Association between physical inactivity in leisure, work, commuting, and household domains and nutritional status in adults in the capital cities of Brazil

Associação entre a inatividade física nos domínios do lazer, trabalho, deslocamento e domicílio e o estado nutricional em adultos das capitais do Brasil

Anne Ribeiro STREB Thiago Sousa MATIAS Larissa dos Santos LEONEL Willen Remon TOZETTO Carolina Graef VIEIRA Giovani Firpo DEL DUCA About the authors

ABSTRACT

Objective

To investigate the association between different domains (leisure, work, commuting, and household) of physical activity, independent and cumulative, and excess weight and obesity in Brazilian adults.

Methods

This is a cross-sectional survey, conducted in 2015, through telephone interviews with a representative sample of adults from the capitals of Brazil. Physical inactivity was defined as non-participation in predefined physical activities for each assessed domain. Excess weight (Body Mass Index?25kg/m2) and obesity (Body Mass Index?30kg/m2) were determined from self-reported measurements of weight and height. A binary logistic regression was conducted after adjusting for sociodemographic factors.

Results

Among 54,174 subjects, physical inactivity in commuting (ORexcess weight=1.27, 95%CI=1.13,1.42 and ORobesity=1.25, 95%CI=1.06,1.47) and leisure (ORexcess weight=1.12, 95%CI=1.04,1.22 and ORobesity=1.30, 95%CI=1.17,1.45) domains were associated with nutritional status. In addition, a linear trend was observed between increasing obesity and cumulative physical inactivity of all four domains (p<0.001).

Conclusion

Cumulative physical inactivity, especially in the commuting and leisure domains, was associated with excess weight and obesity in adults living in the capitals of Brazil. One possible explanation of these findings is that these domains involve particularly longer duration and greater intensity of physical inactivity. Public policies concerning physical activity should prioritize actions focused in promoting physical activity on commuting and leisure-time to help prevent overweight and obesity in the Brazilian adult population.

Keywords
Body Mass Index; Leisure activities; Motor activity; Nutritional status

RESUMO

Objetivo

Investigar a associação entre a atividade física em diferentes domínios (deslocamento, domicílio, lazer e trabalho) isolados e acumulados com a ocorrência de excesso de peso e obesidade em adultos brasileiros.

Métodos

Trata-se de um inquérito transversal, realizado em 2015, por meio de entrevista telefônica com uma amostra representativa de adultos das capitais do Brasil. A inatividade física foi determinada como a não participação em atividades físicas específicas para cada domínio avaliado. O excesso de peso (Índice de Massa Corporal?25kg/m2) e a obesidade (Índice de Massa Corporal ?30kg/m2) foram definidos pelo autorrelato de peso e altura. Na esta-tística, empregou-se a regressão logística binária ajustada para fatores sociodemográficos.

Resultados

Dentre os 54.174 sujeitos, observou-se que a inatividade física no deslocamento (OR=1,27; IC95%:1,13;1,42 e OR=1,25; IC95%:1,06;1,47) e no lazer (OR=1,12; IC95%:1,04;1,22 e OR=1,30; IC95%:1,17;1,45) estiveram associadas ao excesso de peso e à obesidade, respectivamente. Observou-se ainda uma tendência linear de aumento da obesidade à medida que se acumulam domínios com inatividade física (p<0,001).

Conclusão

A inatividade física acumulada em diferentes domínios, particularmente no deslocamento e no lazer, apresentou associação com o excesso de peso e obesidade em adultos residentes nas capitais do Brasil. Possivelmente, importantes características da atividade física nos referidos domínios, como a maior duração e a maior intensidade, sejam potenciais justificativas para o encontro de tais achados. Portanto, recomenda-se que políticas públicas de atividade física possam priorizar ações voltadas para os domínios do deslocamento e do lazer no combate ao excesso de peso e obesidade na população adulta brasileira.

Palavras-chave
Índice de Massa Corporal; Atividades de lazer; Atividade motora; Estado nutricional

INTRODUCTION

Physical inactivity is one of the most common, persistent, and important contributors to poor health; adoption of inactive lifestyles in diverse populations world-wide indicates that campaigns promoting physical activity have been unsuccessful [11 Barreto PS. Why are we failing to promote physical activity globally? Bull World Health Organ. 2013;91(6):390A. http://dx.doi.org/10.2471/BLT.13.120790
https://doi.org/10.2471/BLT.13.120790...
]. According to estimates by the Global Health Observatory, an initiative led by the World Health Organization (WHO), 23% of men and 32% of women over 18 years of age are physically inactive [22 World Health Organization. Prevalence of insufficient physical activity. Geneva: WHO; 2018 [cited 2018 Nov 13]. Available from: http://www.who.int/gho/ncd/risk_factors/physical_activity_text/en/
http://www.who.int/gho/ncd/risk_factors/...
]. Furthermore, globally in 2016, an estimated 39% of adults were overweight and 13% were obese [33 World Health Organization. Obesity and overweight. Geneva: WHO; 2018 [cited 2018 Nov 13]. Available from: http://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
http://www.who.int/news-room/fact-sheets...
].

New paradigms for the reduction of physical inactivity are fundamental. There is a need to understand how the individual domains of physical activity interact with health. Evidence suggests that the practice of physical activity in leisure promotes health benefits, including physical and mental well-being and the maintenance of a healthy body weight [44 Samitz G, Egger M, Zwahlen M. Domains of physical activity and all-cause mortality: Systematic review and dose-response meta-analysis of cohort studies. Int J Epidemiol. 2011;40(5):1382-400. http://dx.doi.org/10.1093/ije/dyr112
https://doi.org/10.1093/ije/dyr112...
]. However, the relationship of other physical activity domains, such as physical activity at work, has presented controversial evidence regarding benefits to health [55 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(9838):258-71. http://dx.doi.org/10.1016/S0140-6736(12)60735-1
https://doi.org/10.1016/S0140-6736(12)60...

6 Holtermann A, Krause N, Van der Beek AJ, Straker L. The physical activity paradox: Six reasons why occupational physical activity (OPA) does not confer the cardiovascular health benefits that leisure time physical activity does. Br J Sports Med. 2018;52(3):149-50. http://dx.doi.org/10.1136/bjsports-2017-097965
https://doi.org/10.1136/bjsports-2017-09...
-77 White RL, Babic MJ, Parker PD, Lubans DR, Astell-Burt T, Lonsdale C. Domain-specific physical activity and mental health: A meta-analysis. Am J Prev Med. 2017;52(5):653-66. http://dx.doi.org/10.1016/j.amepre.2016.12.008
https://doi.org/10.1016/j.amepre.2016.12...
].

The conditions that impede or favor the adoption of a physically active lifestyle can vary based on country and culture [88 Del Duca GF, Garcia LMT, Silva SG, Silva KS, Oliveira ES, Barros MV, et al. Clustering of physical inactivity in leisure, work, commuting, and household domains: data from 47,477 industrial workers in Brazil. J Phys Act Health. 2015;12(9):1264-71. http://dx.doi.org/10.1123/jpah.2014-0309
https://doi.org/10.1123/jpah.2014-0309...
]. Consequently, studies have shown that the health benefits associated with the individual domains of physical activity can show significant discrepancies and are highly dependent on environmental context [99 Bhatnagar P, Townsend N, Shaw A, Foster C. The physical activity profiles of South Asian ethnic groups in England. J Epidemiol Community Health. 2016;70(6):602-8. http://dx.doi.org/10.1136/jech-2015-206455
https://doi.org/10.1136/jech-2015-206455...
,1010 Beenackers MA, Kamphuis CB, Giskes K, Brug J, Kunst AE, Burdorf A, et al. Socioeconomic inequalities in occupational, leisure-time, and transport related physical activity among European adults: A systematic review. Int J Behav Nutr Phys Act. 2012;9(1):116. http://dx.doi.org/10.1186/1479-5868-9-116
https://doi.org/10.1186/1479-5868-9-116...
]. Recent evidence in Brazil establishes that both the practice of physical activity in leisure and the percentage of Brazilians attaining the recommended levels of physical activity have increased [1111 Cruz MS, Bernal RTI, Claro RM. Trends in leisure-time physical activity in Brazilian adults (2006-2016). Cad Saúde Pública. 2018;34(10):e00114817. http://dx.doi.org/10.1590/0102-311x00114817
https://doi.org/10.1590/0102-311x0011481...
]. Yet, in the period of approximately a decade, a notable increase in indicators of excess weight [1212 Malta DC, Santos MAS, Andrade SSCA, Oliveira TP, Stopa SR, Oliveira MM, et al. Tendência temporal dos indicadores de excesso de peso em adultos nas capitais brasileiras, 2006-2013. Ciênc Saúde Coletiva. 2016;21(4):1061-9. http://dx.doi.org/10.1590/1413-81232015214.12292015
https://doi.org/10.1590/1413-81232015214...
], suggests poor management of body mass.

It is important to consider that the domains of physical activity are not independent, and instead are related through complex interactions. As such, the level of physical activity in one domain may strongly influence the level of physical activity in the others [88 Del Duca GF, Garcia LMT, Silva SG, Silva KS, Oliveira ES, Barros MV, et al. Clustering of physical inactivity in leisure, work, commuting, and household domains: data from 47,477 industrial workers in Brazil. J Phys Act Health. 2015;12(9):1264-71. http://dx.doi.org/10.1123/jpah.2014-0309
https://doi.org/10.1123/jpah.2014-0309...
,99 Bhatnagar P, Townsend N, Shaw A, Foster C. The physical activity profiles of South Asian ethnic groups in England. J Epidemiol Community Health. 2016;70(6):602-8. http://dx.doi.org/10.1136/jech-2015-206455
https://doi.org/10.1136/jech-2015-206455...
]. Analyzing the domains of physical inactivity may also contribute to the broader conceptualization of health [1313 Rovniak LS, Sallis JF, Saelens BE, Frank LD, Marshall SJ, Norman GJ, et al. Adults’ physical activity patterns across life domains: Cluster analysis with replication. Health Psychol. 2010;29(5):496-505. http://dx.doi.org/10.1037/a0020428
https://doi.org/10.1037/a0020428...
]. In this way, physical activity can be used to better understand the weight status of Brazilians and guide prevention interventions to address the alarming pandemic of obesity in Brazil. This study aims to investigate the association between different domains (leisure, work, commuting, and household) of physical inactivity, independent and cumulative, and excess weight and obesity in Brazilian adults.

METHODS

This study used a population-based cross-sectional design. Data were extracted from databases, obtained from the Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico (VIGITEL, Vigilance of Risk Factors and Protection of Chronic Diseases by Telephone Inquiry). A telephone interview was conducted in 2015 whereby adult men and women (≥18 years old) were interviewed who had a fixed telephone line and who resided in one of the 26 Brazilian capitals or in the Federal District. The sample of the population was selected from each studied city’s registers of fixed telephone lines. Each register was systematically drawn from 5,000 telephone lines, of which at least 2,000 lines were selected according to the postal code. The interviews were carried out by a specialized company and the interviewers applied a previously validated questionnaire [1414 Monteiro CA, Moura EC, Jaime PC, Lucca A, Florindo AA, Figueiredo ICR, et al. Monitoramento de fatores de risco para doenças crônicas por entrevistas telefônicas. Rev Saúde Pública. 2005;39(1):47-57. http://dx.doi.org/10.1590/S0102-311X2008000600013
https://doi.org/10.1590/S0102-311X200800...
]. The answers to the questionnaire were recorded in an electronic database. More detailed information concerning the sampling process and the questionnaire utilized are reported in the original VIGITEL report [1515 Ministério da Saúde (Brasil). Vigitel Brasil 2015: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2015. Brasília: MS; 2016 [citado 10 dez 2018]. Disponível em: http://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2015.pdf
http://bvsms.saude.gov.br/bvs/publicacoe...
].

Body Mass Index (BMI) was calculated using interviewees’ self-reported measures of weight in kilograms and height in meters squared. Missing data were imputed using the hot deck technique. BMI values defined as being excess weight or obese were ?25kg/m2 and ?30kg/m2, respectively. Furthermore, physical inactivity was defined as not participating in specified physical activities for each domain. In the leisure domain, not engaging in any physical exercise and/or sport within the previous three months was considered inactive. Inactivity within the domain of commuting was defined as not using walking or cycling as a mode of transportation for school, travel or work. Inactivity at home was classified as not being involved in heavy household work. At work, individuals who did not carry weight and/or did not walk during work activities were considered inactive. The sum of physical inactivity was calculated by using a combination of the four domains of physical activity and was categorized into: Inactive in none, one, two, three, or all domains, independently of the domain evaluated. The sociodemographic factors of sex (male vs. female), age (in complete years), and schooling (categorized as 0 to 8, 9 to 11, and ≥12 years of study) were utilized as confounding variables and controlled for in subsequent analysis.

For each variable investigated, descriptive analysis was reported, including the absolute (n), and relative (%) frequencies of the variables with a 95% Confidence Interval (95%CI). We conducted a binary logistic regression analysis, with hierarchical adjustment, to quantify the association between nutritional status and either the individual domains of physical activity or the sum of the domains. In the hierarchical adjustment, the first level comprised of sex and age, and the second level consisted of schooling and the other domains. The significance level was p-value≤0.05. All analyses were performed using statistical software Stata® Standard Edition, version 15.0 (Stata Corp., College Station, Texas, United States). Data weighting and complex sampling were taken into account.

Participants consented verbally via phone call to participating in this study. VIGITEL was approved by the National Commission for Ethics in Research for Human Subjects, of the Ministry of Health, with the opinion No.749/2006 and the registry No.13.081.

RESULTS

Among 76,703 subjects who were eligible for this study, 54,174 adults were interviewed (70.6%). Table 1 describes the sociodemographic characteristics, domain-specific physical inactivity, and excess weight and obesity within the sample population. Over half of participants were women (54.0%; 95%CI:53.1;54.9). The mean age of interviewees was 47.5 (±17.5) years. Approximately 35.0% (95%CI:33.6;35,5) of participants were schooled up to eight years. The majority of the sample population were considered inactive in the commuting (85.9%; 95%CI:87.3;88.7), household (58.4%; 95%CI: 57.5;59.3), and work (62.2%; 95%CI:61.2;63.1) domains. Moreover, in the leisure domain, physical inactivity was present in 48.8% (95%CI:47.8;49.7) interviewees. Over 52.0% (95%CI:53.0;54.8) of the participants were excess weight, while 18.9% (95%CI:18.2;19.7) were obese.

Table 1
Sociodemographic characteristics, domain-specific physical inactivity, and nutritional status of adults living in Brazilian capitals. Brazil, 2015.

Table 2 demonstrates how physical inactivity within the four domains is associated with being excess weight in adults living in the capitals of Brazil. In the sociodemographic adjusted analysis, physical inactivity in the commuting (Odds Ratio [OR]=1.27, 95%CI:1.13;1.42) and leisure (OR=1.12, 95%CI:1.04;1.22) domains was associated with being excess weight. In addition, inactive adults in the household domain were less likely to be excess weight compared to their peers (OR=0.79, 95%CI:0.72;0.86).

Table 2
Domain-specific physical inactivity and its association with excess weight in adults living in the capitals cities of Brazil, 2015 (n=54,174).

Table 3 demonstrates the association between physical inactivity within the four domains and obesity in adults living in the capitals of Brazil. In the adjusted analysis, it was observed that physical inactivity in the commuting (OR=1.25, 95%CI:1.06;1.47) and leisure (OR=1.30, 95%CI:1.17;1.45) domains were associated with obesity.

Table 3
Association between physical inactivity in different domains and obesity in adults living in the capitals cities of Brazil, 2015 (n=54,174).

Figures 1 and 2 establish the aggregate physical inactivity within the four domains relates to excess weight and obesity in adults in the Brazilian capitals. A linear trend of increased obesity was observed as physical inactivity accumulated in the four domains (p<0.001).

Figure 1
Aggregated association between physical inactivity and excess weight in adults living in the capitals cities of Brazil, 2015.
Figure 2
Aggregated association between physical inactivity and obesity in adults living in the capitals cities of Brazil, 2015.

DISCUSSION

The present study investigated the association between of physical inactivity in leisure, work, commuting, and household and excess weight and obesity in Brazilian adults. One possible explanation of our findings is that a sedentary lifestyle is associated with physical inactivity in commuting and leisure domains, thereby causing excess weight and obesity in adults. This interpretation is supported by experimental evidence which indicates that leisure-specific physical inactivity is related to an increased adiposity [1616 Du H, Bennett D, Li L, Whitlock G, Guo Y, Collins R, et al. Physical activity and sedentary leisure time and their associations with BMI, waist circumference, and percentage body fat in 0.5 million adults: The China Kadoorie Biobank study. Am J Clin Nutr. 2013;97(3):487-96. http://dx.doi.org/10.3945/ajcn.112.046854
https://doi.org/10.3945/ajcn.112.046854...
,1717 Sarma S, Devlin RA, Gilliland J, Campbell MK, Zaric GS. The effect of leisure-time physical activity on obesity, diabetes, high BP and heart disease among Canadians: Evidence from 2000/2001 to 2005/2006. Health Econ. 2015;24(12):1531-47. http://dx.doi.org/10.1002/hec.3106
https://doi.org/10.1002/hec.3106...
]. In addition, inactive commuting has been reported to inhibit both general health benefits [1818 Mueller N, Rojas-Rueda D, Cole-Hunter T, Nazelle A, Dons E, Gerike R, et al. Health impact assessment of active transportation: A systematic review. Prev Med. 2015;76:103-14. http://dx.doi.org/10.1016/j.ypmed.2015.04.010
https://doi.org/10.1016/j.ypmed.2015.04....
] and an improved body composition [1919 Flint E, Cummins S. Active commuting and obesity in mid-life: Cross-sectional, observational evidence from UK Biobank. Lancet Diabetes Endocrinol. 2016;4(5):420-35. http://dx.doi.org/10.1016/S2213-8587(16)00053-X
https://doi.org/10.1016/S2213-8587(16)00...
].

Commuting-specific physical inactivity was present in 85.9% of study participants and increased the odds of being excess weight. Consequently, public health policies which focus on increasing active commuting, are critical. Advantageously, active commuting is accessible, and is particularly common in low - and middle-income countries [ 2020 Celis-Morales CA, Lyall DM, Welsh P, Anderson J, Steell L, Guo Y, et al. Association between active commuting and incident cardiovascular disease, cancer, and mortality: Prospective cohort study. BMJ. 2017;357:j1456. http://dx.doi.org/10.1136/bmj.j1456
https://doi.org/10.1136/bmj.j1456...
,2121 Macniven R, Bauman A, Abouzeid M. A review of population-based prevalence studies of physical activity in adults in the Asia-Pacific region. BMC Public Health. 2012;12(1):41. http://dx.doi.org/10.1186/1471-2458-12-41
https://doi.org/10.1186/1471-2458-12-41...
]. Walking and cycling are ideal ways for people to incorporate more physical activity in their daily routines [2222 Ogilvie D, Bull F, Cooper A, Rutter H, Adams E, Brand C, et al. Evaluating the travel, physical activity and carbon impacts of a ‘natural experiment’ in the provision of new walking and cycling infrastructure: Methods for the core module of the iConnect study. BMJ Open. 2012;2(1):e000694. http://dx.doi.org/10.1136/bmjopen-2011-000694
https://doi.org/10.1136/bmjopen-2011-000...
]. Unfortunately, in Brazil, active commuting is still not as culturally accepted, in part as a result of its association with lower socioeconomic levels and social status [2323 Buehler R. Determinants of transport mode choice: A comparison of Germany and the USA. J Transp Geogr. 2011;19(4):644-57. http://dx.doi.org/10.1016/j.jtrangeo.2010.07.005
https://doi.org/10.1016/j.jtrangeo.2010....

24 Lima JS, Ferrari GLM, Ferrari TK, Araujo TL, Matsudo VKR. Mudanças no deslocamento para o trabalho e na atividade física da população de três municípios da região de São Paulo nos anos de 2000 e 2010. Rev Bras Epidemiol. 2017;20(2):274-85. http://dx.doi.org/10.1590/1980-5497201700020008
https://doi.org/10.1590/1980-54972017000...
-2525 Madeira MC, Siqueira FCV, Facchini LA, Silveira DS, Tomasi E, Thumé E, et al. Atividade física no deslocamento em adultos e idosos do Brasil: prevalências e fatores associados. Cad Saúde Pública. 2013;29(5):165-74. http://dx.doi.org/10.1590/S0102-311X2013000100019
https://doi.org/10.1590/S0102-311X201300...
]. An additional challenge in Brazil is the feeling of insecurity, which can reduce the time spent travelling, in spite of the health benefits associated with active commuting [1717 Sarma S, Devlin RA, Gilliland J, Campbell MK, Zaric GS. The effect of leisure-time physical activity on obesity, diabetes, high BP and heart disease among Canadians: Evidence from 2000/2001 to 2005/2006. Health Econ. 2015;24(12):1531-47. http://dx.doi.org/10.1002/hec.3106
https://doi.org/10.1002/hec.3106...
,1818 Mueller N, Rojas-Rueda D, Cole-Hunter T, Nazelle A, Dons E, Gerike R, et al. Health impact assessment of active transportation: A systematic review. Prev Med. 2015;76:103-14. http://dx.doi.org/10.1016/j.ypmed.2015.04.010
https://doi.org/10.1016/j.ypmed.2015.04....
]. Moreover, there are numerous structural barriers, such as, a lack of bicycle lanes hindering accessibility [2626 Fajersztajn L, Veras M, Saldiva PHN. Como as cidades podem favorecer ou dificultar a promoção da saúde de seus moradores? Estud Av. 2016;30(86):7-27. http://dx.doi.org/10.1590/S0103-40142016.00100002
https://doi.org/10.1590/S0103-40142016.0...
]. However, those who manage to become active commuters demonstrate significant benefits in their health status, for example, have reduced risk for cardiovascular disease [2121 Macniven R, Bauman A, Abouzeid M. A review of population-based prevalence studies of physical activity in adults in the Asia-Pacific region. BMC Public Health. 2012;12(1):41. http://dx.doi.org/10.1186/1471-2458-12-41
https://doi.org/10.1186/1471-2458-12-41...
,2727 Gordon-Larsen P, Boone-Heinonen JE, Sidney S, Sternfeld B, Jacobs DR, Lewis CE. Active commuting and cardiovascular disease risk: The CARDIA study. Arch Intern Med. 2009;169(13):1216-23. http://dx.doi.org/10.1001/archinternmed.2009.163
https://doi.org/10.1001/archinternmed.20...
].

Our results demonstrate that physical inactivity in leisure-time is positively associated with excess weight and obesity and is present in 50.9% of the excess weight population and 56.3% of those with obesity. This practice is strongly associated with body mass, in which those who practice activities of moderate/vigorous intensity in this field present positive results in their composition, helping to reduce and maintain the weight, corroborating to lower chances of triggering obesity [1616 Du H, Bennett D, Li L, Whitlock G, Guo Y, Collins R, et al. Physical activity and sedentary leisure time and their associations with BMI, waist circumference, and percentage body fat in 0.5 million adults: The China Kadoorie Biobank study. Am J Clin Nutr. 2013;97(3):487-96. http://dx.doi.org/10.3945/ajcn.112.046854
https://doi.org/10.3945/ajcn.112.046854...
,2828 Xu F, Delmonico MJ, Lofgren IE, Uy KM, Maris SA, Quintanilla D, et al. Effect of a Combined Tai Chi, resistance training and dietary intervention on cognitive function in obese older women. J Frailty Aging. 2017;6(3):167-71. http://dx.doi.org/10.14283/jfa.2017.16
https://doi.org/10.14283/jfa.2017.16...
]. Participating in leisure-time sports in adulthood leads to lower sedentary behavior in old age and therefore, a reduction in health problems, including obesity [2929 Gayman AM, Fraser-Thomas J, Spinney JEL, Stone RC, Baker J. Leisure-time physical activity and sedentary behavior in older people: The influence of sport involvement on behavior patterns in later life. AIMS Public Health. 2017;4(2):171-88. http://dx.doi.org/10.3934/publichealth.2017.2.171
https://doi.org/10.3934/publichealth.201...
]. These studies highlight principal characteristics of physical activity in leisure-time, such as duration and intensity, that must be incorporated within the leisure domain so as to maximize the benefits of intentional practice.

We demonstrate that the sum of physical inactivity across the four activity domains increased the risk of obesity. Samitz et al. [44 Samitz G, Egger M, Zwahlen M. Domains of physical activity and all-cause mortality: Systematic review and dose-response meta-analysis of cohort studies. Int J Epidemiol. 2011;40(5):1382-400. http://dx.doi.org/10.1093/ije/dyr112
https://doi.org/10.1093/ije/dyr112...
], demonstrate that increases in time spent in domain-specific physical activity (e.g., leisure) and total physical activity are associated with a reduction of all-cause mortality. Evidence confirms that increasing an individual’s total time spent engaging in physical activity can protect against cardiovascular disease [3030 Myers J, McAuley P, Lavie CJ, Despres J-P, Arena R, Kokkinos P. Physical activity and cardiorespiratory fitness as major markers of cardiovascular risk: Their independent and interwoven importance to health status. Prog Cardiovasc Dis. 2015;57(4):306-14. http://dx.doi.org/10.1016/j.pcad.2014.09.011
https://doi.org/10.1016/j.pcad.2014.09.0...
], in addition to being an important behavior for the positive regulation of pro-inflammatory and anti-inflammatory cytokines that may be related to obesity and diabetes [3131 Schmidt FM, Weschenfelder J, Sander C, Minkwitz J, Thormann J, Chittka T, et al. Inflammatory cytokines in general and central obesity and modulating effects of physical activity. PLOS One. 2015;10(3):e0121971. http://dx.doi.org/10.1371/journal.pone.0121971
https://doi.org/10.1371/journal.pone.012...
].

While physical inactivity in the domains of commuting and leisure was associated with greater occurrences of both excess weight and obesity in the Brazilian adult population, the same cannot be observed for physical inactivity at household. In the present study, inactive individuals in the domestic environment were less likely to be excess weight. This result is quite conflicting with the literature. However, a likely explanation for this is the interaction between domains. A study of patterns of activity aggregation in different domains found a high possibility of subjects with high physical activity volume at leisure presenting low level of physical activity at household [3232 Rovniak LS, Sallis JF, Saelens BE, Frank LD, Marshall SJ, Norman GJ, et al. Adults’ physical activity patterns across life domains: Cluster analysis with replication. Health Psychol. 2010;29(5):496-505. http://dx.doi.org/10.1037/a0020428
https://doi.org/10.1037/a0020428...
]. It is worth noting that, in our adjusted analysis, all domains are adjusted to each other, but the total volume of physical activity in each domain was not taken into account. The present analysis refers only to the dichotomy between whether or not to do some physical activity in each domain. In our database (unpublished results), we observed a direct association between physical inactivity at household and the reach of physical activity recommendations in leisure, which helps us elucidate the total volume of physical activity in each domain as a possible confounding factor in dichotomous analyzes.

Some limitations are present in this study. Eating behavior as well as time in sedentary behavior were not accounted in the present study. Furthermore, data analysis included individual domains rather than combining different active and inactive domains. In addition, there is the possibility of bias in the questionnaire regarding the self-reported values for weight, height, and physical activity. However, through the use of the VIGITEL procedures, the data collection is reliable. On the other hand, the use of procedures by VIGITEL that supervise and monitor the quality of the data and the constant training of the interviewers, with checks and audits in about 10% of the daily connections in random samples, guarantee reliability of the answers. Likewise, the sample size with the use of capital data, allows the results to be representative of the Brazilian adult population living in the capitals of Brazil with telephone line coverage. In this sense, the other cities in the country may present different prevalence of the variables evaluated, but the contribution of the evidence of the relation between the sum of physical inactivity in domains and the deleterious effects on health is plausible in the general population. Another point to be highlighted is the use of two categories linked to nutritional status, making possible different associations with inactivity.

CONCLUSION

It was concluded that physical inactivity accumulated across four domains (particularly commuting and leisure) is associated with excess weight and obesity among Brazilian adults from capital cities. Important physical activity characteristics in these domains, such as longer duration and greater intensity, are potential justifications for such findings. In order to design effective strategies to encourage physical activity, this study sought to identify which specific domains where Brazilian adults are more physically inactive; and thus, drivers of weight gain and obesity. Therefore, it is recommended that public health promotion policies should emphasize and stimulate voluntary participation in an active lifestyle. In addition, it is important to emphasize that specifically promoting physical activity in commuting and leisure are most effective in protecting against overweight and obesity among the Brazilian adult population.

  • Support: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Finance Code 001).

How to cite cite this article

  • Streb AR, Matias TS, Leonel LS, Tozetto WR, Vieira CG, Del Duca GF. Association between physical inactivity in leisure, work, commuting, and household domains and nutritional status in adults in the capital cities of Brazil. Rev Nutr. 2019;32:e180276. http://dx.doi.org/10.1590/1678-9865201932e180276

REFERENCES

  • 1
    Barreto PS. Why are we failing to promote physical activity globally? Bull World Health Organ. 2013;91(6):390A. http://dx.doi.org/10.2471/BLT.13.120790
    » https://doi.org/10.2471/BLT.13.120790
  • 2
    World Health Organization. Prevalence of insufficient physical activity. Geneva: WHO; 2018 [cited 2018 Nov 13]. Available from: http://www.who.int/gho/ncd/risk_factors/physical_activity_text/en/
    » http://www.who.int/gho/ncd/risk_factors/physical_activity_text/en/
  • 3
    World Health Organization. Obesity and overweight. Geneva: WHO; 2018 [cited 2018 Nov 13]. Available from: http://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
    » http://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
  • 4
    Samitz G, Egger M, Zwahlen M. Domains of physical activity and all-cause mortality: Systematic review and dose-response meta-analysis of cohort studies. Int J Epidemiol. 2011;40(5):1382-400. http://dx.doi.org/10.1093/ije/dyr112
    » https://doi.org/10.1093/ije/dyr112
  • 5
    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(9838):258-71. http://dx.doi.org/10.1016/S0140-6736(12)60735-1
    » https://doi.org/10.1016/S0140-6736(12)60735-1
  • 6
    Holtermann A, Krause N, Van der Beek AJ, Straker L. The physical activity paradox: Six reasons why occupational physical activity (OPA) does not confer the cardiovascular health benefits that leisure time physical activity does. Br J Sports Med. 2018;52(3):149-50. http://dx.doi.org/10.1136/bjsports-2017-097965
    » https://doi.org/10.1136/bjsports-2017-097965
  • 7
    White RL, Babic MJ, Parker PD, Lubans DR, Astell-Burt T, Lonsdale C. Domain-specific physical activity and mental health: A meta-analysis. Am J Prev Med. 2017;52(5):653-66. http://dx.doi.org/10.1016/j.amepre.2016.12.008
    » https://doi.org/10.1016/j.amepre.2016.12.008
  • 8
    Del Duca GF, Garcia LMT, Silva SG, Silva KS, Oliveira ES, Barros MV, et al Clustering of physical inactivity in leisure, work, commuting, and household domains: data from 47,477 industrial workers in Brazil. J Phys Act Health. 2015;12(9):1264-71. http://dx.doi.org/10.1123/jpah.2014-0309
    » https://doi.org/10.1123/jpah.2014-0309
  • 9
    Bhatnagar P, Townsend N, Shaw A, Foster C. The physical activity profiles of South Asian ethnic groups in England. J Epidemiol Community Health. 2016;70(6):602-8. http://dx.doi.org/10.1136/jech-2015-206455
    » https://doi.org/10.1136/jech-2015-206455
  • 10
    Beenackers MA, Kamphuis CB, Giskes K, Brug J, Kunst AE, Burdorf A, et al Socioeconomic inequalities in occupational, leisure-time, and transport related physical activity among European adults: A systematic review. Int J Behav Nutr Phys Act. 2012;9(1):116. http://dx.doi.org/10.1186/1479-5868-9-116
    » https://doi.org/10.1186/1479-5868-9-116
  • 11
    Cruz MS, Bernal RTI, Claro RM. Trends in leisure-time physical activity in Brazilian adults (2006-2016). Cad Saúde Pública. 2018;34(10):e00114817. http://dx.doi.org/10.1590/0102-311x00114817
    » https://doi.org/10.1590/0102-311x00114817
  • 12
    Malta DC, Santos MAS, Andrade SSCA, Oliveira TP, Stopa SR, Oliveira MM, et al Tendência temporal dos indicadores de excesso de peso em adultos nas capitais brasileiras, 2006-2013. Ciênc Saúde Coletiva. 2016;21(4):1061-9. http://dx.doi.org/10.1590/1413-81232015214.12292015
    » https://doi.org/10.1590/1413-81232015214.12292015
  • 13
    Rovniak LS, Sallis JF, Saelens BE, Frank LD, Marshall SJ, Norman GJ, et al Adults’ physical activity patterns across life domains: Cluster analysis with replication. Health Psychol. 2010;29(5):496-505. http://dx.doi.org/10.1037/a0020428
    » https://doi.org/10.1037/a0020428
  • 14
    Monteiro CA, Moura EC, Jaime PC, Lucca A, Florindo AA, Figueiredo ICR, et al Monitoramento de fatores de risco para doenças crônicas por entrevistas telefônicas. Rev Saúde Pública. 2005;39(1):47-57. http://dx.doi.org/10.1590/S0102-311X2008000600013
    » https://doi.org/10.1590/S0102-311X2008000600013
  • 15
    Ministério da Saúde (Brasil). Vigitel Brasil 2015: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2015. Brasília: MS; 2016 [citado 10 dez 2018]. Disponível em: http://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2015.pdf
    » http://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2015.pdf
  • 16
    Du H, Bennett D, Li L, Whitlock G, Guo Y, Collins R, et al Physical activity and sedentary leisure time and their associations with BMI, waist circumference, and percentage body fat in 0.5 million adults: The China Kadoorie Biobank study. Am J Clin Nutr. 2013;97(3):487-96. http://dx.doi.org/10.3945/ajcn.112.046854
    » https://doi.org/10.3945/ajcn.112.046854
  • 17
    Sarma S, Devlin RA, Gilliland J, Campbell MK, Zaric GS. The effect of leisure-time physical activity on obesity, diabetes, high BP and heart disease among Canadians: Evidence from 2000/2001 to 2005/2006. Health Econ. 2015;24(12):1531-47. http://dx.doi.org/10.1002/hec.3106
    » https://doi.org/10.1002/hec.3106
  • 18
    Mueller N, Rojas-Rueda D, Cole-Hunter T, Nazelle A, Dons E, Gerike R, et al Health impact assessment of active transportation: A systematic review. Prev Med. 2015;76:103-14. http://dx.doi.org/10.1016/j.ypmed.2015.04.010
    » https://doi.org/10.1016/j.ypmed.2015.04.010
  • 19
    Flint E, Cummins S. Active commuting and obesity in mid-life: Cross-sectional, observational evidence from UK Biobank. Lancet Diabetes Endocrinol. 2016;4(5):420-35. http://dx.doi.org/10.1016/S2213-8587(16)00053-X
    » https://doi.org/10.1016/S2213-8587(16)00053-X
  • 20
    Celis-Morales CA, Lyall DM, Welsh P, Anderson J, Steell L, Guo Y, et al Association between active commuting and incident cardiovascular disease, cancer, and mortality: Prospective cohort study. BMJ. 2017;357:j1456. http://dx.doi.org/10.1136/bmj.j1456
    » https://doi.org/10.1136/bmj.j1456
  • 21
    Macniven R, Bauman A, Abouzeid M. A review of population-based prevalence studies of physical activity in adults in the Asia-Pacific region. BMC Public Health. 2012;12(1):41. http://dx.doi.org/10.1186/1471-2458-12-41
    » https://doi.org/10.1186/1471-2458-12-41
  • 22
    Ogilvie D, Bull F, Cooper A, Rutter H, Adams E, Brand C, et al Evaluating the travel, physical activity and carbon impacts of a ‘natural experiment’ in the provision of new walking and cycling infrastructure: Methods for the core module of the iConnect study. BMJ Open. 2012;2(1):e000694. http://dx.doi.org/10.1136/bmjopen-2011-000694
    » https://doi.org/10.1136/bmjopen-2011-000694
  • 23
    Buehler R. Determinants of transport mode choice: A comparison of Germany and the USA. J Transp Geogr. 2011;19(4):644-57. http://dx.doi.org/10.1016/j.jtrangeo.2010.07.005
    » https://doi.org/10.1016/j.jtrangeo.2010.07.005
  • 24
    Lima JS, Ferrari GLM, Ferrari TK, Araujo TL, Matsudo VKR. Mudanças no deslocamento para o trabalho e na atividade física da população de três municípios da região de São Paulo nos anos de 2000 e 2010. Rev Bras Epidemiol. 2017;20(2):274-85. http://dx.doi.org/10.1590/1980-5497201700020008
    » https://doi.org/10.1590/1980-5497201700020008
  • 25
    Madeira MC, Siqueira FCV, Facchini LA, Silveira DS, Tomasi E, Thumé E, et al Atividade física no deslocamento em adultos e idosos do Brasil: prevalências e fatores associados. Cad Saúde Pública. 2013;29(5):165-74. http://dx.doi.org/10.1590/S0102-311X2013000100019
    » https://doi.org/10.1590/S0102-311X2013000100019
  • 26
    Fajersztajn L, Veras M, Saldiva PHN. Como as cidades podem favorecer ou dificultar a promoção da saúde de seus moradores? Estud Av. 2016;30(86):7-27. http://dx.doi.org/10.1590/S0103-40142016.00100002
    » https://doi.org/10.1590/S0103-40142016.00100002
  • 27
    Gordon-Larsen P, Boone-Heinonen JE, Sidney S, Sternfeld B, Jacobs DR, Lewis CE. Active commuting and cardiovascular disease risk: The CARDIA study. Arch Intern Med. 2009;169(13):1216-23. http://dx.doi.org/10.1001/archinternmed.2009.163
    » https://doi.org/10.1001/archinternmed.2009.163
  • 28
    Xu F, Delmonico MJ, Lofgren IE, Uy KM, Maris SA, Quintanilla D, et al Effect of a Combined Tai Chi, resistance training and dietary intervention on cognitive function in obese older women. J Frailty Aging. 2017;6(3):167-71. http://dx.doi.org/10.14283/jfa.2017.16
    » https://doi.org/10.14283/jfa.2017.16
  • 29
    Gayman AM, Fraser-Thomas J, Spinney JEL, Stone RC, Baker J. Leisure-time physical activity and sedentary behavior in older people: The influence of sport involvement on behavior patterns in later life. AIMS Public Health. 2017;4(2):171-88. http://dx.doi.org/10.3934/publichealth.2017.2.171
    » https://doi.org/10.3934/publichealth.2017.2.171
  • 30
    Myers J, McAuley P, Lavie CJ, Despres J-P, Arena R, Kokkinos P. Physical activity and cardiorespiratory fitness as major markers of cardiovascular risk: Their independent and interwoven importance to health status. Prog Cardiovasc Dis. 2015;57(4):306-14. http://dx.doi.org/10.1016/j.pcad.2014.09.011
    » https://doi.org/10.1016/j.pcad.2014.09.011
  • 31
    Schmidt FM, Weschenfelder J, Sander C, Minkwitz J, Thormann J, Chittka T, et al Inflammatory cytokines in general and central obesity and modulating effects of physical activity. PLOS One. 2015;10(3):e0121971. http://dx.doi.org/10.1371/journal.pone.0121971
    » https://doi.org/10.1371/journal.pone.0121971
  • 32
    Rovniak LS, Sallis JF, Saelens BE, Frank LD, Marshall SJ, Norman GJ, et al Adults’ physical activity patterns across life domains: Cluster analysis with replication. Health Psychol. 2010;29(5):496-505. http://dx.doi.org/10.1037/a0020428
    » https://doi.org/10.1037/a0020428

Publication Dates

  • Publication in this collection
    27 June 2019
  • Date of issue
    2019

History

  • Received
    18 Dec 2018
  • Reviewed
    15 May 2019
  • Accepted
    31 May 2019
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