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The Influence of Physical Activity Regime on Body Composition in Teenagers With and Without Intellectual Disabilities

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31 October 2023

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01 November 2023

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Abstract
This study aims to assess several morphofunctional parameters in female teenagers with and without intellectual disability to characterise normality and its disturbances. More precisely, the purpose was to examine the factors contributing to the differences in body composition elements between groups, such as the physical activity level. To evaluate these parameters, we used bioelectrical impedance analysis technology (BIA), most commonly used in studies concerning body composition because it is non-invasive, quick, with high data fidelity; it can be easily moved to various locations and applied straightforwardly among populations with diverse types of intellectual disability. Our research sample comprised 212 subjects (boys and girls) aged 17.1±0.6, divided into six groups by gender and type of intellectual disability. The study found influences of physical activity level on body composition components. In addition, we report a highly significant relationship for p<0.05, body mass index and the independent variable (No. of min./week) in some groups.
Keywords: 
body composition
;  
physical activity
;  
intellectual disability
Subject: 
Public Health and Healthcare  -   Public Health and Health Services

1. Introduction

According to WHO, physical activity is “any bodily movement produced by skeletal muscles that requires energy expenditure. Physical activity refers to all movement, including during leisure time, for transport to and from places, or as part of a person’s work”[1]. Physical activity can include various physical activities, such as planned physical effort (participation in Physical Education classes and sports practices), play, indoor/outdoor chores, leisure fitness, and walking [2].
Recent studies [3] have shown that exercising can improve general health, muscle development, cardiorespiratory health, and cognitive and mental performance. Numerous studies argue that physical activity brings benefits to persons with intellectual disability. A systematic review conducted in 2018 by Crespillo-Jurado examined the effects of physical exercises on health and quality of life in persons with intellectual disabilities. The study reports that physical exercises can improve these patients' general health, motor development, and quality of life [4]. Another research carried out in 2023 by Lancioni et al. analysed the effects of long-term physical exercise programs on health and motor skills in youths with an intellectual disability. They concluded that physical exercise programs significantly improved balance, muscle strength, and agility [5]. A different study focused on the effects of a workout routine on functional capacity and the quality of life in teenagers with an intellectual disability. Per the research, the workout routine improved physical effort resistance and quality of life [6]. An investigation conducted in 2020 examined the effects of a workout routine on motor skills and self-esteem in teenagers with an intellectual disability. According to the study, physical exercise programs significantly improved motor skills and self-esteem among the participants [7].
Physical activity correlates positively with cardiorespiratory and muscular fitness; both are essential components of general health, while physical idleness is the fourth most crucial risk factor of early death worldwide. Physical idleness is also a key risk factor for obesity and life-threatening disorders like cardiovascular disease, cancer, and diabetes [8]. Comprehensive research has been carried out on the health benefits of physical activity among adolescents with an intellectual disability. The research suggests that physical activity in and outside school positively impacts teenagers' physical, psychological, and social development. More precisely, physical activity has been proven to improve the quality of life [9], decrease the risk of disease, increase mental and emotional well-being [10,11,12], improve school performance and motor skills [13], increase the frequency of prosocial behaviours [14] and improve self-concept [15].

2. Materials and Methods

This investigation per se began a while ago, through conversations with Physical Education and Sports teachers within inclusive education centres that school children with an intellectual disability, discussions with specialists in the field, and the literature study. The activities took place in the gymnasiums of educational establishments and the physical therapy practices of the “Sf. Andrei” School Centre Gura Humorului (Suceava County), The “Constantin Păunescu” School Centre Iaşi, “Elisabeta Polihroniade” Inclusive Education School Centre Vaslui, “Emil Gârleanu” Special School No. 1 Galați. This study included 212 subjects from the aforementioned institutions, distributed in six groups by gender and type of disability, as illustrated in Table 1.
We used the TANITA MC 580 professional device to determine the body composition and a dedicated analysis software, i.e., TANITA PRO SOFTWARE – 3.4.5 version – the Tanita PRO software pack was developed in partnership with the most significant medical software developer (Medizin & Service GmbH). The software can store and analyse the data from the Tanita MC 580 monitor. According to EU Regulations, both the device for body composition and the software are medically approved, and they observe the Regulations in force (Council Directive 93/42/EEC of 14 June 1993 concerning medical devices). The use of TANITA MC580 and TANITA PRO SOFTWARE generates the following measurements: Body mass – Kg; BMI (kg/h2); Body fat %; Muscle mass %; BMR (kcal); Body fat – Kg; Muscle mass – Kg; SMM – skeletal muscle mass; Bone mineral mass; Segmental analysis on upper/lower limbs, left/right, which, besides height (determined using the telemeter) represent the dependent variables.
The independent variables are gender, type of intellectual disability, and number of minutes of physical activity/week. We analysed the data collected using numerical syntheses in SPSS 20.0., thus removing some of the data to increase relevance.
Ethics: This study was conducted per the 1964 Declaration of Helsinki.
Hypothesis. Physical activity among teenagers with an intellectual disability can influence the body composition parameters.

3. Results

We used simple linear regression to assess the effect of physical activity (No. of min./week) on body composition parameters. Following this analysis, we identified just one interaction in the group of boys, between physical activity (No. of min./week) and skeletal muscle mass, for p<0.05 (Table 2); it can be considered that the independent variable (No. of min./week) influences skeletal muscle mass.
Thus, the value of (adjusted) regression coefficient R2 = 0.038 (Table 3) represents the variation percentage, i.e., 3.8% in the dependent variable of skeletal muscle mass (SMM). This percentage can be explained by the independent variable (No. of min./week).
We did not identify any statistically significant interactions for the two other groups of boys with MID and SID. However, we used a One-Way ANOVA test to determine the effect of physical activity on specific components of body composition. In this respect, to determine the relationship between the dependent variables and the independent variable (weekly physical activity), we identified four levels of physical activity/week in agreement with the activities conducted by the subjects during Physical Education classes, sports circle classes, or other extracurricular sports activities. Hence, we pointed out the following levels of physical activity:
  • NA 1 - Activity level 1 - physical activity < 90 min.
  • NA 2 - Activity level 2 - physical activity ranging between 90 – 135 min.
  • NA 3 - Activity level 3 - physical activity ranging between 135 – 240 min.
  • NA 4 - Activity level 4 - physical activity ˃240 min.
As shown in Table 4, the weekly physical activity level generates significant differences for variables such as height, muscle mass (kg), and skeletal muscle mass. The multiple comparison (Bonferroni) between the activity levels highlights significant differences between NA 2 (AF - 90-135 min) and NA 4 (AF ˃ 240 min) for skeletal muscle mass (Kg) p<0.05 (Table 5) with a difference between means of 6.08 kg skeletal muscle mass and between NA 1 (AF < 90 min.) and NA 4 (AF ˃ 240 min), for the same dependent variable p<0.05 (Table 3), the difference between means with a value of 4.51 kg. Another significant difference was noted in muscle mass in kg for p<0.05 (Table 5) between NA 2 and NA 4 (the difference between means amounts to 9.00 kg).
In the female groups, the most relevant effects of the independent variable No. of min./week on the dependent variables were identified in the group with moderate intellectual disability, as follows:
Skeletal muscle mass (SMM) can be influenced by up to 18.5% by the number of minutes of physical activity (Table 6), for p<0.05 (Table 7)
Concerning body mass index, we note a highly significant relationship for p<0.05 between it and the independent variable (No. of min./week) (Table 8).
As illustrated in Table 9, the value of the regression coefficient squared is 0.303, i.e., the body mass index value can be influenced by up to 30.3% by the No. of min./week. of physical activity.
To determine the effect of the independent variable (physical activity - No. of min./week) on several components of body composition (dependent variables), like in the groups of boys, we used a One-Way ANOVA test for the entire group of girls concerning the four levels of physical activity, but no statistically significant differences were identified.

4. Discussion

Various research [16,17] reports that the physical activity level influences muscle mass in boys. It is due to vigorous physical exercises increasing the synthesis of muscle proteins, which can increase muscle mass. Generally, these studies demonstrate that the physical activity level and the type of physical exercises performed by boys significantly impact muscle mass. Besides these studies, other research indicated that the physical activity level can have a crucial impact on muscle mass in boys. For instance, another investigation conducted by [18] shows that strength training in combination with a protein-rich diet can significantly increase the muscle mass of teenage boys [19].
Studies show that around 47% of disabled adolescents are obese, i.e., 10% higher than typical teenagers [20,21,22]. Generally, the activity level of disabled persons is insufficient to prevent disease and other chronic diseases driven by idleness. Physical activity usually decreases as young people reach adulthood. However, studies have shown that specific physical exercise programs can reverse this trend and create favourable premises for physical activity to remain present in the life of this population [23].
The current methods of adapted sports fail to approach the complexity of life among teenagers with an intellectual disability. Little attention has been given to the motivation necessary to be physically active in a population at risk that requires increased physical activity [24]. However, disabled people usually cannot experience it due to personal and significant environmental barriers or the few opportunities to participate in sports or other physical activities from a young age [25]. Furthermore, as young people become adults, their physical activity level decreases [26,27].
Consequently, disabled people do not carry out enough physical activity to prevent illnesses related to idleness and other chronic diseases driven by inactivity [20,28]. However, youths with intellectual disabilities do not entirely benefit from it because they tend to be less physically fit and overweight than developing youths without intellectual disabilities. Fortunately, previous research [29] has proven that individuals with disabilities can improve their body composition indicators by exercising [30].
Disabled people are significantly less physically active than their typical peers, which can lead to a variety of adverse health consequences [13,31]. The outcomes of this idleness manifest in several secondary diseases, among which cardiovascular disease, i.e., the first cause of death among these persons [20]. Persons without disabilities usually learn valuable motor skills and appreciate sporting activities and other leisure programs from a young age [32,33]. However, disabled people face many barriers to becoming more physically active, primarily due to the lack of proper recreation and adapted sports programs.
Youth programs positively influence physical activity levels until adulthood [26,34]. In contrast, inefficiently designed and unfolded youth programs negatively impact the future physical activity level due to low effort or lack of motivation, which play a significant role in forming a positive attitude for a disabled child. Hence, during training, the recommendation is to insist on the repeated execution of successful actions, on the permanent use of reinforcements and encouragements, and on repeating appreciation regarding the positive aspects of subjects [35].
Disabled youths are disproportionately underserved by the recreation and adapted sports programs compared to typical youths. This lack of programs contributes to higher idleness among youths with disabilities, persisting to adulthood [36]. Providing adapted sports programs is a crucial characteristic of a society promoting equal opportunities [37,38].
In addition, it is relevant to mention that the physical activity level is not the only factor influencing muscle mass in boys. Other significant factors include proper nutrition, hormone level, and the quantity and quality of sleep [39].

5. Conclusions

Generally, adolescents with severe intellectual disabilities tend to have a different body composition than persons without intellectual disabilities. More precisely, individuals with severe intellectual disability tend to have a lower or higher weight than the population’s average value.
Concerning physical activity in persons with an intellectual disability, there is mounting evidence in favour of structured physical exercise programs for these populations, demonstrating body composition alterations. Furthermore, combined exercise programs have positively affected aerobic capacity and muscle power. However, practical and methodological guidelines are not clear concerning the organisation of components suggested for the structure of training sessions and the programs to improve the physical shape and health of persons with intellectual disabilities.
Finally, it is worth noting that the physical activity level is essential in increasing muscle mass in boys. However, it is crucial to consider other factors that can influence this process.

Author Contributions

Conceptualisation: B.C.U., A.C., B.A.A., L.P., E.T., C.E.-V., C.P., A.R.P., F.P.M., C.P. and C.F.B.; methodology: B.C.U., A.C., C.E.-V., E.T., F.P.M., C.P. C.P. and B.A.A.; software: B.C.U., A.C., C.E.-V., C.P., CP. and B.A.A.; validation: B.C.U., A.C., B.A.A., C.E.-V., C.P., C.P. and L.P.; formal analysis: B.C.U., A.C., B.A.A., C.F.B., E.T., F.P.M., C.P., C.P. and L.P.; writing—original draft preparation: B.C.U., A.C., B.A.A., C.F.B., A.R.P., F.P.M., C.P., C.P., A.R.P. and L.P. All authors have equal contributions. All authors have read and agreed to the published version of the manuscript.

Funding

This work was co-funded by the European Social Fund, through Operational Programme Human Capital 2014–2020, project number POCU/993/6/13/153322, project title “Educational and training support for PhD students and young researchers in preparation for insertion in the labor market”.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of “Alexandru Ioan Cuza” University of IASI, ROMANIA (protocol code 10/2020 and date of approval: 7 October 2020).

Data Availability Statement

Informed consent was obtained from all subjects involved in the study.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Distribution of subjects by age, cases, and educational establishments.
Table 1. Distribution of subjects by age, cases, and educational establishments.
Subjects Gender N Age
(mean±std.dev.)		 Case Observation
Group 1(WID)
Without intellectual disabilities 		M 44 17.7±0.9 WID
Group 2 (WID)
Without intellectual disabilities (WID)		 F 55 17.2±0.7 WID
Group 3 (MID)
Moderate intellectual disability 		M 57 17.05±0.7 MID
Group 4 (MID)
Moderate intellectual disability		 F 22 16.6±0.8 MID
Group 5 (SID)
Severe intellectual disability 		M 23 17.4±0.8 SID
Group 6 (SID)
Severe intellectual disability 		F 11 17.1±0.8 SID
Table 2. Linear regression for SMM in the group of boys WID (ANOVAa).
Table 2. Linear regression for SMM in the group of boys WID (ANOVAa).
Model Sum of s#quares df Mean squ#ares F Sign. thresh.
1 Regression 156.055 1 156.055 4.817 .030b
Residual value 3952.040 122 32.394
Total 4108.095 123
a. Dependent variable: SMM; b. Prediction: (Constant), No. of min./week; F-approximation used to
calculate significance; df-degree of freedom for Fisher distribution.
Table 3. The regression coefficient for the group of boys WID (Anovab).
Table 3. The regression coefficient for the group of boys WID (Anovab).
Model R R2 R2 Adjusted Estimated Standard Error
1 .195a .038 .030 5.6916
a. Prediction: (Constant), No. of min./week; b-dependent variable; R- regression coefficient; R2 – regression coefficient squared
Table 4. The ANOVA test for the dependent variables in the groups of boys.
Table 4. The ANOVA test for the dependent variables in the groups of boys.
Sum of Squares df Mean Squares F Sign. Thresh. (p)
Height - cm Between groups 830.194 3 276.731 3.524 *.017
Within the groups 9424.041 120 78.534
Total 10254.234 123
Body mass-Kg Between groups 1403.089 3 467.696 2.172 .095
Within the groups 25839.632 120 215.330
Total 27242.721 123
BMI (kg/m2) Between groups 33.594 3 11.198 .561 .642
Within the groups 2396.306 120 19.969
Total 2429.900 123
Body fat % Between groups 60.423 3 20.141 .306 .821
Within the groups 7904.260 120 65.869
Total 7964.683 123
Muscle mass % Between groups 17.109 3 5.703 .178 .911
Within the groups 3834.498 120 31.954
Total 3851.607 123
BMR (kcal) Between groups 438542.076 3 146180.692 2.307 .080
Within the groups 7603922.916 120 63366.024
Total 8042464.992 123
Body fat-Kg Between groups 40.084 3 13.361 .203 .894
Within the groups 7885.495 120 65.712
Total 7925.580 123
Muscle mass-kg Between groups 964.858 3 321.619 4.175 *.008
Within the groups 9244.679 120 77.039
Total 10209.538 123
SMM Between groups 503.634 3 167.878 5.589 *.001
Within the groups 3604.461 120 30.037
Total 4108.095 123
df-degree of freedom for Fisher distribution; F-approximation used to calculate significance; *Significance threshold for p<0.05.
Table 5. Significance threshold and the difference between means for the group of boys WID.
Table 5. Significance threshold and the difference between means for the group of boys WID.
Dependent Variable (I) Phys. act. lev. (J) Phys. act. lev. The Difference Between Means(I-J) Er.
Std.		 Sig. 95% Confidence Interval
Lower Limit Upper Limit
Muscle mass-Kg 1.00 2.00 3.0655 1.9699 .734 -2.219 8.350
3.00 -4.7827 4.5041 1.000 -16.866 7.300
4.00 -5.9382 2.3037 .067 -12.118 .242
2.00 1.00 -3.0655 1.9699 .734 -8.350 2.219
3.00 -7.8481 4.7025 .586 -20.463 4.767
4.00 -9.0037* 2.6708 .006 -16.169 -1.839
3.00 1.00 4.7827 4.5041 1.000 -7.300 16.866
2.00 7.8481 4.7025 .586 -4.767 20.463
4.00 -1.1556 4.8518 1.000 -14.171 11.860
4.00 1.00 5.9382 2.3037 .067 -.242 12.118
2.00 9.0037* 2.6708 .006 1.839 16.169
3.00 1.1556 4.8518 1.000 -11.860 14.171
SMM 1.00 2.00 1.5690 1.2300 1.000 -1.731 4.869
3.00 -4.9532 2.8124 .485 -12.498 2.592
4.00 -4.5143* 1.4385 .013 -8.373 -.655
2.00 1.00 -1.5690 1.2300 1.000 -4.869 1.731
3.00 -6.5222 2.9363 .169 -14.399 1.355
4.00 -6.0833* 1.6677 .002 -10.557 -1.609
3.00 1.00 4.9532 2.8124 .485 -2.592 12.498
2.00 6.5222 2.9363 .169 -1.355 14.399
4.00 .4389 3.0295 1.000 -7.688 8.566
4.00 1.00 4.5143* 1.4385 .013 .655 8.373
2.00 6.0833* 1.6677 .002 1.609 10.557
3.00 -.4389 3.0295 1.000 -8.566 7.688
The difference between means is significant for the threshold α < 0.05.
Table 6. The regression coefficient (SMM) for the group of girls with MID.
Table 6. The regression coefficient (SMM) for the group of girls with MID.
Model R R2 R2 Adjusted Estimated Standard Error
1 .431a .185 .145 2.9579
a. Prediction: (Constant), No. of min./week; b-dependent variable; R-the regression coefficient; R2 – regression coefficient squared.
Table 7. Linear regression for SMM in the group of girls MID (ANOVAa).
Table 7. Linear regression for SMM in the group of girls MID (ANOVAa).
Model Sum of Squares df Mean Squares F Sign. thresh.
1 Regression 39.825 1 39.825 4.552 .045b
Residual value 174.978 20 8.749
Total 214.804 21
a. Dependent variable: SMM; b. Prediction: (Constant), No. of min./week; F-approximation used to calculate significance; df-degree of freedom for Fisher distribution.
Table 8. Linear regression for BMI in the group of girls MID (ANOVAa).
Table 8. Linear regression for BMI in the group of girls MID (ANOVAa).
Model Sum of Squares df Mean Squares F Sign. thresh.
1 Regression 150.807 1 150.807 8.709 .008b
Residual value 346.324 20 17.316
Total 497.131 21
a. Dependent variable: BMI; b. Prediction: (Constant), No. of min./week; F-approximation used to calculate significance; df-degree of freedom for Fisher distribution.
Table 9. The regression coefficient (BMI) for the group of girls with MID.
Table 9. The regression coefficient (BMI) for the group of girls with MID.
Model R R2 R2 Adjusted Estimated Standard Error
1 .551a .303 .269 4.1613
a. Prediction: (Constant), No. of min./week; b-dependent variable; R-the regression coefficient; R2 – regression coefficient squared.
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