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Article

The Incidence of Body Posture Abnormalities in Relation to the Segmental Body Composition in Early School-Aged Children

by
Michalina Ziętek
,
Mariusz Machniak
,
Dorota Wójtowicz
and
Agnieszka Chwałczyńska
*
Faculty of Physiotherapy, Wroclaw University of Health and Sport Sciences, Al. Paderewskiego 35, 51-612 Wroclaw, Poland
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(17), 10815; https://doi.org/10.3390/ijerph191710815
Submission received: 13 July 2022 / Revised: 22 August 2022 / Accepted: 27 August 2022 / Published: 30 August 2022
(This article belongs to the Special Issue Physical Education and Health at School Age)
Review Reports Versions Notes

Abstract

:
Children are exposed to multiple factors that contribute to an increase in body mass and the development of posture defects. The aim of the study is to assess the relationship between the segmental distribution of fat mass and muscle mass and the incidence of body posture abnormalities in early school-aged children. A total of 190 children aged 7–9 were included in the research project. The examined children were divided according to age (class level) into three groups. Height, weight and body composition, BMI, and body posture were determined. Thoracic and lumbar spine abnormalities occurred most frequently in the examined children (7–95%, 8–92%, 9–89.5%). During the assessment of the segmental body composition, the lowest fat–fat-free index was found in the trunk. The number of abnormalities of the cervical spine, pelvis, and lower extremities increases with age. The number of abnormalities of the thoracic and lumbar spine, as well as of upper extremities and the pectoral girdle decreases with age. Body posture abnormalities are correlated with body composition and in particular with the fat mass percentage. The segmental body com-position analyzer can be used to screen for posture defects.

1. Introduction

The commencement of school education, accompanied by a lifestyle change, increases the risk for posture defects and abnormal body mass [1,2]. Many researchers point out that one in five children aged 7–10 has excess body mass, which may result from the prenatal stage and from the lifestyle during preschool years [3,4,5,6,7,8].
The content of fat mass (FM) and muscle mass (MM) in the human body depends on age and sex. In school-aged children, the extremities become longer, while the proportion between the head and the rest of the body starts to resemble that of adults. During that stage, the amount and distribution of FM begin to differ based on the sex (female—15–25%, male—13–20%); at the same time, the individual’s anatomical proportions change and the final body type takes shape. After the end of puberty, the weight gain rate slows down and body proportion stabilizes [1,9,10]. Many authors emphasize that the weight cut and the BMI calculated on its basis are not sufficient values to assess the occurrence of abnormal body weight. More and more often, the authors consider the importance of fat mass in the development of overweight and obesity [11,12,13,14,15,16]. That is why it is so important to use bioelectrical impedance analysis (BIA) to assess the content of fat and fat-free components [1,3,16,17,18,19].
Posture defects are common and can be observed in children of all ages. The periods of rapid growth coincide with the change in the lifestyle of a child aged 5–7, and the second period is during adolescence (aged 12–16) [1,7]. One of the risk factors for poor posture is excess body weight. However, the authors most often show this dependence using the BMI index; however, they do not associate it with muscle mass, which is possible only in the case of the use of a segment body rock, which allows the assessment of the distribution of muscle mass and related to the occurrence of abnormalities and compensation in body posture [20,21,22,23,24,25,26]. Children with excess FM suffer from defects in the spine, of the shoulder girdle, and weakening of the abdominal muscles or lower limbs. The body’s center of gravity is displaced forward, which causes the lumbar lordosis and the anteversion of the pelvis to increase [27].
One of the key issues related to the progression of those abnormalities is the lack of monitoring of the incidence of abnormal body posture depending on body composition. When the child is diagnosed with a posture defect, an appropriate therapeutic intervention is commenced, one of the few opportunities to monitor the development of a child in early school age is to visit a doctor in case of infection. This is why it is so critical to introduce a simple screening method that would allow the assessment of body posture in children. An attempt was made to evaluate the application of the Fat-Fat-Free Index (FFF) to assess body posture.
The aim of the study was to assess the relationship between the segmental distribution of FM and MM, estimated using the electrical bioimpedance method (BIA), and the incidence of body posture abnormalities in early school-aged children. The authors attempted to answer the question of whether the use of a simple, segmental assessment of body mass could help identify the children who require observation for possible posture defects.
A child’s body posture is a very important element for proper development. At the same time, in early school age, when a child starts learning, his possibilities of taking up physical activity change. The child reduces his/her activity in favor of a sedentary lifestyle at school and, while doing homework at home, gets a schoolbag—a backpack with an additional load (books, notebooks) and at the same time reduces the frequency of medical checks. That is why it is so important to provide easy, generally available screening methods showing the possibility of posture abnormalities. The method we propose is to identify people with abnormalities in the distribution of muscle mass, which, if established over time, may result in postural defects. Owing to the simultaneous application of body composition and posture tests, it is possible to determine the correlation between these values. At the same time, knowing the relationship between the level of FM and FFM and body posture, it is possible to develop and introduce an early intervention aimed at correcting abnormalities.

2. Materials and Methods

The study was approved by the Bioethics Committee of the Wroclaw University of Health and Sport Sciences in Poland (approval no. 12/2019). The study was carried out in accordance with the tenets of the Declaration of Helsinki.
About 314 children aged 7–9 in the Lower Silesian Voivodeship, whose parents gave written consent to their children’s participation in a non-invasive assessment of body composition and posture and who did not follow an extended sports curriculum at school, were included in the research project. The participants had not been previously diagnosed with posture defects that required treatment. The study took into consideration the contraindications to the bioimpedance method (the presence of a pacemaker, metal implants, or active neoplastic condition).
About 190 children (89 girls (Ijerph 19 10815 i001) and 101 boys (Ijerph 19 10815 i002)) aged 7–9 (mean 8.15 ± 0.59), with a mean height of 131.1 ± 6.7 cm, body mass of 29.7 ± 6.8 kg, BMI of 17.1 ± 2.9 kg/m2 and BMI centile of 54.8 ± 2.7 were included in the research project. The BMI centile was determined taking into account the age and sex of the examined child (percentile grids for age and gender were used, developed on the basis of the OLA and OLAF 2010 project for Polish children) [28,29]. The research was conducted at the beginning of the school year. The examined children were divided according to age (class level) into three groups. Group 7 consists of children attending the first grade (average age 7.3 ± 0.25 years, min-max—6.4–7.4 years), who start school, and change their way of functioning from active preschoolers to sedentary students. Group 8 are children attending the second grade (average age 7.9 ± 0.26 years, min-max—7.6–8.4 years), who have been at school for at least a year, during which they participated in physical activity classes as part of their education early school once a week. Group 9 consists of children attending the third grade (average age 8.9 ± 0.27 years, min-max—8.6–9.4 years), who stay at school for at least two years and during this period participated in physical activity classes as part of early childhood education three times a week. The groups differ not only in age but also in the level of education. The participants’ height was measured using SECA 213 stadiometer and rounded to the nearest 0.1 cm. Body mass and composition were examined using the 8-electrode body composition analyzer—MC-780 by TANITA (BIA Technology Multifrequency—5 kHz/50 kHz/250 kHz, it has certificates allowing its use for medical use, meets the NAWI CLASS III standards for scales used for medical measurements) [30]. The analyzer has the EU certificate CE0122. In the field of medical devices, it meets the requirements of the MDD 93/42/EEC Directive (Medical Device Directive). Examinations based on the BIA were used to estimate the general and segmental fat (fat mass [%] and [kg] FM%, FM) and fat-free components (fat-free mass in [kg] FFM, muscle mass in [kg] MM). FM and FFM were used to calculate the general and segmental fat–fat-free (FFF) index (right leg—RL FFF, left leg—LL FFF, right arm—RA FFF, left arm—LA FFF, trunk—TR FFF) [1,3,31,32,33].
Body posture was assessed in accordance with the physiotherapeutic examination, taking into consideration the habitual body posture (without informing the participant that they were being assessed at the time). The assessment included the position of the head in relation to the body (anteversion, forward head posture, head turned or tilted to the right or left), the position of the shoulders and scapulas, the structure of the chest, natural curves of the spine, symmetry of waist angles, the position of the pelvis, position of lower extremities (valgus/varus knees, hyperextended knees, foot arch, valgus/varus feet). The assessment was conducted by a pediatric physiotherapy specialist with long professional experience, in accordance with the methodology of the physiotherapeutic body posture assessment. The assessment takes into account the position of the spine, symmetry of the position of the head, shoulders, shoulder blades, waist angles, and correct positioning of the lower limbs-hips, knees the feet.

Statistical Analysis

Descriptive statistics were used to develop the research: mean value for a given value, standard deviation, and group size. The Shapiro–Wilk test showed that the distribution of the examined features was not consistent with the Gaussian curve, which influenced the selection of non-parametric tests for groups of different sizes. The groups were compared using the non-parametric the Kruskal—Wallis test. For multi-group comparisons, the Pearson chi-square test was used in the case of numerical data. The relationship between the values of BMI, FFF, FM%, and the occurrence of body posture abnormalities was investigated using Spearman’s rank correlation. The level of statistical significance was set at p < 0.05.

3. Results

This physiological increase in body mass and height, resulting from the ontogenetic development, was observed in the sample group. The individual age groups of the participants did not differ in terms of the mean value of the BMI centile. The percentage of overweight and obese children in the sample group was found to increase with age. There was an increase in the percentage of children with high amounts of FM (Table 1).
An increased amount of FM% in the upper and lower extremities, exceeding the normal values, was observed in the study groups. At the same time, the amount of FM% in the upper extremities decreases with age, resulting in an increase in MM and a decrease in RA FFF and LA FFF indexes. Statistically significant differences in MM between age groups were observed. Nine-year-old children exhibited a statistically significant increase in the amount of FM in the trunk area (Table 2).
The incidence of abnormalities in the CS, the pelvis, and the lower extremities increases with age, as evidenced by the increase in the percentage of children diagnosed with such defects at the ages of 7–8 and 9. On the other hand, the incidence of abnormalities of the thoracic (ThS) and lumbar spine (LS), the upper extremities, and the pectoral girdle decreases with age. No statistically significant differences in the incidence of abnormalities of the cervical (CS), ThS and LS, the pelvis, and the lower extremities were found between the age groups. On the other hand, the incidence of abnormalities of the upper extremities and the pectoral girdle is statistically significantly different in individual age groups (Table 3).
The analysis of the 8-year-old participants revealed that the higher the fat mass, the lower the incidence of abnormalities of the CS, which indicates an inversely proportional, statistically significant correlation between these two values. In children aged 7 and 9, there is a correlation between the increase in the fat mass and the incidence of abnormalities of the thoracic and lumbar spine. The examination of individual body segments shows that the increase in fat mass in the right and left lower extremities and in the trunk correlates with the incidence of abnormalities of the T/LS. Furthermore, in this age group, it can be observed that the increase in muscle mass in the right lower extremity and in the right and left upper extremities correlates with the incidence of abnormalities of the thoracic and lumbar spine. The correlation between the general and segmental body composition and the incidence of body posture abnormalities in individual age groups is presented in Table 4.
The analysis of the correlation between the fat–fat-free index and the incidence of abnormalities in individual body segments revealed that in 8-year-old children there is a statistically significant correlation between the fat–fat-free index and the absence of abnormalities of the cervical spine. Correlations between the fat–fat-free index and the incidence of abnormalities of the thoracic and lumbar spine occur in 9-year-old children. In this age group, the increase in the fat–fat-free index in the right and left lower extremities and in the trunk correlates with the incidence of abnormalities of the thoracic and lumbar spine. No statistically significant correlations between the FFF index and the incidence of body posture abnormalities were found in 7-year-old children. The correlation between the FFF index and the incidence of body posture abnormalities in individual age groups is presented in Table 5.

4. Discussion

Human development is a continuous process. As ontogenetic development progresses, the composition of the human body changes and the period of school education determines whether the child will suffer from abnormalities in their adult life. Research has shown that body mass, BMI, and height increase with age [1,34,35,36,37,38,39,40]. Body posture and mass issues are not caused only by the commencement of school education, but also by the reduced frequency of medical check-ups. By guidelines and the vaccination schedule [41], at the early stages of their life, the child is seen by their pediatrician relatively frequently, i.e., at the age of 6 weeks and 2, 3, 4, 5, 6, 7, 13–15 and 16–18 months. Afterward, check-ups take place at the age of 6, 12–13, 14, and 19. This is why it is so crucial to adopt an alternative method for assessing body posture, which could be used during screening tests conducted at school. The introduction of children’s body posture and mass biomonitoring to schools will allow more comprehensive control of those abnormalities and the implementation of therapeutic and educational programs [42]. Periods of growth are intertwined with periods of MM development, posture stabilization, and acquisition of new skills. Healthy development requires a balance between those stages. As mentioned by numerous authors, in the period before the commencement of school education a child’s height increases dynamically, also causing them to gain body mass. However, this period overlaps the beginning of education [1,3,7,9,10]. An active preschooler turns into a student who leads a sedentary lifestyle and spends a lot of time at school, at a desk, in front of a computer monitor, instead of engaging in outdoor PA. All of those factors contribute to the emergence of overweight and obesity, which in turn cause serious posture defects in children [20,21,22,23,24,25,26,33]. The conducted body composition studies allowed for the assessment of the symmetry of the distribution of fat and lean mass in early school-age children. In the study group, the problem of excess body weight increased with age. The highest number of overweight and obese children was found in the group of 9-year-old children, although this group was the smallest. The problem of excess body weight in the study group is not only a BMI above the 85th percentile for age and gender but also a high level of FM%. Owing to the use of an eight-electrode body composition analyzer, it has been observed that the greatest fatness in children occurs in the upper limbs. At the same time, with age and the level of school education, the level of FM% in the upper limbs decreases by an average of 12%, while in the lower limbs it remains at a similar level. On the other hand, the 20% increase in body fatness during the study period is disturbing.
Most studies on the effects of weight on posture focus on abnormalities in the foot. Gijon-Nogueron et al. indicate no correlation between body weight and BMI index and abnormalities in the foot structure [21]. Similar results were obtained by Gonçalves de Carvalho et al., who showed a relationship between foot abnormalities and gender and did not observe any relationship between BMI and body weight [20]. The relationship between abnormalities within the spine and body weight was demonstrated in their studies by Labecka et al. [23]. Similar results of the relationship between body weight and, in fact, its components, especially FM, were observed in the studies presented in the study. It should be emphasized that the problem of abnormalities within the spine appears more and more often, which was observed in the study group, and this confirms the tendency observed by Mrozkowiak et al. In their work assessing the occurrence of abnormalities in body posture in the 1950s and at the beginning of the 21st century [26].
It should be noted that the number of children who exhibit body posture abnormalities in the CS area increases with age. In the sample group, despite the decrease in the percentage of FM in the upper extremities, its distribution remained asymmetrical—irrespective of the children’s age, higher MM was observed on the right-hand side as compared to the left-hand side. This asymmetry causes an uneven position of the shoulders, head tilt to the right and head rotation, usually with the face turned to the right. The studies conducted by Wyszyńska et al. demonstrated that children with excess FM% exhibited differences in the left shoulder angle in the coronal plane. A similar correlation can be observed in the position of the inferior angle of the scapula. In the sagittal plane, children with excess FM% exhibit differences in the depth of the interior angles of the scapulas. In this group of children, the twisted left scapula was observed. In the coronal plane, children with high MM were characterized by the smallest difference in the inclination of the inferior angles of the scapulas [20]. The studies conducted by Bogucka and Głębocka show that both overweight and underweight have a profound effect on the child’s body posture. In the sagittal plane, underweight children suffer from an abnormal position of the shoulders and winged scapula. In the coronal plane, underweight boys were found to have more prominent scapular winging [40]. Studies carried out by Rusek et al. demonstrated that the excess FM% and MM contribute to the development of posture defects in the area of the pectoral girdle and the pelvis in the coronal plane [6]. The progression of those posture defects is caused by the sedentary lifestyle and insufficient physical activity (PA); in addition, abnormalities of the CS result from the use of mobile phones and computers.
In the present study, individual body areas were examined separately, by the segmental assessment carried out using the body composition analyzer. Unlike the majority of researchers, the authors were able to divide posture defects into those affecting the CS, upper extremities and the pectoral girdle, the ThS and LS, and the pelvis with the lower extremities. This division revealed that the posture defects affecting the ThS and LS are the most common. Although the fat-free mass in the trunk area increases with age, thus improving the stabilization of the ThS and Ls, which in turn causes the decrease in the number of children diagnosed with posture defects in this area, that decrease is minor and this abnormality continues to pose a significant problem. The greatest issue in this body area is the decreased abdominal muscle tone, which contributes to the deepening of lumbar lordosis, the shallowing of ThS kyphosis, scapular winging, and asymmetry of waist angles, possibly indicating scoliosis. Hypotonic abdominal muscles may result from the statistically significant increase in the FM% observed in 9-year-old children as compared to the younger participants of the study. In the sample group, the increase in TR FM may be associated with a relatively low level of PA as part of the school curriculum, which causes not only an increased number of children suffering from body posture abnormalities in the ThS and Ls but also an increased number of overweight and obese pupils other authors have also demonstrated in their studies that one of the most common defects in overweight and obese children is the abnormal position of the abdomen [34,43].
The incidence of abnormalities of the ThS and lumbar section in the sample group also correlates with the increase in FM% in the lower extremities. Increased FM% in the lower extremities, accompanied by decreased MM, causes an asymmetrical position of the pelvis, which primarily contributes to the development of scoliosis of the LS and compensation in the ThS. Similar results were reported by Wilczyński et al. who demonstrated that children with the lowest MM were found to have the inferior angles of the scapulas positioned at various heights. On the other hand, children with the highest FM% were characterized by an abnormal position of the inferior angles of the scapulas and the shoulder line but were diagnosed with fewer abnormalities of the ThS and LS [44].
The present study revealed that the incidence of abnormalities of the pelvis and lower extremities increased with age. Many authors confirm that the highest number of posture defects emerge at the early school age [45,46,47,48,49]. Similar correlations between the body mass and the incidence of abnormalities of the pelvis were observed by researchers in children aged 10–15, which may indicate that the abnormalities progress not only as the BMI increases but also as the individual ages [50]. Studies carried out by Rusek et al. demonstrated that also excess FM% and MM contribute to the development of posture defects of the pelvis in the coronal plane [6]. The most common abnormalities of the lower extremities among overweight and obese children are the valgus knees and flat feet [31,40]. The cause of the high incidence of valgus knees in obese individuals is the excessive load placed on the growth plates located in the distal part of the thigh and the proximal part of the lower leg [34].
Research has revealed that the MM and FM% play a crucial role in the maintenance of a healthy body posture in early school-aged children. Unfortunately, the number of children diagnosed with overweight, obesity, and abnormal body posture continues to increase. Posture defects lead to many consequences for the human body. This is why it is crucial to educate both the children and their parents on the factors that adversely impact body posture and body mass. Another factor that contributes to the development of posture defects is school backpacks which are too heavy and not adjusted to the individual child’s body [51,52,53].
The assessment of body posture using the body composition analyzer serves as a screening test. During the measurement, the individual adopts their habitual posture and does not strive to achieve a healthy one, because—in their view—it is not the purpose of the examination. The assessment of the asymmetry of body composition allows the identification of those individuals who should undergo further, a more detailed examination of body posture. At the same time, any disproportions of fat-free mass observed during the assessment should be interpreted as the need for greater focus on the development of MM on the side characterized by increased fat mass. The use of a segmental body composition analyzer is a quick, non-invasive, relatively inexpensive, and—first and foremost—simple method for identifying individuals at risk of developing posture defects.
The bioimpedance method can be complemented by the use of FFF, which is based on the ratio of FM to FFM. The present study demonstrated a statistically significant, albeit relatively low inverse correlation between the value of the FFF index and the incidence of abnormal body posture. Those correlations were observed primarily in the group of 8-year-old children for CS and in the group of 9-year-old children for ThS and LS. The existence of such correlations indicates that one of the elements of the emergence of posture defects may be the abnormal ratio of FM to FFM; however, much more extensive research is required to confirm this conclusion.

5. Conclusions

In the study group, the number of children with abnormal body weight increased. At the same time, the number of children with a high value of fat mass increases statistically significantly. Distal distribution of fat mass was observed in the examined children, regardless of age. The incidence of posture abnormalities correlates with abnormalities in the body composition of the children who participated in the study, in particular with the percentage of body fat. The use of a segmental body composition analyzer can serve as a screening test for postural defects.
In order to be able to conduct screening for abnormal body mass and posture, annual tests of younger schoolchildren in the field of segmental body composition supplemented with the fat-free index (FFF) should be introduced as mandatory. The use of the FFF index is simple and allows for early diagnosis of disorders of the FM to FFM ratio, which may be the cause of posture abnormalities.
Further research and the creation of reference values for children are required to take full advantage of the potential of the FFF index.

Author Contributions

Conceptualization, M.Z., D.W., M.M. and A.C.; methodology, M.Z., D.W. and A.C.; software, M.Z., M.M. and A.C.; validation, M.Z., M.M. and A.C.; formal analysis, M.Z. and A.C.; investigation, M.Z., M.M., D.W. and A.C.; resources, A.C.; data curation, M.Z. and A.C.; writing—original draft preparation, M.Z. and M.M.; writing—review and editing, D.W. and A.C.; visualization, M.M. and A.C.; supervision, A.C.; project administration, A.C.; funding acquisition, D.W. and A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and the research project received approval from the Senate’s Bioethical Committee at the Academy of Physical Education in Wroclaw (no.12/2019; date of ethical approval 15 March 2019). Signed informed consent forms were obtained from all participants.

Informed Consent Statement

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

Data Availability Statement

The research results presented are part of a large ongoing study which has not yet been completed. If you are interested in specific data, please contact the first author—Agnieszka Chwałczyńska ([email protected]).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chwałczyńska, A. Fat-Fat Free Age-Related Index as a New Tool for Body Mass Assessment; Studia I Monografie, No. 124; AWF: Wroclaw, Poland, 2017; ISBN 978-83-64354-22-9. ISSN 0239-6009. [Google Scholar]
  2. Alves Junior, C.A.; Mocellin, M.C.; Gonçalves, E.C.A.; Silva, D.A.; Trindade, E.B. Anthropometric Indicators as Body Fat Discriminators in Children and Adolescents: A Systematic Review and Meta-Analysis. Adv Nutr. 2017, 8, 718–727. [Google Scholar] [CrossRef] [PubMed]
  3. Chwałczyńska, A.; Rutkowski, T.; Jędrzejewski, G.; Wójtowicz, D.; Sobiech, K.A. The Comparison of the Body Composition of Children at the Early School Age from Urban and Rural Area in Southwestern Poland. Biomed. Res. Int. 2018, 2018, 9694615. [Google Scholar] [CrossRef]
  4. Majcher, A.; Czerwonogrodzka-Senczyna, A.; Kądziela, K.; Rumińska, M.; Pyrżak, B. Development of obesity from childhood to adolescents. Pediatric Endocrinol. Diabetes Metab. 2021, 27, 70–75. [Google Scholar] [CrossRef] [PubMed]
  5. Wojtków, M.; Szkoda-Poliszuk, K.; Szotek, S. Influence of body posture on foot load distribution in young school-age children. Acta Bioeng. Biomech. 2018, 20, 101–107. [Google Scholar] [PubMed]
  6. Rusek, W.; Baran, J.; Leszczak, J.; Adamczyk, M.; Weres, A.; Baran, R.; Inglot, G.; Pop, T. The Influence of Body Mass Composition on the Postural Characterization of School-Age Children and Adolescents. Biomed Res. Int. 2018, 2018, 9459014. [Google Scholar] [CrossRef]
  7. Rusek, W.; Leszczak, J.; Baran, J.; Adamczyk, M.; Weres, A.; Baran, R.; Inglot, G.; Czenczek-Lewandowska, E.; Porada, S.; Pop, T. Role of body mass category in the development of faulty postures in school-age children from a rural area in south-eastern Poland: A cross-sectional study. BMJ Open. 2019, 9, e030610. [Google Scholar] [CrossRef]
  8. Baran, J.; Weres, A.; Czenczek-Lewandowska, E.; Leszczak, J.; Kalandyk-Osinko, K.; Łuszczki, E.; Sobek, G.; Mazur, A. Excessive Gestational Weight Gain: Long-Term Consequences for the Child. J. Clin. Med. 2020, 9, 3795. [Google Scholar] [CrossRef]
  9. Rusek, W.; Baran, J.; Leszczak, J.; Adamczyk, M.; Baran, R.; Weres, A.; Inglot, G.; Czenczek-Lewandowska, E.; Pop, T. Changes in Children’s Body Composition and Posture during Puberty Growth. Children 2021, 8, 288. [Google Scholar] [CrossRef]
  10. Bredella, M.A. Sex Differences in Body Composition. Adv. Exp. Med. Biol. 2017, 1043, 9–27. [Google Scholar] [CrossRef] [PubMed]
  11. Bosy-Westphal, A.; Müller, M.J. Diagnosis of obesity based on body composition-associated health risks-Time for a change in paradigm. Obes. Rev. 2021, 22 (Suppl. 2), e13190. [Google Scholar] [CrossRef]
  12. Chung, S. Body composition analysis and references in children: Clinical usefulness and limitations. Eur. J. Clin. Nutr. 2019, 73, 236–242. [Google Scholar] [CrossRef] [PubMed]
  13. Müller, M.J.; Braun, W.; Pourhassan, M.; Geisler, C.; Bosy-Westphal, A. Application of standards and models in body composition analysis. Proc. Nutr. Soc. 2016, 75, 181–187. [Google Scholar] [CrossRef] [PubMed]
  14. Xiao, P.; Cheng, H.; Yan, Y.; Liu, J.; Zhao, X.; Li, H.; Mi, J. High BMI with Adequate Lean Mass Is Not Associated with Cardiometabolic Risk Factors in Children and Adolescents. J. Nutr. 2021, 151, 1213–1221. [Google Scholar] [CrossRef]
  15. Lycett, K.; Kerr, J.A. A Helpful Reminder of BMI’s Nuances but Little Support for the “Obesity Paradox”. J. Nutr. 2021, 151, 1051–1052. [Google Scholar] [CrossRef]
  16. Weber, D.R.; Leonard, M.B.; Shults, J.; Zemel, B.S. A comparison of fat and lean body mass index to BMI for the identification of metabolic syndrome in children and adolescents. J. Clin. Endocrinol. Metab. 2014, 99, 3208–3216. [Google Scholar] [CrossRef]
  17. Liu, P.; Ma, F.; Lou, H.; Liu, Y. The utility of fat mass index vs. body mass index and percentage of body fat in the screening of metabolic syndrome. BMC Public Health 2013, 13, 629. [Google Scholar] [CrossRef] [PubMed]
  18. Eun, Y.; Lee, S.N.; Song, S.W.; Kim, H.N.; Kim, S.H.; Lee, Y.A.; Kang, S.G.; Rho, J.S.; Yoo, K.D. Fat-to-muscle Ratio: A New Indicator for Coronary Artery Disease in Healthy Adults. Int. J. Med. Sci. 2021, 18, 3738–3743. [Google Scholar] [CrossRef]
  19. Ramírez-Vélez, R.; Carrillo, H.A.; Correa-Bautista, J.E.; Schmidt-RioValle, J.; González-Jiménez, E.; Correa-Rodríguez, M.; González-Ruíz, K.; García-Hermoso, A. Fat-to-Muscle Ratio: A New Anthropometric Indicator as a Screening Tool for Metabolic Syndrome in Young Colombian People. Nutrients 2018, 10, 1027. [Google Scholar] [CrossRef]
  20. Gonçalves de Carvalho, B.K.; Penha, P.J.; Ramos, N.L.J.P.; Andrade, R.M.; Ribeiro, A.P.; João, S.M.A. Age, Sex, Body Mass Index, and Laterality in the Foot Posture of Adolescents: A Cross Sectional Study. J. Manip. Physiol. Ther. 2020, 43, 744–752. [Google Scholar] [CrossRef]
  21. Gijon-Nogueron, G.; Montes-Alguacil, J.; Martinez-Nova, A.; Alfageme-Garcia, P.; Cervera-Marin, J.A.; Morales-Asencio, J.M. Overweight, obesity and foot posture in children: A cross-sectional study. J. Paediatr. Child Health 2017, 53, 33–37. [Google Scholar] [CrossRef]
  22. Jimenez-Cebrian, A.M.; Morente-Bernal, M.F.; Román-Bravo, P.D.; Saucedo-Badía, J.F.; Alonso-Ríos, J.A.; Montiel-Luque, A. Influence of Age, Sex, and Anthropometric Determinants on the Foot Posture Index in a Pediatric Population. J. Am. Podiatr. Med. Assoc. 2017, 107, 124–129. [Google Scholar] [CrossRef]
  23. Labecka, M.K.; Górniak, K.; Lichota, M. Somatic determinants of changes in selected body posture parameters in younger school-age children. PeerJ 2021, 9, e10821. [Google Scholar] [CrossRef] [PubMed]
  24. Lizis, P.; Walaszek, R. Evaluation of relations between body posture parameters with somatic features and motor abilities of boys aged 14 years. Ann. Agric. Environ. Med. 2014, 21, 810–814. [Google Scholar] [CrossRef] [PubMed]
  25. Drzał-Grabiec, J.; Szczepanowska-Wołowiec, B. Weight-height ratios and parameters of body posture in 7-9-year-olds with particular posture types. Ortop. Traumatol. Rehabil. 2011, 13, 591–600. [Google Scholar] [CrossRef] [PubMed]
  26. Mrozkowiak, M.; Walicka-Cupryś, K.; Magoń, G. Comparison of Spinal Curvatures in the Sagittal Plane, as Well as Body Height and Mass in Polish Children and Adolescents Examined in the Late 1950s and in the Early 2000s. Med. Sci. Monit. 2018, 24, 4489–4500. [Google Scholar] [CrossRef]
  27. Wyszyńska, J.; Podgórska-Bednarz, J.; Drzał-Grabiec, J.; Rachwał, M.; Baran, J.; Czenczek-Lewandowska, E.; Leszczak, J.; Mazur, A. Analysis of Relationship between the Body Mass Composition and Physical Activity with Body Posture in Children. Biomed. Res. Int. 2016, 2016, 1851670. [Google Scholar] [CrossRef] [PubMed]
  28. Kułaga, Z.; Różdżyńska, A.; Palczewska, I.; Grajda, A.; Gurzkowska, B.; Napieralska, E.; Litwin, M.; Grupa Badaczy OLAF. Siatki centylowe wysokości, masy ciała i wskaźnika masy ciała dzieci i młodzieży w Polsce—Wyniki badania OLAF. Stand. Med./Pediatr. 2010, 7, 690–700. [Google Scholar]
  29. Calculator According to OLAF and OLA. Available online: http://olaf.czd.pl/index.php?option=com_content&view=article&id=103:kalkulator (accessed on 10 August 2022).
  30. DIRECTIVE 2014/31/EU OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 26 February 2014. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32014L0031 (accessed on 10 August 2022).
  31. Rutkowski, T.; Sobiech, K.A.; Chwałczyńska, A. The effect of 10 weeks of karate training on the weight body composition and FFF index of children at the early school age with normal weight and overweight. Arch. Budo. 2020, 16, 211–219. [Google Scholar]
  32. Rutkowski, T.; Sobiech, K.A.; Chwałczyńska, A. The effect of karate training on changes in physical fitness in school-age children with normal and abnormal body weight. Physiother. Quart. 2019, 27, 28–33. [Google Scholar] [CrossRef]
  33. Rutkowski, T.; Chwałczyńska, A.; Cieślik, B.; Sobiech, K.A. Fat-free index as a new tool to assess changes in body composition (Wskaźnik tłuszczowo-beztłuszczowy jako nowe narzędzie do oceny zmian składu ciała). Poszerzamy Horyz. Monografia. T 2017, 5, 383–391. (In Polish) [Google Scholar]
  34. Maciałczyk-Paprocka, K.; Stawińska-Witoszyńska, B.; Kotwicki, T.; Sowińska, A.; Krzyżaniak, A.; Walkowiak, J.; Krzywińska-Wiewiorowska, M. Prevalence of incorrect body posture in children and adolescents with overweight and obesity. Eur. J. Pediatr. 2017, 176, 563–572. [Google Scholar] [CrossRef] [PubMed]
  35. Beyerlein, A.; Toschke, A.M.; Schaffrath Rosario, A.; von Kries, R. Risk factors for obesity: Further evidence for stronger effects on overweight children and adolescents compared to normal-weight subjects. PLoS ONE 2011, 6, e15739. [Google Scholar] [CrossRef] [PubMed]
  36. Dietz, W.H. Overweight in childhood and adolescence. N. Engl. J. Med. 2004, 350, 855–857. [Google Scholar] [CrossRef] [PubMed]
  37. Skinner, A.C.; Ravanbakht, S.N.; Skelton, J.A.; Perrin, E.M.; Armstrong, S.C. Prevalence of Obesity and Severe Obesity in US Children, 1999–2016. Pediatrics 2018, 141, e20173459. [Google Scholar] [CrossRef] [PubMed]
  38. Dereń, K.; Wyszyńska, J.; Nyankovskyy, S.; Nyankovska, O.; Łuszczki, E.; Sobolewski, M.; Mazur, A. Assessment of the Impact of Parental BMI on the Incidence of Overweight and Obesity in Children from Ukraine. J. Clin. Med. 2020, 9, 1060. [Google Scholar] [CrossRef] [PubMed]
  39. Desalew, A.; Mandesh, A.; Semahegn, A. Childhood overweight, obesity and associated factors among primary school children in dire dawa, eastern Ethiopia; a cross-sectional study. BMC Obes. 2017, 4, 20. [Google Scholar] [CrossRef]
  40. Pop, T.L.; Maniu, D.; Rajka, D.; Lazea, C.; Cismaru, G.; Ştef, A.; Căinap, S.S. Prevalence of Underweight, Overweight and Obesity in School-Aged Children in the Urban Area of the Northwestern Part of Romania. Int. J. Environ. Res. Public Health 2021, 18, 5176. [Google Scholar] [CrossRef]
  41. Łubkowska, W.; Mroczek, B. Assessment of body posture of boys aged 7–15 in relations to the body mass index–BMI. J. Educ. Health Sport 2017, 7, 371–380. [Google Scholar]
  42. Announcement of the Chief Sanitary Inspector on the 2022 Immunization Program: Vaccination Calendar. Available online: https://szczepienia.pzh.gov.pl/kalendarz-szczepien-2022-2/ (accessed on 25 April 2022).
  43. Bogucka, A.; Głębocka, A. Body posture of 9–12-year-old children with different relative body weight expressed by the BMI index (Postawa ciała 9–12-letnich dzieci o zróżnicowanej względnej masie ciała wyrażonej wskaźnikiem BMI). Phys. Act. Health 2017, 12, 11–17. (In Polish) [Google Scholar]
  44. Wilczyński, J.; Lipińska-Stańczak, M.; Wilczyński, I. Body Posture Defects and Body Composition in School-Age Children. Children 2020, 7, 204. [Google Scholar] [CrossRef]
  45. Hrycyna, M.; Kołakowski, Ł. Assessment of body posture of children aged 7–9 years. Phys. Act. Health 2018, 13, 15–20. [Google Scholar]
  46. Wojna, D.; Anwajler, J.; Hawrylak, A.; Barczyk, K. Assessment of body posture in younger schoolchildren. Fizjoterapia 2010, 18, 27–39. [Google Scholar] [CrossRef]
  47. da Rosa, B.N.; Furlanetto, T.; Noll, M.; Sedrez, J.A.; Schmit, E.F.D.; Candotti, C.T. 4-year longitudinal study of the assessment of body posture, back pain, postural and life habits of schoolchildren. Motricidade 2017, 13, 3–12. [Google Scholar] [CrossRef]
  48. Rosa, K.; Muszkieta, R.; Zukow, W.; Napierała, M.; Cieślicka, M. The incidence of posture defects in children from grades 1–3 of Primary School (Częstość występowania wad postawy u dzieci z klas I-III Szkoły Podstawowej). J. Health Sci. 2013, 3, 107–136. (In Polish) [Google Scholar]
  49. Hagner, W.; Bąk, D.; Hagner-Derengowska, M. Changes in body posture in children between the 10th and 13th years of age. Pol. Ann. Med. 2011, 18, 76–81. [Google Scholar] [CrossRef]
  50. Sztandera, P.; Szczepankowska-Wołowiec, B.; Kotela, I. The evaluation of the influence of the body mass index on body posture parameters and selected parameters of the dynamic feet analysis. J. Educ. Health Sport 2019, 9, 520–531. [Google Scholar] [CrossRef]
  51. Brzęk, A.; Dworrak, T.; Strauss, M.; Sanchis-Gomar, F.; Sabbah, I.; Dworrak, B.; Leischik, R. The weight of pupils’ schoolbags in early school age and its influence on body posture. BMC Musculoskelet Disord. 2017, 18, 117. [Google Scholar] [CrossRef] [Green Version]
  52. Barbosa, J.P.; Marques, M.C.; Neiva, H.P.; Esteves, D.; Alonso-Martínez, A.M.; Izquierdo, M.; Ramirez-Campillo, R.; Alvarez, C.; Marinho, D.A. Effects of Backpacks on Ground Reaction Forces in Children of Different Ages When Walking, Running, and Jumping. Int. J. Environ. Res. Public Health 2019, 16, 5154. [Google Scholar] [CrossRef]
  53. Zmyślna, A.; Żurawski, A.Ł.; Śliwiński, G.; Śliwiński, Z.W.; Kiebzak, W.P. Assessment of Body Posture of Children With Chest Pain. Front. Pediatr. 2021, 9, 704087. [Google Scholar] [CrossRef]
Table
Table 1. Anthropometric data of the participants by age group.
Table 1. Anthropometric data of the participants by age group.
7 N = 58
Mean ± SD		8 N = 112
Mean ± SD		9 N = 20
Mean ± SD		7 vs. 87 vs. 98 vs. 9
HEIGHT [cm]126.47 ± 5.19129.47 ± 5.97136.15 ± 5.680.1590.0000.000
WEIGHT [kg]26.50 ± 4.6028.08 ± 5.7934.21 ± 7.351.0000.0000.000
BMI [kg/m2]16.46 ± 1.9816.60 ± 2.2918.43 ± 3.861.0000.1010.002
BMI centile53.43 ± 29.5251.58 ± 28.5061.84 ± 27.971.0000.6870.076
Percentage number of children by BMI centile in individual age groups
[%]		Underweight
BMI < 5 percentile		210Pearson’s chi-squared
0.782
Normal body mass
5 percentile < BMI < 85 percentile 		847870
Overweight
85 percentile < BMI < 95 percentile		91420
Obesity BMI > 95 percentile5710
Percentage number of children according to the level of FM% in individual age groups
[%]		Low
♀ < 15%
♂ < 13%		0.03.68.80.069
Good
♀ 15–25%
♂ 13–20%		66.759.840.3
High
♀ > 25%
♂ > 20%		33.336.650.9
Table
Table 2. General and segmental body composition of the participants with the identification of the FFF index for individual age groups.
Table 2. General and segmental body composition of the participants with the identification of the FFF index for individual age groups.
7 N = 58
Mean ± SD		8 N = 112
Mean ± SD		9 N = 20
Mean ± SD		7 vs. 87 vs. 98 vs. 9
BODY FM%21.74 ± 3.7721.28 ± 4.6423.78 ± 8.201.0001.0000.176
MM19.74 ± 2.9120.90 ± 3.5324.31 ± 3.640.7890.0000.000
FFF0.280 ± 0.0620.274 ± 0.0770.330 ± 0.1731.0001.0000.173
RIGHT LEGFM%29.33 ± 3.6228.67 ± 4.0929.23 ± 7.551.0001.0001.000
MM3.01 ± 0.583.28 ± 0.784.31 ± 0.920.5320.0000.000
RLFFF0.417 ± 0.0740.408 ± 0.0790.433 ± 0.1891.0001.0001.000
LEFT LEGFM%29.67 ± 3.6129.09 ± 4.2729.87 ± 7.351.0001.0001.000
MM2.94 ± 0.583.17 ± 0.784.18 ± 1.000.8370.0000.000
LLFFF0.425 ± 0.0700.417 ± 0.0840.444 ± 0.1771.0001.0001.000
RIGHT ARMFM%33.01 ± 5.6731.40 ± 6.9329.05 ± 10.371.0000.3350.420
MM0.70 ± 0.230.77 ± 0.190.98 ± 0.220.2690.0000.000
RAFFF0.507 ± 0.1360.472 ± 0.1460.445 ± 0.2371.0000.3780.786
LEFT ARMFM%34.16 ± 4.8632.08 ± 6.9630.62 ± 11.600.8490.3231.000
MM0.71 ± 0.160.81 ± 0.201.00 ± 0.220.1890.0000.000
LAFFF0.515 ± 0.1210.487 ± 0.1500.496 ± 0.3221.0000.6871.000
TRUNKFM%15.68 ± 3.9115.25 ± 4.9118.83 ± 8.801.0000.7240.049
MM12.38 ± 1.5812.87 ± 1.7513.84 ± 1.721.0000.0080.002
TRFFF0.189 ± 0.0560.184 ± 0.0710.249 ± 0.1581.0000.7530.053
Table
Table 3. Incidence of body posture abnormalities in individual age groups.
Table 3. Incidence of body posture abnormalities in individual age groups.
7 N = 58
[%]		8 N = 112
[%]		9 N = 20
[%]		Pearson’s Chi-Squared
Cervical spine23.824.135.10.2950
Thoracic and lumbar spine95.292.089.50.6999
Pelvis and lower extremities 66.778.682.50.3223
Upper extremities and pectoral girdle90.575.047.40.0001
Table
Table 4. Correlation between the general and segmental body composition and the incidence of body posture abnormalities in individual age groups.
Table 4. Correlation between the general and segmental body composition and the incidence of body posture abnormalities in individual age groups.
Cervical Spine CSThoracic and Lumbar Spine T/LSPelvis and Lower Extremities Upper Extremities
789789789789
FM%0.056−0.2950.0560.2990.0060.2990.0320.1450.032−0.166−0.123−0.166
MM−0.342−0.018−0.051−0.259−0.1100.214−0.0250.012−0.0130.1880.0030.043
RL FM%0.004−0.2100.0040.330−0.0570.3300.0600.0930.060−0.158−0.009−0.158
RL MM−0.315−0.0130.050−0.334−0.1090.2910.0170.0290.0530.027−0.0650.050
LL FM%0.031−0.2290.0310.271−0.0230.2710.0250.1200.025−0.128−0.025−0.128
LL MM−0.2960.0070.028−0.296−0.1110.2280.0500.0290.0130.027−0.0630.038
RA FM%−0.029−0.360−0.0290.108−0.0010.108−0.0640.103−0.064−0.078−0.126−0.078
RA MM−0.3820.0730.010−0.186−0.0960.3090.1940.1330.0870.108−0.037−0.022
LA FM%−0.008−0.347−0.0080.1220.0100.122−0.0180.133−0.018−0.112−0.146−0.112
LA MM−0.2240.0690.005−0.298−0.0920.313−0.0250.0750.1020.135−0.0460.052
TR FM%0.058−0.2960.0580.3130.0410.3130.0760.1730.076−0.174−0.149−0.174
TR MM−0.314−0.037−0.163−0.240−0.1090.1040.025−0.009−0.0510.1340.0610.049
Table
Table 5. Correlation between the FFF index and the incidence of body posture abnormalities in individual age groups.
Table 5. Correlation between the FFF index and the incidence of body posture abnormalities in individual age groups.
Abnormalities of Cervical Spine CSAbnormalities of Thoracic and Lumbar Spine T/LSAbnormalities of the Pelvis and Lower Extremities Abnormalities of Upper Extremities
789789789789
FFF−0.295−0.29120.05810.18460.00760.29540.10010.14540.0308−0.0536−0.1205−0.1666
RL FFF−0.3877−0.19050.00450.1108−0.04220.3214−0.08340.11340.04350.1875−0.0198−0.1645
LL FFF−0.4249−0.21500.02120.1109−0.02740.25540.00000.1326−0.00560.1608−0.0389−0.1153
RA FFF−0.0927−0.3591−0.01790.1113−0.02300.11650.08380.0119−0.0940−0.1614−0.1133−0.0780
LA FFF−0.3524−0.2775−0.00340.2226−0.01330.08700.30170.0726−0.0253−0.2691−0.1806−0.0792
TR FFF−0.2031−0.29670.06030.25850.04320.31270.23350.17160.0757−0.0804−0.1461−0.1730
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Ziętek, M.; Machniak, M.; Wójtowicz, D.; Chwałczyńska, A. The Incidence of Body Posture Abnormalities in Relation to the Segmental Body Composition in Early School-Aged Children. Int. J. Environ. Res. Public Health 2022, 19, 10815. https://doi.org/10.3390/ijerph191710815

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Ziętek M, Machniak M, Wójtowicz D, Chwałczyńska A. The Incidence of Body Posture Abnormalities in Relation to the Segmental Body Composition in Early School-Aged Children. International Journal of Environmental Research and Public Health. 2022; 19(17):10815. https://doi.org/10.3390/ijerph191710815

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Ziętek, Michalina, Mariusz Machniak, Dorota Wójtowicz, and Agnieszka Chwałczyńska. 2022. "The Incidence of Body Posture Abnormalities in Relation to the Segmental Body Composition in Early School-Aged Children" International Journal of Environmental Research and Public Health 19, no. 17: 10815. https://doi.org/10.3390/ijerph191710815

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