Abstract
Objectives: The aim was to examine the association of potential socioeconomic indicators with obesity and physical fitness components in south Brazilian adolescents with Down syndrome.
Methods: This study comprised a total of 1249 (669 boys) adolescents with Down syndrome aged 10 to 20 with complete baseline data. Socioeconomic indicators were assessed by a proxy-report questionnaire. Body mass index and physical fitness were assessed using a PROES-BR health-related fitness test battery.
Results: Socioeconomic status is not associated with body mass index in adolescents with Down syndrome. In addition, two of five physical fitness variables were associated with groups of family income and paternal education level in boys, while one of five physical fitness variables were associated with groups of paternal and maternal education level in girls.
Conclusion: Our results suggest that socioeconomic indicators are associated with some components of physical fitness in Brazilian adolescents with Down syndrome. These associations depend on the socioeconomic status and physical fitness components in boys and girls.
Keywords: disability, youth, fitness, obesity, socioeconomic status, Down syndrome
Introduction
Obesity is considered a health problem in many parts of the world (World Health Organization 2004). A higher rate of obesity has been associated with lower levels of physical fitness, which in turn has a harmful effect on health later in life (Ortega et al. 2008; Ruiz et al. 2009). Likewise, physical fitness is partially determined by genetic endowment, yet it is altered by environmental factors (Bray et al. 2009). For instance, socioeconomic status plays an important role on health such as fatness and physical fitness in youth population (Bergmann et al. 2011, Freitas et al. 2007, Senese et al. 2009). However, more studies focused on adolescents without disabilities and little is known about adolescents with intellectual disabilities or Down syndrome.
Down syndrome is a genetic disorder caused by the presence of an extra chromosome 21 and an estimated incidence of 1 in 1000 live births (Roizen and Patterson 2003). This syndrome is typically associated with more than 80 clinical characteristics (e.g. congenital heart defects, muscle hypotonicity, growth delays, etc.) that may influence fatness and levels of physical fitness (Bull 2011). Overall, individuals with Down syndrome are more likely to be obese and lower levels of physical fitness than the rest of the community, including people with intellectual disabilities (González-Agüero et al. 2010, Pitetti et al. 2013). Therefore, it is important to identify key determinants of fatness and physical fitness in this population.
The socioeconomic status has been considered as an important factor to identify groups of adolescents without disabilities who are at risk of obesity or low levels of physical fitness (Ortega et al. 2013). In fact, socioeconomic status indicator reflects different aspect of social stratification and is normally indexed by one or a combination of the following indicators: education, occupational position and income (Adler and Newman 2002). Education measures cognitive skills and cultural achievement, which make the individual more receptive to health knowledgement. Occupational position is related to social standing, intellect, and income. Income describes economic benefit such as an access to place of residence, recreation, food, and exercise (Galobardes et al. 2006). Thus, it is important to considered different indicators in order to identify the most vulnerable groups that could be targeted in an intervention.
Thus, it is useful to provide an overall picture of the association of socioeconomic status with fatness and physical fitness. Regarding the relationship between socioeconomic status and fatness in adolescents without disabilities, most of the studies carried out in developed countries reported that adolescents with low socioeconomic status had higher risk of obesity (Jiménez-Pavón et al. 2010, Ortega et al. 2013). However, studies carried out in developing countries like Brazil reported that the highest levels of fatness, the highest socioeconomic status of society (Aitsi-Selmi et al. 2013). For example, Silva et al. (2012) showed that those boys with higher socioeconomic status had higher prevalence of body fat than those of lower socioeconomic status.
Concerning the association between socioeconomic status and physical fitness in adolescents without disabilities, there is a conflict in the directions of their results in developed and in developing countries. Some studies demonstrated that adolescents with lower socioeconomic status (e.g. parental occupation, education, income, and housing) had higher levels of physical fitness (e.g. muscular strength, cardiorespiratory fitness) (Finger et al. 2014, Freitas et al. 2007), others showed that adolescents with higher socioeconomic status had lower levels of physical fitness (Filho et al. 2014). In contrast, some studies reported that adolescents who come from higher socioeconomic status had higher levels of physical fitness (e.g. muscular strength, speed agility performance) (Cleland et al. 2009, Jiménez-Pavón et al. 2010, Ortega et al. 2013). It is important to highlight that both social and cultural contexts are often country-specific. However, as far as we know, the association between socioeconomic status and obesity and physical fitness has not been studied in Brazilian adolescents with Down syndrome. Therefore, the aim of this study was to examine the association between potential socioeconomic indicators, obesity, and physical fitness components in a relatively large sample of south Brazilian adolescents with Down syndrome.
Methods
The data presented were gathered for a study carried out in the south of Brazil. Before the study was conducted, three institutions for people with Down syndrome had been contacted (Association of Parents and Friends of People with Disabilities, APAE) in order to explain the aims of the project and to obtain authorization of the organizations. Associations, federations, foundations, and special education schools for people with intellectual disabilities from the states of Rio Grande du Sol, Santa Catarina, and Paraná were approached. All adolescents could participate if they have a moderate intelligence quotient and no severe physical disabilities that interfere in doing physical activities (e.g. wheelchair users). A total of 1249 adolescents with Down syndrome (669 boys) aged 10 to 20 years participated in this study with completed valid body mass index and physical fitness data. Data collection was carried out in 2008.
Adolescents, parents, or caregivers were informed by letter about the purpose of the study and written informed consent was required. The study protocol was designed and approved by the Ethics Committee of the Federal University of Rio Grande do Sul.
Socioeconomic indicators
Family income
The family income was estimated using a model based on economic criteria for classification of Brazil questionnaire established in 2003 by the Brazilian Association of Research Companies (http://www.abep.org). This questionnaire is based on the material conditions of the family. Parents were asked to complete a questionnaire about the number of televisions, radios, cars, etc. This model defined the family income into seven categories (A1 [richest], A2, B1, B2, C, D, and E [poorest]). To simplify analysis, the family income was grouped into two categories: high–medium (A + B + C) and low (D + E) family income.
Parental education level
Both parents were asked to complete a questionnaire about their education level. The minimum training period in the Brazilian education system was 9 years for primary school, 3 years for secondary school, and 3 years for university training. These categories were categorized as primary and secondary or higher education, respectively.
Body mass index variable
Body mass index
Weight and height of participants were measured without shoes and wearing lightweight clothing. Body mass index was calculated as weight in kilograms divided by height in meters squared (kg/m2). Anthropometric measurements were performed twice and the average value was recorded.
Physical fitness components
Physical fitness was examined using the PROES-BR health-related fitness test battery for youth following the measurement procedures suggested by The Project Esporte Brasil (www.proesp.ufrgs.br). All measurements were guided for two instructors with experiences in intellectual disabilities population in order to help adolescents with Down syndrome when it was indispensable. In addition, instructors used direct and simple oral language as visual example of each test. In this study, physical fitness was assessed by the physical fitness tests described below.
Curl-up test (trunk strength)
Adolescents started in supine position with knees flexed to 90° and with arms crossed over their chest. Adolescents began the trunk flexion movement and returned to the starting position. One complete curl-up counted as one run. Their head did not need to touch the floor in every run in order to complete it. The test was performed once and the number of complete curl-ups in 1 min was recorded.
Medicine ball throw (upper body strength)
Adolescents started in sitting position on the floor with their knees straight, legs together and back fully supported against the wall. Adolescents had to throw the ball as far as possible while keeping their back against the wall. The test was completed twice and the maximum score in kilograms was recorded.
Standing long jump test (lower body strength)
Adolescents had to jump as far as possible from a starting position behind a line standing with feet approximately shoulder’s width apart. The distance was measured from the take-off line to the point where the back of the heel closest to the take-off line landed on the mat. The test was completed twice and the longer distance was recorded in centimeters.
Agility square test (speed agility)
Adolescents had to run as fast as possible from the starting line to the next cone en diagonal direction. Subsequently, they had to run towards the cone to their left and then, run to the cone in diagonal position (across the square). Finally, adolescents had to run toward to the last cone, which is the cone closest to the starting line. The test was performed twice and the fastest time was recorded in seconds. The better the performance, the lower the score, it was multiplied by −1. Hence, a higher score indicates a better motor fitness.
Shuttle run speed test (running speed)
Adolescents were required to run between three parallel lines 20 m apart. They had to run as fast as possible from the starting line to the last line. The test was performed twice and the fastest time was recorded in seconds. The better the performance, the lower the score, which was again multiplied by −1. Hence, a higher score indicates a better motor fitness.
Statistical analysis
Data are presented as mean standard ± deviation. Pearson correlations were used to examine the relationships between body mass index and physical fitness variables in adolescents with Down syndrome adjusting for sex and age. Differences in body mass index and physical fitness according to socioeconomic status (family income and parental education level) groups were assessed by one-way analysis of variance (unadjusted model) and covariance (adjusted model). Body mass index variable was adjusting for age and agility square test and physical fitness variables were adjusting for age and body mass index. We used socioeconomic status variables as fixed factors and body mass index or physical fitness variables as dependent variables.
Data were analyzed using SPSS statistical software (version 20.0, Chicago, IL, USA) for Macintosh. The level of significance was set at 0.05 for all analyses.
Results
Table 1 shows descriptive characteristics of the study sample. Overall, boys were less heavy and taller than girls (p < 0.05) and performed a better physical fitness level than girls (p < 0.05).
Table 1. Descriptive characteristics of study sample.
| All | Boys | Girls | Pfor sex | |
|---|---|---|---|---|
| n | 1249 | 669 | 580 | |
| Age (years) | 14.9 ± 3.1 | 14.9 ± 3.1 | 14.9 ± 3.2 | 0.966 |
| Weight (kg) | 50.7 ± 12.5 | 48.8 ± 11.4 | 52.9 ± 13.3 | <0.001 |
| Height (cm) | 138.9 ± 10.7 | 141.3 ± 10.9 | 136.1 ± 9.6 | <0.001 |
| Body mass index (kg/m2) | 26.1 ± 5.2 | 24.2 ± 3.7 | 28.3 ± 5.8 | <0.001 |
| Curl-up (abdominal strength) | 13.23 ± 5.6 | 14.4 ± 5.9 | 11.8 ± 5.0 | <0.001 |
| Medicine ball throw (cm/kg) | 174.5 ± 67.7 | 192.4 ± 66.6 | 153.9 ± 62.9 | <0.001 |
| Standing long jump (cm) | 69.5 ± 28.1 | 75.3 ± 30.5 | 62.9 ± 23.5 | <0.001 |
| Agility square test (sec x−1) | −10.6 ± 1.8 | −10.2 ± 1.7 | −11.1 ± 1.7 | <0.001 |
| Shuttle run speed test (sec x−1) | −6.4 ± 1.4 | −6.2 ± 1.4 | −6.7 ± 1.4 | <0.001 |
Values are mean ± SD.
p < 0.05.
Table 2 shows correlations between body mass index and physical fitness in adolescents with Down syndrome. Body mass index was negatively associated with agility square and shuttle run speed (r−0.611 and −0.566, p < 0.05). Curl-up was associated with medicine ball throw and standing long jump (r = 0.173 and 0.250, p < 0.05). Medicine ball throw was associated with standing long jump and agility square (r = 0.237 and −0.067, p < 0.05), while agility square was associated with shuttle run speed (r = 0.732, p < 0.05).
Table 2. Correlations between body mass index and physical fitness in adolescents with Down syndrome.
| Curl-up | Medicine ball throw | Standing long jump | Agility square test | Shuttle run speed test | |
|---|---|---|---|---|---|
| (abdominal strength) | (cm/kg) | (cm) | (sec x−1) | (sec x−1) | |
| Body mass index (kg/m2) | 0.025 | 0.001 | −0.032 | −0.611** | −0.566** |
| Curl-up (abdominal strength) | – | 0.173** | 0.250** | −0.015 | 0.017 |
| Medicine ball throw (cm/kg) | – | 0.237** | −0.067* | −0.029 | |
| Standing long jump (cm) | – | −0.009 | 0.035 | ||
| Agility square test (sec x−1) | – | 0.732** | |||
| Shuttle run speed test (sec x−1) | – |
Notes: Data were adjusted for sex and age.
p < 0.05;
p < 0.001 denotes statistical significance.
Differences in body mass index and physical fitness according to family income in adolescents with Down syndrome are displayed in Table 3. Boys with higher family income performed a better agility square and shuttle run speed after controlling for age and body mass index (p < 0.05), while there were no significant difference in girls (p < 0.05).
Table 3. Differences in body mass index and physical fitness according to family income in adolescents with Down syndrome.
| Family income | ||||
|---|---|---|---|---|
| Low | High-medium | P1 | P2 | |
| Boys | ||||
| n | 330 | 339 | ||
| Body mass index (kg/m2) | 25.2 ± 3.8 | 23.3 ± 3.5 | <0.001 | 0.987 |
| Curl-up (abdominal strength) | 14.6 ± 5.8 | 14.3 ± 6.0 | 0.548 | 0.125 |
| Medicine ball throw (cm/kg) | 206.7 ± 67.8 | 178.6 ± 62.5 | <0.001 | 0.193 |
| Standing long jump (cm) | 77.3 ± 31.8 | 73.3 ± 29.2 | 0.095 | 0.231 |
| Agility square test (sec x−1) | −10.4 ± 1.7 | −10.0 ± 1.7 | 0.003 | <0.001 |
| Shuttle run speed test (sec x−1) | −6.2 ± 1.3 | −6.2 ± 1.5 | 0.422 | 0.001 |
| Girls | ||||
| n | 289 | 291 | ||
| Body mass index (kg/m2) | 29.6 ± 5.9 | 26.9 ± 5.3 | <0.001 | 0.169 |
| Curl-up (abdominal strength) | 11.8 ± 4.8 | 11.9 ± 5.1 | 0.757 | 0.126 |
| Medicine ball throw (cm/kg) | 170.0 ± 60.4 | 138.0 ± 61.4 | <0.001 | 0.133 |
| Standing long jump (cm) | 64.5 ± 25.8 | 61.3 ± 20.7 | 0.101 | 0.332 |
| Agility square test (sec x−1) | −11.1 ± 1.7 | −11.0 ± 1.7 | 0.541 | 0.881 |
| Shuttle run speed test (sec x−1) | −6.7 ± 1.5 | −6.7 ± 1.3 | 0.904 | 0.605 |
Note: Data are mean ± SD. P1 = unadjusted. P2 = Body mass index was adjusting for age and agility square test; fitness variables were adjusting for age and body mass index.
p < 0.05.
Differences in body mass index and physical fitness according to paternal education level in adolescents with Down syndrome are displayed in Table 4. Boys with a higher paternal education level performed better agility square and shuttle run speed tests (p < 0.05), while girls with a lower paternal education level performed a better medicine ball throw after controlling for age and body mass index (p < 0.05).
Table 4. Differences in body mass index and physical fitness according to paternal education level in adolescents with Down syndrome.
| Paternal education level | ||||
|---|---|---|---|---|
| Primary | Secondary or higher | P1 | P2 | |
| Boys | ||||
| n | 593 | 76 | ||
| Body mass index (kg/m2) | 24.4 ± 3.7 | 22.4 ± 3.6 | <0.001 | 0.615 |
| Curl-up (abdominal strength) | 14.5 ± 5.9 | 14.1 ± 6.0 | 0.574 | 0.534 |
| Medicine ball throw (cm/kg) | 195.7 ± 66.9 | 167.1 ± 59.0 | <0.001 | 0.183 |
| Standing long jump (cm) | 75.8 ± 31.3 | 70.5 ± 23.5 | 0.149 | 0.991 |
| Agility square test (sec x−1) | −10.3 ± 1.7 | −9.7 ± 1.6 | 0.007 | 0.011 |
| Shuttle run speed test (sec x−1) | −6.2 ± 1.4 | −6.0 ± 1.4 | 0.308 | 0.003 |
| Girls | ||||
| n | 504 | 76 | ||
| Body mass index (kg/m2) | 28.6 ± 6.0 | 26.7 ± 4.3 | 0.008 | 0.526 |
| Curl-up (abdominal strength) | 11.9 ± 4.5 | 11.8 ± 5.2 | 0.953 | 0.589 |
| Medicine ball throw (cm/kg) | 158.5 ± 63.4 | 123.6 ± 50.3 | <0.001 | 0.023 |
| Standing long jump (cm) | 63.0 ± 23.6 | 62.3 ± 22.7 | 0.813 | 0.245 |
| Agility square test (sec x−1) | −11.1 ± 1.7 | −11.1 ± 1.7 | 0.769 | 0.601 |
| Shuttle run speed test (sec x−1) | −6.7 ± 1.4 | −6.8 ± 1.4 | 0.591 | 0.981 |
Note: Data are mean ± SD. P1 = unadjusted. P2 = Body mass index was adjusting for age and agility square test; fitness variables were adjusting for age and body mass index.
p < 0.05.
Differences in body mass index and physical fitness according to maternal education level in adolescents with Down syndrome are displayed in Table 5. Boys with lower maternal education level performed a better shuttle run speed tests (p < 0.05) and girls with lower maternal education level performed a better medicine throw ball after controlling for body mass index (p < 0.05).
Table 5. Differences in body mass index and physical fitness according to maternal education level in adolescents with Down syndrome.
| Maternal education level | ||||
|---|---|---|---|---|
| Primary | Secondary or higher | P1 | P2 | |
| Boys | ||||
| n | 411 | 116 | ||
| Body mass index (kg/m2) | 24.2 ± 3.9 | 24.7 ± 3.8 | 0.173 | 0.847 |
| Curl-up (abdominal strength) | 14.7 ± 5.8 | 14.1 ± 6.3 | 0.380 | 0.242 |
| Medicine ball throw (cm/kg) | 196.7 ± 65.9 | 193.1 ± 66.4 | 0.594 | 0.287 |
| Standing long jump (cm) | 76.6 ± 30.8 | 76.0 ± 32.9 | 0.850 | 0.653 |
| Agility square test (sec x−1) | −10.1 ± 1.7 | −10.4 ± 1.7 | 0.079 | 0.263 |
| Shuttle run speed test (sec x−1) | −6.1 ± 1.3 | −6.3 ± 1.5 | 0.065 | 0.024 |
| Girls | ||||
| n | 361 | 95 | ||
| Body mass index (kg/m2) | 28.5 ± 5.6 | 28.2 ± 6.2 | 0.668 | 0.171 |
| Curl-up (abdominal strength) | 12.0 ± 4.9 | 11.6 ± 5.5 | 0.556 | 0.767 |
| Medicine ball throw (cm/kg) | 157.0 ± 61.5 | 132.1 ± 63.4 | 0.001 | 0.026 |
| Standing long jump (cm) | 64.7 ± 23.4 | 60.2 ± 20.1 | 0.079 | 0.282 |
| Agility square test (sec x−1) | −11.0 ± 1.7 | −11.1 ± 1.9 | 0.868 | 0.472 |
| Shuttle run speed test (sec x−1) | −6.7 ± 1.5 | −6.8 ± 1.3 | 0.505 | 0.693 |
Note: Data are mean ± SD. P1 = unadjusted. P2 = Body mass index was adjusting for age and agility square test; fitness variables were adjusting for age and body mass index.
p <0.05.
Discussion
The results of the present study suggest that socioeconomic status is not associated with body mass index in adolescents with Down syndrome and the association of socioeconomic status with physical fitness differ depends on which socioeconomic status variable is analyzed in boys and girls. Overall, 2 of 5 physical fitness variables were associated with groups of family income and paternal education level in boys, while 1 of 5 physical fitness variables were associated with groups of paternal and maternal education level in girls. The present findings extend current scientific knowledge by suggesting that the role of socioeconomic status, as measured by three different indicators, differs between boys and girls and a higher socioeconomic status is associated with better physical fitness in boys but not in girls Brazilian adolescents with Down syndrome.
The present study examined the association between socioeconomic status and obesity. Our data suggest that socioeconomic status was not associated with body mass index in adolescents with Down syndrome. Analysis was also performed using body mass index z-score (Bertapelli et al. 2017) and the results were virtually similar (data not showed). By comparing these results with those adolescents without disabilities from southern Brazilian region, Bozza et al. (2014) found that % of body fat and abdominal obesity was not associated with socioeconomic status established by the Brazilian Association of Research Companies in adolescents aged 11 to 19. In line with these results, Silva et al. (2011) found that maternal schooling was not associated with peripheral and central adiposity using skinfold thickness in adolescents aged 14 to 18. In contrast, others of the Brazilian studies have suggested that higher socioeconomic status (e.g. income, household) was associated with a higher level of adiposity (e.g. body mass index, skinfold thickness) at this age (Aitsi-Selmi et al. 2013, Bergmann et al. 2011, Monteiro et al. 2007, Silva et al. 2012).
These trends observed in developing countries do not parallel the literature on adolescents without disabilities in developed countries. For example, Ortega et al. (2013) reported that a cohort of Estonian and Swedish youth with a high socioeconomic status (e.g. maternal education) showed a reduce risk of remaining fat after six-year follow-up. In Spanish boys, Jiménez-Pavón et al. (2010) also reported that higher maternal education was associated with a lower level of body fat. In France, Lamotte et al. (2013) reported that those adolescents’ boys aged 12 to 17 with a high socioeconomic status measures with the Family Affluences Scale questionnaire have less total and central fat. A possible explanation for the absence of this association in adolescents with Down syndrome may be due that both adolescents of lower and higher socioeconomic status exhibit higher levels of obesity. In addition, when comparing results of this study with those conducted in Brazil and other countries, differences in the association between socioeconomic status and fatness can be found. This may be due to the use of different methods to assess socioeconomic status and body composition.
Another finding in the present study was the diverging association observed between socioeconomic status and physical fitness in terms of sex. Our data suggest that boys with a higher family income and paternal education level performed better agility square and shuttle run speed tests, whereas no association was observed in girls. A lower maternal education level in boys and girls was also associated with better shuttle run speed and medicine throw ball in adolescents with Down syndrome, respectively. This differing association between socioeconomic status and physical fitness was also found in adolescents without disabilities in developing and developed countries, and the finding are so contradictory. Future research needs to determinate this relationship.
In Brazilian studies, Filho et al. (2014) found that the head of the household’s schooling was inversely associated with cardiorespiratory fitness in boys. Similar results were also found in other study with Brazilian adolescents without disabilities (Guedes et al. 2012). In contrast, Jiménez-Pavón et al. (2010) observed that speed agility and cardiorespiratory fitness were not associated with the parental education level or professional levels in Spanish adolescent boys, but these fitness components were positively associated with paternal education or parental professional in adolescent girls. Bohr et al. (2013) also found significant differences for girls but not for boys in American adolescents. The implication that socioeconomic status is related to physical fitness in boys but not in girls in our study is in disagreement with other studies carried out in general Brazilian population. It may be possible that Down syndrome boys with a higher socioeconomic status engage in more organized physical activities than girls since adolescents who come from low-income families often have limited access to the resources needed that support physical activity and physical fitness (Stalsberg and Pedersen 2010). However, these results are difficult to generalize across countries, since socio-economic statuses have different meanings and associations in different cultures and societies. In addition, the socioeconomic association may change over time and vary within and between countries. This reflects the growth a mirror of condition in society.
Moreover, intervention studies to promote health-related physical fitness should consider the socioeconomic statuses in Down syndrome population. A longitudinal study in youth without disabilities showed that improvements in socioeconomic position, indicated by educational level, are associated with increased physical fitness components from childhood to adulthood (Cleland et al. 2009). A key potential strategy could be provided to parents with better health information in order to improve physical fitness and reduce health risk. Therefore, the results of the present study are relevant when considering specific prevention efforts concerning physical fitness of certain groups in Down syndrome population.
One of the several strengths of the present study is the relatively large and heterogeneous sample of adolescents with Down syndrome. Another strength is the use of three indicators for socioeconomic status and the complete assessment of physical fitness components. However, this study has several limitations. The cross-sectional design does not allow for drawing causal inference upon the findings of this study. Although the body mass index was predominantly been used in previous literature, there is a lack of variables for measuring fatness in the present study. Finally, the adolescents’ motivation in the physical fitness test can skew the final performance, so assistants strongly encouraged the adolescents before and during the test in order to avoid this.
Conclusion
In conclusion, this is, to our knowledge, the first study conducted in south Brazilian adolescents with Down syndrome with the aim of analyzing the socioeconomic status and health-related factors. The results suggest that socioeconomic indicators are associated with some components of physical fitness in Brazilian adolescents with Down syndrome and this association depends on the socioeconomic status and physical fitness components. In addition, the results of this research can be useful in order to manage and promote reduce fatness and increase physical fitness in this populations. These findings highlight the need for public health strategies that promote equal environmental opportunities to remove some socioeconomic differences in physical fitness in this target population.
Acknowledgments
We gratefully acknowledge the participation and collaboration of all adolescents with Down syndrome and their families in this study. RIG received a scholarship from the Santander Bank for a brief stay in the Federal University of Pelotas, Brazil. None of the authors had any conflicts of interest.
References
- Adler, N. E. and Newman, K.. 2002. Socioeconomic disparities in health: pathways and policies. Health Affairs, 21, 60–76. 10.1377/hlthaff.21.2.60 [DOI] [PubMed] [Google Scholar]
- Aitsi-Selmi, A., Batty, G. D., Barbieri, M. A., Silva, A. A., Cardoso, V. C., Goldani, M. Z., Marmot, M. G. and Bettiol, H.. 2013. Childhood socioeconomic position, adult socioeconomic position and social mobility in relation to markers of adiposity in early adulthood: Evidence of differential effects by gender in the 1978/79 Ribeirao Preto cohort study. International Journal of Obesity, 37, 439–447. doi: 10.1038/ijo.2012.64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bergmann, M. L., Bergmann, G. G., Halpern, R., Rech, R. R., Constanzi, C. B. and Alli, L. R.. 2011. Associated factors to total cholesterol: School based study in southern Brazil. Arquivos Brasileiros de Cardiologia, 97, 17–25. 10.1590/S0066-782X2011005000065 [DOI] [PubMed] [Google Scholar]
- Bertapelli, F., Machado, M. R., Roso, R. D. and Guerra-Júnior, G.. 2017. Body mass index reference charts for individuals with Down syndrome aged 2–18 years. Journal de Pediatria, 93, 94–99. doi: 10.1016/j.jped.2016.04.005. [DOI] [PubMed] [Google Scholar]
- Bohr, A. D., Brown, D. D., Laurson, K. R., Smith, P. J. and Bass, R. W.. 2013. Relationship between socioeconomic status and physical fitness in junior high school students. Journal of School Health, 83, 542–547. doi: 10.1111/josh.12063. [DOI] [PubMed] [Google Scholar]
- Bozza, R., de Campos, W., Bacil, E. D. and Barbosa,-Filho, V. C., Hardt, J. M. and da Silva, P. M.. 2014. Sociodemographic and behavioral factors associated with body adiposity in adolescents. Revista Paulista de Pediatria, 32, 241–246. doi: 10.1590/0103-0582201432315. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bray, M. S., Hagberg, J. M., Pérusse, L., Rankinen, T., Roth, S. M., Wolfarth, B. and Bouchard, C.. 2009. The human gene map for performance and health-related fitness phenotypes: the 2006–2007 update. Medicine & Science in Sports & Exercise, 41, 35–73. 10.1249/MSS.0b013e3181844179 [DOI] [PubMed] [Google Scholar]
- Bull, M. J. and Committee on Genetics. 2011. Health supervision for children with Down syndrome. Pediatrics, 128, 393–406. https://www.ncbi.nlm.nih.gov/pubmed/21788214 [DOI] [PubMed] [Google Scholar]
- Cleland, V. J., Ball, K., Magnussen, C., Dwyer, T. and Venn, A.. 2009. Socioeconomic position and the tracking of physical activity and cardiorespiratory fitness from childhood to adulthood. American Journal of Epidemiology, 170, 1069–1077. doi: 10.1093/aje/kwp271. [DOI] [PubMed] [Google Scholar]
- Filho, V. C., da Silva Lopes, A., Bozza, R., Rech, C. R. and de Campos, W.. 2014. Correlates of cardiorespiratory and muscular fitness among Brazilian adolescents. American Journal of Health Behavior, 38, 42–52. doi: 10.5993/AJHB.38.1.5. [DOI] [PubMed] [Google Scholar]
- Finger, J. D., Mensink, G. B., Banzer, W., Lampert, T. and Tylleskär, T.. 2014. Physical activity, aerobic fitness and parental socio-economic position among adolescents: the German Health Interview and Examination Survey for Children and Adolescents 2003–2006 (KiGGS). International Journal of Behavioral Nutrition and Physical Activity, 11, 1–10. doi: 10.1186/1479-5868-11-43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Freitas, D., Maia, J., Beunen, G., Claessens, A., Thomis, M., Marques, A., Crespo, M. and Lefevre, J.. 2007. Socio-economic status, growth, physical activity and fitness: the Madeira growth study. Annals of Human Biology , 34, 107–122. 10.1080/03014460601080983 [DOI] [PubMed] [Google Scholar]
- Galobardes, B., Shaw, M., Lawlor, D. A., Lynch, J. W. and Davey Smith, G.. 2006. Indicators of socioeconomic position (Part 1). Journal of Epidemiology & Community Health, 60, 7–12. 10.1136/jech.2004.023531 [DOI] [PMC free article] [PubMed] [Google Scholar]
- González-Agüero, A., Vicente-Rodríguez, G., Moreno, L. A., Guerra-Balic, M., Ara, I. and Casajús, J. A.. 2010. Health-related physical fitness in children and adolescents with Down syndrome and response to training. Scandinavian Journal of Medicine & Science in Sports, 20, 716–724. doi: 10.1111/j.1600-0838.2010.01120.x. [DOI] [PubMed] [Google Scholar]
- Guedes, D. P., Neto, J., Lopes, V. P. and Silva, A. J.. 2012. Health-related physical fitness is associated with selected sociodemographic and behavioral factors in Brazilian school children. Journal of Physical Activity & Health, 9, 473–480. 10.1123/jpah.9.4.473 [DOI] [PubMed] [Google Scholar]
- Jiménez-Pavón, D., Ortega, F. B., Ruiz, J. R., Chillón, P., Castillo, R., Artero, E. G., Martinez-Gómez, D., et al. 2010. Influence of socioeconomic factors on fitness and fatness in Spanish adolescents: the AVENA study. International Journal of Pediatric Obesity, 5, 467–473. doi: 10.3109/17477160903576093. [DOI] [PubMed] [Google Scholar]
- Lamotte, C., Iliescu, C., Beghin, L., Salleron, J., Gonzalez-Gross, M.,Marcos, A., De Henauw, S., et al.. 2013. Association of socioeconomic status, truncal fat and sICAM-1 with carotid intima-media thickness in adolescents: the HELENA study. Atherosclerosis, 228, 460–465. doi: 10.1016/j.atherosclerosis.2013.03.007. [DOI] [PubMed] [Google Scholar]
- Monteiro, C. A., Conde, W. L. and Popkin, B. M.. 2007. Income-specific trends in obesity in Brazil: 1975–2003. American Journal of Public Health, 97, 1808–1812. 10.2105/AJPH.2006.099630 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ortega, F. B., Ruiz, J. R., Castillo, M. J. and Sjöström, M.. 2008. Physical fitness in childhood and adolescence: a powerful marker of health. International Journal of Obesity, 32, 1–11. 10.1038/sj.ijo.0803774 [DOI] [PubMed] [Google Scholar]
- Ortega, F. B., Ruiz, J. R., Labayen, I., Hurtig-Wennlöf, A., Harro, J.,Kwak, L., Oja L., et al. 2013. Role of socio-cultural factors on changes in fitness and adiposity in youth: a 6-year follow-up study. Nutrition, Metabolism and Cardiovascular Diseases, 23, 883–890. doi: 10.1016/j.numecd.2012.05.008. [DOI] [PubMed] [Google Scholar]
- Pitetti, K., Baynard, T. and Agiovlasitis, S.. 2013. Children and adolescents with Down syndrome, physical fitness and physical activity. Journal of Sport & Health Science, 2, 47–57. 10.1016/j.jshs.2012.10.004 [DOI] [Google Scholar]
- Roizen, N. J. and Patterson, D.. 2003. Down’s syndrome. The Lancet, 361, 1281–1289. 10.1016/S0140-6736(03)12987-X [DOI] [PubMed] [Google Scholar]
- Ruiz, J. R., Castro-Pinero, J., Artero, E. G., Ortega, F. B., Sjostrom, M., Suni, J. and Castillo, M. J.. 2009. Predictive validity of health-related fitness in youth: a systematic review. British Journal of Sports Medicine, 43, 909–923. doi: 10.1136/bjsm.2008.056499. [DOI] [PubMed] [Google Scholar]
- Senese, L. C., Almeida, N. D., Fath, A. K., Smith, B. T. and Loucks, E. B.. 2009. Associations between childhood socioeconomic position and adulthood obesity. Epidemiologic Reviews, 31, 21–51. doi: 10.1093/epirev/mxp006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Silva, D. A., Berria, J., Grigollo, L. R. and Petroski, E. L.. 2012. Prevalence and factors associated with high body fat in adolescents from a region of Brazil. Journal of Community Health , 37, 791–798. doi: 10.1007/s10900-011-9512-1. [DOI] [PubMed] [Google Scholar]
- Silva, D. A., Pelegrini, A., de Lima e Silva, J. M. F., Petroski, E. L. and Petroski, E. L.. 2011. Epidemiology of whole body, peripheral, and central adiposity in adolescents from a Brazilian state capital. European Journal of Pediatrics , 170, 1541–1550. doi: 10.1007/s00431-011-1460-3. [DOI] [PubMed] [Google Scholar]
- Stalsberg, R. and Pedersen, A. V.. 2010. Effects of socioeconomic status on the physical activity in adolescents: a systematic review of the evidence. Scandinavian Journal of Medicine & Science in Sports, 20, 368–383. doi: 10.1111/j.1600-0838.2009.01047.x. [DOI] [PubMed] [Google Scholar]
- World Health Organization . 2004. World health organization global strategy on diet, physical activity and health. Geneva: WHO. [Google Scholar]