Abstract

Physical activity is a complex behavior influenced by sociodemographic and clinical factors. A better understanding of the relationships between these factors is essential to better understanding their influence on physical activity. The objective of this study was to examine the association between socioeconomic status, age, body fat, and depressive symptoms and level of physical activity among adults. We conducted a cross-sectional population-based study with 808 individuals to examine the interrelations between the above factors and their influence on level of physical activity using path analysis. Age had a significant direct negative effect on level of physical activity (β = -0.113, p < 0.004) and a significant positive effect on body fat (β = 0.376, p < 0.001). Depressive symptoms were negatively influenced by socioeconomic status (β = -0.126, p < 0.001) and positively influenced by age (β = 0.244, p < 0.001) and body fat (β = 0.169; p < 0.004). Socioeconomic status, body fat and depressive symptoms did not directly influence level of physical activity. This study concludes that level of physical activity declines with advancing age.

Key words
Physical activity; Adiposity; Depressive symptoms; Socioeconomic status

Introduction

Physical activity is defined as any bodily movement produced by skeletal muscles that results in energy expenditure above the rate in the resting state¹1 Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep 1985; 100(2):126-131 and is influenced by intrapersonal, interpersonal, environmental, political, and community factors²2 Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380(9838):258-271.^,33 Li K, Seo DC, Torabi MR, Peng CY, Kay NS, Kolbe LJ. Social-ecological factors of leisure-time physical activity in Black adults. Am J Health Behav 2012; 36(6):797-810.. Regular physical activity has been associated with health benefits and improved quality of life⁴4 American College of Sports M, Chodzko-Zajko WJ, Proctor DN, Fiatarone Singh MA, Minson CT, Nigg CR, et al. American College of Sports Medicine position stand. Exercise and physical activity for older adults. Med Sci Sports Exerc 2009; 41(7):1510-1530.^,55 Reiner M, Niermann C, Jekauc D, Woll A. Long-term health benefits of physical activity - a systematic review of longitudinal studies. BMC Public Health 2013; 13(813):1-9.. Doing regular physical activity can also reduce the risk of developing a host of diseases and chronic conditions and increase life expectancy. In contrast, physical inactivity may contribute to death from cardiovascular disease⁵5 Reiner M, Niermann C, Jekauc D, Woll A. Long-term health benefits of physical activity - a systematic review of longitudinal studies. BMC Public Health 2013; 13(813):1-9.

6 US Department of Health and Human Services. Physical activity guidelines advisory committee report, 2008. Washington: U.S. Public Health Service; 2008.

7 Fogelholm M. Physical activity, fitness and fatness: relations to mortality, morbidity and disease risk factors. A systematic review. Obes Rev 2010; 11(3):202-221.^-88 Oja P, Bull FC, Fogelholm M, Martin BW. Physical activity recommendations for health: what should Europe do? BMC Public Health 2010; 10(1):1-10..

The ecological perspective suggests that physical activity is influenced by the interaction between demographic, physiological, social, and environmental factors⁹9 Sallis J, Owen N. Ecological model of health behavior. In: Glanz K, Rimer BK, Viswanath K, editors. Health behavior and health education. New Jersey: John Wiley & Sons; 2002. p. 462-484.. However, further research is needed to better understand the influence of these factors on physical activity and their interrelations. Understanding why people are physically active or inactive is essential for planning evidence-based public health interventions²2 Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380(9838):258-271..

The determinants of physical activity has drawn interest from epidemiologists and public health professionals and research in this area provides important inputs to inform actions and policies designed to minimize the health effects of physical inactivity¹⁰10 Michelin E, Corrente JE, Burini RC. Fatores associados aos componentes de aptidão e nível de atividade física de usuários da Estratégia de Saúde da Família, Município de Botucatu, Estado de São Paulo, Brasil, 2006 a 2007. Epidemiol Serv Saúde 2011; 20(4):471-480.^,1111 World Health Organization (WHO). Global Recommendations on Physical Activity for Health. Geneva: World Health Organization Library; 2010.. Although interest in this topic in Brazil has also grown, investigations with more complex study designs remain scarce¹²12 Hallal PC. Physical activity and health in Brazil: research, surveillance and policies. Cad Saude Publica 2014; 30(12):2487-2496..

There is a predominance in the literature of studies examining the direct effect of sociodemographic, clinical, and anthropometric factors on physical activity. However, it is important to consider that these factors may also influence physical activity indirectly due to their interactions¹³13 McNeill LH, Wyrwich KW, Brownson RC, Clark EM, Kreuter MW. Individual, social environmental, and physical environmental influences on physical activity among black and white adults: a structural equation analysis. Ann Behav Med 2006; 31(1):36-44.

14 Baretta E, Baretta M, Peres KG. Nível de atividade física e fatores associados em adultos no Município de Joaçaba, Santa Catarina, Brasil. Cad Saude Publica 2007; 23(7):1595-1602.

15 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.^-1616 Shangguan R, Keating XD, Liu X, Fan Y. Physical activity among Chinese university administrators: a path analysis. International Journal of Health Promotion and Education 2018; 56(1):17-31.. The objective of this study was therefore to examine the association between socioeconomic status, age, body fat, and depressive symptoms and level of physical activity among adults. It does this by proposing an explanatory model built around a path diagram depicting the direct and indirect associations between these variables and their influence on level of physical activity among adults.

Methods

Study area and population

We conducted a cross-sectional population-based study with adults aged 18 years and over residing in private permanent households in the urban area of Montes Claros in the State of Minas Gerais, Brazil¹⁷17 Instituto Brasileiro de Geografia e Estatística (IBGE). Censo 2010. [citado 2018 Mar 22]. Disponível em: http://censo2010.ibge.gov.br/
http://censo2010.ibge.gov.br/... .

Sampling plan

This study used population data from a previously published epidemiological study analyzing polymorphism of the leptin receptor (rs1137101) and its association with obesity and cardiovascular disease in Montes Claros, Minas Gerais. We used cluster sampling, adopting a design effect of 2.0 as described in previous studies¹⁸18 Pena GG, Guimarães ALS, Veloso RRR, Reis TC, Gomes CS, Rodrigues Neto JF, Velazquez-Melendez G. Leptin Receptor Gene Gln223Arg Polymorphism Is Not Associated with Hypertension: A Preliminary Population-Based Cross-Sectional Study. Cardiol Res Pract 2014; 2014:879037.^,1919 Reis TC, Silva RR, Pena GG, Domingos PL, Pereira CS, Farias LC, Santos SHS, Jones KM, Paula AMB, Rodrigues Neto JF, Velásquez-Meléndez G, Guimarães ALS. Sex, age and smoking, but not genetic variation in LEPR (rs1137101), are associated with depressive symptoms. Psychiatr Genet 2015; 25(3):137-145., resulting in a minimum sample size of 750 individuals.

The previously defined sample size for the epidemiological study met the assumptions of the present study, which applied path analysis, where the recommended number of observations in the sample is between 250 and 500²⁰20 Schumacker RE, Lomax RG. A beginner’s guide to structural equation modeling. 2ª ed. New Jersey: Mahwah; 2004.

Data collection

The data were collected between January 2012 and March 2013 by previously trained interviewers supervised throughout the collection process. A pilot study was conducted with a convenience sample to calibrate the interviewers. The data were double entered using Epi Info^® 3.5.4 (Centers for Disease Control and Prevention, Atlanta, USA) and checked for consistency.

Study variables

We applied an individual questionnaire devised to collect information on the following: sociodemographic characteristics (sex, age, civil status, education, socioeconomic status); body fat; depressive symptoms; and frequency of physical activity (PA).

Frequency of PA was assessed using the International Physical Activity Questionnaire long form (IPAQ-8) validated for use in Brazil²¹21 Matsudo S, Araújo T, Matsudo V, Andrade D, Andrade E, Oliveira LC, Braggion G. Questionário internacional de atividade física (IPAQ): estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fís Saúde 2001; 6(2):5-18.. We calculated the total time (in minutes) spent on walking and moderate and vigorous activity in the domains work, mode of transport, household (domestic activities), recreation, sport, exercise, and leisure¹¹11 World Health Organization (WHO). Global Recommendations on Physical Activity for Health. Geneva: World Health Organization Library; 2010..

Socioeconomic status was based on the Economic Classification Criteria Brazil proposed by the Brazilian Market Research Association (ABEP)²²22 Associação Brasileira de Empresas de Pesquisa. Dados com base no Levantamento Sócio Econômico 2006 e 2007 - IBOPE. Associação Brasileira de Empresas de Pesquisa; 2009 [citado 2017 Jul 20]. Disponível em: http://www.abep.org/criterio-brasil
http://www.abep.org/criterio-brasil... , with total scores ranging from 0 and 46. This variable was analyzed as a continuous variable where the higher the score the higher the purchasing power.

Body composition was assessed by bioelectrical impedance analysis (BIA) using the BIA 310 Bioimpedance Analyzer (Biodynamics, England), applying a low range (500 to 800mA) and high frequency (50kHz) current with electrocardiogram gel electrodes (LecTec Corporation^®, USA). Before the test, height and weight were measured with the participant wearing light clothes, no accessories, and having emptied the bladder and the time of the last meal was noted. The test was not carried out with individuals who reported having consumed a large amount of alcohol on the previous day, were using metallic prosthetics, and had severe heart disease. The following variables were considered: weight (W), resistance (R), reactance (Xc), impedance (Z), and phase angle (PA)²³23 Paiva CRE, Gaya ACA, Bottaro M, Bezerra RFA. Assessment of the body composition of brazilian boys: the bioimpedence method. Rev Bras Cineantropom Desempenho Hum 2002; 4(1):9..We used the body fat percentages provided by the device²⁴24 Abernathy RP, Black DR. Healthy body weights: an alternative perspective. Am J Clin Nutr 1996; 63(3 Supl.):448S-51S..

Depressive symptoms were assessed using the Portuguese version of the Beck Depression Inventory (BDI)²⁵25 Beck AT, Steer RA, Carbin MG. Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review 1988; 8(1):77-100.^,2626 Gorenstein C, Andrade L. Validation of a Portuguese version of the Beck Depression Inventory and the State-Trait Anxiety Inventory in Brazilian subjects. Braz J Med Biol Res 1996; 29(4):453-460. The BDI is a self-administered questionnaire consisting of 21 sets of four statements ranked in terms of severity and scored from 0 to 3, with total possible scores ranging from 0 to 63. This variable was analyzed as a continuous variable, where higher total scores indicate more severe depressive symptoms²⁶26 Gorenstein C, Andrade L. Validation of a Portuguese version of the Beck Depression Inventory and the State-Trait Anxiety Inventory in Brazilian subjects. Braz J Med Biol Res 1996; 29(4):453-460..

Theoretical model

Using path analysis³¹31 Hair Júnior JF, Anderson RE, Tatham RL, Black WC. Análise multivariada de dados. Porto Alegre: Bookman; 2005.^,3232 Amorim LDAF, Fiaccone RL, Santos CAST, Santos TN, Moraes LTLP, Oliveira NF, Barbosa SO, Santos DN, Santos LM, Matos SM, Barreto ML. Structural equation modeling in epidemiology. Cad Saude Publica 2010; 26(12):2251-2262., a hypothetical model was constructed (Figure 1) to assess the influence of the interrelations between socioeconomic status, age, body fat, and depressive symptoms on frequency of total physical activity¹³13 McNeill LH, Wyrwich KW, Brownson RC, Clark EM, Kreuter MW. Individual, social environmental, and physical environmental influences on physical activity among black and white adults: a structural equation analysis. Ann Behav Med 2006; 31(1):36-44.^,1515 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.^,1616 Shangguan R, Keating XD, Liu X, Fan Y. Physical activity among Chinese university administrators: a path analysis. International Journal of Health Promotion and Education 2018; 56(1):17-31.^,2727 Wittayanukorn S, Qian J, Hansen RA. Prevalence of depressive symptoms and predictors of treatment among U.S. adults from 2005 to 2010. Gen Hosp Psychiatry 2014; 36(3):330-336.

28 Stopa SR, Malta DC, Oliveira MMd, Lopes CS, Menezes PR, Kinoshita RT. Prevalência do autorrelato de depressão no Brasil: resultados da Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol 2015; 18(2):170-180.

29 Beydoun MA, Fanelli-Kuczmarski MT, Shaked D, Dore GA, Beydoun HA, Rostant OS, Evans MK, Zonderman AB. Alternative Pathway Analyses Indicate Bidirectional Relations between Depressive Symptoms, Diet Quality, and Central Adiposity in a Sample of Urban US Adults. J Nutr 2016; 146(6):1241-1249.^-3030 Lee H, Lee JA, Brar JS, Rush EB, Jolley CJ. Physical activity and depressive symptoms in older adults. Geriatric nursing 2014; 35(1):37-41..

The main outcome was frequency of physical activity and the explanatory variables were socioeconomic status, age, body fat, and depressive symptoms. The model tested the following hypotheses: socioeconomic status and body fat have a direct effect on depressive symptoms and frequency of physical activity and an indirect effect on frequency of physical activity, mediated by depressive symptoms; age has a direct effect on body fat, depressive symptoms, and frequency of physical activity and indirectly influences frequency of physical activity mediated by body fat and depressive symptoms; and depressive symptoms have a direct effect on frequency of physical activity.

Figure 1 illustrates the relations between the variables and causal paths of the hypothetical model. The variables are represented by rectangles and the associations by arrows or paths (from the independent variable to the dependent variable)³³33 Marôco J. Análise de equações estruturais: fundamentos teóricos, Software & Aplicações. Aveiro: Report Number; 2010.^,3434 Silva AAM, Vasconcelos AGG, Bettiol H, Barbieri MA. Socioeconomic status, birth weight, maternal smoking during pregnancy and adiposity in early adult life: an analysis using structural equation modeling. Cad Saude Publica 2010; 26(1):15-29..

Statistical analysis

All variables were described using the measures center, variability, skewness (sk), and kurtosis (ku). Skewness values of > than 3 and/or ku values of > than 7 were deemed to indicate departure from normal distribution and received log transformation³⁶36 Kline RB. Principles and Practice of Structural Equation Modeling. New York: Guilford Press; 2005.. The missing values were imputed using linear regression. Multivariate regression was performed (path analysis model) and direct and indirect effects were quantified using standardized coefficients. The significance of the estimated coefficients was tested based on the ratio between the coefficient value and its standard error (critical ratio - CR), where CR values of ≥ 1.96 and ≤ - 1.96 (p ≤ 0.05) were deemed to be statistically significant³³33 Marôco J. Análise de equações estruturais: fundamentos teóricos, Software & Aplicações. Aveiro: Report Number; 2010..

The following indices were used to assess goodness of fit: Bentler’s comparative fit index (CFI), which compares the fit of the study model with that of the baseline model; and the goodness of fit index (GFI), which calculates the proportion of variance between the variables explained by the adjusted model. Values above 0.90 were deemed to indicate good fit³¹31 Hair Júnior JF, Anderson RE, Tatham RL, Black WC. Análise multivariada de dados. Porto Alegre: Bookman; 2005.^,3333 Marôco J. Análise de equações estruturais: fundamentos teóricos, Software & Aplicações. Aveiro: Report Number; 2010.^,3535 Pilati R, Laros JA. Modelos de equações estruturais em psicologia: conceitos e aplicações. Psic: Teor e Pesq 2007; 23(2):205-216..

The root mean square error of approximation (RMSEA) was also used as a test of close fit, comparing the test model and saturated model using the same dataset.³⁵35 Pilati R, Laros JA. Modelos de equações estruturais em psicologia: conceitos e aplicações. Psic: Teor e Pesq 2007; 23(2):205-216. RMSEA values below 0.10 were deemed to indicate reasonable fit³³33 Marôco J. Análise de equações estruturais: fundamentos teóricos, Software & Aplicações. Aveiro: Report Number; 2010.. The absolute fit index (X²2 Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380(9838):258-271./d.f) was also used to assess the goodness of fit test based on the ratio between the model’s X²2 Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380(9838):258-271. value and its degrees of freedom. This index is considered an absolute value because it does not compare the model with any other model³⁵35 Pilati R, Laros JA. Modelos de equações estruturais em psicologia: conceitos e aplicações. Psic: Teor e Pesq 2007; 23(2):205-216.. Values below 5 were deemed to indicate acceptable fit³³33 Marôco J. Análise de equações estruturais: fundamentos teóricos, Software & Aplicações. Aveiro: Report Number; 2010.^,3535 Pilati R, Laros JA. Modelos de equações estruturais em psicologia: conceitos e aplicações. Psic: Teor e Pesq 2007; 23(2):205-216..

The parameters were computed using the maximum likelihood method with the AMOS statistical software (version 18).

Ethical aspects

The study was approved by Montes Claros State University’s Research Ethics Committee.

Results

A total of 808 individuals participated in the study, 52.7% of whom were women. A little over half of the sample were aged 35 and over (54%) and married or living in stable union (54.6%). Almost half of the sample (48.1%) had completed over 12 years of study and 46% of participants had a monthly family income of up to R$1,244.00, or two minimum salaries.

Table 1 presents the descriptive measures of the variables that make up the hypothetical model (age, body fat, depressive symptoms, socioeconomic status, and frequency of physical activity). The mean age of participants was 44.2 years (SD ± 17.8) and mean percentage body fat was 27.4% (minimum 3% and maximum 50%). The mean total scores for depressive symptoms and socioeconomic status were 6.8 (SD ± 6.4) and 18.1 (SD ± 5.8), respectively. The values for these variables did not show severe departure from the normal distribution (sk > 3 and Ku > 10). The multivariate kurtosis coefficient (ku_M) was 8.41.

Figure 2 shows the adjusted structural model and coefficients for all its components. The model showed adequate fit: X²2 Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380(9838):258-271./d.f = 1.343; CFI = 0.999, GFI = 0.999; RMSEA = 0.021 (90% CI 0.000-0.099).

Age had a significant direct negative effect on level of physical activity (β=-0.113; p=0.004). Depressive symptoms were positively influenced by age (β=0.244; p<0.001) and body fat (β=0.169; p<0.001) and negatively influenced by socioeconomic status (β=-0.126; p<0.001). The findings show that there was a direct positive association between age and body fat (β=0.376; p<0.001). Socioeconomic status, body fat, and depressive symptoms did not directly influence level of physical activity (Table 2). Finally, age directly influenced frequency of physical activity, accounting for 89.7% of the total effect (not mediated by other variables) (Table 3).

Discussion

The findings show that there was significant relation between age and physical activity, depressive symptoms, and body fat and that depressive symptoms were influenced by percentage body fat and socioeconomic status.

The data presented also show that age had a direct negative influence on physical activity, corroborating the findings of previous international³⁷37 Camões M, Lopes C. Fatores associados à atividade física na população portuguesa. Rev Saude Publica 2008; 42(2):208-216.

38 Corder K, Winpenny E, Love R, Brown HE, White M, Sluijs EV. Change in physical activity from adolescence to early adulthood: a systematic review and meta- analysis of longitudinal cohort studies. Br J Sports Med 2017; 53(8):496-503.^-3939 Katzmarzyk PT, Lee IM, Martin CK, Blair SN. Epidemiology of Physical Activity and Exercise Training in the United States. Prog Cardiovasc Dis 2017; 60(1):3-10. and national studies¹⁴14 Baretta E, Baretta M, Peres KG. Nível de atividade física e fatores associados em adultos no Município de Joaçaba, Santa Catarina, Brasil. Cad Saude Publica 2007; 23(7):1595-1602.^,1515 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.^,4040 Malta DC, Bernal RTI, Nunes ML, Oliveira MM, Iser BPM, Andrade SSCA, Claro RM, Monteiro CA, Silva Júnior JB. Prevalência de fatores de risco e proteção para doenças crônicas não transmissíveis em adultos: estudo transversal, Brasil 2012. Epidemiol Serv Saúde 2014; 23(4):609-622.. A study in Portugal with 37,692 individuals reported a significant inverse association between age and different types of physical activity³⁷37 Camões M, Lopes C. Fatores associados à atividade física na população portuguesa. Rev Saude Publica 2008; 42(2):208-216., while a population-based study in the north of Minas Gerais showed that the frequency of physical activity decreased with increasing age¹⁵15 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.. A nationwide study conducted with 45,448 individuals showed that physical inactivity increased after the age of 55 and was greater among older people⁴⁰40 Malta DC, Bernal RTI, Nunes ML, Oliveira MM, Iser BPM, Andrade SSCA, Claro RM, Monteiro CA, Silva Júnior JB. Prevalência de fatores de risco e proteção para doenças crônicas não transmissíveis em adultos: estudo transversal, Brasil 2012. Epidemiol Serv Saúde 2014; 23(4):609-622.. This may be partially explained by the fact that physical demands tend to decrease with increasing age³⁷37 Camões M, Lopes C. Fatores associados à atividade física na população portuguesa. Rev Saude Publica 2008; 42(2):208-216.. Furthermore, advancing age is associated with changes in social roles and major transitions, including moving out of the family home and changes in the school/ work environment and financial circumstances. Many of these transitions are linked to health behaviors, including physical activity³⁸38 Corder K, Winpenny E, Love R, Brown HE, White M, Sluijs EV. Change in physical activity from adolescence to early adulthood: a systematic review and meta- analysis of longitudinal cohort studies. Br J Sports Med 2017; 53(8):496-503..

Our findings show a positive direct association between age and depressive symptoms. A nationwide survey of depressive symptoms among US adults conducted between 2005 and 2010 reported that prevalence increased with age²⁷27 Wittayanukorn S, Qian J, Hansen RA. Prevalence of depressive symptoms and predictors of treatment among U.S. adults from 2005 to 2010. Gen Hosp Psychiatry 2014; 36(3):330-336., while a nationwide population-based survey in Brazil documented significant differences in self-reported medical diagnosis of depression between age groups, showing that prevalence was higher among individuals aged between 60 and 64 years²⁸28 Stopa SR, Malta DC, Oliveira MMd, Lopes CS, Menezes PR, Kinoshita RT. Prevalência do autorrelato de depressão no Brasil: resultados da Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol 2015; 18(2):170-180..

The data presented also show that age had a significant direct effect on body fat, corroborating the findings of other studies with the Brazilian population¹⁵15 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.^,2727 Wittayanukorn S, Qian J, Hansen RA. Prevalence of depressive symptoms and predictors of treatment among U.S. adults from 2005 to 2010. Gen Hosp Psychiatry 2014; 36(3):330-336.^,2828 Stopa SR, Malta DC, Oliveira MMd, Lopes CS, Menezes PR, Kinoshita RT. Prevalência do autorrelato de depressão no Brasil: resultados da Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol 2015; 18(2):170-180.^,4040 Malta DC, Bernal RTI, Nunes ML, Oliveira MM, Iser BPM, Andrade SSCA, Claro RM, Monteiro CA, Silva Júnior JB. Prevalência de fatores de risco e proteção para doenças crônicas não transmissíveis em adultos: estudo transversal, Brasil 2012. Epidemiol Serv Saúde 2014; 23(4):609-622.^,4141 Silva VS, Souza I, Silva DAS, Petroski EL, Fonseca MJM. Correspondence between overweight and socioeconomic and demographic indicators in the adult Brazilian population. Rev Bras Epidemiol 2015; 18(2):476-489.. This may be explained by the fact that the aging leads to changes in physiological processes associated with body fat accumulation, such as slowing metabolism and hormonal changes, which can contribute to increased body adiposity levels⁴²42 World Health Organization (WHO). Obesity: preventing and managing the global epidemic. Geneva: WHO; 2000..

The results also show that socioeconomic status had a significant direct negative effect on depressive symptoms, which is consistent with the findings in the literature²⁸28 Stopa SR, Malta DC, Oliveira MMd, Lopes CS, Menezes PR, Kinoshita RT. Prevalência do autorrelato de depressão no Brasil: resultados da Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol 2015; 18(2):170-180.^,4343 Gomes VF, Miguel TLB, Miasso AI. Common Mental Disorders: socio-demographic and pharmacotherapy profile. Rev Latino-Am Enfermagem 2013; 21(6):1203- 1211.^,4444 Lepiece B, Reynaert C, Jacques D, Zdanowicz N. Poverty and mental health: What should we know as mental health professionals? Psychiatr Danub 2015; 27(Supl. 1):S92-96..

The association between socioeconomic status and physical activity in our study was not significant. These results contrast with the findings of a prospective cohort study with 16,571 British men and women using structural equation modeling, which observed that social class was associated with physical activity⁴⁵45 Juneau CE, Sullivan A, Dodgeon B, Cote S, Ploubidis GB, Potvin L. Social class across the life course and physical activity at age 34 years in the 1970 British birth cohort. Ann Epidemiol 2014; 24(9):641-648.. This discrepancy may be due to the fact that the two countries have completely different socioeconomic contexts.

Body fat was shown to have a significant positive effect on depressive symptoms, which is in line with the findings of a study with US adults using path analysis²⁹29 Beydoun MA, Fanelli-Kuczmarski MT, Shaked D, Dore GA, Beydoun HA, Rostant OS, Evans MK, Zonderman AB. Alternative Pathway Analyses Indicate Bidirectional Relations between Depressive Symptoms, Diet Quality, and Central Adiposity in a Sample of Urban US Adults. J Nutr 2016; 146(6):1241-1249.. Increased body mass index may influence the development of depression through biological mechanisms such as inflammation and dysregulation of the stress hormone system, increased risk of developing other diseases, and the negative effects of overweight on self-image⁴⁶46 Luppino FS, de Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, Zitman FG. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010; 67(3):220-229.. Although our study did not identify an association between these variables and frequency of physical activity, a previous study reported that physical activity is a protective factor for many physical conditions, promoting adequate body mass index and better mental health³⁰30 Lee H, Lee JA, Brar JS, Rush EB, Jolley CJ. Physical activity and depressive symptoms in older adults. Geriatric nursing 2014; 35(1):37-41..

Body fat did not have a significant direct effect on physical activity, which may be partially explained by the fact that daily physical activity alone many be insufficient to maintain body composition and health-related physical fitness⁴⁷47 Michelin E, Corrente JE, Burini RC. Associação dos níveis de atividade física com indicadores socioeconômicos, de obesidade e de aptidão física em adultos. Rev Bras Ativ Fís Saúde 2010; 15(1):35-41..

The direct relationship between age and frequency of physical activity was the most important association observed by this study, explaining most of the effect. These findings show that differences between age groups should be taken into account when planning, implementing, and reorienting policies and interventions aimed at increasing levels of physical activity¹⁵15 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.^,4848 Brito WF, Santos CL, Marcolongo AA, Campos MD, Bocalini DS, Antonio EL, Silva Junior JA, Tucci PJF, Serra AJ. Nível de atividade física em professores da rede estadual de ensino. Rev Saude Publica 2012; 46(1):104-113., focusing on the population subgroups most likely to adopt sedentary behaviors¹⁵15 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354.. Promoting physical activity can contribute to improving health indicators and quality of life¹⁰10 Michelin E, Corrente JE, Burini RC. Fatores associados aos componentes de aptidão e nível de atividade física de usuários da Estratégia de Saúde da Família, Município de Botucatu, Estado de São Paulo, Brasil, 2006 a 2007. Epidemiol Serv Saúde 2011; 20(4):471-480.^,1515 Freire RS, Lélis FLO, Fonseca Filho JA, Nepomuceno MO, Silveira MF. Prática regular de atividade física: estudo de base populacional no Norte de Minas Gerais, Brasil. Rev Bras Med Esporte 2014; 20(5):345-354..

In the adjusted structural model, the indirect associations between the variables were not statistically significant, as hypothesized by the study. A possible explanation is that the coefficient values of the indirect effects mediated by depressive symptoms and body fat were low and not significant. Further research exploring the relationship between individual, social, and environmental factors and their influence on physical activity is needed¹³13 McNeill LH, Wyrwich KW, Brownson RC, Clark EM, Kreuter MW. Individual, social environmental, and physical environmental influences on physical activity among black and white adults: a structural equation analysis. Ann Behav Med 2006; 31(1):36-44..

By identifying the direct and indirect pathways linking socioeconomic status, age, body fat, and depressive symptoms and their influence on physical activity, this study sought to go beyond the assessment of direct associations between physical activity and commonly investigated sociodemographic variables, thus helping to fill a gap in the literature¹²12 Hallal PC. Physical activity and health in Brazil: research, surveillance and policies. Cad Saude Publica 2014; 30(12):2487-2496..

Limitations

One of the limitations of the present study is the use of the long form of the IPAQ, which has been shown to overestimate self-reported physical activity⁴⁹49 Sebastiao E, Gobbi S, Chodzko-Zajko W, Schwingel A, Papini CB, Nakamura PM, Netto AV, Kokubun E. The International Physical Activity Questionnaire-long form overestimates self-reported physical activity of Brazilian adults. Public Health 2012; 126(11):967-975.. However, it is important to highlight that the IPAQ has also been found to be a reliable and valid tool for population studies¹⁰10 Michelin E, Corrente JE, Burini RC. Fatores associados aos componentes de aptidão e nível de atividade física de usuários da Estratégia de Saúde da Família, Município de Botucatu, Estado de São Paulo, Brasil, 2006 a 2007. Epidemiol Serv Saúde 2011; 20(4):471-480., providing an internationally comparable measure of physical activity and thus making it highly recommended⁵⁰50 Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003; 35(8):1381-1395.. Another limitation is that cross-sectional studies are limited in their ability to determine the cause-and-effect relationship between variables.

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