Body Mass Index Trajectories Research Articles

Prospective prediction of childhood body mass index trajectories using multi-task Gaussian processes.

Body mass index (BMI) trajectories have been used to assess the growth of children with respect to their peers, and to anticipate future obesity and disease risk. While retrospective BMI trajectories have been actively studied, models to prospectively predict continuous BMI trajectories have not been investigated. Using longitudinal BMI measurements between birth and age 10 y from a mother-offspring cohort, we leveraged a multi-task Gaussian process approach to develop and evaluate a unified framework for modeling, clustering, and prospective prediction of BMI trajectories. We compared its sensitivity to missing values in the longitudinal follow-up of children, compared its prediction performance to cubic B-spline and multilevel Jenss-Bayley models, and used prospectively predicted BMI trajectories to assess the probability of future BMIs crossing the clinical cutoffs for obesity. MagmaClust identified 5 distinct patterns of BMI trajectories between 0 to 10 y. The method outperformed both cubic B-spline and multilevel Jenss-Bayley models in the accuracy of retrospective BMI trajectories while being more robust to missing data (up to 90%). It was also better at prospectively forecasting BMI trajectories of children for periods ranging from 2 to 8 years into the future, using historic BMI data. Given BMI data between birth and age 2 years, prediction of overweight/obesity status at age 10 years, as computed from MagmaClust's predictions exhibited high specificity (0.94), negative predictive value (0.89), and accuracy (0.86). The accuracy, sensitivity, and positive predictive value of predictions increased as BMI data from additional time points were utilized for prediction. MagmaClust provides a unified, probabilistic, non-parametric framework to model, cluster, and prospectively predict childhood BMI trajectories and overweight/obesity risk. The proposed method offers a convenient tool for clinicians to monitor BMI growth in children, allowing them to prospectively identify children with high predicted overweight/obesity risk and implement timely interventions.

Association between body mass index trajectories and type 2 diabetes incidence over an 18-year follow-up in the Tehran Lipid and Glucose Study.

Body mass index (BMI) is a well-known risk factor for type 2 diabetes mellitus (T2DM). We aimed to identify BMI trajectory patterns and evaluate their association with T2DM during 18 years of follow-up. We included 6026 participants aged 20 to 65 from the prospective population-based Tehran Lipid and Glucose Study (TLGS). The BMI trajectory patterns were identified using latent growth mixture modeling (LGMM) during the measurement period. The association between the BMI trajectory patterns and future T2DM was evaluated using the Cox proportional hazard regression models. Three BMI trajectory patterns of low-increasing (38.6%), medium-increasing (47.1%), and high-increasing (14.3%) were detected. The participants in the medium-increasing and high-increasing BMI trajectory groups had HRs of 1.87 (95% CI 1.53-2.28) and 3.41(95% CI 2.71-4.29) for T2DM incidence, respectively. Within the normoglycemic subpopulation, the high-increasing BMI group had an HR of 3.82 (95% CI 2.79-5.24) compared to the low-increasing BMI group, while in the prediabetic subpopulation, the high-increasing BMI group had an HR of 2.93 (95% CI 2.04-4.19) compared to the low-increasing BMI group. Body weight varies in a relatively stable pattern in adulthood over the long-term period. Medium and high-increasing BMI trajectory patterns have a significantly increased risk for future T2DM in both normoglycemic and prediabetic individuals. Identifying BMI trajectory patterns can help healthcare providers in early prediction, risk assessment, and monitoring strategies development for the prevention of T2DM.

BMI trajectories from birth to young adulthood associate with distinct cardiometabolic profiles.

Numerous studies have investigated links between body mass index (BMI) trajectories and cardiovascular risk, yet discrepancies in BMI measurement duration and timing of the cardiovascular-related outcome evaluation have led to inconsistent findings. We included participants from the Swedish birth cohort (BAMSE) and applied latent class mixture modeling to identify BMI trajectories using data of multiple BMI measures (≥ 4 times) from birth until 24-year follow-up (n = 3204). Subsequently, we analyzed the associations of BMI trajectories with lipids (n = 1974), blood pressure (n = 2022), HbA1c (n = 941), and blood leukocytes (n = 1973) using linear regression. We also investigated the circulating levels of 92 inflammation-related proteins (n = 1866) across BMI trajectories. Six distinct BMI groups were identified, denoted as increasing-persistent high (n = 74; 2.3%), high-accelerated increasing (n = 209; 6.5%), increasing-accelerated resolving (n = 142; 4.4%), normal-above normal (n = 721; 22.5%), stable normal (n = 1608; 50.2%), and decreasing-persistent low (n = 450; 14.1%) BMI groups. The increasing-persistent high and high-accelerated increasing BMI groups had higher levels of total cholesterol [mean difference (95% confidence intervals): 0.30 (0.04-0.56) and 0.16 (0.02-0.31) mmol/L], triglyceride, low-density lipoprotein, hemoglobin A1C [3.61 (2.17-5.54) and 1.18 (0.40-1.98) mmol/mol], and low-density lipoprotein/high-density lipoprotein ratios, but a lower level of high-density lipoprotein than the stable normal BMI group. These two groups also had higher leukocyte cell counts and higher circulating levels of 28 inflammation-related proteins. No increased cardiometabolic markers were observed in the increasing-accelerated resolving BMI group. Participants with persistently high or accelerated increasing BMI trajectories from birth to young adulthood have elevated levels of cardiometabolic risk markers at young adulthood than those with stable normal BMI. However, a raised BMI in childhood may not be inherently harmful to cardiometabolic health, provided it does not persist into adulthood.

Shaping childhood obesity: behavioral and environmental risk factors associated with body mass index trajectories between 2 and 9 years in Samoan children.

Pacific children are at high obesity risk, yet the behavioral and environmental factors that contribute to obesity development in this setting remain poorly understood. We assessed associations between childhood risk factors for obesity with body mass index (BMI) trajectories between ages 2-9 years in Samoa. In a prospective cohort of 485 children from 'Upolu, we measured weight and height at ages 2-4 (2015), 3.5-8 (2017-18), and 5.5-11 years (2019-20). Modern dietary pattern adherence was assessed using factor analysis of primary caregiver-reported food frequency questionnaire data. Physical activity was estimated with the Netherlands Physical Activity Questionnaire. Socioeconomic resources were assessed using an 18-item household asset score. Urbanicity was based on village residence. Associations of these risk factors with predicted weight, height, and BMI (at 1-year intervals and velocity) were assessed using multilevel cubic spline regressions. Females had greater adjusted weight velocity with high modern dietary pattern adherence compared to low (p-value for interaction with age spline term 1 = 0.028 and age spline term 2 = 0.007). Starting at age 3 years, children with higher physical activity had higher BMI, but this association was not meaningful up to age 9 (all p-value > 0.05). Males with very high compared to low household assets had higher BMI from age 2 to 4 years (95% CI: 0.26-1.53 kg/m2, p = 0.006) and greater BMI velocity (p-value for interaction with age spline term 2 = 0.001). Males in the urban region had the greatest BMI gain after age 5 compared to the rural region (p-value for interaction with age spline term 2 = 0.014). High, centile-crossing BMI trajectories suggest that obesity prevention and intervention are needed among Samoan children before age 9 years. Positive associations between high modern dietary pattern adherence, greater asset ownership, and urbanization offer initial insights into who, and which behavioral risk factors, should be prioritized in implementing public health solutions.

BMI Trajectories and the Influence of Missing Data

Abstract Introduction Body Mass Index (BMI) trajectories have been estimated in various ways. These estimates are important to understand how BMI develops over time and for use in cost-effectiveness analysis. However, missing data is often stated as a limitation in studies that analyse BMI over time and there is little research into how missing data can influence these BMI trajectories. The aim of this study is to determine how much influence missing data can have when estimating BMI trajectories and to explore the effects this has on subsequent analysis. Methods This study uses data from the English Longitudinal Study of Aging. First, a growth mixture model is used to estimate distinct BMI trajectories in adults over the age of 50. Next, methods that assume data is missing at random (MAR) are used: complete case analysis and multiple imputation. Finally, Diggle Kenward and Roy methods that assume data is missing not at random (MNAR) are implemented. Estimated trajectories from each method are then used to predict the risk of developing type 2 diabetes (T2DM) using discrete-time survival analysis. Results Four distinct trajectories are identified using each of the methods to account for missing data: stable overweight, elevated BMI, increasing BMI, and decreasing BMI. However, the likelihoods of individuals following the different trajectories differs between the different methods. Results show that the influence of BMI trajectory on T2DM is reduced after accounting for missing data. More work is needed to understand which methods for missing data are most appropriate and give the most reliable results. Conclusions Missing data can significantly influence estimations of BMI trajectories. When using BMI trajectories to inform cost-effectiveness analysis or policymaking, missing data should be considered. More research is needed to examine the extent to which accounting for missing data might influence the cost-effectiveness of policies, e.g. weight management interventions. Key messages • Missing data is important when modelling BMI trajectories. • More research is needed to examine the extent to which accounting for missing data might influence the cost-effectiveness of policies, e.g. weight management interventions.

Body mass index trajectories from birth to early adulthood and lung function development.

Limited studies have investigated the influence of body mass index (BMI) trajectories on lung function covering the entire growth period. We conducted a prospective study utilizing data from the Swedish BAMSE birth cohort. Latent class mixture modelling was employed to examine the diversity in BMI z-scores from birth to 24 years of age. Participants with four or more BMI z-scores were included (n=3204, 78·4%). Pre-bronchodilator (BD) spirometry was tested at 8, 16, and 24 years, while post-BD spirometry, multiple-breath nitrogen washout (for lung clearance index, LCI), and urinary metabolomics data were assessed at 24 years. Six distinct BMI development groups were identified. Compared to the stable normal BMI group, the accelerated increasing BMI group exhibited reduced pre- and post-BD FEV1/FVC ratio z scores (β=-0·26, 95% CI=[-0·44, -0·08], and -0·22, [ -0·39, -0·05], respectively), along with elevated LCI (0·30, [0·22, 0·42]) at 24 years. The persistent high BMI group demonstrated lower FEV1, and FVC z scores growth between 16 and 24 years (-0.24, [-0.42, -0.05], and -0.27, [-0.45, -0.01], respectively), and elevated LCI (0·20, [0·03, 0·39]) at 24 years. However, those impairments were not observed in the accelerated resolving BMI group. Conversely, the persistent low BMI group displayed persistently decreased FEV1, and FVC from 8 to 24 years, as well as decreased lung function growth. Additionally, histidine-related metabolites were associated with pre- and post-BD FEV1 (hypergeometric FDR=0.008 and <0.001, respectively). Early interventions aiming for normal BMI during childhood may contribute to improved lung health later in life.

Trajectory of change in body mass index in Parkinson's disease

IntroductionGastrointestinal (GI) symptoms are some of the most common non-motor symptoms in Parkinson's. Weight is a nutritional metric and can be affected by dysfunction of the gastrointestinal (GI) tract. This study aims to explore the change in trajectory of body mass index (BMI) in individuals with Parkinson's over the course of the disease including the prodromal and post-diagnostic periods. MethodsThis was a retrospective longitudinal study of data from participants from the PRIME Parkinson UK cross-sectional study. Participants were included if they had had one or more weights and height recorded in the primary care electronic health record. Results287 patients were initially included but only 234 could be included in the analysis of BMI trajectory. Using a piecewise linear mixed model, we determined that there was a ‘change point’ in BMI trajectory. This occurred on average 3.73 years after diagnosis, when the mean BMI was 26.4 kg/m2. Prior to this change point, the estimated mean rate of change in BMI was −0.09 kg/m2 (95 % credible interval −0.20,0.00 kg/m2) per year. However, after the change point, we observed a more accelerated decline in BMI, with an estimated mean rate of change of −0.34 kg/m2 (95 % credible interval −0.70,-0.07 kg/m2) per year. ConclusionThere was a modest weight loss trajectory in the pre-diagnostic period consistent with clinically stable weight. However, after several years, post-diagnosis BMI loss became more marked. In clinical practice interventions could be targeted at this time point to optimize and maintain nutritional intake.

Adherence to a sustainable diet, measured via the EAT-Lancet Index, predicts incident short-term and long-term cardiovascular disease incidence: the ATTICA study (2002-2022)

Abstract Background/Introduction The World Heart Federation has estimated that air pollution was the second most fatal modifiable risk factor for cardiovascular disease (CVD), causing approximately 5 million CVD deaths in 2021. Diets and food systems can affect the environment; however, research scarcely focuses on the association between planet-healthy dietary habits and CVD risk. Purpose The purpose of this study was to evaluate the adherence to a sustainable diet and CVD incidence during 20 years of follow-up. Methods Participants initially free-of-CVD from the ATTICA study were used (n=1,958). CVD events were assessed at baseline and at all follow-ups (i.e., 2002, 2012, 2022) according to WHO-ICD-10. Adherence to a sustainable diet was assessed via the EAT-Lancet Index (EAT-LI) (Education and Agriculture Together-EAT) (range: 0-42) based on the published algorithm. Results CVD incidence was 16.2% (n=317 incident cases) at 10-years and 35.3% (n=691 incident cases) at 20-years. Mean EAT-LI was: 17.3 (6.7) for the total sample. EAT-LI was lower in those that had a CVD event during the follow-up, i.e., EAT-LI: 10.5 (6.3) vs 18.5 (5.9) at 10-years (p&amp;lt;0.001) and 10.9 (6.4) vs 20.8 (3.8) at 20-years (p&amp;lt;0.001), in participants with and without a CVD event, respectively. In multi-adjusted analyses, adjusted for age, sex, body mass index trajectories, lifestyle trajectories, and clinical factors (diabetes, hypercholesterolemia, hypertension), higher adherence to a sustainable diet was inversely associated with CVD risk at a short-term and a long-term period (i.e., at 10 and 20 years). Specifically, per 1/42 increase in the EAT-Lancet index, CVD risk was reduced by 11% [Hazard ratio-HR: 0.89, 95%Confidence Interval: 0.86-0.93] and by 16% [HR: 0.84, 95%CI: 0.80-0.89] at 10 and 20 years, respectively. Conclusion Future guidelines for CVD prevention should take into account the sustainable nature of dietary habits, to efficiently nourish the growing world population, and concomitantly protect heart and planet health.

Infant BMI trajectories as early risk markers of poor psychosocial health in preadolescence

BackgroundCommon mental disorders often emerge during childhood and adolescence, and their prevalence is disproportionately elevated among those affected by obesity. Early life growth patterns may provide a useful target for primordial prevention; however, research is lacking. Therefore, this study aimed to identify distinct body mass index (BMI) trajectories during the first year of life and to assess their associations with psychosocial outcomes in preadolescence (9–13 years).MethodsData were obtained from n = 1778 Greek children (9–13 years). Infant anthropometric data were obtained from paediatric health records and BMI trajectories during the first year of life were estimated using group-based trajectory modelling. Preadolescent emotional functioning, self-esteem, body image dissatisfaction and dieting behaviours were self-reported via validated questionnaires. Associations were estimated using binary and ordinal logistic regression, adjusted for key confounders.ResultsFour BMI trajectories were identified: low (26.7%), average (41.8%), high (25.2%), and very high (6.4%). Children belonging to the very high trajectory had greater odds of body image dissatisfaction (OR: 1.62, 95%CI: 1.11, 2.38), dieting behaviour (OR: 1.49, 95%CI: 1.01, 2.20) and restrained eating (OR: 1.69 95%CI: 1.14, 2.52) than children belonging to the average trajectory. Body image dissatisfaction was also greater in children belonging to the high trajectory (OR: 1.40, 95%CI: 1.11, 1.76). However, infant BMI trajectories did not significantly predict childhood emotional functioning or self-esteem status.ConclusionInfants with BMI growth in the high reference ranges had poorer psychosocial outcomes in preadolescence. Whilst further research is needed to replicate these findings, monitoring early infant growth trajectories may allow for early stratification of infants at risk of poor psychosocial outcomes.

Body mass index trajectories and time in target range after delivery and long-term type 2 diabetes risk in women with a history of gestational diabetes mellitus.

This study aims to determine whether postpartum body mass index (BMI) trajectories and its time in target range (TTR) are associated with long-term type 2 diabetes risk in women with a history of gestational diabetes mellitus (GDM). The present study included 1057 women with a history of GDM who participated in the Tianjin Gestational Diabetes Mellitus Prevention Program (TGDMPP). Oral glucose tolerance tests or physician-diagnosed information were used to diagnose type 2 diabetes after a median follow-up period of 8.47 years. Latent class modelling was applied to identify trajectories of BMI after delivery. TTR was defined as the proportion of time that BMI was within the standard range (18.5 ≤ BMI < 24.0 kg/m2). The associations of BMI trajectories and TTR with type 2 diabetes risk were analysed using multivariable Cox modelling. Five distinct trajectories of postpartum BMI were identified. Compared with low-stable class, the multivariable-adjusted hazard ratios of type 2 diabetes were 2.02 (95% confidence interval 0.99-4.10) for median-stable class, 3.01 (1.17-7.73) for high-stable class, 2.15 (0.63-7.38) for U-shape class and 7.15 (2.08-24.5) for inverse U-shape class (p for trend = 0.012), respectively. Multivariable-adjusted hazard ratios of type 2 diabetes associated with postpartum BMI TTR of 100%, >43.4%-<100%, >0%-≤43.4% and 0% were 1.00, 1.84 (0.72-4.73), 2.75 (1.23-6.15) and 2.31 (1.05-5.08) (p for trend = 0.039), respectively. Postpartum BMI trajectories of high-stable and inverse U-shape class as well as lower TTR were associated with an increased risk of type 2 diabetes among women with a history of GDM. Reducing BMI to a normal range in the early postpartum period and maintaining stable over time could attenuate the development of long-term type 2 diabetes.

Sex-specific associations between body mass index trajectories and risk of hypertension

BackgroundAlthough it is well established that obesity is a risk factor for hypertension, the effect of distinct long-term patterns of body mass index (BMI) on blood pressure (BP) in later life is poorly understood.MethodsBased on the China Health and Nutrition Survey, we analyzed 2920 participants aged 3–17 years with initial normal BP at baseline (1991–2011), who were followed up for the development of hypertension (1993–2015). The group-based trajectory model was applied to identify BMI trajectories, and Cox regression was used to assess their associations with hypertension risk. Stratified analyses were conducted to explore differences across subgroups.ResultsDuring an average follow-up time of 11.20 (7.69) years for males and 7.20 (5.21) years for females, 339 males and 212 females were identified with hypertension, respectively. Three BMI trajectories were identified: low-increasing (60.58% of males and 73.03% of females), moderate-increasing (33.08% of males and 24.22% of females), and high-increasing (6.34% of males and 2.76% of females). Our study found a significant positive association between a higher BMI trajectory and hypertension risk in males (all P for trend < 0.05). Specifically, males in the high-increasing BMI group had a higher risk of hypertension compared with those in the low-increasing group (HR = 1.76, 95% CI: 1.04–2.97). Stratified analyses revealed stronger associations among smokers, drinkers, and inactive individuals.ConclusionOur findings suggest that maintaining a normal BMI and healthy lifestyle from childhood may lower subsequent risk of hypertension.

Associations of 1.5- and 3-year phthalate exposure levels with early adiposity rebound and overweight/obesity in Japanese children: An adjunct study of the Japan Environment and Children's Study

The relationship between early childhood phthalate exposure and early adiposity rebound (EAR) is unclear. This study aimed to investigate the association between 1.5- and 3-year phthalate exposure and EAR and overweight/obesity in 7.5-year-old Japanese children. A total of 452 mother–child pairs were enrolled from the Aichi Regional Cohort of the Japan Environment and Children's Study. The children were followed up at birth and at 1.5, 2, 3, 4, 5, 6, and 7.5 years of age for physical examination. Human biomonitoring of 16 urinary metabolites of eight phthalates was performed at 1.5 and 3 years of age. Latent class mixed models, binary logistic regression, and quantile g-computation were performed to identify body mass index (BMI) trajectories and investigate the relationships of single or mixed phthalate exposure with EAR and overweight/obesity. A one-unit increase in log10-transformed 3-year-old Σdi(2-ethylhexyl) phthalate (ΣDEHP) exposure levels was significantly associated with 6-year-old BMI in girls. The 1.5-year mono-iso-butyl phthalate and 3-year Σdi-isodecyl phthalate exposure levels were significantly associated with the repeated measures of longitudinal BMIs in girls. Single phthalate exposure showed null associations with EAR or overweight/obesity in the 7.5-year-old children. Σdi-isononyl phthalate, ΣDEHP, and mono-n-butyl phthalate exhibited the highest proportion of partial positive weights of being in the EAR trajectory after confounder adjustment. Phthalate mixture exposure in 1.5- and 3-year-old children was not significantly associated with EAR. Early childhood phthalate exposure was not related to EAR or overweight/obesity in 7.5-year-old Japanese children. However, few phthalates were positively associated with longitudinal BMIs in girls.

Association of maternal pre-pregnancy BMI, gestational weight gain, and gestational diabetes mellitus with BMI trajectory in early childhood: a prospective cohort study

Objective: To examine the associations of pre-pregnancy body mass index (BMI), gestational weight gain, and gestational diabetes mellitus (GDM) with early childhood BMI trajectories. Methods: A total of 1 227 mother-child pairs from the Peking University Birth Cohort in Tongzhou were included in this study. In the cohort, maternal pre-pregnancy weight, height, gestational weight gain, and GDM diagnosis were collected. The children were followed up at birth and at 1, 3, 6, 9, 12, 18, 24, 30, and 36 months of age to obtain height/length and weight data. The longitudinal data-based k-means clustering algorithm was used to identify early childhood BMI trajectory groups. The associations of maternal pre-pregnancy BMI, gestational weight gain, and GDM with early childhood BMI trajectories were analyzed using the logistic regression model. We further explored whether there is an interaction effect between pre-pregnancy overweight/obesity and excessive gestational weight gain on the risk of the high BMI trajectory in early childhood through multiplicative and additive interaction analyses. Results: The prevalence rates of overweight and obesity before pregnancy were 21.2% (260 cases) and 6.6% (81 cases) respectively. The prevalence of excessive gestational weight gain and GDM was 57.7% (708 cases) and 30.9% (379 cases). The early childhood BMI trajectories were named low, medium, and high trajectories, accounting for 30.5%, 45.4% and 24.1%, respectively. After controlling potential confounding factors, it was found that pre-pregnancy overweight (OR=1.54, 95%CI: 1.12-2.12), obesity (OR=2.33, 95%CI: 1.41-3.85), and excessive gestational weight gain (OR=1.47, 95%CI: 1.10-1.97) were risk factors for being in the high BMI trajectory in early childhood. GDM was not significantly associated with early childhood BMI trajectories (P>0.05). Compared with the independent effects of pre-pregnancy overweight/obesity (OR=1.90, 95%CI: 1.17-3.09) and excessive gestational weight gain (OR=1.45, 95%CI: 1.03-2.04), the risk of being in the high BMI trajectory in early childhood was greater when the two factors coexisted (OR=2.38, 95%CI: 1.60-3.54). However, both the multiplicative and additive models showed no interaction effect between pre-pregnancy overweight/obesity and excessive gestational weight gain. Conclusions: Maternal pre-pregnancy overweight/obesity and excessive gestational weight gain are independent risk factors for children being in the high BMI trajectory in early childhood, providing scientific evidence for obesity prevention.

Trend analysis, gender-specific patterns, and age dynamics of childhood and adolescent obesity: insights from the Tehran lipid and glucose study

BackgroundChildhood and adolescent obesity pose significant challenges to global health, with escalating prevalence and associated short- and long-term health consequences. This longitudinal study leveraged data from the Tehran Lipid and Glucose Study (TLGS) to investigate the trends of obesity among Tehranian children and adolescents over a 21-year period.MethodsUtilizing data from TLGS phases I to VII (1999–2021), we included 3845 participants aged 3–18 years at the beginning of phase I. Anthropometric measures, including height and weight, were collected, and body mass index (BMI) was calculated. Childhood obesity (2–19 years) was defined as BMI-for-age > 2SD based on World Health Organization (WHO) standards, and adult obesity was defined as BMI ≥ 30. Descriptive statistics, trend analysis, prevalence calculations, odds ratios, and interaction analyses were employed for data interpretation.ResultsThe mean BMI increased from 18.46 ± 4.37 kg/m² at Phase I to 26.36 ± 5.03 kg/m² at Phase VII. Boys exhibited a greater increase in BMI than girls, and age at study entry influenced BMI trajectories. The prevalence of obesity rose from 6.4% at Phase I to 21.5% at Phase VII, with a more pronounced increase in boys. Odds ratios for obesity steadily increased across phases, indicating a growing risk. Interaction analyses revealed age-specific dynamics, with older participants demonstrating lower odds ratios initially but higher odds ratios in later phases.ConclusionOur study shows a worrisome increase in childhood obesity among Tehranian children and adolescents over 21 years. Sex- and age-specific trends emphasize the necessity for targeted interventions, informing policymakers, healthcare practitioners, and educators regarding public health strategies and interventions against the obesity epidemic.

Body mass index across development and adolescent hair cortisol: the role of persistence, variability, and timing of exposure.

Research suggests a putative role of the glucocorticoid stress hormone cortisol in the accumulation of adiposity. However, obesity and weight fluctuations may also wear and tear physiological systems promoting adaptation, affecting cortisol secretion. This possibility remains scarcely investigated in longitudinal research. This study tests whether trajectories of body mass index (BMI) across the first 15 years of life are associated with hair cortisol concentration (HCC) measured two years later and whether variability in BMI and timing matter. BMI (kg/m2) was prospectively measured at twelve occasions between age 5 months and 15 years. Hair was sampled at age 17 in 565 participants. Sex, family socioeconomic status, and BMI measured concurrently to HCC were considered as control variables. Latent class analyses identified three BMI trajectories: "low-stable" (59.2%, n = 946), "moderate" (32.6%, n = 507), and "high-rising" (8.2%, n = 128). BMI variability was computed by dividing the standard deviation of an individual's BMI measurements by the mean of these measurements. Findings revealed linear effects, such that higher HCC was noted for participants with moderate BMI trajectories in comparison to low-stable youth (β = 0.10, p = 0.03, 95% confidence interval (CI) = [0.02-0.40]); however, this association was not detected in the high-rising BMI youth (β = -0.02, p = 0.71, 95% CI = [-0.47-0.32]). Higher BMI variability across development predicted higher cortisol (β = 0.17, p = 0.003, 95% CI = [0.10-4.91]), additively to the contribution of BMI trajectories. BMI variability in childhood was responsible for that finding, possibly suggesting a timing effect. This study strengthens empirical support for BMI-HCC association and suggests that more attention should be devoted to BMI fluctuations in addition to persistent trajectories of BMI.

Body Mass Index Trajectories among Adolescents and Young Adults with CKD

Body Mass Index Trajectories among Adolescents and Young Adults with CKD

A growth curve model to estimate longitudinal effects of parental BMI on Indonesian children's growth patterns.

The global surge in childhood obesity is also evident in Indonesia. Parental body mass index (BMI) values were found to be one of the major determinants of the increasing prevalence of childhood obesity. It is uncertain if parental BMI during their offspring's childhood significantly affects their children's BMI trajectories into adulthood. We aimed to investigate the influence of parental BMI Z-scores on BMI trajectories of Indonesian school-aged children, with a focus on sex-specific effects. This study utilized data from the Indonesian Family Life Survey and tracked the same respondents over four time points, from wave 2 (1997-1998) to wave 5 (2014-2015). The sample of this study consisted of children aged 5-12 years in wave 2 for whom height and weight data were available. We utilized a two-level growth curve model to account for the hierarchical structure of the data, with time nested within individual children. Fathers' BMI Z-scores in wave 2 had a pronounced influence (β = 0.31) on female children's BMI Z-scores compared to the influence of mothers' BMI Z-scores (β = 0.17). Mothers' BMI Z-scores in wave 2 showed a stronger positive association with male children's BMI Z-scores (β = 0.22) than did the father's BMI Z-scores (β = 0.19). A significant interaction of fathers' BMI Z-scores and years of follow-up was found for male children. As male children's BMI Z-scores increased by year, this effect was stronger in those whose fathers' BMI Z-scores were at a higher level. In conclusion, we found that parental BMI values profoundly influenced their children's BMI trajectories.

Impact of adiposity indices changes across the lifespan on risk of diabetes in women: trajectory modeling approach

AimsThe impact of life-course different adiposity indices on diabetes mellitus (DM) is poorly understood. We aimed to do trajectory analysis with repeated measurements of adiposity indices in the development of DM among women across the lifespan.MethodsThis study prospectively investigated the 1,681 population of Tehran Lipid and Glucose Study. At baseline, all individuals were free of diabetes. Trajectory analysis was used to identify homogeneous distinct clusters of adiposity indices trajectories and assign individuals to unique clusters.ResultsOf the 1681 healthy women, 320 progressed to the DM. Three distinct body mass index (BMI) trajectories and 2 distinct trajectories of other adiposity indices (waist circumstance (WC), conicity index (C-index), and body roundness index (BRI)) were chosen as the best fitting of the latent class growth mixture model. In the adjusted model, total participants [HR (CI 95%): 2.83 (2.05, 3.91); p < 0.001], and menopause [1.35 (1.10, 2.11); p = 0.001] and reproductive-age women [2.93 (1.80, 4.78); p = 0.003] of the high BMI trajectory compared to the ones in the low trajectory of BMI were more likely to develop DM. The high BRI in menopause had a significantly higher risk of DM compared to the low trajectory. In menopause (1.80 (1.26, 2.58)) and reproductive-age women (4.32 (2.49, 7.47)) with high trajectory of C-index, the DM risk decreased after adjustment.ConclusionsThe risk of DM was greater for high BMI, WC, C-index, and BRI trajectories than for lower trajectories. Hence, the development of general, abdominal, and visceral obesity trajectories in the prevention of DM should be considered by clinicians.

212 Multi-trajectory analysis of changes in physical activity, BMI and cardiorespiratory fitness in adolescence

Abstract Purpose Over the past four decades, the worldwide prevalence of obesity has nearly tripled, with childhood obesity being now more common than ever. Furthermore, children and adolescents with overweight or obesity are at a higher risk of retaining this condition into adulthood (Lobstein et al., 2015). Previous studies have shown that larger increase in body mass index (BMI) during adolescence is associated with less improvements in cardiorespiratory fitness (CRF) and steeper decline in moderate to vigorous physical activity (MVPA) (Kolunsarka et al., 2021). However, the trajectories of these three variables during adolescence are diverse. Therefore, this study aimed to identify and investigate adolescents with similar concurrent changes in MVPA, CRF and BMI throughout adolescence. Methods In this four-year longitudinal study (2017-2021), device-measured MVPA, BMI and CRF data were collected annually from 1157 participants (Mage = 11.37 ± 0.37). A multivariate trajectory analysis was used to identify adolescents who share similar BMI, MVPA and CRF trajectories over four years. Results Three distinct groups were identified and labelled according to BMI trajectories. The ‘persistently normal’ group (86%) exhibited the highest baseline levels of CRF and MVPA, with significant increases in CRF and a concurrent decrease in MVPA. Conversely, the ‘improving from high’ group (5%) demonstrated a significant increase in CRF and a non-significant (p = 0.07) increase in MVPA. In contrast, the ‘progressing to very high’ group (9%) showed no significant changes in either MVPA or CRF. Conclusion These findings underscore the critical importance of early identification and targeted interventions to mitigate the risk of accelerated weight gain, insufficient physical activity and declining fitness during adolescence. Funding Source This study was funded by the Strategic Research Council within the Academy of Finland within the project SchoolWell, and the Finnish Ministry of Education and Culture.

Early childhood executive control modulates negative affectivity's role in increasing adolescent body mass index trajectories.

Executive control and temperament have been associated with pediatric obesity. However, interactions between these constructs in relation to future weight outcomes have not been investigated. This longitudinal study examined early childhood executive control, early temperament (negative affectivity and surgency), and their interactions as predictors of adolescent BMI trajectories. At age 5.25, children (N = 229) completed executive control tasks, and parents completed the Child Behavior Questionnaire to assess temperament. BMI was calculated annually between ages 14-17. Greater early negative affectivity predicted more positive BMI growth. Although early childhood executive control was not associated with BMI growth, greater negative affectivity predicted greater BMI escalation at average and below average executive control abilities. For children without robust executive control abilities early in development, negative affectivity may be a risk factor for accelerated adolescent BMI growth. Targeted assessment of early risk factors may be useful for childhood obesity prevention efforts.