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Infant BMI trajectories are associated with young adult body composition.

ABSTRACT: The dynamic aspect of early life growth is not fully captured by typical analyses, which focus on one specific time period. To better understand how infant and young child growth relate to the development of adult body composition, the authors characterized body mass index (BMI) trajectories using latent class growth analysis (LCGA) and evaluated their association with adult body composition. Data are from the Cebu Longitudinal Health and Nutrition Survey, which followed a birth cohort to age 22 years (n = 1749). In both males and females, LCGA identified seven subgroups of respondents with similar BMI trajectories from 0 to 24 months (assessed with bimonthly anthropometrics). Trajectory groups were compared with conventional approaches: (1) accelerated growth between two time points (0-4 months), (2) continuous BMI gain between two points (0-4 months and 0-24 months) and (3) BMI measured at one time point (24 months) as predictors of young adult body composition measures. The seven trajectory groups were distinguished by age-specific differences in tempo and timing of BMI gain in infancy. Infant BMI trajectories were better than accelerated BMI gain between 0 and 4 months at predicting young adult body composition. After controlling for BMI at age 2 years, infant BMI trajectories still explained variation in adult body composition. Using unique longitudinal data and methods, we find that distinct infant BMI trajectories have long-term implications for the development of body composition.

SUBMITTER: Slining MM

PROVIDER: S-EPMC3769801 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Infant BMI trajectories are associated with young adult body composition.

Slining M M MM Herring A H AH Popkin B M BM Mayer-Davis E J EJ Adair L S LS

Journal of developmental origins of health and disease 20130201 1

The dynamic aspect of early life growth is not fully captured by typical analyses, which focus on one specific time period. To better understand how infant and young child growth relate to the development of adult body composition, the authors characterized body mass index (BMI) trajectories using latent class growth analysis (LCGA) and evaluated their association with adult body composition. Data are from the Cebu Longitudinal Health and Nutrition Survey, which followed a birth cohort to age 22 ...[more]

PMID: 24040489

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Project description:Aims/hypothesisThe aim of this study was to characterise longitudinal profiles of BMI from childhood and to examine the impact of level-independent childhood BMI trajectories on adult type 2 diabetes.MethodsThe longitudinal cohort consisted of 2449 adults (1613 white and 836 black) who had their BMI measured between four and 15 times from childhood (4-19 years) to adulthood (20-51 years) and fasting glucose measured in adulthood. Model-estimated levels and linear slopes of BMI at childhood age points were calculated in 1-year intervals using growth-curve parameters and their first derivatives, respectively.ResultsBMI from childhood to adulthood fit cubic growth curves; linear and non-linear curve parameters differed significantly between race-sex groups. BMI showed race and sex differences from 15 years onwards. Individuals with hyperglycaemia had higher long-term BMI levels than those who were normoglycaemic in race-sex groups. Linear and non-linear slope parameters of BMI differed consistently and significantly between adult hyperglycaemia groups. The OR of childhood BMI levels for ages 4-19 years was 1.45-1.83 (p < 0.001 for all) for adult hyperglycaemia after adjustment for confounders. Level-adjusted linear slopes of BMI at ages 10-19 years showed significantly positive associations with adult hyperglycaemia (OR 1.17-1.50, p < 0.01 for all). The associations of childhood BMI linear slopes with adult hyperglycaemia were not significant during the age period 5-9 years. The trends in these associations were consistent across race-sex groups.Conclusions/interpretationThese observations indicate that childhood BMI trajectories have a significant impact on adult diabetes, independent of BMI levels. The adolescence age period is a crucial window for the development of diabetes in later life, which has implications for early-life prevention.Data availabilityAll data and materials are publicly available at the National Heart, Lung, and Blood Institute (NHLBI) Biologic Specimen and Data Repository and can be accessed at https://biolincc.nhlbi.nih.gov/studies/bhs .

Project description:BackgroundThe influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers.MethodsOur study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks.ResultsWe identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers.ConclusionsAssociations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Project description:BackgroundThe influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remain underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers.MethodsOur study included two cohorts of longitudinally followed twins: FinnTwin12 (N=651) and the Netherlands Twin Register (NTR) (N=665). Follow-up comprised four BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated using latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. The sources of genetic and environmental variation underlying the protein abundances were quantified using twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) using mixed-effect models and correlation networks.ResultsWe identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 6 and 4 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with many metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers.ConclusionsAssociations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Project description:BackgroundKnee pain is studied mostly in older age groups, although in young adults it may be an indicator of future impaired musculoskeletal health. Therefore, the aim of this study was to examine the longitudinal association between knee pain and thigh muscle strength in young adult women and to explore the associations between muscle strength, body composition, physical activity and knee pain.MethodsThe PEAK-25 cohort consists of women aged 25 at baseline (N=1064). At the 10-year follow-up n=728 attended for DXA-measured body composition and muscle strength assessment and n=797 answered the questionnaire on health and lifestyle. Independent samples t-test was used to compare women with and without knee pain, Spearman correlation was used to test the longitudinal association between strength and knee pain.ResultsKnee pain was reported by one third of the women at follow-up (n=260, 33%), although physical activity levels were similar in those with and without pain (high level 50 vs 45 % (p= 0.18). Body composition differed, however. Women with knee pain had higher BMI (25.6 vs 24.1), fat mass index (9.2 vs 8.2) and % total body fat mass (34.7 vs 33.2). Simultaneously, they had lower % lean mass (total body 61.5 vs 62.8; legs 20.6 vs 21.0) and lower thigh muscle strength (extensors 184.9 vs 196.8, flexors 96.6 vs 100.9, p<0.05), but slightly higher hamstrings-to -quadriceps ratio (0.53 vs 0.51, p=0.04). Muscle strength at baseline weakly correlated with knee pain at follow-up (extensor rs= -0.04; flexor -0.02, p>0.2). Overweight women had higher absolute thigh muscle strength, but lower weight-adjusted strength than normal weight women (p<0.001). Leg lean mass explained 26-34% of the variation in muscle strength and adjustment for physical activity level had little effect.ConclusionKnee pain is already common among women in their mid-thirties. Lower thigh muscle strength in the mid-twenties was not associated with future knee pain, however women with knee pain tended to have lower thigh muscle strength and a body composition of higher body fat combined with lower lean mass. Maintaining a healthy body composition and adequate thigh muscle strength may be beneficial for knee joint health.

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Infant BMI trajectories are associated with young adult body composition.

Publications

Infant BMI trajectories are associated with young adult body composition.

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