Body Mass Index Trajectories Research Articles

Body Mass Indices of Girls with and without ADHD: Developmental Trajectories from Childhood to Adulthood

ABSTRACT Objective We examined the predictive relation between childhood-diagnosed ADHD and trajectories of body mass index (BMI) from childhood to adulthood in an all-female sample, accounting for socioeconomic status (SES), childhood comorbidities (e.g., depression/anxiety), and stimulant usage. Childhood executive functioning (i.e., planning, sustained attention, and response inhibition) was also evaluated as a possible predictor of BMI trajectories. Method We utilized longitudinal data from a full sample of 140 girls diagnosed with ADHD in childhood and 88 comparison girls matched on age and ethnicity. Girls were 6–12 years old at the first assessment and followed prospectively for 16 years. Data were collected on their BMI and stimulant medication usage across four evaluation waves. Using latent growth curve modeling, we evaluated the BMI trajectories of girls with ADHD and the comparison sample from childhood to adulthood. Results Although there was no significant difference in initial childhood BMI, girls with ADHD increased in BMI at a significantly faster rate than comparison girls across development, even when adjusting for covariates. Significant differences in BMI first emerged in adolescence; by adulthood, 40.2% of the ADHD sample met criteria for obesity versus 15.4% of the comparison sample. When covarying ADHD diagnosis, executive functioning measures were not significantly predictive of BMI increase. Adjusting for stimulant medication usage within the ADHD sample did not alter core findings. Conclusions We discuss health-related implications for girls with ADHD, potential underlying mechanisms, and how our findings may inform both ADHD and obesity interventions.

Body mass index trajectories and the risk for Alzheimer\u2019s disease among older adults

The effect of body mass index (BMI) changes and variability on the risk for Alzheimer’s disease (AD) remains unclear. We analyzed 45,076 participants, whose BMI were measured on phase 1 (2002–2003), phase 2 (2004–2005), and phase 3 (2006–2007), of the Korean National Health Insurance Service-Health Screening Cohort. We evaluated the effect of 2- and 4-year BMI changes and BMI variability on the risk of AD using Cox regression models. In men, association between 2-year BMI changes, BMI variability, and the risk of AD was not significant. Risk of AD was higher in men whose BMI had decreased 10.1–15.0% over 4 years. In women, aHRs and 95% CIs for AD were 1.14 (1.02–1.29), 1.44 (1.17–1.79), and 1.51 (1.09–2.09) when 2-year BMI loss was 5.1–10.0%, 10.1–15.0%, and > 15.0%. The HRs for AD in women significantly increased when 4-year BMI loss was > 5.0%. The aHR and 95% CI for AD was 1.31 (1.17–1.46) in the 4th quartile of average successive variability (ASV) compared with the 1st quartile of ASV in women. BMI loss over 2- and 4-year period was associated with increased risk for AD, and risk increased in women with higher BMI variability. Appropriate body weight management is recommended to prevent AD.

Latent Class Trajectory Modeling of Adult Body Mass Index and Risk of Obesity-Related Cancer: Findings from the Melbourne Collaborative Cohort Study.

Obesity increases the risk of 13 cancer types. Given the long process of carcinogenesis, it is important to determine the impact of patterns of body mass over time. Using data from 30,377 participants in the Melbourne Collaborative Cohort Study, we identified body mass index (BMI) trajectories across adulthood and examined their association with the risk of obesity-related cancer. Participants completed interviews and questionnaires at baseline (1990-1994, age 40-69 years), follow-up 1 (1995-1998), and follow-up 2 (2003-2005). Body mass was recalled for age 18 to 21 years, measured at baseline, self-reported at follow-up 1, and measured at follow-up 2. Height was measured at baseline. Cancer diagnoses were ascertained from the Victorian Cancer Registry and the Australian Cancer Database. A latent class trajectory model was used to identify BMI trajectories that were not defined a priori. Cox regression was used to estimate HRs and 95% confidence intervals (CI) of obesity-related cancer risks by BMI trajectory. Six distinct BMI trajectories were identified. Compared with people who maintained lower normal BMI, higher risks of developing obesity-related cancer were observed for participants who transitioned from normal to overweight (HR, 1.29; 95% CI, 1.13-1.47), normal to class I obesity (HR, 1.50; 95% CI, 1.28-1.75), or from overweight to class II obesity (HR, 1.66; 95% CI, 1.32-2.08). Our findings suggest that maintaining a healthy BMI across the adult lifespan is important for cancer prevention. Categorization of BMI by trajectory allowed us to identify specific risk groups to target with public health interventions.

Life-long body mass index trajectories and mortality in two generations

To identify life-long body mass index (BMI) trajectories across two related generations and estimate their associated mortality risks and population attributable deaths. We use prospective cohort data from the Framingham Heart Study (1948-2011) original (4576 individuals, 3913 deaths) and offspring (3753 individuals, 967 deaths) cohorts and latent trajectory models to model BMI trajectories from age 31 to 80 years. Survival models are used to estimate trajectory-specific mortality risk. We define seven BMI trajectories among original cohort and six among offspring cohort. Among original cohort, people who are normal weight at age 31 years and gradually move to overweight status in middle or later adulthood have the lowest mortality risk even compared to those who maintain normal weight throughout adulthood, followed by overweight stable, lower level of normal weight, overweight downward, class I obese upward, and class II/III upward trajectories. Mortality risks associated with obesity trajectories have declined across cohorts, while the prevalence of high-risk trajectories has increased. The mortality impact of weight gain depends on an individual's BMI trajectory. Population attributable deaths associated with unhealthy weight trajectories have grown over generations because the prevalence has increased, offsetting the decline in trajectory-specific mortality risks.

Exposure to multiple childhood social risk factors and adult body mass index trajectories from ages 20 to 64 years.

While childhood social risk factors appear to be associated with adult obesity, it is unclear whether exposure to multiple childhood social risk factors is associated with accelerated weight gain during adulthood. We used the Medical Research Council National Survey of Health and Development, a British population-based birth cohort study of participants born in 1946, height and weight were measured by nurses at ages 36, 43, 53 and 60-64 and self-reported at 20 and 26 years. The 9 childhood socioeconomic risk factors and 8 binary childhood psychosocial risk factors were measured, with 13 prospectively measured at age 4 years (or at 7 or 11 years if missing) and 3 were recalled when participants were age 43. Multilevel modelling was used to examine the association between the number of childhood social risk factors and changes in body mass index (BMI) with age. Increasing exposure to a higher number of childhood socioeconomic risk factors was associated with higher mean BMI across adulthood for both sexes and with a faster increase in BMI from 20 to 64 years, among women but not men. Associations remained after adjustment for adult social class. There was no evidence of an association between exposure to childhood psychosocial risk factors and mean BMI in either sex at any age. Strategies for the prevention and management of weight gain across adulthood may need to tailor interventions in consideration of past exposure to multiple socioeconomic disadvantages experienced during childhood.

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory

Background/objectivesThe mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain.Subjects/methodsWe followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of ‘disinhibition’, indicative of opportunistic eating or overeating and ‘hunger’ which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex.ResultsDisinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66–3.25 kg/m2), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82–1.59 kg/m2) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition.ConclusionsAppetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry.

Feeding patterns and BMI trajectories during infancy: a multi-ethnic, prospective birth cohort

BackgroundMilk feeding type (exclusive breastfeeding [EBF], formula feeding or mixed feeding) and timing of complementary feeding (CF) have been associated with infant growth. However, studies evaluating their combined role, and the role of ethnicity, are scarce. We examined associations of feeding patterns (milk feeding type combined with timing of CF) with infant body mass index (BMI) trajectories and potential ethnic-specific associations.MethodsInfant feeding and BMI data during the 1st year of life from 3524 children (Dutch n = 2880, Moroccan n = 404 and Turkish n = 240) from the Amsterdam Born Children and their Development (ABCD) cohort were used. Six feeding patterns were defined: EBF/earlyCF, EBF/lateCF (reference), formula/earlyCF, formula/lateCF, mixed/earlyCF and mixed/lateCF. A covariate adjusted latent class mixed model was applied to simultaneously model BMI trajectories and associations with feeding patterns. Potential ethnic differences in the associations were studied in a separate model where interactions between ethnicity and feeding patterns were included.ResultsFour distinct BMI trajectories (low, mid-low, mid-high and high) were identified. Feeding pattern of formula/earlyCF was associated with lower odds for low (OR: 0.43; 95% CI: 0.25, 0.76) or mid-high (0.28; 0.16, 0.51) (ref: high) trajectory compared with EBF/lateCF pattern (ref). An ethnic-specific model revealed that among Dutch infants, formula/earlyCF pattern was associated with lower odds for low trajectory (0.46; 0.24, 0.87), whereas among Turkish/Moroccan infants almost all feeding patterns were associated with lower odds for the low trajectory (ref: high).ConclusionInfant feeding patterns are associated with early BMI trajectories with specific ethnic differences. Future studies should take the role of ethnicity into account in the associations between infant feeding and growth.

Longitudinal Trends in Childhood Insulin Levels and Body Mass Index and Associations With Risks of Psychosis and Depression in Young Adults

Cardiometabolic disorders often occur concomitantly with psychosis and depression, contribute to high mortality rates, and are detectable from the onset of the psychiatric disorders. However, it is unclear whether longitudinal trends in cardiometabolic traits from childhood are associated with risks for adult psychosis and depression. To examine whether specific developmental trajectories of fasting insulin (FI) levels and body mass index (BMI) from early childhood were longitudinally associated with psychosis and depression in young adults. A cohort study from the Avon Longitudinal Study of Parents and Children, a prospective study including a population-representative British cohort of 14 975 individuals, was conducted using data from participants aged 1 to 24 years. Body mass index and FI level data were used for growth mixture modeling to delineate developmental trajectories, and associations with psychosis and depression were assessed. The study was conducted between July 15, 2019, and March 24, 2020. Fasting insulin levels were measured at 9, 15, 18, and 24 years, and BMI was measured at 1, 2, 3, 4, 7, 9, 10, 11, 12, 15, 18, and 24 years. Data on sex, race/ethnicity, paternal social class, childhood emotional and behavioral problems, and cumulative scores of sleep problems, average calorie intake, physical activity, smoking, and alcohol and substance use in childhood and adolescence were examined as potential confounders. Psychosis risk (definite psychotic experiences, psychotic disorder, at-risk mental state status, and negative symptom score) depression risk (measured using the computerized Clinical Interview Schedule-Revised) were assessed at 24 years. From data available on 5790 participants (3132 [54.1%] female) for FI levels and data available on 10 463 participants (5336 [51.0%] female) for BMI, 3 distinct trajectories for FI levels and 5 distinct trajectories for BMI were noted, all of which were differentiated by mid-childhood. The persistently high FI level trajectory was associated with a psychosis at-risk mental state (adjusted odds ratio [aOR], 5.01; 95% CI, 1.76-13.19) and psychotic disorder (aOR, 3.22; 95% CI, 1.29-8.02) but not depression (aOR, 1.38; 95% CI, 0.75-2.54). A puberty-onset major increase in BMI was associated with depression (aOR, 4.46; 95% CI, 2.38-9.87) but not psychosis (aOR, 1.98; 95% CI, 0.56-7.79). The cardiometabolic comorbidity of psychosis and depression may have distinct, disorder-specific early-life origins. Disrupted insulin sensitivity could be a shared risk factor for comorbid cardiometabolic disorders and psychosis. A puberty-onset major increase in BMI could be a risk factor or risk indicator for adult depression. These markers may represent targets for prevention and treatment of cardiometabolic disorders in individuals with psychosis and depression.

BMI trajectories after primary school-based lifestyle intervention: Unravelling an uncertain future. A mixed methods study.

This mixed methods study aimed to examine plausible body mass index (BMI) trajectories after exposure to a primary school-based lifestyle intervention to aid in estimating the long-term intervention benefits. BMI trajectories for children at control schools (mean 7.6years of age) were modelled until 20years of age through extrapolating trial evidence (N=1647). A reference scenario assumed that the observed 2-year effects of the 'Healthy Primary Schools of the Future' (HPSF) and 'Physical Activity Schools' (PAS) were fully maintained over time. This was modelled by applying the observed 2-year BMI effects until 20years of age. Expert opinions on likely trends in effect maintenance after the 2-year intervention period were elicited qualitatively and quantitatively, and were used for developing alternative scenarios. Expert elicitation revealed three scenarios: (a) a constant exposure-effect and an uncontrolled environment with effect decay scenario, (b) a household multiplier and an uncontrolled environment with effect decay scenario, and (c) a household multiplier and maintainer scenario. The relative effect of HPSF at 20years of age was -0.21kg/m2 under the reference scenario, and varied from -0.04kg/m2 (a) to -0.06kg/m2 (b), and -0.50kg/m2 (c). For PAS, the relative effect was -0.17kg/m2 under the reference scenario, and varied from -0.04kg/m2 (a, b), to -0.21kg/m2 (c). The mixed methods approach proved to be useful in modelling plausible BMI trajectories and specifying uncertainty on effect maintenance. Further observations until adulthood could reduce the uncertainty around future benefits. This trial was retrospectively registered at Clinicaltrials.gov (NCT02800616).

Associations of caesarean section with body mass and waist circumference trajectories from age 2 to 13 years: A nationally representative birth cohort study in Australia.

Measuring obesity at a single time point does not explain the independent association between C-section birth and obesity in a child's life course. This study aimed to explore the longitudinal link between C-section with obesity trajectories during childhood. We analysed data from a nationally representative birth cohort study named "Longitudinal Study of Australian Children (LSAC)", commenced in 2004. General obesity was measured through the Body Mass Index (BMI) and abdominal obesity by the Waist Circumference (WC) using the biennially collected data from age 2 to 13 years (2006-2016). Group-based trajectory modelling was applied to identify the distinct pattern of BMI & WC trajectories. Multivariable multinomial logistic regression models were used to assess the association between C-section and obesity trajectories after adjusting for perinatal factors. Of the 3524 study children, 30% were born by C-section. Three distinct BMI trajectory groups emerged: stable normal (60%), moderately rising (33%) and accelerated (7%). The WC trajectories were, stable normal (58%), moderate (34%) and accelerated (8%). Compared with the stable normal group, children born through C-section had a higher risk to follow accelerated trajectories for both BMI (OR:1.72; 95% CI: 1.28-2.32) and WC (OR: 1.51; 95% CI: 1.15-1.98) with P-value <0.01. Adjustment of potential confounders did not alter these associations substantially. C-section birth significantly increases the risk of having an accelerated obesity trajectory in children. Limiting the C-section for absolute clinical causes and early institution of preventive approach can reduce the obesity burden among children delivered through C-section.

Body Mass Index Trajectories and Duration of Obesity in Thai Children Diagnosed with Hypertension.

This study explored the relationship between BMI trajectories and the duration of obesity in Thai children diagnosed with hypertension. Demographic and blood pressure data from 536 children (270 boys, 50.3%) from a school in Bangkok, Thailand were collected. Hypertension was defined as blood pressure above the cutoff values specified in the 2017 American Academy of Pediatrics guidelines on 3 occasions. Records of BMI over the previous 3 years were reviewed. The prevalence of hypertension was 2.61% (14/536). Complete data on BMI trajectories were available in 421 non-hypertensive and 12 hypertensive children. The increase in BMI z-score over the previous 3 years was significantly greater in the hypertensive group than the non-hypertensive group, 1.45 (95% CI 0.42 to 1.88) versus 0.09 (95% CI: −0.35, 0.65), P = .008. In conclusion, children with a confirmed diagnosis of hypertension had a greater increase in BMI over the past 3 years than non-hypertensive children.

Body Mass Index Trajectories From Childhood to Mid-Adulthood and Their Sociodemographic Predictors: Evidence From the International Childhood Cardiovascular Cohort (i3C) Consortium

Body Mass Index Trajectories From Childhood to Mid-Adulthood and Their Sociodemographic Predictors: Evidence From the International Childhood Cardiovascular Cohort (i3C) Consortium

Long-term trajectories and current BMI are associated with poorer cognitive functioning in middle-aged adults at high Alzheimer's disease risk.

IntroductionWe examined relationships of body mass index (BMI) with cognition in middle‐aged adults at Alzheimer's disease (AD) risk due to parental family history.MethodsParticipants are offspring of AD patients from the Israel Registry of Alzheimer's Prevention (N = 271). Linear regressions assessed associations of BMI and cognition, and whether associations differed by maternal/paternal history. Analyses of covariance examined associations of long‐term trajectories of BMI with cognition.ResultsHigher BMI was associated with worse language (P = .045). Interactions of BMI with parental history were significant for episodic memory (P = .023), language (p = .027), working memory (P = .006), global cognition (P = .008); associations were stronger among participants with maternal history. Interactions of BMI trajectories with parental history were significant for episodic memory (P = .017), language (P = .013), working memory (P = .001), global cognition (P = .005), with stronger associations for maternal history.DiscussionHigher BMI and overweight/obese trajectories were associated with poorer cognition in adults with maternal history of AD, but not those with paternal history.

Maternal Obesity Before Pregnancy Predicts Offspring Blood Pressure at 18 Years of Age – A Causal Mediation Analysis

Background: Hypertension is the second most common pediatric chronic disease in Westernized countries. Understanding the natural history of hypertension is key to identifying prevention strategies. The present study will examine the relationship between maternal pre-pregnancy body mass index (BMI) and the possible mediating role of growth throughout childhood and adolescence on offspring blood pressure at 18 years. Methods: We performed multivariable regression and causal mediation analyses within 3217 mother - offspring pairs from the Avon Longitudinal Study of Parents and Children (ALSAPC) prospective birth cohort. The main exposure was maternal pre-pregnancy BMI. Latent trajectory analysis (LTA) was used to quantify the mediating variable of offspring BMI Z scores from 7 to 18 years of age. The main outcome was offspring blood pressure at 18 years of age categorized as normal or elevated as per the 2017 American Academy of Pediatrics guidelines. Findings: At 18 years of age, among 3217 offspring, 676 (21%) were overweight or obese, 865 (27%) had elevated blood pressure, and 510 (16%) were hypertensive. LTA identified five distinct offspring BMI trajectories. Multivariable logistic regression revealed that for every 1 unit increase in maternal BMI the risk of elevated blood pressure at 18 years of age increased by 5% (aOR: 1.05, 95% CI: 1.03 – 1.07; p <0.001) and this effect was reduced after adjusting for offspring BMI trajectory (aOR: 1.03, 95% CI: 1.00 – 1.05; p = 0.017). Causal mediation analysis confirmed offspring BMI trajectory as a mediator, accounting for 46% of the total effect of maternal BMI on elevated offspring blood pressure (aOR 1.22; 95% CI: 1.07-1.39). Interpretation: Maternal BMI prior to pregnancy is associated with an increased risk of elevated blood pressure in offspring at 18 years of age and is largely mediated by offspring BMI trajectory throughout childhood and adolescence. Funding Statement: The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). JMM was supported by a Canadian Institute of Health Research (CIHR) Applied Public Health Chair, MBA holds a Tier 2 Canada Research Chair (CRC) in the Developmental Origins of Chronic Disease. JMM holds grants from the CIHR, Diabetes Canada, the Heart and Stroke Foundation (HSF), the Cosmopolitan Foundation, and the Lawson Foundation. AD currently has research funding from CIHR, Research Manitoba and CHRIM. MBA holds grants from the CIHR, The Bill and Melinda Gates Foundation, the Canada Foundation for Innovation, the Garfield G. Weston Foundation, Prolacta Biosciences, Mitacs, the Canadian Institutes for Advanced Research, the Children’s Hospital Foundation of Manitoba, and Research Manitoba; NB and Drs JMM, MBA and AD were also supported by a Research Manitoba grant to the DEVOTION research cluster. Declaration of Interests: None of the authors report potential or actual conflicts of interest. All authors have completed and submitted a Conflict of Interest Statement. Ethics Approval Statement: Ethical approval was obtained from the ALSPAC Law and Ethics Committee and the Biomedical Research Ethics Board at the University of Manitoba. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time.

Nighttime sleep duration trajectories were associated with body mass index trajectories in early childhood.

The respective contribution of total, daytime and nighttime sleep duration in childhood obesity remains unclear. To assess the longitudinal association between developmental trajectories of sleep duration and BMI z-score in early childhood. Data were from the Melbourne INFANT program, a prospective cohort with 4-month-old infants being followed-up until age 60 months (n=528). Sleep duration (total, daytime, nighttime) and BMI z-score were measured using questionnaire at ages 4, 9, 18, 43 and 60 months. Group-based trajectory modelling was used to describe longitudinal trajectories from ages 4 to 60 months. Multivariable logistic regression was conducted to assess the association between sleep duration and BMI z-score trajectories. Three nighttime sleep duration trajectory groups were identified: "Long stable" (10.5 to 11.0hours, 61%), "catchup long" (8.0 to 11.5hours, 23%) and "short stable" (8.7 to 9.8hours, 16%) nighttime sleepers. BMI z-score trajectory groups were classified as "low-BMIz" (-1.5 to -0.5 unit, 21%), "mid-BMIz" (-0.5 to 0.5 unit, 58%) and "high-BMIz" (0.8 to 1.4 unit, 21%). With adjustment for child and maternal covariates, both "catchup long" (OR 3.69 95%CI 1.74, 7.92) and "long stable" nighttime sleepers (OR 4.27 95%CI 2.21, 8.25) revealed higher odds of being in the "mid-BMIz" than the "high-BMIz" group. By contrast, total or daytime sleep duration trajectories were not associated with BMI z-score trajectories. Longer nighttime, but not total or daytime, sleep duration was associated with lower BMI z-score trajectories in early childhood. Our findings reinforce the importance of nighttime sleep for healthy body-weight development in early childhood.

BMI trajectory and subsequent risk of type 2 diabetes among middle-aged women

Background and aimsLittle is known about how weight trajectories among women during menopausal transition and beyond may be related to risk of type 2 diabetes mellitus (T2DM). The aim of this study was to examine associations between body mass index (BMI) trajectories over 20 years, age of obesity onset, cumulative obese-years and incidence of T2DM among middle-aged women. Methods and results12,302 women enrolled in the Australian Longitudinal Study on Women's Health (ALSWH) were surveyed in 1996 (Survey 1, age 45–50), 1998 and then every three years to 2016. Self-reported weight and height were collected for up to eight time points. Incident diabetes was assessed via validated self-report of physician-diagnosed diabetes. Growth mixture models were used to identify distinct BMI trajectories. A total of 1380 (11.2%) women newly developed T2DM over an average 16 years of follow-up. Seven distinct BMI trajectories were identified with differential risk of developing T2DM. Initial BMI was positively associated with T2DM risk. We also observed that risk of T2DM was positively associated with rapid weight increase, early age of obesity onset and greater obese-years. ConclusionSlowing down weight increases, delaying the onset of obesity, or reducing cumulative exposure to obesity may substantially lower the risk of developing T2DM.

Body mass index trajectories among people with obesity and association with mortality: Evidence from a large Israeli database.

ObjectivePrevious studies using longitudinal weight data to characterize obesity are based on populations of limited size and mostly include individuals of all body mass index (BMI) levels, without focusing on weight changes among people with obesity. This study aimed to identify BMI trajectories over 5 years in a large population with obesity, and to determine the trajectories' association with mortality.MethodsFor inclusion, individuals aged 30–74 years at index date (1 January 2013) with continuous membership in Clalit Health Services from 2008 to 2012 were required to have ≥1 BMI measurement per year in ≥3 calendar years during this period, of which at least one was ≥30 kg/m2. Latent class analysis was used to generate BMI trajectories over 5 years (2008–2012). Cox proportional hazards models were used to assess the association between BMI trajectories and all‐cause mortality during follow‐up (2013–2017).ResultsIn total, 367,141 individuals met all inclusion criteria. Mean age was 57.2 years; 41% were men. The optimal model was a quadratic model with four classes of BMI clusters. Most individuals (90.0%) had stable high BMI over time. Individuals in this cluster had significantly lower mortality than individuals in the other trajectory clusters (p < 0.01), including clusters of people with dynamic weight trajectories.ConclusionsThe results of the current study show that people with stable high weight had the lowest mortality of all four BMI trajectories identified. These findings help to expand the scientific understanding of the impact that weight trajectories have on health outcomes, while demonstrating the challenges of discerning the cumulative effects of obesity and weight change, and suggest that dynamic historical measures of BMI should be considered when assessing patients' future risk of obesity‐related morbidity and mortality, and when choosing a treatment strategy.

Intergenerational social mobility and body mass index trajectories - A follow-up study from Finland.

Evidence remains unclear on how intergenerational social mobility is associated with body mass index (BMI) and its long-term changes. Our study identified BMI trajectories from middle to older age by intergenerational social mobility groups and stratified the analyses by gender and two birth cohorts (birth years 1940‒1947 and 1950–1962). We used questionnaire-based cohort data that consists of four survey phases: 2000–2002, 2007, 2012, and 2017. In Phase 1, participants were 40–60-year-old employees of the City of Helsinki, Finland. Our analytical sample consisted of 6,971 women and 1,752 men. Intergenerational social mobility was constructed based on self-reported parental and own education—both divided into high and low—yielding four groups: stable high socioeconomic position (SEP) (high-high), upward social mobility (low-high), downward social mobility (high-low), and stable low SEP (low-low). BMI was calculated from self-reported height and weight from all four phases. Using mixed-effects linear regression, we found increasing BMI trajectories in all four social mobility groups until the age of 65. Women and men with stable high SEP had lower BMI trajectories compared to those with stable low SEP. In the younger birth cohort, women with upward social mobility had a lower BMI trajectory than women with stable low SEP. Additionally, women and men with downward social mobility had higher BMI trajectories than those with stable high SEP. In the older birth cohort, however, the BMI trajectories of upward and downward social mobility groups were somewhat similar and settled between the BMI trajectories of stable high and stable low SEP groups. Our results indicate that the associations between intergenerational social mobility and BMI may depend on gender and birth cohort. Nevertheless, to reduce socioeconomic inequalities in unhealthy weight gain, obesity prevention actions that focus on people who are likely to remain in low SEP might be worthwhile.

Studying pediatric health outcomes with electronic health records using Bayesian clustering and trajectory analysis

Use of routinely collected data from electronic health records (EHR) can expedite longitudinal studies that investigate childhood exposures and rare pediatric health outcomes. For instance, characteristics of the body mass index (BMI) trajectory early in life may be associated with subsequent development of type 2 diabetes. Past studies investigating these relationships have used longitudinal cohort data collected over the course of many years to investigate the connection between BMI trajectory and subsequent development of diabetes. In contrast, EHR data from routine clinical care can provide longitudinal information on early-life BMI trajectories as well as subsequent health outcomes without requiring any additional data collection. In this study, we introduce a Bayesian joint phenotyping and BMI trajectory model to address data quality challenges in an EHR-based study of early-life BMI and type 2 diabetes in adolescence. We compared this joint modeling approach to traditional approaches using a computable phenotype for type 2 diabetes or separately estimated BMI trajectories and type 2 diabetes phenotypes. In a sample of 49,062 children derived from the PEDSnet consortium of pediatric healthcare systems, a median 8 (interquartile range [IQR] 5–13) BMI measurements were available to characterize the early-life BMI trajectory. The joint modeling and computable phenotype approaches found that age at adiposity rebound between 5 and 9 years was associated with higher odds of type 2 diabetes in adolescence compared to age at adiposity rebound between 2 and 5 years (joint model odds ratio [OR] = 1.77; computable phenotype OR = 1.88) and that BMI in excess of 140% of the 95th percentile for age and sex at age 9 years was associated with higher odds of type 2 diabetes in adolescence relative to children with BMI from 100 to 120% of the 95th percentile (joint model OR = 6.22; computable phenotype OR = 13.25). Estimates from the separate phenotyping and trajectory model were substantially attenuated towards the null. These results demonstrate that EHR data coupled with modern methodologic approaches can improve efficiency and timeliness of studies of childhood exposures and rare health outcomes.

Duration of obesity exposure between ages 10 and 40 years and its relationship with cardiometabolic disease risk factors: A cohort study.

Individuals with obesity do not represent a homogeneous group in terms of cardiometabolic risk. Using 3 nationally representative British birth cohorts, we investigated whether the duration of obesity was related to heterogeneity in cardiometabolic risk. We used harmonised body mass index (BMI) and cardiometabolic disease risk factor data from 20,746 participants (49.1% male and 97.2% white British) enrolled in 3 British birth cohort studies: the 1946 National Survey of Health and Development (NSHD), the 1958 National Child Development Study (NCDS), and the 1970 British Cohort Study (BCS70). Within each cohort, individual life course BMI trajectories were created between 10 and 40 years of age, and from these, age of obesity onset, duration spent obese (range 0 to 30 years), and cumulative obesity severity were derived. Obesity duration was examined in relation to a number of cardiometabolic disease risk factors collected in mid-adulthood: systolic (SBP) and diastolic blood pressure (DBP), high-density-lipoprotein cholesterol (HDL-C), and glycated haemoglobin (HbA1c). A greater obesity duration was associated with worse values for all cardiometabolic disease risk factors. The strongest association with obesity duration was for HbA1c: HbA1c levels in those with obesity for <5 years were relatively higher by 5% (95% CI: 4, 6), compared with never obese, increasing to 20% (95% CI: 17, 23) higher in those with obesity for 20 to 30 years. When adjustment was made for obesity severity, the association with obesity duration was largely attenuated for SBP, DBP, and HDL-C. For HbA1c, however, the association with obesity duration persisted, independent of obesity severity. Due to pooling of 3 cohorts and thus the availability of only a limited number harmonised variables across cohorts, our models included adjustment for only a small number of potential confounding variables, meaning there is a possibility of residual confounding. Given that the obesity epidemic is characterised by a much earlier onset of obesity and consequently a greater lifetime exposure, our findings suggest that health policy recommendations aimed at preventing early obesity onset, and therefore reducing lifetime exposure, may help reduce the risk of diabetes, independently of obesity severity. However, to test the robustness of our observed associations, triangulation of evidence from different epidemiological approaches (e.g., mendelian randomization and negative control studies) should be obtained.