dataset of medical and administrative records of patients in primary and secondary healthcare centres followed up over seven consecutive years (2004-2010) in Spain. Our findings indicate that severe and moderate obesity imposes a substantial burden on the Spanish healthcare system. Specifically, being severely obese is associated with increases in medical costs of 26 % (instrumental variables (IV) estimate, 34 %) compared to a normal-weight individual. The effects of moderate obesity and overweight are more modest, raising medical costs by 16 % (IV estimate, 29 %) and 8.5 % (IV estimate, 23 %), respectively. These changes in costs are slightly higher for those patients below the median age and for the women. Notwithstanding, the effects found in this study are comparatively much lower than that reported for the USA, based basically on a private healthcare system and characterised by a more obese population.