Heterogeneity in Trajectories of Body Mass Index and Their Associations with Mortality in Old Age: A Literature Review

Association between distinct body mass index trajectories according to the group-based trajectory modeling and the risk of incident diabetes: A systematic review

We aimed to determine the association between distinct body mass index (BMI) trajectories, using group-based trajectory modeling, and the subsequent risk of incident diabetes. Five databases were systematically searched. Fourteen population-based cohort studies that summarized the association between different BMI trajectories and subsequent diabetes, with the four most common BMI trajectories including the "stable," "increasing," "decreasing," and "turning" groups, were included. The rapid increase and stable high-level BMI groups showed the strongest association with the subsequent risk of diabetes compared with the stable normal BMI group. Increased baseline BMI levels resulted in a steeper slope and greater risk of subsequent diabetes. In the decreasing BMI group, one study reported that those aged >50 years showed the highest incidence of subsequent diabetes, whereas the other two studies reported no association between these two variables. In the turning group, an increase followed by a decrease in BMI levels from adolescence to late adulthood could reduce the risk of developing diabetes, although the residual risk remained. By contrast, the incidence of subsequent diabetes remained high in the middle-aged BMI-turning group. This study can provide further insights for identifying populations at high risk of diabetes and for developing targeted prevention strategies.

Prepregnancy weight change associated with high gestational weight gain

OBJECTIVE

Gestational weight gain (GWG) above recommendations is a risk factor for adverse maternal, perinatal, and long-term outcomes. This study hypothesized that prepregnancy weight gain may portend excess GWG.

METHODS

Among 1,126 women (51% of whom were of Black race) in the Coronary Artery Risk Development in Young Adults (CARDIA) study with post-baseline births, the prepregnancy annual rate of BMI change per woman was estimated (slope; 5 years before pregnancy) and was related to the risk of GWG above Institute of Medicine recommendations using mixed-effects models (binary) and GWG z score (continuous), adjusting for confounders, and stratified by prepregnancy overweight/obesity status.

RESULTS

A total of 626 women (56%) had excess GWG. Each standard deviation increase in prepregnancy BMI (0.16 kg/m2 per year) was associated with an 18% increased risk of excess GWG (95% CI: 1.13-1.23), adjusted for covariates. Stratified results showed an association for women without overweight or obesity (adjusted relative risk = 1.71 [95% CI: 1.38-2.13]) but not among those with overweight or obesity (adjusted relative risk = 0.98 [95% CI: 0.91-1.05]). When evaluated as a z score, prepregnancy weight gain was associated with higher GWG among women with and without overweight or obesity (mean = 0.24 [0.10] and 0.28 [0.12] z score, respectively).

CONCLUSIONS

Weight gain before pregnancy is associated with higher GWG during pregnancy. Assessment of prepregnancy weight changes may identify those at risk for high GWG.

Body mass index trajectories during mid to late life and risks of mortality and cardiovascular outcomes: Results from four prospective cohorts

BACKGROUND

Our understanding of the weight-outcome association mainly comes from single-time body mass index (BMI) measurement. However, data on long-term trajectories of within-person changes in BMI on diverse study outcomes are sparse. Therefore, this study is to determine the associations of individual BMI trajectories and cardiovascular outcomes.

METHODS

The present analysis was based on data from 4 large prospective cohorts and restricted to participants aged ≥45 years with at least two BMI measurements. Hazard ratios (HR) and 95% confidence intervals(95%CI) for each outcome according to different BMI trajectories were calculated in Cox regression models.

FINDINGS

The final sample comprised 29,311 individuals (mean age 58.31 years, and 77.31% were white), with a median 4 BMI measurements used in this study. During a median follow-up of 21.16 years, there were a total of 10,192 major adverse cardiovascular events (MACE) and 11,589 deaths. A U-shaped relation was seen with all study outcomes. Compared with maintaining stable weight, the multivariate adjusted HR for MACE were 1.53 (95%CI 1.40-1.66), 1.26 (95%CI 1.16-1.37) and 1.08 (95%CI 1.02-1.15) respectively for rapid, moderate and slow weight loss; 1.01 (95%CI 0.95-1.07), 1.13 (95%CI 1.05-1.21) and 1.29 (95%CI 1.20-1.40) respectively for slow, moderate and rapid weight gain. Identical patterns of association were observed for all other outcomes. The development of BMI differed markedly between the outcome-free individuals and those who went on to experience adverse events, generally beginning to diverge 10 years before the occurrence of the events.

INTERPRETATION

Our findings may signal an underlying high-risk population and inspire future studies on weight management.

FUNDING

National Natural Science Foundation of China, Guangdong Natural Science Foundation.

Long-term trends in the body mass index and obesity risk in Estonia: an age-period-cohort approach

OBJECTIVES

To analyse the age, period and cohort effects on the mean body mass index (BMI) and obesity over the past two decades in Estonia.

METHODS

Study used data from nationally representative repeated cross-sectional surveys on 11,547 men and 16,298 women from 1996 to 2018. The independent effects of age, period and cohort on predicted mean BMI and probability of obesity (BMI ≥ 30 kg/m²) were modelled using hierarchical age-period-cohort analysis.

RESULTS

Curvilinear association between age and mean BMI was found for men, whereas the increase in mean BMI was almost linear for women. The predicted mean BMI for 40-year-old men had increased by 6% and probability of obesity by 1.8 times over 1996-2018; the period effects were slightly smaller for women. Men from the 1970s birth cohort had higher mean BMI compared to the average, whereas no significant cohort effects were found for obesity outcome.

CONCLUSIONS

Population-level BMI changes in Estonia during 1996-2018 were mostly driven by period rather than cohort-specific changes.

Distinct developmental trajectories of body mass index and diabetes risk: A 5-year longitudinal study of Chinese adults

AIMS/INTRODUCTION

This longitudinal study aimed to explore whether distinct developmental trajectories of body mass index (BMI) would be predictive of diabetes risk in general Chinese adults.

MATERIALS AND METHODS

A total of 4,519 participants aged >18 years who were free of diabetes in 2011 (baseline of the current analysis) were enrolled in this study. All participants completed a medical examination every year during 2011-2016, and BMI levels were measured two to six (average 5.6) times. Group-based trajectory modeling was applied to identify BMI trajectories over time. New-onset diabetes was confirmed in 2016.

RESULTS

During 2011-2016, four distinct BMI trajectories were identified according to BMI range and changing pattern over time: "low" (19.6%), "moderate" (33.4%), "moderate-high" (33.4%) and "high" (13.6%). A total of 168 (3.7%) new-onset diabetes cases were confirmed in 2016. Compared with the "low" BMI trajectory, participants in the "high" BMI trajectory were at significantly higher risk for new-onset diabetes (adjusted relative risk 3.24, 95% confidence interval 1.27-8.24). Notably, BMI trajectories based on the first four or three annual BMI tests yielded similar results. By contrast, no significant correlation was found between categories of baseline BMI and new-onset diabetes in 2016 after multivariate adjustment.

CONCLUSIONS

The present results show that distinct BMI trajectories, even identified using just four or three annual BMI tests, are significantly associated with new-onset diabetes. Monitoring BMI trajectories over time might provide an important approach to identify subpopulations at higher risk for developing diabetes.