Height, weight, and body mass index trajectories and their correlation with functional outcome assessments in young males with Duchenne muscular dystrophy.

To examine the factors influencing height, weight, and body mass index (BMI) z-scores, and the relationship between them and motor performance, in boys with Duchenne muscular dystrophy (DMD). This was a randomized, double-blind, parallel group trial involving 32 study sites across five countries. Height, weight, BMI z-scores, and clinical outcome assessments (COAs)-rise from supine velocity, 10-m walk/run velocity, NorthStar Ambulatory Assessment, and 6-minute walk test-were analysed in 4-year-old to 7-year-old boys with DMD randomized to 0.75 mg/kg/day prednisone, 0.75 mg/kg/day intermittent prednisone, or 0.90 mg/kg/day deflazacort in the FOR-DMD study. Trajectories were modelled using a linear mixed-effects model and correlations were explored through Spearman's partial correlations. In 194 boys with DMD, higher height at glucocorticoid initiation was associated with slower growth (p < 0.001) and older age was associated with increased weight gain (p = 0.001). Glucocorticoid type and regimen influenced height and weight trajectories but not BMI. Changes in height and weight z-scores were negatively correlated with COAs (p < 0.05 in all cases). Correlations were weak 3 years after glucocorticoid initiation and moderate after 5 years (closer to the age of loss of ambulation). Changes in anthropometric measures after glucocorticoid initiation are associated with COA performance and larger correlations closer to the age of loss of ambulation. This emphasizes the need for weight management strategies and discussions that support treatment.

BackgroundTaiwan has gone through rapid industrialization, urbanization and economic growth in the 20th and early 21st centuries. Therefore, the population has experienced significant changes in the physical and social environment during the life course, which may affect the overall adiposity. Our aim was to examine the age trajectories of height, weight and body mass index (BMI) in the Taiwanese population and to explore the influences of sex, birth cohort and education.MethodsThe sample comprised 572,358 residents between 20 and 94 years of age in Taiwan who attended at least one health examination during 1996 to 2017 in a cohort study. Repeated measures of body weight and height were collected using an auto-anthropometer. We conducted a series of linear mixed-effects growth curve models to examine the trajectory of height, weight, and BMI across the life course with stratification by sex.ResultsAge-related trajectories of BMI differed between men and women and stronger cohort effects were observed among men, with younger cohorts having higher BMI. After holding cohort and age variables constant, men with junior high or lower education were shorter, thinner and had higher BMI than men with university or higher education (effect sizes: − 3.138 cm, p < 0.001; − 2.277 kg, p < 0.001; 0.121 kg/m2, p < 0.001, respectively). Women with junior high or lower education were shorter, heavier and had higher BMI than women with university or higher education (effect sizes: − 2.368 cm, p < 0.001; 2.417 kg, p < 0.001; 1.691 kg/m2, p < 0.001, respectively). The educational disparities in BMI were found to be larger among women.ConclusionsOur findings suggest that younger generations, especially men, and lower educational level individuals, particularly women, have increasing levels of BMI. The influence of age and cohort effects together with sex and educational disparities on adiposity should be highlighted when designing future interventions and policies regarding overweight and obesity.

Background:The gene (Huntingtin or HTT) causing Huntington’s disease (HD) is vital for development and is expressed throughout the brain and body lifelong. The mutant form (mHTT) may influence growth and development.Objective:To determine the impact of mHTT on human measures of growth, including height, weight, and body mass index (BMI), between child and adolescent carriers of mHTT and control peers.Methods:Children ages 6–18 years of age (n = 186) at risk for HD were enrolled in the KidsHD study. For research purposes only, genetic testing was performed to classify participants as Gene-Expanded (GE = 78) or as Gene Non-Expanded (GNE = 108). Outcome measures included height, weight, and body mass index (BMI). Mixed models were used to determine if non-linear age trends differed between groups for BMI, height, and weight.Results:Differences were seen in the trajectory of BMI in which the GE group reached a plateau in late adolescence with no further increase, compared with a nearly linear increase in the GNE group. There was a significant sex interaction pattern where GE males were taller than GNE males in adolescence, in the presence of similar weight. In contrast, GE females weighed significantly less than their GNE counterparts in adolescence, in the presence of similar height.Conclusion:Measures of growth are abnormal in child and adolescent carriers of mHTT, decades before HD onset. Although further studies are needed for replication, the current findings suggest that developmental aberrations may be systemic and a vital part of disease pathology.

Associations of birth size with BMI trajectories and fluctuation across adolescence and adulthood: A longitudinal study of two Finnish twin cohorts.

Participants were 526 mother-child pairs, born ≥37 weeks. Cotinine was measured at ~27 weeks gestation. Whole pregnancy and trimester-specific O3 and PM2.5 were estimated via. inverse-distance weighted interpolation from stationary monitors. Neonatal adiposity (fat mass percentage) was measured via. air displacement plethysmography. Child weight and length/height were abstracted from medical records. Interaction was assessed by introducing cotinine (<31.5 vs. ≥31.5 ng/mL [indicating active smoking]), O3/PM2.5 (low [tertiles 1-2] vs. high [tertile 3]), and their product term in linear regression models for birth weight and neonatal adiposity and mixed-effects models for BMI trajectories. The rate of BMI growth among offspring jointly exposed to maternal smoking and high PM2.5 (between 8.1 and 12.7 μg/m3) in the third trimester was more rapid than would be expected due to the individual exposures alone (0.8 kg/m2 per square root year; 95% CI = 0.1, 1.5; P for interaction = 0.03). We did not detect interactions between maternal smoking and O3 or PM2.5 at any other time on birth weight, neonatal adiposity, or BMI trajectories. Although PM2.5 was generally below the EPA annual air quality standards of 12.0 μg/m3, exposure during the third trimester may influence BMI trajectories when combined with maternal smoking.

Objective: Childhood disadvantage is associated with a higher risk of adult obesity, but little is known about its associations with body mass index (BMI) trajectories during adulthood. This study aimed first to identify adulthood BMI trajectories, and second to investigate how childhood disadvantage is associated with trajectory group membership. Methods: Data from the Helsinki Health Study, a longitudinal cohort study of initially 40- to 60-year-old employees of the City of Helsinki in Finland, were used. The baseline survey was conducted in 2000–2002, and similar follow-up surveys in 2007, 2012, and 2017. Based on self-reported BMI, participants’ (n =5,266; 83% women) BMI trajectories, including their retrospectively reported BMI at the age of 25 years, were examined. Data on childhood disadvantage, including parental education and 7 types of childhood adversity (their own serious illness; parental divorce, death, mental disorder, or alcohol problems; economic difficulties at home; and peer group bullying) before the age of 16 years, were obtained from the baseline survey. Group-based trajectory modeling was used to identify BMI trajectories, and multinomial logistic regression to analyze the odds for trajectory group membership for the disadvantage variables. Results: Four ascending BMI trajectories in women and men were found: persistent normal weight (trajectory 1; women 35% and men 25%), normal weight to overweight (trajectory 2; women 41% and men 48%), normal weight to class I obesity (trajectory 3; women 19% and men 23%) and overweight to class II obesity (trajectory 4; women 5% and men 4%). Compared to trajectory 1, women with multiple adversities and repetitive peer bullying in childhood had greater odds of belonging to trajectories 3 and 4, whereas men with parental alcohol problems had greater odds of belonging to trajectory 4. For women and men, a low level of parental education was associated with a higher-level BMI trajectory. Conclusions: Low parental education for both genders, multiple adversities and repetitive peer bullying in childhood among women, and parental alcohol problems among men increased the odds of developing obesity during adulthood. Further studies are needed to clarify how gender differences modify the effects of childhood disadvantage on adult BMI trajectories.

Trajectories of Growth Associated With Long-Term Stimulant Medication in the Multimodal Treatment Study of Attention-Deficit/Hyperactivity Disorder

Background/objectivesWe aimed to determine whether serum uric acid (SUA) and body mass index (BMI) trajectories in childhood have longitudinal association with liver enzymes in adolescence.MethodsWe conducted a study using data from the Ewha Birth and Growth Cohort. Individual trajectories of SUA (n = 203) and BMI (n = 206) from 5, 7, and 9 years were defined by group-based trajectory modeling. Also, liver function enzymes were collected at 11 to 12 year of age (Aspartate Aminotransferase [AST], Alanine transaminase [ALT], and Gamma-glutamyl transferase [γ–GTP]) (n = 206). Using a generalized linear model, the effects of SUA trajectory and BMI trajectory on liver function enzymes were assessed. We also assessed the interaction effect of SUA and BMI trajectories on liver enzymes.ResultsFor trajectory patterns, both SUA and BMI were classified into two distinct groups (High or Low). Both trajectory of SUA and BMI in childhood were positively associated with levels of liver enzymes at 11–12 years of age. The results showed that the combined effect of SUA and BMI trajectories on liver enzymes had a higher means in high-risk group (high SUA–high BMI trajectories group) than in low-risk group (low SUA-low BMI trajectories group) for ALT and γ–GTP, respectively. It remained significant association when adjusted for covariates. In addition, the interaction of BMI and SUA trajectories showed a significant synergistic effect.ConclusionElevated childhood SUA and BMI trajectories are associated with increased liver enzymes in beginning of adolescent. This finding suggesting that early interventions in SUA and BMI may need for optimization of liver enzymes as potential marker for development of related disease in later life.

BackgroundA more comprehensive assessment of growth and nutrition in children is required in China due to rapid socioeconomic processes. We aimed to investigate height and body mass index (BMI) trajectories from 1975 to 2015 and the prevalence of stunting and obesity in 2016 among children in Chinese cities.MethodsA total of 904,263 children from birth to 6.9 years were collected from a series of nationally representative surveys in China. Height and BMI trajectories and prevalence of stunting, underweight, overweight and obesity were assessed.ResultsThe average height level of Chinese urban children under 7 years presented a positive secular trend from 1975 to 2015; however, a slowing tendency occurred in 2005‒2015. An apparent increase was observed at the 5th, 50th and 95th percentiles of BMI in urban children aged 3 years and older, with a more prominent increase at the 95th percentile. The total prevalence of stunting and underweight under 7 years was 1.4% and 2.0%, respectively. The total prevalence of overweight and obesity under 7 years was 12.6% and 4.3%, respectively, with 12.7% and 4.9% for boys, 12.6% and 3.6% for girls, 12.1% and 4.0% in urban areas and 13.1% and 4.5% in suburban rural areas.ConclusionsThe average height level of Chinese urban children has reached World Health Organization child growth standards since 2005 and presented a slowing tendency in secular trend in 2005‒2015. More attention and efforts and public health interventions should be urgently made to combat overweight and obesity among preschool children.6vUvDz8DH1EFmJqaqHYybhVideo

The impact of lifetime body mass index (BMI) trajectories on adult lung function abnormalities has not been investigated previously. We investigated associations of BMI trajectories from childhood to mid-adulthood with lung function deficits and COPD in mid-adulthood. Five BMI trajectories (n = 4194) from age 5 to 43 were identified in the Tasmanian Longitudinal Health Study. Lung function outcomes were defined using spirometry at 45 and 53 years. Associations between these BMI trajectories and lung function outcomes were investigated using multivariable regression. Compared to the average BMI trajectory, the child's average-increasing BMI trajectory was associated with greater FVC decline from 45 to 53 years (β = -178 mL; 95% CI -300.6, -55.4), lower FRC, ERV and higher TLco at 45 years, lower FVC (-227 mL; -345.3, -109.1) and higher TLco at 53 years. The High BMI trajectory was also associated with lower FRC, ERV and higher TLco at 45 years, while spirometric restriction (OR = 6.9; 2.3, 21.1) and higher TLco at 53 years. The low BMI trajectory was associated with an obstructive picture: lower FEV1 (-124 mL; -196.4, -51.4) and FVC (-91 mL; -173.4, -7.7), and FEV1/FVC (-1.2%; -2.2, -0.1) and higher ERV and lower TLco at 45 and 53 years. A similar pattern was found at 53 years. No associations were observed with spirometrically defined COPD. Our findings revealed contrasting lung function abnormalities were associated with high, subsequently increasing, and low BMI trajectories. These results emphasise the importance of tracking changes in BMI over time and the need to maintain an average BMI trajectory (BMI-Z-score 0 at each time point) throughout life.

Children exposed to gestational diabetes mellitus (GDM) in utero are at high risk of developing overweight and obesity, but their postnatal growth trajectories and risk profiles remain unclear. We aimed to identify distinct body mass index (BMI) trajectories from birth to 10 years of age in children exposed to GDM and to explore their associations with infant and maternal characteristics. This nationwide cohort study linked data from Danish registries on 15 509 children exposed to GDM in utero, born in Denmark from January 2008 to October 2019. We applied latent class trajectory modeling to identify distinct BMI trajectories. Associations of BMI trajectories with infant and maternal characteristics were analyzed using multiple linear regression. We identified 3 distinct BMI trajectories characterized by a "normal" (60%), a "late accelerating" (28%) and an "early accelerating" (12%) BMI trajectory, the 2 latter at risk of overweight and obesity, respectively, at age 10 years, relative to World Health Organization child growth standards. Children in the "late accelerating" BMI trajectory were more often born large for gestational age (P < .001). More children in the "early accelerating" BMI trajectory were boys, born small for gestational age, and had mothers with a higher pre-pregnancy BMI compared to the other groups (P < .001). Children exposed to GDM in utero differ widely in their BMI trajectory. The detection of risk profiles based on early BMI growth and infant and maternal characteristics provides an opportunity for future targeted care and prevention.

Per- and polyfluoroalkyl substances in umbilical cord serum and body mass index trajectories from birth to age 10 years: Findings from a longitudinal birth cohort (SMBCS)

ObjectiveThis study aimed to identify body mass index (BMI) trajectories and their predictors in Australian children by their maternal immigrant status.MethodsData on 4142 children aged 2–3 years were drawn from...

Body mass index (BMI) trajectories that improve over the lifecourse result in better cardiometabolic profiles, but only a small proportion of children of an unhealthy weight show improving BMI trajectories. This study aimed to examine the childhood factors related to diverging BMI trajectories from childhood into adulthood using data from the Childhood Determinants of Adult Health study. A convergent parallel mixed methods design was used. Quantitative data (n=2206) came from the first (2004-06) and second (2009-11) adult follow-ups of 8498 Australian children (7-15 years) assessed in 1985. Using BMI z-scores, group-based trajectory modelling identified five trajectory groups: Persistently Low, Persistently Average, High Decreasing, Average Increasing and High Increasing. Qualitative data (n=50) were collected from a sub-group (2016; 38-46 years). Semi-structured interviews with 6-12 participants from each BMI trajectory group focused on individual, social and environmental influences on weight, diet and physical activity across the lifecourse. Log multinomial regression modelling estimated relative risks of trajectory group membership across childhood demographic, behavioural, health, parental and school factors. Qualitative data were thematically analysed using a constant comparative approach. Childhood factors influenced BMI trajectories. Paternal education, main language spoken, alcohol and self-rated health were significant quantitative childhood predictors of BMI trajectory. A distinct 'legacy effect' of parental lifestyle influences during childhood was apparent among interview participants in the Stable and High Decreasing groups, a strong and mostly positive concept discussed by both men and women in these groups and persisting despite phases of unhealthy behaviours. In contrast, the 'legacy effect' was much weaker in the two Increasing BMI groups. This study is the first to simultaneously identify important quantitative and qualitative childhood factors related to divergent BMI trajectories, and to observe a legacy effect of parents' lifestyle behaviours on divergent BMI trajectories. This work provides direction for further exploration of the factors driving divergent BMI trajectories.

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.