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Leisure-time physical activity and psychotropic medication: A prospective cohort study
Preventive Medicine 57 (2013) 173–177
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Leisure-time physical activity and psychotropic medication: A prospective cohort study Jouni Lahti a,⁎, Tea Lallukka a,b, Eero Lahelma a, Ossi Rahkonen a a b
Department of Public Health, University of Helsinki, Finland Finnish Institute of Occupational Health, Helsinki, Finland
a r t i c l e
i n f o
Available online 31 May 2013 Keywords: Physical activity Exercise Mental health Depression Anxiety
a b s t r a c t Background. Physical inactivity is a major public health problem associated with an increased risk of mental health problems. The aim of this study was to examine the associations of leisure-time physical activity with subsequent psychotropic medication among middle-aged people employed at baseline. Methods. Questionnaire survey data collected in 2000–02 among 40–60-year-old employees of the City of Helsinki (N = 8960) were linked with register data on prescribed psychotropic medication (74% gave permission to linkage). The mean follow-up time was 4.2 years. The analysis included 5961 respondents (78% women). The participants were classified into four groups according to physical activity recommendations. Cox regression analysis was used to calculate hazard ratios (HR) for the first psychotropic medication purchase. Results. Leisure-time physical activity was associated with decreased risk of any psychotropic medication. After adjusting for prior psychotropic medication conditioning exercisers (HR = 0.65, 95% CI, 0.53–0.80), the vigorously active (HR = 0.83, 95% CI, 0.71–0.98) and the moderately active (HR = 0.85, 95% CI, 0.74–0.97) all showed a reduced risk of medication compared with the inactive. The associations were similar for the two main groups of psychotropic medication: antidepressants as well as sedatives and sleep medication. Conclusions. Leisure-time physical activity is potentially important for preventing mental health problems among the middle-aged. © 2013 Elsevier Inc. All rights reserved.
Introduction Physical inactivity is a key risk factor for major chronic diseases such as cardiovascular disease (Kohl, 2001), type II diabetes (Hu et al., 2003) and mental disorders (De Moor et al., 2006; Physical Activity Guidelines Advisory Committee, 2008) such as depression (Strawbridge et al., 2002) and anxiety (Ströhle, 2009). A review showed that even low doses of physical activity may prevent depression (Teychenne et al., 2008). However, some studies suggest that vigorous activity may be more beneficial for reducing depression (Lampinen et al., 2000) and related work disability (Lahti et al., in press) than lower intensity activity. The majority of previous prospective studies examining physical activity and mental health have been on depression with some studies on anxiety whereas other mental disorders have been less studied (Paluska and Schwenk, 2000). The evidence comes from studies with various designs and using self-reported as well as clinical diagnoses as outcomes (Physical Activity Guidelines Advisory Committee, 2008). However,
⁎ Corresponding author at: Hjelt Institute, Department of Public Health, P.O. Box 41, FIN-00014, University of Helsinki, Finland. E-mail address: jouni.mm.lahti@helsinki.fi (J. Lahti). 0091-7435/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ypmed.2013.05.019
we lack prospective cohort studies examining leisure-time physical activity and register-based subsequent psychotropic medication. The association between physical activity and mental health is typically reciprocal. Mental disorders such as depression are associated with low physical activity (Roshanaei-Moghaddam et al., 2009). Thus existing and prior mental health problems need to be considered when examining leisure-time physical activity and subsequent mental health problems. In addition, poor physical health is associated with mental health (Scott et al., 2007) and restricts physical functioning and participation in physical activity. Physical health may thus confound the association between leisure-time physical activity and subsequent mental health problems. Also health related behaviours such as smoking and alcohol use (Hämaläinen et al., 2001) as well as obesity (Scott et al., 2008) are associated with both mental health problems and physical activity (Laaksonen et al., 2001). In addition, low socioeconomic position is associated with increased mental health problems (Fryers et al., 2003; Lahelma et al., 2006) and physical activity (Seiluri et al., 2011). These factors are potentially important covariates to be considered when examining the association between leisure-time physical activity and subsequent mental health. The aim of this study was to examine whether recommended levels of moderately intensive and vigorous leisure-time physical
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activity are associated with subsequent mental health problems measured by psychotropic medication during a five-year follow-up. Methods The baseline questionnaire survey data were collected in 2000, 2001 and 2002 among 40- to 60-year-old employees of the City of Helsinki. The sample consisted of 13 346 persons and 67% responded to the questionnaires (N = 8960, 78% women). The data satisfactorily represent the target population although men, younger employees and manual workers were somewhat underrepresented among the respondents (Laaksonen et al., 2008; Lahelma et al., 2012). The questionnaire survey data were prospectively linked to the national register on prescribed psychotropic medication purchases obtained from the Social Insurance Institution of Finland (74% gave informed written consent for the linkages). According to our non-response analyses denying permission to the data linkage was unlikely to lead to substantially biased results (Laaksonen et al., 2008; Lahelma et al., 2012). There was missing information in some of the study variables (n = 326). Users of psychotropic medication at baseline (n = 319) were excluded and thus the present analyses included 5961 (78% women) respondents. The study has been approved by the ethics committees of the Department of Public Health, University of Helsinki and the health authorities of the City of Helsinki.
work) and professionals (e.g. teachers and doctors), semi-professionals (e.g. nurses and foremen), routine non-manual employees (e.g. child minders and assistant maids), and manual workers (e.g. transport and cleaning work) (Lahelma et al., 2005). Body mass index was calculated, using questionnaire data on height (m) and weight (kg). Smoking was dichotomized into non-smokers and smokers. Drinking problems were measured by the CAGE questionnaire (Schofield, 1988). Statistical methods Cox regression analysis was used to calculate hazard ratios (HR) and their 95% confidence intervals (95% CI) for first psychotropic medication purchase during the follow-up period. The inactive group was used as the reference group. The associations were not significantly different between genders (p = 0.1 for interaction) thus women and men were not analysed separately. In model 1 age and gender were adjusted for. In model 2 covariates in model 1 and prior (3 years) psychotropic medication were adjusted for. In model 3 covariates in model 2 and socioeconomic position were adjusted for. In model 4 covariates in model 3 and smoking, problem drinking and body mass index were adjusted for. In model 5 covariates in model 3 and physical health functioning were adjusted for. The proportional hazards assumption was examined using Schoenfeld residuals (Schoenfeld, 1982) and confirmed for leisure-time physical activity and covariates. PASW 18 statistical package was used.
Leisure-time physical activity The respondents were asked about their average weekly hours of leisure-time physical activity/exercise (including commuting) within the previous 12 months. Physical activity was divided into four grades of intensity and exemplified by common activities that people usually engage in: walking, brisk walking, jogging, and running, or their equivalent activities. Each intensity grade had five response alternatives, ranging from not at all to more than 4 h per week. The respondents were asked to estimate their average weekly hours in leisure-time physical activity corresponding to each grade of intensity. The volume of leisure-time physical activity was estimated by approximate metabolic equivalents (MET). MET hours per week were calculated by multiplying the time used (weekly hours) by the estimated MET value of each physical activity grade (Kujala et al., 1998) and then adding the four values together (Ainsworth et al., 2000). We classified participants into four groups according to physical activity recommendations (Fogelholm et al., 2005; Physical Activity Guidelines Advisory Committee, 2008) and according to the participation in vigorous intensity activities: 1. Inactive = under 14 MET hours per week; 2. Active moderate = 14–50 MET hours per week in moderately intensive activities (walking, brisk walking, or their equivalent activities) e.g. brisk walking for 30 min on five days per week equals 15 MET hours per week; 3. Active vigorous = 14–50 MET hours per week in moderately intensive and vigorous activities (jogging, running, or their equivalent activities) e.g. running for 45 min and walking briskly for 45 min in a week are sufficient; and 4. Conditioning exercise =over 50 MET hours per week in both moderately intensive and vigorous activities (Lahti et al., in press). Psychotropic medication The purchases of prescribed psychotropic medication were classified according to the Anatomical Therapeutic Chemical (ATC) classification system (WHO, 2009). In addition to any psychotropic medication (ATC codes N05 and N06 except medication for dementia N06D) the two largest groups of psychotropic medication i.e. antidepressants (N06A) and sedatives and sleep medication (N05B and N05C) were also examined. The follow-up started on the day of returning the questionnaire and continued for a maximum of 5 years or ended on the date of death providing a mean follow-up time of 4.2 years. Covariates Age included five groups at baseline: 40, 45, 50, 55 and 60 years. Prior psychotropic medication in 3 years preceding baseline was obtained from the register data. Physical health functioning was measured by the physical component summary score of the Short-Form 36 (SF-36) health questionnaire (Ware et al., 1994). Four occupational social classes were used as an indicator of socioeconomic position: managers (managerial and administrative
Results Table 1 presents the distributions of study variables. Women were less often in the vigorously active and conditioning exercise groups than men and the vigorously active and conditioning exercisers were younger than the less active groups. The vigorously active and conditioning exercisers were less often smokers than the less active. There were only minor differences in drinking problems between physical activity groups. Body mass index was the highest among the inactive and lowest among the conditioning exercisers. The inactive and moderately active tended to come more often from lower SEP groups. Physical health functioning was highest among the conditioning exercisers and lowest among the inactive. Prior psychotropic medication tended to be lower among the vigorously active and conditioning exercisers. During the follow-up one-fifth (21.7%) had any psychotropic medication (Table 2). Of the inactive 25.7% had purchases of any psychotropic medication whereas among the conditioning exercisers, the vigorously active and the moderately active the corresponding figures were 15.1%, 19.6% and 22.5%, respectively. The patterns between
Table 1 Description of study variables by leisure-time physical activity. The Helsinki Health Study 1997–2002. Leisure-time physical activity All
Inactive
N 5961 1410 Age (mean) 49.3 50.0 Women (%) 78.2 76.7 Smokers (%) 22.2 27.0 Drinking problems (%) 17.1 19.2 Body mass index (mean) 25.5 27.0 Socioeconomic position (%) Manual workers 14.0 15.8 Routine non-manuals 34.0 34.0 Semi-professionals 19.7 18.2 Managers/professionals 32.3 31.9 Physical health 49.5 47.5 functioning (mean) 14.4 16.5 Prior psychotropic medicationa (%) a
Active Active moderate vigorous
Conditioning exercise
2483 50.0 84.8 23.2 15.1 25.7
1311 48.0 73.2 18.6 18.6 24.5
757 47.8 67.8 16.2 16.8 24.0
14.2 38.2 19.3 28.1 48.9
10.4 28.5 21.0 40.2 51.2
16.4 28.9 21.1 33.6 52.6
16.4
11.5
8.7
From the register 3 years before baseline (2000–02).
J. Lahti et al. / Preventive Medicine 57 (2013) 173–177 Table 2 Psychotropic medication (proportions of first purchases (%) with (95% CI)) during the follow-up by physical activity groups: Any, antidepressants and sedatives and sleep medication. The Helsinki Health Study 2000–07. PA
n
Any
Antidepressants
Sedatives and sleep medication
All Inactive Active moderate Active vigorous Conditioning exercise
5961 1410 2483 1311 757
21.7 25.7 (23.6–27.9) 22.5 (20.9–24.1) 19.6 (17.4–21.8) 15.1 (12.1–18.0)
14.9 18.2 (16.4–20.1) 14.9 (13.5–16.3) 14.0 (12.0–15.9) 9.9 (7.4–12.4)
11.5 13.5 (11.9–15.2) 12.0 (10.7–13.2) 10.3 (8.6–12.0) 8.5 (6.2–10.7)
physical activity groups were largely similar for the two main groups of psychotropic medication: 1. antidepressants and 2. sedatives and sleep medication. Other physical activity groups were then compared with the inactive group for the risk of subsequent psychotropic medication adjusting for covariates (Table 3). In model 1 (adjusted for age and gender) the physical activity groups had a lower risk of subsequent psychotropic medication compared with the inactive. The conditioning exercise group had the lowest risk (HR = 0.56, 0.45–0.69) and also the vigorously active (HR = 0.74, 0.63–0.87) and the moderately active (HR = 0.84, 0.74–0.96) groups had a lower risk of psychotropic medication. Adjusting for prior psychotropic medication attenuated the associations of the vigorously active and conditioning groups whereas occupational social class had no effects. Adjusting for smoking, problem drinking and body mass index slightly attenuated the associations. Adjusting for physical health functioning also slightly attenuated the differences found between physical activity groups which remained for the conditioning exercise group, however, statistical significance was lost for the vigorously and moderately active groups.
Discussion We examined whether leisure-time physical activity was associated with subsequent mental health problems measured by prescribed psychotropic medication purchases. Physical activity was associated with reduced risk of subsequent mental health problems among middle-aged women and men. Those moderately and vigorously active had slightly reduced risk of mental health problems after adjusting for prior psychotropic medication. Conditioning exercise more clearly reduced the risk of mental health problems. The Table 3 Hazard ratios (95% CI) for psychotropic medication according to physical activity levels at baseline based on models that cumulatively control for age, gender, prior psychotropic medication, occupational social class, smoking, drinking problems, body mass index and physical health functioning. The Helsinki Health Study 2000–07. HR (95% CI) according to physical activity levels
Model Model Model Model Model
1 2 3 4 5
Inactive
Active moderate
Active vigorous
Conditioning exercise
1.00 1.00 1.00 1.00 1.00
0.84 0.85 0.84 0.87 0.87
0.74 0.83 0.83 0.86 0.88
0.56 0.65 0.65 0.70 0.72
(0.74–0.96) (0.74–0.97) (0.74–0.96) (0.76–1.00) (0.76–0.99)
(0.63–0.87) (0.71–0.98) (0.71–0.97) (0.73–1.02) (0.75–1.03)
(0.45–0.69) (0.53–0.80) (0.53–0.80) (0.56–0.87) (0.58–0.89)
Model 1 adjusted for age and gender. Model 2 adjusted for covariates in model 1 and additionally for prior psychotropic medication (3 years). Model 3 adjusted for covariates in model 2 and additionally for occupational social class. Model 4 adjusted for covariates in model 3 and additionally for smoking, drinking problems and body mass index. Model 5 adjusted for covariates in model 3 and additionally for physical health functioning.
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associations were similar for the two main groups of psychotropic medication i.e. antidepressants and sedatives and sleep medication. Previous studies also suggest that physical activity may prevent mental health problems among the middle-aged. Most convincing is the evidence regarding depression (Strawbridge et al., 2002) and somewhat less studied are anxiety disorders (Ströhle, 2009) and other mental disorders (Physical Activity Guidelines Advisory Committee, 2008). In this study, a slight reduction in the risk of subsequent mental health problems was found among those doing moderately intensive physical activity only and those doing vigorous activity which suggests that avoiding physical inactivity may be beneficial for mental health. However, the most active conditioning group had the lowest risk of subsequent mental health problems. Thus, higher volume of physical activity than the minimum of physical activity recommendations may provide further benefits for mental health. As mental health problems may be a cause for physical inactivity (Roshanaei-Moghaddam et al., 2009) we excluded current users of any psychotropic medication. In addition, we adjusted for prior psychotropic medication in the analyses which somewhat attenuated the lower risk found among the vigorously active and conditioning exercisers, however, the associations remained. Furthermore, the physically inactive may have various health problems that restrict their physical activity. We adjusted for physical health functioning which indicates health problems that affect physical functioning such as participation in physical activities. The adjustment made for physical health functioning attenuated the lower risk found among the physically active, suggesting that some of the inactive may have had physical health problems at the baseline which also contribute to mental health problems during the follow-up period. However, the differences in physical health functioning at baseline may partly originate from differences in physical activity (Hillsdon et al., 2005; Lahti et al., 2010a) potentially leading to overadjustment. In addition, we adjusted simultaneously for smoking, problem drinking and body mass index which also slightly attenuated the associations, suggesting that some of the inactive had also otherwise unhealthy behaviour such as drinking problems which contributes to poor mental health and the use of psychotropic medication. In addition to any psychotropic medication we examined the two main groups of psychotropic medication i.e. antidepressants and sedatives and sleep medication. The associations found were largely similar for these groups and for any psychotropic medication. There is comorbidity between depression and anxiety (Scott et al., 2007) and we lack information on the specific mental disorders that these medications were prescribed for. Furthermore, e.g. antidepressants are also prescribed for anxiety disorders (Sihvo et al., 2006). Thus we chose to do the main analyses using any psychotropic medication purchases which we think best indicate general mental health. There were some differences in leisure-time physical activity between women and men. Men did more vigorous activity than women, however, the proportion of the inactive was similar among women and men. The psychotropic medication purchases are known to be more prevalent among women than men as was also the case in these data (Mauramo et al., 2012). However, the associations between leisure-time physical activity and psychotropic medication were largely similar for women and men. We made some additional sensitivity analyses. In order to get an indication about the incidence we also did the analyses excluding those who had any psychotropic medication within the previous three years before the baseline survey (14.4%). The associations were quite similar to those presented in model 1 when gender and age were adjusted for. However, we do not have the information on lifetime psychotropic medication and therefore we cannot fully rule out previous mental health problems. Furthermore, as the results showed that higher volumes of physical activity than recommended may be needed for reducing mental health problems as indicated by psychotropic medication we did additional analyses and classified
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physical activity into five groups according to quintiles (Lahti et al., 2010b). The results showed a graded reduction in the purchases of psychotropic medication (from 26% to 17%) as physical activity increased. Compared with the lowest physical activity group statistically significantly lower risks were found from second highest physical activity quintile (>28 MET-hours per week) upward (data not shown). This volume of physical activity corresponds to approximately 5 h of brisk walking per week which is considered the optimal for health benefits (Fogelholm et al., 2005). However, further elaboration of the association between the volume of physical activity and psychotropic medication is out of the scope of this study. This study suggests that physical activity during leisure-time may reduce mental health problems among the middle-aged. In addition, interventions have been successful in treating mild forms of depression (Daley, 2008) and reducing anxiety (Long and van Stavel, 1995) with exercise. From the public health perspective, the increasingly common mental health problems and a sedentary way of life in many Western societies warrant large scale measures to promote physical activity in everyday life to enhance the mental health among populations.
Conclusions Leisure-time physical activity was associated with reduced risk of subsequent mental health problems. Recommended volumes of moderately intensive and vigorous activity were relatively weakly associated, whereas higher volume of physical activity was more clearly associated with reduced risk of mental health problems, as indicated by psychotropic medication. Leisure-time physical activity should be encouraged at work places and in general for preventing mental health problems among middle-aged people. Conflict of interest statement The authors declare that there are no conflicts of interest.
Acknowledgments We thank the City of Helsinki and all the members of the Helsinki Health Study group for their contribution. The study was supported by the University of Helsinki, the Ministry of Education and Culture, the Juho Vainio Foundation and the Academy of Finland. References
Study strengths and limitations The main strength of this study was the prospective design with complete national register data on psychotropic medication purchases linked with the survey data. We were also able to exclude those with current medication at the baseline. Furthermore, we adjusted for prior medication which strengthens the results and conclusions regarding causality between leisure-time physical activity and mental health. We were also able to adjust for physical health functioning which is important as physical health problems may also confound the examined associations. There are also limitations in this study. The purchases of prescribed psychotropic medication are not a direct measure of mental health problems. Psychotropic medications such as antidepressants are also used for other purposes such as treatment of pain and sleep problems. Information on leisure-time physical activity was self-reported and the series of questions are not validated. A large review, however, concluded that there is no single questionnaire proven to be superior for measuring leisure-time physical activity in large surveys (van Poppel et al., 2010). The cut-point for physical inactivity was taken from physical activity recommendations. It has been shown that lower physical activity than recommended for health benefits may prevent mental health problems such as depression (Teychenne et al., 2008). Our additional analyses, however, showed that the amount of physical activity corresponding to 5 h of brisk walking per week showed significant reduction in the risk of mental health problems. Attrition may be a problem in prospective studies. In our study, the baseline response rate (67%) was acceptable. In addition, there was further attrition due to consenting to the register linkage. According to our non-response analyses e.g. the non-respondents had somewhat higher rates of longer sickness absence compared with the responders, however, the results are unlikely to be markedly biased as the differences were small (Laaksonen et al., 2008; Lahelma et al., 2012). Furthermore, we tested that those consenting and not consenting to the register linkage had similar scores on the SF-36 mental component summary (data not shown). We were able to consider various confounders in the analyses, however, residual and unmeasured confounding remains a problem. There are characteristics of our data that limit the generalisability of the results. The participants were middle-aged public sector employees and 80% of them were women corresponding to the gender distribution of the target population and the municipal sector in general. Women and men were combined in the analyses, thus these results are female dominated although the associations were not significantly different between genders.
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Contents lists available at SciVerse ScienceDirect
Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Leisure-time physical activity and psychotropic medication: A prospective cohort study Jouni Lahti a,⁎, Tea Lallukka a,b, Eero Lahelma a, Ossi Rahkonen a a b
Department of Public Health, University of Helsinki, Finland Finnish Institute of Occupational Health, Helsinki, Finland
a r t i c l e
i n f o
Available online 31 May 2013 Keywords: Physical activity Exercise Mental health Depression Anxiety
a b s t r a c t Background. Physical inactivity is a major public health problem associated with an increased risk of mental health problems. The aim of this study was to examine the associations of leisure-time physical activity with subsequent psychotropic medication among middle-aged people employed at baseline. Methods. Questionnaire survey data collected in 2000–02 among 40–60-year-old employees of the City of Helsinki (N = 8960) were linked with register data on prescribed psychotropic medication (74% gave permission to linkage). The mean follow-up time was 4.2 years. The analysis included 5961 respondents (78% women). The participants were classified into four groups according to physical activity recommendations. Cox regression analysis was used to calculate hazard ratios (HR) for the first psychotropic medication purchase. Results. Leisure-time physical activity was associated with decreased risk of any psychotropic medication. After adjusting for prior psychotropic medication conditioning exercisers (HR = 0.65, 95% CI, 0.53–0.80), the vigorously active (HR = 0.83, 95% CI, 0.71–0.98) and the moderately active (HR = 0.85, 95% CI, 0.74–0.97) all showed a reduced risk of medication compared with the inactive. The associations were similar for the two main groups of psychotropic medication: antidepressants as well as sedatives and sleep medication. Conclusions. Leisure-time physical activity is potentially important for preventing mental health problems among the middle-aged. © 2013 Elsevier Inc. All rights reserved.
Introduction Physical inactivity is a key risk factor for major chronic diseases such as cardiovascular disease (Kohl, 2001), type II diabetes (Hu et al., 2003) and mental disorders (De Moor et al., 2006; Physical Activity Guidelines Advisory Committee, 2008) such as depression (Strawbridge et al., 2002) and anxiety (Ströhle, 2009). A review showed that even low doses of physical activity may prevent depression (Teychenne et al., 2008). However, some studies suggest that vigorous activity may be more beneficial for reducing depression (Lampinen et al., 2000) and related work disability (Lahti et al., in press) than lower intensity activity. The majority of previous prospective studies examining physical activity and mental health have been on depression with some studies on anxiety whereas other mental disorders have been less studied (Paluska and Schwenk, 2000). The evidence comes from studies with various designs and using self-reported as well as clinical diagnoses as outcomes (Physical Activity Guidelines Advisory Committee, 2008). However,
⁎ Corresponding author at: Hjelt Institute, Department of Public Health, P.O. Box 41, FIN-00014, University of Helsinki, Finland. E-mail address: jouni.mm.lahti@helsinki.fi (J. Lahti). 0091-7435/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ypmed.2013.05.019
we lack prospective cohort studies examining leisure-time physical activity and register-based subsequent psychotropic medication. The association between physical activity and mental health is typically reciprocal. Mental disorders such as depression are associated with low physical activity (Roshanaei-Moghaddam et al., 2009). Thus existing and prior mental health problems need to be considered when examining leisure-time physical activity and subsequent mental health problems. In addition, poor physical health is associated with mental health (Scott et al., 2007) and restricts physical functioning and participation in physical activity. Physical health may thus confound the association between leisure-time physical activity and subsequent mental health problems. Also health related behaviours such as smoking and alcohol use (Hämaläinen et al., 2001) as well as obesity (Scott et al., 2008) are associated with both mental health problems and physical activity (Laaksonen et al., 2001). In addition, low socioeconomic position is associated with increased mental health problems (Fryers et al., 2003; Lahelma et al., 2006) and physical activity (Seiluri et al., 2011). These factors are potentially important covariates to be considered when examining the association between leisure-time physical activity and subsequent mental health. The aim of this study was to examine whether recommended levels of moderately intensive and vigorous leisure-time physical
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activity are associated with subsequent mental health problems measured by psychotropic medication during a five-year follow-up. Methods The baseline questionnaire survey data were collected in 2000, 2001 and 2002 among 40- to 60-year-old employees of the City of Helsinki. The sample consisted of 13 346 persons and 67% responded to the questionnaires (N = 8960, 78% women). The data satisfactorily represent the target population although men, younger employees and manual workers were somewhat underrepresented among the respondents (Laaksonen et al., 2008; Lahelma et al., 2012). The questionnaire survey data were prospectively linked to the national register on prescribed psychotropic medication purchases obtained from the Social Insurance Institution of Finland (74% gave informed written consent for the linkages). According to our non-response analyses denying permission to the data linkage was unlikely to lead to substantially biased results (Laaksonen et al., 2008; Lahelma et al., 2012). There was missing information in some of the study variables (n = 326). Users of psychotropic medication at baseline (n = 319) were excluded and thus the present analyses included 5961 (78% women) respondents. The study has been approved by the ethics committees of the Department of Public Health, University of Helsinki and the health authorities of the City of Helsinki.
work) and professionals (e.g. teachers and doctors), semi-professionals (e.g. nurses and foremen), routine non-manual employees (e.g. child minders and assistant maids), and manual workers (e.g. transport and cleaning work) (Lahelma et al., 2005). Body mass index was calculated, using questionnaire data on height (m) and weight (kg). Smoking was dichotomized into non-smokers and smokers. Drinking problems were measured by the CAGE questionnaire (Schofield, 1988). Statistical methods Cox regression analysis was used to calculate hazard ratios (HR) and their 95% confidence intervals (95% CI) for first psychotropic medication purchase during the follow-up period. The inactive group was used as the reference group. The associations were not significantly different between genders (p = 0.1 for interaction) thus women and men were not analysed separately. In model 1 age and gender were adjusted for. In model 2 covariates in model 1 and prior (3 years) psychotropic medication were adjusted for. In model 3 covariates in model 2 and socioeconomic position were adjusted for. In model 4 covariates in model 3 and smoking, problem drinking and body mass index were adjusted for. In model 5 covariates in model 3 and physical health functioning were adjusted for. The proportional hazards assumption was examined using Schoenfeld residuals (Schoenfeld, 1982) and confirmed for leisure-time physical activity and covariates. PASW 18 statistical package was used.
Leisure-time physical activity The respondents were asked about their average weekly hours of leisure-time physical activity/exercise (including commuting) within the previous 12 months. Physical activity was divided into four grades of intensity and exemplified by common activities that people usually engage in: walking, brisk walking, jogging, and running, or their equivalent activities. Each intensity grade had five response alternatives, ranging from not at all to more than 4 h per week. The respondents were asked to estimate their average weekly hours in leisure-time physical activity corresponding to each grade of intensity. The volume of leisure-time physical activity was estimated by approximate metabolic equivalents (MET). MET hours per week were calculated by multiplying the time used (weekly hours) by the estimated MET value of each physical activity grade (Kujala et al., 1998) and then adding the four values together (Ainsworth et al., 2000). We classified participants into four groups according to physical activity recommendations (Fogelholm et al., 2005; Physical Activity Guidelines Advisory Committee, 2008) and according to the participation in vigorous intensity activities: 1. Inactive = under 14 MET hours per week; 2. Active moderate = 14–50 MET hours per week in moderately intensive activities (walking, brisk walking, or their equivalent activities) e.g. brisk walking for 30 min on five days per week equals 15 MET hours per week; 3. Active vigorous = 14–50 MET hours per week in moderately intensive and vigorous activities (jogging, running, or their equivalent activities) e.g. running for 45 min and walking briskly for 45 min in a week are sufficient; and 4. Conditioning exercise =over 50 MET hours per week in both moderately intensive and vigorous activities (Lahti et al., in press). Psychotropic medication The purchases of prescribed psychotropic medication were classified according to the Anatomical Therapeutic Chemical (ATC) classification system (WHO, 2009). In addition to any psychotropic medication (ATC codes N05 and N06 except medication for dementia N06D) the two largest groups of psychotropic medication i.e. antidepressants (N06A) and sedatives and sleep medication (N05B and N05C) were also examined. The follow-up started on the day of returning the questionnaire and continued for a maximum of 5 years or ended on the date of death providing a mean follow-up time of 4.2 years. Covariates Age included five groups at baseline: 40, 45, 50, 55 and 60 years. Prior psychotropic medication in 3 years preceding baseline was obtained from the register data. Physical health functioning was measured by the physical component summary score of the Short-Form 36 (SF-36) health questionnaire (Ware et al., 1994). Four occupational social classes were used as an indicator of socioeconomic position: managers (managerial and administrative
Results Table 1 presents the distributions of study variables. Women were less often in the vigorously active and conditioning exercise groups than men and the vigorously active and conditioning exercisers were younger than the less active groups. The vigorously active and conditioning exercisers were less often smokers than the less active. There were only minor differences in drinking problems between physical activity groups. Body mass index was the highest among the inactive and lowest among the conditioning exercisers. The inactive and moderately active tended to come more often from lower SEP groups. Physical health functioning was highest among the conditioning exercisers and lowest among the inactive. Prior psychotropic medication tended to be lower among the vigorously active and conditioning exercisers. During the follow-up one-fifth (21.7%) had any psychotropic medication (Table 2). Of the inactive 25.7% had purchases of any psychotropic medication whereas among the conditioning exercisers, the vigorously active and the moderately active the corresponding figures were 15.1%, 19.6% and 22.5%, respectively. The patterns between
Table 1 Description of study variables by leisure-time physical activity. The Helsinki Health Study 1997–2002. Leisure-time physical activity All
Inactive
N 5961 1410 Age (mean) 49.3 50.0 Women (%) 78.2 76.7 Smokers (%) 22.2 27.0 Drinking problems (%) 17.1 19.2 Body mass index (mean) 25.5 27.0 Socioeconomic position (%) Manual workers 14.0 15.8 Routine non-manuals 34.0 34.0 Semi-professionals 19.7 18.2 Managers/professionals 32.3 31.9 Physical health 49.5 47.5 functioning (mean) 14.4 16.5 Prior psychotropic medicationa (%) a
Active Active moderate vigorous
Conditioning exercise
2483 50.0 84.8 23.2 15.1 25.7
1311 48.0 73.2 18.6 18.6 24.5
757 47.8 67.8 16.2 16.8 24.0
14.2 38.2 19.3 28.1 48.9
10.4 28.5 21.0 40.2 51.2
16.4 28.9 21.1 33.6 52.6
16.4
11.5
8.7
From the register 3 years before baseline (2000–02).
J. Lahti et al. / Preventive Medicine 57 (2013) 173–177 Table 2 Psychotropic medication (proportions of first purchases (%) with (95% CI)) during the follow-up by physical activity groups: Any, antidepressants and sedatives and sleep medication. The Helsinki Health Study 2000–07. PA
n
Any
Antidepressants
Sedatives and sleep medication
All Inactive Active moderate Active vigorous Conditioning exercise
5961 1410 2483 1311 757
21.7 25.7 (23.6–27.9) 22.5 (20.9–24.1) 19.6 (17.4–21.8) 15.1 (12.1–18.0)
14.9 18.2 (16.4–20.1) 14.9 (13.5–16.3) 14.0 (12.0–15.9) 9.9 (7.4–12.4)
11.5 13.5 (11.9–15.2) 12.0 (10.7–13.2) 10.3 (8.6–12.0) 8.5 (6.2–10.7)
physical activity groups were largely similar for the two main groups of psychotropic medication: 1. antidepressants and 2. sedatives and sleep medication. Other physical activity groups were then compared with the inactive group for the risk of subsequent psychotropic medication adjusting for covariates (Table 3). In model 1 (adjusted for age and gender) the physical activity groups had a lower risk of subsequent psychotropic medication compared with the inactive. The conditioning exercise group had the lowest risk (HR = 0.56, 0.45–0.69) and also the vigorously active (HR = 0.74, 0.63–0.87) and the moderately active (HR = 0.84, 0.74–0.96) groups had a lower risk of psychotropic medication. Adjusting for prior psychotropic medication attenuated the associations of the vigorously active and conditioning groups whereas occupational social class had no effects. Adjusting for smoking, problem drinking and body mass index slightly attenuated the associations. Adjusting for physical health functioning also slightly attenuated the differences found between physical activity groups which remained for the conditioning exercise group, however, statistical significance was lost for the vigorously and moderately active groups.
Discussion We examined whether leisure-time physical activity was associated with subsequent mental health problems measured by prescribed psychotropic medication purchases. Physical activity was associated with reduced risk of subsequent mental health problems among middle-aged women and men. Those moderately and vigorously active had slightly reduced risk of mental health problems after adjusting for prior psychotropic medication. Conditioning exercise more clearly reduced the risk of mental health problems. The Table 3 Hazard ratios (95% CI) for psychotropic medication according to physical activity levels at baseline based on models that cumulatively control for age, gender, prior psychotropic medication, occupational social class, smoking, drinking problems, body mass index and physical health functioning. The Helsinki Health Study 2000–07. HR (95% CI) according to physical activity levels
Model Model Model Model Model
1 2 3 4 5
Inactive
Active moderate
Active vigorous
Conditioning exercise
1.00 1.00 1.00 1.00 1.00
0.84 0.85 0.84 0.87 0.87
0.74 0.83 0.83 0.86 0.88
0.56 0.65 0.65 0.70 0.72
(0.74–0.96) (0.74–0.97) (0.74–0.96) (0.76–1.00) (0.76–0.99)
(0.63–0.87) (0.71–0.98) (0.71–0.97) (0.73–1.02) (0.75–1.03)
(0.45–0.69) (0.53–0.80) (0.53–0.80) (0.56–0.87) (0.58–0.89)
Model 1 adjusted for age and gender. Model 2 adjusted for covariates in model 1 and additionally for prior psychotropic medication (3 years). Model 3 adjusted for covariates in model 2 and additionally for occupational social class. Model 4 adjusted for covariates in model 3 and additionally for smoking, drinking problems and body mass index. Model 5 adjusted for covariates in model 3 and additionally for physical health functioning.
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associations were similar for the two main groups of psychotropic medication i.e. antidepressants and sedatives and sleep medication. Previous studies also suggest that physical activity may prevent mental health problems among the middle-aged. Most convincing is the evidence regarding depression (Strawbridge et al., 2002) and somewhat less studied are anxiety disorders (Ströhle, 2009) and other mental disorders (Physical Activity Guidelines Advisory Committee, 2008). In this study, a slight reduction in the risk of subsequent mental health problems was found among those doing moderately intensive physical activity only and those doing vigorous activity which suggests that avoiding physical inactivity may be beneficial for mental health. However, the most active conditioning group had the lowest risk of subsequent mental health problems. Thus, higher volume of physical activity than the minimum of physical activity recommendations may provide further benefits for mental health. As mental health problems may be a cause for physical inactivity (Roshanaei-Moghaddam et al., 2009) we excluded current users of any psychotropic medication. In addition, we adjusted for prior psychotropic medication in the analyses which somewhat attenuated the lower risk found among the vigorously active and conditioning exercisers, however, the associations remained. Furthermore, the physically inactive may have various health problems that restrict their physical activity. We adjusted for physical health functioning which indicates health problems that affect physical functioning such as participation in physical activities. The adjustment made for physical health functioning attenuated the lower risk found among the physically active, suggesting that some of the inactive may have had physical health problems at the baseline which also contribute to mental health problems during the follow-up period. However, the differences in physical health functioning at baseline may partly originate from differences in physical activity (Hillsdon et al., 2005; Lahti et al., 2010a) potentially leading to overadjustment. In addition, we adjusted simultaneously for smoking, problem drinking and body mass index which also slightly attenuated the associations, suggesting that some of the inactive had also otherwise unhealthy behaviour such as drinking problems which contributes to poor mental health and the use of psychotropic medication. In addition to any psychotropic medication we examined the two main groups of psychotropic medication i.e. antidepressants and sedatives and sleep medication. The associations found were largely similar for these groups and for any psychotropic medication. There is comorbidity between depression and anxiety (Scott et al., 2007) and we lack information on the specific mental disorders that these medications were prescribed for. Furthermore, e.g. antidepressants are also prescribed for anxiety disorders (Sihvo et al., 2006). Thus we chose to do the main analyses using any psychotropic medication purchases which we think best indicate general mental health. There were some differences in leisure-time physical activity between women and men. Men did more vigorous activity than women, however, the proportion of the inactive was similar among women and men. The psychotropic medication purchases are known to be more prevalent among women than men as was also the case in these data (Mauramo et al., 2012). However, the associations between leisure-time physical activity and psychotropic medication were largely similar for women and men. We made some additional sensitivity analyses. In order to get an indication about the incidence we also did the analyses excluding those who had any psychotropic medication within the previous three years before the baseline survey (14.4%). The associations were quite similar to those presented in model 1 when gender and age were adjusted for. However, we do not have the information on lifetime psychotropic medication and therefore we cannot fully rule out previous mental health problems. Furthermore, as the results showed that higher volumes of physical activity than recommended may be needed for reducing mental health problems as indicated by psychotropic medication we did additional analyses and classified
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physical activity into five groups according to quintiles (Lahti et al., 2010b). The results showed a graded reduction in the purchases of psychotropic medication (from 26% to 17%) as physical activity increased. Compared with the lowest physical activity group statistically significantly lower risks were found from second highest physical activity quintile (>28 MET-hours per week) upward (data not shown). This volume of physical activity corresponds to approximately 5 h of brisk walking per week which is considered the optimal for health benefits (Fogelholm et al., 2005). However, further elaboration of the association between the volume of physical activity and psychotropic medication is out of the scope of this study. This study suggests that physical activity during leisure-time may reduce mental health problems among the middle-aged. In addition, interventions have been successful in treating mild forms of depression (Daley, 2008) and reducing anxiety (Long and van Stavel, 1995) with exercise. From the public health perspective, the increasingly common mental health problems and a sedentary way of life in many Western societies warrant large scale measures to promote physical activity in everyday life to enhance the mental health among populations.
Conclusions Leisure-time physical activity was associated with reduced risk of subsequent mental health problems. Recommended volumes of moderately intensive and vigorous activity were relatively weakly associated, whereas higher volume of physical activity was more clearly associated with reduced risk of mental health problems, as indicated by psychotropic medication. Leisure-time physical activity should be encouraged at work places and in general for preventing mental health problems among middle-aged people. Conflict of interest statement The authors declare that there are no conflicts of interest.
Acknowledgments We thank the City of Helsinki and all the members of the Helsinki Health Study group for their contribution. The study was supported by the University of Helsinki, the Ministry of Education and Culture, the Juho Vainio Foundation and the Academy of Finland. References
Study strengths and limitations The main strength of this study was the prospective design with complete national register data on psychotropic medication purchases linked with the survey data. We were also able to exclude those with current medication at the baseline. Furthermore, we adjusted for prior medication which strengthens the results and conclusions regarding causality between leisure-time physical activity and mental health. We were also able to adjust for physical health functioning which is important as physical health problems may also confound the examined associations. There are also limitations in this study. The purchases of prescribed psychotropic medication are not a direct measure of mental health problems. Psychotropic medications such as antidepressants are also used for other purposes such as treatment of pain and sleep problems. Information on leisure-time physical activity was self-reported and the series of questions are not validated. A large review, however, concluded that there is no single questionnaire proven to be superior for measuring leisure-time physical activity in large surveys (van Poppel et al., 2010). The cut-point for physical inactivity was taken from physical activity recommendations. It has been shown that lower physical activity than recommended for health benefits may prevent mental health problems such as depression (Teychenne et al., 2008). Our additional analyses, however, showed that the amount of physical activity corresponding to 5 h of brisk walking per week showed significant reduction in the risk of mental health problems. Attrition may be a problem in prospective studies. In our study, the baseline response rate (67%) was acceptable. In addition, there was further attrition due to consenting to the register linkage. According to our non-response analyses e.g. the non-respondents had somewhat higher rates of longer sickness absence compared with the responders, however, the results are unlikely to be markedly biased as the differences were small (Laaksonen et al., 2008; Lahelma et al., 2012). Furthermore, we tested that those consenting and not consenting to the register linkage had similar scores on the SF-36 mental component summary (data not shown). We were able to consider various confounders in the analyses, however, residual and unmeasured confounding remains a problem. There are characteristics of our data that limit the generalisability of the results. The participants were middle-aged public sector employees and 80% of them were women corresponding to the gender distribution of the target population and the municipal sector in general. Women and men were combined in the analyses, thus these results are female dominated although the associations were not significantly different between genders.
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