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Johnson W, Pereira SMP, Costa S, Baker JL, Norris T. The associations of maternal and paternal obesity with latent patterns of offspring BMI development between 7 and 17 years of age: pooled analyses of cohorts born in 1958 and 2001 in the United Kingdom. Int J Obes (Lond) 2023; 47:39-50. [PMID: 36357563 PMCID: PMC9834052 DOI: 10.1038/s41366-022-01237-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE We aimed to 1) describe how the UK obesity epidemic reflects a change over time in the proportion of the population demonstrating adverse latent patterns of BMI development and 2) investigate the potential roles of maternal and paternal BMI in this secular process. METHODS We used serial BMI data between 7 and 17 years of age from 13220 boys and 12711 girls. Half the sample was born in 1958 and half in 2001. Sex-specific growth mixture models were developed. The relationships of maternal and paternal BMI and weight status with class membership were estimated using the 3-step BCH approach, with covariate adjustment. RESULTS The selected models had five classes. For each sex, in addition to the two largest normal weight classes, there were "normal weight increasing to overweight" (17% of boys and 20% of girls), "overweight increasing to obesity" (8% and 6%), and "overweight decreasing to normal weight" (3% and 6%) classes. More than 1-in-10 children from the 2001 birth cohort were in the "overweight increasing to obesity" class, compared to less than 1-in-30 from the 1958 birth cohort. Approximately 75% of the mothers and fathers of this class had overweight or obesity. When considered together, both maternal and paternal BMI were associated with latent class membership, with evidence of negative departure from additivity (i.e., the combined effect of maternal and paternal BMI was smaller than the sum of the individual effects). The odds of a girl belonging to the "overweight increasing to obesity" class (compared to the largest normal weight class) was 13.11 (8.74, 19.66) times higher if both parents had overweight or obesity (compared to both parents having normal weight); the equivalent estimate for boys was 9.01 (6.37, 12.75). CONCLUSIONS The increase in obesity rates in the UK over more than 40 years has been partly driven by the growth of a sub-population demonstrating excess BMI gain during adolescence. Our results implicate both maternal and paternal BMI as correlates of this secular process.
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Affiliation(s)
- William Johnson
- grid.6571.50000 0004 1936 8542School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Snehal M. Pinto Pereira
- grid.83440.3b0000000121901201UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Silvia Costa
- grid.6571.50000 0004 1936 8542School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Jennifer L. Baker
- grid.411702.10000 0000 9350 8874Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
| | - Tom Norris
- grid.83440.3b0000000121901201UCL Division of Surgery & Interventional Science, University College London, London, UK
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Oosterhoff M, Jolani S, De Bruijn-Geraets D, van Giessen A, Bosma H, van Schayck OC, Joore MA. BMI trajectories after primary school-based lifestyle intervention: Unravelling an uncertain future. A mixed methods study. Prev Med Rep 2021; 21:101314. [PMID: 33537184 PMCID: PMC7841358 DOI: 10.1016/j.pmedr.2021.101314] [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] [Received: 06/09/2020] [Revised: 12/13/2020] [Accepted: 12/20/2020] [Indexed: 11/03/2022] Open
Abstract
This mixed methods study aimed to examine plausible body mass index (BMI) trajectories after exposure to a primary school-based lifestyle intervention to aid in estimating the long-term intervention benefits. BMI trajectories for children at control schools (mean 7.6 years of age) were modelled until 20 years of age through extrapolating trial evidence (N = 1647). A reference scenario assumed that the observed 2-year effects of the 'Healthy Primary Schools of the Future' (HPSF) and 'Physical Activity Schools' (PAS) were fully maintained over time. This was modelled by applying the observed 2-year BMI effects until 20 years of age. Expert opinions on likely trends in effect maintenance after the 2-year intervention period were elicited qualitatively and quantitatively, and were used for developing alternative scenarios. Expert elicitation revealed three scenarios: (a) a constant exposure-effect and an uncontrolled environment with effect decay scenario, (b) a household multiplier and an uncontrolled environment with effect decay scenario, and (c) a household multiplier and maintainer scenario. The relative effect of HPSF at 20 years of age was -0.21 kg/m2 under the reference scenario, and varied from -0.04 kg/m2 (a) to -0.06 kg/m2 (b), and -0.50 kg/m2 (c). For PAS, the relative effect was -0.17 kg/m2 under the reference scenario, and varied from -0.04 kg/m2 (a, b), to -0.21 kg/m2 (c). The mixed methods approach proved to be useful in modelling plausible BMI trajectories and specifying uncertainty on effect maintenance. Further observations until adulthood could reduce the uncertainty around future benefits. This trial was retrospectively registered at Clinicaltrials.gov (NCT02800616).
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Affiliation(s)
- Marije Oosterhoff
- Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA) Maastricht University Medical Centre MUMC+, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands
| | - Shahab Jolani
- Department of Methodology and Statistics, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands
| | - Daisy De Bruijn-Geraets
- Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA) Maastricht University Medical Centre MUMC+, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands
| | - Anoukh van Giessen
- Center for Prevention and Health Services, National Institute of Public Health and the Environment, Bilthoven, the Netherlands
| | - Hans Bosma
- Department of Social Medicine, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands
| | - Onno C.P. van Schayck
- Department of Family Medicine, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands
| | - Manuela A. Joore
- Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA) Maastricht University Medical Centre MUMC+, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands
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O'Connor TG, Williams J, Blair C, Gatzke-Kopp LM, Francis L, Willoughby MT. Predictors of Developmental Patterns of Obesity in Young Children. Front Pediatr 2020; 8:109. [PMID: 32266187 PMCID: PMC7105829 DOI: 10.3389/fped.2020.00109] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/03/2020] [Indexed: 12/22/2022] Open
Abstract
Introduction: The current study characterizes longitudinal patterns in obesity in young children and their prediction from developmental programming and social determinant hypotheses. Materials and Methods: The data are based on the Family Life Project, a prospective longitudinal study of 1,292 families recruited from low-income, racially diverse, rural communities in Pennsylvania, and North Carolina. Pre-natal, peri-natal, and post-natal risks for childhood obesity were collected from 2 months of age; in-person assessments of child growth were used to identity obesity on multiple occasions from 24 to 90 months of age. Results: Two major novel findings emerged. First, longitudinal analyses identified four distinct obesity development profiles: stable obesity, later-onset obesity, moderate/declining obesity, and non-obese; these groups had distinct risk profiles. Second, prediction analyses favored developmental programming explanations for obesity, including evidence even in early childhood that both low- and high birth weight was associated with stable obesity. There was no indication that pre- and peri-natal and post-natal factors predicted obesity differently in non-minority and minority children. Discussion: Factors derived from the developmental programming model of obesity overlapped with, but predicted early onset obesity independently from, risks associated with social determinant models of obesity.
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Affiliation(s)
- Thomas G O'Connor
- Department of Psychiatry, University of Rochester, Rochester, NY, United States.,Department of Psychology, University of Rochester, Rochester, NY, United States.,Department of Neuroscience, University of Rochester, Rochester, NY, United States.,Department of Obstetrics and Gynecology, University of Rochester, Rochester, NY, United States.,Wynne Center for Family Research, University of Rochester, Rochester, NY, United States
| | - Jason Williams
- RTI International, Research Triangle Park, Durham, NC, United States
| | - Clancy Blair
- Department of Population Health, New York University, New York, NY, United States
| | - Lisa M Gatzke-Kopp
- Department of Human Development and Family Studies, The Pennsylvania State University, State College, PA, United States
| | - Lori Francis
- Department of Biobehavioral Health, The Pennsylvania State University, State College, PA, United States
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Wu Z, Ma Y. The relationship of cardiorespiratory fitness and venous thromboembolism: yes or no? SCAND CARDIOVASC J 2019; 54:66. [PMID: 31707863 DOI: 10.1080/14017431.2019.1684551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Zhoupeng Wu
- Department of Vascular Surgery, West China Hospital, Chengdu, China
| | - Yukui Ma
- Department of Vascular Surgery, West China Hospital, Chengdu, China
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Robinson HA, Dam R, Hassan L, Jenkins D, Buchan I, Sperrin M. Post-2000 growth trajectories in children aged 4-11 years: A review and quantitative analysis. Prev Med Rep 2019; 14:100834. [PMID: 30976485 PMCID: PMC6439270 DOI: 10.1016/j.pmedr.2019.100834] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 02/15/2019] [Accepted: 02/16/2019] [Indexed: 02/08/2023] Open
Abstract
Children's body mass index (BMI) growth trajectories are associated with adult health outcomes, and vary by geography and epoch. Understanding these trajectories could help to identify high risk children and thus support improved health outcomes. In this review, we compare and quantitatively analyse BMI level and trajectory data published since 2010. We characterise recent growth in children aged 4-11 years, an age range most frequently targeted for BMI intervention, yet less studied than young childhood or infancy. Through searches in OVID, we identified 54 relevant texts which describe either post-2000 summary BMI values by age and gender in cohorts with sample sizes of over 1000 children, or the results of latent class analyses of BMI trajectories within the 4-11 year age range. Population level median growth curves were projected and visualised as weighted means. These BMI curves, based on data from 729,692 children, can be visually clustered into 'high' and 'low' charting groups with extreme outlying values. Within populations, latent class analyses converge on 3-4 individual child trajectories, two of which predispose adult overweight. These growth pathways diverge early in childhood, yet are not effectively distinguished via isolated BMI measurements taken between 4 and 11 years, meaning some high risk children may currently be poorly identified.
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Graversen L, Howe LD, Sørensen TIA, Sovio U, Hohwü L, Tilling K, Laitinen J, Taanila A, Pouta A, Järvelin M, Obel C. Body mass index trajectories from 2 to 18 years - exploring differences between European cohorts. Pediatr Obes 2017; 12:102-109. [PMID: 26918667 PMCID: PMC5347959 DOI: 10.1111/ijpo.12115] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Revised: 10/26/2015] [Accepted: 11/28/2015] [Indexed: 12/03/2022]
Abstract
BACKGROUND In recent decades, there has been an increase in the prevalence of childhood overweight in most high-income countries. Within northern Europe, prevalence tends to be higher in the UK compared with the Scandinavian countries. We aimed to study differences in body mass index (BMI) trajectories between large cohorts of children from UK and Scandinavian populations. METHODS We compared BMI trajectories in participants from the English Avon Longitudinal Study of Parents and Children born in 1991-1993 (ALSPAC) (N = 6517), the Northern Finland Birth Cohorts born in 1966 (NFBC1966) (N = 3321) and 1986 (NFBC1986) (N = 4764), and the Danish Aarhus Birth Cohort born in 1990-1992 (ABC) (N = 1920). We used multilevel models to estimate BMI trajectories from 2 to 18 years. We explored whether cohort differences were explained by maternal BMI, height, education or smoking during pregnancy and whether differences were attributable to changes in the degree of skew in the BMI distribution. RESULTS Differences in mean BMI between the cohorts were small but emerged early and persisted in most cases across childhood. Girls in ALSPAC had a higher BMI than all other cohorts throughout childhood, e.g. compared with the NFBC1986 BMI was 2.2-3.5% higher. For boys, the difference emerging over time (comparing the two NFBC's) exceeded the differences across populations (comparing NFBC1986, ABC and ALSPAC). BMI distribution demonstrated increasing right skew with age. CONCLUSION Population-level differences between cohorts were small, tended to emerge very early, persisted across childhood, and demonstrated an increase in the right-hand tail of the BMI distribution.
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Affiliation(s)
- L. Graversen
- Section for General Medical Practice, Department of Public HealthAarhus UniversityAarhusDenmark
| | - L. D. Howe
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK,School of Social and Community MedicineUniversity of BristolBristolUK
| | - T. I. A. Sørensen
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK,Institute of Preventive MedicineBispebjerg and Frederiksberg HospitalsCopenhagenDenmark,Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical SciencesUniversity of CopenhagenCopenhagenDenmark
| | - U. Sovio
- Department of Obstetrics and GynaecologyUniversity of CambridgeCambridgeUK,Department of Epidemiology and BiostatisticsImperial CollegeLondonUK
| | - L. Hohwü
- Section for General Medical Practice, Department of Public HealthAarhus UniversityAarhusDenmark
| | - K. Tilling
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK,School of Social and Community MedicineUniversity of BristolBristolUK
| | - J. Laitinen
- Finnish Institute of Occupational HealthHelsinkiFinland
| | - A. Taanila
- Institute of Health SciencesUniversity of OuluOuluFinland,Unit of Primary CareUniversity Hospital of OuluOuluFinland
| | - A. Pouta
- National Institute of Health and WelfareOuluFinland,Department of Obstetrics and GynecologyUniversity of Oulu and Oulu University HospitalOuluFinland
| | - M‐R. Järvelin
- Department of Epidemiology and BiostatisticsImperial CollegeLondonUK,Unit of Primary CareUniversity Hospital of OuluOuluFinland,Biocenter OuluUniversity of OuluOuluFinland,Center for Life Course EpidemiologyUniversity of OuluOuluFinland
| | - C. Obel
- Section for General Medical Practice, Department of Public HealthAarhus UniversityAarhusDenmark
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