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Associations among self-perceived work and life stress, trouble sleeping, physical activity, and body weight among Canadian adults
Preventive Medicine 96 (2017) 16–20
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Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Associations among self-perceived work and life stress, trouble sleeping, physical activity, and body weight among Canadian adults Hugues Sampasa-Kanyinga a,⁎, Jean-Philippe Chaput b,c a b c
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, Canada Department of Pediatrics, Faculty of Medicine, University of Ottawa, Ottawa, Ontario K1H 8L1, Canada
a r t i c l e
i n f o
Article history: Received 9 September 2016 Received in revised form 7 December 2016 Accepted 13 December 2016 Available online 18 December 2016 Keywords: Work stress Life stress Trouble sleeping Physical activity Excess weight Body mass index
a b s t r a c t We investigated the associations among self-perceived work and life stress, trouble sleeping, physical activity and body weight among Canadian adults, and tested whether trouble sleeping and physical activity moderated the relationship between work/life stress and body weight, and whether work/life stress and physical activity moderated the relationship between trouble sleeping and body weight. Data on 13,926 Canadian adults aged 20 years and older were derived from the nationally representative 2012 Canadian Community Health Survey. After adjusting for age, sex, education level, household income, marital status and job insecurity, self-perceived work and life stress and trouble sleeping were associated with a higher BMI. The associations of work and life stress with higher BMI were independent of trouble sleeping and physical activity in addition to other covariates, while that of trouble sleeping and higher BMI was independent of work and life stress. Results further indicated that trouble sleeping among inactive participants was related to a higher BMI; however, this relationship was almost null for adults who self-reported being physically active for about 8 h/week. These findings suggest that work and life stress are both associated with excess weight in adults, regardless of physical activity level, while the link of trouble sleeping with BMI varies by physical activity level. Future research is necessary to determine whether reducing work and life stress and improving sleep habits would benefit the prevention of weight gain and obesity. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Obesity continues to be a major public health problem worldwide. In 2014, it was estimated that N1.9 billion adults aged 18 years and older were overweight. Of these, over 600 million were obese (World Health Organization, 2016). Obesity results from an imbalance between energy intake and expenditure (Hall et al., 2012; Hill et al., 2012), and has been associated with an increased risk of several chronic diseases and premature mortality (Berenson et al., 1998; Bigaard et al., 2004; Pi-Sunyer, 2002). Stress has been identified as one of numerous factors influencing energy balance and contributing to the development of obesity (Bose et al., 2009; Torres & Nowson, 2007). Stress is often defined as the generalized, non-specific response of the body to any factor that overwhelms, or threatens to overwhelm, the body's compensatory abilities to maintain homeostasis (Sherwood, 2001), while work stress is defined as the harmful physical and emotional responses that occur when job requirements do not match the worker's capabilities,
⁎ Corresponding author at: School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada. E-mail address: [email protected] (H. Sampasa-Kanyinga).
http://dx.doi.org/10.1016/j.ypmed.2016.12.013 0091-7435/© 2016 Elsevier Inc. All rights reserved.
resources, and needs (National Institute for Occupational Safety and Health (NIOSH), 1999). Work and life stress are omnipresent in today's modern society and are associated with negative health behaviors and outcomes (McEwen, 1998; Wang, 2005). It is therefore important to identify protective factors for stressed individuals. Research has shown that physical activity is inversely associated with stress (Salmon, 2001; Schnohr et al., 2005), and that stress may impair efforts on adopting or maintaining healthy physical activity levels (Stults-Kolehmainen & Sinha, 2014). Furthermore, insufficient sleep has been identified as an important correlate of stress (Han et al., 2012; Kalimo et al., 2000). Åkerstedt et al. (2002) found that the risk of sleep disturbances was related to numerous factors, including work stress, high BMI, and physical inactivity. Although the links between work/life stress and excess weight and between sleep quality and excess weight have been previously documented (Åkerstedt et al., 2002; Block et al., 2009; Moore & Cunningham, 2012; Wardle et al., 2011), the role of trouble sleeping and/or physical activity on these relationships is largely unknown. Adequate sleep and physical activity are well known to contribute to quality of life, healthy weights and the prevention of several chronic diseases (Chaput, 2014; Chaput et al., 2009; Durstine et al., 2013; Kruk, 2007; Liu et al., 2013). Short sleep duration and poor sleep quality are
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associated with higher body weight and adiposity (Cappuccio et al., 2008; Markwald et al., 2013; Spaeth et al., 2013). Regular physical activity is a well-known treatment intervention for obesity and stress (Hill & Wyatt, 2005; Janiszewski & Ross, 2007). In parallel, having a good night's sleep has protective effects on stress and research has recently begun to investigate sleep in relation to obesity treatment and prevention (Hamilton et al., 2007; Magee et al., 2010). However, it is unclear whether trouble sleeping and physical activity have only direct links to excess weight or can also moderate the negative effects of work and like stress on body weight. Given the epidemic nature of obesity and its negative effects on health and well-being, it is also important to understand whether self-reported work and life stress contribute to excess weight independently of trouble sleeping and physical activity. The first objective of the present study was to examine the associations among self-perceived work and life stress, trouble sleeping, physical activity, and body weight among Canadian adults. The second objective of this study was to test whether trouble sleeping and physical activity moderate the relationships between work/life stress and body weight, and whether work/life stress and physical activity moderate the relationship between trouble sleeping and body weight. Undertaking such a study will help to better inform the development of intervention strategies aimed at preventing excess weight and its complications in adults. 2. Methods 2.1. Study population Data were derived from the 2012 cycle of the Canadian Community Health Survey (CCHS): Mental Health, a nationally representative crosssectional survey of Canadian household residents aged 15 years and older living in any of the 10 provinces, that was conducted by Statistics Canada (2013). Excluded were people living on reserves and other Aboriginal settlements, full-time members of the Canadian Armed Forces, and residents of institutions. These exclusions represented 3% of the national population. The survey uses a complex multi-stage sampling procedure, based on random selection of geographical areas, followed by selection of households within those areas, and finally by selection of one respondent per household. A total of 25,113 interviews were conducted using computer assisted personal interviewing. With a survey response rate of 77%, most interviews (87%) were conducted in person; the remainder were conducted by telephone. Our analyses were restricted to individuals aged between 20 and 74 years who have worked at a job or business at any time in the past 12 months, and to women who were not pregnant at the time of survey administration, because body mass index (BMI) was not calculated for participants aged b 20 years (N = 2024) or pregnant women (N = 208). Also, the perceived work stress question was not asked to participants who reported that they did not work at a job or business at any time in the past 12 months (N = 6471) and who were aged 75 years or over (N = 2767). After exclusion, the final sample included 14,416 participants. A complete description of the study methodology is available on-line (Statistics Canada, 2013). 2.2. Measures 2.2.1. Self-perceived work and life stress The measures of work and life stress are the respondent's subjective rating of work and life stress. They were assessed by the following questions: “thinking about the amount of stress in your life, would you say that most days are...?” and “the next question is about your main job or business in the past 12 months. Would you say that most days at work were...?”. Response options included not at all stressful, not very stressful, a bit stressful, quite a bit stressful, or extremely stressful. Responses were scored on a 5-point Likert scale, with higher scores indicating greater perceived work or life stress.
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2.2.2. Trouble sleeping Trouble sleeping was measured using the following item: “How often do you have trouble going to sleep or staying asleep?” Response options included none of the time, a little of the time, some of the time, most of the time, and all of the time. Responses were scored on a 5-point Likert scale, with higher scores indicating more frequent trouble sleeping. 2.2.3. Physical activity Physical activity was measured with the following question: “In the past 7 days, how many times did you participate in moderate or vigorous physical activity?” Moderate or vigorous physical activity causes an increase in breathing and heart rate. Physical activity related to transportation includes brisk walking and cycling. Time was provided in hours per week. 2.2.4. BMI BMI was based on self-reported height and weight, and was calculated by dividing weight in kilograms by height in metres squared. BMI values have been regrouped to a minimum of 14 and a maximum of 58. These ranges were determined by Statistics Canada, and BMI data were not provided outside this range. In total, 400 participants had missing values for BMI and have been excluded from our analyses. 2.2.5. Covariates Covariates included sociodemographic characteristics (age, sex, education level, household income, and marital status), and job insecurity. Age was measured in years and grouped into 4 categories, including 20 to 34, 35 to 49, 50 to 64, and 65 or more. Respondents reported their highest education level and response options included less than secondary, secondary graduation, some postsecondary, and postsecondary graduation. Household income represented the total income before taxes, including income from all sources and across all household members. This was grouped into the following five categories: less than $15,000, $15,000 to $29,999, $30,000 to $49,999, $50,000 to $79,999 and $80,000 or more. Marital status was grouped into three categories: married or common-law; widowed, separated or divorced; and never married. Participants were also asked to indicate whether their job security was good. Response options included strongly agree, agree, neither agree nor disagree, disagree, or strongly disagree. Responses were scored on a 5-point Likert scale, with higher scores indicating greater perceived job insecurity. 2.3. Statistical analyses Analyses were conducted with STATA (version 14.0, Stata Corp., College Station, Texas). Missing data were handled through listwise deletion reducing the sample size by 3.4% (i.e. from 14,416 to 13,926). All analyses were weighted and accounted for the complex survey design of the survey. Since there was no statistically significant sex interaction between independent variables and BMI, data for both sexes were combined to maximize power. In order to achieve normality criteria, the outcome variable of BMI was log-transformed in the analytical steps. With regards to descriptive analyses, categorical variables were described by count and percentage, while continuous variables were described by their means and standard deviations. Univariate (Model 1) and multivariate linear regression analyses were use to examine the associations between work and life stress with body mass index. Covariates included age, sex, education level, household income, marital status and job insecurity (Model 2); all variables in Model 2 + physical activity (Model 3); and all variables in Model 3 + trouble sleeping (Model 4). Similarly, univariate (Model 1) and multivariate linear regression analyses were use to examine the association between trouble sleeping and body mass index. Covariates included age, sex, education level, household income, marital status and job insecurity (Model 2); all variables in Model 2 + physical activity (Model 3); and all variables
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in Model 3 + work and life stress (Model 4). Two-way interactions were also tested to examine whether trouble sleeping and physical activity moderated the relationships between work/life stress and BMI, and whether work/life stress and physical activity moderated the relationships between trouble sleeping and BMI. Analyses were adjusted for age, sex, education level, household income, marital status and job insecurity (Model 1) and all variables in Model 1 + work and life stress (Model 2). The margins and marginsplot post-estimation commands in STATA were used to clarify significant interaction using the simple slopes approach, i.e., the slopes of the dependent variable on the independent variable when the moderator variable is held constant at different values running from the minimum to maximum value (Aiken et al., 1991). 3. Results Table 1 presents characteristics of the study population. Nearly twothird (66%) of the sample was aged b50 years and married/common law. Most participants achieved greater than a high school education (70%), and nearly three-in-five participants reported a household income of $80,000 or more. The average BMI and time spent in moderate-to-vigorous physical activity over the last 7 days were 26 kg/m2 and 4 h, respectively. Results of multiple linear regression analyses examining the associations between self-perceived work and life stress and BMI are summarized in Table 2. Before adjustment, self-perceived work (β = 0.009, p = 0.001) and life (β = 0.007, p = 0.014) stress showed linear relationships with BMI (Model 1). Results were similar after adjusting for age, sex, education level, household income, marital status, and job insecurity (Model 2). The associations of work (β = 0.011, p b 0.001) and life (β = 0.010, p b 0.001) stress with excess weight were also
Table 1 Characteristics of the study population. N (%) or mean ± SD Age 20–34 years 35–49 years 50–64 years 65 + years
4477 (31.3) 4301 (34.3) 4378(30.5) 770 (4.0)
Sex Male Female
7055 (54.5) 6871 (45.5)
Education Less than secondary Secondary graduation Some postsecondary Post secondary graduation
1258 (8.9) 2256 (15.2) 859 (6.2) 9553 (69.7)
Household income b$15,000 $15,000–29,999 $30,000–49,999 $50,000–79,999 $80,000+
403 (1.9) 1403 (7.1) 2558 (15.2) 2579 (17.6) 6983 (58.2)
Marital status Married or common law Separated, divorced, or widowed Never married Work stressa Life stressa Job insecuritya Trouble sleepinga Physical activity (hours in last 7 days) Body mass index (kg/m2)
7924 (66.2) 1985 (9.8) 4017 (24.0) 2.95 ± 1.03 2.87 ± 0.95 1.01 ± 1.04 2.14 ± 1.16 3.76 ± 4.18 26.2 ± 5.4
Data are presented as N (%) or mean ± SD. N = 13,926. a Responses were scored on a 5-point Likert scale, with higher score indicating greater perceived work/life stress, job insecurity, or more frequent trouble sleeping.
Table 2 Associations between work and life stress with body mass index among Canadian adults. β
SE
p-Value
Model 1 Unadjusted Work stress 0.009 0.003 0.001 Life stress 0.007 0.003 0.014 Model 2 Adjusted for age, sex, education level, household income, marital status and job insecurity Work stress 0.012 0.002 b0.001 Life stress 0.012 0.003 b0.001 Model 3 Adjusted for all variables in Model 2 + physical activity Work stress 0.012 0.002 b0.001 Life stress 0.012 0.003 b0.001 Model 4 Adjusted for all variables in Model 3 + trouble sleeping Work stress 0.011 0.003 b0.001 Life stress 0.010 0.003 b0.001 Body mass index was log-transformed. SE: standard error. N = 13,926.
independent of physical activity (Model 3) and trouble sleeping (Model 4) in addition to other covariates. Table 3 presents results of multiple linear regression analyses examining the association between trouble sleeping. Before adjustment, trouble sleeping (β = 0.005, p = 0.036) showed a linear relationship with BMI (Model 1). Results were similar after adjusting for age, sex, education level, household income, marital status, and job insecurity (Model 2: β = 0.008, p = 0.001). The association of trouble sleeping with BMI remained significant even after controlling for physical activity (Model 3) and work/life stress (Model 4; β = 0.013, p = 0.007) in addition to other covariates. The moderating role of physical activity on the relationships between trouble sleeping and BMI was further explored and is summarized in Table 4. Results indicated that physical activity was a significant moderator of the association between trouble sleeping and BMI before (Model 1) and after adjusting for work/life stress (Model 2) in addition to other covariates. Fig. 1 displays this interaction using the model adjusted for age, sex, education level, household income, marital status, job insecurity, and work and life stress. More trouble sleeping among inactive participants was related to a higher BMI; however, this relationship was almost null for adults who were physically active for about 8 h/week. In contrast, work stress or life stress were not significant moderators of the association between trouble sleeping and BMI (results not shown). Similarly, trouble sleeping and physical activity were not significant moderators of the relationships between work stress or life stress and BMI (results not shown).
Table 3 Association between trouble sleeping and body mass index among Canadian adults. β Model 1 Unadjusted Model 2 Adjusted for age, sex, education level, household income, marital status and job insecurity Model 3 Adjusted for all variables in Model 2 + physical activity Model 4 Adjusted for all variables in Model 3 + work and life stress Body mass index was log-transformed. SE: standard error. N = 13,926.
SE
p-Value
0.005 0.002 0.036
0.008 0.002 0.001
0.008 0.002 0.001
0.006 0.002 0.018
H. Sampasa-Kanyinga, J.-P. Chaput / Preventive Medicine 96 (2017) 16–20 Table 4 The moderating role of physical activity on the relationships between trouble sleeping and body mass index. β
SE
p-Value
Model 1 Adjusted for age, sex, education level, household income, marital status and job insecurity. Trouble sleeping 0.012 0.003 b0.001 Physical activity 0.0004 0.001 0.762 Trouble sleeping × physical activity –0.001 0.0005 0.025 Model 2 Adjusted for all variables in Model 1 + work and life stress Trouble sleeping 0.010 0.003 0.001 Work stress 0.008 0.003 0.003 Life stress 0.006 0.003 0.034 Physical activity 0.0006 0.001 0.659 Trouble sleeping × physical activity –0.001 0.0005 0.020 SE: standard error. N = 13,926.
4. Discussion The findings from the current study, based on a nationally representative sample of Canadian adults, showed that self-perceived work and life stress and trouble sleeping were associated with excess weight. The associations of work and life stress with excess weight were independent of trouble sleeping and physical activity in addition to other covariates, while that of trouble sleeping and excess weight was independent of work and life stress. Of particular interest, trouble sleeping among inactive participants was related to a higher BMI; however, this relationship was almost null for adults who were physically active for about 8 h/week, suggesting that high levels of physical activity could mitigate the adverse effects of trouble sleeping on BMI. However, longitudinal and experimental studies will be needed to confirm this observation. Our results are consistent with previous studies indicating that work and life stress are associated with excess weight among adults (Block et al., 2009; Moore & Cunningham, 2012; Wardle et al., 2011). However, the present study extends these studies by examining the moderating role of trouble sleeping and physical activity on these relationships. Our analyses showed that these associations are independent of trouble sleeping and physical activity levels, and that neither trouble sleeping nor physical activity moderated these relationships, indicating that the association between work/life stress and BMI did not vary by sleep
Fig. 1. Moderating role of physical activity on the relationship between trouble sleeping and body mass index. PA: physical activity; Hrs: hours. Trouble sleeping scale ranged from 1 (none of the time) to 5 (all of the time). Model is adjusted for age, sex, education level, household income, marital status, job insecurity, and work and life stress. N = 13,926.
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quality and/or physical activity level. It is nevertheless possible that the observed relationships are driven by unmeasured variables such as eating behaviour which is well known to influence BMI (Hays et al., 2002; Ma et al., 2003; Torres & Nowson, 2007). For example, Torres and Nowson indicated that stress-induced eating may be one factor contributing to the development of obesity (Torres & Nowson, 2007). This highlights the need for further studies. The observation that trouble sleeping is positively associated with BMI is consistent with previous research indicating that inadequate sleep is an important determinant of excess weight (Meyer et al., 2012; Nordin & Kaplan, 2010; Patel & Hu, 2008; Wheaton et al., 2011). For example, in a study of approximately 7000 middle-age adults in California followed for 29 years, Nordin and Kaplan found that consistent sleep discontinuity and impaired sleep continuity increased the risk of transition to obesity or of remaining obese (Nordin & Kaplan, 2010). To our knowledge, no previous study examined whether physical activity moderates the association between trouble sleeping and body weight among adults. Our finding that trouble sleeping among physically inactive participants was related to a higher BMI is in line with previous studies indicating that trouble sleeping and physical inactivity are related to excess weight (Hargens et al., 2013). Future studies are necessary to examine whether better sleep coupled to adequate physical activity level may help to achieve a healthy body weight. Our results also indicated that trouble sleeping among those who report very high levels of physical activity (i.e. N8 h/week) was negatively associated with BMI. This is not surprising because inadequate sleep summed to excessive physical activity may be more destructive for general well-being and body weight, thus potentially leading to weight loss. However, our findings revealed that the relationship between trouble sleeping and BMI was almost null for adults who are physically active for about 8 h/week. We could have expected to observe such findings at or near the recommended level of moderate-to-vigorous physical activity of 150 min/week (i.e. 2.5 h/week) for adults (Tremblay et al., 2011; World Health Organization, 2015). For additional health benefits, the World Health Organization posits that adults should increase their moderate-intensity physical activity to 300 min/week (i.e. 5 h/week), or equivalent (World Health Organization, 2015). Although the data used in the present study were derived from a nationally representative survey of adult population, it is possible that the study population is just more physically active than the general population or that the physical activity measure was affected by a desirability bias which could have leaded to an overestimation of physical activity levels. This emphasizes the need for future investigations using more objective measures of physical activity (e.g. accelerometry). Nevertheless, current findings are important and indicate that physical inactivity combined with trouble sleeping is related to a greater risk of excess weight, while excessive physical activity coupled to trouble sleeping is negatively associated with BMI. There are several limitations that need to be considered when interpreting the results of this study. First, it is not possible to determine the direction of the observed relationships because of the cross-sectional study design of the study. This emphasizes the need for further studies using longitudinal designs. Second, the psychometric properties of many measures used herein are unknown. Third, the present study used self-reported measures of physical activity and body weight and height. Future research may consider using more objective measures. Fourth, the present study did not adjust for eating behaviour. Given that the latter constitutes an important correlate of BMI and stress (Torres & Nowson, 2007), future studies may consider examining its role (as a covariate, moderator or mediator) on the relationships between work/life stress and BMI. Finally, there is a possibility of residual confounding by unmeasured variables (e.g. eating disorders and medication use). Despite these limitations, results of the present study may have important implications from a practical standpoint. Our results suggest that self-reporting being physically active for about 8 h/week could
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mitigate the adverse effects of trouble sleeping on BMI. However, achieving such an amount of physical activity per week may not be easy for everybody. Research has shown that a potentially important way to achieve the physical activity required for maintaining and improving health is through alternative, non-leisure forms of physical activity such as active transportation (i.e. walking or biking) (Berrigan et al., 2006). For example, walking is one of the least expensive and most broadly accessible forms of physical activity (Siegel et al., 1995), and it is easier to reach recommended physical activity targets through such a daily routine than occasional recreational activities (Berrigan et al., 2006). 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Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Associations among self-perceived work and life stress, trouble sleeping, physical activity, and body weight among Canadian adults Hugues Sampasa-Kanyinga a,⁎, Jean-Philippe Chaput b,c a b c
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, Canada Department of Pediatrics, Faculty of Medicine, University of Ottawa, Ottawa, Ontario K1H 8L1, Canada
a r t i c l e
i n f o
Article history: Received 9 September 2016 Received in revised form 7 December 2016 Accepted 13 December 2016 Available online 18 December 2016 Keywords: Work stress Life stress Trouble sleeping Physical activity Excess weight Body mass index
a b s t r a c t We investigated the associations among self-perceived work and life stress, trouble sleeping, physical activity and body weight among Canadian adults, and tested whether trouble sleeping and physical activity moderated the relationship between work/life stress and body weight, and whether work/life stress and physical activity moderated the relationship between trouble sleeping and body weight. Data on 13,926 Canadian adults aged 20 years and older were derived from the nationally representative 2012 Canadian Community Health Survey. After adjusting for age, sex, education level, household income, marital status and job insecurity, self-perceived work and life stress and trouble sleeping were associated with a higher BMI. The associations of work and life stress with higher BMI were independent of trouble sleeping and physical activity in addition to other covariates, while that of trouble sleeping and higher BMI was independent of work and life stress. Results further indicated that trouble sleeping among inactive participants was related to a higher BMI; however, this relationship was almost null for adults who self-reported being physically active for about 8 h/week. These findings suggest that work and life stress are both associated with excess weight in adults, regardless of physical activity level, while the link of trouble sleeping with BMI varies by physical activity level. Future research is necessary to determine whether reducing work and life stress and improving sleep habits would benefit the prevention of weight gain and obesity. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Obesity continues to be a major public health problem worldwide. In 2014, it was estimated that N1.9 billion adults aged 18 years and older were overweight. Of these, over 600 million were obese (World Health Organization, 2016). Obesity results from an imbalance between energy intake and expenditure (Hall et al., 2012; Hill et al., 2012), and has been associated with an increased risk of several chronic diseases and premature mortality (Berenson et al., 1998; Bigaard et al., 2004; Pi-Sunyer, 2002). Stress has been identified as one of numerous factors influencing energy balance and contributing to the development of obesity (Bose et al., 2009; Torres & Nowson, 2007). Stress is often defined as the generalized, non-specific response of the body to any factor that overwhelms, or threatens to overwhelm, the body's compensatory abilities to maintain homeostasis (Sherwood, 2001), while work stress is defined as the harmful physical and emotional responses that occur when job requirements do not match the worker's capabilities,
⁎ Corresponding author at: School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada. E-mail address: [email protected] (H. Sampasa-Kanyinga).
http://dx.doi.org/10.1016/j.ypmed.2016.12.013 0091-7435/© 2016 Elsevier Inc. All rights reserved.
resources, and needs (National Institute for Occupational Safety and Health (NIOSH), 1999). Work and life stress are omnipresent in today's modern society and are associated with negative health behaviors and outcomes (McEwen, 1998; Wang, 2005). It is therefore important to identify protective factors for stressed individuals. Research has shown that physical activity is inversely associated with stress (Salmon, 2001; Schnohr et al., 2005), and that stress may impair efforts on adopting or maintaining healthy physical activity levels (Stults-Kolehmainen & Sinha, 2014). Furthermore, insufficient sleep has been identified as an important correlate of stress (Han et al., 2012; Kalimo et al., 2000). Åkerstedt et al. (2002) found that the risk of sleep disturbances was related to numerous factors, including work stress, high BMI, and physical inactivity. Although the links between work/life stress and excess weight and between sleep quality and excess weight have been previously documented (Åkerstedt et al., 2002; Block et al., 2009; Moore & Cunningham, 2012; Wardle et al., 2011), the role of trouble sleeping and/or physical activity on these relationships is largely unknown. Adequate sleep and physical activity are well known to contribute to quality of life, healthy weights and the prevention of several chronic diseases (Chaput, 2014; Chaput et al., 2009; Durstine et al., 2013; Kruk, 2007; Liu et al., 2013). Short sleep duration and poor sleep quality are
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associated with higher body weight and adiposity (Cappuccio et al., 2008; Markwald et al., 2013; Spaeth et al., 2013). Regular physical activity is a well-known treatment intervention for obesity and stress (Hill & Wyatt, 2005; Janiszewski & Ross, 2007). In parallel, having a good night's sleep has protective effects on stress and research has recently begun to investigate sleep in relation to obesity treatment and prevention (Hamilton et al., 2007; Magee et al., 2010). However, it is unclear whether trouble sleeping and physical activity have only direct links to excess weight or can also moderate the negative effects of work and like stress on body weight. Given the epidemic nature of obesity and its negative effects on health and well-being, it is also important to understand whether self-reported work and life stress contribute to excess weight independently of trouble sleeping and physical activity. The first objective of the present study was to examine the associations among self-perceived work and life stress, trouble sleeping, physical activity, and body weight among Canadian adults. The second objective of this study was to test whether trouble sleeping and physical activity moderate the relationships between work/life stress and body weight, and whether work/life stress and physical activity moderate the relationship between trouble sleeping and body weight. Undertaking such a study will help to better inform the development of intervention strategies aimed at preventing excess weight and its complications in adults. 2. Methods 2.1. Study population Data were derived from the 2012 cycle of the Canadian Community Health Survey (CCHS): Mental Health, a nationally representative crosssectional survey of Canadian household residents aged 15 years and older living in any of the 10 provinces, that was conducted by Statistics Canada (2013). Excluded were people living on reserves and other Aboriginal settlements, full-time members of the Canadian Armed Forces, and residents of institutions. These exclusions represented 3% of the national population. The survey uses a complex multi-stage sampling procedure, based on random selection of geographical areas, followed by selection of households within those areas, and finally by selection of one respondent per household. A total of 25,113 interviews were conducted using computer assisted personal interviewing. With a survey response rate of 77%, most interviews (87%) were conducted in person; the remainder were conducted by telephone. Our analyses were restricted to individuals aged between 20 and 74 years who have worked at a job or business at any time in the past 12 months, and to women who were not pregnant at the time of survey administration, because body mass index (BMI) was not calculated for participants aged b 20 years (N = 2024) or pregnant women (N = 208). Also, the perceived work stress question was not asked to participants who reported that they did not work at a job or business at any time in the past 12 months (N = 6471) and who were aged 75 years or over (N = 2767). After exclusion, the final sample included 14,416 participants. A complete description of the study methodology is available on-line (Statistics Canada, 2013). 2.2. Measures 2.2.1. Self-perceived work and life stress The measures of work and life stress are the respondent's subjective rating of work and life stress. They were assessed by the following questions: “thinking about the amount of stress in your life, would you say that most days are...?” and “the next question is about your main job or business in the past 12 months. Would you say that most days at work were...?”. Response options included not at all stressful, not very stressful, a bit stressful, quite a bit stressful, or extremely stressful. Responses were scored on a 5-point Likert scale, with higher scores indicating greater perceived work or life stress.
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2.2.2. Trouble sleeping Trouble sleeping was measured using the following item: “How often do you have trouble going to sleep or staying asleep?” Response options included none of the time, a little of the time, some of the time, most of the time, and all of the time. Responses were scored on a 5-point Likert scale, with higher scores indicating more frequent trouble sleeping. 2.2.3. Physical activity Physical activity was measured with the following question: “In the past 7 days, how many times did you participate in moderate or vigorous physical activity?” Moderate or vigorous physical activity causes an increase in breathing and heart rate. Physical activity related to transportation includes brisk walking and cycling. Time was provided in hours per week. 2.2.4. BMI BMI was based on self-reported height and weight, and was calculated by dividing weight in kilograms by height in metres squared. BMI values have been regrouped to a minimum of 14 and a maximum of 58. These ranges were determined by Statistics Canada, and BMI data were not provided outside this range. In total, 400 participants had missing values for BMI and have been excluded from our analyses. 2.2.5. Covariates Covariates included sociodemographic characteristics (age, sex, education level, household income, and marital status), and job insecurity. Age was measured in years and grouped into 4 categories, including 20 to 34, 35 to 49, 50 to 64, and 65 or more. Respondents reported their highest education level and response options included less than secondary, secondary graduation, some postsecondary, and postsecondary graduation. Household income represented the total income before taxes, including income from all sources and across all household members. This was grouped into the following five categories: less than $15,000, $15,000 to $29,999, $30,000 to $49,999, $50,000 to $79,999 and $80,000 or more. Marital status was grouped into three categories: married or common-law; widowed, separated or divorced; and never married. Participants were also asked to indicate whether their job security was good. Response options included strongly agree, agree, neither agree nor disagree, disagree, or strongly disagree. Responses were scored on a 5-point Likert scale, with higher scores indicating greater perceived job insecurity. 2.3. Statistical analyses Analyses were conducted with STATA (version 14.0, Stata Corp., College Station, Texas). Missing data were handled through listwise deletion reducing the sample size by 3.4% (i.e. from 14,416 to 13,926). All analyses were weighted and accounted for the complex survey design of the survey. Since there was no statistically significant sex interaction between independent variables and BMI, data for both sexes were combined to maximize power. In order to achieve normality criteria, the outcome variable of BMI was log-transformed in the analytical steps. With regards to descriptive analyses, categorical variables were described by count and percentage, while continuous variables were described by their means and standard deviations. Univariate (Model 1) and multivariate linear regression analyses were use to examine the associations between work and life stress with body mass index. Covariates included age, sex, education level, household income, marital status and job insecurity (Model 2); all variables in Model 2 + physical activity (Model 3); and all variables in Model 3 + trouble sleeping (Model 4). Similarly, univariate (Model 1) and multivariate linear regression analyses were use to examine the association between trouble sleeping and body mass index. Covariates included age, sex, education level, household income, marital status and job insecurity (Model 2); all variables in Model 2 + physical activity (Model 3); and all variables
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in Model 3 + work and life stress (Model 4). Two-way interactions were also tested to examine whether trouble sleeping and physical activity moderated the relationships between work/life stress and BMI, and whether work/life stress and physical activity moderated the relationships between trouble sleeping and BMI. Analyses were adjusted for age, sex, education level, household income, marital status and job insecurity (Model 1) and all variables in Model 1 + work and life stress (Model 2). The margins and marginsplot post-estimation commands in STATA were used to clarify significant interaction using the simple slopes approach, i.e., the slopes of the dependent variable on the independent variable when the moderator variable is held constant at different values running from the minimum to maximum value (Aiken et al., 1991). 3. Results Table 1 presents characteristics of the study population. Nearly twothird (66%) of the sample was aged b50 years and married/common law. Most participants achieved greater than a high school education (70%), and nearly three-in-five participants reported a household income of $80,000 or more. The average BMI and time spent in moderate-to-vigorous physical activity over the last 7 days were 26 kg/m2 and 4 h, respectively. Results of multiple linear regression analyses examining the associations between self-perceived work and life stress and BMI are summarized in Table 2. Before adjustment, self-perceived work (β = 0.009, p = 0.001) and life (β = 0.007, p = 0.014) stress showed linear relationships with BMI (Model 1). Results were similar after adjusting for age, sex, education level, household income, marital status, and job insecurity (Model 2). The associations of work (β = 0.011, p b 0.001) and life (β = 0.010, p b 0.001) stress with excess weight were also
Table 1 Characteristics of the study population. N (%) or mean ± SD Age 20–34 years 35–49 years 50–64 years 65 + years
4477 (31.3) 4301 (34.3) 4378(30.5) 770 (4.0)
Sex Male Female
7055 (54.5) 6871 (45.5)
Education Less than secondary Secondary graduation Some postsecondary Post secondary graduation
1258 (8.9) 2256 (15.2) 859 (6.2) 9553 (69.7)
Household income b$15,000 $15,000–29,999 $30,000–49,999 $50,000–79,999 $80,000+
403 (1.9) 1403 (7.1) 2558 (15.2) 2579 (17.6) 6983 (58.2)
Marital status Married or common law Separated, divorced, or widowed Never married Work stressa Life stressa Job insecuritya Trouble sleepinga Physical activity (hours in last 7 days) Body mass index (kg/m2)
7924 (66.2) 1985 (9.8) 4017 (24.0) 2.95 ± 1.03 2.87 ± 0.95 1.01 ± 1.04 2.14 ± 1.16 3.76 ± 4.18 26.2 ± 5.4
Data are presented as N (%) or mean ± SD. N = 13,926. a Responses were scored on a 5-point Likert scale, with higher score indicating greater perceived work/life stress, job insecurity, or more frequent trouble sleeping.
Table 2 Associations between work and life stress with body mass index among Canadian adults. β
SE
p-Value
Model 1 Unadjusted Work stress 0.009 0.003 0.001 Life stress 0.007 0.003 0.014 Model 2 Adjusted for age, sex, education level, household income, marital status and job insecurity Work stress 0.012 0.002 b0.001 Life stress 0.012 0.003 b0.001 Model 3 Adjusted for all variables in Model 2 + physical activity Work stress 0.012 0.002 b0.001 Life stress 0.012 0.003 b0.001 Model 4 Adjusted for all variables in Model 3 + trouble sleeping Work stress 0.011 0.003 b0.001 Life stress 0.010 0.003 b0.001 Body mass index was log-transformed. SE: standard error. N = 13,926.
independent of physical activity (Model 3) and trouble sleeping (Model 4) in addition to other covariates. Table 3 presents results of multiple linear regression analyses examining the association between trouble sleeping. Before adjustment, trouble sleeping (β = 0.005, p = 0.036) showed a linear relationship with BMI (Model 1). Results were similar after adjusting for age, sex, education level, household income, marital status, and job insecurity (Model 2: β = 0.008, p = 0.001). The association of trouble sleeping with BMI remained significant even after controlling for physical activity (Model 3) and work/life stress (Model 4; β = 0.013, p = 0.007) in addition to other covariates. The moderating role of physical activity on the relationships between trouble sleeping and BMI was further explored and is summarized in Table 4. Results indicated that physical activity was a significant moderator of the association between trouble sleeping and BMI before (Model 1) and after adjusting for work/life stress (Model 2) in addition to other covariates. Fig. 1 displays this interaction using the model adjusted for age, sex, education level, household income, marital status, job insecurity, and work and life stress. More trouble sleeping among inactive participants was related to a higher BMI; however, this relationship was almost null for adults who were physically active for about 8 h/week. In contrast, work stress or life stress were not significant moderators of the association between trouble sleeping and BMI (results not shown). Similarly, trouble sleeping and physical activity were not significant moderators of the relationships between work stress or life stress and BMI (results not shown).
Table 3 Association between trouble sleeping and body mass index among Canadian adults. β Model 1 Unadjusted Model 2 Adjusted for age, sex, education level, household income, marital status and job insecurity Model 3 Adjusted for all variables in Model 2 + physical activity Model 4 Adjusted for all variables in Model 3 + work and life stress Body mass index was log-transformed. SE: standard error. N = 13,926.
SE
p-Value
0.005 0.002 0.036
0.008 0.002 0.001
0.008 0.002 0.001
0.006 0.002 0.018
H. Sampasa-Kanyinga, J.-P. Chaput / Preventive Medicine 96 (2017) 16–20 Table 4 The moderating role of physical activity on the relationships between trouble sleeping and body mass index. β
SE
p-Value
Model 1 Adjusted for age, sex, education level, household income, marital status and job insecurity. Trouble sleeping 0.012 0.003 b0.001 Physical activity 0.0004 0.001 0.762 Trouble sleeping × physical activity –0.001 0.0005 0.025 Model 2 Adjusted for all variables in Model 1 + work and life stress Trouble sleeping 0.010 0.003 0.001 Work stress 0.008 0.003 0.003 Life stress 0.006 0.003 0.034 Physical activity 0.0006 0.001 0.659 Trouble sleeping × physical activity –0.001 0.0005 0.020 SE: standard error. N = 13,926.
4. Discussion The findings from the current study, based on a nationally representative sample of Canadian adults, showed that self-perceived work and life stress and trouble sleeping were associated with excess weight. The associations of work and life stress with excess weight were independent of trouble sleeping and physical activity in addition to other covariates, while that of trouble sleeping and excess weight was independent of work and life stress. Of particular interest, trouble sleeping among inactive participants was related to a higher BMI; however, this relationship was almost null for adults who were physically active for about 8 h/week, suggesting that high levels of physical activity could mitigate the adverse effects of trouble sleeping on BMI. However, longitudinal and experimental studies will be needed to confirm this observation. Our results are consistent with previous studies indicating that work and life stress are associated with excess weight among adults (Block et al., 2009; Moore & Cunningham, 2012; Wardle et al., 2011). However, the present study extends these studies by examining the moderating role of trouble sleeping and physical activity on these relationships. Our analyses showed that these associations are independent of trouble sleeping and physical activity levels, and that neither trouble sleeping nor physical activity moderated these relationships, indicating that the association between work/life stress and BMI did not vary by sleep
Fig. 1. Moderating role of physical activity on the relationship between trouble sleeping and body mass index. PA: physical activity; Hrs: hours. Trouble sleeping scale ranged from 1 (none of the time) to 5 (all of the time). Model is adjusted for age, sex, education level, household income, marital status, job insecurity, and work and life stress. N = 13,926.
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quality and/or physical activity level. It is nevertheless possible that the observed relationships are driven by unmeasured variables such as eating behaviour which is well known to influence BMI (Hays et al., 2002; Ma et al., 2003; Torres & Nowson, 2007). For example, Torres and Nowson indicated that stress-induced eating may be one factor contributing to the development of obesity (Torres & Nowson, 2007). This highlights the need for further studies. The observation that trouble sleeping is positively associated with BMI is consistent with previous research indicating that inadequate sleep is an important determinant of excess weight (Meyer et al., 2012; Nordin & Kaplan, 2010; Patel & Hu, 2008; Wheaton et al., 2011). For example, in a study of approximately 7000 middle-age adults in California followed for 29 years, Nordin and Kaplan found that consistent sleep discontinuity and impaired sleep continuity increased the risk of transition to obesity or of remaining obese (Nordin & Kaplan, 2010). To our knowledge, no previous study examined whether physical activity moderates the association between trouble sleeping and body weight among adults. Our finding that trouble sleeping among physically inactive participants was related to a higher BMI is in line with previous studies indicating that trouble sleeping and physical inactivity are related to excess weight (Hargens et al., 2013). Future studies are necessary to examine whether better sleep coupled to adequate physical activity level may help to achieve a healthy body weight. Our results also indicated that trouble sleeping among those who report very high levels of physical activity (i.e. N8 h/week) was negatively associated with BMI. This is not surprising because inadequate sleep summed to excessive physical activity may be more destructive for general well-being and body weight, thus potentially leading to weight loss. However, our findings revealed that the relationship between trouble sleeping and BMI was almost null for adults who are physically active for about 8 h/week. We could have expected to observe such findings at or near the recommended level of moderate-to-vigorous physical activity of 150 min/week (i.e. 2.5 h/week) for adults (Tremblay et al., 2011; World Health Organization, 2015). For additional health benefits, the World Health Organization posits that adults should increase their moderate-intensity physical activity to 300 min/week (i.e. 5 h/week), or equivalent (World Health Organization, 2015). Although the data used in the present study were derived from a nationally representative survey of adult population, it is possible that the study population is just more physically active than the general population or that the physical activity measure was affected by a desirability bias which could have leaded to an overestimation of physical activity levels. This emphasizes the need for future investigations using more objective measures of physical activity (e.g. accelerometry). Nevertheless, current findings are important and indicate that physical inactivity combined with trouble sleeping is related to a greater risk of excess weight, while excessive physical activity coupled to trouble sleeping is negatively associated with BMI. There are several limitations that need to be considered when interpreting the results of this study. First, it is not possible to determine the direction of the observed relationships because of the cross-sectional study design of the study. This emphasizes the need for further studies using longitudinal designs. Second, the psychometric properties of many measures used herein are unknown. Third, the present study used self-reported measures of physical activity and body weight and height. Future research may consider using more objective measures. Fourth, the present study did not adjust for eating behaviour. Given that the latter constitutes an important correlate of BMI and stress (Torres & Nowson, 2007), future studies may consider examining its role (as a covariate, moderator or mediator) on the relationships between work/life stress and BMI. Finally, there is a possibility of residual confounding by unmeasured variables (e.g. eating disorders and medication use). Despite these limitations, results of the present study may have important implications from a practical standpoint. Our results suggest that self-reporting being physically active for about 8 h/week could
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mitigate the adverse effects of trouble sleeping on BMI. However, achieving such an amount of physical activity per week may not be easy for everybody. Research has shown that a potentially important way to achieve the physical activity required for maintaining and improving health is through alternative, non-leisure forms of physical activity such as active transportation (i.e. walking or biking) (Berrigan et al., 2006). For example, walking is one of the least expensive and most broadly accessible forms of physical activity (Siegel et al., 1995), and it is easier to reach recommended physical activity targets through such a daily routine than occasional recreational activities (Berrigan et al., 2006). However, given that the experiences of trouble sleeping and the resulting sleepiness and fatigue may impair motivation to be physically active (Kline, 2014; Knutson et al., 2007), it is necessary to support those individuals and encourage healthy active living to help them achieve or maintain healthy weight. In conclusion, this study found that work and life stress are both associated with excess weight in adults, regardless of physical activity level, while the link of trouble sleeping with BMI varies by physical activity level. Future research is necessary to determine whether reducing work and life stress and improving sleep habits would benefit the prevention of weight gain and obesity. Conflict of interest The authors declare that they have no conflicts of interest. References Aiken, L.S., West, S.G., Reno, R.R., 1991. Multiple Regression: Testing and Interpreting Interactions. Sage. Åkerstedt, T., Knutsson, A., Westerholm, P., Theorell, T., Alfredsson, L., Kecklund, G., 2002. 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