Determinants of physical inactivity among urban adolescents

Abstracts

OBJETIVO: Investigar fatores determinantes da inatividade física entre adolescentes de 15 a 19 anos na cidade do Recife (PE). MÉTODO: O estudo foi caso-controle, envolvendo 597 adolescentes de 15 a 19 anos, estudantes de escolas particulares, selecionadas por conveniência. Os critérios de exclusão foram adolescentes com doenças que interferissem ou impossibilitassem a avaliação antropométrica, que estavam em tratamento medicamentoso ou dietético para sobrepeso ou que haviam modificado sua atividade física nos últimos 30 dias. Eles foram recrutados de acordo com a atividade física, determinada pelo International Physical Activity Questionnaire: casos - inativos (sedentários e insuficientemente ativos); e controles - ativos (ativos e muito ativos). Os adolescentes informaram quantas horas diárias assistiam televisão e usavam computador para identificar o número de horas sedentárias/dia. A antropometria (peso e estatura) dos adolescentes foi aferida pela técnica de Gibson; assim, foi calculado o índice de massa corporal. O peso, a estatura e a escolaridade das mães foram autorreferidos. Os dados foram analisados por análise múltipla de regressão logística, utilizando o programa SPSS, versão 11.5, objetivando controlar variáveis de confusão. RESULTADOS: Adolescentes do sexo feminino tiveram risco cerca de duas vezes maior de serem inativos (odds ratio = 1,94; intervalo de confiança de 95% = 1,35-2,79) em relação àqueles do sexo masculino. Assistir televisão mais de 1 hora/dia foi de maior risco para inatividade física em relação a menos de 1 hora/dia (odds ratio = 1,55; intervalo de confiança de 95% = 1,01-2,39). CONCLUSÃO: Inatividade física em adolescentes foi associada com o sexo feminino e maior tempo diário assistindo televisão.

Atividade física; fatores de risco; sobrepeso; televisão; estudos de casos e controles; adolescente

ORIGINAL ARTICLE

Determinants of physical inactivity among urban adolescents

Bruno Rodrigo da Silva Lippo^I; Itamar Manoel da Silva^II; Claudia Regina Pereira Aca^III; Pedro Israel Cabral de Lira^IV; Gisélia Alves Pontes da Silva^V; Maria Eugênia Farias Almeida Motta^VI

^IMestre, Saúde da Criança e do Adolescente. Professor, Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brazil

^IIGraduando, Educação Física, Universidade Federal de Pernambuco (UFPE), Recife, PE, Brazil

^IIIMestre, Saúde da Criança e do Adolescente. UFPE, Recife, PE, Brazil

^IVDoutor, Medicina. Professor associado, Departamento de Nutrição, UFPE, Recife, PE, Brazil

^VDoutora, Medicina. Professora associada, Departamento Materno Infantil, UFPE, Recife, PE, Brazil

^VIDoutora, Medicina. Professora adjunta, Departamento Materno Infantil, UFPE, Recife, PE, Brazil

ABSTRACT

OBJECTIVE: To investigate determinants of physical inactivity among adolescents aged 15 to 19 years in the city of Recife, northeastern Brazil.

METHOD: This case-control study involved 597 private school students aged 15 to 19 years selected by convenience sampling. Exclusion criteria were adolescents with diseases that interfered with or hindered anthropometric measurements, who were being treated with drugs or diet for excess weight or who had changed their physical activity over the past 30 days. The students were recruited according to physical activity, as determined by the International Physical Activity Questionnaire: cases – inactive (sedentary or insufficiently active); and controls – active (active and very active). The adolescents reported the number of hours per day of television watching and computer use to identify the number of sedentary hours/day. Anthropometry (weight and height) of the adolescents was measured by Gibson’s technique and used to calculate the body mass index. Weight, height and educational level of mothers were self-reported. Data were analyzed by multiple logistic regression, using the SPSS software, version 11.5, in order to control for confounding variables.

RESULTS: Female adolescents were twice as likely to be inactive (odds ratio = 1.94; 95% confidence interval = 1.35-2.79) compared to male adolescents. Watching television for more than 1 hour/day showed increased risk for physical inactivity compared to less than 1 hour/day (odds ratio = 1.55; 95% confidence interval = 1.01-2.39).

CONCLUSION: Physical inactivity among adolescents was associated with females and longer time spent per day watching television.

Keywords: Physical activity, risk factors; overweight, television, case-control studies, adolescents.

Introduction

Physical inactivity reduces morbidity and mortality from chronic degenerative diseases, optimizing an individual’s physical and psychological health and quality of life.¹ It is an important means to increase energy expenditure in order to balance food energy intake and prevent chronic degenerative diseases and their consequences.² Physical activity is a complex phenomenon involving any bodily movement that allows muscle contraction, including daily activities, mobility, personal care, free time (unintentional physical activity), exercise, and sports (intentional physical activity).³

Physical activity has decreased around the world, especially among adolescents, with high rates of physical inactivity observed in studies conducted in the last decade.^4-7 Sedentary habits are established in childhood and adolescence and tend to perpetuate into adulthood, with biological, family and cultural factors involved in physical inactivity.⁸ Adolescents around the world are adopting an increasingly passive lifestyle, with less physical activity and changes in eating habits.⁹ Although studies have shown that factors such as sex, overweight adolescents and mothers, mother’s education, and time spent on sedentary activities are highlighted as some of the determinants of physical inactivity, there is still controversy over this.^6,7,9-15 Furthermore, only a few studies have addressed physical inactivity among Brazilian adolescents.

Therefore, identifying determinants of physical inactivity in adolescents in different populations is critical for the development of programs to promote physical activity according to local needs, which may thus contribute to the reduction of chronic diseases in adults. The objective of this study was to investigate determinants of physical inactivity among private school adolescents aged 15 to 19 years in the city of Recife, northeastern Brazil.

Methods

This is a case-control study involving all adolescents aged 15 to 19 years enrolled in six private schools in the city of Recife, selected by convenience sampling. Exclusion criteria were adolescents with diseases that interfered with or hindered anthropometric measurements (congenital malformation, orthopedic changes, edema), who were being treated with drugs or diet for excess weight/obesity or who had changed their physical activity over the past 30 days. After the interview, we verified whether or not the adolescents showed physical inactivity, according to the International Physical Activity Questionnaire (IPAQ),¹⁶ thus defining the following study groups: cases – inactive adolescents (categorized as sedentary or insufficiently active A and B of IPAQ); and controls – active adolescents (categorized as active and very active of IPAQ).

To estimate sample size, we used the Epi-Info^® software, version 6.04b (CDC, USA). We considered a frequency of 2 or more hours watching television on a weekday of 41% in adolescents without sedentary behavior,¹⁷ a risk of physical inactivity 1.8 higher in adolescents watching television for over 2 hours per day, a ratio of one case to one control, with 80% statistical power and significance level < 5%. The minimum sample size to be studied was 197 cases and 197 controls.

Data were collected by research assistants previously trained to administer the questionnaires and perform anthropometric measurements. Initially, the short version of IPAQ was applied to assess the level of physical activity. To ensure the quality of responses, the questionnaire was applied directly to the adolescents during individual interviews (face to face, as recommended for developing countries). The interview ended with the following questions answered by the adolescents: "On a normal school day, how many hours do you spend watching television?" and "On a normal school day, how many hours do you spend on the computer?," in order to identify the number of sedentary hours/day, adopting a normal school day to avoid recall bias, since regular activities could be a fixed reference to recall these time periods with more reliability of response. The cutoff point adopted was time > 1 hour/day.¹⁸

Anthropometry of the adolescents was measured by Gibson’s technique.¹⁹ The students were weighted using a platform scale (Filizola, Brazil), with maximum capacity of 150 kg and sensitivity of 0.1 kg, and their height was measured with a stadiometer (Professional Gofeka, Brazil), with accuracy of 0.1 cm. With data on weight and height, it was possible to calculate the body mass index (BMI), according to the reference standards by the Centers for Disease Control and Prevention.²⁰ BMI was then categorized as overweight (BMI > 85th percentile for age and sex) and adequate weight (BMI < 85th percentile and > 5th percentile for age and sex).

BMI of mothers was calculated based on the written responses received on mothers’ weight and height, being then categorized, according to the reference standards by the Centers for Disease Control and Prevention,²¹ as overweight (BMI > 25 kg/m²) and adequate weight (BMI < 24.9 kg/m²). Reported maternal educational level was classified as < 8 years and > 9 years of schooling.

To detect variables associated with physical inactivity, data were analyzed by multiple logistic regression to control for confounding variables using the Statistical Package for the Social Sciences (SPSS), version 11.5, for Windows (IBM, USA). The hierarchical model was used for data analysis, with the inclusion of exploratory variables in the following order, provided they obtained a p value < 0.20 in the univariate analysis (chi-square test): model 1 – adolescent’s biological variables (sex and BMI); model 2 – mother’s variables (education and BMI); model 3 – cultural variables (time spent watching television and using the computer). Variables that remained significant at a level of 20% were maintained and included in the adjustment of the subsequent model. Baseline category to estimate adjusted and unadjusted odds ratio (OR) was defined as that with less risk for physical inactivity. For acceptance of the final model of physical inactivity, we used 95% confidence interval (95%CI) of the OR and a significance level of 5%.

This study was approved by the Research Ethics Committee of the Center for Health Sciences of Universidade Federal de Pernambuco, Brazil. The adolescents and their parents or legal guardians signed the written consent form upon agreeing to participate in this study.

Results

Of all adolescents participating in the study (n = 597), 50.6% (302/597) were male. Regarding age, 45.1% (269/597) were 15 years old; 34.5% (206/597) were 16 years old; 16.1% (96/597) were 17 years old; 3.7% (22/597) were 18 years old; and 0.7% (4/597) were 19 years old. Physical inactivity was detected in 35.2% (210/597) of adolescents, more frequently among female adolescents (63.3%; 133/210), with adequate weight (75.7%; 159/210), who watched television (73.3%; 154/210) and used the computer (55.2%; 116/210) less than 1 hour/day, whose mothers had 9 years or more of schooling (52%; 105/210), and who were not overweight (56.3%; 112/210). According to the univariate analysis, female sex was the only determinant of physical inactivity (OR = 2.23; 95%CI 1.58-3.15).

Sex and overweight adolescents were included as variables in the multiple logistic regression model 1. In model 2, adolescent’s sex and mother’s education and excess weight were included; the variable "overweight adolescent" was not used to adjust this model due to a p value = 0.66 in the previous model, being then removed from the analysis. In model 3 (final model), adolescent’s sex, mother’s education and excess weight, time spent watching television and using the computer were included as variables. The variables associated with physical inactivity among adolescents were female sex and watching television for over 1 hour per day.

Female adolescents were twice as likely to be inactive (OR = 1.94; 95%CI 1.35-2.79) compared to male adolescents (Table 1). Watching television for more than 1 hour/day was not associated with physical inactivity in the univariate analysis (p = 0.06), but was statistically significant in the multivariate analysis (OR = 1.55; 95%CI 1.01-2.39) (Table 1). There was no statistically significant association with overweight adolescent and mother’s education and excess weight.

Discussion

The results of this study indicate that physical inactivity is more common among female adolescents with the habit of watching television.

Studies have shown that female adolescents are less active than male adolescents.^6,7,22,23 The factors responsible for most physical inactivity in females have not yet been fully elucidated in the literature. Female adolescents have reported internal barriers (engagement in technology-related activities) and external barriers (family influence), which contribute to physical inactivity, emphasizing the preference to perform individual activities with lower energy expenditure.²⁴ Encouraging physical activities of greater interest, combined with family support and information on the importance of this practice to health, seems to guarantee an increase in physical activity among girls.^24,25

The relationship between excess weight and physical inactivity demonstrates that overweight people have more difficulty in performing physical activities, thus reducing their motivation to practice exercises and establishing obesity as one of its determinants.^10,14,26 The study showed no relationship between physical inactivity and excess weight, probably because most (75.2%) adolescents had adequate weight. However, some authors have reported that physical inactivity may result from excess weight, not only because of impaired mobility, but also due to emotional factors related to perceived competence to perform planned physical activities and dissatisfaction with excess weight, which favors sedentary behaviors.^{8,11,12,23,25,27}

Although not detected in this sample, other studies found lower maternal educational level and excess weight to be associated with physical inactivity.^9,27,28 In general, lower educational level and low income are associated with higher rates of physical inactivity and reflect the lack of information on the benefits of physical activity to health, as well as the lack of suitable environments (infrastructure and safety) to practice exercises^9,29 Improved levels of physical activity are related to families with higher educational level, who understand the benefits of exercise, are more active and act as a social support, encouraging their children to practice exercises.^8,9,23 Overweight mothers who are physically inactive may negatively affect the decision of adolescents about physical activity.^9,30,31 Although the family can influence the adoption of healthy behaviors, it is worth noting that many adolescents tend to dismiss such attitudes as a way of asserting their autonomy, becoming physically inactive, regardless of family habits.²⁴

Time spent watching television has been positively associated with physical inactivity, which is consistent with our findings.^6,9,24,32 The interrelationship between sedentary behaviors and physical inactivity is complex.²³ Sedentary behaviors are likely to consume time that might otherwise be spent on physical activity.³³ However, increasing physical activity does not interfere with time spent by adolescents on sedentary activities (television watching and computer use), confirming that specific measures to reduce time spent on sedentary behaviors should be developed.¹³

This study has some limitations. Objective assessment of physical activity (accelerometer, pedometer) is more accurate than using a questionnaire, but costs increase and individual behaviors can change during measurements.² However, IPAQ is a validated questionnaire that assesses total physical activity rather than simply assessing activities performed during free time. The use of self-reported weight of mothers can affect BMI real value, with a tendency to underestimate it; however, self-reported data are commonly used in epidemiological studies due to the convenience and low cost.³⁴

Our study found that female adolescents are at greater risk for physical inactivity, in addition to spending more time watching television. Health professionals and families should encourage adolescents to incorporate physical activity into their daily life and observe the influence of media on adolescents’ attitudes, which may be encouraging the adoption of sedentary behaviors in daily activities.

References

• 1. Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA. 1995;273:402-7.
• 2. Caspersen CJ, Pereira MA, Curran KM. Changes in physical activity patterns in the United States, by sex and cross-sectional age. Med Sci Sports Exerc. 2000;32:1601-9.
• 3. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health related research. Public Health Rep. 1985;100:126-31.
• 4. Tammelin T, Ekelund U, Remes J, Nayha S. Physical activity and sedentary behaviors among Finnish youth. Med Sci Sports Exerc. 2007;39:1067-74.
• 5. Teixeira e Seabra AF, Maia JA, Mendonça DM, Thomis M, Caspersen CJ, Fulton JE. Age and sex differences in physical activity of Portuguese adolescents. Med Sci Sports Exerc. 2008;40:65-70.
• 6. Ceschini FL, Andrade DR, Oliveira LC, Araújo Júnior JF, Matsudo VK. Prevalence of physical inactivity and associated factors among high school students from state's public schools. J Pediatr (Rio J). 2009;85:301-6.
• 7. Rivera IR, Silva MA, Silva RD, Oliveira BA, Carvalho AC. Physical inactivity, TV-watching hours and body composition in children and adolescents. Arq Bras Cardiol. 2010;95:159-65.
• 8. Nowicka P, Flodmark CE. Physical activity-key issues in treatment of childhood obesity. Acta Pćdiatr Suppl. 2007;96:39-45.
• 9. Trang NH, Hong TK, Dibley MJ, Sibbritt DW. Factors associated with physical inactivity in adolescents in Ho Chi Minh City, Vietnam. Med Sci Sports Exerc. 2009;41:1374-83.
• 10. Alves JG, Siqueira PP, Figueiroa JN. Overweight and physical inactivity in children living in favelas in the metropolitan region of Recife, Brazil. J Pediatr (Rio J). 2009;85:67-71.
• 11. Metcalf BS, Hosking J, Jeffery AN, Voss LD, Henley W, Wilkin TJ. Fatness leads to inactivity, but inactivity does not lead to fatness: a longitudinal study in children (EarlyBird 45). Arch Dis Child. Epub 2010 Jun 23.
• 12. Kwon S, Janz KF, Burns TL, Levy SM. Effects of adiposity on physical activity in childhood: Iowa Bone Development Study. Med Sci Sports Exerc. Epub 2010 Jul 7.
• 13. Fernandes RA, Júnior IF, Cardoso JR, Vaz Ronque ER, Loch MR, de Oliveira AR. Association between regular participation in sports and leisure time behaviors in Brazilian adolescents: a cross-sectional study. BMC Public Health. 2008;8:329.
• 14. Moraes AC, Fernandes CA, Elias RG, Nakashima AT, Reichert FF, Falcão MC. Prevalence of physical inactivity and associated factors in adolescents. Rev Assoc Med Bras. 2009;55:523-8.
• 15. Ball K, Cleland VJ, Timperio AF, Salmon J, Crawford DA. Socioeconomic position and children's physical activity and sedentary behaviors: longitudinal findings from the CLAN study. J Phys Act Health. 2009;6:289-98.
• 16. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381-95.
• 17. Lowry R, Wechsler H, Galuska DA, Fulton JE, Kann L. Television viewing and its associations with overweight, sedentary lifestyle, and insufficient consumption of fruits and vegetables among US high school students: differences by race, ethnicity, and gender. J Sch Health. 2002;72:413-21.
• 18. American Academy of Pediatrics. Committee on Public Education. American Academy of Pediatrics : children, adolescents and television. Pediatrics. 2001;107:423-6.
• 19. Gibson RS. Principles of nutritional assessment. New York: Oxford University; 1990.
• 20. Centers for Disease Control and Prevention (CDC US). CDC growth charts: United States; 2000. www.cdc.org/growthcharts
• ²¹
  Center for Disease Control and Prevention. Body mass index-for-age-BMI is used differently with children than it is with adults. Atlanta, Estados Unidos; 2001. http://www.cdc.gov/nchs/datawh/nchsdefs/bmi.htm
• 22. Senbanjo IO, Oshikoya KA. Physical activity and body mass index of school children and adolescents in Abeokuta, Southwest Nigeria. World J Pediatr 2010;6:217-22.
• 23. Koezuka N, Koo M, Allison KR, Adlaf EM, Dwyer JJ, Faulkner G, et al. The relationship between sedentary activities and physical inactivity among adolescents: results from the Canadian Community Health Survey. J Adolesc Health. 2006;39:515-22.
• 24. Santos MS, Hino AA, Reis RS, Rodriguez-Ãnez CR. Prevalência de barreiras para a prática de atividade física em adolescentes. Rev Bras Epidemiol. 2010;13:94-104.
• 25. Trost SG, Rosenkranz RR, Dzewaltowski D. Physical activity levels among children attending after-school programs. Med Sci Sports Exerc. 2008;40:622-9.
• 26. Ekelund U, Brage S, Besson H, Sharp S, Wareham NJ. Time spent being sedentary and weight gain in healthy adults: reverse or bidirectional causality? Am J Clin Nutr. 2008;88:612-7.
• 27. Hannon JC. Physical activity levels of overweight and nonoverweight high school students during physical education classes. J Sch Health. 2008;78:425-31.
• 28. Jackson DM, Djafarian K, Stewart J, Speakman JR. Increased television viewing is associated with elevated body fatness but not with lower total energy expenditure in children. Am J Clin Nutr. 2009;89:1031-6.
• 29. Singh GK, Yu SM, Siahpush M, Kogan MD. High levels of physical inactivity and sedentary behaviors among US immigrant children and adolescents. Arch Pediatr Adolesc Med. 2008;162:756-63.
• 30. Ornelas IJ, Perreira KM, Ayala GX. Parental influences on adolescent physical activity: a longitudinal study. Int J Behav Nutr Phys Act. 2007;4:3.
• 31. Lombard CB, Deeks AA, Ball K, Jolley D, Teede HJ. Weight, physical activity and dietary behaviour change in young mothers: short term results of the HeLP-her cluster randomized controlled trial. Nutr J. 2009;8:17.
• 32. Hohepa M, Scragg R, Schofield G, Kolt GS, Schaaf D. Associations between after-school physical activity, television use, and parental strategies in a sample of New Zealand adolescents. J Phys Act Health. 2009;6:299-305.
• 33. Bryant MJ, Lucove JC, Evenson KR, Marshall S. Measurement of television viewing in children and adolescents: a systematic review. Obes Rev. 2007,8:197-209.
• 34. Gorber SC, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007;8:307-26.

Correspondence

Publication Dates

• Publication in this collection
  17 Jan 2011
• Date of issue
  Dec 2010

History

• Received
  28 July 2010
• Accepted
  29 Sept 2010