Abstracts

Background

The benefits of physical activity are widely recognized for mental and physical health in all age groups ¹1. Andersen LB, Mota J, Di Pietro L. Update on the global pandemic of physical inactivity. Lancet 2016; 388:1255-6.^,22. Ding D, Mutrie N, Bauman A, Pratt M, Hallal PRC, Powell KE. Physical activity guidelines 2020: comprehensive and inclusive recommendations to activate populations. Lancet 2020; 396:1780-2.. The regular practice of physical activity improves physical fitness, bodyweight control, and sleep quality and reduces the risk of cardiovascular diseases, high blood pressure, and type II diabetes ¹1. Andersen LB, Mota J, Di Pietro L. Update on the global pandemic of physical inactivity. Lancet 2016; 388:1255-6.. Although these messages are highlighted in every health and well-being guideline ²2. Ding D, Mutrie N, Bauman A, Pratt M, Hallal PRC, Powell KE. Physical activity guidelines 2020: comprehensive and inclusive recommendations to activate populations. Lancet 2020; 396:1780-2., physical activity levels are still insufficient worldwide ³3. Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet Glob Health 2018; 6:e1077-e1086.^,44. Guthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1.6 million participants. Lancet Child Adolesc Health 2020; 4:23-35.. Besides this pandemic of physical inactivity, the prevalence of obesity is expected to continue rising in the following years ⁵5. Ward ZJ, Bleich SN, Cradock AL, Barrett AL, Giles CM, Flax C, et al. Projected U.S. State-level prevalence of adult obesity and severe obesity. N Engl J Med 2019; 381:2440-50., with serious implications for the global burden of chronic diseases. Note that the prolonged quarantine imposed by the COVID-19 pandemic had a negative impact on the physical activity level around the world, contributing to a worse quality of life, and that physical activity has proven to be beneficial in clinical conditions frequently associated with severe COVID-19 ⁶6. Dwyer MJ, Pasini M, De Dominicis S, Righi E. Physical activity: benefits and challenges during the COVID-19 pandemic. Scand J Med Sci Sports 2020; 30:1291-4.. Many countries are currently struggling to attenuate the negative impacts of these diseases, spending large amounts of public funds to keep complex health systems instead of investing in simple and inexpensive actions to promote physical activity ⁷7. Ding D, Lawson KD, Kolbe-Alexander TL, Finkelstein EA, Katzmarzyk PT, Mechelen W, et al. The economic burden of physical inactivity: a global analysis of major non-communicable diseases. Lancet 2016; 388:1311-24.^,88. Sato M, Du J, Inoue Y, Funk DC, Weaver F. Older adults' physical activity and healthcare costs, 2003-2014. Am J Prev Med 2020; 58:e141-8.^,99. Ranasinghe PD, Pokhrel S, Anokye NK. Economics of physical activity in low-income and middle-income countries: a systematic review. BMJ Open 2021; 11:e037784..

This scenario places physical activity at the center of the public health program ¹⁰10. Reis RS, Kelly CM, Parra DC, Barros M, Gomes G, Malta D, et al. Developing a research agenda for promoting physical activity in Brazil through environmental and policy change. Rev Panam Salud Pública 2012; 32:93-100., with a growing need for evidence on the effectiveness of different strategies to increase its levels. Thus, the scientific literature has shifted from emphasizing indicators and outcomes of physical activity to a more recent focus on context determinants, public policies, and global monitoring ¹¹11. Morris JN, Heady JA, Raffle PA, Roberts CG, Parks JW. Coronary heart-disease and physical activity of work. Lancet 1953; 262:1053-7.^,1212. Varela AR, Pratt M, Harris J, Lecy J, Salvo D, Browson RC, et al. Mapping the historical development of physical activity and health research: a structured literature review and citation network analysis. Prev Med 2018; 111:466-72.. However, comprehending all aspects that affect physical activity as a lifestyle behavior is a complex task. Many personal and environmental factors, including age, sex, urban characteristics, safety, income, and others, play a role in people’s decision to engage in health practices as part of their daily lives ¹³13. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW, et al. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380:258-71.. Similarly, economic and cultural aspects of different communities and regions can impact the perception of barriers encountered by population groups to perform physical activity ¹³13. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW, et al. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380:258-71.^,1414. Rech CR, Camargo EM, Araujo PAB, Loch MR, Reis RS. Perceived barriers to leisure-time physical activity in the Brazilian population. Rev Bras Med Esporte 2018; 24:303-9.. Nevertheless, most research is conducted in high-income countries ¹⁵15. Gomez LF, Sarmiento R, Ordoñez MF, Pardo CF, de Sá TH, Mallarino CH, et al. Urban environment interventions linked to the promotion of physical activity: a mixed methods study applied to the urban context of Latin America. Soc Sci Med 2015; 131:18-30..

Brazil has achieved some advances with surveillance programs and specific interventions targeting physical activity in different domains. In recent decades, behavior change programs have focused on physical activity for leisure, with educational and counseling actions associated with infrastructure investments and qualification of human resources ¹⁶16. Tusset D, Olkoski M, Merchan-Hamann E, Calmon PCDP, Santos L. Programa Academia da Saúde: um olhar quantitativo das adesões entre 2011 a 2017. Rev Bras Ativ Fís Saúde 2020; 25:e0165.^,1717. Sá GBAR, Dornelles GC, Cruz KG, Amorim RCA, Andrade SSCA, Oliveira TP, et al. The Health Academy Program as a strategy to promote health and healthy lifestyles: the national implementation scenario. Ciênc Saúde Colet 2016; 21:1849-60.. Nonetheless, information about the process and impacts of these programs across regional areas and vulnerable groups is scarce ¹⁸18. Gelius P, Messing S, Goodwin L, Schow D, Abu-Omar K. What are effective policies for promoting physical activity? A systematic review of reviews. Prev Med Rep 2020; 18:101095.^,1919. Becker L, Gonçalves P, Reis R. Primary health care programs for physical activity promotion in the Brazil: a systematic review. Rev Bras Ativ Fís Saúde 2016; 21:110-22.. These programs have given less attention to physical activity for transportation, with limited actions to promote active commuting for schools or local changes in urban structure and facilities to enable walking and bicycling ¹⁷17. Sá GBAR, Dornelles GC, Cruz KG, Amorim RCA, Andrade SSCA, Oliveira TP, et al. The Health Academy Program as a strategy to promote health and healthy lifestyles: the national implementation scenario. Ciênc Saúde Colet 2016; 21:1849-60.. The unequal distribution of these initiatives and the shortage of supportive urban environments in many countries of Latin America make sustaining these approaches in the long term more challenging ¹⁵15. Gomez LF, Sarmiento R, Ordoñez MF, Pardo CF, de Sá TH, Mallarino CH, et al. Urban environment interventions linked to the promotion of physical activity: a mixed methods study applied to the urban context of Latin America. Soc Sci Med 2015; 131:18-30.^,2020. Ferrari CKB. Implementation of public health policies for healthy lifestyles promotion: what Brazil should tell us? Health Promot Perspect 2018; 8:243-8..

Among these countries, Brazil stands out for monitoring physical activity behavior since 2006, with the Risk and Protective Factors Surveillance System for Chronic Noncomunicable Diseases Through Telephone Interview (Vigitel, in the Portuguese-language acronym) ²¹21. Mielke GI, Hallal PC, Malta DC, Lee IM. Time trends of physical activity and television viewing time in Brazil: 2006-2012. Int J Behav Nutr Phys Act 2014; 11:101.. The Vigitel survey holds people sociodemographic and health information from all capitals and the Federal District, enabling a longitudinal analysis of physical activity among the Brazilian population ²²22. Ide PH, Martins MSAS, Segri NJ. Tendência dos diferentes domínios da atividade física em adultos brasileiros: dados do Vigitel de 2006-2016. Cad Saúde Pública 2020; 36:e00142919.. An annual scientific report gathering all these data provides a unique opportunity to guide public health decision-making and tailor physical activity promotion strategies according to regional contexts and population profiles.

Despite the successful implementation of physical activity promotion strategies in Brazil, the implementation of actions is still rising, and more research is necessary to identify the circumstances and the differences among groups for the effective and sustainable adoption of an active lifestyle. Therefore, to better understand the physical activity pattern at the national level in different groups and guide policymakers to develop strategies to promote public health, this study aimed to analyze a historical series of the physical activity prevalence for leisure and transportation in the Brazilian population according to sex, age group, schooling, and race/skin color, by a 10-year temporal trend from 2010 to 2019. We have also investigated the difference in the overall prevalence of physical activity in both domains in the Brazilian state capitals and Federal District comparing the rates of the initial and final years of the historical series.

Methods

This time-series study analyzed data from the Brazilian adult population (≥ 18 years) from the Vigitel between 2010 and 2019. The Vigitel is a population-based study, started in 2006, whose objective is to monitor, by a telephone survey, the frequency and distribution of the main determinants of chronic diseases. For that purpose, each year, the system obtains probabilistic samples of adult individuals residing in households with at least one landline phone registered in each of the Brazilian state capitals and Federal District ²³23. Moura EC, Morais Neto OL, Malta DC, Moura L, Silva NN, Bernal R, et al. Surveillance of risk-factors for chronic diseases through telephone interviews in 27 Brazilian cities - 2006. Rev Bras Epidemiol 2008; 11 Suppl 1:20-37.^,2424. Departamento de Vigilância de Doenças e Agravos Não Transmissíveis e Promoção da Saúde, Secretaria de Vigilância em Saúde, Ministério da Saúde. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Brasília: Ministério da Saúde; 2020..

The Vigitel sample size calculation defined a minimum sample of approximately 2,000 adults per city/year to estimate the frequency of any risk factor in this population, using a 95% confidence interval (95%CI) and a maximum error of two percentage points. For specific estimates, according to sex, a maximum error of three percentage points was expected, assuming similar proportions of women and men in the sample.

Briefly, the Vigitel sampling procedure is conducted in two stages. In the first stage, 5,000 probabilistic samples of telephone lines in each city are drawn. The Vigitel obtains the lists of telephone lines from the landline phone companies operating in the cities. Commercial and non-operational lines are excluded. This draw takes place systematically and stratified by region of the city or according to the prefix of the phone lines (area code). Then, the phone line samples are drawn again and organized into replicas of 200 lines. Each replica reproduces the same distribution ratio as the original record. The second stage involves identifying active residential lines in parallel with randomly selecting a resident aged 18 or over living in the respective household to answer the questionnaire ²³23. Moura EC, Morais Neto OL, Malta DC, Moura L, Silva NN, Bernal R, et al. Surveillance of risk-factors for chronic diseases through telephone interviews in 27 Brazilian cities - 2006. Rev Bras Epidemiol 2008; 11 Suppl 1:20-37.. More details of the sampling procedure can be seen in a previous publication and the annual report of the Brazilian Ministry of Health ²³23. Moura EC, Morais Neto OL, Malta DC, Moura L, Silva NN, Bernal R, et al. Surveillance of risk-factors for chronic diseases through telephone interviews in 27 Brazilian cities - 2006. Rev Bras Epidemiol 2008; 11 Suppl 1:20-37.^,2424. Departamento de Vigilância de Doenças e Agravos Não Transmissíveis e Promoção da Saúde, Secretaria de Vigilância em Saúde, Ministério da Saúde. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Brasília: Ministério da Saúde; 2020..

The outcomes considered in this time-series study were the practice of physical activity for leisure and transportation. The block of questions corresponding to the physical activity practice was validated by Monteiro et al. ²⁵25. Monteiro CA, Florindo AA, Claro RM, Moura EC. Validade de indicadores de atividade física e sedentarismo obtidos por inquérito telefônico. Rev Saúde Pública 2008; 42:575-81. and remained unchanged over the analyzed period.

Physical activity for leisure was assessed using the following questions: “In the last three months, have you practiced any type of physical exercise or sport? (yes/no)”, “Do you exercise at least once a week? (yes/no)”, “How many days a week do you usually practice physical exercise or sport? (1-2; 3-4; 5-6 days/week; every day including Saturday and Sunday)”, “On the day you practice exercise or sport, how long does this activity last? (< 10; 10-19; 20-29; 30-39; 40-49; 50-59; ≥ 60 minutes)” ²⁴24. Departamento de Vigilância de Doenças e Agravos Não Transmissíveis e Promoção da Saúde, Secretaria de Vigilância em Saúde, Ministério da Saúde. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Brasília: Ministério da Saúde; 2020.. Individuals who reported practicing at least 150 minutes/week of moderate-intensity physical activity or at least 75 minutes/week of vigorous-intensity physical activity were considered active during leisure time ²⁶26. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 2020; 54:1451-62..

Concerning physical activity for transportation, the following questions were asked: “Do you go to or return from work walking or cycling?” (yes, the entire journey; yes, part of the journey; no)”, “How much time do you spend to go to and return from this journey (on foot or by bicycle)? (< 10; 10-19; 20-29; 30-39; 40-49; 50-59; ≥ 60 minutes)”, “Currently, are you attending a course/school or taking someone to a course/school? (yes/no)”, “Do you go to or return from school walking or cycling? (yes, the entire journey; yes, part of the journey; no)”, “How much time do you spend to go to and return from this journey (on foot or by bicycle)? (< 10; 10-19; 20-29; 30-39; 40-49; 50-59; ≥ 60 minutes)” ²⁴24. Departamento de Vigilância de Doenças e Agravos Não Transmissíveis e Promoção da Saúde, Secretaria de Vigilância em Saúde, Ministério da Saúde. Vigitel Brasil 2019: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico. Brasília: Ministério da Saúde; 2020.. Individuals who reported walking or cycling to/from work, course, or school at least 30 minutes/day, equivalent to at least 150 minutes/week of moderate-intensity physical activity, were considered active during transportation ²⁶26. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 2020; 54:1451-62..

The prevalence of active individuals in leisure and transportation was calculated annually from 2010 to 2019 for the total level and stratified by sex (male/female), age group (18-34/35-59/≥ 60 years), schooling in years (0-8/9-11/≥ 12), and self-perceived race/skin color (white/non-white). The prevalence was also estimated for the state capitals and Federal District for the initial and final years of the time series and the prevalence difference between these years (change) was calculated.

Data analysis

The annual prevalence of physical activity for leisure and transportation was calculated for the total sample and according to sex, age group, schooling, and self-perceived race/skin color. The complex sample design and the sample-weighting factor were considered in all these analyses. The differences between groups were evaluated using a 95%CI.

A segmental regression model was used to analyze the physical activity prevalence time series ²⁷27. Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med 2000; 19:335-51.. This statistical modeling technique, also called joinpoint regression or regression with inflection points, explains the relationship between two variables by using regression lines. It also assumes a linear trend between these points and has the same assumptions of the linear regression, except for homoscedasticity and no autocorrelation. This analysis allows incorporating such conditions when they are violated in an adjustment using a weighted regression model.

In this study, the annual prevalence rates of physical activity were considered as dependent variables (Y) and years of the study period as independent variables (X). The segmented regression model allowed to categorize the prevalence trends as stationary, increasing, or decreasing and to detect points of change in the trends. This statistical approach assumes that the change in rates is constant over each time partition defined by the transition points but varies among different time partitions. This model also provides annual percent change (APC), average annual percent change (AAPC), and their respective 95%CI. Significant changes (increase or decrease) in variables were indicated when regression coefficients were significantly different from zero (p < 0.05).

Lastly, the chi-square test (χ²) was used to verify differences in the prevalence of physical activity for leisure and transportation between 2010 and 2019 for all state capitals and the Federal District. We used Stata, version 16.0 (https://www.stata.com); Python, version 3.7.10 (http://www.python.org); and R (http://www.r-project.org). The significance level adopted was 5%.

Results

From 2010 to 2019, the Vigitel interviewed 512,969 individuals. Participants were mostly women (53.9%); aged 35-59 years (42.7%); reported 9-11 years of schooling (37.5%), and declared having non-white skin color (55.6%). The annual prevalence rates of physical activity for leisure and transportation between 2010 and 2019 to total sample and by sex, age group, schooling, and race/skin color were calculated.

Figure 1 shows a 10-year temporal trend (2010-2019) of physical activity for leisure and transportation according to sex, age group, schooling, and race/skin color. During the entire study period, prevalence of physical activity for leisure was significantly higher among men compared with women, individuals aged 18-34 years compared with the other age groups, and those with ≥ 12 years of schooling compared with other groups. The prevalence between white and non-white individuals showed no significant difference, except for the years 2010 and 2011, when the prevalence was significantly higher among white individuals. Concerning physical activity for transportation, we observed a significantly lower prevalence among those aged ≥ 60 years compared with younger groups and a significantly higher prevalence among non-white individuals compared with white individuals in all analyzed years. No significant difference was found between the sexes, age groups 18-34 and 35-59 years, and individuals with 0-8 and 9-11 years of schooling over the entire study period. Prevalence rates were significantly lower among those with ≥ 12 years of schooling compared with the other groups in the years 2010, 2014, 2017, and 2018.

Table 1 shows the time trend analysis of physical activity for leisure. All variables showed a trend with only one inflection point over the study period. The total sample showed a significant increasing trend from 2010-2015 (APC = 1.31%). The same trend occurred among men in 2010-2016 (APC = 0.94%) and among women in 2010-2014 (APC = 1.85%) and 2015-2019 (APC = 0.50%). Increasing trends were also observed for individuals aged 18-34 years (APC = 1.75%) and 35-59 years (APC = 1.41%) in 2010-2015; for those with 0-8 years of schooling (APC = 0.83%) and 9-11 years (APC = 1.00%) in 2010-2015 and for those with ≥ 12 years in 2010-2014 (APC = 1.51%); for white individuals in 2010-2014 (APC = 1.15%) and non-white individuals in 2010-2015 (APC = 1.77%). All variables had a significant increasing trend during the whole period, with AAPC ranging from 0.45% for the age group ≥ 60 years to 1.11% for non-white individuals.

In the time trend analysis of physical activity for transportation, we found only one inflection point over the study period in all investigated variables (Table 2). Significant decreasing trends occurred for the total sample in 2010-2013 (APC = -1.80%); for males in 2010-2012 (APC = -2.05%) and for females in 2010-2013 (APC = -1.81%). The same occurred with individuals aged 18-34 years in 2010-2013 (APC = -2.42%) and aged 35-59 years in 2010-2012 (APC = -2.20%); those with 0-8 years of schooling in 2010-2012 (APC = -2.05%), 9-11 years in 2010-2013 (APC = -1.86%), and ≥ 12 years in 2010-2013 (APC = -1.35%); white (APC = -1.39%) and non-white individuals (APC = -1.95%) in 2010-2013. Conversely, significant increasing trends occurred for the total sample in 2014-2019 (APC = 0.46%); for males in 2013-2019 (APC = 0.45%); for females in 2014-2019 (APC = 0.48%); for individuals aged 35-59 years in 2013-2019 (APC = 0.54%); for those with 0-8 years of schooling in 2013-2019 (APC = 0.49%) and 9-11 years in 2014-2019 (APC = 0.55%). A significant decreasing trend in the period occurred for most variables, except the age group ≥ 60 years and white race/skin color, which exhibited a stationary trend. Significant AAPC values ranged between -0.25% for the 35-59 years age group and -0.56% for the 18-34 years age group (Table 2).

Considering the Brazilian state capitals and Federal District, all cities, except for the Federal District and Porto Alegre, showed a statistically significant increase in the prevalence of physical activity for leisure between 2010 and 2019. The significant increase ranged from 5.5% in Recife to 18.7% in Rio Branco. Regarding physical activity for transportation, 17 out of 27 cities showed a significant reduction in prevalence between 2010 and 2019. The significant reduction ranged from 3% in Natal to 8.6% in Rio Branco (Table 3).

Discussion

This nationally representative study conducted with the Brazilian adult population showed opposite trends when analyzing the prevalence of physical activity for leisure and transportation over a 10-year period. We found that the prevalence of physical activity for leisure increased and the prevalence of physical activity for transportation decreased. The highest prevalence of physical activity for leisure occurred among males, young individuals (18-34 years), and those with high education (≥ 12 years), whereas older adults (≥ 60 years), those with high education (≥ 12 years), and white people presented the lowest prevalence of physical activity for transportation over the last decade. Considering the World Health Organization (WHO) action plan on physical activity that aims to support all people being more physically active and improving health ²⁶26. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 2020; 54:1451-62., our findings are quite relevant due to revealing inequalities in the physical activity levels in Brazil and identifying subgroups on which the public policies should be focused.

The lower prevalence of physical activity for leisure observed in women, older individuals, and among those with lower schooling has been well documented in the literature ²⁸28. Seefeldt V, Malina RM, Clark MA. Factors affecting levels of physical activity in adults. Sports Med 2002; 32:143-68.^,2929. He XZ, Baker DW. Differences in leisure-time, household, and work-related physical activity by race, ethnicity, and education. J Gen Intern Med 2005; 20:259-66.^,3030. Florindo AA, Guimarães VV, Cesar CL, Barros MB, Alves MC, Goldbaum M. Epidemiology of leisure, transportation, occupational, and household physical activity: prevalence and associated factors. J Phys Act Health 2009; 6:625-32.^,3131. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet 2012; 380:247-57.^,3232. Sallis JF, Bull F, Guthold R, Heath GW, Inoue S, Kelly P, et al. Progress in physical activity over the Olympic quadrennium. Lancet 2016; 388:1325-36.^,3333. Mielke GI, da Silva ICM, Kolbe-Alexander TL, Brown WJ. Shifting the physical inactivity curve worldwide by closing the gender gap. Sports Med 2018; 48:481-9.^,3434. Salvo D, Garcia L, Reis RS, Stankov I, Goel R, Schipperijn J, et al. Physical activity promotion and the United Nations Sustainable Development Goals: building synergies to maximize impact. J Phys Act Health 2021; 18:1163-80.. Regarding race/skin color, some studies have described an association between white race/skin color and higher physical activity levels for leisure ²⁹29. He XZ, Baker DW. Differences in leisure-time, household, and work-related physical activity by race, ethnicity, and education. J Gen Intern Med 2005; 20:259-66.^,3535. Crespo CJ, Smit E, Andersen RE, Carter-Pokras O, Ainsworth BE. Race/ethnicity, social class and their relation to physical inactivity during leisure time: results from the Third National Health and Nutrition Examination Survey, 1988-1994. Am J Prev Med 2000; 18:46-53., but little is known about the nature of this disparity. Most evidence attributes it to social class issues, such as unaffordable facilities, unavailable childcare, high crime rates, and fear for personal safety ²⁸28. Seefeldt V, Malina RM, Clark MA. Factors affecting levels of physical activity in adults. Sports Med 2002; 32:143-68.^,3434. Salvo D, Garcia L, Reis RS, Stankov I, Goel R, Schipperijn J, et al. Physical activity promotion and the United Nations Sustainable Development Goals: building synergies to maximize impact. J Phys Act Health 2021; 18:1163-80.^,3535. Crespo CJ, Smit E, Andersen RE, Carter-Pokras O, Ainsworth BE. Race/ethnicity, social class and their relation to physical inactivity during leisure time: results from the Third National Health and Nutrition Examination Survey, 1988-1994. Am J Prev Med 2000; 18:46-53.. A prior study designed to examine the differences in physical activity for leisure by race/ethnicity and education in a nationally representative cohort of 9,261 community-dwelling adults in the United States showed that education was far more important than race/ethnicity as a determinant of physical activity for leisure ²⁹29. He XZ, Baker DW. Differences in leisure-time, household, and work-related physical activity by race, ethnicity, and education. J Gen Intern Med 2005; 20:259-66.. A more recent study, also conducted in the United States, demonstrated that white adults had a higher prevalence of physical activity than black adults, considering achieving 10 minutes of moderate activity and 10 minutes of vigorous activity in the past month. Nevertheless, individual poverty and neighborhood poverty were associated with decreased physical activity rates among both white and black participants ³⁶36. Hawes AM, Smith GS, McGinty E, Bell C, Bower K, LaVeist TA, et al. Disentangling race, poverty, and place in disparities in physical activity. Int J Environ Res Public Health 2019; 16:1193.. Findings from the National Health and Nutrition Examination Survey (NHANES 2007-2016), also demonstrated that among adolescents and young adults (12-29 years), younger age, white race, and higher income were associated with a higher level of physical activity for leisure ³⁷37. Armstrong S, Wong CA, Perrin E, Page S, Sibley L, Skinner A. Association of physical activity with income, race/ethnicity, and sex among adolescents and young adults in the United States: findings from the National Health and Nutrition Examination Survey, 2007-2016. JAMA Pediatr 2018; 172:732-40..

As far as we know, in Brazil, only two studies investigated the relationship between physical activity for leisure and race/skin color and they found a higher prevalence of physical activity for leisure among white adults ³⁰30. Florindo AA, Guimarães VV, Cesar CL, Barros MB, Alves MC, Goldbaum M. Epidemiology of leisure, transportation, occupational, and household physical activity: prevalence and associated factors. J Phys Act Health 2009; 6:625-32.^,3838. Las Casas RCR, Bernal RTI, Melo EM, Malta DC. Prevalência da atividade física no tempo livre nas capitais brasileiras. Rev Med Minas Gerais 2016; 26 Suppl 8:S260-5.. In this study, the prevalence of physical activity for leisure was higher in white adults solely in the years 2010-2011, showing no difference in the years from 2012 to 2019. A possible explanation for the lack of difference observed since 2012 is the implementation of the Health Academy Program in Brazil, by the Ministry of Health, in 2011 ³⁹39. Silva AG, Prates EJS, Malta DC. Evaluation of community physical activity programs in Brazil: a scoping review. Cad Saúde Pública 2021; 37:e00277820.. Preliminary results from one center of the Health Academy Program in Belo Horizonte showed that most participants of this program were non-white individuals (56.4%) ⁴⁰40. Departamento de Análise de Situação em Saúde, Secretaria de Vigilância em Saúde, Ministério da Saúde. Avaliação da efetividade de programas de atividade física no Brasil. Brasília: Ministério da Saúde; 2011..

The main objective of the Health Academy Program is to promote health for all the population by implementing gym centers throughout Brazil, with infrastructure, equipment, and professional staff ⁴¹41. Ministério da Saúde. Portaria nº 681, de 7 de novembro de 2013. Redefine o Programa Academia da Saúde no âmbito do Sistema Único de Saúde. Diário Oficial da União 2013; 8 nov.. This program includes physical activity classes in rehabilitated public open spaces in low-income neighborhoods, health screening and counseling, and many other community-building activities in place-based settings (parks and plazas) ³⁹39. Silva AG, Prates EJS, Malta DC. Evaluation of community physical activity programs in Brazil: a scoping review. Cad Saúde Pública 2021; 37:e00277820.. A prior study investigated the impact of the Health Academy Program in 80 cities in the Pernambuco state, assessing 2,370 individuals in 2011, 3,824 individuals in 2012, and 3,835 individuals in 2013. The authors reported that the odds of reaching 150 minutes/week of physical activity for leisure was 5.06 (95%CI: 3.34; 7.67) for current participants (≤ 6 months) and 10.35 (95%CI: 6.93; 15.47) for current participants (> 6 months) compared with individuals that never participated ⁴²42. Simões EJ, Hallal PC, Siqueira FV, Schmaltz C, Menor D, Malta DC, et al. Effectiveness of a scaled up physical activity intervention in Brazil: a natural experiment. Prev Med 2017; 103S:S66-72.. A recent scoping review, including 24 studies published between 2008 and 2020, concluded that the Health Academy Program increases the amount of physical activity for leisure ³⁹39. Silva AG, Prates EJS, Malta DC. Evaluation of community physical activity programs in Brazil: a scoping review. Cad Saúde Pública 2021; 37:e00277820.. These findings are in line with our results, which showed an increase in the prevalence of physical activity for leisure from 2010 to 2015 in the Brazilian adult population, irrespective of sex, schooling, and race/skin color. The national coverage of this program can also justify the increase in the prevalence of physical activity for leisure in most Brazilian state capitals.

Regarding the physical activity for transportation, shifts from sedentary transport to active transport (walking and cycling) are a potential source of physical activity and enable its accumulation in daily life, rather than requiring intentional exercise ⁴³43. Patterson R, Webb E, Millett C, Laverty AA. Physical activity accrued as part of public transport use in England. J Public Health (Oxf) 2019; 41:222-30.. In this study, the prevalence of adults that reached the recommended level of 150 minutes of moderate activity during the week accrued from active transport was low compared with studies from other countries ⁴³43. Patterson R, Webb E, Millett C, Laverty AA. Physical activity accrued as part of public transport use in England. J Public Health (Oxf) 2019; 41:222-30.^,4444. Liao Y, Tsai H, Wang H, Lin C, Wu M, Chen J. Travel mode, transportation-related physical activity, and risk of overweight in Taiwanese adults. J Transp Health 2016; 3:220-5., varying from 11.9% to 17.9%, and it decreased over the 10-year period (AAPC = -0.32). In fact, the prevalence of physical activity for transportation decreased from 2010 to 2013 (APC = -1.80) and increased slightly from 2014 to 2019 (APC = 0.46). However, the increase was insufficient to offset the decrease at the beginning of the decade.

The use of public transportation in Brazil is associated with lower income ⁴⁵45. Sá TH, Pereira RHM, Duran AC, Monteiro CA. Diferenças socioeconômicas e regionais na prática do deslocamento ativo no Brasil. Rev Saúde Pública 2016; 50:37.^,4646. Moreira BS, Andrade ACS, Bastone AC, Vasconcelos KSS, Teixeira VBD, Xavier CC, et al. Individual characteristics, perceived neighborhood, and walking for transportation among older Brazilian people residing in a large urban area. Int J Environ Health Res 2021; [Online ahead of print]., which hinders access to individual means of transportation more efficient than collective modes ⁴⁷47. Cardoso L. Transporte público, acessibilidade urbana e desigualdades socioespaciais na região metropolitana de Belo Horizonte [Doctoral Dissertation]. Belo Horizonte: Universidade Federal de Minas Gerais; 2007.. From 2001 to 2012, the increase in the average income of the Brazilian population was accompanied by a rise of 138.6% in the fleet of motor vehicles, with a remarkable increase of 14.6% in the year 2012 ⁴⁸48. Rodrigues JM. Evolução da frota de automóveis e motos no Brasil 2001-2012. Relatório 2013 (sinopse preliminar). https://observatoriodasmetropoles.net.br/arquivos/biblioteca/abook_file/relatorio_frota2013.pdf (accessed on 11/Nov/2021).
https://observatoriodasmetropoles.net.br... , which may have contributed substantially to reducing physical activity for transportation as observed in this study. A study conducted on a large sample of Swedish adults reported that vehicle ownership mediated a significant proportion of the association between walkability parameters (e.g., residential density and land use mix) and walking for transportation ⁴⁹49. Eriksson U, Arvidsson D, Gebel K, Ohlsson H, Sundquist K. Walkability parameters, active transportation and objective physical activity: moderating and mediating effects of motor vehicle ownership in a cross-sectional study. Int J Behav Nutr Phys Act 2012; 9:123.. Note that the inflection point observed between 2013 and 2014 happened at the same time as the deep economic Brazilian recession that started in the second trimester of 2014 and severely compromised the workers’ income ⁵⁰50. Oreiro JL. A grande recessão brasileira: diagnóstico e uma agenda de política econômica. Estud Av 2017; 31:75-88., which may have contributed to an increase in active transport in this period. Regarding the increase in the prevalence of physical activity for transportation in the period from 2014 to 2019, note that the bike lanes in Brazilian capitals increased by 133% from 2014 to 2018, which is as an effective government strategy to improve cycling for transport and leisure ⁵¹51. Reis RS, Salvo D, Ogilvie D, Lambert EV, Goenka S, Brownson RC, et al. Scaling up physical activity interventions worldwide: stepping up to larger and smarter approaches to get people moving. Lancet 2016; 388:1337-48..

The higher prevalence of physical activity for transportation in adults with lower education (< 12 years of schooling) and non-white race/skin color observed in all years studied reinforces the association between active transport and lower socioeconomic status. In Brazil, these individual characteristics are associated with informal work, unemployment, and lower average earnings per hour ⁵²52. Instituto Brasileiro de Geografia e Estatísticas. Summary of Social Indicators: in 2019, proportion of poor people falls to 24.7% but extreme poverty still reaches 6.5% of the population. Agência IBGE Notícias 2020; 12 nov. https://agenciadenoticias.ibge.gov.br/en/agencia-press-room/2185-news-agency/releases-en/29439-sintese-de-indicadores-sociais-em-2019-proporcao-de-pobres-cai-para-24-7-e-extrema-pobreza-se-mantem-em-6-5-da-populacao-2.
https://agenciadenoticias.ibge.gov.br/en... . When considering solely the race/skin color, 70% of the people who live below the poverty line and 69% of the people who live in houses with some sort of inadequacy are black or mixed race ⁵³53. Instituto Brasileiro de Geografia e Estatísticas. Labor, income and housing: inequalities between whites and blacks or browns go on in Brazil. Agência IBGE Notícias 2020; 12 nov. https://agenciadenoticias.ibge.gov.br/en/agencia-news/2184-news-agency/news/29442-trabalho-renda-e-moradia-desigualdades-entre-brancos-e-pretos-ou-pardos-persistem-no-pais-2.
https://agenciadenoticias.ibge.gov.br/en... . A prior study developed in Curitiba (Brazil) has shown that adults living in areas with higher income showed a 44% lower likelihood of walking for transportation when compared with residents of lower-income areas ⁵⁴54. Hino AA, Reis RS, Sarmiento OL, Parra DC, Brownson RC. Built environment and physical activity for transportation in adults from Curitiba, Brazil. J Urban Health 2014; 91:446-62..

The inverse relationship between socioeconomic status and physical activity for transportation has been described elsewhere, mainly in low- and middle-income countries ⁴⁵45. Sá TH, Pereira RHM, Duran AC, Monteiro CA. Diferenças socioeconômicas e regionais na prática do deslocamento ativo no Brasil. Rev Saúde Pública 2016; 50:37.^,4646. Moreira BS, Andrade ACS, Bastone AC, Vasconcelos KSS, Teixeira VBD, Xavier CC, et al. Individual characteristics, perceived neighborhood, and walking for transportation among older Brazilian people residing in a large urban area. Int J Environ Health Res 2021; [Online ahead of print].^,5454. Hino AA, Reis RS, Sarmiento OL, Parra DC, Brownson RC. Built environment and physical activity for transportation in adults from Curitiba, Brazil. J Urban Health 2014; 91:446-62., where occupational, household, and transport domains are the most common types of physical activity. A prior study designed to provide data about the frequency and distribution of active transportation to work in Brazil showed that around one-third of the adult population travels on foot or by bike to work and the frequency of active transportation decreased with increased income and schooling in both sexes and was higher among younger adults ⁴⁵45. Sá TH, Pereira RHM, Duran AC, Monteiro CA. Diferenças socioeconômicas e regionais na prática do deslocamento ativo no Brasil. Rev Saúde Pública 2016; 50:37.. According to Rydin et al. ⁵⁵55. Rydin Y, Bleahu A, Davies M, Dávila JD, Friel S, De Grandis G, et al. Shaping cities for health: complexity and the planning of urban environments in the 21st century. Lancet 2012; 379:2079-108., the higher prevalence of physical activity for transportation in low- and middle-income countries might be due to the budgetary constraint of the poorest families, the spatial segregation existing in the metropolises, and the precariousness of public transport, rather than a practice guided by the health benefits. By contrast, in high-income countries, physical activity for leisure is the main contributor to the total physical activity level ¹³13. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW, et al. Correlates of physical activity: why are some people physically active and others not? Lancet 2012; 380:258-71..

This study has some limitations. The Vigitel sample included only the households with landlines, which could potentially introduce some selection bias. However, post-stratification weights were used to minimize possible sociodemographic differences and the absence of universal coverage of the telephone landline network ⁵⁶56. Bernal R, Silva NN. Home landline telephone coverage and potential bias in epidemiological. Rev Saúde Pública 2009; 43:421-6.. Also, physical activity measures were obtained by self-report, which could lead to an under or overestimation of the prevalence. To minimize this bias, the Vigitel planning included information quality control with the management of each survey measure. Studies evaluating the physical activity indicators’ validity and reliability have shown that they seem reproducible and sufficiently accurate ²⁵25. Monteiro CA, Florindo AA, Claro RM, Moura EC. Validade de indicadores de atividade física e sedentarismo obtidos por inquérito telefônico. Rev Saúde Pública 2008; 42:575-81.^,5757. Moreira AD, Claro RM, Felisbino-Mendes MS, Velasquez-Melendez G. Validity and reliability of a telephone survey in Brazil. Rev Bras Epidemiol 2017; 20:136-46..

As for strengths, we highlight the use of data from a population-based survey including all Brazilian capitals and the Federal District, with a large sample in a 10-year historical series. Also, we analyzed the trends of physical activity for leisure and transportation according to important sociodemographic characteristics of the sample, such as sex, age group, schooling, and race/skin color. The study results may contribute to monitoring risk factors for chronic diseases and subside the policymakers to implementing public policies to promote physical activity and improve active mobility in cities.

To comprehend other aspects associated with the variation in the prevalence of physical activity for leisure and transportation in the Brazilian adult population, future studies should address environmental factors, such as climate and urban characteristics, including safety, structure, and facilities that enable walking and cycling.

Conclusions

During the 10-year study period, the prevalence of physical activity for leisure increased and the prevalence of physical activity for transportation decreased. Regarding the different sociodemographic groups, women, individuals aged ≥ 35 years, and those with lower education (< 12 years) showed a lower prevalence of physical activity for leisure, whereas older adults (≥ 60 years), those with high education (≥ 12 years), and white people demonstrated a lower prevalence of physical activity for transportation. Considering the Brazilian state capitals and Federal District, the prevalence of physical activity for leisure increased in most cities, whereas the prevalence of physical activity for transportation decreased in 17 out of 27 cities. To increase the overall physical activity level of the population, policymakers should propose synergic strategies that encourage and facilitate physical activity for leisure and transportation, also considering the differences among sex, age group, schooling, and race/skin color.

References

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History