Dataset Information

Physical Activity among U.S. Preschool-Aged Children: Application of Machine Learning Physical Activity Classification to the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey.

ABSTRACT: Early childhood is an important development period for establishing healthy physical activity (PA) habits. The objective of this study was to evaluate PA levels in a representative sample of U.S. preschool-aged children. The study sample included 301 participants (149 girls, 3-5 years of age) in the 2012 U.S. National Health and Examination Survey National Youth Fitness Survey. Participants were asked to wear an ActiGraph accelerometer on their wrist for 7 days. A machine learning random forest classification algorithm was applied to accelerometer data to estimate daily time spent in moderate- and vigorous-intensity PA (MVPA; the sum of minutes spent in running, walking, and other moderate- and vigorous-intensity PA) and total PA (the sum of MVPA and light-intensity PA). We estimated that U.S. preschool-aged children engaged in 28 min/day of MVPA and 361 min/day of total PA, on average. MVPA and total PA levels were not significantly different between males and females. This study revealed that U.S. preschool-aged children engage in lower levels of MVPA and higher levels of total PA than the minimum recommended by the World Health Organization.

SUBMITTER: Kwon S

PROVIDER: S-EPMC9600221 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Physical Activity among U.S. Preschool-Aged Children: Application of Machine Learning Physical Activity Classification to the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey.

Kwon Soyang S O'Brien Megan K MK Welch Sarah B SB Honegger Kyle K

Children (Basel, Switzerland) 20220921 10

Early childhood is an important development period for establishing healthy physical activity (PA) habits. The objective of this study was to evaluate PA levels in a representative sample of U.S. preschool-aged children. The study sample included 301 participants (149 girls, 3-5 years of age) in the 2012 U.S. National Health and Examination Survey National Youth Fitness Survey. Participants were asked to wear an ActiGraph accelerometer on their wrist for 7 days. A machine learning random forest ...[more]

PMID: 36291373

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Project description:BackgroundPrevious findings have revealed that disorders of lipid metabolism may be a risk factor for pulmonary function damage; however, the combined effect of dyslipidemia and central obesity on pulmonary function is unclear. The cardiometabolic index (CMI) is a composite of serum lipids (triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C)) and visceral fat parameters (waist-to-height ratio (WHtR)). This research aimed to investigate the link between CMI and pulmonary function, employing large-scale demographic data sourced from the National Health and Nutrition Examination Survey (NHANES) database.MethodsThis cross-sectional study used data involving 4125 adults aged 20 and above collected by NHANES between 2007 and 2012. We defined CMI as the exposure variable and measured outcomes using forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC to evaluate pulmonary function. Weighted multiple linear regression models and subgroup analyses were employed to investigate separate relationships between CMI and pulmonary function. In addition, to investigate variations across different strata and evaluate the robustness of the findings, interaction tests and sensitivity analyses were conducted.ResultsResults from the weighted multiple linear regression analysis indicated a unit increase in log2-CMI was associated with a reduction of 82.63 mL in FEV1 and 112.92 mL in FVC. The negative association remained significant after transforming log2-CMI by quartile (Q). When the log2-CMI level reached Q4, β coefficients (β) were -128.49 (95% CI: -205.85, -51.13), -169.01 (95% CI: -266.72, -71.30), respectively. According to the interaction test findings, the negative association linking log2-CMI with FEV1 and FVC persists regardless of confounding factors including age, gender, BMI, physical activity (PA), and smoking status. A subsequent sensitivity analysis provided additional confirmation of the stability and reliability of the results. For females, the inflection points for the nonlinear relationships between log2-CMI and FEV1, as well as log2-CMI and FVC, were identified at 2.33 and 2.11, respectively. While in males, a consistent negative association was observed.ConclusionsOur findings suggest that higher CMI is associated with lower FEV1 and FVC. CMI may serve as a complementary consideration to the assessment and management of pulmonary function in clinical practice.

Dataset Information

Physical Activity among U.S. Preschool-Aged Children: Application of Machine Learning Physical Activity Classification to the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey.

Publications

Physical Activity among U.S. Preschool-Aged Children: Application of Machine Learning Physical Activity Classification to the 2012 National Health and Nutrition Examination Survey National Youth Fitness Survey.

Similar Datasets

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