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Amati F, McCann L, Castañeda-Gutiérrez E, Prior E, van Loo-Bouwman CA, Abrahamse-Berkeveld M, Oliveros E, Ozanne S, Symonds ME, Chang CY, Modi N. Infant fat mass and later child and adolescent health outcomes: a systematic review. Arch Dis Child 2024; 109:125-129. [PMID: 37940360 PMCID: PMC10850671 DOI: 10.1136/archdischild-2023-325798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 09/27/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVE Obesity and excess adiposity are leading causes of metabolic and cardiovascular morbidity and mortality. Early identification of individuals at risk is key for preventive strategies. We examined the relationship between infant body composition (0-2 years of age) and later (>2 years) health outcomes using a systematic review. DESIGN We preregistered the study on PROSPERO (ID 288013) and searched Embase, PubMed and Cochrane databases for English language publications using the Medical Subject Headings (MeSH) terms 'infant' and 'body composition' and 'risk' between January 1946 and February 2022. We included studies which assessed infant body composition using predetermined in vivo methods other than body mass index (BMI). RESULTS We identified 6015 articles. After abstract screening to assess eligibility, we reviewed 130 full text publications. 30 were included in the final assessment and narrative synthesis. Meta-analysis was not possible due to heterogeneity of results. All 30 studies were of high quality and reported associations between infant body composition and 19 different health outcomes after 2 years of age. Outcome measurements ranged from 2 years to 16 years. The strongest associations were found between infant fat mass and later fat mass (7 studies), and later BMI (5 studies). For 11 of the outcomes assessed, there was no relationship to infant adiposity detected. CONCLUSIONS Current evidence, from a small number of studies, suggests a positive association between infant adiposity and future adiposity or BMI, but the validity of infant body composition as a biomarker of future health remains inconclusive. Carefully designed, standardised studies are required to identify the value of infant body composition for predicting later health. TRIAL REGISTRATION PROSPERO: 288013.
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Affiliation(s)
- Federica Amati
- Department of Primary Care and Public Health, Imperial College London, London, UK
| | - Lucy McCann
- Centre for Primary Care, Wolfson Insitute of Population Health, Queen Mary University, London, UK
| | | | - Emily Prior
- Section of Neonatal Medicine, School of Public Health, Imperial College London, London, UK
| | | | - Marieke Abrahamse-Berkeveld
- Department of Nutritional Physiology and Functional Nutrients, Danone Nutricia Research, Utrecht, The Netherlands
| | - Elena Oliveros
- Abbott Nutrition Research and Development, Abbott Laboratories, Granada, Spain
| | - Susan Ozanne
- Metabolic Research Laboratories and MRC Metabolic Diseases Unit, University of Cambridge, Cambridge, UK
| | - Michael Edward Symonds
- Centre for Perinatal Research, Academic Unit of Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Ching-Yu Chang
- International Life Science Institute, International Life Science Institute, European Branch, Brussels, Belgium
| | - Neena Modi
- Section of Neonatal Medicine, School of Public Health, Imperial College London, London, UK
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Aris IM, Perng W, Dabelea D, Padula AM, Alshawabkeh A, Vélez-Vega CM, Aschner JL, Camargo CA, Sussman TJ, Dunlop AL, Elliott AJ, Ferrara A, Joseph CLM, Singh AM, Breton CV, Hartert T, Cacho F, Karagas MR, Lester BM, Kelly NR, Ganiban JM, Chu SH, O’Connor TG, Fry RC, Norman G, Trasande L, Restrepo B, Gold DR, James P, Oken E. Neighborhood Opportunity and Vulnerability and Incident Asthma Among Children. JAMA Pediatr 2023; 177:1055-1064. [PMID: 37639269 PMCID: PMC10463174 DOI: 10.1001/jamapediatrics.2023.3133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 06/29/2023] [Indexed: 08/29/2023]
Abstract
Background The extent to which physical and social attributes of neighborhoods play a role in childhood asthma remains understudied. Objective To examine associations of neighborhood-level opportunity and social vulnerability measures with childhood asthma incidence. Design, Setting, and Participants This cohort study used data from children in 46 cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) Program between January 1, 1995, and August 31, 2022. Participant inclusion required at least 1 geocoded residential address from birth and parent or caregiver report of a physician's diagnosis of asthma. Participants were followed up to the date of asthma diagnosis, date of last visit or loss to follow-up, or age 20 years. Exposures Census tract-level Child Opportunity Index (COI) and Social Vulnerability Index (SVI) at birth, infancy, or early childhood, grouped into very low (<20th percentile), low (20th to <40th percentile), moderate (40th to <60th percentile), high (60th to <80th percentile), or very high (≥80th percentile) COI or SVI. Main Outcomes and Measures The main outcome was parent or caregiver report of a physician's diagnosis of childhood asthma (yes or no). Poisson regression models estimated asthma incidence rate ratios (IRRs) associated with COI and SVI scores at each life stage. Results The study included 10 516 children (median age at follow-up, 9.1 years [IQR, 7.0-11.6 years]; 52.2% male), of whom 20.6% lived in neighborhoods with very high COI and very low SVI. The overall asthma incidence rate was 23.3 cases per 1000 child-years (median age at asthma diagnosis, 6.6 years [IQR, 4.1-9.9 years]). High and very high (vs very low) COI at birth, infancy, or early childhood were associated with lower subsequent asthma incidence independent of sociodemographic characteristics, parental asthma history, and parity. For example, compared with very low COI, the adjusted IRR for asthma was 0.87 (95% CI, 0.75-1.00) for high COI at birth and 0.83 (95% CI, 0.71-0.98) for very high COI at birth. These associations appeared to be attributable to the health and environmental and the social and economic domains of the COI. The SVI during early life was not significantly associated with asthma incidence. For example, compared with a very high SVI, the adjusted IRR for asthma was 0.88 (95% CI, 0.75-1.02) for low SVI at birth and 0.89 (95% CI, 0.76-1.03) for very low SVI at birth. Conclusions In this cohort study, high and very high neighborhood opportunity during early life compared with very low neighborhood opportunity were associated with lower childhood asthma incidence. These findings suggest the need for future studies examining whether investing in health and environmental or social and economic resources in early life would promote health equity in pediatric asthma.
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Affiliation(s)
- Izzuddin M. Aris
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Wei Perng
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora
| | - Amy M. Padula
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco
| | - Akram Alshawabkeh
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts
| | - Carmen M. Vélez-Vega
- University of Puerto Rico (UPR) Graduate School of Public Health, UPR Medical Sciences Campus, San Juan, Puerto Rico
| | - Judy L. Aschner
- Department of Pediatrics, Hackensack Meridian School of Medicine, Nutley, New Jersey
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, New York
| | - Carlos A. Camargo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Tamara J. Sussman
- Department of Psychiatry, Columbia University and New York State Psychiatric Institute, New York
| | - Anne L. Dunlop
- Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, Georgia
| | - Amy J. Elliott
- Avera Research Institute, Sioux Falls, South Dakota
- Department of Pediatrics, University of South Dakota School of Medicine, Sioux Falls
| | - Assiamira Ferrara
- Division of Research, Kaiser Permanente Northern California, Oakland
| | | | - Anne Marie Singh
- Division of Allergy, Immunology and Rheumatology, Department of Pediatrics, University of Wisconsin–Madison
| | - Carrie V. Breton
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles
| | - Tina Hartert
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ferdinand Cacho
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Margaret R. Karagas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire
| | - Barry M. Lester
- Department of Pediatrics, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Nichole R. Kelly
- Department of Counseling Psychology and Human Services, Prevention Science Institute, University of Oregon, Eugene
| | - Jody M. Ganiban
- Department of Psychological and Brain Sciences, George Washington University, Washington, DC
| | - Su H. Chu
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Rebecca C. Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina, Chapel Hill
| | - Gwendolyn Norman
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Wayne State University, Detroit, Michigan
| | - Leonardo Trasande
- Department of Pediatrics, Grossman School of Medicine, New York University, New York
| | - Bibiana Restrepo
- Department of Pediatrics, School of Medicine, University of California, Davis, Sacramento
| | - Diane R. Gold
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Peter James
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
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Prior E, Uthaya SN, Gale C. Measuring body composition in children: research and practice. Arch Dis Child Educ Pract Ed 2023:archdischild-2022-324920. [PMID: 36813541 DOI: 10.1136/archdischild-2022-324920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 12/14/2022] [Indexed: 02/24/2023]
Affiliation(s)
- Emily Prior
- Neonatal Medicine, School of Public Health, Faculty of Medicine, Imperial College, London, UK
| | - Sabita N Uthaya
- Neonatal Medicine, School of Public Health, Faculty of Medicine, Imperial College, London, UK.,Chelsea and Westminster NHS Foundation Trust, London, UK
| | - Chris Gale
- Neonatal Medicine, School of Public Health, Faculty of Medicine, Imperial College, London, UK
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Aris IM, Perng W, Dabelea D, Padula AM, Alshawabkeh A, Vélez-Vega CM, Aschner JL, Camargo CA, Sussman TJ, Dunlop AL, Elliott AJ, Ferrara A, Zhu Y, Joseph CLM, Singh AM, Hartert T, Cacho F, Karagas MR, North-Reid T, Lester BM, Kelly NR, Ganiban JM, Chu SH, O’Connor TG, Fry RC, Norman G, Trasande L, Restrepo B, James P, Oken E. Associations of Neighborhood Opportunity and Social Vulnerability With Trajectories of Childhood Body Mass Index and Obesity Among US Children. JAMA Netw Open 2022; 5:e2247957. [PMID: 36547983 PMCID: PMC9857328 DOI: 10.1001/jamanetworkopen.2022.47957] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 10/30/2022] [Indexed: 12/24/2022] Open
Abstract
Importance Physical and social neighborhood attributes may have implications for children's growth and development patterns. The extent to which these attributes are associated with body mass index (BMI) trajectories and obesity risk from childhood to adolescence remains understudied. Objective To examine associations of neighborhood-level measures of opportunity and social vulnerability with trajectories of BMI and obesity risk from birth to adolescence. Design, Setting, and Participants This cohort study used data from 54 cohorts (20 677 children) participating in the Environmental Influences on Child Health Outcomes (ECHO) program from January 1, 1995, to January 1, 2022. Participant inclusion required at least 1 geocoded residential address and anthropometric measure (taken at the same time or after the address date) from birth through adolescence. Data were analyzed from February 1 to June 30, 2022. Exposures Census tract-level Child Opportunity Index (COI) and Social Vulnerability Index (SVI) linked to geocoded residential addresses at birth and in infancy (age range, 0.5-1.5 years), early childhood (age range, 2.0-4.8 years), and mid-childhood (age range, 5.0-9.8 years). Main Outcomes and Measures BMI (calculated as weight in kilograms divided by length [if aged <2 years] or height in meters squared) and obesity (age- and sex-specific BMI ≥95th percentile). Based on nationwide distributions of the COI and SVI, Census tract rankings were grouped into 5 categories: very low (<20th percentile), low (20th percentile to <40th percentile), moderate (40th percentile to <60th percentile), high (60th percentile to <80th percentile), or very high (≥80th percentile) opportunity (COI) or vulnerability (SVI). Results Among 20 677 children, 10 747 (52.0%) were male; 12 463 of 20 105 (62.0%) were White, and 16 036 of 20 333 (78.9%) were non-Hispanic. (Some data for race and ethnicity were missing.) Overall, 29.9% of children in the ECHO program resided in areas with the most advantageous characteristics. For example, at birth, 26.7% of children lived in areas with very high COI, and 25.3% lived in areas with very low SVI; in mid-childhood, 30.6% lived in areas with very high COI and 28.4% lived in areas with very low SVI. Linear mixed-effects models revealed that at every life stage, children who resided in areas with higher COI (vs very low COI) had lower mean BMI trajectories and lower risk of obesity from childhood to adolescence, independent of family sociodemographic and prenatal characteristics. For example, among children with obesity at age 10 years, the risk ratio was 0.21 (95% CI, 0.12-0.34) for very high COI at birth, 0.31 (95% CI, 0.20-0.51) for high COI at birth, 0.46 (95% CI, 0.28-0.74) for moderate COI at birth, and 0.53 (95% CI, 0.32-0.86) for low COI at birth. Similar patterns of findings were observed for children who resided in areas with lower SVI (vs very high SVI). For example, among children with obesity at age 10 years, the risk ratio was 0.17 (95% CI, 0.10-0.30) for very low SVI at birth, 0.20 (95% CI, 0.11-0.35) for low SVI at birth, 0.42 (95% CI, 0.24-0.75) for moderate SVI at birth, and 0.43 (95% CI, 0.24-0.76) for high SVI at birth. For both indices, effect estimates for mean BMI difference and obesity risk were larger at an older age of outcome measurement. In addition, exposure to COI or SVI at birth was associated with the most substantial difference in subsequent mean BMI and risk of obesity compared with exposure at later life stages. Conclusions and Relevance In this cohort study, residing in higher-opportunity and lower-vulnerability neighborhoods in early life, especially at birth, was associated with a lower mean BMI trajectory and a lower risk of obesity from childhood to adolescence. Future research should clarify whether initiatives or policies that alter specific components of neighborhood environment would be beneficial in preventing excess weight in children.
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Affiliation(s)
- Izzuddin M. Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Wei Perng
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora
| | - Amy M. Padula
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco
| | - Akram Alshawabkeh
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts
| | - Carmen M. Vélez-Vega
- UPR Medical Sciences Campus, University of Puerto Rico Graduate School of Public Health, San Juan
| | - Judy L. Aschner
- Department of Pediatrics, Hackensack Meridian School of Medicine, Nutley, New Jersey
- Department of Pediatrics, Albert Einstein College of Medicine, New York, New York
| | - Carlos A. Camargo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Emergency Medicine, Massachusetts General Hospital, Boston
| | - Tamara J. Sussman
- Department of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, New York
| | - Anne L. Dunlop
- Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, Georgia
| | - Amy J. Elliott
- Avera Research Institute, Sioux Falls, South Dakota
- Department of Pediatrics, University of South Dakota School of Medicine, Sioux Falls
| | - Assiamira Ferrara
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Yeyi Zhu
- Division of Research, Kaiser Permanente Northern California, Oakland
| | | | - Anne Marie Singh
- Division of Allergy, Immunology and Rheumatology, University of Wisconsin–Madison, Madison
| | - Tina Hartert
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ferdinand Cacho
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Margaret R. Karagas
- Department of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire
| | - Tiffany North-Reid
- Department of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire
| | - Barry M. Lester
- Department of Pediatrics, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Nichole R. Kelly
- Department of Counseling Psychology and Human Services, Prevention Science Institute, University of Oregon, Eugene
| | - Jody M. Ganiban
- Department of Psychological and Brain Sciences, George Washington University, Washington, District of Columbia
| | - Su H. Chu
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Rebecca C. Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - Gwendolyn Norman
- Institute for Environmental Health Sciences, Wayne State University School of Medicine, Detroit, Michigan
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan
| | - Leonardo Trasande
- Department of Pediatrics, New York University Grossman School of Medicine, New York
| | - Bibiana Restrepo
- Department of Pediatrics, University of California Davis School of Medicine, Sacramento
- MIND Institute, University of California Davis, Sacramento, California
| | - Peter James
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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5
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Ong YY, Pang WW, Huang JY, Aris IM, Sadananthan SA, Tint MT, Yuan WL, Chen LW, Chan YH, Karnani N, Velan SS, Fortier MV, Choo J, Ling LH, Shek L, Tan KH, Gluckman PD, Yap F, Chong YS, Godfrey KM, Chong MFF, Chan SY, Eriksson JG, Wlodek ME, Lee YS, Michael N. Breastfeeding may benefit cardiometabolic health of children exposed to increased gestational glycemia in utero. Eur J Nutr 2022; 61:2383-2395. [PMID: 35124728 PMCID: PMC7613060 DOI: 10.1007/s00394-022-02800-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 01/06/2022] [Indexed: 02/03/2023]
Abstract
PURPOSE There is altered breastmilk composition among mothers with gestational diabetes and conflicting evidence on whether breastfeeding is beneficial or detrimental to their offspring's cardiometabolic health. We aimed to investigate associations between breastfeeding and offspring's cardiometabolic health across the range of gestational glycemia. METHODS We included 827 naturally conceived, term singletons from a prospective mother-child cohort. We measured gestational (26-28 weeks) fasting plasma glucose (FPG) and 2-h plasma glucose (2 hPG) after an oral glucose tolerance test as continuous variables. Participants were classified into 2 breastfeeding categories (high/intermediate vs. low) according to their breastfeeding duration and exclusivity. Main outcome measures included magnetic resonance imaging (MRI)-measured abdominal fat, intramyocellular lipids (IMCL), and liver fat, quantitative magnetic resonance (QMR)-measured body fat mass, blood pressure, blood lipids, and insulin resistance at 6 years old (all continuous variables). We evaluated if gestational glycemia (FPG and 2 hPG) modified the association of breastfeeding with offspring outcomes after adjusting for confounders using a multiple linear regression model that included a 'gestational glycemia × breastfeeding' interaction term. RESULTS With increasing gestational FPG, high/intermediate (vs. low) breastfeeding was associated with lower levels of IMCL (p-interaction = 0.047), liver fat (p-interaction = 0.033), and triglycerides (p-interaction = 0.007), after adjusting for confounders. Specifically, at 2 standard deviations above the mean gestational FPG level, high/intermediate (vs. low) breastfeeding was linked to lower adjusted mean IMCL [0.39% of water signal (0.29, 0.50) vs. 0.54% of water signal (0.46, 0.62)], liver fat [0.39% by weight (0.20, 0.58) vs. 0.72% by weight (0.59, 0.85)], and triglycerides [0.62 mmol/L (0.51, 0.72) vs. 0.86 mmol/L (0.75, 0.97)]. 2 hPG did not significantly modify the association between breastfeeding and childhood cardiometabolic risk. CONCLUSION Our findings suggest breastfeeding may confer protection against adverse fat partitioning and higher triglyceride concentration among children exposed to increased glycemia in utero.
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Affiliation(s)
- Yi Ying Ong
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wei Wei Pang
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jonathan Y Huang
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Suresh Anand Sadananthan
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - Mya-Thway Tint
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - Wen Lun Yuan
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ling-Wei Chen
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Neerja Karnani
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - S Sendhil Velan
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore
| | - Marielle V Fortier
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore
| | - Jonathan Choo
- Department of Paediatrics, KK Women's and Children's Hospital, Singapore, Singapore
| | - Lieng Hsi Ling
- Department of Cardiology, National University Heart Centre, Singapore, Singapore
| | - Lynette Shek
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Division of Paediatric Endocrinology, Department of Paediatrics, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore, Singapore
| | - Kok Hian Tan
- Duke-NUS Medical School, Singapore, Singapore
- Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore
| | - Peter D Gluckman
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Fabian Yap
- Department of Paediatrics, KK Women's and Children's Hospital, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Yap-Seng Chong
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Mary F-F Chong
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Shiao-Yng Chan
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
| | - Johan G Eriksson
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Mary E Wlodek
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Yung Seng Lee
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore.
- Division of Paediatric Endocrinology, Department of Paediatrics, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore, Singapore.
| | - Navin Michael
- Brenner Centre for Molecular Medicine, Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, 30 Medical Drive, Singapore, 117609, Singapore.
- , 1E Kent Ridge Road, NUHS Tower Block Level 12, Singapore, 119228, Singapore.
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Childhood vascular phenotypes have differing associations with prenatal and postnatal growth. J Hypertens 2021; 39:1884-1892. [PMID: 33853103 PMCID: PMC8373454 DOI: 10.1097/hjh.0000000000002870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
OBJECTIVE In children aged 8--9 years, we examined the associations of linear and abdominal circumference growth during critical stages of prenatal and postnatal development with six vascular measurements commonly used as early markers of atherosclerosis and later cardiovascular disease (CVD) risk. METHODS In 724 children from the UK Southampton Women's Survey mother--offspring cohort, offspring length/height and abdominal circumference measurements were collected at 10 ages between 11 weeks' gestation and age 8--9 years. Using residual growth modelling and linear regression, we examined the independent associations between growth and detailed vascular measures made at 8--9 years. RESULTS Postnatal linear and abdominal circumference growth were associated with higher childhood SBP and carotid--femoral pulse wave velocity, whereas prenatal growth was not. For example, 1SD faster abdominal circumference gain between ages 3 and 6 years was associated with 2.27 [95% confidence interval (CI): 1.56--2.98] mmHg higher SBP. In contrast, faster abdominal circumference gain before 19 weeks' gestation was associated with greater carotid intima--media thickness [0.009 mm (0.004--0.015) per 1SD larger 19-week abdominal circumference), whereas later growth was not. We found no strong associations between prenatal or postnatal growth and DBP or measures of endothelial function. CONCLUSION Higher postnatal linear growth and adiposity gain are related to higher SBP and carotid--femoral pulse wave velocity in childhood. In contrast, faster growth in early gestation is associated with greater childhood carotid intima--media thickness, perhaps resulting from subtle changes in vascular structure that reflect physiological adaptations rather than subclinical atherosclerosis.
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Aris IM, Lin PID, Rifas-Shiman SL, Bailey LC, Boone-Heinonen J, Eneli IU, Solomonides AE, Janicke DM, Toh S, Forrest CB, Block JP. Association of Early Antibiotic Exposure With Childhood Body Mass Index Trajectory Milestones. JAMA Netw Open 2021; 4:e2116581. [PMID: 34251440 PMCID: PMC8276083 DOI: 10.1001/jamanetworkopen.2021.16581] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
IMPORTANCE Past studies have showed associations between antibiotic exposure and child weight outcomes. Few, however, have documented alterations to body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) trajectory milestone patterns during childhood after early-life antibiotic exposure. OBJECTIVE To examine the association of antibiotic use during the first 48 months of life with BMI trajectory milestones during childhood in a large cohort of children. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study used electronic health record data from 26 institutions participating in the National Patient-Centered Clinical Research Network from January 1, 2009, to December 31, 2016. Participant inclusion required at least 1 valid set of same-day height and weight measurements at each of the following age periods: 0 to 5, 6 to 11, 12 to 23, 24 to 59, and 60 to 131 months (183 444 children). Data were analyzed from June 1, 2019, to June 30, 2020. EXPOSURES Antibiotic use at 0 to 5, 6 to 11, 12 to 23, 24 to 35, and 36 to 47 months of age. MAIN OUTCOMES AND MEASURES Age and magnitude of BMI peak and BMI rebound. RESULTS Of 183 444 children in the study (mean age, 3.3 years [range, 0-10.9 years]; 95 228 [51.9%] were boys; 80 043 [43.6%] were White individuals), 78.1% received any antibiotic, 51.0% had at least 1 episode of broad-spectrum antibiotic exposure, and 65.0% had at least 1 episode of narrow-spectrum antibiotic exposure at any time before 48 months of age. Exposure to any antibiotics at 0 to 5 months of age (vs no exposure) was associated with later age (β coefficient, 0.05 months [95% CI, 0.02-0.08 months]) and higher BMI (β coefficient, 0.09 [95% CI, 0.07-0.11]) at peak. Exposure to any antibiotics at 0 to 47 months of age (vs no exposure) was associated with an earlier age (-0.60 months [95% CI, -0.81 to -0.39 months]) and higher BMI at rebound (β coefficient, 0.02 [95% CI, 0.01-0.03]). These associations were strongest for children with at least 4 episodes of antibiotic exposure. Effect estimates for associations with age at BMI rebound were larger for those exposed to antibiotics at 24 to 35 months of age (β coefficient, -0.63 [95% CI, -0.83 to -0.43] months) or 36 to 47 (β coefficient, -0.52 [95% CI, -0.72 to -0.31] months) than for those exposed at 0 to 5 months of age (β coefficient, 0.26 [95% CI, 0.01-0.51] months) or 6 to 11 (β coefficient, 0.00 [95% CI, -0.20 to 0.20] months). CONCLUSIONS AND RELEVANCE In this cohort study, antibiotic exposure was associated with statistically significant, but small, differences in BMI trajectory milestones in infancy and early childhood. The small risk of an altered BMI trajectory milestone pattern associated with early-life antibiotic exposure is unlikely to be a key factor during prescription decisions for children.
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Affiliation(s)
- Izzuddin M. Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Pi-I D. Lin
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Sheryl L. Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - L. Charles Bailey
- Applied Clinical Research Center, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | - Ihuoma U. Eneli
- Center for Healthy Weight and Nutrition, Nationwide Children’s Hospital, Columbus, Ohio
| | - Anthony E. Solomonides
- Center for Biomedical Research Informatics, NorthShore University Health System, Evanston, Illinois
| | - David M. Janicke
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville
| | - Sengwee Toh
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts
| | - Christopher B. Forrest
- Applied Clinical Research Center, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Jason P. Block
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
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Ong YY, Huang JY, Michael N, Sadananthan SA, Yuan WL, Chen LW, Karnani N, Velan SS, Fortier MV, Tan KH, Gluckman PD, Yap F, Chong YS, Godfrey KM, Chong MFF, Chan SY, Lee YS, Tint MT, Eriksson JG. Cardiometabolic Profile of Different Body Composition Phenotypes in Children. J Clin Endocrinol Metab 2021; 106:e2015-e2024. [PMID: 33524127 PMCID: PMC7610678 DOI: 10.1210/clinem/dgab003] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Indexed: 12/11/2022]
Abstract
CONTEXT Cardiometabolic profiles of different body composition phenotypes are poorly characterized in young children, where it is well established that high adiposity is unfavorable, but the role of lean mass is unclear. OBJECTIVE We hypothesized that higher lean mass attenuates cardiometabolic risk in children with high fat mass. METHODS In 6-year-old children (n = 377) from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) prospective birth cohort, whole-body composition was measured by quantitative magnetic resonance, a novel validated technology. Based on fat mass index (FMI) and lean mass index (LMI), 4 body composition phenotypes were derived: low FMI-low LMI (LF-LL), low FMI-high LMI (LF-HL), high FMI-low LMI (HF-LL), high FMI-high LMI (HF-HL). MAIN OUTCOME MEASURES Body mass index (BMI) z-score, fasting plasma glucose, insulin resistance, metabolic syndrome risk score, fatty liver index, and blood pressure. RESULTS Compared with the LF-HL group, children in both high FMI groups had increased BMI z-score (HF-HL: 1.43 units 95% CI [1.11,1.76]; HF-LL: 0.61 units [0.25,0.96]) and metabolic syndrome risk score (HF-HL: 1.64 [0.77,2.50]; HF-LL: 1.28 [0.34,2.21]). The HF-HL group also had increased fatty liver index (1.15 [0.54,1.77]). Girls in HF-HL group had lower fasting plasma glucose (-0.29 mmol/L [-0.55,-0.04]) and diastolic blood pressure (-3.22 mmHg [-6.03,-0.41]) than girls in the HF-LL group. No similar associations were observed in boys. CONCLUSION In a multi-ethnic Asian cohort, lean mass seemed to protect against some cardiometabolic risk markers linked with adiposity, but only in girls. The FMI seemed more important than lean mass index in relation to cardiometabolic profiles of young children.
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Affiliation(s)
- Yi Ying Ong
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jonathan Y. Huang
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Navin Michael
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Suresh Anand Sadananthan
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Wen Lun Yuan
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ling-Wei Chen
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Neerja Karnani
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
| | - S. Sendhil Velan
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore
| | - Marielle V. Fortier
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Diagnostic and Interventional Imaging, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Kok Hian Tan
- Duke-NUS Medical School, Singapore, Singapore
- Department of Maternal Fetal Medicine, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Peter D. Gluckman
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Fabian Yap
- Duke-NUS Medical School, Singapore, Singapore
- Department of Paediatrics, KK Women’s and Children’s Hospital, Singapore, Singapore
| | - Yap-Seng Chong
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Keith M. Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Mary F-F. Chong
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Shiao-Yng Chan
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yung Seng Lee
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Division of Paediatric Endocrinology, Department of Paediatrics, Khoo Teck Puat-National University Children’s Medical Institute, National University Hospital, National University Health System, Singapore
| | - Mya-Thway Tint
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Johan G. Eriksson
- Singapore Institute for Clinical Science, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
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9
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Cai S, Aris IM, Yuan WL, Tan KH, Godfrey KM, Gluckman PD, Shek LPC, Chong YS, Yap F, Fortier MV, Meaney MJ, Lee YS, Qiu A. Neonatal amygdala microstructure mediates the relationship between gestational glycemia and offspring adiposity. BMJ Open Diabetes Res Care 2021; 9:e001396. [PMID: 33888539 PMCID: PMC8070871 DOI: 10.1136/bmjdrc-2020-001396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 03/24/2021] [Accepted: 04/03/2021] [Indexed: 11/16/2022] Open
Abstract
INTRODUCTION To determine if variations in the neonatal amygdala mediate the association between maternal antenatal glycemia and offspring adiposity in early childhood. RESEARCH DESIGN AND METHODS 123 non-obese pregnant women with no pregnancy complications aside from gestational diabetes underwent a 75 g 2-hour oral glucose tolerance test at 26-28 weeks' gestation. Volume and fractional anisotropy (FA) of the neonatal amygdala (5-17 days old) were measured by MRI. The Body Mass Index (BMI) z-scores and sum of skinfold thickness (subscapular and triceps) of these children were tracked up to 60 months of age (18, 24, 36, 48, 54 and 60 months). RESULTS Maternal fasting glucose levels were positively associated with the offspring's sum of skinfold thickness at age 48 months (β=3.12, 95% CI 0.18 to 6.06 mm) and 60 months (β=4.14, 95% CI 0.46 to 7.82 mm) and BMI z-scores at 48 months (β=0.94, 95% CI 0.03 to 1.85), 54 months (β=0.74, 95% CI 0.12 to 1.36) and 60 months (β=0.74, 95% CI 0.08 to 1.39). Maternal fasting glucose was negatively associated with the offspring's FA of the right amygdala (β=-0.019, 95% CI -0.036 to -0.003). Right amygdala FA was negatively associated with the sum of skinfold thickness in the offspring at age 48 months (β=-56.95, 95% CI -98.43 to -15.47 mm), 54 months (β=-46.18, 95% CI -88.57 to -3.78 mm), and 60 months (β=-53.69, 95% CI -105.74 to -1.64 mm). The effect sizes mediated by right amygdala FA between fasting glucose and sum of skinfolds were estimated at β=5.14 (95% CI 0.74 to 9.53) mm (p=0.022), β=4.40 (95% CI 0.08 to 8.72) (p=0.049) mm and β=4.56 (95% CI -0.17 to 9.29) mm (p=0.059) at 48, 54 and 60 months, respectively. CONCLUSIONS In the offspring of non-obese mothers, gestational fasting glucose concentration is negatively associated with neonatal right amygdala FA and positively associated with childhood adiposity. Neonatal right amygdala FA may be a potential mediator between maternal glycemia and childhood adiposity.
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Affiliation(s)
- Shirong Cai
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department for Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Wen Lun Yuan
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Kok Hian Tan
- Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore
- Duke-NUS Medical School, Singapore
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Peter D Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- The Liggins Institute, The University of Auckland, Aukland, New Zealand
| | - Lynette Pei-Chi Shek
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yap-Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department for Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Fabian Yap
- Department of Pediatric Endocrinology, KK Women's and Children's Hospital, Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Departments of Psychiatry and Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Yung Seng Lee
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, Singapore
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10
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Ong YY, Sadananthan SA, Aris IM, Tint MT, Yuan WL, Huang JY, Chan YH, Ng S, Loy SL, Velan SS, Fortier MV, Godfrey KM, Shek L, Tan KH, Gluckman PD, Yap F, Choo JTL, Ling LH, Tan K, Chen L, Karnani N, Chong YS, Eriksson JG, Wlodek ME, Chan SY, Lee YS, Michael N. Mismatch between poor fetal growth and rapid postnatal weight gain in the first 2 years of life is associated with higher blood pressure and insulin resistance without increased adiposity in childhood: the GUSTO cohort study. Int J Epidemiol 2020; 49:1591-1603. [PMID: 32851407 PMCID: PMC7116531 DOI: 10.1093/ije/dyaa143] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Using longitudinal ultrasounds as an improved fetal growth marker, we aimed to investigate if fetal growth deceleration followed by rapid postnatal weight gain is associated with childhood cardiometabolic risk biomarkers in a contemporary well-nourished population. METHODS We defined fetal growth deceleration (FGD) as ultrasound-measured 2nd-3rd-trimester abdominal circumference decrease by ≥0.67 standard deviation score (SDS) and rapid postnatal weight gain (RPWG) as 0-2-year-old weight increase by ≥0.67 SDS. In the GUSTO mother-offspring cohort, we grouped 797 children into four groups of FGD-only (14.2%), RPWG-only (23.3%), both (mismatch, 10.7%) or neither (reference, 51.8%). Adjusting for confounders and comparing with the reference group, we tested associations of these growth groups with childhood cardiometabolic biomarkers: magnetic resonance imaging (MRI)-measured abdominal fat (n = 262), liver fat (n = 216), intramyocellular lipids (n = 227), quantitative magnetic resonance-measured overall body fat % (BF%) (n = 310), homeostasis model assessment of insulin resistance (HOMA-IR) (n = 323), arterial wall thickness (n = 422) and stiffness (n = 443), and blood pressure trajectories (ages 3-6 years). RESULTS Mean±SD birthweights were: FGD-only (3.11 ± 0.38 kg), RPWG-only (3.03 ± 0.37 kg), mismatch (2.87 ± 0.31 kg), reference (3.30 ± 0.36 kg). FGD-only children had elevated blood pressure trajectories without correspondingly increased BF%. RPWG-only children had altered body fat partitioning, higher BF% [BF = 4.26%, 95% confidence interval (CI) (2.34, 6.19)], HOMA-IR 0.28 units (0.11, 0.45)] and elevated blood pressure trajectories. Mismatch children did not have increased adiposity, but had elevated ectopic fat, elevated HOMA-IR [0.29 units (0.04,0.55)] and the highest blood pressure trajectories. Associations remained even after excluding small-for-gestational-age infants from analyses. CONCLUSIONS Fetal growth deceleration coupled with rapid postnatal weight gain was associated with elevated childhood cardiometabolic risk biomarkers without correspondingly increased BF%.
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Affiliation(s)
- Yi Ying Ong
- Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Suresh Anand Sadananthan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Mya Thway Tint
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wen Lun Yuan
- Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jonathan Y Huang
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sharon Ng
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - See Ling Loy
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Sendhil S Velan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Lynette Shek
- Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Pediatrics, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore, Singapore
| | - Kok Hian Tan
- Duke-NUS Medical School, Singapore, Singapore
- Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore
| | - Peter D Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Fabian Yap
- Duke-NUS Medical School, Singapore, Singapore
- Department of Pediatrics, KK Women's and Children's Hospital, Singapore, Singapore
| | | | - Lieng Hsi Ling
- Department of Cardiology, National University Heart Centre, Singapore, Singapore
| | - Karen Tan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Molecular Diagnosis Centre, Department of Laboratory Medicine, National University Health System, Singapore, Singapore
| | - Li Chen
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Neerja Karnani
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Yap-Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Johan G Eriksson
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Mary E Wlodek
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Physiology, University of Melbourne, Melbourne, VIC, Australia
| | - Shiao-Yng Chan
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yung Seng Lee
- Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Pediatrics, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore, Singapore
| | - Navin Michael
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
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11
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Cheng TS, Leung GM, Hui LL, Leung JYY, Kwok MK, Au Yeung SL, Schooling CM. Associations of growth from birth to puberty with blood pressure and lipid profile at ~17.5 years: evidence from Hong Kong's "Children of 1997" birth cohort. Hypertens Res 2020; 42:419-427. [PMID: 30559401 DOI: 10.1038/s41440-018-0170-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The role of early growth in later health is controversial. We examined the associations of growth at different phases from birth to puberty with blood pressure and lipid profile at ~17.5 years. In the population-representative "Children of 1997" birth cohort, growth was measured as (i) weight-for-age z score (WAZ) at birth and WAZ gains from 0 to 2 and 2 to 8 years and (ii) body-mass-index-for-age z score (BAZ) and length/height-for-age z score (LAZ) at 3 months and BAZ and LAZ gains from 3 months to 3 years, 3 to 8 years and 8 to 14 years, based on the World Health Organization growth standards/references. Adjusted partial least squares regression was used to assess simultaneously the associations of growth with height-, age- and sex-specific systolic (SBPZ) and diastolic blood pressure z scores (DBPZ), low- (LDL) and high-density lipoprotein (HDL) and triglycerides (TG) at ~17.5 years. Among 3410 children, higher WAZ, BAZ and LAZ gains from initial size to 8 years were associated with higher SBPZ. Higher gains in WAZ and BAZ from 2 to 8 years were consistently associated with higher DBPZ, LDL and TG and lower HDL. Lower LAZ at 3 months and higher LAZ gain from 3 months to 3 years were associated with lower HDL and higher TG. Greater growth in weight, body mass index and length/height had negative associations with blood pressure and lipid profile at ~17.5 years, but the differences by growth measure, phase and outcome suggest a complex underlying process.
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Affiliation(s)
- Tuck Seng Cheng
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Gabriel M Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Lai Ling Hui
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - June Yue Yan Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Man Ki Kwok
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China. .,School of Public Health and Health Policy, City University of New York, New York, NY, USA.
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12
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Zhang X, Martin RM, Oken E, Aris IM, Yang S, Kramer MS. Growth During Infancy and Early Childhood and Its Association With Metabolic Risk Biomarkers at 11.5 Years of Age. Am J Epidemiol 2020; 189:286-293. [PMID: 31595955 DOI: 10.1093/aje/kwz234] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 09/17/2019] [Accepted: 09/30/2019] [Indexed: 02/06/2023] Open
Abstract
The evidence that fetal life and early infancy are "critical" or "sensitive" ages for later development of cardiometabolic disease is based on flawed methods for comparing different age periods. Moreover, most previous studies have limited their focus to weight gain, rather than growth in length/height or body mass index (weight (kg)/height (m)2). We undertook a secondary analysis of data from the Promotion of Breastfeeding Intervention Trial (1996-2010), a birth cohort study nested within a large cluster-randomized trial in the Republic of Belarus, that had repeated measurements of weight and length/height taken from birth to 11.5 years of age. We used mixed-effects linear models to analyze associations of changes in standardized weight, length/height, and body mass index during 5 age periods (conception to birth, birth to age 3 months, ages 3-12 months, ages 12 months-6.5 years, and ages 6.5-11.5 years) with fasting glucose, insulin, insulin resistance, β-cell function, and adiponectin at age 11.5 years. We observed strong associations between the metabolic markers and all 3 growth measures, with the largest magnitudes being observed during the latest age period (ages 6.5-11.5 years) and negligible associations during gestation and the first year of life. Later age periods appear more "sensitive" than earlier periods to the adverse metabolic association with rapid growth in childhood.
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Affiliation(s)
- Xun Zhang
- Department of Obstetrics and Gynecology, School of Medicine, National University of Singapore, Singapore
| | - Richard M Martin
- Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Emily Oken
- NIHR Bristol Biomedical Research Centre, Bristol, United Kingdom
| | - Izzuddin M Aris
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Seungmi Yang
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Michael S Kramer
- Author affiliations: Department of Pediatrics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
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13
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Zhang X, Tilling K, Martin RM, Oken E, Naimi AI, Aris IM, Yang S, Kramer MS. Analysis of 'sensitive' periods of fetal and child growth. Int J Epidemiol 2020; 48:116-123. [PMID: 29618044 DOI: 10.1093/ije/dyy045] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 03/05/2018] [Accepted: 03/14/2018] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Birth weight and weight gain in infancy and early childhood are commonly studied as risk factors for later cardiometabolic diseases. In this study, we explore methods for quantifying weight gain during different age periods and for comparing the magnitude of the associations with later blood pressure. METHODS Based on data from a birth cohort study nested within a large cluster-randomized trial with repeated measures of weight from birth to 16 years of age, we compared the results of four analytic approaches to assess sensitive periods of growth in relation to blood pressure at age 16 years. RESULTS Approaches based on z-scores of weight or weight gain velocity (both standardized for age and sex) or on regression-based conditional weight standardized residuals yielded more coherent results than an approach based on absolute weight gain velocity. Weight gain standardized by sex and age was positively associated with blood pressure at 16 years at all postnatal age periods, but the magnitude of association was larger during adolescence (11.5-16 years) than during earlier intervals (0-3 months, 3-12 months, 1-6.5 years or 6.5-11.5 years). CONCLUSIONS Standardization of weight and weight gain by age and sex, or regression-based standardized residuals based on conditional weight, reflects relative gain and thus accounts for the rapid weight gains normally observed in early infancy and puberty. Adolescence appears to be a more sensitive period for relative weight gain effects on later blood pressure than earlier periods, even those of similar duration.
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Affiliation(s)
- Xun Zhang
- Department of Pediatrics, McGill University Faculty of Medicine, Montreal, Canada
| | - Kate Tilling
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK.,National Institute for Health Research, Bristol Biomedical Research Center, Bristol, UK
| | - Emily Oken
- Division of Chronic Disease Research across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Ashley I Naimi
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Izzuddin M Aris
- Department of Obstetrics and Gynaecology, National University of Singapore, Singapore
| | - Seungmi Yang
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada
| | - Michael S Kramer
- Department of Pediatrics, McGill University Faculty of Medicine, Montreal, Canada.,Department of Epidemiology, Biostatistics, and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada
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14
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Eny KM, Maguire JL, Dai DWH, Lebovic G, Adeli K, Hamilton JK, Hanley AJ, Mamdani M, McCrindle BW, Tremblay MS, Parkin PC, Birken CS. Association of accelerated body mass index gain with repeated measures of blood pressure in early childhood. Int J Obes (Lond) 2019; 43:1354-1362. [PMID: 30940913 PMCID: PMC6760600 DOI: 10.1038/s41366-019-0345-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 02/18/2019] [Accepted: 02/24/2019] [Indexed: 01/05/2023]
Abstract
Background/objectives We examined the association for rates of age- and sex-standardized body mass index (zBMI) gain between 0–3, 3–18, and 18–36 months with BP in children at 36–72 months of age. Methods We collected repeated measures of zBMI and BP in 2502 children. zBMI was calculated using the World Health Organization standards. Each child’s zBMI at birth and rates of zBMI gain in each period from birth to 36 months were estimated using linear spline multilevel models. Generalized estimating equations were used to determine whether zBMI at birth and zBMI gain between 0–3, 3–18, and 18–36 months were each associated with repeated measures of BP at 36–72 months of age. We sequentially conditioned on zBMI at birth and zBMI gain in each period prior to each period tested, as covariates, and adjusted for important socio-demographic, familial, and study design covariates. We examined whether these associations were modified by birthweight or maternal obesity, by including interaction terms. Results After adjusting for all covariates and conditioning on prior zBMI gains, a 1 standard deviation unit faster rate of zBMI gain during 0–3 months, (β = 0.59 mmHg; 95% CI 0.31, 0.86) and 3–18 months (β = 0.74 mmHg; 95% CI 0.46, 1.03) were each associated with higher systolic BP at 36–72 months. No significant associations were observed, however, for zBMI at birth or zBMI gain in the 18–36 month growth period. zBMI gains from 0–3 and 3–18 months were also associated with diastolic BP. Birthweight significantly modified the relationship during the 3–18 month period (p = 0.02), with the low birthweight group exhibiting the strongest association for faster rate of zBMI gain with higher systolic BP (β = 1.31 mmHg; 95% CI 0.14, 2.48). Conclusions Given that long-term exposure to small elevations in BP are associated with subclinical cardiovascular disease, promoting interventions targeting healthy growth in infancy may be important.
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Affiliation(s)
- Karen M Eny
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Canada
| | - Jonathon L Maguire
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada.,Department of Pediatrics, St. Michael's Hospital, Toronto, Canada.,Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.,Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, Canada.,Department of Nutritional Sciences, University of Toronto, Toronto, Canada
| | - David W H Dai
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
| | - Gerald Lebovic
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada.,Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Khosrow Adeli
- Department of Laboratory Medicine and Pathobiology, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Jill K Hamilton
- Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, Canada.,Division of Endocrinology, The Hospital for Sick Children, Toronto, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, University of Toronto, Toronto, Canada
| | - Muhammad Mamdani
- Li Ka Shing Centre for Healthcare Analytics Research and Training, St. Michael's Hospital, Toronto, Canada
| | - Brian W McCrindle
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Canada.,Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, Canada.,Preventative Cardiology, The Hospital for Sick Children, Toronto, Canada
| | - Mark S Tremblay
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Patricia C Parkin
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Canada.,Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.,Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Catherine S Birken
- Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Canada. .,Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada. .,Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, Canada. .,Department of Nutritional Sciences, University of Toronto, Toronto, Canada.
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15
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Oh JH, Hong YM. Blood Pressure Trajectories from Childhood to Adolescence in Pediatric Hypertension. Korean Circ J 2019; 49:223-237. [PMID: 30808073 PMCID: PMC6393321 DOI: 10.4070/kcj.2018.0448] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 12/24/2018] [Indexed: 11/29/2022] Open
Abstract
It has been known for a long time that elevated blood pressure (BP) in the young may persist and progress into adult hypertension (HTN). Multiple studies have revealed the predicted BP trajectory lines starting from childhood and related them to later cardiovascular (CV) risks in adulthood. As a small baby grows into a tall adult, BP will also naturally increase. Among early-life predictors of adult HTN, birth history, such as prematurity, and low birth weight have been popular subjects in research on pediatric HTN, because body size at birth has been reported to be inversely related to the risk of adulthood HTN. The hypothesis of HTN in prematurely born adolescents has been postulated as a physiological predisposition to postnatal excessive weight gain. Current body weight is a well-known independent predictor of HTN in children, and some studies showed that children demonstrating upward crossing of their weight percentiles while growing into adolescents have significantly increased risk for elevated BP later in life. Recently, reports focused on the adverse effect of excessive catch-up growth in this population are gradually drawing attention. Accordingly, children born prematurely or with intrauterine growth restriction who show rapid changes in their weight percentile should be under surveillance with BP monitoring. Prevention of childhood obesity, along with special care for premature infants or infants small for their gestational age, by providing healthy nutritional guidelines should be cardinal strategies for the prevention of adult HTN and CV risks later in life.
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Affiliation(s)
- Jin Hee Oh
- Department of Pediatrics, St.Vincent's Hospital, The Catholic University of Korea, Seoul, Korea
| | - Young Mi Hong
- Department of Pediatrics, Ewha Womans University Hospital College of Medicine, Seoul, Korea.
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16
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Sadananthan SA, Tint MT, Michael N, Aris IM, Loy SL, Lee KJ, Shek LPC, Yap FKP, Tan KH, Godfrey KM, Leow MKS, Lee YS, Kramer MS, Gluckman PD, Chong YS, Karnani N, Henry CJ, Fortier MV, Velan SS. Association Between Early Life Weight Gain and Abdominal Fat Partitioning at 4.5 Years is Sex, Ethnicity, and Age Dependent. Obesity (Silver Spring) 2019; 27:470-478. [PMID: 30707510 PMCID: PMC6392178 DOI: 10.1002/oby.22408] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 11/28/2018] [Indexed: 12/20/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the independent associations between age-specific annual weight gain from birth to age 4 years and fat deposition in metabolically distinct compartments at age 4.5 years in a South Asian longitudinal birth cohort. METHODS Volumetric abdominal magnetic resonance imaging with comprehensive segmentation of deep and superficial subcutaneous adipose tissue (SAT) and visceral adipose tissues (VAT) was performed in 316 children (150 boys and 166 girls in three ethnic groups; 158 Chinese, 94 Malay, and 64 Indian) aged 4.5 years. Associations between fat volumes and annual relative weight gain conditional on past growth were assessed overall and stratified by sex and ethnicity. RESULTS Conditional relative weight gain had stronger associations with greater SAT and VAT at age 4.5 years in girls than boys and in Indians compared with Malay and Chinese. Overall, the magnitude of association was the largest during 2 to 3 years for SAT and 1 to 2 years for VAT. Despite similar body weight, Indian children and girls had the highest deep and superficial SAT volumes at age 4.5 years (all interactions P < 0.05). No significant sex or ethnic differences were observed in VAT. With increasing BMI, Indian children had the highest tendency to accumulate VAT, and girls accumulated more fat than boys in all depots (all interactions P < 0.001). CONCLUSIONS Indian ethnicity and female sex predisposed children to accumulate more fat in the VAT depot with increasing conditional relative weight gain in the second year of life. Thus, 1 to 2 years of age may be a critical window for interventions to reduce visceral fat accumulation.
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Affiliation(s)
- Suresh Anand Sadananthan
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
| | - Mya Thway Tint
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Navin Michael
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
| | - Izzuddin M Aris
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
| | - See Ling Loy
- Department of Reproductive Medicine, KK Women’s and Children’s Hospital, Singapore
- Duke-NUS Medical School, Singapore
| | - Kuan Jin Lee
- Singapore BioImaging Consortium, Agency for Science Technology and Research, Singapore
| | - Lynette Pei-Chi Shek
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Fabian Kok Peng Yap
- Duke-NUS Medical School, Singapore
- Department of Paediatric Endocrinology, KK Women’s and Children’s Hospital, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Kok Hian Tan
- Duke-NUS Medical School, Singapore
- Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, Singapore
| | - Keith M. Godfrey
- MRC Lifecourse Epidemiology Unit & NIHR Southampton Biomedical Research Centre, University of Southampton & University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Melvin Khee-Shing Leow
- Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences, Agency for Science Technology and Research and National University Health System, Singapore
- Department of Endocrinology, Tan Tock Seng Hospital, Singapore
| | - Yung Seng Lee
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael S. Kramer
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Canada
| | - Peter D. Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Neerja Karnani
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
| | - Christiani Jeyakumar Henry
- Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences, Agency for Science Technology and Research and National University Health System, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Marielle Valerie Fortier
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Department of Diagnostic and Interventional Imaging, KK Women’s and Children’s Hospital, Singapore
| | - S. Sendhil Velan
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore
- Singapore BioImaging Consortium, Agency for Science Technology and Research, Singapore
- Corresponding author: S. Sendhil Velan, Singapore Institute for Clinical Sciences and Singapore Bioimaging Consortium, 11 Biopolis Way, #02-02, Singapore 138667. Phone: +65 64788757,
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17
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Aris IM, Rifas-Shiman SL, Li LJ, Kleinman KP, Coull BA, Gold DR, Hivert MF, Kramer MS, Oken E. Patterns of body mass index milestones in early life and cardiometabolic risk in early adolescence. Int J Epidemiol 2019; 48:157-167. [PMID: 30624710 PMCID: PMC6380298 DOI: 10.1093/ije/dyy286] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2018] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Few studies have examined the independent and combined relationships of body mass index (BMI) peak and rebound with adiposity, insulin resistance and metabolic risk later in life. We used data from Project Viva, a well-characterized birth cohort from Boston with repeated measures of BMI, to help fill this gap. METHODS Among 1681 children with BMI data from birth to mid childhood, we fitted individual BMI trajectories using mixed-effects models with natural cubic splines and estimated age, and magnitude of BMI, at peak (in infancy) and rebound (in early childhood). We obtained cardiometabolic measures of the children in early adolescence (median 12.9 years) and analysed their associations with the BMI parameters. RESULTS After adjusting for potential confounders, age and magnitude at infancy BMI peak were associated with greater adolescent adiposity, and earlier adiposity rebound was strongly associated with greater adiposity, insulin resistance and metabolic risk score independently of BMI peak. Children with a normal timing of BMI peak plus early rebound had an adverse cardiometabolic profile, characterized by higher fat mass index {β 2.2 kg/m2 [95% confidence interval (CI) 1.6, 2.9]}, trunk fat mass index [1.1 kg/m2 (0.8, 1.5)], insulin resistance [0.2 units (0.04, 0.4)] and metabolic risk score [0.4 units (0.2, 0.5)] compared with children with a normal BMI peak and a normal rebound pattern. Children without a BMI peak (no decline in BMI after the rise in infancy) also had adverse adolescent metabolic profiles. CONCLUSIONS Early age at BMI rebound is a strong risk factor for cardiometabolic risk, independent of BMI peak. Children with a normal peak-early rebound pattern, or without any BMI decline following infancy, are at greatest risk of adverse cardiometabolic profile in adolescence. Routine monitoring of BMI may help to identify children who are at greatest risk of developing an adverse cardiometabolic profile in later life and who may be targeted for preventive interventions.
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Affiliation(s)
- Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Ling-Jun Li
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Division of Obstetrics and Gynecology, KK Women’s and Children’s Hospital, Singapore, Singapore
- Obstetrics and Gynecology Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
| | - Ken P Kleinman
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Diane R Gold
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Environmental Medicine, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Michael S Kramer
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Departments of Pediatrics
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, QC, Canada
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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18
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Chia AR, Tint MT, Han CY, Chen LW, Colega M, Aris IM, Chua MC, Tan KH, Yap F, Shek LPC, Chong YS, Godfrey KM, Fortier MV, Lee YS, Chong MFF. Adherence to a healthy eating index for pregnant women is associated with lower neonatal adiposity in a multiethnic Asian cohort: the Growing Up in Singapore Towards healthy Outcomes (GUSTO) Study. Am J Clin Nutr 2018; 107:71-79. [PMID: 29381790 PMCID: PMC5972656 DOI: 10.1093/ajcn/nqx003] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 10/13/2017] [Indexed: 12/20/2022] Open
Abstract
Background Evidence linking maternal diet quality during pregnancy with infant birth outcomes is limited in Asia. Objective We investigated the association of maternal diet quality with the risk of preterm birth, offspring birth size, and adiposity in a multiethnic Asian birth cohort. Design Dietary intakes of 1051 pregnant women were ascertained at 26-28 wk of gestation with the use of 24-h recalls and 3-d food diaries, from which diet quality (score range: 0-100) was measured by the Healthy Eating Index for pregnant women in Singapore (HEI-SGP). Gestational age was established by first-trimester ultrasound dating scan. Neonatal weight and length were measured at birth. Body composition was assessed by air displacement plethysmography in a subset of infants (n = 313) within 72 h after birth, and abdominal adiposity was assessed by MRI (n = 316) within the first 2 wk of life. Associations were assessed by multivariable linear regression for continuous outcomes and logistic regression for preterm birth. Results The mean ± SD maternal HEI-SGP score was 52.1 ± 13.6. Maternal diet quality during pregnancy was not associated with preterm birth or birth weight. Greater adherence to the HEI-SGP (per 10-point increment in HEI-SGP score) was associated with longer birth length [β (95% CI): 0.14 (0.03, 0.24 cm)], lower body mass index (in kg/m2) at birth [-0.07 (-0.13, -0.01)], lower sum of triceps and subscapular skinfold thickness [-0.15 (-0.26, -0.05 mm)], lower percentage body fat [-0.52% (-0.84%, -0.20%)], lower fat mass [-17.23 (-29.52, -4.94 g)], lower percentage abdominal superficial subcutaneous adipose tissue [-0.16% (-0.30%, -0.01%)], and lower percentage deep subcutaneous adipose tissue [-0.06% (-0.10%, -0.01%)]. Conclusions Higher maternal diet quality during pregnancy was associated with longer birth length and lower neonatal adiposity but not with birth weight and preterm birth. These findings warrant further investigation in independent studies. This trial was registered at clinicaltrials.gov as NCT01174875.
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Affiliation(s)
- Ai-Ru Chia
- Departments of Obstetrics and Gynecology and Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Mya-Thway Tint
- Departments of Obstetrics and Gynecology and Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Chad Yixian Han
- Department of Dietetics and Nutrition, Ng Teng Fong General Hospital, National University Health System, Singapore
| | - Ling-Wei Chen
- Departments of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Marjorelee Colega
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore
| | - Izzuddin M Aris
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore
| | - Mei-Chien Chua
- Departments of Neonatology, Maternal Fetal Medicine, Pediatrics, and Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore
| | - Kok-Hian Tan
- Departments of Maternal Fetal Medicine, Pediatrics, and Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore
| | - Fabian Yap
- Departments of Pediatrics, and Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Lynette Pei-Chi Shek
- Departments of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Divisions of Pediatric Allergy, Immunology, and Rheumatology and Pediatric Endocrinology and Diabetes, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore
| | - Yap-Seng Chong
- Departments of Obstetrics and Gynecology and Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore
| | - Keith M Godfrey
- Medical Research Council Lifecourse Epidemiology Unit and National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service Foundation Trust, Southampton, United Kingdom
| | - Marielle V Fortier
- Departments of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore
| | - Yung Seng Lee
- Departments of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore
- Divisions of Pediatric Endocrinology and Diabetes, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore
| | - Mary Foong-Fong Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
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19
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Aris IM, Chen LW, Tint MT, Pang WW, Soh SE, Saw SM, Shek LPC, Tan KH, Gluckman PD, Chong YS, Yap F, Godfrey KM, Kramer MS, Lee YS. Body mass index trajectories in the first two years and subsequent childhood cardio-metabolic outcomes: a prospective multi-ethnic Asian cohort study. Sci Rep 2017; 7:8424. [PMID: 28827610 PMCID: PMC5567284 DOI: 10.1038/s41598-017-09046-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Accepted: 07/20/2017] [Indexed: 12/31/2022] Open
Abstract
We investigated body mass index (BMI) trajectories in the first 2 years of life in 1170 children from an Asian mother-offspring cohort in Singapore, and examined their predictors and associations with childhood cardio-metabolic risk measures at 5 years. Latent class growth mixture modelling analyses were performed to identify distinct BMI z-score (BMIz) trajectories. Four trajectories were identified: 73.2%(n = 857) of the children showed a normal BMIz trajectory, 13.2%(n = 155) a stable low-BMIz trajectory, 8.6%(n = 100) a stable high-BMIz trajectory and 5.0%(n = 58) a rapid BMIz gain after 3 months trajectory. Predictors of the stable high-BMIz and rapid BMIz gain trajectories were pre-pregnancy BMI, gestational weight gain, Malay and Indian ethnicity, while predictors of stable low-BMIz trajectory were preterm delivery and Indian ethnicity. At 5 years, children with stable high-BMIz or rapid BMIz gain trajectories had increased waist-to-height ratios [B(95%CI) 0.02(0.01,0.03) and 0.03(0.02,0.04)], sum of skinfolds [0.42(0.19,0.65) and 0.70(0.36,1.03)SD units], fat-mass index [0.97(0.32,1.63)SD units] and risk of obesity [relative risk 3.22(1.73,6.05) and 2.56 (1.19,5.53)], but not higher blood pressure. BMIz trajectories were more predictive of adiposity at 5 years than was BMIz at 2 years. Our findings on BMIz trajectories in the first 2 years suggest important ethnic-specific differences and impacts on later metabolic outcomes.
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Affiliation(s)
- Izzuddin M Aris
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.
| | - Ling-Wei Chen
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Mya Thway Tint
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wei Wei Pang
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shu E Soh
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Lynette Pei-Chi Shek
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kok-Hian Tan
- Department of Obstetrics and Gynaecology, KK Women's and Children's Hospital, Singapore, Singapore
| | - Peter D Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Yap-Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Fabian Yap
- Department of Paediatrics, KK Women's and Children's Hospital, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Singapore, Singapore
| | - Michael S Kramer
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Canada
| | - Yung Seng Lee
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore
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