Abstract
The aim of this paper was to contribute to the elaboration of the Environmental Stress Hypothesis framework by testing eight hypotheses addressing the direct impact of gross motor coordination problems in elementary-school on selected physical, behavioral and psychosocial outcomes in adolescence. Results are based on a longitudinal sample of 940 participants who were (i) recruited as part of a population-based representative survey on health, physical fitness and physical activity in childhood and adolescence, (ii) assessed twice within 6 years, between the ages of 6 and 10 years old as well as between the ages of 12 and 16 years old (Response Rate: 55.9%) and (iii) classified as having gross motor coordination problems (N = 115) or having no gross motor coordination problems (N = 825) at baseline. Motor tests from the Körperkoordinationstest, measures of weight and height, a validated physical activity questionnaire as well as the Strength and Difficulties Questionnaire were conducted. Data were analyzed by use of binary logistic regressions. Results indicated that elementary-school children with gross motor coordination problems show a higher risk of persistent gross motor coordination problems (OR = 7.99, p < 0.001), avoiding organized physical activities (OR = 1.53, p < 0.05), an elevated body mass (OR = 1.78, p < 0.05), bonding with sedentary peers (OR = 1.84, p < 0.01) as well as emotional (OR = 1.73, p < 0.05) and conduct (OR = 1.79, p < 0.05) problems in adolescence in comparison to elementary-school children without gross motor coordination problems. However, elementary-school children with gross motor coordination problems did not show a significantly higher risk of peer problems (OR = 1.35, p = 0.164) or diminished prosocial behavior (OR = 1.90, p = 0.168) in adolescence, respectively in comparison to elementary-school children without gross motor coordination problems. This study is the first to provide population-based longitudinal data ranging from childhood to adolescence in the context of the Environmental Stress Hypothesis which can be considered a substantial methodological progress. In summary, gross motor coordination problems represent a serious issue for a healthy transition from childhood to adolescence which substantiates respective early movement interventions.
Introduction
Recent research indicates that children with motor coordination problems often show reduced physical fitness (e.g., Schott et al., ) as well as an increased risk in becoming overweight or obese (e.g., Cairney et al., ), which could be explained by a reduced participation in physical activity (e.g., Rivilis et al., ) especially concerning team sports (e.g., Poulsen et al., ). To the extent of being integrated in a group or a team, it is well known that children with motor coordination problems face a variety of difficulties concerning social interaction including lower sociometric peer-preference scores (e.g., Livesey et al., ) or peer-victimization (e.g., Campbell et al., ).
Besides the effects of motor coordination-related social interaction problems on the children's family system and especially their parents (Stephenson and Chesson, ) who were—similar to the teachers—partially found to react in a negative way on comorbid behaviors such as inattention and task avoidance (Missiuna et al., ) but also to more frequently assist and encourage their children (Pless et al., ), a decreased participation in social activities (e.g., Sylvestre et al., ) first and foremost affects the child itself. In this regard, most frequently reported psychosocial outcomes of having motor coordination problems are a reduced self-worth (e.g., Skinner and Piek, ) which could likely develop due to bullying-experiences (Piek et al., ) and result in further decreased participation levels (Cairney et al., ), less enjoyment of physical education classes, (Cairney et al., ), reduced perceived (Schoemaker and Kalverboer, ) or actual (e.g., Cummins et al., ) social competence skills, lower levels of perceived social support (e.g., Skinner and Piek, ), loneliness (e.g., Poulsen et al., ) as well as anxiety and depression (e.g., Missiuna et al., ).
In terms of a more systematic understanding of the association between motor coordination problems and mental health, Mancini et al. () recently adapted a conceptual framework termed the Environmental Stress Hypothesis (see Figure 1) in this journal. While the framework is based on Pearlin‘s stress process model (Pearlin et al., ; Pearlin, ), the term Environmental Stress Hypothesis was initially inducted by Cairney et al. () and elaborated by Cairney et al. () in the context of Developmental Coordination Disorder (DCD; Blank et al., ).
Figure 1
Following the key-assumption of the framework, poor motor skills—in terms of observable motor coordination problems—are considered a primary source of stress which raises the risk for psychological distress via secondary environmental risk factors, so called stressors. Within the framework, psychological distress is represented in terms of internalizing problems. Longitudinal research documenting the impact of childhood motor coordination problems on internalizing problems in adulthood was recently provided by Poole et al. (
In accordance with Missiuna and Campbell (
Referring to Mancini et al. (
Since motor coordination problems should not typically be diagnosed before 5 years of age (Blank et al.,
When defining the primary stressor within the Environmental Stress Hypothesis one must further consider, that following the International Classification of Diseases (ICD 10), motor coordination problems (F 0.82) could be categorized as either gross (F 82.0) or fine (F 82.1) motor dysfunctions (see also Blank et al.,
Finally, we propose to operationalize psychological distress as well as corresponding secondary risk and protective factors with reference to significant preliminary studies (e.g., Green et al.,
Table 1
| Constructs and exemplary operationalizations as used by Mancini et al. ( | Operationalizations in our study | Hypothesis |
|---|---|---|
| Motor skills | Gross motor coordination problems | 1 |
| Physical Inactivity | Avoiding organized physical activities | 2 |
| Obesity | Elevated body mass | 3 |
| Stressors (Interpersonal conflict) | Peer problems | 4 |
| Personal Resources (Mastery, Self-esteem, Social competence) | Diminished prosocial behavior | 5 |
| Social Resources (Peer and parental social support) | Bonding with sedentary peers | 6 |
| Internalizing Problems (Anxiety, Depression) | Emotional problems | 7 |
| Conduct problemsa | 8 |
Constructs, operationalization, and assignment to the hypotheses.
Conduct problems were integrated as an important aspect of externalizing problems to foster an extended view on potential mental health outcomes.
For answering the above stated research question and taking into account the age- and construct-related specifications as described above, it is assumed that elementary-school children with gross motor coordination problems show a higher risk of persistent gross motor coordination problems (Hypothesis 1), avoiding organized physical activities (Hypothesis 2), an elevated body mass (Hypothesis 3), peer problems (Hypothesis 4), diminished prosocial behavior (Hypothesis 5), bonding with sedentary peers (Hypothesis 6) as well as emotional (Hypothesis 7), and conduct (Hypothesis 8) problems in adolescence compared to elementary-school children without gross motor coordination problems.
Materials and methods
Participants
The here pursued elaboration of the Environmental Stress Hypothesis framework is based on a longitudinal sample of 940 participants who were (i) recruited as part of a population-based representative survey on health, physical fitness and physical activity in childhood and adolescence, (ii) assessed twice within 6 years, between the ages of 6 and 10 years old as well as between the ages of 12 and 16 years old (Response Rate: 55.9%) and (iii) classified as having gross motor coordination problems (N = 115) or having no gross motor coordination problems (N = 825) at baseline.
Baseline-data were obtained from the nationwide German Health Interview and Examination Survey for Children and Adolescents (KiGGS; www.kiggs.de) which was conducted by the Robert Koch-Institute (RKI, Berlin) between 2003 and 2006 (KiGGS Baseline Study; Kurth et al.,
The MoMo Baseline Study continued longitudinally in 2009 as a joint project between the University of Konstanz, the Karlsruhe Institute of Technology and the University of Education Karlsruhe (see Wagner et al.,
Within this paper we focus on elementary-school children between the ages of 6 and 10 years old at baseline (N = 1681; Mage = 8.27 ± 1.48; 50.4% boys) who were re-examined in adolescence between the ages of 12 and 16 years old (N = 940; Response Rate: 55.9%; Mage = 14.37 ± 1.46 years; 49.1% boys). Participants in the longitudinal sample were classified according to their gross motor coordination status (gross motor coordination problems/no gross motor coordination problems) at baseline (elementary-school age) using three common gross motor coordination tasks. A description of corresponding tasks as well as their composition to the respective gross motor coordination score is provided at the beginning of the measures section. Table 2 shows the sociodemographic characteristics of the longitudinal sample including participants mean age as well as the distribution of gender, migration background (Kurth et al.,
Table 2
| Total | Age in elementary-school | Age in adolescence | Boys | Girls | No migration background | Migration background | High SES | Middle SES | Low SES | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N | % | M | SD | M | SD | N | % | N | % | N | % | N | % | N | % | N | % | N | % | |
| GMCP in elementary-school | 115 | 12.2 | 8.12 | 1.53 | 14.35 | 1.52 | 55 | 47.8 | 60 | 52.2 | 105 | 92.1 | 9 | 7.9 | 27 | 23.5 | 58 | 50.4 | 30 | 26.1 |
| No GMCP in elementary-school | 825 | 87.8 | 8.15 | 1.45 | 14.38 | 1.45 | 407 | 49.3 | 418 | 50.7 | 776 | 94.7 | 43 | 5.3 | 266 | 32.2 | 428 | 51.9 | 131 | 15.9 |
| Total | 940 | 100.0 | 8.14 | 1.46 | 14.37 | 1.46 | 462 | 49.15 | 478 | 50.85 | 881 | 94.4 | 52 | 5.6 | 293 | 31.2 | 486 | 51.7 | 161 | 17.1 |
Sociodemographic characteristics of the longitudinal sample (N = 940).
GMCP, Gross motor coordination problems; SES, Socioeconomic Status.
Study groups did not significantly differ by age, neither at baseline [F(1, 938) = 0.03, p = 0.867, = 0.000] nor at the time of the first follow up [F(1, 938) = 0.04, p = 0.851, = 0.000]. Further, no significant difference was found concerning the distribution of gender [χ2(1, N = 940) = 0.09, p = 0.762, Φ = 0.010] or migration background [χ2(1, N = 933) = 1.33, p = 0.249, Φ = 0.038] among both study groups, respectively. However, there was a significant but small difference concerning the distribution of socioeconomic status (SES) at baseline among both study groups [χ2(2, N = 940) = 8.67, p < 0.05; Cramér's V = 0.096] with a comparatively higher proportion of low SES within the group of children with gross motor coordination problems. Compared to the representative baseline sample, our longitudinal sample provides slightly more high SES elementary-school children (31.2 vs. 26.3%) indicating an expectable selection bias.
To further verify the distinction between both study groups with reference to Dewey et al. (
Table 3
| Gross motor coordination in elementary-school [Z-Score] | Gross motor coordination in adolescence [Z-Score] | No ADHD in elementary-school | ADHD in elementary-school | No delayed language development in elementary-school | Delayed language development in elementary-school | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N | M | SD | N | M | SD | N | % | N | % | N | % | N | % | |
| GMCP in elementary-school | 115 | −3.67 | 1.23 | 115 | −2.50 | 2.57 | 101 | 92.7 | 8 | 7.3 | 61 | 91.0 | 6 | 9.0 |
| No GMCP in elementary-school | 825 | 0.71 | 1.75 | 825 | 0.35 | 2.05 | 774 | 97.0 | 24 | 3.0 | 453 | 96.6 | 16 | 3.4 |
| Total | 940 | 0.17 | 2.22 | 940 | 0 | 2.31 | 875 | 96.5 | 32 | 3.5 | 514 | 95.9 | 22 | 4.1 |
Characteristics of gross motor coordination performance and DCD-related co-morbidities within the longitudinal sample (N = 940).
GMCP, Gross motor coordination problems; ADHD, Attention Deficit Hyperactivity Disorder.
When compared to elementary-school children without gross motor coordination problems, elementary-school children with gross motor coordination problems not only showed a significantly lower gross motor coordination score at baseline [F(1, 938) = 670.18, p < 0.001, = 0.417] but also 6 years later, at the time of the first follow up [F(1, 938) = 183.51, p < 0.001, = 0.164]. Further, there was a significant but small difference concerning the distribution of ADHD [χ2(1, N = 907) = 5.29, p < 0.05, Φ = 0.076] and LD [χ2(1, N = 536) = 4.58, p < 0.05, Φ = 0.092] status among both study groups with a slightly higher proportion of ADHD and delayed LD within the group of elementary-school children with gross motor coordination problems.
Measures
A comprehensive list of all concepts and measures used within the MoMo Longitudinal study can be found in Wagner et al. (
Table 4
| Operationalizations | Measures | References |
|---|---|---|
| Gross motor coordination problems | MoMo test battery | Worth et al., |
| Avoiding organized physical activities | MoMo-Physical Activity Questionnaire | Jekauc et al., |
| Bonding with sedentary peers | ||
| Elevated body mass | Body-Mass Index | Stolzenberg et al., |
| Peer problems | Strength and Difficulties Questionnaire | Goodman, |
| Diminished prosocial behavior | ||
| Emotional problems | ||
| Conduct problems |
Operationalizations, measures and references.
Gross motor coordination problems were assessed using three common gross motor coordination tasks from the MoMo test battery (Wort het al.,
Figure 2

Gross motor coordination tasks (a, one-leg stand; b, balancing backwards; c, jumping side-to-side).
All motor tests as described above have already been successfully applied to our baseline data (e.g., Woll et al.,
Avoiding organized physical activities (Hypothesis 2) as well as bonding with sedentary peers (Hypothesis 6) were assessed via self-report using the MoMo-Physical Activity Questionnaire (MoMo-PAQ) which was found to be a reliable and valid assessment with psychometric properties comparable to other established physical activity questionnaires (Jekauc et al.,
An elevated body mass (Hypothesis 3) was determined on the basis of an independent measurement of participants' weight and height and the subsequent calculation of their individual Body-Mass-Index (BMI; Stolzenberg et al.,
Both, the MoMo-PAQ as well as the BMI have already been successfully applied to our longitudinal data (Spengler et al.,
Finally, peer problems (Hypothesis 4), diminished prosocial behavior (Hypothesis 5) as well emotional (Hypothesis 7) and conduct (Hypothesis 8) problems were assessed using the parent version of the Strength and Difficulties Questionnaire (SDQ, Goodman,
All motor tests (including the measurement of weight and height) as well as the MoMo-PAQ were guided by experienced assessors of the MoMo-team in the respective test-centers in both survey waves and took each participant between 70 and 90 min to complete it. The SDQ was guided by experienced assessors of the KiGGS-team in the respective test-centers at baseline and within a telephone interview at the time of the first follow-up.
Participants' testing and questioning was approved in written form by the ethical commission of the involved universities and research centers.
Statistical analysis
For analyzing the developmental risk of having gross motor coordination problems concerning the binary encoded outcome measures as described within the respective section, we opted for binary logistic regressions (e.g., Bender,
Results
Persistence of gross motor coordination problems (Hypothesis 1)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of persistent gross motor coordination problems in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 1); testing of corresponding null-hypothesis was based on a total of 940 longitudinal observations.
Descriptive results indicated that 47.8% (n = 55) of elementary-school children with gross motor coordination problems compared to 10.3% (n = 85) of elementary-school children without gross motor coordination problems show gross motor coordination problems in adolescence; in line with hypothesis 1, the hereon based results of the binary logistic regression (see Table 5) indicated that elementary-school children with gross motor coordination problems show a 7.99 times higher risk (p < 0.001) of gross motor coordination problems in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children's age (OR = 1.01, p = 0.892) and elementary-school children's sex (OR = 0.94, p = 0.731) both show no significant impact on the risk of gross motor coordination problems in adolescence.
Table 5
| Gross motor coordination problems in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 2.08 | 89.89 | 1 | 0.000c | 7.99 |
| Age at baseline | 0.01 | 0.02 | 1 | 0.892 | 1.01 |
| Sexb | −0.07 | 0.12 | 1 | 0.731 | 0.94 |
| Intercept | −2.13 | 12.56 | 1 | 0.000 | 0.12 |
| Nagelkerke‘s Pseudo-R2 | 0.152 | ||||
| N | 940 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on gross motor coordination problems in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and avoiding organized physical activities (Hypothesis 2)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of avoiding organized physical activities in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 2); testing of corresponding null-hypothesis was based on a total of 913 longitudinal observations.
Descriptive results indicated that 45% (n = 50) of elementary-school children with gross motor coordination problems compared to 31.3% (n = 251) of elementary-school children without gross motor coordination problems avoid organized physical activities in adolescence; in line with hypothesis 2, the hereon based results of the binary logistic regression (see Table 6) indicated that elementary-school children with gross motor coordination problems show a 1.53 times higher risk (p < 0.05) of avoiding organized physical activities in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children who avoid organized physical activities show a 4.44 times higher risk (p < 0.001), older elementary-school children show a 1.13 times higher risk (p < 0.05) and girls show a 1.36 times higher risk (p < 0.05) of avoiding organized physical activities in adolescence compared to elementary-school children who do not avoid organized physical activities, younger elementary-school children and boys, respectively.
Table 6
| Avoiding organized physical activities in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.43 | 3.71 | 1 | 0.027d | 1.53 |
| Avoiding organized physical activities in childhoodb | 1.49 | 92.81 | 1 | 0.000 | 4.44 |
| Age at baseline | 0.12 | 5.43 | 1 | 0.020 | 1.13 |
| Sexc | 0.30 | 3.95 | 1 | 0.047 | 1.36 |
| Intercept | −2.75 | 32.75 | 1 | 0.000 | 0.06 |
| Nagelkerke‘s Pseudo-R2 | 0.172 | ||||
| N | 913 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on avoiding organized physical activities in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, not avoiding organized physical activities in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and an elevated body mass (Hypothesis 3)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of an elevated body mass in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 3); testing of corresponding null-hypothesis was based on a total of 939 longitudinal observations.
Descriptive results indicated that 27.8% (n = 32) of elementary-school children with gross motor coordination problems compared to 12.3% (n = 101) of elementary-school children without gross motor coordination problems show an elevated body mass in adolescence; in line with hypothesis 3, the hereon based results of the binary logistic regression (see Table 7) indicated that elementary-school children with gross motor coordination problems show a 1.78 times higher risk (p < 0.05) of an elevated body mass in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children with an elevated body mass show a 17.22 times higher risk (p < 0.001) and girls show a 1.85 times lower risk (1/0.54; p < 0.01) of an elevated body mass in adolescence compared to normal-weighed elementary-school children and boys, respectively, whereat elementary-school children‘s age had no significant impact (OR = 1.04, p = 0.618) on the risk of developing an elevated body mass in adolescence.
Table 7
| Elevated body mass in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.58 | 4.25 | 1 | 0.020d | 1.78 |
| Elevated body mass in childhoodb | 2.85 | 116.29 | 1 | 0.000 | 17.22 |
| Age at baseline | 0.04 | 0.25 | 1 | 0.618 | 1.04 |
| Sexc | −0.61 | 7.95 | 1 | 0.005 | 0.54 |
| Intercept | −1.76 | 7.46 | 1 | 0.006 | 0.17 |
| Nagelkerke‘s Pseudo-R2 | 0.255 | ||||
| N | 939 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on an elevated body mass in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, no elevated body mass in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and peer problems (Hypothesis 4)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of peer problems in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 4); testing of corresponding null-hypothesis was based on a total of 937 longitudinal observations.
Descriptive results indicated that 15.8% (n = 18) of elementary-school children with gross motor coordination problems compared to 9.5% (n = 78) of elementary-school children without gross motor coordination problems show peer problems in adolescence; contrary to hypothesis 4, the hereon based results of the binary logistic regression (see Table 8) indicated that elementary-school children with gross motor coordination problems do not show a significantly higher risk (OR = 1.35, p = 0.164) of peer problems in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children with peer problems show a 4.80 times higher risk (p < 0.001) and girls show a 1.67 times lower risk (1/0.60; p < 0.05) risk of peer problems in adolescence compared to elementary-school children without peer problems and boys, whereat elementary-school children's age had no significant impact (OR = 0.95, p = 0.515) on the risk of peer problems in adolescence.
Table 8
| Peer problems in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.30 | 0.96 | 1 | 0.164d | 1.35 |
| Peer problems in childhoodb | 1.57 | 29.87 | 1 | 0.000 | 4.80 |
| Age at baseline | −0.05 | 0.42 | 1 | 0.515 | 0.95 |
| Sexc | −0.51 | 5.14 | 1 | 0.023 | 0.60 |
| Intercept | −1.30 | 3.67 | 1 | 0.056 | 0.27 |
| Nagelkerke‘s Pseudo-R2 | 0.079 | ||||
| N | 937 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on peer problems in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, no peer problems in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and diminished prosocial behavior (Hypothesis 5)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of diminished prosocial behavior in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 5); testing of corresponding null-hypothesis was based on a total of 937 longitudinal observations.
Descriptive results indicated that 2.6% (n = 3) of elementary-school children with gross motor coordination problems compared to 1.3% (n = 11) of elementary-school children without gross motor coordination problems show diminished prosocial behavior in adolescence; contrary to hypothesis 5, the hereon based results of the binary logistic regression (see Table 9) indicated that elementary-school children with gross motor coordination problems do not show a significantly higher risk (OR = 1.90, p = 0.168) of diminished prosocial behavior in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children with diminished prosocial behavior show a 7.38 times higher risk (p < 0.05) of diminished prosocial behavior in adolescence compared to elementary-school children with a normal prosocial behavior, whereat both elementary-school children's age (OR = 0.93, p = 0.694) and sex (OR = 0.43, p = 0.163) had no significant impact on the risk of diminished prosocial behavior in adolescence.
Table 9
| Diminished prosocial behavior in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.64 | 0.09 | 1 | 0.168d | 1.90 |
| Diminished prosocial behavior in childhoodb | 2.00 | 5.90 | 1 | 0.015 | 7.38 |
| Age at baseline | −0.08 | 0.16 | 1 | 0.694 | 0.93 |
| Sexc | −0.84 | 1.95 | 1 | 0.163 | 0.43 |
| Intercept | −2.67 | 2.55 | 1 | 0.111 | 0.07 |
| Nagelkerke‘s Pseudo-R2 | 0.060 | ||||
| N | 937 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on diminished prosocial behavior in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, no diminished prosocial behavior in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and bonding with sedentary peers (Hypothesis 6)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of bonding with sedentary peers in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 6); testing of corresponding null-hypothesis was based on a total of 817 longitudinal observations.
Descriptive results indicated that 36.3% (n = 37) of elementary-school children with gross motor coordination problems compared to 21.1% (n = 151) of elementary-school children without gross motor coordination problems are bonding with sedentary peers in adolescence; in line with hypothesis 6, the hereon based results of the binary logistic regression (see Table 10) indicated that elementary-school children with gross motor coordination problems show a 1.84 times higher risk (p < 0.01) of bonding with sedentary peers in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children who are bonding with sedentary peers show a 1.92 times higher risk (p < 0.01) and girls show a 2.64 times higher risk (p < 0.001) of bonding with sedentary peers in adolescence compared to elementary-school children who are bonding with physically active peers and boys, whereby elementary-school children‘s age had no significant impact (OR = 1.04, p = 0.475) on the risk of bonding with sedentary peers in adolescence.
Table 10
| Bonding with sedentary peers in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.61 | 6.64 | 1 | 0.005d | 1.84 |
| Bonding with sedentary peers in childhoodb | 0.65 | 9.80 | 1 | 0.002 | 1.92 |
| Age at baseline | 0.04 | 0.51 | 1 | 0.475 | 1.04 |
| Sexc | 0.97 | 29.51 | 1 | 0.000 | 2.64 |
| Intercept | −3.28 | 35.05 | 1 | 0.000 | 0.04 |
| Nagelkerke‘s Pseudo-R2 | 0.095 | ||||
| N | 817 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on bonding with sedentary peers in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, bonding with physically active peers in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and emotional problems (Hypothesis 7)
It was is assumed that elementary-school children with gross motor coordination problems show a higher risk of emotional problems in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 7); testing of corresponding null-hypothesis was based on a total of 937 longitudinal observations.
Descriptive results indicated that 16.7% (n = 19) of elementary-school children with gross motor coordination problems compared to 9.5% (n = 78) of elementary-school children without gross motor coordination problems show emotional problems in adolescence; in line with hypothesis 7, the hereon based results of the binary logistic regression (see Table 11) indicated that elementary-school children with gross motor coordination problems show a 1.73 times higher risk (p < 0.05) of emotional problems in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children with emotional problems show a 4.61 times higher risk (p < 0.001) of emotional problems in adolescence compared to elementary-school children without emotional problems, whereat both children‘s age (OR = 0.97, p = 0.661) and sex (OR = 1.36, p = 0.169) had no significant impact on the risk of emotional problems in adolescence.
Table 11
| Emotional problems in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.55 | 3.61 | 1 | 0.029d | 1.73 |
| Emotional problems in childhoodb | 1.53 | 29.22 | 1 | 0.000 | 4.61 |
| Age at baseline | −0.03 | 0.19 | 1 | 0.661 | 0.97 |
| Sexc | 0.31 | 1.89 | 1 | 0.169 | 1.36 |
| Intercept | −2.66 | 14.78 | 1 | 0.000 | 0.07 |
| Nagelkerke‘s Pseudo-R2 | 0.071 | ||||
| N | 937 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on emotional problems in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, no emotional problems in childhood;
Reference, boys;
One-tailed.
Gross motor coordination problems and conduct problems (Hypothesis 8)
It was assumed that elementary-school children with gross motor coordination problems show a higher risk of conduct problems in adolescence compared to elementary-school children without gross motor coordination problems (Hypothesis 8); testing of corresponding null-hypothesis was based on a total of 937 longitudinal observations.
Descriptive results indicated that 19.3% (n = 22) of elementary-school children with gross motor coordination problems compared to 12.2% (n = 100) of elementary-school children without gross motor coordination problems show conduct problems in adolescence; in line with hypothesis 8, the hereon based results of the binary logistic regression (see Table 12) indicated that elementary-school children with gross motor coordination problems show a 1.79 times higher risk (p < 0.05) of conduct problems in adolescence compared to elementary-school children without gross motor coordination problems. Furthermore, analysis of integrated co-variates indicated that elementary-school children with conduct problems show a 8.38 times higher risk (p < 0.001) and older elementary-school children show a 1.28 times lower risk (1/0.78; p < 0.01) of conduct problems in adolescence compared to elementary-school children without conduct problems and younger elementary-school children, whereat children‘s sex had no significant impact (OR = 0.77, p = 0.217) on the risk of conduct problems in adolescence.
Table 12
| Conduct problems in adolescence | |||||
|---|---|---|---|---|---|
| B | Wald | df | p | OR | |
| GMCPa | 0.58 | 4.24 | 1 | 0.020d | 1.79 |
| Conduct problems in childhoodb | 2.13 | 89.16 | 1 | 0.000 | 8.38 |
| Age at baseline | −0.24 | 10.28 | 1 | 0.001 | 0.78 |
| Sexc | −0.26 | 1.52 | 1 | 0.217 | 0.77 |
| Intercept | −0.28 | 0.19 | 1 | 0.67 | 0.76 |
| Nagelkerke‘s Pseudo-R2 | 0.195 | ||||
| N | 937 | ||||
Binary logistic regression to determine the impact of gross motor coordination problems in childhood on conduct problems in adolescence.
GMCP, Gross motor coordination problems;
Reference, no GMCP in childhood;
Reference, no conduct problems in childhood;
Reference, boys;
One-tailed.
Discussion
Summary
The Environmental Stress Hypothesis represents a heuristic framework recently adapted by Mancini et al. (
Figure 3

Elaborated pathways within the Environmental Stress Hypothesis framework (N = 940; Baseline: 6–10 years; Follow-up: 12–16 years); H, Hypothesis; H1 refers to the persistence of gross motor coordination problems from elementary-school to adolescence.
In accordance with Mancini et al. (
Limitations
The 6-year time-interval between the baseline assessment and the first follow-up certainly provides a rather rough reflection of the developmental changes characterizing the transition from childhood to adolescence. In other words, the apparently low predictive power of gross motor coordination problems cannot be seen independently from our particular design and should therefore not be misunderstood in terms of a generalized weakening of the Environmental Stress Hypothesis framework.
The framework itself was originally developed for children with DCD. However, in our study we focused particularly on children's gross motor coordination performance rather than on the full spectrum of diagnostic DCD-criteria, did not apply recommended test batteries such as the M-ABC or the BOT and used the 15th percentile as a rather moderate cut-off for the distinction between children with and without gross motor coordination problems. Therefore, our study group with gross motor coordination problems apparently represents a superset of children including those with actual DCD. Thus, from a population-standpoint and despite the fact that we used a dichotomous sample-classification, our results provide certain evidence for the Environmental Stress hypothesis framework in terms of the recent Mancini et al. (
Focusing on organized physical activities certainly excludes the possibility, that children and adolescents in our study could have also been active in other informal or school-related settings at the time of their questioning. Thus, our results on the linkage between gross motor coordination problems and physical inactivity are actually limited to the sports club setting or even more specifically, to participants' respective member status. In other words, results might display in a different manner when focusing on the amount of physical activity in this particular setting or when applying an extended setting-approach. Furthermore, while sports clubs certainly represent an important setting for sports and physical activity in Germany with a membership-rate of 57.4% in childhood and adolescence and an average exercise-rate of 4 h per week with moderate to high intensity (see Jekauc et al.,
Using the 90th BMI Percentile only provides evidence for the assumption that gross motor coordination problems have an impact on an elevated body-mass in general. Thus, one has to be aware of the fact that results may be different when explicitly focusing on the risk for pathological obesity as addressed by Mancini et al. (
Concerning the assessment of psychological distress as well as corresponding secondary risk and protective factors we have to keep in mind that the Strength and Difficulties Questionnaire only provides screening information which cannot be equated with a respective clinical diagnosis. Thus, we might have indicated children and adolescents as having respective problems even though they would potentially not meet more restrictive clinical criteria. All the more when considering that our classification beyond the borderline cases followed the original SDQ cut-off recommendations whereat more recently, a dichotomous categorization has been proposed to further differentiate the so called abnormal category. Moreover, it has to be considered that parents of pubescent and especially conspicuous adolescents might not have sufficient emotional access to their children and thus, our informants were potentially not able to provide a valid personality profile at the time of the first follow-up. Concerning potential mental health problems it has to be stated that we only screened for emotional and conduct problems which certainly represent important aspects of internalizing and externalizing problems in terms of Mancini et al. (
Finally, it has to be stated that we initially tested direct pathways leading from gross motor coordination problems to the respective physical, behavioral and psychosocial outcomes. Thus, our results do not allow for an evaluation of the Environmental Stress Hypothesis framework in terms of the postulated mediating and moderating effects.
The limitations discussed in this section will be considered core elements of the following implications.
Implications
Stronger evidence for the particular pathways within the Environmental Stress Hypothesis framework requires closed meshed monitoring (e.g., Cairney et al.,
When aiming to further elaborate the Environmental Stress Hypothesis framework in terms of Mancini et al. (
Concerning a more detailed view on physical inactivity, information on duration, frequency, intensity and seasonality in different settings should be assessed. Corresponding data could be summarized to a minutes per week-based total physical activity score for example, whereby culture-specific settings would be ineffectual. Concerning the assessment of corresponding data, one has to keep in mind that self-reports are rather easy to administer in the context of epidemiological studies (e.g., Dishman et al.,
When using the SDQ to screen for psychological distress as well as corresponding secondary risk and protective factors in future studies as recommended by Becker et al. (
Future elaborations of the Environmental Stress Hypothesis framework should primarily be focused on the postulated mediating and moderating effects. To that extent, our particular data suggests that peer-problems might be a comparatively weak operationalization of social interaction problems which opens the field for the assessment of different interaction partners such as parents or teachers (e.g., Missiuna et al.,
Concerning practical implications our longitudinal data suggests that an elementary-school child with gross motor coordination problems is more likely to develop into an overweight adolescent who avoids organized physical activities, bonds with sedentary peers and shows either emotional or conduct problems. Thus, gross motor coordination problems (even when assessed on a basic skill level) apparently represent a serious issue for a healthy transition from childhood to adolescence which substantiates early movement interventions beyond the DCD population. Similarly to programs particularly designed for children with DCD (e.g., Missiuna et al.,
Funding
This work has been developed within the Motorik-Modul Longitudinal Study (MoMo) (2009–2021): Physical fitness and physical activity as determinants of health development in children and adolescents. MoMo is funded by the Federal Ministry of Education and Research (funding reference number: 01ER1503) within the research program 'long-term studies‘ in public health research.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Statements
Author contributions
MW: Substantially contributed to the conception and design of the work as well as to the analysis and interpretation of the data. Drafted the work and revised it critically for important intellectual content. Approved the version to be published. Is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. DJ: Substantially contributed to the analysis and interpretation of the data. Revised the work critically for important intellectual content. Approved the version to be published. Is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. ANW: Substantially contributed to the acquisition of the data. Revised the work critically for important intellectual content. Approved the version to be published. Is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. AW: Substantially contributed to the acquisition of the data. Revised the work critically for important intellectual content. Approved the version to be published. Is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Acknowledgments
We would like to thank all children, adolescents and parents who participated in our study.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
ArbuckleJ. L. (2014). SPSS 23.0 User's Guide. Chicago, IL: SPSS.
2
BeckerA.RothenbergerA.SohnA.Ravens-SiebererU.KlasenF. (2015). Six years ahead: a longitudinal analysis regarding course and predictive value of the Strengths and Difficulties Questionnaire (SDQ) in children and adolescents. Euro. J. Child Adolesc. Psychiatry.24, 715–725. 10.1007/s00787-014-0640-x
3
BenderR. (2009). Introduction to the use of regression models in epidemiology. Methods Mol. Biol.471, 179–195. 10.1007/978-1-59745-416-2_9
4
BlankR.Smits-EngelsmanB.PolatajkoH.WilsonP. (2012). European academy for childhood disability (EACD): recommendations on the definition, diagnosis and intervention of developmental coordination disorder (long version). Dev. Med. Child Neurol.54, 54–93. 10.1111/j.1469-8749.2011.04171.x
5
BlankR.VinçonS.JenetzkyE. (2014). Bruininks-Oseretsky Test der motorischen Fähigkeiten (BOT-2). Frankfurt am Main: Pearson Assessment.
6
BruininksR. H.BruininksB. D. (2014). The Bruininks-Oserektsky Test of Motor Proficiency (BOT-2), 2nd Edn.Minneapolis, MN: Pearson Assessment.
7
BurtonA. W.MillerD. E. (1998). Movement Skill Assessment. Champaign, IL: Human Kinetics.
8
CairneyJ.HayJ. A.FaughtB. E.HawesR. (2005a). Developmental coordination disorder and overweight and obesity in children aged 9–14 y. Int. J. Obes.29, 369–372. 10.1038/sj.ijo.0802893
9
CairneyJ.HayJ. A.FaughtB. E.WadeT. J.CornaL. M.FlourisA. (2005b). Developmental coordination disorder, generalized self-efficacy toward physical activity, and participation in organized and free play activities. J. Pediatr.147, 515–520. 10.1016/j.jpe.2005.05.013
10
CairneyJ.HayJ.MandigoJ.WadeT.FaughtB. E.FlourisA. (2007). Developmental coordination disorder and reported enjoyment of physical education in children. Euro. Phys. Educ. Rev.13, 81–98. 10.1177/1356336x07072678
11
CairneyJ.HayJ.VeldhuizenS.MissiunaC.MahlbergN.FaughtB. E. (2010a). Trajectories of relative weight and waist circumference among children with and without developmental coordination disorder. Can. Med. Assoc. J.182, 1167–1172. 10.1503/cmaj.091454
12
CairneyJ.MissiunaC.TimmonsB. W.RodriguezC.VeldhuizenS.King-DowlingS.et al. (2015). The Coordination and Activity Tracking in CHildren (CATCH) study: rationale and design. BMC Public Health15:1266. 10.1186/s12889-015-2582-8
13
CairneyJ.RigoliD.PiekJ. (2013). Developmental coordination disorder and internalizing problems in children: the environmental stress hypothesis elaborated. Develop. Rev.33, 224–238. 10.1016/j.dr.2013.07.002
14
CairneyJ.VeldhuizenS.SzatmariP. (2010b). Motor coordination and emotional-behavioral problems in children. Curr. Opin. Psychiatry23, 324–329. 10.1097/YCO.0b013e32833aa0aa
15
CampbellW. N.MissiunaC.VaillancourtT. (2012). Peer victimization and depression in children with and without motor coordination difficulties. Psychol. Sch.49, 328–341. 10.1002/pits.21600
16
ColeT. J.BellizziM. C.FlegalK. M.DietzW. H. (2000). Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ320, 1240–1243. 10.1136/bmj.320.7244.1240
17
CumminsA.PiekJ. P.DyckM. J. (2005). Motor coordination, empathy, and social behaviour in school-aged children. Develop. Med. Child Neurol.47, 437–442. 10.1111/j.1469-8749.2005.tb01168.x
18
DeweyD.KaplanB. J.CrawfordS. G.WilsonB. N. (2002). Developmental coordination disorder: associated problems in attention, learning, and psychosocial adjustment. Hum. Mov. Sci.21, 905–918. 10.1016/s0167-9457(02)00163-x
19
DishmanR. K.WashburnR. A.SchoellerD. A. (2001). Measurement of physical activity. Quest53, 295–309. 10.1080/00336297.2001.10491746
20
FransenJ.D'HondtE.BourgoisJ.VaeyensR.PhillipaertsR. M.LenoirM. (2014). Motor competence assessment in children: convergent and discriminant validity between the BOT-2 Short Form and KTK testing batteries. Res. Dev. Disabil.35, 1375–1383. 10.1016/j.ridd.2014.03.011
21
GoodmanR. (1997). The strengths and difficulties questionnaire: a research note. J. Child Psychol. Psychiatry38, 581–586. 10.1111/j.1469-7610.1997.tb01545.x
22
GoodmanR.FordT.SimmonsH.GatwardR.MeltzerH. (2000). Using the Strengths and Difficulties Questionnare (SDQ) to screen for child psychiatric disorders in a community sample. Br. J. Psychiatry177, 534–539. 10.1192/bjp.177.6.534
23
GravetterF. J.WallnauL. B. (2014). Essentials of Statistics for the Behavioral Science, 8th Edn.Belmont, CA: Wadsworth Cengage Learning.
24
GreenD.BairdG.SugdenD. (2006). A pilot study of psychopathology in developmental coordination disorder. Child Care Health Dev.32, 741–750. 10.1111/j.1365-2214.2006.00684.x
25
HallD. M. B.ColeT. J. (2006). What use is the BMI?Arch. Dis. Child.91, 283–286. 10.1136/adc.2005.077339
26
HendersonS. E.SugdenD. A.BarnettA. L. (2007). Movement Assessment Battery for Children-2-Second Edition (Movement ABC-2). Examiner's Manual. London: Harcourt Assessment.
27
HöllingH.SchlackR.KamtsiurisP.ButschalowskyH.SchlaudM.KurthB. M. (2012). Die KiGGS-Studie. Bundesweit repräsentative Längs- und Querschnittstudie zur Gesundheit von Kindern und Jugendlichen im Rahmen des Gesundheitsmonitorings am Robert Koch-Institut [The KIGGS study. Nationwide representative longitudinal and cross-sectional study on the health of children and adolescents within the framework of health monitoring at the Robert Koch Institute]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz55, 836–842. 10.1007/s00103-012-1486-3
28
HöllingH.SchlackR.PetermannF.Ravens-SiebererU.MauzE. (2014). Psychische Auffälligkeiten und psychosoziale Beeinträchtigungen bei Kindern und Jugendlichen im Alter von 3 bis 17 Jahren in Deutschland – Prävalenz und zeitliche Trends zu 2 Erhebungszeitpunkten (2003–2006 und 2009–2012). Ergebnisse der KiGGS-Studie – Erste Folgebefragung (KiGGS Welle 1) [Psychopathological problems and psychosocial impairment in children and adolescents aged 3–17 years in the German population: prevalence and time trends at two measurement points (2003–2006 and 2009–2012)]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz57, 807–819. 10.1007/s00103-014-1979-3
29
JekaucD.ReimersA. K.WagnerM. O.WollA. (2012). Prevalence and socio-demographic correlates of the compliance with the physical activity guidelines in children and adolescents in Germany. BMC Public Health12:714. 10.1186/1471-2458-12-714
30
JekaucD.ReimersA. K.WagnerM. O.WollA. (2013a). Physical activity in sports clubs of children and adolescents in Germany: results from a nationwide representative survey. J. Public Health21, 505–513. 10.1007/s10389-013-0579-2
31
JekaucD.VölkleM.WagnerM. O.MewesN.WollA. (2013b). Reliability, validity, and measurement invariance of the german version of the physical activity enjoyment scale. J. Pediatr. Psychol.38, 104–115. 10.1093/jpepsy/jss088
32
JekaucD.WagnerM. O.KahlertD.WollA. (2013c). Reliabilität und Validität des MoMo-Aktivitätsfragebogens für Jugendliche (MoMo-AFB) [Reliability and validity of MoMo-Physical-Activity-Questionnaire for Adolescents (MoMo-AFB)]. Diagnostica59, 100–111. 10.1026/0012-1924/a000083
33
KamtsiurisP.LangeM.Schaffrath RosarioA. (2007). Der Kinder- und Jugendgesundheitssurvey (KiGGS): Stichprobendesign, Response und Nonresponse-Analyse. [The German Health Interview and Examination Survey for Children and Adolescents (KiGGS): sample design, response and nonresponse analysis]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz50, 547–556. 10.1007/s00103-007-0215-9
34
Kromeyer-HauschildK.DortschyR.StolzenbergH.NeuhauerH.Schaffrath RosarioA. (2011). Nationally representative waist circumference percentiles in German adolescents aged 11.0–18.0 years. Int. J. Pediat. Obesity6, e129–e137. 10.3109/17477166.2010.490267
35
KurthB. M.KamtsiurisP.HöllingH.SchlaudM.DölleR.EllertU.et al. (2008). The challenge of comprehensively mapping children's health in a nation-wide health survey: design of the German KiGGS-Study. BMC Public Health8:196. 10.1186/1471-2458-8-196
36
LämmleL.TittlbachS.ObergerJ.WorthA.BösK. (2010). A two-level model of motor performance ability. J. Exerc. Sci. Fit.8, 41–49. 10.1016/S1728-869X(10)60006-8
37
LingamR.JongmansM. J.EllisM.HuntL. P.GoldingJ.EmondA. (2012). Mental health difficulties in children with developmental coordination disorder. Pediatrics129, e882–e891. 10.1542/peds.2011-1556
38
LiveseyD.Lum MowM.ToshackT.ZhengY. (2011). The relationship between motor performance and peer relations in 9-to 12-year-old children. Child Care Health Dev.37, 581–588. 10.1111/j.1365-2214.2010.01183.x
39
ManciniV. O.RigoliD.CairneyJ.RobertsL. D.PiekJ. P. (2016). The elaborated environmental stress hypothesis as a framework for understanding the association between motor skills and internalizing problems: a mini-review. Front. Psychol.7:239. 10.3389/fpsyg.2016.00239
40
McIntyreF.ChiversP.LarkinD.RoseE.HandsB. (2014). Exercise can improve physical self-perceptions in adolescents with low motor competence. Hum. Mov. Sci.42, 333–343. 10.1016/j.humov.2014.12.003
41
MissiunaC. A.PollockN. A.LevacD. E.CampbellW. N.WhalenS. D.BennettS. M.et al. (2012). Partnering for change: an innovative school-based occupational therapy service delivery model for children with developmental coordination disorder. Can. J. Occupat. Ther.79, 41–50. 10.2182/cjot.2012.79.1.6
42
MissiunaC.CampbellW. N. (2014). Psychological aspects of developmental coordination disorder: can we establish causality?Curr. Dev. Disord. Rep.1, 125–131. 10.1007/s40474-014-0012-8
43
MissiunaC.CairneyJ.PollockN.CampbellW.RussellD. J.MacdonaldK.et al. (2014). Psychological distress in children with developmental coordination disorder and attention-deficit hyperactivity disorder. Res. Dev. Disabil.35, 1198–1207. 10.1016/j.ridd.2014.01.007
44
MissiunaC.MollS.KingS.LawM.KingG. (2006). “Missed and misunderstood”: children with coordination difficulties in the school system. Int. J. Spec. Educ.21, 53–67.
45
PearlinL. I. (1989). The sociological study of stress. J. Health Soc. Behav.30, 241–256. 10.2307/2136956
46
PearlinL. I.MenaghanE. G.LiebermanM. A.MullanJ. T. (1981). The stress process. J. Health Soc. Behav.22, 337–356. 10.2307/2136676
47
PeterhansE.WorthA.WollA. (2013). Association between health behaviors and cardiorespiratory fitness in adolescents: results from the cross-sectional MoMo-study. J. Adolesc. Health53, 272–279. 10.1016/j.jadohealth.2013.02.011
48
PetermannF. (Hrsg.).(2011). Movement Assessment Battery for Children-2 (M-ABC-2) (3. überarb. erw. Aufl.).Frankfurt/Main: Pearson Assessment.
49
PiekJ. P.BarrettN. C.AllenL. S.JonesA.LouiseM. (2005). The relationship between bullying and self-worth in children with movement coordination problems. Br. J. Educ. Psychol.75, 453–463. 10.1348/000709904X24573
50
PiekJ. P.KaneR.RigoliD.McLarenS.RobertsC. M.RooneyR.et al. (2015). Does the Animal Fun program improve social-emotional and behavioural outcomes in children aged 4–6 years?Hum. Mov. Sci.43, 155–163. 10.1016/j.humov.2015.08.004
51
PlessM.PerssonK.SundelinC.CarlssonM. (2001). Children with developmental co-ordination disorder: a qualitative study of parents' descriptions. Adv. Physiother.3, 128–135. 10.1080/140381901750475375
52
PooleK. L.SchmidtL. A.MissiunaC.SaigalS.BoyleM. H.et al. (2015). Motor coordination and mental health in extremely low birth weight survivors during the first four decades of life. Res. Dev. Disabil.4, 87–96. 10.1016/j.ridd.2015.06.004
53
PoulsenA. A.ZivianiJ. M.CuskellyM.SmithR. (2007). Boys with developmental coordination disorder: loneliness and team sports participation. Am. J. Occupat. Ther.61, 451–462. 10.5014/ajot.61.4.451
54
PrinceS. A.AdamoK. B.HamelM. E.HardtJ.Conner GorberS.TremblayM. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. Int. J. Behav. Nutr. Phys. Act.5:56. 10.1186/1479-5868-5-56
55
RaunerA.JekaucD.MessF.SchmidtS.WollA. (2015). Tracking physical activity in different settings from late childhood to early adulthood in Germany: the MoMo Longitudinal Study. BMC Public Health15:391. 10.1186/s12889-015-1731-4
56
ReimersA. K.JekaucD.PeterhansE.WagnerM. O.WollA. (2013). Prevalence and socio-demographic correlates of active commuting to school in a nationwide representative sample of German adolescents. Prev. Med.56, 64–69. 10.1016/j.ypmed.2012.11.011
57
RigoliD.PiekJ. P.KaneR. (2012). Motor coordination and psychosocial correlates in a normative adolescent sample. Pediatrics129, e892–e900. 10.1542/peds.2011-1237
58
RivilisI.HayJ.CairneyJ.KlentrouP.LiuJ.FaughtB. E. (2011). Physical activity and fitness in children with developmental coordination disorder: a systematic review. Res. Dev. Disabil.32, 894–910. 10.1016/j.ridd.2011.01.017
59
RothenbergerA.BeckerA.ErhartM.WilleN.Ravens-SiebererU. (2008). Psychometric properties of the parent strengths and difficulties questionnaire in the general population of German children and adolescents: results of the BELLA study. Eur. Child Adolesc. Psychiatry17, 99–105. 10.1007/s00787-008-1011-2
60
SchillingF. (1974). Körperkoordinationstest für Kinder. KTK. Manual. Weinheim: Beltz Test.
61
SchillingF.BaedkeD. (1980). Screening Test für den motorischen Bereich bei der Einschulung. Motorik3, 84–86.
62
SchoemakerM. M.KalverboerA. F. (1994). Social and affective problems of children who are clumsy: how early do they begin?Adapt. Phys. Act. Q.11, 130–140.
63
SchottN.AlofV.HultschD.MeermannD. (2007). Physical fitness in children with developmental coordination disorder. Res. Q. Exerc. Sport78, 438–450. 10.1080/02701367.2007.10599444
64
SkinnerR. A.PiekJ. P. (2001). Psychosocial implications of poor motor coordination in children and adolescents. Hum. Mov. Sci.20, 73–94. 10.1016/s0167-9457(01)00029-x
65
SlaterL. M.HillierS. L.CivettaL. R. (2010). The clinimetric properties of performance-based gross motor tests used for children with developmental coordination disorder: a systematic review. Pediatr. Phys. Ther.22, 170–179. 10.1097/PEP.0b013e3181dbeff0
66
Smits-EngelsmanB.HendersonS. E.MichelsC. G. J. (1998). The assessment of children with developmental coordination disorders in the Netherlands: the relationship between the Movement Assessment Battery for Children and the Körperkoordinations Test für Kinder. Hum. Mov. Sci.17, 699–709. 10.1016/S0167-9457(98)00019-0
67
SpenglerS.MessF.SchmockerE.WollA. (2014). Longitudinal associations of health-related behaviour patterns in adolescence with change of weight status and self-rated health over a period of 6 years: results of the MoMo longitudinal study. BMC Pediatr.14:24210.1186/1471-2431-14-242
68
SpenglerS.WollA. (2013). The more physically active, the healthier? The relationship between physical activity and health-related quality of life in adolescents: the MoMo-Study. J. Phys. Act. Health10, 708–715. 10.1123/jpah.10.5.708
69
StephensonE. A.ChessonR. A. (2008). ‘Always the guiding hand’: parents' accounts of the long-term implications of developmental co-ordination disorder for their children and families. Child Care Health Dev.34, 335–343. 10.1111/j.1365-2214.2007.00805.x
70
StolzenbergH.KahlH.BergmannK. E. (2007). Körpermaße bei Kindern und Jugendlichen in Deutschland. Ergebnisse des Kinder- und Jugendgesundheitssurveys (KiGGS) [Body measurements of children and adolescents in Germany. Results of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS)]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz50, 659–669. 10.1007/s00103-007-0227-5
71
SylvestreA.NadeauL.CharronL.LaroseN.LepageC. (2013). Social participation by children with developmental coordination disorder compared to their peers. Disabil. Rehabil.35, 1814–1820. 10.3109/09638288.2012.756943
72
TittlbachS. A.SyguschR.BrehmW.WollA.LampertT.AbeleA. E.et al. (2011). Association between physical activity and health in German adolescents. Eur. J. Sport Sci.11, 283–291. 10.1080/17461391.2010.509891
73
TurnerE. L.DobsonJ. E.PocockS. J. (2010). Categorisation of continuous risk factors in epidemiological publications: a survey of current practice. Epidemiol. Perspect. Innov.15:9. 10.1186/1742-5573-7-9
74
WebsterE. K.UlrichD. A. (in press). Evaluation of the psychometric properties of the test of gross motor development. J. Mot. Learn. Dev.
75
ViholainenH.AroT.PurtsiJ.TolvanenA.CantellM. (2014). Adolescents' school-related self-concept mediates motor skills and psychosocial well-being. Br. J. Educ. Psychol.84, 268–280. 10.1111/bjep.12023
76
WagnerM. O.BösK.JascenokaJ.JekaucD.PetermannF. (2012). Peer problems mediate the relationship between developmental coordination disorder and behavioral problems in school-aged children. Res. Dev. Disabil.33, 2072–2079. 10.1016/j.ridd.2012.05.012
77
WagnerM. O.BösK.JekaucD.KargerC.MewesN.ObergerJ.et al. (2014). Cohort Profile: the Motorik-Modul Longitudinal Study: physical fitness and physical activity as determinants of health development in German children and adolescents. Int. J. Epidemiol.43, 1410–1416. 10.1093/ije/dyt098
78
WagnerM. O.WebsterE. K.UlrichD. (2016). Psychometric properties of the Test of Gross Motor Development 3 (German translation) – Results of a pilot study. J. Motor Learn. Dev. 10.1123/jmld.2016-0006. [Epub ahead of print].
79
WagnerM.WorthA.SchlenkerL.BösK. (2010). Motorische Leistungsfähigkeit im Kindes- und Jugendalter. Ausgewählte Ergebnisse des Motorik-Moduls (MoMo-Studie) [Motor fitness in childhood and adolescence. Selected results from the “Motorik-Modul” (MoMo study)]. Monatsschrift Kinderheilkunde158, 432–440. 10.1007/s00112-009-2121-8
80
WilsonA.PiekJ. P.KaneR. (2013).The mediating role of social skills in the relationship between motor ability and internalizing symptoms in pre-primary children. Infant. Child Dev.22, 151–164. 10.1002/icd.1773
81
WinklerJ.StolzenbergH. (1999). Der Sozialschichtindex im Bundes-Gesundheitssurvey [Social class index in the Federal Health Survey]. Gesundheitswesen61, S178–S183.
82
WoernerW.BeckerA.FriedrichC.RothenbergerA.KlasenH.GoodmanR. (2002). Normierung und Evaluation der deutschen Elternversion des Strengths and Difficulties Questionnaire (SDQ): Ergebnisse einer repräsentativen Felderhebung. Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie30, 105–112. 10.1024//1422-4917.30.2.105
83
WollA.KurthB. M.OpperE.WorthA.BösK. (2011). The ‘Motorik-Modul’ (MoMo): physical fitness and physical activity in German children and adolescents. Eur. J. Pediatr.170, 1129–1142. 10.1007/s00431-010-1391-4
84
WollA.WorthA.MündermannA.HöllingH.JekaucD.BösK. (2013). Age- and sex-dependent disparity in physical fitness between obese and normalweight children and adolescents. J. Sports Med. Phys. Fit.53, 48–55.
85
WorthA.WollA.AlbrechtC.KargerC.MewesN.ObergerJ.et al. (2015). MoMo-Längsschnittstudie “Physical Fitness and Physical Activity as Determinants of Health Development in Children and Adolescents” - Testmanual zu den motorischen Tests und den Anthropometrischen Messungen. KIT Scientific Reports.Karlsruhe: KIT Scientific Publishing.
Summary
Keywords
gross motor coordination problems, poor motor skills, mental health problems, overweight and obesity, physical inactivity
Citation
Wagner M, Jekauc D, Worth A and Woll A (2016) Elaboration of the Environmental Stress Hypothesis–Results from a Population-Based 6-Year Follow-Up. Front. Psychol. 7:1904. doi: 10.3389/fpsyg.2016.01904
Received
24 June 2016
Accepted
21 November 2016
Published
15 December 2016
Volume
7 - 2016
Edited by
Pietro Avanzini, University of Parma, Italy
Reviewed by
Winona Snapp-Childs, Indiana University Bloomington, USA; Philip Edward Kearney, University of Chichester, UK
Updates

Check for updates
Copyright
© 2016 Wagner, Jekauc, Worth and Woll.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Matthias Wagner matthias.wagner@uni-konstanz.de
This article was submitted to Movement Science and Sport Psychology, a section of the journal Frontiers in Psychology
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.