The Relationship Between Physical Activity, Physical Fitness and Body Composition in Preschool (3-6 Years)

doi:10.21203/rs.3.rs-210370/v1

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Research Article

The Relationship Between Physical Activity, Physical Fitness and Body Composition in Preschool (3-6 Years)

https://doi.org/10.21203/rs.3.rs-210370/v1

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posted 18 Feb, 2021

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Background

Physical Activity (PA), body composition and fitness in children has been associated with short and long-term health benefits. However, little research that analizes these variables focuses on the Preschool Education stage. For this reason, the aim of this research is to study the relationship between PA, fatness and fitness in the Preschool Education stage (3-6 years).

Methods

This study included 230 children (109 boys and 121 girls) aged 3 to 5 years old with a mean age of 4.92±0.84. Body composition and fitness were assessed using PREFIT battery and a sit and reach test. For the multiple linear regression models of this study, we only included a total of 151 (65.65%) children in which PA levels were measured using accelerometers for seven days.

Results

There were differences in the fitness test between boys and girls. There were not significant differences in fitness tests between normal-weight and over-weight children, except in handgrip strength in which over-weight children had better results. There was no significant association between body composition and PA subcomponents. Higher PA levels were related with better physical fitness values.

Discussion

The few studies that have studied the relationship between fatness, physical fitness and PA in Preschool have had controversial results. These differences might be caused by different reasons: different tests, age of the participants, sample size, study design, etc. were used.

Conclusions

PA is associated with better physical fitness performance in Preschool children, although fitness is also influenced by sex in these ages. Thus, generally, except in the case of flexibility, boys obtained better results in fitness tests than girls. However, body composition does not seem to be related to PA or sex in Preschool children.

Internal Medicine

Physical Activity

Physical Fitness

Fatness

Preschool

Children

Sex

There were differences in the fitness test between boys and girls.
There were not significant differences in fitness tests between normal-weight and over-weight children, except in handgrip strength.
There was no significant association between fatness and PA subcomponents.
Higher PA levels were related with better physical fitness values.

Physical Activity (PA) is currently widely studied. PA in children has been associated with short and long-term health benefits [1–2]. Regular PA improves fitness levels in children and teenagers [3]. PA also prevents obesity [4]. Nowadays, urbanization processes, environment pollution, security consideration, and changes in family structure [5] have decreased PA levels. Furthermore, Aranceta-Bartrina et al. [6] have shown that the prevalence of being overweight in Spanish children between 3 and 8 years old is 40%, while obesity is 16%. This fact is aggravated by the importance that this stage has for the creation of healthy habits that are maintained in adulthood [7].

Some research have shown higher intensity PA levels (moderate-to-vigorous PA (MVPA) and vigorous PA) are more related to better results in fitness and fatness than light PA [8].

Most of the research has shown that fitness is a powerful health indicator in children [2, 9–11]. In addition, a lot of studies have shown a direct relationship between PA, especially MVPA, and fitness [5, 8, 12].

Moreover, the term body composition generates controversy between different researchers, whether it should be included within physical fitness as an additional component or whether it should be treated individually as a health outcome itself [10]. For this research it will be treated as a separate element of physical fitness. Over-weight and obesity in childhood are linked to the increase of cardiometabolic risk and to a higher risk of becoming obese adults. In addition, it is also associated with a greater possibility of future diseases, such as type 2 diabetes mellitus, cardiovascular disease, and some types of cancer [6]. Studies have shown that body composition correlates inversely with PA levels [9].

The majority of the research that has studied fatness, fitness and PA has been conducted in Primary and Secondary Education stages (6–18 years) [4, 13], but there are few studies that have been developed in the Preschool Education stage (3–6 years) [10, 14]. For this reason, the aim of this research is to study the relationship between PA, fatness and fitness in the Preschool Education stage (3–5 years).

Participants

This cross-sectional research included 230 children (109 boys and 121 girls) aged 3 to 5 years old with a mean age of 4.92 ± 0.84 from three urban and public schools in Cuenca, Spain. The participants of the three schools included in the study possess similar socio-economic characteristics. The majority of them are residents of Cuenca, a small city with approximately 50,000 inhabitants. Their families maintain a low to middle economic level. However, in one of the schools, most families are upper-middle class, while in the others two schools there is a higher average of lower-middle to lower class families.

Of the 230 participants included in this study, a subsample of 202 children (87.82%) were a randomly selected to wear accelerometers, but only 151 participants (65,65%) who had data that met the PA inclusion criteria were included in the multiple linear regression models. The children included in this analysis did not differ in age or sex from the whole sample of children participating in the study.

Procedures

Firstly, written consent from the researchers’ Castilla-La Mancha University Ethics Committee, the school’s Board of Governors and the students’ parents were obtained to conduct the study. The directors of the different schools were contacted to explain what the study consisted of. Researchers assured them of the anonymity and confidentiality of the data obtained and that no student would suffer any type of harm. Parents could refuse to allow their children to participate in the research or in part of it. In addition, teachers were interviewed to find information about the health history of the participants, in order to know if any of them had medical problems that could affect the measures. Furthermore, all the researchers were specifically trained to conduct the study. To collect the data, a cross-sectional study was carried out between February and June 2019. Each course was measured one day. An informative sheet was sent to the parents the day before data was taken to remind them that the next day children must wear sports clothes.

Anthropometry measures

The tests included were weight, height, fat mass percentage, triceps skinfold and waist circumference. Fat mass percentage and weight were measured twice with an electronic scale (SECA Model 861; Vogel and Halke, Hamburg, Germany, precision = 100 g, range = 0–150 kg): students wore light clothing and no shoes. Height was measured twice using a wall-mounted stadiometer (Seca Model 222; Vogel and Halke, Hamburg, Germany, precision = 0.1 cm, range = 6–230 cm): children stood barefoot and straight against the wall to align the spine with the instrument; the head was positioned with the chin parallel to the floor.

The mean of the two measurements of weight and height was used to calculate students’ body mass index (BMI): weight in kilograms divided by the square of the height in metres (BMI: Kg/m²). Cole & Lobstein [16] age-adjusted BMI cut off points were used to define thinness, normal-weight, over-weight and obese children. We grouped the participants into two groups to analyse the group differences between means. One group was normal-weight and included thinness and normal-weight subjects and the other group was over-weight and included over-weight and obese children. Waist circumference was measured two times at the midpoint between the last rib and the iliac crest using a flexible tape. Triceps skinfold was measured three times at the triceps on the non-dominant side of the body halfway between the acromion process and the olecranon process using a Holtain Ltd. Caliber (0.2 mm accuracy and consistent 10 g/mm² pressure between valves).

Physical fitness measures

A PREFIT (FITness testing in PREschool children) battery was used to measure physical fitness that it is designed and validated for 3–5 years [10, 16]. Moreover, the sit and reach test was used to measure flexibility, a health-related fitness component [5] that is not measured in PREFIT battery.

Handgrip strength and standing long jump tests were used to assess muscular strength. Handgrip strength was measured with a manual dynamometer (TKK 5001, Grip-A, Takei, Tokyo, Japan). For the standing long jump the child jumped horizontally to achieve maximum distance, the best of the three attempts were recorded in centimetres. Speed-agility was assessed with the 4 x 10 m shuttle-run test of speed-of-movement, agility, and coordination [16]. An evaluator drew two parallel lines 10 m apart on the floor. Two examinator were placed behind the lines. Participants ran 4 x 10 m (back and forth) as fast as possible crossing each line with both feet every time. Every time children crossed any of the lines, they would touch the examinator hand. The stopwatch was stopped when the children crossed the end line with one foot. The test was performed twice with at least five minutes of rest between attempts and the best score was recorded in seconds: hundredths.

Finally, the PREFIT 20m shuttle run test was used to assess cardiorespiratory fitness [16]. For this test, 10 lanes of 20 m were created. In addition, the warning zone where children should be when the beep sounded was marked at 3 m. The test was led by a recording that indicated with beeps the speed at which they should run. An examiner stood on one of the lanes and ran alongside the students during the test to help them adjust their speed to that of the recording. The initial speed of the signal was 6.5 Km / h and increased by 0.5 km / h / min. Children had to get to the 20 m line before changing direction whether they were inside or outside the warning zone, even if the signal sounded. If a child was not in the designated 3 m zone when the signal sounded, a warning was given and if this happened again for the second consecutive time, the test finished. The test also ended when the students could not continue due to exhaustion. The test was performed only once and the total number of laps in which each student had travelled the distance of 20 m was recorded.

In addition, Sit and reach test were used to assess flexibility [17]. The children sat barefoot with their legs stretched out in front of them and the soles of their feet completely touching the drawer wall. They put one hand on top pf the other and without bending their knees, slowly and progressively, did a deep trunk flexion in front. They made three attempts that we registered in cm and mm and then we documented the best attempt.

Measurement of physical activity

Children wore a triaxial accelerometer (Actigraph GT3X model) for seven consecutive days to measure PA. Accelerometers are worn on the right side of the waist attached with an elastic band. A sheet with information related to the accelerometers was sent to the parents to explain that these devices cannot get wet; so to bathe the children or to go to the pool, parents had to take it off and when the activity was over, the device had to be adjusted with the elastic band on the right side of the waist again. The information from each accelerometer was programmed in 100 Hz and exported in one-second epoch. The cut-off values of Pate at al. [18] were used to define the intensity of PA and, therefore, quantify the mean time in each intensity: sedentary time = < 800 counts per min (cpm), light PA = 800–1679 cpm, moderate PA = 1680–3367, vigorous PA = > 3368, and MVPA was calculated as the sum of moderate and vigorous PA. In addition, total PA per day was calculated as the sum of light, moderate and vigorous PA.

Accelerometer data was processed by the software Actilife V. 6.13.4 to provide values for total daily and hourly cpm. The inclusion criteria were to wear the accelerometer a minimum of three days, including at least two weekdays and one weekend day for minimum 10 registered hours per day [19], excluding 20-min intervals of continuous ‘zero’ activity with allowance for 1–2 min of counts between 0 and 100 [20]. The sleep period was also ignored because the study only analyzed the performance level of PA during the day. Children who did not accomplish them were excluded for the analysis.

Statistical analyses

Data analysis was made using the Statistical Package for Social Sciences (SPSS) version 25.0 for Windows (IBM SPSS Statistics, Armonk, NY). Descriptive statistics were presented as mean ± standard deviations. Since each accelerometer recorded different time validation, descriptive data of the PA subcomponents were adjusted for the total PA per day recorded. A covariance analysis was used in order to calculate the mean of the PA subcomponents. Kolmogorov-Smirnov test was used to check for normality before the analysis. All variables presented normal distribution. Independent t-test was used to analyse group differences between means. Multiple linear regression models were used to examine the independent associations of body composition (BMI, % body fat, waist circumference and triceps skinfold) variables with fitness indices (20 m shuttle run, 4x10 m shuttle run, standing long jump, sit and reach, handgrip strength) and PA subcomponents (Sedentary, Light, Moderate, Vigorous, MVPA, Total PA and Counts per minute). Standardised β coefficients were used. The variance inflation factors between variables were less than five, suggesting that multicollinearity was not a problem in the models [21]. Two regression models were used: unadjusted model and model adjusted for age and sex of the child (Model 1). Moreover, the associations between fitness indices with PA subcomponents were further examined. Two regression models were also used: unadjusted model and model adjusted for age and sex (Model 1). Significance was set at 5%. So, all p-values less than 0.05 were treated as significant.

Data of participants compared by sex are demonstrated in Table 1. Boys had a better significant performance (p < 0.05) in standing long jump, 4x10 m shuttle run, and 20 m shuttle run tests, while girls had better results in the sit and reach test. Moreover, fatness and PA subcomponent values were similar among both sexes.

Table 1

Descriptive data of the participants comparing by sex
	Boys (n = 109)	Girls (n = 121)	Whole sample (n = 230)
Age (years)	4.97 ± 0.85	4.88 ± 0.84	4.92 ± 0.84
Height (cm)	108.93 ± 7.17	108.38 ± 8.06	108.64 ± 7.64
Weight (Kg)	18.92 ± 3.67	18.55 ± 3.88	18.73 ± 3.78
BMI (Kg/m²)	15.82 ± 1.72	15.63 ± 1.63	15.72 ± 1.67
% Fat mass	21.01 ± 3.57	20.92 ± 4.86	20.96 ± 4.28
Waist circumference (cm)	53.69 ± 4.44	53.54 ± 4.34	53.61 ± 4.37
Triceps skinfold (mm)	10.85 ± 3.37	11.43 ± 3.26	11.15 ± 3.32
Handgrip strength (kg)	7.31 ± 1.89	6.81 ± 1.99	7.05 ± 1.96
Standing long jump (cm)	90.93 ± 26.87*	82.75 ± 28.62	86.64 ± 28.04
Sit and reach (cm)	27.15 ± 4.10	29.51 ± 3.75*	28.39 ± 4.09
4x10 m shuttle run (s)	16.48 ± 2.14*	17.15 ± 2.37	16.83 ± 2.28
20 m shuttle run (laps)	33.45 ± 19.39*	28.02 ± 17.82	30.58 ± 18.73
	Boys (n = 70)	Girls (n = 81)	Whole sample (n = 151)
Sedentary time per day (min)^a	588.82 ± 47.33	599.01 ± 34.99	594.28 ± 41.53
Light PA per day (min) ^a	55.86 ± 12.10	55.95 ± 8.08	55.91 ± 10.17
Moderate PA per day (min) ^a	58.85 ± 11.15	58.73 ± 9.75	58.79 ± 10.50
Vigorous PA per day (min) ^a	50.12 ± 14.68	50.16 ± 11.19	50.14 ± 12.96
MVPA per day (min) ^a	108.98 ± 20.81	108.89 ± 19.18	108.93 ± 20.10
Counts per minute (counts) ^a	1587.35 ± 240.79	1552.10 ± 222.28	1568.44 ± 234.45
Values are means ± standard deviations; *better significant performance (p < 0.05); ^a adjusted for total PA recorded BMI – body mass index; PA – physical activity; MVPA – moderate-vigorous physical activity

Descriptive data of the participants according to weight status are showed in Table 2. Over-weight children had higher significant values (p < 0.05) in height, weight, BMI, fat mass percentage, waist circumference, triceps skinfold and handgrip strength in comparison with normal-weight children. Furthermore, fitness tests performances and PA subcomponent values were similar between normal-weight and over-weight children.

Table 2

Descriptive data of the participants according to weight status
	Thinness/Normal-weight (n = 194)	Over-weight/Obesity (n = 36)
Age (years)	4.89 ± 0.84	5.09 ± 0.86
Height (cm)	107.75 ± 7.40	113.40 ± 7.23*
Weight (Kg)	17.69 ± 2.76	24.28 ± 3.68*
BMI (Kg/m²)	15.15 ± 0.98	18.78 ± 1.27*
% Body fat	19.70 ± 3.12	27.75 ± 3.14*
Waist circumference (cm)	52.26 ± 2.99	60.81 ± 3.56*
Triceps skinfold (mm)	10.18 ± 2.24	16.36 ± 3.30*
Handgrip strength (kg)	6.86 ± 1.77	8.04 ± 2.54*
Standing long jump (cm)	86.83 ± 28.18	86.36 ± 27.68
Sit and reach (cm)	28.52 ± 3.96	27.78 ± 4.76
4x10 m shuttle run (s)	16.76 ± 2.27	17.20 ± 2.40
20 m shuttle run (laps)	31.01 ± 19.01	28.45 ± 17.45
	Normal-weight (n = 128)	Over-weight (n = 23)
Sedentary time per day (min) ^a	593.30 ± 40.92	599.53 ± 46.24
Light PA per day (min) ^a	55.92 ± 10.58	56.33 ± 7.71
Moderate PA per day (min) ^a	58.73 ± 10.64	59.82 ± 9.44
Vigorous PA per day (min) ^a	50.44 ± 13.48	48.93 ± 9.91
MVPA per day (min) ^a	109.17 ± 20.52	108.76 ± 17.69
Counts per minute (counts) ^a	1577.23 ± 242.13	1531.10 ± 185.73
Values are means ± standard deviations; * significantly higher values (p < 0.05); ^a adjusted for total PA recorded BMI – body mass index; PA – physical activity; MVPA – moderate-vigorous physical activity

The associations among the different variables of the body composition with each fitness test and PA subcomponents are demonstrated in Table 3. Higher BMI was positively associated with better results in handgrip strength in both models. Thus, increase in BMI by one unit (kg/m²) was associated with a 0.20 kg increase in unadjusted model and with 0.16 kg increase in Model 1. In addition, negative association was found between BMI and 4x10 m shuttle run in Model 1. Each unit increase in BMI was associated with the worsening result in 4x10 m shuttle by 0.11 seconds. The increase in the percentage of fat mass was related to worse results in sit and reach and 4x10 m shuttle run tests in both models and reduced cpm in unadjusted model. Increase in percentage of fat mass by one unit was associated with a decrease in the performance of 4x10 m shuttle test by 0.18–0.19 s. Each unit increase in the percentage of fat mass was associated with a decrease in the results of cpm by 0.17 cpm. Waist circumference was positively related to handgrip strength, standing long jump and time spent in sedentary. However, the associations with standing long jump and sedentary time were no longer significant after adjusting with age and sex. Increase in waist circumference by one unit (cm) was associated with a 0.27 kg better handgrip strength result in unadjusted model and with 0.13 kg in Model 1. Finally, higher triceps skinfold was related to worse performance in 4x10 m shuttle run in Model 1 and with lower counts per minute in unadjusted model. Increase in triceps skinfold by one unit (mm) was associated with a decrease in the performance of 4x10 m shuttle test by 0.14 s in Model 1. In addition, each unit increase in triceps skinfold was associated with a decrease in the results of cpm by 0.16 cpm.

Table 3

Relations between physical fitness and physical activity with body composition values
	BMI			% Body fat			Waist circumference			Triceps skinfold
	r²	β	p	r²	Β	p	r²	β	p	r²	β	p
Handgrip strength	0.042	0.206	0.006	0.013	0.114	0.131	0.073	0.270	0.000	0.012	0.111	0.142
Model 1	0.378	0.161	0.008	0.363	0.102	0.093	0.369	0.130	0.038	0.364	0.105	0.086
Standing long jump	0.002	0.041	0.541	0.002	-0.045	0.501	0.023	0.153	0.021	0.002	-0.044	0.508
Model 1	0.341	0.002	0.976	0.343	-0.039	0.474	0.341	-0.019	0.735	0.337	-0.056	0.313
Sit and reach	0.000	-0.011	0.863	0.021	-0.145	0.028	0.001	-0.026	0.696	0.001	-0.037	0.575
Model 1	0.085	0.005	0.941	0.105	-0.142	0.026	0.084	-0.025	0.706	0.090	-0.064	0.322
4x10 m shuttle run^a	0.005	0.069	0.299	0.037	0.191	0.004	0.010	-0.101	0.126	0.016	0.126	0.058
Model 1	0.375	0.112	0.035	0.396	0.184	0.000	0.369	0.084	0.130	0.375	0.140	0.009
20 m shuttle run	0.000	-0.019	0.778	0.011	-0.105	0.114	0.004	0.060	0.367	0.004	-0.063	0.343
Model 1	0.230	-0.049	0.408	0.237	-0.097	0.098	0.233	-0.082	0.180	0.226	-0.065	0.274
Sedentary time per day	0.006	0.077	0.349	0.003	0.055	0.502	0.032	0.180	0.027	0.005	0.072	0.381
Model 1	0.088	0.046	0.566	0.087	0.030	0.712	0.093	0.091	0.281	0.087	0.036	0.655
Light PA per day	0.001	0.037	0.656	0.006	-0.080	0.333	0.000	0.003	0.973	0.007	-0.085	0.299
Model 1	0.013	0.045	0.543	0.015	-0.066	0.424	0.013	0.016	0.852	0.016	-0.069	0.411
Moderate PA per day	0.003	0.053	0.519	0.001	-0.034	0.675	0.002	0.040	0.622	0.005	-0.071	0.391
Model 1	0.024	0.063	0.760	0.022	-0.017	0.835	0.025	0.057	0.513	0.022	-0.048	0.565
Vigorous PA per day	0.001	-0.025	0.760	0.013	-0.112	0.171	0.001	-0.024	0.768	0.014	-0.119	0.148
Model 1	0.014	-0.021	0.803	0.021	-0.099	0.233	0.015	-0.028	0.746	0.024	-0.105	0.210
MVPA per day	0.000	0.011	0.890	0.008	-0.091	0.270	0.000	0.006	0.946	0.013	-0.114	0.166
Model 1	0.022	0.019	0.816	0.027	-0.073	0.376	0.024	0.011	0.895	0.030	-0.093	0.265
Total PA per day	0.001	0.023	0.782	0.010	-0.100	0.225	0.000	0.005	0.949	0.014	-0.119	0.146
Model 1	0.024	0.032	0.699	0.029	-0.081	0.325	0.025	0.015	0.863	0.032	-0.097	0.243
Counts per minute	0.004	-0.067	0.416	0.029	-0.171	0.037	0.009	-0.093	0.258	0.026	-0.160	0.050
Model 1	0.036	-0.054	0.513	0.055	-0.148	0.070	0.041	-0.080	0.354	0.050	-0.132	0.111
Model 1 – adjusted for age and sex; ^a Lower values indicate better performance BMI – body mass index; PA – physical activity; MVPA – moderate-vigorous physical activity

The associations between physical fitness tests and PA subcomponents are demonstrated in Table 4. Time spent in sedentary was only related to worse results in 4x10 m shuttle run test in Model 1. Light and moderate PA were associated with better performance in 4x10 m shuttle run test in both models. Vigorous, MVPA, total PA and cpm were associated with better values in standing long jump and 4x10 m shuttle run in both models. Thus, each measured unit of vigorous PA was associated with 0.22–0.26 cm better performance in standing long jump and with 0.22–0.29 s better 4x10 m shuttle run result. In addition, MVPA, total PA and cpm were positively associated with 20 m shuttle in unadjusted model. Each unit of MVPA was associated with 0.22–0.25 cm better standing long jump result, with 0.27–0.37 s better performance in 4x10 m shuttle run and with an increase in the result of 20 m shuttle run by 0.16 laps. Each unit increase in total PA was related with an increase in the results of standing long jump by 0.19–0.22 cm, with 0.27–0.38 s better 4x10 m shuttle run result and with 0.16 laps better performance in 20 m shuttle run test. Finally, each unit of cpm was positively associated with 0.27–0.34 cm better performance in standing long jump, with 0.28–0.42 s better 4x10 m shuttle run result and with 0.16 laps better result in 20 m shuttle run.

Table 4

Relations between physical fitness values and different PA subcomponents
	Handgrip strength			Standing long jump			Sit and reach			4x10 m shuttle run^a			20 m shuttle run
	r²	β	p	r²	Β	P	r²	β	p	r²	β	p	r²	β	p
Sedentary time per day	0.002	0.040	0.433	0.001	-0.028	0.733	0.015	0.122	0.137	0.000	0.022	0.787	0.000	0.005	0.951
Model 1	0.087	-0.137	0.202	0.111	-0.181	0.047	0.094	0.095	0.241	0.126	0.258	0.010	0.096	-0.120	0.190
Light PA per day	0.005	-0.074	0.429	0.005	0.073	0.378	0.008	0.090	0.272	0.033	-0.181	0.026	0.007	0.084	0.305
Model 1	0.024	-0.049	0.661	0.017	0.080	0.404	0.026	0.123	0.145	0.056	-0.270	0.010	0.017	0.083	0.384
Moderate PA per day	0.001	0.023	0.810	0.022	0.148	0.072	0.001	0.028	0.733	0.059	-0.244	0.003	0.017	0.131	0.110
Model 1	0.042	0.118	0.284	0.042	0.160	0.091	0.027	0.066	0.429	0.094	-0.344	0.001	0.034	0.124	0.190
Vigorous PA per day	0.000	0.017	0.860	0.050	0.224	0.006	0.000	-0.005	0.954	0.049	-0.221	0.006	0.024	0.156	0.055
Model 1	0.020	0.103	0.355	0.063	0.261	0.006	0.015	0.023	0.787	0.067	-0.297	0.004	0.032	0.157	0.099
MVPA per day	0.001	0.023	0.802	0.049	0.222	0.007	0.000	0.012	0.888	0.073	-0.270	0.001	0.022	0.169	0.038
Model 1	0.041	0.134	0.225	0.069	0.251	0.007	0.026	0.049	0.556	0.107	-0.371	0.000	0.044	0.166	0.079
Total PA per day	0.000	-0.014	0.884	0.039	0.196	0.016	0.002	0.043	0.597	0.075	-0.275	0.001	0.026	0.161	0.049
Model 1	0.040	0.080	0.466	0.060	0.221	0.018	0.032	0.085	0.312	0.115	-0.385	0.000	0.044	0.158	0.094
Counts per minute	0.001	0.030	0.749	0.076	0.276	0.001	0.002	0.044	0.589	0.081	-0.285	0.000	0.027	0.164	0.044
Model 1	0.065	0.179	0.102	0.123	0.345	0.000	0.044	0.093	0.263	0.146	-0.428	0.000	0.058	0.176	0.062
Model 1 – adjusted for age and sex; ^a Lower values indicate better performance BMI – body mass index; PA – physical activity; MVPA – moderate-vigorous physical activity

This research aimed to study the relationship between PA, fatness, and fitness in the Preschool Education stage. The major findings were: 1) There were differences in fitness test between boys and girls; 2) There were not significant differences in fitness tests between normal-weight and over-weight children, except in handgrip strength in which over-weight children had better results; 3) There were no significant associations between body composition and PA subcomponents; 4) Higher PA levels were related with better physical fitness values.

Differences in physical fitness tests were more related to sex than fatness. Boys had significant better results in standing long jump, 4x10 m shuttle run and 20 m shuttle run tests, but their performance in the sit and reach test was worse. This finding is in concordance with Cadenas-Sánchez et al. [22] study that found significant better results in the standing long jump test in boys than girls. Latorre et al. [23] found that boys had better performance in speed and lower body strength tests and girls had higher values in the cardiorespiratory fitness test. This last difference could be because a different test was used to measure cardiorespiratory fitness.

However, significant differences were not found in fitness tests means between normal-weight and over-weight children, except in handgrip strength, in which over-weight children had higher results. Thus, higher BMI was associated with better results in handgrip strength. These results agree with Cadenas-Sánchez et al. [22] study that found this result in both sex and Riso et al. [8] research that found that the mean in handgrip strength of normal-weight children was 10.5 kg, while the mean of over-weight participants was 12.2 kg. In addition, higher BMI was associated with worse performance in 4x10 m shuttle run. This finding does not agree with Henriksson et al. [14] and Riso et al. [8], that both did not find significant association (p < 0.05) between BMI and 4x10 m shuttle run. This discrepancy in the results could be due to the different age of the participants in these studies. However, no significant association with standing long jump, sit and reach and 20 m shuttle run test was found. Henriksson et al. [2] aimed that BMI could not detect the associations between body composition and physical fitness in Preschool children. This could be because Preschool children are so young [14] due to the fact that different research with older participants (6-7-year-old) observed significant associations between higher BMI, greater standing long jump and lower cardiorespiratory fitness [8]. Thus, for example, Carson et al. [12] found some research with mixed or null findings because of their infants and toddlers’ samples.

Furthermore, fat mass percentage was related with lower results in 4x10 m shuttle run. This concordats with Henriksson et al. [14] study that found a significant negatively association (p < 0.001) among both variables, but not with Riso et al. [8] research that did not find a significant association (p > 0.05). This difference could be because of the different age of the participants in each study. Moreover, our results showed that waist circumference was associated with better performance in handgrip strength and triceps skinfold was related with worse results in 4x10 m shuttle run test. As far as we know, no study has analysed the relationship of these two components of body composition with these fitness tests in Preschool children, so we cannot compare these findings with others. So, there are some studies that have studied the relationship between body composition and physical fitness in Preschool children [14] and their results have been controversial [5, 21, 23]. These differences might be caused by different reasons: different tests, age of the participants, sample size, study design, etc. were used [5, 23].

Body composition values were not significantly related to PA levels, although waist circumference was associated positively with sedentary time. These results coincide with those found by Carson et al. [12] review that observed a lot of null, unfavorable and mixed associations between PA and adiposity. Previous studies have shown BMI was not related to PA in some studies [25]. For this reason, Leppänen et al. [25] aimed future research should include different body composition variables instead of just BMI. The results in this research were in agreement with this fact because BMI is the only value that had no significant associations, while waist circumference was related to sedentary time and fat mass percentage and triceps skinfold were associated negatively with the number of counts per minute. Moreover, Fang et al. [5] found that MVPA was associated with triceps skinfold, but the results of this study showed no association between both. So, there were discordant results among the studies. Regarding sedentary time, our results were in concordance with Riso et al. [8] study. Both found that sedentary time did not relate to BMI and fat mass.

Finally, higher PA levels, specially MVPA, vigorous PA and total PA, were associated with better performance in physical fitness tests. This finding is in accordance with Carson et al. [12]; Fang et al. [5] and Riso et al. [8] research. Thus, like Carson et al. [12] and Riso et al. [8] studies, a greater performance in standing long jump, 4x10 m shuttle run and 20 m shuttle run were associated with PA, while more time spent in sedentary was related to lower results standing long jump and 4x10 m shuttle run tests. However, according with Fang et al. [5], associations between PA levels and handgrip strength and sit and reach tests were not found. Nevertheless, Riso et al. [8] found significant associations (p. 0.045) between MVPA and handgrip strength. The difference might be caused by the age of the participants.

Nevertheless, this research has some limitations. Firstly, sample size was not too big, especially the over-weight population (n = 36). So, we could not separate over-weight and obese children into different groups. This could influence the significant differences that were found as Niederer et al. [24] found associations between normal-weight and obese children which were not found in over-weight participants. In addition, 79 children did not accomplish the inclusion criteria. Therefore, PA associations could be influenced by the relatively small final sample (n = 151). Another limitation was that a cross-sectional design was used, so we could not conclude causality and direction of associations found. Moreover, the research did not analyse some variables that could be influential like socioeconomic status or participation in sports clubs. Regarding the body composition, fat free mass was not studied, which Riso et al. [8] found was associated with all physical fitness and PA levels. For this reason, considering that it is an important value, it should have been analysed. However, we used waist circumference and triceps skinfold that few research has studied, so our study revealed new information about the relationship of these body composition variables with fitness and PA levels.

The strength of this study is that the measurements used were objective. PA was measured by accelerometer and physical fitness was measured by PREFIT battery, which is validated for 3-5-year-old children [10]. In addition, we analysed some variables that only some research studied such as: flexibility, waist circumference and cpm. Moreover, we used a model that was adjusted for age and sex of the participants to analyse data. Differences among the variables in unadjusted model usually disappeared in the adjusted model because these variables are influenced by age and sex. So, our results showed the real relationship between fatness, fitness, and PA regardless of age or sex. Finally, our sample included 3-year-old children, who were not included in the research that has studied Preschool children health.

PA is associated with a better physical fitness in Preschool children. However, fitness is also influenced by sex at this stage. Thus, except in sit and reach test, boys had better performance in fitness tests than girls. Nevertheless, body composition is not related to PA or sex in children so young. All the same, some experts have aimed that the relationship between PA, fitness and body composition increases with the age of the participants [14].

The discrepancy between the results of the different research makes it necessary to carry out more studies that analyze the relationship between these three variables separately in each year of age (3, 4 and 5 years) because it has been demonstrated that there are differences in the results with respect to the studies whose sample only includes children from the last year of Preschool. Therefore, it would be interesting to analyze the evolution of the relationship between these three variables from year to year to see if age explains the discrepancies found. Likewise, it would be interesting to analyze the relationship of these three variables with other sociocultural ones (urban or rural environment, socio-economic level, level of education of the parents, type of family, etc.) to check if they also affect the relationship.

PA: Physical activity
MVPA: Moderate-to-vigorous physical activity
BMI: Body mass index
Cpm: Counts per min

Ethical Approval and Consent to participate

In process

Consent for publication

Not applicable

Availability of data and material

The data that support the findings of this study are available from Natalia María Arias-Palencia but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Natalia María Arias-Palencia.

Competing interests

Guiomar Serrano-Gallén, Natalia María Arias-Palencia, Sixto González-Víllora, Víctor Gil-López and Monserrat Solera-Martínez declare that they have no competing interests.

Funding

Not applicable.

Authors' contributions

GSG, VGL and NMAP collected the data. GSG and MSM analyzed and interpreted the data. GSG, NMAP and SGV were major contributors in writing the manuscript. All authors read and approved the final manuscript.

Acknowledgements

The authors would like to thank the schools, parents of the children and children who participated in the study for allowing us to collect the data, and the examiners who helped collect it.

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The Relationship Between Physical Activity, Physical Fitness and Body Composition in Preschool (3-6 Years)

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Abstract

Key Points

Background

Methods

Participants

Procedures

Anthropometry measures

Physical fitness measures

Measurement of physical activity

Statistical analyses

Results

Discussion

Conclusions

Abbreviations

Declarations

References

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