Mortality Risk of Obesity and Underweight Is Overestimated with Self-Reported Body Mass Index:

Self-reported and measured anthropometric variables in association with cardiometabolic markers: A Danish cohort study

General obesity is a recognized risk factor for various metabolically related diseases, including hypertension, dyslipidemia, and pre-diabetes. In epidemiological studies, anthropometric variables such as height and weight are often self-reported. However, misreporting of self-reported data may bias estimates of associations between anthropometry and health outcomes. Further, few validation studies have compared self-reported and measured waist circumference (WC). This study aimed to quantify the agreement between self-reported and measured height, weight, body mass index (BMI), WC, and waist-to-height ratio (WHtR), and to investigate associations of these anthropometric measures with cardiometabolic biomarkers. A total of 39,514 participants aged above 18 years were included into the Diet, Cancer, and Health-Next Generation Cohort in 2015-19. Self-reported and measured anthropometric variables, blood pressure, and cardiometabolic biomarkers (HbA1c, lipid profiles, C-reactive protein and creatinine) were collected by standard procedures. Pearson correlations (r) and Lin's concordance correlations were applied to evaluate misreporting. Misreporting by age, sex and smoking status was investigated in linear regression models. Multivariable regression models and Receiver Operating Characteristic analyses assessed associations of self-reported and measured anthropometry with cardiometabolic biomarkers. Self-reported height was overreported by 1.07 cm, and weight was underreported by 0.32 kg on average. Self-reported BMI and WC were 0.42 kg/m2 and 0.2 cm lower than measured, respectively. Self-reported and measured height, weight, BMI, WC and WtHR were strongly correlated (r = 0.98, 0.99, 0.98, 0.88, 0.86, respectively). Age, sex, smoking, and BMI contributed to misreporting of all anthropometric measures. Associations between self-reported or measured anthropometric measures and cardiometabolic biomarkers were similar in direction and strength. Concordance between self-reported and measured anthropometric measures, including WC, was very high. Self-reported anthropometric measures were reliable when estimating associations with cardiometabolic biomarkers.

Bias in Hazard Ratios Arising From Misclassification According to Self-Reported Weight and Height in Observational Studies of Body Mass Index and Mortality

Misclassification of body mass index (BMI) categories arising from self-reported weight and height can bias hazard ratios in studies of BMI and mortality. We examined the effects on hazard ratios of such misclassification using national US survey data for 1976 through 2010 that had both measured and self-reported weight and height along with mortality follow-up for 48,763 adults and a subset of 17,405 healthy never-smokers. BMI was categorized as <22.5 (low), 22.5-24.9 (referent), 25.0-29.9 (overweight), 30.0-34.9 (class I obesity), and ≥35.0 (class II-III obesity). Misreporting at higher BMI categories tended to bias hazard ratios upwards for those categories, but that effect was augmented, counterbalanced, or even reversed by misreporting in other BMI categories, in particular those that affected the reference category. For example, among healthy male never-smokers, misclassifications affecting the overweight and the reference categories changed the hazard ratio for overweight from 0.85 with measured data to 1.24 with self-reported data. Both the magnitude and direction of bias varied according to the underlying hazard ratios in measured data, showing that findings on bias from one study should not be extrapolated to a study with different underlying hazard ratios. Because of misclassification effects, self-reported weight and height cannot reliably indicate the lowest-risk BMI category.

Comparative effects of the restriction method in two large observational studies of body mass index and mortality among adults

BACKGROUND

A method applied in some large studies of weight and mortality is to begin with a well-defined analytic cohort and use successive restrictions to control for methodologic bias and arrive at final analytic results.

MATERIALS AND METHODS

Two observational studies of body mass index and mortality allow a comparative assessment of these restrictions in very large data sets. One was a meta-analysis of individual participant data with a sample size of 8 million. The second was a study of a South Korean cohort with a sample size of 12 million. Both presented results for participants without pre-existing disease before and after restricting the sample to never-smokers and deleting the first 5 years of follow-up.

RESULTS

Initial results from both studies were generally similar, with hazard ratios (HRs) below 1 for overweight and above 1 for underweight and obesity. The meta-analysis showed higher HRs for overweight and obesity after the restrictions, including a change in the direction of the HR for overweight from 0·99 (95% CI: 0·98-1·01) to 1·11 (95% CI: 1·10, 1·11). The South Korean data showed little effect of the restrictions and the HR for overweight changed from 0·85 (95% CI: 0·84-0·86) to 0·91 (95% CI: 0·90, 0·91). The summary effect size for overweight was 0·90 (95% CI: 0·89-0·91) before restrictions and 1·02 (95% CI: 1·02, 1·03) after restrictions.

CONCLUSIONS

The effect of the restrictions is not consistent across studies, weakening the argument that analyses without such restrictions lack validity.

Estimating population attributable fractions to quantify the health burden of obesity

PURPOSE

Obesity is a highly prevalent condition in the United States and elsewhere and is associated with increased mortality and morbidity. Here, we discuss some issues involved in quantifying the health burden of obesity using population attributable fraction (PAF) estimates and provide examples.

METHODS

We searched PubMed for articles reporting attributable fraction estimates for obesity. We reviewed eligible articles to identify methodological concerns and tabulated illustrative examples of PAF estimates for obesity relative to cancer, diabetes, cardiovascular disease, and all-cause mortality.

RESULTS

There is considerable variability among studies regarding the methods used for PAF calculation and the selection of appropriate counterfactuals. The reported estimates ranged from 5% to 15% for all-cause mortality, -0.2% to 8% for all-cancer incidence, 7% to 44% for cardiovascular disease incidence, and 3% to 83% for diabetes incidence.

CONCLUSIONS

To evaluate a given estimate, it is important to consider whether the exposure and outcome were defined similarly for the PAF and for the relative risks, whether the relative risks were suitable for the population at hand, and whether PAF was calculated using correct methods. Strong causal assumptions are not necessarily warranted. In general, PAFs for obesity may be best considered as indicators of association.

Body mass index categories in observational studies of weight and risk of death

The World Health Organization (Geneva, Switzerland) and the National Heart, Lung, and Blood Institute (Bethesda, Maryland) have developed standard categories of body mass index (BMI) (calculated as weight (kg)/height (m)(2)) of less than 18.5 (underweight), 18.5-24.9 (normal weight), 25.0-29.9 (overweight), and 30.0 or more (obesity). Nevertheless, studies of BMI and the risk of death sometimes use nonstandard BMI categories that vary across studies. In a meta-analysis of 8 large studies that used nonstandard BMI categories and were published between 1999 and 2014 and included 5.8 million participants, hazard ratios tended to be small throughout the range of overweight and normal weight. Risks were similar between subjects of high-normal weight (BMI of approximately 23.0-24.9) and those of low overweight (BMI of approximately 25.0-27.4). In an example using national survey data, minor variations in the reference category affected hazard ratios. For example, choosing high-normal weight (BMI of 23.0-24.9) instead of standard normal weight (BMI of 18.5-24.9) as the reference category produced higher nonsignificant hazard ratios (1.05 vs. 0.97 for men and 1.06 vs. 1.02 for women) for the standard overweight category (BMI of 25.0-29.9). Use of the standard BMI groupings avoids problems of ad hoc and post hoc category selection and facilitates between-study comparisons. The ways in which BMI data are categorized and reported may shape inferences about the degree of risk for various BMI categories.

Mortality risk associated with underweight: a census-linked cohort of 31,578 individuals with up to 32 years of follow-up

Background

In contrast to obesity, information on the health risks of underweight is sparse. We examined the long-term association between underweight and mortality by considering factors possibly influencing this relationship.

Methods

We included 31,578 individuals aged 25–74 years, who participated in population based health studies between 1977 and 1993 and were followed-up for survival until 2008 by record linkage with the Swiss National Cohort (SNC). Body Mass Index (BMI) was calculated from measured (53% of study population) or self-reported height and weight. Underweight was defined as BMI < 18.5 kg/m². Cox regression models were used to determine mortality Hazard Ratios (HR) of underweight vs. normal weight (BMI 18.5- < 25.0 kg/m²). Covariates were study, sex, smoking, healthy eating proxy, sports frequency, and educational level.

Results

Underweight individuals represented 3.0% of the total study population (n = 945), and were mostly women (89.9%). Compared to normal weight, underweight was associated with increased all-cause mortality (HR: 1.37; 95% CI: 1.14-1.65). Increased risk was apparent in both sexes, regardless of smoking status, and mainly driven by excess death from external causes (HR: 3.18; 1.96-5.17), but not cancer, cardiovascular or respiratory diseases. The HR were 1.16 (0.88-1.53) in studies with measured BMI and 1.59 (1.24-2.05) with self-reported BMI.

Conclusions

The increased risk of dying of underweight people was mainly due to an increased mortality risk from external causes. Using self-reported BMI may lead to an overestimation of mortality risk associated with underweight.