Abstract
Objectives
This study aimed to examine the long-term effects of parenting practice during preschool years on children’s movement performance in primary school.
Methods
This three-year longitudinal study included 225 children aged 3–6-years-old. Parents reported baseline parenting practice and evaluated children’s movement performance three years later. Latent class analysis was used to explore latent classes of movement performance. A post hoc test was used to identify the characteristics of different patterns. Finally, adjusted multinomial logistic regression models were used to test the influence of parenting practice on identified patterns of movement performance.
Results
Children in this study were grouped into three movement performance patterns, labelled as ‘least difficulties’ (n = 131, 58.2%), ‘low back pain’ (n = 68, 30.2%) and ‘most difficulties’ (n = 26, 11.6%). After controlling for age, gender, having siblings or not, family structure, standardised body mass index, sleep condition and dietary habits, the researchers found that if parents played games with children frequently, the children would have a 0.287 times lower probability of being in the ‘low back pain’ class (95% confidence interval [CI]: 0.105–0.783). In addition, if parents take children to meet peers of a similar age frequently, children would have a 0.339 times lower probability of being in ‘most difficulties’ class (95% CI: 0.139–0.825).
Conclusion
Primary healthcare providers should pay careful attention to children with movement difficulties. The study provides longitudinal evidence to support the applicability of positive parenting practice in early childhood to prevent children’s movement difficulties.
Keywords: Movement, Parenting, Latent Class Analysis, Child, Longitudinal Study, Japan
Advances in Knowledge
- The study originally used the person-centred method to explore three patterns of children’s movement performance in the context of a Japanese community.
- This study confirmed the long-term effects of parenting practice during preschool years on children’s movement performance when they enter primary school.
- It was indicated that playing games with other children frequently contributed to preventing participants from developing low back pain, while taking children to meet peers of a similar age helped in preventing their movement difficulties during school age.
Application to patient care
- Primary healthcare providers should pay special attention to children with movement difficulties. The study provides longitudinal evidence to support the applicability of positive parenting practice in early childhood to prevent children’s movement difficulties.
Movement performance is defined asthe competence or skills related to motor coordination, muscle strength and balance, which are shown in self-care, sport and other daily activities.1 School-aged children need to possess motor skills, coordination and body control in order to complete daily activities.2 Movement difficulties in childhood may reduce a child’s participation in daily activities and even impact their quality of life in adulthood.3,4 Recently, the prevalence of movement difficulties has been rising worldwide.5 In Oman (N = 97; mean age = 12.9 ± 1.6 years old), 55% of the total sample developed low grip strength and approximately 45% scored low in flexibility and sit-up tests.6 National reports in Japan also show a decline in school-aged children’s movement performance, particularly among boys, which is at a historically low level.7 However, there is no gold standard for measuring children’s movement performance in existing research.8 Therefore, person-oriented cluster analysis might be a possible method to identify the characteristics of movement performance of children in a community.
Movement performance is determined by complex interactions between biological development and social environment.9 Differences are always expected for the movement performance of children in terms of age, gender, body size and lifestyles.10–13 Home-rearing environment is one of the most important social environments in which parenting practice affects children directly.14 Parenting practice refers to the observable behaviours that parents use to socialise their children in daily activities.15 A cross-sectional study demonstrated that maternal permissive parenting was gender-specifically associated with better physical activity (PA) performance in children experiencing authoritative parenting.16 However, results were not consistent with the findings of Bradley et al., which indicated that high parental monitoring was associated with poorer PA performance for boys experiencing late puberty but increased PA performance in boys experiencing early puberty using longitudinal data.17 Furthermore, only 16 of the 30 quantitative studies in an integrative review showed significant positive associations between supportive parenting and children’s physical performance.18 The majority of studies to date have focused on the intensity and frequency of PA instead of using health conditions or function status as the outcomes. Limited studies have explored the relationships between parenting practice and movement performance.
To fill gaps in existing research, the present three-year longitudinal study examined the influence of specific parenting practices for preschool children on patterns of movement performance while being of school age. To avoid bias of variable-centred methods, the study aimed to investigate: (1) the patterns of children’s movement performance based on person-oriented cluster analysis; and (2) the effects of daily parenting practice on children during the preschool period. The researchers hypothesised that: (1) patterns of children’s movement performance could be identified using different characteristics in a typical community; and (2) more positive stimulations in parenting contribute to preventing children from developing movement difficulties.
Methods
The present three-year longitudinal research study was part of a cohort study named “Community Empowerment and Care for well-being and healthy longevity” (CEC), involving all residents in T village, a typical suburban community of Japan with a population of almost 5,000 since 1991.19 The inclusion criteria were as follows: (1) being aged 3–6-years-old; (2) living in T village; and (3) having at least one parent living together. The exclusion criteria were as follows: (1) having a disability, serious disease, or developmental delay; and (2) not living in T village for the next three years. In the baseline survey, 289 parents with children aged 3–6 years provided the information on demographics and parenting practice. After three years, children’s movement performance was evaluated by parents. As 27 families dropped out of the project and 37 were excluded due to incomplete evaluation of movement performance, the final sample size was 225. All research procedures were reviewed and approved by the institutional review board and ethics committee of University of Tsukuba (Approved Number 1331). All participants provided written consent before participation.
Parenting practice was measured using the Index of Child Care Environment (ICCE), which has been used in Japanese child cohort studies for over 20 years.20,21 ICCE is a Japanese questionnaire edition of the globally-used scale called the Home Observation for Measurement of the Environment (HOME) and shows high reliability (α = 0.891).22
The ICCE is a self-reported questionnaire for parents; it consists of 13 items regarding parenting practice which are used independently in the present study. Questions for the 13 parenting practices are as follows: (1) How often do you play games with your child?; (2) How often do you go shopping with your child?; (3) How often do you read to your child?; (4) How often do you sing songs with your child?; (5) How often do you go to the park with your child?; (6) How often do you and your child meet with friends or relatives with children of a similar age?; (7) How often do you talk with your spouse about child care?; (8) How often does your spouse or any other caregiver help you with the child?; (9) How often do you and your spouse eat meals together with the child?; (10) What do you do if your child spills milk on purpose?; (11) How many times did you spank your child last week?; (12) Do you have anyone else that helps you with daily home-rearing?; and (13) Do you have anyone to consult with about child care?
Items 1–9 were measured using five-point Likert scale (1 = rarely, 2 = 1–3 times per month, 3 = 1–2 times per week, 4 = 3–4 times per week, 5 = almost every day). As the responses were not normally distributed, binary-category classification was used in the analysis based on ICCE manual (Unfavourable group = the bottom 25% of the total sample, favourable group = the rest). Item 10 had five options (1= hit the child, 2 = scold the child, 3 = discipline in another way, 4 = determine how to prevent it in the future, 5 = in other ways). Item 11 had five different options (1 = never, 2 = 1–2 times, 3 = 3–4 times, 4 = 5–6 times, 5 = almost every day). For items 10 and 11, responses were categorised into two groups (unfavourable = spank children and favourable = no spank). For items 12 and 13, responses were originally measured in a binary manner (i.e. yes or no), in which the answer ‘yes’ was evaluated as favourable and ‘no’ was evaluated as unfavourable.
Movement performance of children in the present study was investigated using a nine-item parent-reported movement performance questionnaire, which has been used by community government in large scale population-based surveys of the general population in Japan for over 20 years.23 Parents were required to compare their children’s coordination with other children of the same age based on their daily observations after the community government explained evaluation points in detail. The nine items included the following: (1) Does your child always appear energetic before and after school? (Keep active); (2) Are there any difficulties your child faces in order to continue running? (Keep running); (3) Does your child have difficulties maintaining correct sitting posture? (Good sitting posture); (4) Does your child have any arm pain? (Arm strength); (5) Does your child have any lower low back pain? (Low back strength); (6) Does your child have any leg pain? (Leg strength); (7) Are there any difficulties for your child in moving agilely to avoid obstacles? (Agility); (8) Does your child have any difficulties balancing? (Balance); and (9) Does your child have any difficulties moving their body flexibly? (Flexibility). Participants could respond to each item with ‘no’ (without any difficulties) or ‘yes’ (having some difficulties).
Demographics as well as children’s sleep condition and dietary habits were considered as covariates in the analysis models. Demographics included children’s age, gender, body mass index (BMI; standardised BMI [BMI SDS] was used in the analysis), having siblings or not and family structure (e.g. nuclear family type and extended family type). Children’s sleep condition was reported by parents as ‘sufficient’ or ‘not sufficient’. Dietary habits were also reported by parents as ‘no fussy eating’ or ‘having fussy eating behaviours’.
First, descriptive statistics were used to confirm demographics, baseline condition of parenting practice and follow-up year’s movement performance. Second, latent class analysis (LCA) was used to explore patterns of movement performance.24 Third, a post hoc test for the Chi-squared test (Bonferroni) and analysis of variance (ANOVA; LSD and S-N-K) was used to clarify differences in demographics among the patterns of movement performance and to identify the characteristics of the patterns. Finally, adjusted multinominal logistic regression analysis was applied to confirm the associations between parenting practice and movement performance patterns.
All statistical analyses were performed using the statistical package for the social sciences (SPSS), version 26.0 (IBM Corporation, Armonk, New York, USA) and Mplus, version 8.0 (Muthén and Muthén, Los Angeles, California, USA).
Results
A total of 225 children (mean age = 4.13 ± 0.87 years; mean BMI SDS = 0.12 ± 0.98) were evenly distributed in gender and family structure—boys (n = 119, 52.9%), girls (n = 106, 47.1%), nuclear family (n = 107, 47.6%) and extended family (n = 118, 52.4%)—while 83.6% of children (n = 188) had siblings. A total of 85.8% of children (n = 193) had sufficient sleep, while 68.9% of children (n = 155) had fussy eating behaviours [Table 1].
Table 1.
Demographic background in the baseline year of the children included in this study (N = 225)
| Variable | n (%) |
|---|---|
| Mean age of child in years ± SD | 4.13 ± 0.87 |
| Gender of child | |
| Boy | 119 (52.9) |
| Girl | 106 (47.1) |
| Siblings | |
| Only child | 37 (16.4) |
| Having siblings | 188 (83.6) |
| Family structure | |
| Nuclear family | 107 (47.6) |
| Extended family | 118 (52.4) |
| BMI SDS of child | 0.12 ± 0.98* |
| Sleep condition of child | |
| Sufficient | 193 (85.8) |
| Not sufficient | 32 (14.2) |
| Fussy eating behaviour of child | |
| No | 70 (31.1) |
| Yes | 155 (68.9) |
SD = standard deviation; BMI SDS = standardised body mass index
In baseline year, the item with most negative evaluations was ‘How many times did you spank your child last week?’, in which 37.8% of parents (n = 85) reported they had spanked their child in the last week. The item with least negative evaluations was ‘Do you have anyone else help you in daily home-rearing?’, in which only 2.2% of parents (n = 5) reported they took care of children without any help from others [Table 2]. As for the movement performance of children three years later, the present study showed that more than half of the children were reported to have some difficulties on: (1) maintaining right sitting posture (n = 139, 61.8%); (2) arm strength (n = 127, 56.4%); (3) agility (n = 114, 50.7%); and (4) flexibility (n = 163, 72.4%).
Table 2.
Parenting practice in baseline year and movement performance of children three years’ later (N = 225)
| Parenting practice | n (%) |
|---|---|
| Play games with child | |
| Few | 44 (19.6) |
| Frequently | 181 (80.4) |
| Shopping with child | |
| Few | 21 (9.3) |
| Frequently | 204 (90.7) |
| Read books to child | |
| Few | 56 (24.9) |
| Frequently | 169 (75.1) |
| Sing songs with child | |
| Few | 45 (20.0) |
| Frequently | 179 (79.6) |
| NA | 1 (0.4) |
| Take child to play outside | |
| Few | 27 (12.0) |
| Frequently | 197 (87.6) |
| NA | 1 (0.4) |
| Take child to meet peers of similar age | |
| Few | 46 (20.5) |
| Frequently | 178 (79.1) |
| NA | 1 (0.4) |
| Eat meals together with child | |
| Few | 48 (21.4) |
| Frequently | 176 (78.2) |
| NA | 1 (0.4) |
| Spank child for mistakes | |
| Spank | 14 (6.3) |
| Not spank | 210 (93.3) |
| NA | 1 (0.4) |
| Spank child last week | |
| Spank | 85 (37.8) |
| Not spank | 138 (61.3) |
| NA | 2 (0.9) |
| Take care of child with others | |
| Few | 18 (8.0) |
| Frequently | 204 (90.7) |
| NA | 3 (1.3) |
| Have helpers | |
| No | 5 (2.2) |
| Yes | 218 (96.9) |
| NA | 2 (0.9) |
| Have someone to consult with | |
| No | 7 (3.1) |
| Yes | 216 (96.0) |
| NA | 2 (0.9) |
| Movement performance | |
| Keep active | |
| With difficulties | 69 (30.7) |
| Without difficulties | 156 (69.3) |
| Keep running | |
| With difficulties | 62 (27.6) |
| Without difficulties | 163 (72.4) |
| Good sitting posture | |
| With difficulties | 139 (61.8) |
| Without difficulties | 86 (38.2) |
| Arm strength | |
| With difficulties | 127 (56.4) |
| Without difficulties | 98 (43.6) |
| Low back strength | |
| With difficulties | 59 (26.2) |
| Without difficulties | 166 (73.8) |
| Leg strength | |
| With difficulties | 54 (24.0) |
| Without difficulties | 171 (76.0) |
| Agility | |
| With difficulties | 114 (50.7) |
| Without difficulties | 111 (49.3) |
| Balanced | |
| With difficulties | 94 (41.8) |
| Without difficulties | 131 (58.2) |
| Flexibility | |
| With difficulties | 163 (72.4) |
| Without difficulties | 62 (27.6) |
NA = no answer.
Table 3 shows the model fit information for five LCA models with 2–6 latent classes. Akaike information criterion (AIC), Bayesian information criterion (BIC) and sample-adjusted Bayesian information criterion (aBIC) in the three-class model decreased more sharply than in the two-class model and the decline scope was the biggest among all the models (ΔAIC = −71.126, ΔBIC = −36.965, ΔaBIC = −68.657). Entropy in the three-class model was the highest among all the models (0.935). The smallest sample size of the latent class is just over 25 (n = 26) and the three-class model was significantly better than two-class model (P <0.01). Based on model selection recommendations for LCA model, the three-class model was considered as the best identified class.
Table 3.
Model fit information for the latent class analysis models
| Log-likelihood | df | G-squared | AIC | BIC | aBIC | Entropy | BLRT | |
|---|---|---|---|---|---|---|---|---|
| Two-class model | −1112.676 | 492 | 381.606 | 2263.352 | 2328.258 | 2268.043 | 0.827 | <0.01 |
| Three-class model | −1067.113 | 481 | 278.509 | 2192.226 | 2291.293 | 2199.386 | 0.935 | <0.01 |
| Four-class model | −1036.648 | 471 | 217.222 | 2151.296 | 2284.524 | 2160.925 | 0.903 | <0.01 |
| Five-class model | −1018.885 | 462 | 194.023 | 2135.769 | 2303.158 | 2147.867 | 0.921 | <0.01 |
| Six-class model | −1009.066 | 452 | 174.386 | 2136.133 | 2337.683 | 2150.700 | 0.935 | 0.122 |
df = degrees of freedom; AIC = Akaike information criteria; BIC = Bayesian information criteria; aBIC = adjusted Bayesian information criterion; BLRT = bootstrapped likelihood ratio test.
Table 4 presents the results of the Chi-squared test and one-way ANOVA analysis, showing the demographics and movement performance characteristics of the three latent patterns. There was no significant difference between the demographics of the three movement performance patterns (P >0.1). All nine items, except flexibility, showed significant differences among three movement performance patterns (P <0.05). The results of post hoc test indicated that the number of responses of movement with difficulties in class 3 was significantly greater than that in class 1 among all the nine items, except flexibility (P <0.05). No significant difference was found between class 2 and class 1 in the following categories: keep active, keep running, arm strength, agility and flexibility. No significant difference was shown between class 2 and class 3 in the following categories: good sitting posture, arm strength, leg strength and balance (P >0.05). The number of responses indicating having low back pain in class 2 was significantly greater than that in class 1, but less than that in class 3 (P <0.05). Class 1 was labelled as having the least difficulties (LD), class 2 was labelled as having low back pain (LBP) and class 3 was labelled as having the most difficulties (MD).
Table 4.
Demographics and movement performance characteristics of three patterns
| Variable | Movement performance, n (%) | F/χ2 | P value | ||
|---|---|---|---|---|---|
| Class 1 | Class 2 | Class 3 | |||
| Age in years ± SD | 4.13 ± 0.87 | 2.112 | 0.123 | ||
| Gender | |||||
| Boy | 65 (54.6) | 14 (11.8) | 40 (33.6) | 1.533 | 0.465 |
| Girl | 66 (62.3) | 12 (11.3) | 28 (26.4) | ||
| Siblings | |||||
| Single child | 23 (62.2) | 4 (10.8) | 10 (27.0) | 0.289 | 0.865 |
| Having siblings | 108 (57.4) | 22 (11.7) | 58 (30.9) | ||
| Family structure | |||||
| Nuclear family | 61 (57.0) | 11 (10.3) | 35 (32.7) | 0.757 | 0.685 |
| Extended family | 70 (59.3) | 15 (12.7) | 33 (28.0) | ||
| BMISDS ± SD | 0.12 ± 0.98 | 0.389 | 0.678 | ||
| Sleep | |||||
| Sufficient | 19 (59.4) | 3 (9.4) | 10 (31.3) | 0.175 | 0.916 |
| Not sufficient | 112 (58.0) | 23 (11.9) | 58 (30.1) | ||
| Fussy eating | |||||
| No | 93 (60.0) | 17 (11.0) | 45 (29.0) | 0.653 | 0.721 |
| Yes | 38 (54.3) | 9 (12.9) | 23 (32.9) | ||
| Keep active | |||||
| With difficulties | 21a (30.4) | 5a (7.2) | 43b (62.3) | 48.721 | <0.001 |
| Without difficulties | 110 (70.5) | 21 (13.5) | 25 (16.0) | ||
| Keep running | |||||
| With difficulties | 15a (24.2) | 4a (6.5) | 43b (69.4) | 62.315 | <0.001 |
| Without difficulties | 116 (71.2) | 22 (13.5) | 25 (15.3) | ||
| Good sitting posture | |||||
| With difficulties | 66a (47.5) | 20b (14.4) | 53b (38.1) | 17.254 | <0.001 |
| Without difficulties | 65 (75.6) | 6 (7.0) | 15 (17.4) | ||
| Arm strength | |||||
| With difficulties | 59a (46.5) | 16a,b (12.6) | 52b (40.9) | 18.300 | <0.001 |
| Without difficulties | 72 (73.5) | 10 (10.2) | 16 (16.3) | ||
| Low back strength | |||||
| With difficulties | 12a (20.3) | 20b (33.9) | 27c (45.8) | 60.649 | <0.001 |
| Without difficulties | 119 (71.7) | 6 (3.6) | 41 (24.7) | ||
| Leg strength | |||||
| With difficulties | 15a (27.8) | 14b (25.9) | 25b (46.3) | 30.083 | <0.001 |
| Without difficulties | 116 (67.8) | 12 (7.0) | 43 (25.1) | ||
| Agility | |||||
| With difficulties | 47a (41.2) | 15a,b (13.2) | 52b (45.6) | 30.090 | <0.001 |
| Without difficulties | 84 (75.7) | 11 (9.9) | 16 (14.4) | ||
| Balanced | |||||
| With difficulties | 42a (44.7) | 16b (17.0) | 36b (38.3) | 12.743 | 0.002 |
| Without difficulties | 89 (67.9) | 10 (7.6) | 32 (24.4) | ||
| Flexibility | |||||
| With difficulties | 95a (58.3) | 18a (11.0) | 50a (30.7) | 0.175 | 0.916 |
| Without difficulties | 36 (58.1) | 8 (12.9) | 18 (29.0) | ||
SD = standard deviation.
a,b, c refer to different groups based on the results of the post hoc test using Bonferroni method.
The LD class contained 58.2% (n = 131) of the sample and had high probabilities of movement performance without difficulties. The LBP class contained 11.6% (n = 26) of the sample, and all samples showed low back pain in the group. The MD class contained 30.2% (n = 68) of the sample and had low probabilities of movement performance without difficulties [Figure 1].
Figure 1.
Item probability of movement performance without difficulties in three classes.
Table 5 shows the associations between parenting practice and children’s movement performance. In the multinomial logistic regression models, each parenting practice was considered as an independent variable respectively, while age, gender, having siblings or not, family structure, BMI SDS, sleep condition and dietary habits were included in the models as covariates. The LD class was used as the reference class to show the effect of positive parenting practice on preventing movement difficulties. Model 1 indicated that if parents played games with children frequently, the children would have a 0.287 times lower probability of being in the LBP class (95% confidence interval [CI]: 0.105–0.783). Model 2 indicated that if parents take their children to meet peers of a similar age frequently, the children would have a 0.339 times lower probability of being in the MD class (95% CI: 0.139–0.825).
Table 5.
Significant results of multinominal logistic regression model showing associations between parenting practice and movement performance
| Variable | LBP versus LD class | MD versus LD class | ||
|---|---|---|---|---|
| OR (95% CI) | P value | OR (95% CI) | P value | |
| Model 1 | ||||
| Play games with child | 0.287 (0.105–0.783) | 0.015 | 0.834 (0.371–1.873) | 0.660 |
| Age | 0.860 (0.499–1.480) | 0.585 | 1.389 (0.965–1.998) | 0.077 |
| Gender | 1.101 (0.453–2.674) | 0.833 | 1.491 (0.804–2.764) | 0.205 |
| Having siblings or not | 0.543 (0.141–2.092) | 0.375 | 0.847 (0.362–1.984) | 0.702 |
| Family structure | 0.773 (0.315–1.901) | 0.575 | 1.166 (0.634–2.147) | 0.621 |
| BMI SDS | 0.997 (0.616–1.612) | 0.989 | 0.957 (0.695–1.316) | 0.785 |
| Sleep condition | 0.961 (0.245–3.777) | 0.955 | 1.144 (0.475–2.759) | 0.764 |
| Fussy eating | 0.914 (0.349–2.393) | 0.855 | 0.843 (0.436–1.631) | 0.613 |
| Model 2 | ||||
| Take child to meet peers of a similar age | 1.175 (0.443–3.115) | 0.746 | 0.339 (0.139–0.825) | 0.017 |
| Age | 0.936 (0.552–1.586) | 0.806 | 1.401 (0.973–2.019) | 0.070 |
| Gender | 1.006 (0.419–2.413) | 0.990 | 1.399 (0.745–2.627) | 0.296 |
| Having siblings or not | 0.634 (0.169–2.378) | 0.499 | 0.837 (0.357–1.964) | 0.682 |
| Family structure | 0.880 (0.367–2.110) | 0.774 | 1.155 (0.626–2.134) | 0.645 |
| BMI SDS | 1.085 (0.681–1.728) | 0.732 | 0.941 (0.685–1.294) | 0.710 |
| Sleep condition | 0.853 (0.220–3.300) | 0.818 | 1.117 (0.459–2.718) | 0.807 |
| Fussy eating | 0.921 (0.356–2.385) | 0.865 | 0.878 (0.450–1.712) | 0.703 |
LBP = low back pain; LD = least difficulties; MD = most difficulties; OR = odds ratio; CI = confidence interval.
Reference group: play games with child = few; encourage child to play with peers of a similar age = few; gender = boy; having siblings or not = only child; family structure = nuclear family; sleep = sufficient; fussy eating = no fussy eating behaviours; age and BMI SDS = continuous variables.
Discussion
To the best of the authors’ knowledge, this study is the first in Japan to examine the long-term effects of parenting practice in children’s preschool period on their movement performance outcomes when they are of school-going age. The researchers originally explored three patterns of children’s movement performance and identified their characteristics in a sample of children from a suburban area in central Japan. Based on the longitudinal results, the researchers indicated that more positive stimulations in parenting practice, such as frequently playing games with children frequently and taking children to meet peers of a similar age, contribute to preventing children from developing movement difficulties three years later.
Several studies have used the person-oriented method to explore patterns of movement performance; however, the results were inconsistent. Jaakkola et al. investigated PA, sedentary time, perceived competence, motor competence, cardiorespiratory fitness and muscular fitness in a Finnish elementary school student sample (N = 491, mean age = 11.27 ± 0.32 years) and labelled three movement profiles as ‘at-risk’ (37.7%, n = 185), ‘intermediate’ (49.3%, n = 242) and ‘desirable’ (13.0%, n = 64).25 Four movement profiles—which were ‘poor movers’ (27.9%, n = 129), ‘average movers’ (38.4%, n = 177), ‘skilled movers’ (18.9%, n = 87) and ‘expert movers’ (14.8%, n = 68)—were identified when focusing on the performance of leap, throw-catch, jump, push-up, sit-up tests.26 The present study explored three patterns of children’s movement performance and originally identified the characteristics associated with different types of movement difficulties. The biggest cluster, LD (n = 131, 58.2%), received significantly higher probability of ‘no difficulties’ than the MD cluster (n = 68, 30.2%) for all nine items except flexibility. All samples in the LBP cluster (n = 26, 11.6%) reported having pain in their low back, which was significantly different from the other two clusters. Previous studies highlighted the prevalence of low back pain in school-aged children, which was 24% in a British sample (N = 1,376), 22% in an American sample (N = 1,241) and 51% in a Danish sample (N = 1,395). This suggests low back pain is an important and relatively common problem in school children.27 The present study’s results are consistent with the existing research and additionally suggest that low back pains should also be given attention in Japan.
Many previous studies have indicated that parent-related factors, such as parents’ attitude towards children’s PA, parents’ exercise habits and parenting practice, are associated with children’s daily physical activities and, therefore, influence children’s motor competence and physical performance.28 A systematic review indicated supporting children to do PA or enrol in PA classes as doing PA together significantly contributed to improving children’s physical performance.29 Davison originally created the Activity Support Scale (ACTS) to measure parental support for children’s PA and confirmed that providing children with the chance or places to be active as well as playing sports with them is beneficial for children to improve their physical activity levels.30 In addition, previous studies also highlighted the important role of peer interactions on children’s motor performance.31 One systematic review reported a positive influence of peers’ support on PA and health outcomes.32 The present study’s results are consistent with previous studies and further clarified long-term effects of parenting practice during preschool years on children’s movement performance on entering primary school. The researchers indicated that playing games with preschool children frequently contributes to preventing them from developing back pain three years later, while taking children to meet peers of a similar age is beneficial to the prevention of children’s movement difficulties when reaching school-going age.
On the other hand, children’s age, gender, BMI, sleep condition and dietary habits were not significantly associated with children’s movement performance in the current study, which are not consistent with existing research. Boys performed better in ‘walking’, while girls performed better in ‘ball control’, and no gender difference were observed in ‘running’ and ‘kicking’ in a meta-analysis for Japanese preschool children.33 Cardio-respiratory fitness and flexibility decreased with increasing age in a sample of 4,903 European children aged 6–11 years.34 Sleep duration did not have a consistent significant effect on physical fitness, while fruit and vegetable intake positively related to physical performance with small effects.35 Inconsistent results suggested influence factors and that their effects of movement performance are complex and different across cultures.
Several limitations should be considered when interpreting the present study’s results and designing future studies. First, children’s movement performance was only measured by parent-reported questionnaires in the present study. Objective tests should be performed to verify the consistency of the results in the future. Second, although the researchers controlled several covariates, more related factors, such as SES and baseline movement performance, should also be included in the final analysis model. Finally, the sample size was small because of the loss to follow-up.
Conclusion
Children in this study were grouped into three movement performance patterns labelled LD, LBP and MD, based on a person-oriented perspective and cluster analysis. The LD group was characterised as having the highest probability of having no difficulties for all items, while the MD group was characterised as having the lowest probability of having no difficulties. The LBP group was characterised by having all samples in the group develop low back pain. More positive stimulations in parenting practice during preschool years, such as frequently playing games with children and taking them to meet peers of a similar age contributed to preventing children’s movement difficulties when they entered primary school. Children with movement difficulties should be carefully monitored by healthcare providers. Parents’ support is beneficial for children to prevent developing movement difficulties. Nevertheless, there is still a great need for more diverse samples and sufficient sample sizes to confirm the results across cultures.
ACKNOWLEDGEMENTS
The researchers express their deepest gratitude to all the participants and staff members of Tobishima for their voluntary participation in this study. The work was also supported by Japan society for the promotion of Science (JSPS) to provide the funding (Grant nos. JP21H00790 and JP21K18449).
Footnotes
AUTHORS’ CONTRIBUTION
ZZ and CK conceptualised the study. ZZ, DJ and TK designed the methodology. YZ and XL contributed with the software. ZZ, DJ, AA and MM contributed to the validation process. ZZ performed the formal analysis. DJ, XL, AA, MM, YS, SI and RO performed the investigation. TA provided the resources. DJ, YS, TW, EtT, EmT and TA contributed to the data curation. ZZ, CK, DJ and XL contributed to the drafting, review and editing of the manuscript. TA contributed to the visualisation, supervision of the work, project administration and funding acquisition. All authors have approved the final version of the manuscript.
CONFLICT OF INTEREST
The authors declare no conflicts of interest.
FUNDING
This study was funded by Japan Society for the Promotion of Science under Grants-in-Aid for Scientific Research (17H02604).
References
- 1.Missiuna C, Moll S, King S, King G, Law M. A trajectory of troubles: Parents’ impressions of the impact of developmental coordination disorder. Phys Occup Ther Pediatr. 2007;27:81–101. [PubMed] [Google Scholar]
- 2.Holm I, Tveter AT, Aulie VS, Stuge B. High intra- and inter-rater chance variation of the movement assessment battery for children 2, ageband 2. Res Dev Disabil. 2013;34:795–800. doi: 10.1016/j.ridd.2012.11.002. [DOI] [PubMed] [Google Scholar]
- 3.Kwan MY, Cairney J, Hay JA, Faught BE. Understanding physical activity and motivations for children with developmental coordination disorder: An investigation using the theory of planned behavior. Res Dev Disabil. 2013;34:3691–8. doi: 10.1016/j.ridd.2013.08.020. [DOI] [PubMed] [Google Scholar]
- 4.Canto EG, Guillamon AR, Lopez LN. Relationship between overall physical condition, 211 motor coordination and perceived quality of life in Spanish adolescents. Acta Colomb de 212 Psicol. 2021;24:96–106. doi: 10.14718/acp.2021.24.1.9. [DOI] [Google Scholar]
- 5.World Health Organization. Guidelines on physical activity, sedentary behaviour and sleep for children under 5 years of age. [Accessed: Nov 2021]. From https://apps.who.int/iris/handle/10665/311664. [PubMed]
- 6.Kilani H, Alyaarubi S, Zayed K, Alzakwani I, Bererhi H, Shukri R, et al. Physical Fitness Attributes, Vitamin D, Depression, and BMD in Omani’s Children. Eur Sci J. 2013;9:156–73. [Google Scholar]
- 7.Japan Sports Agency. The national survey of children’s physical fitness, motor 221 competence, and physical activity. [Accessed: Nov 2021]. From: https://www.mext.go.jp/sports/content/20191225-spt_sseisaku02-000003330_1.pdf.
- 8.Cools W, Martelaer KD, Samaey C, Andries C. Movement skill assessment of typically developing preschool children: A review of seven movement skill assessment tools. J Sports Sci Med. 2009;8:154–68. [PMC free article] [PubMed] [Google Scholar]
- 9.Davids K, Baker J. Genes, environment, and sport performance: Why the nature-nurture dualism is no longer relevant. Sports Med. 2007;37:961–80. doi: 10.2165/00007256-200737110-00004. [DOI] [PubMed] [Google Scholar]
- 10.Johnston LM, Burns YR, Brauer SG, Richardson CA. Differences in postural control and movement performance during goal directed reaching in children with developmental coordination disorder. Hum Mov Sci. 2002;21:583–601. doi: 10.1016/s0167-9457(02)00153-7. [DOI] [PubMed] [Google Scholar]
- 11.Ikeda T, Aoyagi O. Relationships between gender difference in motor performance and age, movement skills and physical fitness among 3- to 6-year-old Japanese children based on effect size calculated by meta-analysis. School Health. 2009;5:9–23. doi: 10.20812/jash.SH-2009_031. [DOI] [Google Scholar]
- 12.Jaric S. Role of body size in the relation between muscle strength and movement performance. Exerc Sport Sci Rev. 2003;31:8–12. doi: 10.1097/00003677-200301000-00003. [DOI] [PubMed] [Google Scholar]
- 13.Tyler RPO. Health, Fitness, Lifestyle and Physical Competency of School Children in Wales. Swansea University. 2018 doi: 10.23889/Suthesis.50798. [DOI] [Google Scholar]
- 14.Newland LA. Family well-being, parenting, and child well-being: Pathways to healthy adjustment. Clin Psychol. 2020;19:3–14. doi: 10.1111/cp.12059. [DOI] [Google Scholar]
- 15.Kahraman H, Yilmaz Irmak T, Basokcu TO. Parenting Practices Scale: Its Validity and Reliability for Parents of School-Aged Children. Educ Sci Theory Pract. 2017;17:745–69. doi: 10.12738/estp.2017.3.0312. [DOI] [Google Scholar]
- 16.Jago R, Davison KK, Brockman R, Page AS, Thompson JL, Fox KR. Parenting styles, parenting practices, and physical activity in 10- to 11-year olds. Prev Med. 2011;52:44–7. doi: 10.1016/j.ypmed.2010.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Bradley RH, McRitchie S, Houts RM, Nader P, O’brien M. Parenting and the decline of physical activity from age 9 to 15. Int J Behav Nutr Phys Act. 2011;8:1–10. doi: 10.1186/1479-5868-8-33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hutchens A, Lee RE. Parenting Practices and Children’s Physical Activity: An Integrative Review. J Sch Nurs. 2018;34:68–85. doi: 10.1177/1059840517714852. [DOI] [PubMed] [Google Scholar]
- 19.Jiao D, Watanabe Miura K, Sawada Y, Tanaka E, Watanabe T, Tomisaki E, et al. Changes in Social Relationships and Physical Functions in Community-Dwelling Older Adults. J Nurs Res. 2022;30:5. doi: 10.1097/jnr.0000000000000513. [DOI] [PubMed] [Google Scholar]
- 20.Anme T, Tanaka E, Watanabe T, Tomisaki E, Mochizuki Y, Tokutake K. Validity and reliability of the Index of Child Care Environment (ICCE) Public Health Front. 2013;2:141–5. doi: 10.5963/PHF0203003. [DOI] [Google Scholar]
- 21.Chen W, Tanaka E, Watanabe K, Tomisaki E, Watanabe T, Wu B, et al. The influence of home-rearing environment on children’s behavioral problems 3 years’ later. Psychiatry Res. 2016;244:185–93. doi: 10.1016/j.psychres.2016.07.043. [DOI] [PubMed] [Google Scholar]
- 22.Bradley RH, Caldwell BM. The HOME Inventory and family demographics. Dev Psychol. 1984;20:315–20. [Google Scholar]
- 23.Anme T. Empowerment for Healthy Longevity–Effective Utilization as Skills for Care Prevention and Health Premotion (in Japanese) Tokyo, Japan: Ishiyaku Publishers, Inc; 2007. pp. 42–55. [Google Scholar]
- 24.Lanza ST, Cooper BR. Latent class analysis for developmental research. Child Dev Perspect. 2016;10:59–64. doi: 10.1111/cdep.12163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Jaakkola T, Yli-Piipari S, Stodden DF, Huhtiniemi M, Salin K, Seppälä S, et al. Identifying childhood movement profiles and tracking physical activity and sedentary time across 1 year. Transl Sports Med. 2020;3:480–7. doi: 10.1002/tsm2.156. [DOI] [Google Scholar]
- 26.Jaakkola T, Hakkarainen A, Grasten A, Sipinen E, Vanhala A, Huhtiniemi M, et al. Identifying childhood movement profiles and comparing differences in mathematical skills between clusters: A latent profile analysis. J Sports Sci. 2021;39:2503–8. doi: 10.1080/02640414.2021.1949114. [DOI] [PubMed] [Google Scholar]
- 27.Watson KD, Papageorgiou AC, Jones GT, Taylor S, Symmons DP, Silman AJ, Macfarlane GJ. Low back pain in schoolchildren: Occurrence and characteristics. Pain. 2002;97:87–92. doi: 10.1016/s0304-3959(02)00008-8. [DOI] [PubMed] [Google Scholar]
- 28.Newland LA. Family well-being, parenting, and child well-being: Pathways to healthy adjustment. Clinical Psychologist. 2020;19:3–14. [Google Scholar]
- 29.Sleddens EF, Kremers SP, Hughes SO, Cross MB, Thijs C, De Vries NK, et al. Physical activity parenting: A systematic review of questionnaires and their associations with child activity levels. Obes Rev. 2012;13:1015–33. doi: 10.1111/j.1467-789X.2012.01018.x. [DOI] [PubMed] [Google Scholar]
- 30.Davison K. Activity-related support from parents, peers and siblings and adolescents’ physical activity: are there gender differences? J Phys Activ Health. 2004;1:363–376. doi: 10.1123/jpah.2012-0054. [DOI] [Google Scholar]
- 31.Herrmann C, Bretz K, Khnis J, Seelig H, Keller R, Ferrari I. Connection between social relationships and basic motor competencies in early childhood. Children. 2021;8:10. doi: 10.3390/children8010053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Jenkinson KA, Naughton G, Benson AC. Peer-assisted learning in school physical 268 education, sport and physical activity programmes: A systematic review. Phys Educ Sport 269 Pedagogy. 2014;19:253–77. doi: 10.1080/17408989.2012.754004. [DOI] [Google Scholar]
- 33.Ikeda T, Aoyagi O. Relationships between gender difference in motor performance and age, movement skills and physical fitness among 3-to 6-year-old Japanese children based on effect size calculated by meta-analysis[J] School Health. 2009;5:9–23. [Google Scholar]
- 34.Zaqout M, Vyncke K, Moreno LA, De Miguel-Etayo P, Lauria F, Molnar D, et al. Determinant factors of physical fitness in European children. Int J Public Health. 2016;61:573–82. doi: 10.1007/s00038-016-0811-2. [DOI] [PubMed] [Google Scholar]
- 35.Jaikaew R, Satiansukpong N. Movement performance and movement difficulties in typical school-aged children. PLoS One. 2021;16:e0249401. doi: 10.1371/journal.pone.0249401. [DOI] [PMC free article] [PubMed] [Google Scholar]