Relationship between the 24-Hour Movement Guidelines and Fundamental Motor Skills in Preschoolers

Abstract

OBJECTIVE:

To examine the association among 24-hour movement guidelines and fundamental motor skills (FMS) in preschoolers.

DESIGN:

Prospective cohort study with one-year follow-up.

METHODS:

Parents of 3–4-year-old children reported child age, sex, race, and time spent viewing screens (hours/day). Accelerometers measured preschooler physical activity (PA) and sleep. The 24-hour movement guidelines were examined (≥3 hours/day total PA including ≥1 hour/day of moderate-to-vigorous [MVPA], 10–13 hours/day of sleep, and ≤1 hour/day of screen-time). Trained researchers administered the Test of Gross Motor Development-Third Edition (TGMD-3) to assess FMS. Linear regression was used to assess guidelines met and raw locomotor, ball skills, and total TGMD-3 scores with adjustment for covariates.

RESULTS:

One hundred and seven preschoolers provided complete cross-sectional data, and 53 preschoolers provided complete longitudinal data. Of the 107 preschoolers, they were 3.4±0.6 years of age, 44% were male, 50% were White, and the mean age-and-sex adjusted TGMD-3 total score percentile was below average (41±22). Many preschoolers met the PA guideline (91%) and sleep guideline (83%), but few preschoolers met the screen-time guideline (8%) or all three guidelines (6%). MVPA was positively associated with locomotor and total TGMD-3 scores in cross-sectional analysis (p<0.05 for all). Baseline PA, sleep, and screen-time were associated with total TGMD-3 score at follow-up (p<0.05 for all). Meeting the screen-time guideline and all three guidelines at baseline were each positively associated with total TGMD-3 score at follow-up (p<0.05 for all).

CONCLUSION:

Each movement behavior contributed to later FMS. Promotion of adequate movement behaviors is warranted for child health.

INTRODUCTION

Achieving adequate physical activity and sleep while minimizing sedentary screen-time is important for young children’s healthy development.¹ An inappropriate balance, i.e. high levels of screen-time and low levels of physical activity and sleep, may promote excess weight gain² and poor health-related quality of life.³ The Canadian 24-Hour Movement Guidelines were created to address these interconnected behaviors⁴ and were recently adopted by the World Health Organization.⁵ Preschool children are recommended to attain sufficient daily physical activity (180 minutes of which 60 minutes is moderate-to-vigorous (MVPA)) and sleep (10.0–13.0 hours/night) and to limit screen-time (≤60 minutes/day).⁵

Another important component of early childhood is fundamental motor skills (FMS), which are foundational for movement behaviors. These FMS are generally categorized as locomotor skills (advancing body through space) or ball skills (controlling an object).⁶ Physical activity opportunities can facilitate FMS development (e.g. galloping, sliding), though these skills must be learned, practiced, and reinforced.⁷ Preschoolers’ (ages 2–5 years) MVPA is related to subsequent FMS proficiency at school-entry,⁸ but it is unclear if children’s total physical activity and specifically meeting the 24-hour Movement Guidelines relate to FMS during the preschool years.

The relationship between physical activity, sleep, and screen-time may provide a novel avenue of understanding FMS development. In toddlers (ages 1–3 years), adequate sleep was associated with beneficial motor development.⁹ Further, screen-time was negatively associated with locomotor skills in a cross-sectional study of school-age children (ages 5–16 years).¹⁰ These findings suggest sleep and screen-time may contribute to future FMS, but these associations have not been explored together in preschoolers. School-entry may alter movement patterns,¹ thus total assessment within the preschool years is critical to evaluate the relationship between early movement and FMS. Therefore, the first aim of this analysis was to examine the association among child movement and FMS in a cross-sectional manner, including evaluation of movement quantity and movement classified by individual and number of 24-Hour Movement Guidelines met. The second aim was to examine the relationship between child movement and FMS one-year later.

METHODS

The present analysis used baseline and one-year follow-up data from a prospective observational cohort called “Pause and Play,” which focused on state-level policy changes in screen-time and physical activity within Early Childhood Education (ECE) centers in the state of Louisiana.¹¹ ECE centers were eligible to participate if they served children ages 3-to-5 years and were located within a specific metropolitan parish (county). Researchers stratified ECE centers by governmental childcare assistance and invited them to participate based on an order that was randomly generated by a biostatistician. Ten ECE centers agreed to participate in baseline measurements and nine of the same ECE centers participated in follow-up measurements. One center was not included in the follow-up assessment due to a change in management and few children from baseline still attending the center. Baseline measurements occurred before implementation of the state policy (April 2016–June 2017). Follow-up measures occurred approximately one-year after each ECE center’s respective baseline assessment (May 2017-May 2018).¹² The Pennington Biomedical Research Center Institutional Review Board approved the study and the study was carried out in accordance with the Declaration of Helsinki.

Parents were recruited from participating ECE centers through at least two of the following methods: informational flyer, phone call, email, mail or in-person. Children were eligible if they were 3–4.9 years of age (thus preschool age one-year later), attended the ECE center full time (at least 6 hours/day), and planned to attend the ECE center one-year later. At follow-up, parents of newly enrolled preschoolers who met eligibility criteria were invited to participate and be included in the cross-sectional analysis. Parents provided written consent. The measurements were explained to the preschoolers using age-appropriate language, and preschoolers were offered the opportunity to refuse. After consent, parents completed a demographic questionnaire at home that included their child’s date of birth, sex, race, and household income (options of <$10,000 and then $20,000 increments until $140,000 and above) as well as child’s screen-time.

Physical activity and sleep were measured using accelerometry. Trained researchers placed an ActiGraph GT3X+ accelerometer (Pensacola, FL) on the right hip of the preschooler with an elastic waistband, and data were recorded in 15-second epochs. The parent was instructed to have the preschooler wear the device continuously (including overnight) for a total of eight days (one day familiarization and a full seven day week)¹³ and only remove for water-based activities (e.g. bathing). A previously published algorithm, developed using a pediatric cohort, was used to differentiate between sleep time, wear, and non-wear time.¹⁴ Thirty minutes or more of non-wear time was removed from analysis in processing similar to other protocols in preschoolers (e.g. Moller et al.).¹⁵ Age-appropriate cut points for 15-second epochs were applied, including 200–419 counts for light physical activity (LPA) and ≥420 counts for MVPA.¹⁶ Total physical activity was the sum of LPA and MVPA. Preschoolers with ≥3 days (at least 1 weekday and 1 weekend day) of ≥10 hours of wear were included for analysis similar to a previously published 3-day protocol in this age range.¹³

Daily sleep was the amount between algorithm-determined bedtime and wake time. Naptime was not included in sleep time as naptime is unable to be detected by the algorithm.¹⁴ Preschoolers with at least 3 days with ≥160 minutes of overnight sleep were included in analysis, as 160 minutes is the minimum amount of time needed to detect a sleep phase.¹⁴

Daily screen-time of the preschooler was assessed by parent report of average screen-time use over the last 30 days. Parents reported daily use/viewing of television, computer games, video games, smartphones, and tablets in individual questions. Screen-time questions were based on the National Health and Nutrition Examination Survey 2009–2010 questionnaire and comparable to other screen-time reports.¹⁷ Question responses were none (or zero), <1 hour (treated as 0.5 hours in analysis), 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, or >5 hours with an option to write in the amount. Screen-time amount per day was the sum of all devices.

The 24-Hour Movement Guidelines for the Early Years includes standards for daily physical activity, sleep, and screen-time for preschool age (2–5 years) children.⁵ In this sample, preschoolers who averaged ≥3.0 hours of total physical activity per day with ≥60.0 minutes of MVPA were classified as meeting the physical activity guideline. Preschoolers who averaged between 10.0–13.0 hours of sleep per night were classified as meeting the sleep guideline. Preschoolers whose parents reported their child watched ≤60.0 minutes of screen-time per day were classified as meeting the screen-time guideline. The number of guidelines met was summed, with a possible total of 0–3.

The Test of Gross Motor Development-3^rd edition (TGMD-3) assessed FMS. This test is a direct observation of 13 FMS for children, including locomotor and ball skills,¹⁸ and has been validated within children ages 3 to 10.9 years.¹⁹ The ball skills subscale includes 2-hand strike, 1-hand strike, catch, kick, dribble, overhand throw, and underhand throw. The locomotor subscale includes run, gallop, hop, skip, jump, and slide. Each skill is evaluated using systematic observation of process and product-oriented performance criteria; there are 3–5 performance criteria per skill.

Per standardized protocol outlined in the manual, a trained administrator conducted assessments at the ECE center in small groups (3–4 preschoolers) and took approximately 30 minutes for each group.¹⁸ The trained administrator started with a demonstration of the skill, and then allowed the preschooler one practice trial and two graded, formal trials. These trials were video recorded and later coded by trained researchers who had established >95% reliability with an expert coder (intra-class correlation: 98%). Graded trials were scored either “1” for meeting appropriate criteria or “0” for not meeting appropriate criteria. A raw score was calculated using both graded trials and summed for each subscale (ball skills and locomotor) and overall (total TGMD-3). Raw scores were used to capture child-level FMS proficiency and change over time, as performed in other studies.²⁰ The maximum score for each scale was 54 for ball skills, 46 for locomotor, and 100 for overall. A higher score indicates a more proficient FMS performance.

The first aim (cross-sectional) included preschoolers with complete data for all movement behaviors (physical activity, sleep, and screen-time) and FMS for at least one time point (i.e. at baseline or follow-up). A series of three models tested the independent variables: continuous movement behaviors (LPA, MVPA, sleep, and screen-time), meeting the movement guidelines (physical activity, sleep, screen-time), and number of guidelines met (0–3). The dependent variables were raw scores of ball skills, locomotor, and total TGMD-3 scores. Crude models were conducted, along with models that adjusted for age, sex, race, other behaviors (e.g. physical activity guideline was adjusted for meeting the sleep and screen-time guideline), and average accelerometer wear time.

The second aim (longitudinal) included preschoolers with complete baseline movement behavior and FMS data and a complete follow-up FMS measurement. For aim two, like the prior aim, a series of models included the following independent variables: baseline movement behaviors as continuous variables, meeting the movement guidelines, and number of guidelines met. The dependent variables were follow-up raw FMS scores. Crude models were conducted and models that adjusted for baseline raw score (ball skills, locomotor, or TGMD-3), race, the other behaviors, and accelerometer wear time. Significance was set at p<0.05. A sensitivity analysis was conducted with additional adjustment for age and sex together with original covariates. All analyses were performed using SAS 9.4 (Cary, N.C.)

RESULTS

In Aim 1, 169 preschoolers participated in either baseline or follow-up, and 107 had complete data to be included in cross-sectional analyses. Twenty-one participants did not have adequate wear time for physical activity, 33 participants did not have adequate wear time for sleep, one participant was missing screen-time data, and one participant did not complete a TGMD-3 assessment.

For cross-sectional analysis, less than half the sample was male (44.6%), half were White (50.5%), and most participants (66.4%) had a household income of $70,000 or more (Table 1). Using the 24-hour Movement Guidelines as a reference, on average preschoolers exceeded the MVPA guideline, fell within the sleep guideline range, and greatly exceeded the screen-time guideline (Table 1). The sample was below average in locomotor and total TGMD-3 skills, as the average TGMD-3 percentiles were below 50.0 (Table 1). Most preschoolers met the physical activity or sleep guideline, and all met at least one movement guideline.

Table 1.

Descriptive characteristics of sample (n=107)

	Cross Sectional (n=107)			Longitudinal^ (n=53)
	Mean	SD	%	Mean	SD	%
Demographics
Age (years)	3.4	0.6		3.2	0.5
Male			44.6			52.6
Race
White			50.5			58.5
African American			38.3			28.3
Other			11.2			13.2
Household Income
Less than $29,999			28.9			18.9
$30,000 – 69,999			4.7			3.7
$70,000 – 109,999			16.8			18.9
$110,000 or more			36.5			45.3
Missing/ Refused			13.1			13.2
Behaviors (hours/day)
LPA	4.2	0.6		4.1	0.5
MVPA	1.7	0.6		1.7	0.5
Total PA	5.9	1.0		5.8	0.8
Sleep	10.7	0.9		11.0	0.8
Screen-time	4.5	3.3		3.8	3.5
Fundamental Motor Skills
Ball Skills	20.2	7.5		19.0	7.6
Ball Skills Percentile	52.5	24.2		50.9	26.9
Locomotor Skills	15.8	6.9		14.7	6.8
Locomotor Skills Percentile	34.9	22.8		35.0	24.3
Total TGMD-3	36.0	11.6		33.7	11.5
Total TGMD-3 Percentile	41.7	22.5		41.4	23.8
Movement Guidelines Met
Physical Activity
MVPA			91.6			90.6
Total PA			99.1			100.0
Sleep			83.2			90.6
Screen-time			8.4			13.2
Number of Guidelines Met
Met Only One			23.4			15.1
Guideline
Met Two Guidelines			70.1			75.5
Met Three Guidelines			6.5			9.4

^{^}Baseline measures of participants included in longitudinal analysis reported; LPA = Light Physical Activity; MVPA= Moderate-to-Vigorous Physical Activity; Total PA includes both MVPA and LPA; TGMD-3 = Test of Gross Motor Development—Third Edition

For Aim 1, an additional hour per day of MVPA was related to a 3.8±1.2 higher locomotor score and 4.5±1.9 higher total TGMD-3 score in adjusted models (p<0.05 for all, Table 2). No significant associations between movement guidelines, number of guidelines, and FMS were found in crude or adjusted models (p>0.05).

Table 2.

Associations among daily Physical Activity, Sleep, and Screen-time with Fundamental Motor Skills in Preschoolers (n=107)^{^}

	Ball Skills				Locomotor Skills				Total TGMD-3
	Beta	SE	p-value	R2	Beta	SE	p-value	R2	Beta	SE	p-value	R2
Behaviors (hours/day)
LPA	−1.64	1.30	0.21	0.41	−2.15	1.31	0.10	0.31	−3.79	2.07	0.07	0.38
MVPA	0.67	1.24	0.58		3.87	1.25	0.002*		4.54	1.97	0.02*
Sleep	−2.18	1.51	0.15		1.76	1.52	0.24		−0.41	2.40	0.86
Screen-time	−0.03	0.21	0.85		0.36	0.21	0.08		0.32	0.33	0.33
Movement Guidelines Met
Physical Activity	0.06	2.27	0.97	0.39	1.40	2.40	0.56	0.21	1.46	3.69	0.69	0.32
Sleep	−3.33	2.32	0.15		1.53	2.45	0.53		−1.80	3.78	0.63
Screen-time	−1.36	2.24	0.54		−2.50	2.36	0.29		−3.87	3.64	0.29
Number of Guidelines Met
Met Only One Guideline	Ref	Ref	Ref	0.39	Ref	Ref	Ref	0.21	Ref	Ref	Ref	0.32
Met Two Guidelines	−2.26	1.79	0.20		2.09	1.87	0.26		−0.16	2.91	0.95
Met Three Guidelines	−2.54	2.95	0.39		−1.67	3.09	0.58		−4.22	4.80	0.38

^{^}Assessed using linear regression with raw fundamental motor skill scores and adjustment for age, sex, race, the other movement behaviors (physical activity, sleep, and screen-time), and accelerometer wear time; R² presented is for the entire model (movement and covariates); LPA = Light Physical Activity; MVPA= Moderate-to-Vigorous Physical Activity; TGMD-3 = Test of Gross Motor Development—Third Edition;

^*p<0.05;

Fifty-three participants were included in the analyses for Aim 2 with complete baseline movement and TGMD-3 data and complete follow-up TGMD-3 measurement. Of the 54 participants not included in Aim 2, nine participants were newly enrolled at the follow-up assessment (thereby missing baseline data), seven participants did not have a baseline TGMD-3 assessment, seven participants did not have adequate wear for physical activity at baseline, and 31 participants did not have a follow-up TGMD-3 assessment. On average, the 53 participants included were 4.3±0.4 years of age at follow-up. Compared to those not included in the analysis, those included in the analyses were younger (3.2±0.5 vs. 3.6±0.6 years of age, p=0.01), reported less screen-time (3.8±3.5 vs. 5.5±3.6 hours/day, p=0.01) and slept more (10.9±0.7 vs. 10.4±1.1 hours/day, p=0.01). There were no other differences in demographics, movement behaviors, FMS, or guidelines met between groups.

For Aim 2, meeting the physical activity at baseline was associated with a higher ball score at follow-up in crude models (6.1±2.9, p=0.03). There were no other associations between movement guidelines or number of guidelines met with baseline or follow-up FMS in unadjusted models. In adjusted models, baseline LPA was negatively associated with follow-up locomotor skills and total TGMD-3 score (p<0.05 for all, Table 3). Baseline MVPA was positively associated with follow-up locomotor skills and total TGMD-3 (p<0.05 for all). Baseline sleep was positively associated with follow-up locomotor skills (p=0.02). Baseline screen-time was negatively associated with follow-up total TGMD-3 (p=0.03). Specific to the movement behaviors, baseline MVPA (4%) explained slightly more of the variance for follow-up locomotor skills compared to the other movement behaviors (1–2% each). Each movement behavior explained 2–3% of the variance for follow-up total TGMD-3 score. Movement behaviors explained some of the variance of ball skills (10%), locomotor skills (11%), and total TGMD-3 (16%) without covariates. As for movement guidelines, meeting the screen-time guideline at baseline was associated with a 6.4±3.0 higher follow-up total TGMD-3 score (p=0.04). Those who met all three movement guidelines at baseline had a 9.2±4.3 higher follow-up total TGMD-3 score compared to those who met one guideline (p=0.03). In the sensitivity analysis of models that had additional adjustment for age and sex, an additional hour of sleep at baseline was associated with a 5.5±2.7 increase in total TGMD-3 score (p=0.04). All other associations were sustained, and the variance explained was comparable.

Table 3.

Associations among daily Physical Activity, Sleep, and Screen-time with Fundamental Motor Skills at One-year Follow up in Preschoolers (n=53)^{^}

	Ball Skills				Locomotor Skills				Total TGMD-3
	Beta	SE	p-value	R2	Beta	SE	p-value	R2	Beta	SE	p-value	R2
Behaviors (hours/day)
LPA	−1.77	1.78	0.32	0.52	−4.18	1.62	0.01*	0.57	−5.88	2.19	0.01*	0.68
MVPA	1.34	1.66	0.42		3.54	1.46	0.02*		4.68	2.03	0.02*
Sleep	0.51	2.13	0.80		4.68	1.94	0.02*		5.19	2.64	0.05
Screen-time	−0.29	0.28	0.30		−0.42	0.26	0.11		−0.79	0.36	0.03*
Movement Guidelines Met
Physical Activity	2.66	2.38	0.27	0.52	1.92	2.31	0.41	0.48	4.34	3.13	0.17	0.63
Sleep	0.03	2.60	0.98		0.98	2.62	0.70		0.79	3.49	0.82
Screen-time	2.96	2.11	0.16		2.98	2.10	0.16		6.42	2.82	0.03*
Number of Guidelines Met
Met Only One Guideline	Ref	Ref	Ref	0.57	Ref	Ref	Ref	0.48	Ref	Ref	Ref	0.63
Met Two Guidelines	0.07	1.97	0.96		1.85	1.99	0.35		1.63	3.94	0.54
Met Three Guidelines	4.73	2.92	0.11		4.25	2.98	0.16		9.09	3.94	0.02*

^{^}Assessed using linear regression using raw fundamental motor skill scores and adjustment for race, the other movement behaviors (physical activity, sleep, and screen-time), and accelerometer wear time; R² presented is for the entire model (movement and covariates); LPA = Light Physical Activity; MVPA= Moderate-to-Vigorous Physical Activity; TGMD-3 = Test of Gross Motor Development—Third Edition;

^*p<0.05;

DISCUSSION

The purpose of this study was to examine the combined relationship of child movement (physical activity, sleep, screen-time) with FMS. In the cross-sectional assessment, only physical activity contributed to FMS but not sleep or screen-time. Physical activity, sleep, and screen-time were associated with FMS one-year later. This study provides evidence that attaining an adequate balance of movement may have long-term benefits on FMS development.

Overall, few preschoolers met the screen-time guideline, but most met the physical activity guideline and sleep guideline. These results are similar to an Australian preschool-age sample, where most preschoolers met the physical activity and sleep guideline (93.1% and 88.7%, respectively) but few preschoolers met the screen-time guideline (17.3%).²¹ A Canadian study of preschoolers reported a higher amount of their sample meeting the screen-time guideline (50.5%) and a lower amount meeting the physical activity guideline (19.3%).²² Both studies reported a small portion of their sample meeting all three guidelines (14.9%²¹ and 5.0%²²), which is similar to the current study. The FMS scores of the current sample were average or below average, with a slightly higher age-and-sex percentile score for ball skills, comparable to another Australian sample of preschoolers.⁸

In cross-sectional analysis, physical activity was the only movement behavior related to FMS. In this sample, the association between MVPA and FMS existed independent of LPA and other behaviors. The relationship between MVPA and FMS may be more apparent when adjusting for other behaviors that also contribute to FMS, which was not performed in other studies (e.g., Barnett, Salmon, and Hesketh⁸). Further, an FMS intervention in preschoolers resulted in more time spent in MVPA and less time spent in LPA, suggesting that FMS is specifically linked with MVPA in preschoolers.²⁰ In the current sample, baseline LPA was negatively associated with follow-up FMS. This finding may suggest that FMS advancement cannot be obtained by solely increasing total physical activity (which includes LPA and MVPA). Promotion of higher intensity physical activity (i.e. MVPA) and practice targeting specific skills may provide the most benefit for preschool children’s future FMS.²³

There is limited information on sleep and screen-time with FMS in preschoolers. Sleep features and quality were related to motor coordination in a younger sample (1-to-3 years of age).⁹ The current study suggests the duration of sleep is important for early FMS. In a cross-sectional analysis of preschoolers, screen-time was inversely associated with manual dexterity skills.²⁴ The current study suggests screen-time may also influence FMS, as the baseline screen-time guideline was associated with FMS in the longitudinal analysis. Spending less than one hour per day viewing screens may allow for more time in active pursuits, and these active pursuits may allow additional opportunity to develop and practice FMS. These findings may support models indicating a dynamic and reciprocal relationship between physical activity and FMS,^25,26 as a balance of these three behaviors contributed to future FMS. Additional investigation into the mechanism of appropriate movement and FMS on future development is necessary.

Of note, there were no significant associations among movement behaviors and ball skills in this sample. Other studies have found mixed associations between MVPA and ball skills,²⁷ or no association.²⁸ It is also possible ball skills have not fully developed in this age range, or hip accelerometry may not fully capture ball skills performed by the upper body. Adequate sleep and limiting sedentary screen-time may allow for other experiences that contribute to mental development, including social-cognitive performance,²¹ but do not translate into opportunities to practice these skills. Therefore, the lack of association between movement behavior and ball skills may be expected.

The study’s strengths include concurrent assessment of multiple behaviors, objective measure of physical activity and sleep, and longitudinal assessment of FMS. This sample included children from diverse backgrounds, including by race and household income. A limitation of the study was the number of children retained for follow-up. Few preschoolers (n=33, 31% of cross-sectional sample) had data for complete movement behaviors at both time points. This study returned to the same classroom one-year later, where children may have switched classrooms in that time. Therefore, another limitation was the limited ability to assess the mechanism of movement and FMS by evaluating baseline FMS and follow-up movement behaviors. Habitual screen-time measurements encompassed a recall of 30 days, whereas accelerometry was used to monitor seven days of physical activity and sleep in the current study. The recall was a longer period and may be subject to multiple biases, yet we chose not to ask the parent to track screen-time during the accelerometry monitoring period to reduce potential for the Hawthorne effect or introduce additional burden. Objective and user-friendly measurements of screen-time in this age range are needed. Finally, those included in the longitudinal sample reported less screen-time and more sleep than those not included, which may limit generalizability of the findings.

Future studies should consider parental influence on children’s movement and FMS development, as maternal habits were related to movement behaviors in a previous sample.¹³ Parents play an important role in facilitating physical activity, sleep, and screen-time in the home,²⁹ as well as contributing to child compliance in this age range. ECE centers are also an important area for FMS promotion³⁰ and movement behaviors.¹² In a previous investigation of these ECE centers, the ECE centers averaged ~30 minutes of screen-time at baseline and around eight minutes at follow-up which contributed to additional sedentary time and less active play.¹² This amount was not included in analysis, as it was measured at the level of the classroom rather than child-level. Specific to sleep, it is important to incorporate naptime (which may occur at ECE center). Future research should capture movement in each environment of the child’s day, including the ECE center. Finally, there is a need for opportunities to decrease child screen-time and harness this high screen use to deliver content that promotes physical activity for children and their families.

CONCLUSION

In this study, each movement behavior contributed to prospective FMS one year later. This study contributes to the scientific evidence that physical activity, sleep, and reduced screen-time are important to FMS development. An appropriate balance of all movement behaviors should be encouraged for healthy development.

Practical Implications.

• Many preschoolers exceeded the screen-time guideline, suggesting the promotion of less screen-time in young children

• Physical activity that is moderate or vigorous was related to fundamental motor skills both cross-sectionally and one-year later

• Promotion of more physical activity, adequate sleep, and less screen-time among preschoolers may lead to fundamental motor skills improvements

Abbreviations:

ECE

Early Childhood Education

FMS

Fundamental Motor Skills

MVPA

Moderate-to-vigorous Physical Activity

LPA

Light Physical Activity

PA

Physical Activity

TGMD-3

Test of Gross Motor Development-Third Edition

VPA

Vigorous Physical Activity

WHO

World Health Organization