Sedentary behavior is recognized as an important modifiable health risk behavior distinct from physical inactivity [1]. Activities conducted in the sitting position that involve low metabolic energy expenditure (≤1.5 metabolic equivalents task) such as watching TV and desk work, computer activities, and sitting during commuting constitute sedentary behavior [2,3]. Sedentary behavior can adversely impact physical and mental health and mortality independent of the physical activity level [2,4,5]. However, implementing breaks during sedentary activity, such as a short period of standing, and physical activity between prolonged periods of sitting, can potentially benefit physical and metabolic health irrespective of physical activity level and sitting time [6,7]. Specific interventions separate from increasing physical activity may be needed to reduce sedentary behavior, given the possible distinct influence of sedentary behavior on overall health [3].

Understanding the factors that influence sedentary behavior is crucial to identify the at-risk population and target interventions to reduce sedentary behavior. Current literature shows that age [2,8-10], sex [2,11], marital status [11], education [2,8,11], employment status [2,9,11-13], income [2,8,11,12], ethnicity [9], personal beliefs [2], and area of residence [8,13] are sociodemographic correlates of sedentary behavior. Health and behavioral factors, such as obesity [2,8,11,13], insufficient physical activity [2,8,11,13], alcohol use [8], and smoking status [2], were also found to be associated with sedentary behavior. Additionally, individuals with poor physical health, increased prescribed medications [9,13], depressive symptoms, low quality of life [2,14], disability, and chronic conditions [9,11,13] have higher odds of sedentary behavior. Environmental factors such as traffic, pollution, safety, lack of green spaces, and lessened access to sidewalks and recreational facilities are also thought to promote sedentary behavior and prevent physical activity [11,15-17].

The 2014 Bhutan National Survey for Noncommunicable Disease Risk Factors and Mental Health (referred to as the Bhutan STEPS Survey in the present study) showed that the mean sitting time per day among adults was 148.0 minutes [18]. A similar survey of the capital city in 2007 reported a mean time spent in sedentary behavior of 174.2 minutes per day, with higher time among older adults [19]. Both surveys reported significantly increased mean sitting time among women compared to men, which may indicate an existing within-population variation in sex. A more recent survey among school-going children found that around 30% spent ≥3 hours per day engaged in sedentary activities, and only 23.5% were physically active [20]. To date, no studies have explored the factors that influence sedentary behavior in Bhutan. Review studies also found that data on the correlates of sedentary behavior in low- and middle-income countries are limited [11,12]. We aimed to bridge this gap in the body of knowledge by examining the factors associated with sedentary behavior among adults using data from the 2014 Bhutan STEPS Survey, with an emphasis on examining sex differences.

The mean age of the participants was 40.1 years. The overall weighted prevalence of sedentary behavior was 8%. The characteristics of the study sample and the distribution of sedentary behavior are presented in Table 1 for the overall, female, and male sample populations. Overall, the prevalence of sedentary behavior was higher among females (10.3%), those who were ≤30 years of age (13.3%), single individuals (18.4%), individuals with a secondary level of education or higher (23.2%), employed (13.2%) or unemployed (13.4%) individuals, high income earners (14.9%), and urban residents (18.3%). Those who were physically less active (22.8%), non-smokers (8.3%), underweight (13.2%), overweight/obese (9.1%), had high blood sugar levels (12.7%), or had normal blood pressure (9%) also reported higher sedentary behavior. For individual female and male sample groups, similar consistent prevalence and distribution of sedentary behavior were observed for almost all factors.

In the full sample, bivariate analysis showed that females and those who were young, single, had a primary level of education or higher, had medium or high income, and resided in urban areas were more likely to be sedentary (Table 2). The odds of sedentary behavior were also greater among those who were physically less active, underweight, and had high blood sugar, while those who smoked, were selfemployed, and were hypertensive had lower odds. In the male and female subsamples, the associations retained a similar direction for most independent variables. However, in both females and males, smoking and being underweight became non-significant, and being hypertensive was associated in females, while being overweight or obese was assosciated only in males.

For the overall sample, multivariable analysis showed that two demographic factors (sex and marital status), four socioeconomic factors (education, employment, household income, and place of residence), and two health and behavioral factors (physical activity and high blood sugar) were significantly associated with sedentary behavior (Table 3). Specifically, being female (AOR, 2.50; 95% CI, 1.75–3.58) and single (AOR, 2.22; 95% CI, 1.27–3.89) were associated with increased odds of sedentary behavior compared to their counterparts. The odds of increased sedentary behavior were also higher among urban residents (AOR, 2.66; 95% CI, 1.29–5.48), those with a primary level of education or higher (AOR, 1.81; 95% CI, 1.18–2.79), and those from highincome households (AOR, 2.05; 95% CI,1.14–3.64). Compared to those who were unemployed, those who were self-employed (AOR, 0.55; 95% CI, 0.35–0.85) had reduced odds of sedentary behavior. The likelihood of sedentary behavior was 2.25 (95% CI, 1.28–3.96) and 1.97 (95% CI, 1.13–3.45) times higher among those who were physically less active and who had high blood sugar, respectively.

For the female subsample, being single, having primary level of education or higher, residing in urban areas, and being physically less active were associated with a higher likelihood of having sedentary behavior. By contrast, self-employed females had reduced odds of sedentary behavior compared to those who were unemployed. In the male subsample, similar to females, those who were single, had a primary level of education or higher, and resided in urban areas had a higher likelihood of being sedentary, and the association for these variables appeared more pronounced in males. However, employment, household income, and physical activity were not significant factors influencing sedentary behavior among men. The VIFs were less than 10, indicating that multicollinearity was not an issue in the regression analysis.

To our knowledge, this is the first study from Bhutan that examined factors associated with sedentary behavior with comparison of sex differences. The overall prevalence of sedentary behavior was 8.2%. With a two-fold significantly higher prevalence among females, roughly one in 10 Bhutanese women were sedentary. A study that examined nationally representative data from six low- and middle-income countries also reported an overall sedentary behavior prevalence of 8.3%, although the prevalence varied from 4.6% in South Africa to as high as 17.7% in Russia [13]. Analysis of the total sample population demonstrated that being female, being single, high education level, high income, urban residence, high blood sugar levels, and inadequate physical activity were correlated with sedentary behavior. For the subsamples separated by sex, the common factors of sedentary behavior were being single, having primary education level or higher, and urban residence. Being self-employed was associated with reduced odds of sedentary behavior among females as well as the overall sample population. Particularly for females, the odds of sedentary behavior were higher among those who were physically less active and had a high income.

Consistent with the data in the literature [11,21,22], our study found that females were more likely to engage in sedentary behavior than males. Bhutanese women are more likely to have a higher body mass index, are physically less active [18] and experience more unpleasant feelings or emotions such as anxiety, sadness, and other signs of mental ill-health [23]. Inadequate physical activity, high body weight, and poor mental health are correlated with sedentary behavior [2,8,13,14]. Moreover, our results also showed that less physically active females were more likely to be sedentary. Similar to the findings of previous studies [9,21], our findings suggest that being married was associated with reduced odds of high sitting time among both men and women. Married individuals may have children, and the increased associated responsibility may necessitate more physical movement. Studies have also shown that having children is associated with a lower sitting time [2,11]. Single individuals may spend more time using computers and watching TV than those married [22]; thus, they may be more sedentary.

Although young individuals tended to be more sedentary, this association was not significant in the multivariate analysis. Older adults (≥60 years of age) are shown to have higher levels of sedentary behavior that increases with age, with more elderly males spending more time engaged in sedentary activities than females [10,11,22]. Only individuals aged 18–69 years were recruited for the 2014 Bhutan STEPS Survey; therefore, our data on older individuals is somewhat limited. The available data suggest that age is positively associated with TV viewing and negatively associated with computer use, while the findings are mixed for generalized screen time and sitting [2]. The lack of information on domain-specific sedentary activities and limited age range of individuals assessed might explain this discrepancy.

Our findings showed that education level and household income were directly associated with sedentary behavior. Our results replicate the data in the literature that show a positive association between socioeconomic status and sedentary behavior [11,12,17,21]. Greater use of motor vehicles and technology and sedentary occupations may explain this association. Easy access to electronic gadgets, such as computers and notepads, can lead to increased screen time. Moreover, those with higher education levels may be more likely to be employed in professions that involve sitting while working [11]. Nevertheless, higher education level and employment are also associated with lower leisure-time sedentary behavior [12]. This sitting duration could have been captured in the total sitting time in our study.

Females from wealthier households had higher odds of sedentary behavior, while self-employed females had lower odds. Owing to financial security, women from wealthy households may be less likely to undertake paid jobs or perform daily household chores, increasing the probability of being sedentary. Self-employment is associated with better physical and mental health [24]. Psychological benefits from greater autonomy and the consequent physical health gains, and flexible working hours that may enable healthy behaviors such as physical activity, may provide some explanation [24]. Self-employed females may have better control over the way they work and may use skills that enable them to engage in healthy behaviors. A previous study showed that self-employed females reported a higher level of well-being, which may be attributable to better autonomy related to being self-employed [25]. However, being unemployed was found to be associated with sedentary behavior [13]. Those unemployed may have more time at their disposition for leisure activities, such as watching TV [26]. They may also opt for cheaper recreational activities such as TV, and time spent watching TV can reduce the time for higher intensity physical activity [2]. Moreover, unemployed individuals may have other chronic conditions that may prohibit physical movement [13]. In the Asian context, low priority for physical activity, upholding cultural traditions, lack of support, and perceived physical appearance may affect physical activity among women [27]. The unemployed category in our study included those who were retired, unable to work, and homemakers. In Bhutan, homemakers are usually female, and our data suggest that females are more sedentary.

In agreement with the data in the literature [12,13], our study found that those living in urban areas were more likely to be sedentary than their rural counterparts. Rural employment usually consists of agricultural jobs requiring physical movement, whereas the higher use of technology in urban settings may facilitate sedentary behavior. In Bhutan, rural residents largely depend on farming for their livelihood. Furthermore, urban environmental features, such as high traffic and crime, may promote prolonged sitting [11,15]. Presently, urban Bhutan is experiencing increases in traffic, air pollution, and crime partly driven by an increase in rural-urban migration [28,29]. These environmental attributes may also promote the use of cars and affect mental health, which, in turn, can influence sedentary behavior.

Inadequate physical activity and high blood sugar levels were correlated with sedentary behavior. This aligns with data in the literature [9,11,13,17]. Those with chronic conditions might be physically less active and may have a greater number of comorbid conditions associated with sedentary behavior, possibly due to mobility restrictions, discomfort, or mental health problems [13]. However, sedentary behavior may also predict blood sugar and physical activity levels. The cross-sectional study design prevents the assessment of the directionality of the association. The findings regarding inadequate physical activity may be more relevant to the development of targeted interventions, given that high physical activity may potentially attenuate the detrimental effects of sedentary behavior [30]. The association for physical activity was robust only among females, which supports data indicating that Bhutanese women are likely to be less physically active than men [18]. We found no strong evidence for an association between body weight and sedentariness, which supports the findings of a previous systematic review [4] and study [17]. However, specific measures of sitting time, such as TV viewing, were found to be associated with being overweight [31], implying that the association may depend on domain-specific sedentary behavior.