Dynamic prediction model to identify young children at high risk of future overweight: Development and internal validation in a cohort study

Autor: Marleen Hamoen, Jos W. R. Twisk, Ulrike Gehring, Marlou L. A. de Kroon, Martijn W. Heymans, Gerard H. Koppelman, Hein Raat, Alet H. Wijga, Marieke Welten
Přispěvatelé: Public Health, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Epidemiology and Data Science, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Methodology, Groningen Research Institute for Asthma and COPD (GRIAC), Public Health Research (PHR)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Male
0301 basic medicine
Pediatric Obesity
Overweight
general population
Body Mass Index
Cohort Studies
0302 clinical medicine
Pregnancy
Risk Factors
Surveys and Questionnaires
Ethnicity
Birth Weight
4-YEAR-OLD CHILDREN
Child
Generalized estimating equation
Original Research
Netherlands
young children
education.field_of_study
Nutrition and Dietetics
Health Policy
Incidence (epidemiology)
Area under the curve
PREVALENCE
Child
Preschool
OBESITY
Educational Status
GROWTH
Female
medicine.symptom
Cohort study
Population
future overweight
030209 endocrinology & metabolism
primordial prevention
dynamic prediction model
03 medical and health sciences
medicine
cohort study
Humans
education
CHILDHOOD OVERWEIGHT
030109 nutrition & dietetics
CONSEQUENCES
business.industry
Public Health
Environmental and Occupational Health
Infant
medicine.disease
Obesity
PREVENTION
primordialprevention
Pediatrics
Perinatology and Child Health
WEIGHT
business
Body mass index
Demography
Zdroj: Pediatric obesity, 15(9):e12647. Wiley-Blackwell for the International Association for the Study of Obesity
Pediatric Obesity, 15(9):e12647. Wiley-Blackwell
Pediatric obesity, 15(9):12647
Pediatric Obesity
Welten, M, Wijga, A H, Hamoen, M, Gehring, U, Koppelman, G H, Twisk, J W R, Raat, H, Heymans, M W & de Kroon, M L A 2020, ' Dynamic prediction model to identify young children at high risk of future overweight : Development and internal validation in a cohort study ', Pediatric Obesity, vol. 15, no. 9, e12647 . https://doi.org/10.1111/ijpo.12647
Pediatric obesity, 15(9), 1. Wiley-Blackwell for the International Association for the Study of Obesity
ISSN: 2047-6310
2047-6302
Popis: BACKGROUND: Primary prevention of overweight is to be preferred above secondary prevention, which has shown moderate effectiveness.OBJECTIVE: To develop and internally validate a dynamic prediction model to identify young children in the general population, applicable at every age between birth and age 6, at high risk of future overweight (age 8).METHODS: Data were used from the Prevention and Incidence of Asthma and Mite Allergy birth cohort, born in 1996 to 1997, in the Netherlands. Participants for whom data on the outcome overweight at age 8 and at least three body mass index SD scores (BMI SDS) at the age of ≥3 months and ≤6 years were available, were included (N = 2265). The outcome of the prediction model is overweight (yes/no) at age 8 (range 7.4-10.5 years), defined according to the sex- and age-specific BMI cut-offs of the International Obesity Task Force.RESULTS: After backward selection in a Generalized Estimating Equations analysis, the prediction model included the baseline predictors maternal BMI, paternal BMI, paternal education, birthweight, sex, ethnicity and indoor smoke exposure; and the longitudinal predictors BMI SDS, and the linear and quadratic terms of the growth curve describing a child's BMI SDS development over time, as well as the longitudinal predictors' interactions with age. The area under the curve of the model after internal validation was 0.845 and Nagelkerke R2 was 0.351.CONCLUSIONS: A dynamic prediction model for overweight was developed with a good predictive ability using easily obtainable predictor information. External validation is needed to confirm that the model has potential for use in practice.
Databáze: OpenAIRE
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