Blood pressure and resting heart rate in 3-17-year-olds in Germany in 2003-2006 and 2014-2017

Evaluation of physical fitness and health of young children aged between 3 and 6 based on cluster and factor analyses

BACKGROUND

As life improves and sedentary time increases, young children's physical fitness gradually declines.

METHODS

Multi-stage stratified whole cluster sampling was utilized to sample 5584 preschoolers. Young infants' morphology, function, and quality were revealed using cluster and factor analysis.

RESULTS

The cluster analysis separated 3-6-year-olds into two genders: 1,551 men in group A "high physical fitness" 1,499 men in group B "low physical fitness"; 1,213 women in group A and 1,321 women in group B. Young children's fitness was measured by standing long jump(1.00), weight(1.00), and height(1.00). A cluster analysis of 3-4-year-olds classified them into three groups: 272 "muscular strength," 75 "average physical fitness," and 250 "low agility." Young children's health depends on weight (1.00), height (0.57), and chest circumference (0.54). A cluster analysis of the 4-5-year-olds classified them into two groups: 1070 "balance" and 806 "muscular strength." Young children's health depends on weight (1.00), height (0.74), and chest circumference (0.71). A cluster analysis of the 5-6-year-olds divided them into three groups: 1762 "high physical fitness," 384 "obese," and 105 "low physical fitness." Young children's physical health depends on BMI (1.00), weight (1.00), and chest circumference (1.00). Factor analysis demonstrated that muscle strength, body shape, cardiovascular variables, and physical fitness composite components affected young children's health.

CONCLUSION

Women should focus on motor function and strength, while men on flexibility. Male group B "low physical fitness" should focus on strength, motor function, and balance, whereas male group A "high physical fitness" should focus on flexibility. Then, female group A "high physical fitness" should emphasize variety.2) For 3-4-year-olds, group A "muscular strength" should focus on flexibility, and group C "low agility" on motor function. 3) For 4-5-year-olds, group A "balanced" should focus on strength and motor function; 4) For 5-6-year-olds, group B "obese" should emphasize weight loss, and group C "low fitness" should emphasize strength, motor function, and flexibility; 5) Young children's physical fitness depends on muscle strength, body shape, cardiovascular factors, and physical fitness composite.

Body size influences heart rate in children aged 6 to 18 years old

Previous research established age-related normal limits for children's heart rates (HRs). However, children of the same age can have significantly different HRs, depending on whether they are overweight or underweight, tall or short. Studies on children HR have failed to find a clear correlation between HR and body size. The goal of our study was to create Z scores for HR based on weight (W), height (H), body mass index (BMI), and body surface area (BSA) and compare them to normal age-related HR limits. Electrocardiograms were recorded from a total of 22,460 healthy children ranging in age from 6 to 18 years old using BTL machines. A comparison was made between different age groups, in function of W, H, BMI, and BSA, based on the HR that was automatically detected by using the digitally stored electrocardiogram. Z scores were computed for each of the categories that were mentioned. Incremental Z score values between -2.5 and 2.5 were calculated to establish upper and lower limits of HR. The BSA's estimation of HR is the most accurate of the available methods and can be utilized with accuracy in clinical practice. Z scores for HR in children differ in function of the age, W, H, BMI and BSA. The best estimation is based on BSA. The novelty of our study is that we developed Z scores for HR in relation to body size, age and sex, producing a standardized, consistent, and reproducible result without requiring practitioners to learn and remember cutoff values for a wide range of variables across age groups and sexes. Z scores minimize observer and institutional bias, hence generating uniform and reproducible standards.