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

Body mass index and all-cause mortality in HUNT and UK biobank studies: revised non-linear Mendelian randomisation analyses

OBJECTIVES

To estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomisation framework.

DESIGN

Mendelian randomisation analyses of two prospective population-based cohorts.

SETTING

Individuals of European ancestries living in Norway or the UK.

PARTICIPANTS

56 150 participants from the Trøndelag Health Study (HUNT) in Norway and 366 385 participants from UK Biobank recruited by postal invitation.

OUTCOMES

All-cause mortality and cause-specific mortality (cardiovascular, cancer, non-cardiovascular non-cancer).

RESULTS

A previously published non-linear Mendelian randomisation analysis of these data using the residual stratification method suggested a J-shaped association between genetically predicted BMI and mortality outcomes with the lowest mortality risk at a BMI of around 25 kg/m2. However, the 'constant genetic effect' assumption required by this method is violated. The reanalysis of these data using the more reliable doubly-ranked stratification method provided some indication of a J-shaped relationship, but with much less certainty as there was less precision in estimates at the lower end of the BMI distribution. Evidence for a harmful effect of reducing BMI at low BMI levels was only present in some analyses, and where present, only below 20 kg/m2. A harmful effect of increasing BMI for all-cause mortality was evident above 25 kg/m2, for cardiovascular mortality above 24 kg/m2, for cancer mortality above 30 kg/m2 and for non-cardiovascular non-cancer mortality above 26 kg/m2. In UK Biobank, the association between genetically predicted BMI and mortality at high BMI levels was stronger in women than in men.

CONCLUSION

This research challenges findings from previous conventional observational epidemiology and Mendelian randomisation investigations that the lowest level of mortality risk is at a BMI level of around 25 kg/m2. Our results provide some evidence that reductions in BMI will increase mortality risk for a small proportion of the population, and clear evidence that increases in BMI will increase mortality risk for those with BMI above 25 kg/m2.

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.

Familial aggregation of the aging process: biological age measured in young adult offspring as a predictor of parental mortality

Measures of biological age (BA) integrate information across organ systems to quantify "biological aging," i.e., inter-individual differences in aging-related health decline. While longevity and lifespan aggregate in families, reflecting transmission of genes and environments across generations, little is known about intergenerational continuity of biological aging or the extent to which this continuity may be modified by environmental factors. Using data from the Jerusalem Perinatal Study (JPS), we tested if differences in offspring BA were related to mortality in their parents. We measured BA using biomarker data collected from 1473 offspring during clinical exams in 2007-2009, at age 32 ± 1.1. Parental mortality was obtained from population registry data for the years 2004-2016. We fitted parametric survival models to investigate the associations between offspring BA and parental all-cause and cause-specific mortality. We explored potential differences in these relationships by socioeconomic position (SEP) and offspring sex. Participants' BAs widely varied (SD = 6.95). Among those measured to be biologically older, parents had increased all-cause mortality (HR = 1.10, 95% CI: 1.08, 1.13), diabetes mortality (HR = 1.19, 95% CI: 1.08, 1.30), and cancer mortality (HR = 1.07, 95% CI: 1.02, 1.13). The association with all-cause mortality was stronger for families with low compared with high SEP (P_interaction = 0.04) and for daughters as compared to sons (P_interaction < 0.001). Using a clinical-biomarker-based BA estimate, observable by young adulthood prior to the onset of aging-related diseases, we demonstrate intergenerational continuity of the aging process. Furthermore, variation in this familial aggregation according to household socioeconomic position (SEP) at offspring birth and between families of sons and daughters proposes that the environment alters individuals' aging trajectory set by their parents.

Association of Weight at Different Ages and All-Cause Mortality Among Older Adults in the US

Objective: Assess the association of BMI and BMI change with mortality. Methods: Using data from the Wisconsin Longitudinal Study (WLS) on participants born mainly in 1939 (n=4922), we investigated the associations between various measures of BMI across the life course (age 54 BMI; age 65 BMI; age 72 BMI; lifetime maximum BMI; BMI change between ages 54 and 65; BMI change between ages 65 and 72) and mortality. We also assessed whether these associations are mediated by late life health. Results: BMI at age 54 was more strongly associated with late life mortality than BMI at older ages. The association between BMI change and mortality varied based on the timing of weight change. Health at age 72, particularly self-rated health, diabetes, and physical functioning, mediated the observed associations. Conclusion: Knowing older people's weight at midlife and how their weight has changed may be more important in assessing late life mortality risk than their current weight.

Associations between body composition, fat distribution and metabolic consequences of excess adiposity with severe COVID-19 outcomes: observational study and Mendelian randomisation analysis

Background

Higher body mass index (BMI) and metabolic consequences of excess weight are associated with increased risk of severe COVID-19, though their mediating pathway is unclear.

Methods

A prospective cohort study included 435,504 UK Biobank participants. A two-sample Mendelian randomisation (MR) study used the COVID-19 Host Genetics Initiative in 1.6 million participants. We examined associations of total adiposity, body composition, fat distribution and metabolic consequences of excess weight, particularly type 2 diabetes, with incidence and severity of COVID-19, assessed by test positivity, hospital admission, intensive care unit (ICU) admission and death.

Results

BMI and body fat were associated with COVID-19 in the observational and MR analyses but muscle mass was not. The observational study suggested the association with central fat distribution was stronger than for BMI, but there was little evidence from the MR analyses than this was causal. There was evidence that strong associations of metabolic consequences with COVID-19 outcomes in observational but not MR analyses. Type 2 diabetes was strongly associated with COVID-19 in observational but not MR analyses. In adjusted models, the observational analysis showed that the association of BMI with COVID-19 diminished, while central fat distribution and metabolic consequences of excess weight remained strongly associated. In contrast, MR showed the reverse, with only BMI retaining a direct effect on COVID-19.

Conclusions

Excess total adiposity is probably casually associated with severe COVID-19. Mendelian randomisation data do not support causality for the observed associations of central fat distribution or metabolic consequences of excess adiposity with COVID-19.

Stratified Restricted Mean Survival Time Model for Marginal Causal Effect in Observational Survival Data

Time to event outcomes is commonly encountered in epidemiologic research. Multiple papers have discussed the inadequacy of using the hazard ratio as a causal effect measure due to its noncollapsibility and the time-varying nature. In this paper, we further clarified that the hazard ratio might be used as a conditional causal effect measure, but it is generally not a valid marginal effect measure, even under randomized design. We proposed to use the restricted mean survival time (RMST) difference as a causal effect measure, since it essentially measures the mean difference over a specified time horizon and has a simple interpretation as the area under survival curves. For observational studies, propensity score adjustment can be implemented with RMST estimation to remove observed confounding bias. We proposed a propensity score stratified RMST estimation strategy, which performs well in our simulation evaluation and is relatively easy to implement for epidemiologists in practice. Our stratified RMST estimation includes two different versions of implementation, depending on whether researchers want to involve regression modeling adjustment, which provides a powerful tool to examine the marginal causal effect with observational survival data.

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.

Assessing the linear and non-linear association of HbA1c with cardiovascular disease: a Mendelian randomisation study

AIMS/HYPOTHESIS

We aimed to evaluate whether genetically predicted HbA_1c has an effect on the risk of cardiovascular diseases and investigate the shape of the relationship of genetically predicted HbA_1c with cardiovascular diseases.

METHODS

We performed linear univariable, multivariable and non-linear Mendelian randomisation analyses in 373,571 white British participants (mean age 56.9) from the UK Biobank.

RESULTS

In univariable linear Mendelian randomisation analysis, a 1 mmol/mol increase in genetically predicted HbA_1c was associated with higher risk of coronary artery disease (OR 1.03, 95% CI 1.02, 1.05), stroke (OR 1.02, 95% CI 1.00, 1.05) and hypertension (OR 1.02, 95% CI 1.01, 1.03). Multivariable Mendelian randomisation adjusted for the effect of haemoglobin gave a consistent conclusion for coronary artery disease. The associations with stroke and hypertension were directionally similar but with wider CI overlapping the null. Non-linear Mendelian randomisation indicated that the shape of the effect of genetically predicted HbA_1c on cardiovascular outcomes was likely linear.

CONCLUSIONS/INTERPRETATION

The study suggests a detrimental effect of HbA_1c on coronary artery disease in both men and women, and the effect is via a glycaemic characteristic. The shape of the genetic association of HbA_1c with these cardiovascular outcomes, in particular coronary artery disease, is likely to be linear.

The 3Ds - Discussion, diagnosis and direction: Elements for effective obesity care by healthcare professionals

BACKGROUND

The care of people with obesity is often suboptimal due to both physician and patient perceptions about obesity itself and clinical barriers. Using data from the ACTION-IO study, we aimed to identify factors that might improve the quality of obesity care through adoption of the 3D approach (Discussion, Diagnosis and Direction [follow-up]) by healthcare professionals (HCPs).

METHODS

An online survey was completed by HCPs in 11 countries. Exploratory beta regression analyses identified independent variables associated with each component of the 3D approach.

RESULTS

Data from 2,331 HCPs were included in the statistical models. HCPs were significantly more likely to initiate weight discussions and inform patients of obesity diagnoses, respectively, if (odds ratio [95% confidence interval]): they recorded an obesity diagnosis in their patient's medical notes (1.59, [1.43-1.76] and 2.16 [1.94-2.40], respectively); and they were comfortable discussing weight with their patients (1.53 [1.39-1.69] and 1.15 [1.04-1.27]). HCPs who reported feeling motivated to help their patients lose weight were also more likely to initiate discussions (1.36 [1.21-1.53]) and schedule follow-up appointments (1.21 [1.06-1.38]). By contrast, HCPs who lacked advanced formal training in obesity management were less likely to inform patients of obesity diagnoses (0.83 [0.74-0.92]) or schedule follow-up appointments (0.69 [0.62-0.78]).

CONCLUSION

Specific actions that could improve obesity care through the 3D approach include: encouraging HCPs to record an obesity diagnosis; providing tools to help HCPs feel more comfortable initiating weight discussions; and provision of training in obesity management.

CLINICAL TRIAL REGISTRATION

NCT03584191.

Cardiovascular symptoms affect the patterns of habitual coffee consumption

BACKGROUND

Excessive coffee consumption can lead to unpleasant sensations such as tachycardia and heart palpitations.

OBJECTIVES

Our aim was to investigate if cardiovascular symptoms can lead to alterations in habitual patterns of coffee consumption.

METHODS

We used information from up to 390,435 European ancestry participants in the UK Biobank, aged 39-73 y. Habitual coffee consumption was self-reported, and systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate were measured at baseline. Cardiovascular symptoms at baseline were based on hospital diagnoses, primary care records, and/or self-report. Mendelian randomization (MR) was used to examine genetic evidence for a causal association between SBP, DBP, and heart rate with habitual coffee consumption.

RESULTS

Participants with essential hypertension, angina, or heart arrhythmia were all more likely to drink less caffeinated coffee and to be non-habitual or decaffeinated coffee drinkers compared with those who did not report related symptoms (P ≤ 3.5 × 10-8 for all comparisons). Higher SBP and DBP were associated with lower caffeinated coffee consumption at baseline, with consistent genetic evidence to support a causal explanation across all methods [MR-Egger regression (MREggr) β: -0.21 cups/d (95% CI: -0.34, -0.07) per 10 mm Hg higher SBP and -0.33 (-0.61, -0.07) per 10 mm Hg higher DBP)]. In genetic analyses, higher resting heart rate was associated with a greater odds of being a decaffeinated coffee drinker (MREggr OR: 1.71; 95% CI: 1.31, 2.21) per 10 beats/min).

CONCLUSIONS

We provide causal genetic evidence for cardiovascular system-driven influences on habitual coffee intakes, suggesting that people tend to naturally regulate their coffee consumption based on blood pressure levels and heart rate. These findings suggest that observational studies of habitual coffee intakes are prone to influences by reverse causation, and caution is required when inferred health benefits result from comparisons with coffee abstainers or decaffeinated coffee drinkers.

Fitness, Fatness, and Mortality in Men and Women From the UK Biobank: Prospective Cohort Study

Background Cardiorespiratory fitness may moderate the association between obesity and all-cause mortality (ie, the "fat-but-fit" hypothesis), but unaddressed sources of bias are a concern. Methods and Results Cardiorespiratory fitness was estimated as watts per kilogram from a submaximal bicycle test in 77 169 men and women from the UK Biobank cohort and combined with World Health Organization standard body mass index categories, yielding 9 unique fitness-fatness combinations. We also formed fitness-fatness combinations based on bioimpedance as a direct measure of body composition. All-cause mortality was ascertained from death registries. Multivariable-adjusted Cox regression models were used to estimate hazard ratios and 95% CIs. We examined the association between fitness-fatness combinations and all-cause mortality in models with progressively more conservative approaches for accounting for reverse causation, misclassification of body composition, and confounding. Over a median follow-up of 7.7 years, 1731 participants died. In our base model, unfit men and women had higher risk of premature mortality irrespective of levels of adiposity, compared with the normal weight-fit reference. This pattern was attenuated but maintained with more conservative approaches in men, but not in women. In analysis stratified by sex and excluding individuals with prevalent major chronic disease and short follow-up and using direct measures of body composition, mortality risk was 1.78 (95% CI, 1.17-2.71) times higher in unfit-obese men but not higher in obese-fit men (0.94 [95% CI, 0.60-1.48]). In contrast, there was no increased risk in obese-unfit women (1.09 [95% CI, 0.44-1.05]) as compared with the reference. Conclusions Cardiorespiratory fitness modified the association between obesity and mortality in men, but this pattern appeared susceptible to biases in women.

Lifestyle-Related Factors and Total Mortality in a Mediterranean Prospective Cohort

INTRODUCTION

Lifestyle-related habits have a strong influence on morbidity and mortality worldwide. This study investigates the association between a multidimensional healthy lifestyle score and all-cause mortality risk, including in the score some less-studied lifestyle-related factors.

METHODS

Participants (n=20,094) of the Seguimiento Universidad de Navarra cohort were followed up from 1999 to 2018. The analysis was conducted in 2019. A 10-point healthy lifestyle score previously associated with a lower risk of major cardiovascular events was applied, assigning 1 point to each of the following items: never smoking, moderate-to-high physical activity, moderate-to-high Mediterranean diet adherence, healthy BMI, moderate alcohol consumption, avoidance of binge drinking, low TV exposure, short afternoon nap, time spent with friends, and working ≥40 hours per week.

RESULTS

During a median follow-up of 10.8 years, 407 deaths were documented. In the multivariable adjusted analysis, the highest category of adherence to the score (7-10 points) showed a 60% lower risk of all-cause mortality than the lowest category (0-3 points) (hazard ratio=0.40, 95% CI=0.27, 0.60, p<0.001 for trend). In analyses of the healthy lifestyle score as a continuous variable, for each additional point in the score, a 18% relatively lower risk of all-cause mortality was observed (adjusted hazard ratio=0.82, 95% CI=0.76, 0.88).

CONCLUSIONS

Adherence to a healthy lifestyle score, including some less-studied lifestyle-related factors, was longitudinally associated with a substantially lower mortality rate in a Mediterranean cohort. Comprehensive health promotion should be a public health priority.

Levels and changes in body mass index decomposed into fat and fat-free mass index: relation to long-term all-cause mortality in the general population

BACKGROUND

In the general population, body mass index (BMI = weight (kg)/(height (m))²) shows a U-shaped relation to mortality, which is attributable to a combination of an inverse association with fat-free mass index (FFMI) and a direct association with fat mass index (FMI). However, preceding changes in body composition related to diseases, health behaviors, or social conditions that are also influencing later mortality may confound these associations.

OBJECTIVE

To examine associations of FFMI and FMI, adjusted for preceding changes in FFMI and FMI over a 6 years period, with all-cause mortality in a healthy general population.

METHODS

The study population was a random subset of adult Danes, participating in the Danish MONICA project; 989 men and 962 women, born 1922, 1932, 1942, and 1952, and examined in 1987-88 and 1993-94. They had no known major co-morbidities until start of follow-up in 1993-94, and were followed up for 18 years. Measures included height, weight, and bio-impedance, from which BMI, FFMI, and FMI were calculated, and information on educational level, smoking, alcohol drinking, leisure-time physical activity, which were obtained by questionnaires. We analyzed the relation between body composition and all-cause mortality by Cox proportional hazards model with splines, stratified by birth cohorts, and with adjustment for preceding changes in body composition and for the covariates including gender. We estimated hazard ratios (HR) with 95% confidence intervals (CI) relative to HR = 1.00 at the median values of BMI, FMI, and FFMI.

RESULTS

During 18 years of follow-up, 286 men and 200 women died. BMI showed the well-known U-shaped association with mortality, and FMI was directly and FFMI inversely associated with mortality. Associations were not significantly modified by gender. Preceding changes in BMI, FMI, and FFMI were only weakly and not significantly associated with mortality. Associations for FMI and FFMI were monotonic, but curve-linear with a higher mortality above and below the respective median values of FMI and FFMI: at the 5th percentiles of FMI and FFMI, HRs were 0.80 (CI 0.57-1.13) and 2.01 (1.24-3.27), and at the 95th percentiles, HRs were 2.16 (1.38-3.38) and 0.81 (0.52-1.27), respectively.

CONCLUSIONS

In an apparently healthy general population, a large fat mass and a small fat-free mass are associated with greater risk of early mortality, also after adjusting for preceding changes in body composition, health behaviors, and educational level.

Effects of Weight History on the Association Between Directly Measured Adiposity and Mortality in Older Adults

BACKGROUND

It is controversial whether an altered relationship between adiposity and mortality occurs with aging. We evaluated associations between adiposity and mortality in younger and older participants before and after considering historical weight loss.

METHODS

This study used whole-body dual-energy x-ray absorptiometry data from the National Health and Nutrition Examination Survey in adults at least 20 years of age. Fat mass index (FMI), determined by dual-energy x-ray absorptiometry, was converted to age-, sex-, and race-specific Z-Scores. Percent change in weight from the maximum reported weight was determined and categorized. Cox proportional hazards models assessed associations between quintile of FMI Z-Score and mortality. Sequential models adjusted for percent weight change since the maximum weight.

RESULTS

Participants with lower FMI were more likely to have lost weight from their maximum, particularly among older participants with lower FMI. Substantially greater risk of mortality was observed for the highest quintile of FMI Z-Score compared to the second quintile among younger individuals [HR 2.50 (1.69, 3.72) p < .001]. In contrast, a more modest association was observed among older individuals in the highest quintile [HR 1.23 (0.99, 1.52) p = .06] (p for interaction <.001). In both the younger and older participants, the risks of greater FMI Z-Score were magnified when adjusting for percent weight change since maximum reported weight.

CONCLUSIONS

Older people with low fat mass report greater historical weight loss, potentially explaining substantially altered relationships between fat mass and mortality in older individuals. As a result, epidemiologic studies performed in older populations will likely underestimate the causal risks of excess adiposity.

The Effects of Reverse Causality and Selective Attrition on the Relationship Between Body Mass Index and Mortality in Postmenopausal Women

Concerns about reverse causality and selection bias complicate the interpretation of studies of body mass index (BMI, calculated as weight (kg)/height (m)2) and mortality in older adults. The objective of this study was to investigate methodological explanations for the apparent attenuation of obesity-related risks in older adults. We used data from 68,132 participants in the Women's Health Initiative (WHI) clinical trial for this analysis. All of the participants were postmenopausal women aged 50-79 years at baseline (1993-1998). To examine reverse causality and selective attrition, we compared rate ratios from inverse probability of treatment- and censoring-weighted Poisson marginal structural models with results from an unweighted adjusted Poisson regression model. The estimated mortality rate ratios and 95% confidence intervals for BMIs of 30.0-34.9, 35.0-39.9 and ≥40.0 were 0.86 (95% confidence interval (CI): 0.77, 0.96), 0.85 (95% CI: 0.72, 0.99), and 0.88 (95% CI: 0.72, 1.07), respectively, in the unweighted model. The corresponding mortality rate ratios were 0.96 (95% CI: 0.86, 1.07), 1.12 (95% CI: 0.97, 1.29), and 1.31 95% CI: (1.08, 1.57), respectively, in the marginal structural model. Results from the inverse probability of treatment- and censoring-weighted marginal structural model were attenuated in low BMI categories and increased in high BMI categories. The results demonstrate the importance of accounting for reverse causality and selective attrition in studies of older adults.

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.

Obesity and depressive symptoms in mid-life: a population-based cohort study

BACKGROUND

Obesity and depression are both highly prevalent public health disorders and evidence on their relationship is inconsistent. This study examined whether depressive symptoms are associated with current obesity, and further, whether obesity in turn is associated with an increased odds of depressive symptoms five years later after accounting for potential lifestyle confounders and depressive symptoms at baseline.

METHODS

Data were obtained from the 1958 British birth cohort (N = 9217 for cross-sectional and 7340 for prospective analysis). Clinical Interview Schedule-Revised and Mental Health Inventory-5 were used for screening depressive symptoms at ages 45 and 50 years, respectively. General and central obesity were defined using measurements of body mass index (BMI) and waist circumference (WC) at 45 years, respectively.

RESULTS

There was a cross-sectional association between depressive symptoms and obesity: participants with ≥2 depressive symptoms had 31% (95%CI 11% to 55%) higher odds of general and 26% higher odds of central obesity (95%CI 8% to 47%). In prospective analyses, both general and central obesity were associated with higher odds of depressive symptoms five years later among women but not in men (P_interaction < 0.01). After adjustment for depressive symptoms at baseline, sociodemographic and lifestyle factors, women with general obesity had 38% (95% CI 7% to 77%) and women with central obesity 34% (95%CI 9% to 65%) higher odds of depression compared to others.

CONCLUSIONS

Depressive symptoms are associated with concurrent obesity and related lifestyle factors among women and men in mid-life. Our study suggests that obesity in turn affects long-term risk of depressive symptoms in women but not in men, independently of concurrent associations, providing an important target group for the implementation of preventative strategies.

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.