A Cross-Sectional Investigation of Preadolescent Cardiometabolic Health: Associations with Fitness, Physical Activity, Sedentary Behavior, Nutrition, and Sleep

Author:

Castro Nicholas1,Zieff Gabriel2ORCID,Bates Lauren C.2ORCID,Pagan Lassalle Patricia2,Higgins Simon2,Faulkner James3ORCID,Lark Sally4,Skidmore Paula5,Hamlin Michael J.6ORCID,Signal T. Leigh7,Williams Michelle A.8,Stoner Lee2ORCID

Affiliation:

1. School of Health and Applied Human Sciences, University of North Carolina Wilmington, Wilmington, NC 28403, USA

2. Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27513, USA

3. School of Sport, Health, and Community, University of Winchester, Winchester SO224NR, UK

4. School of Sport, Exercise and Nutrition, Massey University, Wellington 4442, New Zealand

5. Department of Medicine, University of Otago, Dunedin 9016, New Zealand

6. Department of Tourism, Sport and Society, Lincoln University, Christchurch 7647, New Zealand

7. School of Health Sciences, Sleep-Wake Research Centre, Massey University, Wellington 4442, New Zealand

8. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA

Abstract

Background: Cardiometabolic disease (CMD) risk often begins early in life. Healthy lifestyle behaviors can mitigate risk, but the optimal combination of behaviors has not been determined. This cross-sectional study simultaneously examined the associations between lifestyle factors (fitness, activity behaviors, and dietary patterns) and CMD risk in preadolescent children. Methods: 1480 New Zealand children aged 8–10 years were recruited. Participants included 316 preadolescents (50% female, age: 9.5 ± 1.1 years, BMI: 17.9 ± 3.3 kg/m2). Fitness (cardiorespiratory fitness [CRF], muscular fitness), activity behaviors (physical activity, sedentary, sleep), and dietary patterns were measured. Factor analysis was used to derive a CMD risk score from 13 variables (adiposity, peripheral and central hemodynamics, glycemic control, and blood lipids). Results: Only CRF (β = −0.45, p < 0.001) and sedentary time (β = 0.12, p = 0.019) were associated with the CMD risk score in the adjusted multivariable analysis. CRF was found to be nonlinear (VO2 max ≤ ≈42 mL/kg/min associated with higher CMD risk score), and thus a CRF polynomial term was added, which was also associated (β = 0.19, p < 0.001) with the CMD risk score. Significant associations were not found with sleep or dietary variables. Conclusion: The findings indicate that increasing CRF and decreasing sedentary behavior may be important public health targets in preadolescent children.

Funder

Massey University Research Fund

New Zealand International Doctoral Research Scholarship Recipient

Massey University Doctoral Research Scholarship Recipient

Publisher

MDPI AG

Subject

Pediatrics, Perinatology and Child Health

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