Trajectories of Body Mass Index from Young Adulthood to Middle Age among Canadian Men and Women

Wang, Meng; Yi, Yanqing; Roebothan, Barbara; Colbourne, J. S.; Maddalena, Victor; Sun, Guang

doi:10.1155/2015/121806

Cited by 14 publications

(16 citation statements)

References 71 publications

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“…Over one third of patients in the PORTAL Overweight/Obesity Cohort did not maintain their initial weight over the 5‐year period. Specifically, the steady weight gain then maintenance trajectory is a consistent weight change pattern found in other US, Canadian, and Chinese cohort studies. The steady weight loss then relapse group represents the experience of most individuals who try to lose weight but are unsuccessful long term.…”

Section: Discussionsupporting

confidence: 71%

“…Seven distinct 5‐year weight trajectories were identified in a diverse health system‐based cohort of adults with overweight and obesity: (a) significant weight loss then maintenance; (b) higher stable weight; (c) moderate stable weight; (d) steady weight loss then relapse; (e) weight gain then weight loss; (f) steady weight gain then maintenance; and (g) lower stable weight. These trajectories are fairly consistent with trajectories established in previous cohort studies . Age, sex, race/ethnicity, and BMI at baseline significantly predicted patients' membership in a weight change trajectory cluster.…”

Section: Discussionmentioning

confidence: 99%

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Behavioural and psychosocial factors associated with 5‐year weight trajectories within the PORTAL Overweight/Obesity Cohort

Fitzpatrick

Rosales

Brown

et al. 2020

Obesity Science & Practice

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Objective: The purpose of this study was to model weight trajectories over a 5-year time period (2012)(2013)(2014)(2015)(2016) and their association with behavioural and psychosocial characteristics and health care-related experiences using data from the Patient Outcomes Research to Advance Learning (PORTAL) overweight/obesity cohort.Methods: Weight trajectories for each eligible patient in the PORTAL overweight/obesity cohort (n = 2864) were identified first using growth modelling; trajectories were then grouped using a hierarchical cluster analysis. Weight trajectory clusters that emerged were compared on demographics, and predictors of cluster membership were examined. Clusters were also compared on responses to a survey assessing health behaviours, quality of life, and health care experience completed in 2015 by 49% of the total sample (n = 1391).Results: Seven distinct weight trajectory clusters were identified: (a) significant weight loss then maintenance; (b) higher stable weight; (c) moderate stable weight;(d) steady weight loss then relapse; (e) weight gain then weight loss; (f) steady weight gain then maintenance; and (g) lower stable weight. Age, sex, race/ethnicity, and body mass index at baseline predicted patient's weight trajectory (P < .001). Over two thirds of patients maintained their weight over the 5-year period. Significant weight loss then maintenance, weight gain then weight loss, and higher stable weight patients were more likely to report receiving weight counselling from their provider.Patients in the significant weight loss then maintenance and lower stable weight clusters were more likely to be physically active than the other clusters.Conclusion: Findings suggest variability in patterns of weight change among adults with overweight or obesity who have access to health care and that these patterns differ on demographic, behavioural and psychosocial factors, and health care experience. K E Y W O R D Sobesity, population health, health behaviors, weight trajectories

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Section: Discussionsupporting

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Behavioural and psychosocial factors associated with 5‐year weight trajectories within the PORTAL Overweight/Obesity Cohort

Fitzpatrick

Rosales

Brown

et al. 2020

Obesity Science & Practice

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“…In the absence of an established standard, we used the IPC-BMI category of 0 to < 1 units as our reference because it is consistent with the expected BMI trajectory (i.e. increasing BMI with age) [17–19].…”

Section: Discussionmentioning

confidence: 99%

Interpregnancy change in body mass index and infant outcomes in Texas: a population-based study

Benjamin

Littlejohn

Canfield

et al. 2019

BMC Pregnancy Childbirth

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Background Maternal prepregnancy body mass index (BMI) is associated with several infant outcomes, but it is unclear whether these associations reflect causal relationships. We conducted a study of interpregnancy change in BMI (IPC-BMI) to improve understanding of the associations between BMI and large for gestational age (LGA), small for gestational age (SGA), and preterm birth (PTB). Methods Birth certificate data from 2481 linked sibling pairs (Texas, 2005–2012) were used to estimate IPC-BMI and evaluate its association with LGA, SGA, and PTB in the younger sibling of the pair. Multivariable logistic regression was used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) using data from the full sample and within strata defined by prepregnancy BMI for the older sibling. Results On average, women gained 1.1 BMI units between pregnancies. In the full sample, interpregnancy BMI decreases were associated with reduced odds of LGA and increased odds of SGA and PTB (IPC-BMI < -1 versus 0 to < 1: LGA aOR 0.7, 95% CI 0.4, 1.1; SGA aOR 1.6, 95% CI 1.0, 2.7; PTB aOR 1.9, 95% CI 1.3, 2.8). In stratified analyses, similar associations were observed in some, but not all, strata. Findings for interpregnancy BMI increases were less consistent, with little evidence for associations between these outcomes and the most extreme IPC-BMI increases. Conclusions There is growing evidence that interpregnancy BMI decreases are associated with LGA, SGA, and PTB. However, taken as a whole, the literature provides insufficient evidence to establish causal links between maternal BMI and these outcomes.

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“…All analyses were conducted using SAS version 9.3 (SAS Institute). The modelling selection process of BMI trajectories followed the criteria presented in the authors' previous work [ 22 ]. LCGM was also used to define three latent variables to identify different patterns of the probability of being physically active, smoking, and living with low income.…”

Section: Methodsmentioning

confidence: 99%

Body Mass Index Trajectories among Middle-Aged and Elderly Canadians and Associated Health Outcomes

Wang

Roebothan

et al. 2016

Journal of Environmental and Public Health

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Background. Whether there is heterogeneity in the development of BMI from middle-age onward is still unknown. The primary aim of this study is to analyze long-term obesity and how BMI trajectories are associated with health outcomes in midlife. Methods. Latent Class Growth Modelling was used to capture the changes in BMI over time. In this study, 3070 individuals from the National Population Health Survey (NPHS), aged 40–55 years at baseline, were included. Results. Four BMI trajectory groups, “Normal-Stable” (N-S), “Overweight-Stable” (OV-S), “Obese I-Stable” (OB I-S), and “Obese II-Stable” (OB II-S), were identified. Men, persons of White ancestry, and individuals who had no postsecondary education had higher odds of being in the latter three groups. Moreover, members of the OV-S, OB I-S, and OB II-S groups experienced more asthma, arthritis, hypertension, diabetes, heart disease, cognitive impairment, and reduced self-rated overall health. Individuals in the OB II-S group were at greater risk for back problems, chronic bronchitis or emphysema, and emotional issues when compared to the N-S group. Conclusion. Understanding different BMI trajectories is important in order to identify people who are at the highest risk of developing comorbidities due to obesity and to establish programs to intervene appropriately.

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Trajectories of Body Mass Index from Young Adulthood to Middle Age among Canadian Men and Women

Cited by 14 publications

References 71 publications

Behavioural and psychosocial factors associated with 5‐year weight trajectories within the PORTAL Overweight/Obesity Cohort

Behavioural and psychosocial factors associated with 5‐year weight trajectories within the PORTAL Overweight/Obesity Cohort

Interpregnancy change in body mass index and infant outcomes in Texas: a population-based study

Body Mass Index Trajectories among Middle-Aged and Elderly Canadians and Associated Health Outcomes

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