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Background Recent studies have found that long-term changes in weight during adulthood are associated with a high risk of mortality. The objective of this study was to characterize body mass index (BMI) trajectories during adulthood and to examine the association between BMI trajectories and risk of death in the Japanese population. Methods The data were extracted from Japan Public Health Center-based Prospective Study—a population-based prospective cohort study in Japan with participants aged 40–69 years followed over 20 years. The participants were categorized into multiple BMI trajectory groups using the latent class growth model. The Cox proportional-hazards model was conducted using all-cause mortality and cause-specific mortality as outcomes and the identified BMI trajectory groups as a predictor. In total, 65 520 participants were included in the analysis. Results Six BMI trajectory groups were identified: underweight stable (Group 1), low-to-high normal (Group 2), high-to-low normal (Group 3), normal to overweight (Group 4), overweight to normal (Group 5) and normal to obese (Group 6). Our Cox models showed a higher hazard (risk) of all-cause mortality among participants in the BMI-declining groups [Group 3, adjusted hazard ratio (aHR): 1.10, 95% CI: 1.05–1.16; Group 5, aHR: 1.16, 95% CI: 1.08–1.26], underweight stable group (Group 1, aHR: 1.27, 95% CI: 1.21–1.33) and normal to obese group (Group 6, aHR: 1.22, 95% CI: 1.13–1.33) than Group 2 (low-to-high normal BMI trajectory). Conclusions Stable underweight and weight loss were associated with a high risk of mortality, both of which were uniquely observed in a Japanese population. [ABSTRACT FROM AUTHOR]

The association of obesity with mortality has been the subject of scientific investigation for centuries. Although historical observations, as well as more recent quantitative analyses, demonstrate a relationship of obesity with early death, there remain questions about the degree of the association and how it may vary with age, diet, physical activity, and other life circumstances. The relationship between body mass index (BMI) and mortality is "U-shaped," with the lowest mortality rate observed at a mildly overweight BMI. Many potential explanations have been postulated for higher mortality at both lower and higher levels of BMI, such as occult disease in those at low BMI; difference across categories in weight variability, smoking, and/or distribution of body fat; and the "fit but fat" phenotype. This review discusses some of the continuing questions and hypotheses surrounding the relationship of BMI with mortality and identifies additional research needed. [ABSTRACT FROM AUTHOR]

We discuss 12 misperceptions, misstatements, or mistakes concerning the use of covariates in observational or nonrandomized research. Additionally, we offer advice to help investigators, editors, reviewers, and readers make more informed decisions about conducting and interpreting research where the influence of covariates may be at issue. We primarily address misperceptions in the context of statistical management of the covariates through various forms of modeling, although we also emphasize design and model or variable selection. Other approaches to addressing the effects of covariates, including matching, have logical extensions from what we discuss here but are not dwelled upon heavily. The misperceptions, misstatements, or mistakes we discuss include accurate representation of covariates, effects of measurement error, overreliance on covariate categorization, underestimation of power loss when controlling for covariates, misinterpretation of significance in statistical models, and misconceptions about confounding variables, selecting on a collider, and p value interpretations in covariate-inclusive analyses. This condensed overview serves to correct common errors and improve research quality in general and in nutrition research specifically., Competing Interests: XY, RZ, DF, LM, DV, CT, CV, YJ, SC, SL, DA No competing interests declared, (© 2024, Yu, Zoh et al.)