Abstract

The aim of this study was to describe sedentary behavior (SB) across leisure, occupation, and transport domains and determine factors associated with excessive sedentary behavior (ESB). Cross-sectional survey with a representative sample of 1,126 women aged 20-69 years living in São Leopoldo/RS. SB, demographic, socioeconomic, behavioral and health factors data were collected using a questionnaire administered by interviewers. The cut-off point for ESB was defined as the median. Associations were tested using Poisson regression with robust error variance. The medians and interquartile intervals (min/day) for leisure, occupation, and transport SB were 163.9(86.6-2710.5), 51.4(0-257.1), and 17.1(5.7-37.3), respectively. The likelihood of leisure SB increased with education level, was higher among women who were not employed, lived in household without children, and smokers. In other domains, there was an inverse association between age, being white, economic class, education level, and income and ESB. Direct association between living in a household with a car and excessive transport SB and women who were not employed were 30% less likely to engage in ESB in this domain. The predominant domain in Total SB was leisure. Associations differed across domains, indicating that domain-specific interventions should be implemented in addressing excessive SB.

Key words
Sedentary lifestyle; Women’s health; Epidemiology

Introduction

In recent decades, research examining the relationship between lifestyle and health has shown that sedentary behavior (SB) is a risk factor for morbidity and mortality¹1 Dunstan DW, Barr EL, Healy GN, Salmon J, Shaw JE, Balkau B, Magliano DJ, Cameron AJ, Zimmet PZ, Owen N. Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Circulation 2010; 121(3):384-391.^,22 Owen N, Healy GN, Matthews CE, Dunstan DW. Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev 2010; 38(3):105-113.. SB comprises activity in a sitting or reclining posture while awake characterized by an energy expenditure of ≤ 1.5 metabolic equivalents (METs)³3 Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, Chastin SFM, Altenburg TM, Chinapaw MJM, SBRN Terminology Consensus Project Participants. Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act 2017; 14(1):75.. This concept differs from physical inactivity, when an individual does not practice the amount of daily physical activity (PA) recommended by the World Health Organization⁴4 World Health Organization (WHO). Global recommendations on physical activity for health. Geneva: WHO; 2010.. Evidence from prospective studies shows that spending more time engaging in SB increases the risk of diabetes, cardiovascular disease, metabolic syndrome, and death⁵5 Wilmot EG, Edwardson CL, Achana FA, Davies MJ, Gorely T, Gray LJ, Khunti K, Yates T, Biddle SJ. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia 2012; 55(11):2895-2905.^,66 Ford ES, Caspersen CJ. Sedentary behaviour and cardiovascular disease: a review of prospective studies. Int J Epidemiol 2012; 41(5):1338-1353.. Although high levels of moderate PA (~60-75 minutes per day) can eliminate or reduce some of these risks⁷7 Ekelund U, Steene-Johannessen J, Brown WJ, Fagerland MW, Owen N, Powell KE, Bauman A, Lee IM, Lancet Physical Activity Series 2 Executive Committee, Lancet Sedentary Behaviour Working Group. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet 2016; 388(10051):1302-1310., the majority of Brazil’s female population (91.5%)⁸8 Knuth AG, Malta DC, Dumith SC, Pereira CA, Morais Neto OL, Temporao JG, Penna G, Hallal PC. Practice of physical activity and sedentarism among Brazilians: results of the National Household Sample Survey-2008. Cien Saude Colet 2011; 16(9):3697-3705. do not practice the minimum recommended amount of PA (~30 minutes per day of moderate-intensity physical activity)⁴4 World Health Organization (WHO). Global recommendations on physical activity for health. Geneva: WHO; 2010..

Generally, it is the sum total of all types of sedentary behavior, or total sedentary behavior (Total SB), that determines health impact⁶6 Ford ES, Caspersen CJ. Sedentary behaviour and cardiovascular disease: a review of prospective studies. Int J Epidemiol 2012; 41(5):1338-1353.. However, some studies suggest that certain types of SB may contribute to given morbidities more than others⁹9 Saidj M, Jorgensen T, Jacobsen RK, Linneberg A, Aadahl M. Separate and joint associations of occupational and leisure-time sitting with cardio-metabolic risk factors in working adults: a cross-sectional study. PLoS One 2013; 8(8):e70213.^,1010 Hsueh MC, Liao Y, Chang SH. Are Total and Domain-Specific Sedentary Time Associated with Overweight in Older Taiwanese Adults? Int J Environ Res Public Health 2015; 12(10):12697-12705.. While assessing Total SB may help identify individuals or population groups at a higher risk¹¹11 Owen N, Sugiyama T, Eakin EE, Gardiner PA, Tremblay MS, Sallis JF. Adults’ sedentary behavior determinants and interventions. Am J Prev Med 2011; 41(2):189-196., this indicator alone is insufficient to plan interventions, because it does not provide an understanding of the sedentary activities that contribute most to excessive Total SB and the contexts in which it take place. It has therefore been suggested that studies examining SB should consider behavior across life domains, such as leisure, transport, and occupation¹²12 Bauman A, Ainsworth BE, Sallis JF, Hagstromer M, Craig CL, Bull FC, Pratt M, Venugopal K, Chau J, Sjöström M, IPS Group. The descriptive epidemiology of sitting. A 20-country comparison using the International Physical Activity Questionnaire (IPAQ). Am J Prev Med 2011; 41(2):228-235.. This approach helps to understand both the composition of Total SB and associated factors, which may differ by domain¹³13 O’Donoghue G, Perchoux C, Mensah K, Lakerveld J, van der Ploeg H, Bernaards C, Chastin SF, Simon C, O’Gorman D, Nazare JA, DEDIPAC Consortium. A systematic review of correlates of sedentary behaviour in adults aged 18-65 years: a socio-ecological approach. BMC Public Health 2016; 16:163.^,1414 Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: a systematic review. Am J Prev Med 2012; 42(3):e3-28..

Few epidemiological studies have examined SB in Brazil⁸8 Knuth AG, Malta DC, Dumith SC, Pereira CA, Morais Neto OL, Temporao JG, Penna G, Hallal PC. Practice of physical activity and sedentarism among Brazilians: results of the National Household Sample Survey-2008. Cien Saude Colet 2011; 16(9):3697-3705.^,1515 Gomes VB, Siqueira KS, Sichieri R. Physical activity in a probabilistic sample in the city of Rio de Janeiro. Cad Saude Publica 2001; 17(4):969-976.

16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614.

17 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.^-1818 Suzuki CS, Moraes SA, Freitas IC. Sitting-time means and correlates in adults living in Ribeirao Preto-SP, Brazil, in 2006: OBEDIARP project. Rev Bras Epidemiol 2010; 13(4):699-712. and only one investigated behavior across different domains¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614.. Little is known about the combined contribution of demographic, socioeconomic, behavioral, and health factors on the distribution of SB in population groups in developing countries. The survey “Condições de Vida e Saúde de Mulheres Adultas: Estudo de Base Populacional no Vale dos Sinos. Avaliação após 10 Anos” (The Living and Health Conditions of Adult Women: a Population-Based Study in Vale dos Sinos. A 10-Year Follow-up) provides an opportunity to investigate SB in this segment of the population. The objective of the present study was therefore to describe SB among these women across leisure, occupation, and transport domains (LSB, OSB, and TSB, respectively) and determine the factors associated with excessive sedentary behavior in each domain (ELSB, EOSB, and ETSB, respectively).

Methods

Conducted in 2015, the Living and Health Conditions of Adult Women survey is a cross-sectional study that investigated a representative sample of women aged between 20 and 69 years living in São Leopoldo. The following individuals were excluded: pregnant women; those mentally incapable of answering the questionnaire, based on the observations of the interviewer and confirmed by a person living in the household; and women unable to participate due to health reasons in the week prior to the interview.

São Leopoldo belongs to the Metropolitan Region of Porto Alegre and is located 33km from the capital of the State of Rio Grande do Sul. It has an area of 102,738 km² and the population at the time of the 2010 Census was 214,087 inhabitants (population density 2060.31 inhabitants/km²) and showed a predominance of women (109,845)¹⁹19 Instituto Brasileiro de Geografia e Estatística (IBGE). Censo Demográfico 2010 [página na Internet]. [acessado 2014 Jun 10]. Disponível em: http://censo2010.ibge.gov.br
http://censo2010.ibge.gov.br... . The Municipal Human Development Index in 2010 was 0.739, which is classified as high and above the national average (0.727)²⁰20 Instituto Brasileiro de Geografia e Estatística (IBGE). Cidades@: São Leopoldo: RS [página na Internet]. 2016 [acessado 2014 set 30]. Disponível em: http://www.ibge.gov.br/cidadesat/painel/painel.php?codmun=432200
http://www.ibge.gov.br/cidadesat/painel/... .

The survey sample size was calculated for each of the various study outcomes, with the outcome “overdue cytopathologic test” and exposure variable “education level” resulting in the largest samples. Sample size was calculated considering a risk ratio of 2.0, 95% confidence level, 80% statistical power, and unexposed/exposed ratio of 1:2. The resulting sample size was increased by 10% to compensate for potential losses and refusals and 15% to control for confounding factors, resulting in a final sample of 1,281 women. The sample was selected using two-stage cluster sampling. In the first stage, 45 census tracts were randomly selected from the total number of tracts in the city (n = 371)¹⁹19 Instituto Brasileiro de Geografia e Estatística (IBGE). Censo Demográfico 2010 [página na Internet]. [acessado 2014 Jun 10]. Disponível em: http://censo2010.ibge.gov.br
http://censo2010.ibge.gov.br... , followed by the random sampling of 36 households in each selected tract. Losses and refusals amounted to 12.1% of the sample, resulting in a final sample of 1,126 interviewed women. This number was used to calculate the power to detect the association between exposure variables and SB outcomes, resulting in a power of ≥ 70% to detect significant associations (prevalence ratio of ≥ 1.2) for exposure variables affecting between 33.6% and 78% of the sample, adopting a 95% confidence interval.

Sedentary behavior (SB) was measured using a questionnaire developed by the authors based on a review of the literature²¹21 Clemes SA, David BM, Zhao Y, Han X, Brown W. Validity of two self-report measures of sitting time. J Phys Act Health 2012; 9(4):533-539.^,2222 Healy GN, Clark BK, Winkler EA, Gardiner PA, Brown WJ, Matthews CE. Measurement of adults’ sedentary time in population-based studies. Am J Prev Med 2011; 41(2):216-227. and an existing instrument¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614.. The questionnaire was developed to enable the inclusion of sedentary activities in both sitting and reclining postures, in accordance with the definition of SB, and record activities on both weekdays and weekends. The following situations and/or places were included: a) computer, tablet or cellphone use for work/study at home; b) computer, tablet or cellphone use for leisure at home; c) watching TV; d) motorized transport (car, motorcycle, train, bus); e) the workplace, f) at college, on a course, or at university; g) drinking mate, h) visiting/seeing friends; and i) other activities (reading, religious activities, and manual activities). In the case of engagement in combined sedentary activities, the respondent was asked to report the main activity. Total SB and total leisure, occupation (including work and study), and transport SB (LSB, OSB, and TSB, respectively), expressed in minutes per day, were calculated considering different combinations of the situations and places outlined above: Total SB (all situations and places); LSB (b, c, g, and h); OSB (a, e, and f), and TSB (d). The totals were calculated based on the total amount of the time spent engaging in each activity each day divided by 7. The reliability of the questionnaire was tested using the test-retest method on sample of 97 study participants, resulting in correlation coefficients of 0.79, 0.79, and 0.82 (strong correlation) for Total SB, LSB, and OSB, respectively, and 0.60 (moderate correlation) for TSB.

For the independent variables we used a standardized, pre-coded, and pre-tested questionnaire based on different instruments administered by an interviewer. The questionnaire included the following demographic, socioeconomic, and behavioral variables: demographic variables - age (categorized in 10-year groups), skin color (white, non-white), marital status (with a partner, without a partner); socioeconomic variables - economic status (class A/B, C, D/E)²³23 Associação Brasileira de Empresas de Pesquisa (ABEP). Critério Brasil: Critério de classificação econômica 2015 [página na Internet]. [acessado 2014 ago 10]. Disponível em: http://www.abep.org/criterio-brasil
http://www.abep.org/criterio-brasil... , education level (0 to 4, 5 to 7, 8 to 10, 11 to 14, ≥ 15 years), per capita family income (number of minimum salaries in quartiles), employed (yes; no); behavioral variables - smoking (non-smoker, smoker), alcohol intake (< 30g/day, ≥ 30g/day)²⁴24 Costa JS, Silveira MF, Gazalle FK, Oliveira SS, Hallal PC, Menezes AM, Gigante DP, Olinto MT, Macedo S. Heavy alcohol consumption and associated factors: a population-based study. Rev Saude Publica 2004; 38(2):284-291.^,2525 Moreira LB, Fuchs FD, Moraes RS, Bredemeier M, Cardozo S, Fuchs SC, Victoria CG. Alcoholic beverage consumption and associated factors in Porto Alegre, a southern Brazilian city: a population-based survey. J Stud Alcohol 1996; 57(3):253-259., leisure time PA (≥ 150 min/week, < 150 min/week)⁴4 World Health Organization (WHO). Global recommendations on physical activity for health. Geneva: WHO; 2010., and transport PA (yes, no). For simplification purposes, the physical activity items covered only transport and leisure using questions adapted from the short International Physical Activity Questionnaire (IPAQ)²⁶26 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.. Intensity of the activity (moderate/vigorous) was asked in the case of an affirmative answer. The questionnaire also included the following items: household cars (none; one; two or more); household computers (none; one; two or more); children in the household (none; one; two or more); and self-reported health (excellent/very good/good, fair/bad).

The interviews were conducted by trained interviewers who participated in the pilot study using a census tract not selected in the sampling phase. Data collection was conducted by a group of researchers over an 8-month period. Data quality was tested on a random sample of 10% of the respondents using a sample of the questions from the questionnaire with fixed responses in the short-term (age, number of children, etc.).

The study was approved by the Research Ethics Committee of the Vale do Rio dos Sinos University and all participants signed an informed consent form.

The data was double entered into the EpiData software version 3.1 to check and correct for possible entry errors. Descriptive analysis was performed using the IBM SPSS software version 22.0 (IBM Corp., Armonk, United States). Since the data were not normally distributed, they were described with medians and interquartile ranges. Excessive SB was defined using the corresponding median of each domain as a cut-off point. This procedure was adopted by previous studies because a SB threshold for health risk has not been established¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614.^,2727 Storgaard RL, Hansen HS, Aadahl M, Glumer C. Association between neighbourhood green space and sedentary leisure time in a Danish population. Scand J Public Health 2013; 41(8):846-852.. The data were expressed as percentages with their respective 95% confidence interval (95% CI). Since some women reported unreal Total SB values (> 24h/day), the maximum value was defined as 1,140 minutes per day, considering a minimum of 5 hours of sleep per day and values above this cut-off were replaced by the median (1.1% of the sample). Associations were tested using Poisson regression with robust error variance²⁸28 Barros AJ, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol 2003; 3:21. and the statistical software Stata MP 14.0 (Stata Corp., College Station, the United States). Variables that obtained p ≤ 0.20 in the bivariate analysis were included in the adjusted analysis, performed using a conceptual model comprising three levels of determination: level 1, including the demographic variables adjusted to each other; level 2, including the socioeconomic variables adjusted to each other and to the variables that obtained p ≤ 0.20 in level 1; and level 3, including the behavioral variables and household cars, children in the household, and self-reported health adjusted to each other and the variables that obtained p ≤ 0.20 in the previous levels. Marital status, employment, household cars, children in the household, self-reported health, and the behavioral variables were not included in the EOSB model because it is understood that these factors do not influence this outcome. Marital status and household computers were not tested in the ETSB model for the same reason. Variables with p < 0.05 were considered to be significantly associated with the outcome. In view of the sample design, the analyses were performed using Stata’s svy command.

Results

The mean age of the respondents was 43.3 years (SD±13.4) and the majority of the sample were white (74.4%), had a partner (63.8%), and lived in a household without a child (59.1%). Average education level was 9.8 years (SD±10.8) and the majority of the respondents worked (56%), had a per capita income of < 1.5 minimum salaries (74.7%), and belonged to economic class C (52.8%). The majority of the sample lived in households with at least one car and computer (62.4% and 63%, respectively). A large majority of respondents did not practice a minimum of 150 minutes of leisure time PA per week (85.7%). On the other hand, the majority of the sample did not report alcohol abuse (97.5%), were not smokers (81.5%), and reported excellent/very good/good self-reported health (66.3%) (Table 1).

The medians and interquartile ranges for Total SB, LSB, OSB, and TSB were 271.4 min/day (150.0-463.2), 163.9 min/day (86.8-270.5), 51.4 min/day (0-257, 1), and 17.1 min/day (5.7-37.3), respectively. The means and respective 95% confidence intervals for Total SB, LSB, OSB, and TSB were 319.4 min/day (306.8-331.9), 208.1 min/day (197.1-219.2), 141.5 min/day (95%CI: 128.7-154.4), and 33.1 min/day (95%CI: 29.8-36.2), respectively (data not shown in the Table).

The contribution of each domain to Total SB in the overall sample and by economic class is shown in Figure 1. This graph shows the mean SB values (min/day). In the overall sample, the predominant domain in Total SB was LSB (63%), followed by OSB (27%) and TSB (10%). There was no difference in the distribution of LSB across the different economic classes (p ≥ 0.05). However, the percentage contribution of LSB to Total SB in each class varied, accounting for 82% of Total SB in class D/E and 52% in class and A/B. There was a statistically significant difference in the distribution of OSB across classes (p < 0.001) and in the percentage contribution of OSB to Total SB in each class. The domain that contributed least to Total SB in each category was TSB (ranging from 9 to 11%). Although the percentage contributions of TSB to Total SB in each class were similar, there was a difference in the distribution of TSB across the classes (p < 0.001).

Table 2 shows that the variables that showed an association with ELSB after control for confounding factors were education level, employment, children in the household, and smoking. Respondents with 15 years or more of education were 30% more likely to show ELSB than those with 0 to 4 years of study, while women who did not work were 60% more likely to show ELSB than those who did. Respondents without children in the household and smokers were 40% and 30% more likely, respectively, to show ELSB (95%CI: 1.1-14).

All the variables tested in the adjusted analysis except household computers showed a statistically significant association with EOSB. The data also showed an inverse linear association between age group and EOSB and a direct linear association between socioeconomic class, education level, and income and the outcome. White women were 40% more likely than non-whites to show EOSB (Table 3).

All the variables tested in the adjusted analysis except smoking, leisure time PA, transport PA, and self-reported health were significantly associated with ETSB (Table 4). The data also showed that the likelihood of ETSB decreases with age, while white women were 20% more likely than non-whites to show ETSB. There was a direct linear association between socioeconomic class, education level, and income and ETSB. Women who did not work were 30% less likely to show ETSB than those who work (95% CI: 0.6-08). The likelihood of ETSB increased with the number of cars in the household.

Discussion

Half of the overall sample reported that they spent at least 270 minutes engaging in SB (equivalent to 4.5 hours per day), with LSB, OSB and TSB accounting for 63%, 27%, and 10% of Total SB, respectively. Certain variables were associated with all three domains, while others were domain-specific.

Both the median and mean values of Total SB observed in the present study (271.4 min/day; IQR: 150.0-463.2 and 319.4 min/day; 95% CI: 306.8-331.9) were similar to the findings of a study of a female sample in Pelotas¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614. (median: 240 min/day, IQR:135.0-480; mean: 323 min/day, 95% CI: 305,0-341.0). The respondents of the present study spent a mean of 50 more minutes a day engaging in SB than the women of a study in Ribeirão Preto¹⁸18 Suzuki CS, Moraes SA, Freitas IC. Sitting-time means and correlates in adults living in Ribeirao Preto-SP, Brazil, in 2006: OBEDIARP project. Rev Bras Epidemiol 2010; 13(4):699-712. (mean: 270.3 min/day; 95% CI: 256.3-284.23). However, these comparisons should be treated with caution since the studies used different instruments to measure SB¹²12 Bauman A, Ainsworth BE, Sallis JF, Hagstromer M, Craig CL, Bull FC, Pratt M, Venugopal K, Chau J, Sjöström M, IPS Group. The descriptive epidemiology of sitting. A 20-country comparison using the International Physical Activity Questionnaire (IPAQ). Am J Prev Med 2011; 41(2):228-235.. For example, the lower values among women in Ribeirão Preto may be partially explained by the use of the IPAQ, which contains only one question on time spent sitting, thus leading to a possible underestimation of total sitting time¹⁸18 Suzuki CS, Moraes SA, Freitas IC. Sitting-time means and correlates in adults living in Ribeirao Preto-SP, Brazil, in 2006: OBEDIARP project. Rev Bras Epidemiol 2010; 13(4):699-712.. In addition, the IPAQ does not consider time spent in engaging in TSB. The higher values observed by the present study may also be due to the fact that our instrument assessed SB in both sitting and reclining postures, while the studies mentioned above included only sitting posture.

The data presented show that half of the respondents reported spending at least 163.9 min/day engaging in LSB. The lack of studies using the same approach as the present study (for example, the inclusion of TV watching and leisure time computer use) hampers comparisons with national averages. Although our findings demonstrate that watching TV is the most frequent LSB, national data show a declining trend in the time spent on this activity in recent years¹⁷17 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..

Half of the respondents who worked or studied (n = 685) spent at least 50 min/day engaged in workplace and/or study sedentary activities. The mean values for these activities (141.5 min/day; 95% CI: 121.68-161.41) were similar to those reported by the study conducted in Pelotas (~150 min/day; 95% CI: 130-165)¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614.. Furthermore, the respondents of the present study spent a mean of 10 minutes more a day in TSB than the participants of the study in Pelotas (33 min/day; 95% CI: 29.8-36.2 compared to ~45 min/day; 95% CI: 40-50)¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614.. All the women in the sample were included in this domain, considering that for the purposes of this study transport includes travel to work and for study and leisure purposes. However, occupation can have a significant influence on time spent engaging in TSB. The fact that a large part of respondents were not working at the time of the study may therefore have contributed to the low values found for this domain. Though not investigated in this study, it is also possible that the city’s characteristics may facilitate other forms of transport, such as walking or bicycle, reducing time spent on motorized transport due to the shorter distances travelled between places²⁹29 Frank LD, Andresen MA, Schmid TL. Obesity relationships with community design, physical activity, and time spent in cars. Am J Prev Med 2004; 27(2):87-96.^,3030 Koohsari MJ, Sugiyama T, Kaczynski AT, Owen N. Associations of leisure-time sitting in cars with neighborhood walkability. J Phys Act Health 2014; 11(6):1129-1132..

The data presented show that the domain that contributed most to Total SB in the overall sample was LSB (63% do Total SB). This finding is important because LSB is the domain that has the greatest potential for reduction³¹31 Wijndaele K, Sharp SJ, Wareham NJ, Brage S. Mortality Risk Reductions from Substituting Screen Time by Discretionary Activities. Med Sci Sports Exerc 2017; 49(6):1111-1119., which is desirable considering the increased risk of morbidity and mortality associated with SB⁵5 Wilmot EG, Edwardson CL, Achana FA, Davies MJ, Gorely T, Gray LJ, Khunti K, Yates T, Biddle SJ. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia 2012; 55(11):2895-2905.^,66 Ford ES, Caspersen CJ. Sedentary behaviour and cardiovascular disease: a review of prospective studies. Int J Epidemiol 2012; 41(5):1338-1353.. Evidence from studies examining cardiometabolic risk markers show that reallocating 30 minutes of sedentary time with either light-intensity physical activity or moderate to vigorous physical activity may be beneficial for health³²32 Del Pozo-Cruz J, Garcia-Hermoso A, Alfonso-Rosa RM, Alvarez-Barbosa F, Owen N, Chastin S, Del Pozo-Cruz B. Replacing Sedentary Time: Meta-analysis of Objective-Assessment Studies. Am J Prev Med 2018; 55(3):395-402.. In the present study, this would require a 20% reduction in the time spent engaging in LSB. Figure 1 also shows that mean domain values and their respective percentage contribution to Total SB may vary according to exposure variable. We chose economic class to demonstrate these differences because socioeconomic inequalities can influence SB in different situations: at home, through the use of appliances and devices that can save time spent on household chores and promote leisure time sedentary activities (internet, computers, etc.); in the workplace, where new technologies mean work activities are performed in a sitting position; and transport, though access to motorized transport³³33 Bennie JA, Chau JY, van der Ploeg HP, Stamatakis E, Do A, Bauman A. The prevalence and correlates of sitting in European adults - a comparison of 32 Eurobarometer-participating countries. Int J Behav Nutr Phys Act 2013; 10:107.. Despite methodological differences in SB assessment, our results are similar to the findings of the Pelotas study¹⁶16 Mielke GI, Silva IC, Owen N, Hallal PC. Brazilian adults’ sedentary behaviors by life domain: population-based study. PLoS One 2014; 9(3):e91614., which showed a reduction in the percentage contribution of OSB and an increase in the percentage contribution of LSB to Total SB with decreasing economic status and similar percentage contributions of TSB across the three economic classes. One possible explanation for the differences in the percentage contributions of OSB and LSB across economic classes is that women with lower economic status tend to work in more physically demanding occupations and therefore spend less time in a sitting posture at work. However, although our findings show a large difference in the percentage contribution of LSB to Total SB in each economic class, there was no significant difference in the distribution of LSB across the classes. These findings are important because they show that interventions should be domain-specific³⁴34 Bennie JA, Pedisic Z, Timperio A, Crawford D, Dunstan D, Bauman A, van Uffelen J, Salmon J. Total and domain-specific sitting time among employees in desk-based work settings in Australia. Aust N Z J Public Health 2015; 39(3):237-242. and tailored to the specific characteristics of the target population.

The results of the adjusted analysis showed a direct linear association between education level and ELSB. This finding is consistent with the literature that looked at leisure time sedentary activities beyond time spent watching TV²⁷27 Storgaard RL, Hansen HS, Aadahl M, Glumer C. Association between neighbourhood green space and sedentary leisure time in a Danish population. Scand J Public Health 2013; 41(8):846-852.^,3535 Pomerleau J, McKee M, Robertson A, Vaasc S, Kadziauskiene K, Abaravicius A, Bartkeviciute R, Pudule I, Grinberga D. Physical inactivity in the Baltic countries. Prev Med 2000; 31(6):665-672.. It is therefore likely that the respondents with a higher level of education level performed other types of leisure time sedentary activities. Our study showed a positive association between not working and lower number of children in the household and ELSB, which suggests that women with more spare time spend this time on leisure time sedentary activities³⁶36 van der Ploeg HP, Venugopal K, Chau JY, van Poppel MN, Breedveld K, Merom D, Bauman AE. Non-occupational sedentary behaviors: population changes in The Netherlands, 1975-2005. Am J Prev Med 2013; 44(4):382-387.. Our findings show that smokers were more likely to show ELSB, suggesting clustering of unhealthy behaviors³⁷37 Katzmarzyk PT, Church TS, Craig CL, Bouchard C. Sitting time and mortality from all causes, cardiovascular disease, and cancer. Med Sci Sports Exerc 2009; 41(5):998-1005.. Although there is no evidence on which types of interventions are most effective in reducing ELSB³⁸38 Thraen-Borowski KM, Ellingson LD, Meyer JD, Cadmus-Bertram L. Nonworksite Interventions to Reduce Sedentary Behavior among Adults: A Systematic Review. Transl J Am Coll Sports Med 2017; 2(12):68-78., our findings suggest that actions should include the promotion of healthy lifestyles and raising awareness about the danger of spending excessive time engaging in SB³⁹39 Nooijen CFJ, Möller J, Forsell Y, Ekblom M, Galanti MR, Engström K. Do unfavourable alcohol, smoking, nutrition and physical activity predict sustained leisure time sedentary behaviour? A population-based cohort study. Prev Med 2017; 101:23-27.^,4040 Martin A, Fitzsimons C, Jepson R, Saunders DH, van der Ploeg HP, Teixeira PJ, Gray CM, Mutrie N, EuroFIT consortium. Interventions with potential to reduce sedentary time in adults: systematic review and meta-analysis. Br J Sports Med 2015; 49(16):1056-1063..

The data presented show an inverse linear association between age and EOSB. This association may be partially explained by the fact that OSB included time spent sitting for study, which tends to be greater in younger women. However, studies that assessed only work SB reported similar findings⁴¹41 Saidj M, Menai M, Charreire H, Weber C, Enaux C, Aadahl M, Kesse-Guyot E, Hercberg S, Simon C, Oppert JM. Descriptive study of sedentary behaviours in 35,444 French working adults: cross-sectional findings from the ACTI-Cites study. BMC Public Health 2015; 15:379.. The results of the final model also showed an association between OSB and skin color, revealing that white women were 38% more likely to show EOSB than non-whites. A study assessing occupational differences and skin color showed that white women are more likely to work in administrative or technical activities than non-whites⁴²42 Oliveira AM, Miranda PR. Diferenças ocupacionais por raça e gênero no mercado de trabalho de trabalhadores no Brasil [Internet]. In: XI Encontro Nacional de Estudos Populacionais da Associação Brasileira de Empresas de Pesquisa 1998. [acessado 2018 Set 14]. Disponível em: http://www.abep.org.br/~abeporgb/publicacoes/index.php/anais/article/viewFile/946/911
http://www.abep.org.br/~abeporgb/publica... . All the socioeconomic variables were directly associated with EOSB, regardless of skin color, which is consistent with the findings of other studies⁴¹41 Saidj M, Menai M, Charreire H, Weber C, Enaux C, Aadahl M, Kesse-Guyot E, Hercberg S, Simon C, Oppert JM. Descriptive study of sedentary behaviours in 35,444 French working adults: cross-sectional findings from the ACTI-Cites study. BMC Public Health 2015; 15:379.^,4343 Wallmann-Sperlich B, Bucksch J, Schneider S, Froboese I. Socio-demographic, behavioural and cognitive correlates of work-related sitting time in German men and women. BMC Public Health 2014; 14:1259.. Although not assessed by the present study, other studies have reported that working in certain types of occupations such as administrative, office, and service jobs increases the likelihood of high levels of SB, compared to more physically demanding occupations⁴⁴44 Chau JY, van der Ploeg HP, Merom D, Chey T, Bauman AE. Cross-sectional associations between occupational and leisure-time sitting, physical activity and obesity in working adults. Prev Med 2012; 54(3-4):195-200.^,4545 Jans MP, Proper KI, Hildebrandt VH. Sedentary behavior in Dutch workers: differences between occupations and business sectors. Am J Prev Med 2007; 33(6):450-454.. These studies suggest that women who show EOSB would benefit from workplace interventions, such as the use of workstations that create a variation in sitting postures⁴⁶46 Hutcheson AK, Piazza AJ, Knowlden AP. Work Site-Based Environmental Interventions to Reduce Sedentary Behavior: A Systematic Review. Am J Health Promot 2018; 32(1):32-47..

All the sociodemographic variables analyzed in the adjusted model showed an association with ETSB in the same direction as the associations with EOSB. Other variables that maintained a direct association with ETSB in the final model were working and having a household car. We did not find studies examining this domain with female-only samples, thus limiting comparisons. Further research is needed to determine whether having access to environments that provide favorable conditions for walking and cycling reduces ETSB among women⁴⁷47 Prince SA, Reed JL, McFetridge C, Tremblay MS, Reid RD. Correlates of sedentary behaviour in adults: a systematic review. Obes Rev 2017; 18(8):915-935..

One of the strengths of the present study is that it is a representative population-based study, meaning that the results can be extrapolated to the female population of São Leopoldo. Furthermore, SB was measured across various activities taking into account both weekdays and weekends. Finally, our analysis considered three different SB domains and a wide range of exposure variables.

Limitations include the fact that cross-sectional studies are limited in their ability to determine the cause-and-effect relationship between variables. Another limitation is the fact that the validity of the questionnaire used was not tested, thus leading to the possibility of over or underestimation of SB. It is also possible that some combined sedentary activities were doubly reported, overestimating the time spent engaging in Total SB. Finally, despite using medians to describe the characteristics of women engaging in ESB, these values do not necessarily represent a health risk. Evidence shows that the risk of all-cause mortality among adults increases when Total SB exceeds 7 hours per day⁴⁸48 Ku PW, Steptoe A, Liao Y, Hsueh MC, Chen LJ. A cut-off of daily sedentary time and all-cause mortality in adults: a meta-regression analysis involving more than 1 million participants. BMC Med 2018; 16:74.. Based on this finding, one-quarter of the sample of the present study have an increased risk of mortality, showing a minimum of 7.7 hours per day spent on SB. Thus, the use of the median may attenuate the measures of effect. However, to the best of our knowledge, criteria for classifying ESB in each domain have not been established.

LSB was the predominant domain in Total SB. The percentage contribution of each domain and distribution of SB varied according to economic class. The findings showed an association between demographic variables and EOSB and ETSB, but no association was found with ELSB. At least one socioeconomic variable was positively associated with the outcome in each domain. Having a job was the only variable that showed an association in opposite directions, being directly associated with ELSB and inversely associated with ETSB. In addition, having a household car and not living in a household without a child directly influenced SB in two domains. Of all the behavioral variables analyzed, only smoking was associated with ELSB.

The findings of this study contribute to the identification of women at greater risk of engaging in excessive SB and defining appropriate interventions to reduce SB in each domain. Future studies should examine social, political, and environmental variables to obtain a deeper understanding of the factors influencing SB.

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