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Are physical activity levels associated with better health outcomes in people with epilepsy?
Epilepsy & Behavior 72 (2017) 28–34
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Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh
Are physical activity levels associated with better health outcomes in people with epilepsy? César Augusto Häfele ⁎, Matheus Pintanel Freitas, Marcelo Cozzensa da Silva, Airton José Rombaldi Escola Superior de Educação Física, Universidade Federal de Pelotas, RS, Brazil Programa de Pós-Graduação em Educação Física, Universidade Federal de Pelotas, RS, Brazil Grupo de Estudos em Epidemiologia da Atividade Física, Universidade Federal de Pelotas, RS, Brazil School of Physical Education, Federal University of Pelotas, Rua Luís de Camões, 625, 96055630 Pelotas, RS, Brazil
a r t i c l e
i n f o
Article history: Received 16 January 2017 Revised 19 April 2017 Accepted 22 April 2017 Available online xxxx Keywords: Mental health Seizure Epilepsy Physical activity Behavior
a b s t r a c t The aim of the study was to investigate the association of physical activity in three categories (inactive, insufficiently active and active) with health outcomes in people with epilepsy. The dependent variables and the instruments used in the study were: a) quality of life — measured by Quality of Life in Epilepsy-31 for adults and Quality of Life in Epilepsy for Adolescents, b) side effects of medication — measured by Adverse Events Profile, c) depression — measured by Neurological Disorders Depression Inventory for Epilepsy, and d) state and trait anxiety — measured by State–Trait Anxiety Inventory. Physical activity levels were analyzed using the International Physical Activity Questionnaire (IPAQ) for adults in the commuting and leisure domains and Physical Activity Questionnaire for Adolescents (PAQ-A). Simple and multiple linear regression was used in the statistical analysis. The cross-sectional study with one hundred and one individuals was conducted in Pelotas/RS, Brazil, at the Neurology Clinic of the Faculty of Medicine of the Federal University of Pelotas. In the crude analysis, physical activity was positively associated with quality of life (p b 0.001) and negatively associated with depression (p = 0.046), state of anxiety (p = 0.014), trait of anxiety (p = 0.015) and side effect of medication (p = 0.01). In addition, physical activity levels explained 10% of the quality of life (R2 = 0.10). In the adjusted analysis, physical activity remained associated with side effect of medication (p = 0.014) and was not associated with trait anxiety (p = 0.066). However, quality of life showed a positive linear trend (p = 0.001) while depression (p = 0.033) and anxiety state (p = 0.004) showed a negative trend according to physical activity levels. Physical activity was associated with health outcomes, and can be a nonpharmacological treatment in people with epilepsy for improving health and life conditions. © 2017 Elsevier Inc. All rights reserved.
1. Introduction Epilepsy is a neurological disease which affects around 65 million people in the world [1]. Fisher et al. [2] proposed that this disease is characterized by a brain disorder defined by any of the following conditions: (1) at least two unprovoked seizures occurring in an interval longer than 24 h; (2) one unprovoked seizure and a risk greater than 60% of a new seizures; and (3) diagnosis of an epilepsy syndrome. When compared to the general population, people with epilepsy (PWE) show higher levels of depression and anxiety [3], which leads to a reduction in the quality of life scores [4–6]. In addition, the drugs used in the treatment of the disease, despite promoting significant seizure control [7], cause several side effects such as: weight gain [8], reduction in bone ⁎ Corresponding author at: Rua Luís de Camões, 625, 96055630 Pelotas, RS, Brazil. E-mail addresses: [email protected] (C.A. Häfele), [email protected] (M.P. Freitas), [email protected] (M.C. da Silva), [email protected] (A.J. Rombaldi).
http://dx.doi.org/10.1016/j.yebeh.2017.04.038 1525-5050/© 2017 Elsevier Inc. All rights reserved.
mineral density [9], fatigue/tiredness, gastrointestinal disorders, appetite reduction, and hand shaking, among others [10]. Historically, PWE have been advised against participation in physical exercise and sports, mainly because of overprotection, fear, and ignorance about the risks and benefits of physical activity practice [11]. However, a number of studies reported that these activities may have a positive influence on the frequency and severity of seizures. Thus, recommendations in clinical practice and attitudes toward sports and epilepsy have changed considerably [11,12]. Recently, The Task Force on Sports and Epilepsy developed a consensus paper with general guidance concerning participation in physical exercise and sports for PWE. These suggestions are directed to physicians and other health care professionals involved in the treatment of PWE [12]. Studies, which compare physical activity levels and physical fitness among PWE and the general population, concluded that PWE had worse physical fitness and a greater number of individuals who never performed any physical activity [13,14]. In addition, a study, which compared teens with epilepsy to their siblings without epilepsy, found that
C.A. Häfele et al. / Epilepsy & Behavior 72 (2017) 28–34
teens with epilepsy participated less in sports activities than their control siblings [15]. Physical activity practice promotes several health benefits. In 2012, in a Lancet physical activity series, Lee et al. [16] reported that if physical inactivity levels were reduced by 25%, around 1.3 million deaths would be avoided each year. In addition to the benefits regarding chronic diseases, it is well known that physical activity practice reduces the levels of depression [17] and anxiety [18] in the general population, thus, improving quality of life [19]. Studies evaluating the association between physical activity practice and depression/anxiety in PWE reported positive results for the physically active [20,21]. A different study evaluating the influence of physical activity in the quality of life of PWE showed that the group which performed physical activity improved the general scores in this aspect and the control group did not show any alteration [22]. It is well known that PWE show worse health scores and undoubtedly, physical activity plays an important role in improving these scores in the general population [16–18]. However, few studies on this topic were found [20,23], mainly in low- and middle-income countries [21] where approximately 80% of PWE are living [24]. Therefore, the aim of this study was to verify the association between physical activity levels (inactive, insufficiently active and active) with scores regarding quality of life, depression, anxiety and side effects of medication in PWE. 2. Materials and methods 2.1. Participants A cross-sectional study was carried out aiming at determining the influence of physical activity on different health outcomes in PWE. The study was conducted in Pelotas, southern Brazil, at the neurology clinic of the Faculty of Medicine of the Federal University of Pelotas. One hundred and one individuals (101) between 12 and 75 years diagnosed with epilepsy participated in the study. Data collection was carried out for five months, from December 1st 2015 to April 30th 2016. 2.2. Procedure First, the director of the Medicine Faculty was contacted to obtain authorization for data collection. After which a visit was made to the clinic with the purpose of meeting the staff. Data collection was carried out as follows: first, using the records of the neurology clinic in 2015, patients with epilepsy were diagnosed. Following this procedure a telephone contact was made with these individuals explaining the aims of the research and inviting them to take part. Second, at neurological service days, the researcher accessed the patient records prior to consultation to verify those who were diagnosed with epilepsy. While the patients waited for their consultation, the researcher invited them to participate in the study. This procedure was not conducted for first-time patients. In this case, the researcher waited for the consultation and if the doctor diagnosed the patient with epilepsy, he/she would invite him/her for the study. 2.3. Demographic and epilepsy data questionnaires 2.3.1. Dependent variables The following continuous dependent variables were used in the present study: a) quality of life, measured using Quality of Life in Epilepsy Inventory-31 for adults (QOLIE-31) [25] and Quality of Life in Epilepsy Inventory for Adolescents (QOLIE-AD-48) [26]. The QOLIE-31 is made up of 31 questions distributed into seven domains: general quality of life, seizure worry, emotional wellness, energy and fatigue, cognitive function, social functioning and medication effects. On the other hand, QOLIE-AD-48 is made up of 48 questions distributed into eight domains: epilepsy impact, memory and concentration, attitude toward epilepsy, physical functioning, epilepsy stigma, social support, scholar behavior,
29
and health perception. Both instruments generated a continuous total score ranging from zero to 100. The higher the score, the higher the quality of life. This study used only the total score from both questionnaires. b) Side effects: the Adverse Effects Profile (AEP) scale is made up of 19 questions which were answered using a Likert-type scale; individuals with scores ranging from 19 to 76 and individuals above 45 points are considered at higher risk of side effects [27]. c) Depression was measured using the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) which consists of six questions generating a continuous score ranging from six to 24 points. Scores higher than or equal to 15 indicate a diagnosis of depression [28]; d) Anxiety: the short version of the State–Trait Anxiety Inventory (STAI) was used. The questionnaire is divided in two instruments, one assesses the anxiety status (STAI-S-6) and the other the anxiety traits (STAI-T-6). Each one consists of six questions ranging from six to 24 points. The higher the scores, the higher the state and anxiety traits [29]. 2.3.2. Independent variable To measure physical activity in adolescents and adults, the Physical Activity Questionnaire for Adolescents (PAQ-A) [30] and the International Physical Activity Questionnaire (IPAQ) [31] — long version, were respectively used. The IPAQ measures physical activity levels for a normal week in the domestic, leisure, commuting and work domains. However, this study only used the leisure and commuting domains, as the domestic and work domains seemed overestimated [32]. In the present study, the physical activity variable was categorized as follows: a) adults — inactive (less than 10 min of physical activity per week), insufficiently active (10 min or more per week and less than 150 min per week) and active (150 min or more of physical activity per week). b) Adolescents: inactive (0 min of physical activity per week), insufficiently active (more than 0 min and less than 300 min per week) and active (300 min or more of physical activity per week). Additionally, to calculate the scores for the IPAQ domains, minutes of vigorous physical activity were multiplied by two. The same process was followed for PAQ-A, in which sports were considered vigorous physical activities and, as a result, the reported time was also multiplied by two. The physical activity scores for leisure and commuting were added. As a cut-off point for the individuals considered active, recommendations from the World Health Organization (WHO) of 300 min of physical activity per week for adolescents and 150 min for adults in a week were used [33]. 2.3.3. Control variables The following variables were collected: 1) sociodemographic — sex (male/female), age (years), skin color (white, black, brown), marital status (single, married, widower, divorced), schooling (years), number of children (zero, one, two, three or more), income (reais), occupation (employed, unemployed, student or retired), and on social welfare (yes/no); 2) clinic — number of seizures during lifetime (≤15 seizures, N15 seizures), seizure type (generalized, focal, focal secondarily generalized or unknown), etiology of seizures (idiopathic, symptomatic or unknown) duration of epilepsy (≤ 15 years, N15 years), treatment (monotherapy/polytherapy), active epilepsy (yes/no) and seizure control (controlled, not always controlled, not controlled); 3) behavioral — smoking (never, ex-smoker, smoker); 4) health related — quality of sleep assessed by the Pittsburgh Sleep Quality Index (PSQI), containing 19 questions distributed in seven domains: subjective quality of the sleep, sleep latency, sleep duration, sleep efficiency, sleep disorders, drug-induced sleep use and diurnal disorder. Each item ranges from zero to three making up a total score of 21. The scores between zero and four indicate good sleep quality, scores between five and 10 show bad sleep quality and a score above 10 a sleep disorder is characterized [34]; stress levels — measured using Perceived Stress Scale (PSS-10), made up of 10 items regarding the situation in the last 30 days. Each item is answered according to the Likert scale ranging from zero (never) to four (very
30
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frequent). The scores range from zero to forty and the higher the score, the higher the individual perceived stress [35].
Table 1 General characteristics of people with epilepsy according physical activity levels (n = 101). Characteristics
2.4. Ethical procedure The study was analyzed and approved by the Ethical Committee from the Physical Education College of the Federal University of Pelotas under protocol numbered 1.231.971. The participants of the study were informed of the protocol and provided written consent. For individuals younger than 18 years, the participants' parents signed the consent form. 2.5. Statistical analysis Epidata software 3.1 was used to build up a dataset which was doubleentered and after checking for error, transfer of the dataset to Stata 13.1 was carried out. Descriptive statistics were used to characterize the sample (mean, standard deviation, median, interquartilic range and relative frequency). To verify the association of physical activity levels according to the control variables, analysis of variance (ANOVA) was used with post-hoc Bonferroni for parametric variables, and Kruskal–Wallis with Dun post-hoc for the non-parametric variables. Categorical variables were analyzed by Chi-squared tests. The visual histogram inspection along with the Shapiro–Wilk test to check the dependent variable normality and the Bartlet test to check variance homogeneity were used. All dependent variables were considered parametric. Simple linear regression was used for the crude analysis of all dependent variables according to physical activity levels. Adjusted analysis by multiple linear regression was conducted including sociodemographic, clinic, behavioral and health variables which the crude association with each dependent variables was p ≤ 0.05. The variables which were included in the model were removed one at a time (variables with higher p values) up to a point in which all included variables showed a p ≤ 0.2 value. The significance level was set at p b 0.05. 3. Results The characteristics of the sample study according to physical activity levels are shown in Table 1. Most of the independent variables do not present differences according to physical activity levels. Physical activity was associated with occupation. The active group showed better quality of sleep compared with the inactive and insufficiently active groups. Table 2 shows the crude association among dependent and control variables that were taken for regression analysis. Fifteen control variables were associated with quality of life and six variables remain associated after the adjusted regression analysis (skin color, welfare, active epilepsy, smoking, quality of sleep and stress). In the crude analysis, the dependent variable side effect of medication was associated with eight control variables and five variables remained associated after adjusted regression analysis (sex, number of seizures, etiology of seizure, quality of sleep and stress). Depression was associated with eight control variables in the crude analysis and five variables remained associated after adjusted regression analysis (sex, etiology of seizure, active epilepsy, quality of sleep and stress). After crude analysis, the state anxiety variable was associated with 10 control variables and seven variables remained associated (sex, skin color, marital status, schooling, income, quality of sleep and stress) after adjusted regression analysis. Finally, the trait anxiety variable was associated with six control variables and two variables remained associated after adjusted regression analysis (quality of sleep and stress). Table 3 shows the results of the crude and adjusted analyses among physical activity levels and dependent variables. In the crude analysis all dependent variables were associated with physical activity levels: depression (p = 0.046), anxiety state (p = 0.014), anxiety trait (p = 0.015), side effects of medication (p = 0.01) and quality of life (p b 0.001). In the crude analysis, physical activity levels could predict 10% of the quality of life score (R2 = 0.10) — individuals in the active group increased 17
Age (years) Schooling (years) Income (Reais) Sex (%) Male Female Skin color (%) White Black Brown Occupation (%) Student Employed Unemployed Retired Marital status (%) Single Married Widowed Divorced Number of children (%) 0 1 2 3 or more Welfare (%) Yes No Seizure type (%) Generalized Focal Focal secondarily generalized Unknown Etiology (%) Idiopathic Symptomatic Unknown Number of seizure during life (%) ≤15 seizures N15 seizures Duration of epilepsy (%) ≤15 years N15 years Treatment (%) Monotherapy Polytherapy Active epilepsy (%) Yes No Seizure control (%) Controlled Not always controlled Not controlled Smoking (%) Never Ex-smoker Smoker Quality of sleep Stress
Physical activity Inactive
Insufficiently active
Active
p value
35 ± 17 8±4 788 (0–1.200)
32 ± 17 7±3 788 (400–1.200)
31 ± 17 8±4 788 (600–1.200)
0.57α 0.82α 0.66†
51.4 48.7
42.9 57.1
55.6 44.4
70.2 13.5 16.2
50.0 25.0 25.0
55.6 27.8 16.7
13.5 32.4 35.1 18.9
32.1 17.9 42.9 7.1
44.4 33.3 11.1 11.1
46.0 43.2 8.1 2.7
60.7 21.4 3.6 14.3
69.4 22.2 5.6 2.8
62.2 13.5 13.5 10.8
57.1 10.7 28.6 3.6
69.4 11.1 2.8 16.7
27.0 73.0
32.1 67.9
11.1 88.9
26.2 50.0 57.6
28.6 50.0 21.2
45.2 00.0 21.2
40.0
40.0
20.0
22.7 54.2 42.1
22.7 16.7 36.8
54.5 29.2 21.0
0.61£
0.41£
0.01£
0.13£
0.10£
0.09£
0.05£
0.04£
0.58£ 33.3 66.7
33.3 66.7
44.1 55.9
48.6 51.4
53.9 46.1
57.1 42.9
57.6 42.4
57.1 42.9
81.3 18.8
70.3 29.7
78.6 21.4
55.6 44.4
48.6 25.7 25.7
44.0 32.0 24.0
75.0 11.1 13.9
59.5 21.6 18.9 8.1 ± 3.2 22.1 ± 6.5
78.6 10.7 10.7 8.3 ± 3.4 22.1 ± 7.6
69.4 22.2 8.3 6.4 ± 2.7a 19.5 ± 7.2
0.81£
0.07£
0.14£
0.09£
0.44£
0.03α 0.26α
Results are expressed as mean ± SD (parametric variables), median and interquartile range (nonparametric variables) and relative frequency (%) (categorical variables). Statistical tests: analysis of variance with Bonferroni post-hoc (α), Kruskal–Wallis with Dun post-hoc (†) and Chi-squared (£). a Statistically significant difference between groups (p b 0.05).
points when compared to the inactive group (β = 17.46). In the adjusted analysis, even after controlling for all control variables, physical activity levels were still associated with quality of life (p = 0.001), showing a
C.A. Häfele et al. / Epilepsy & Behavior 72 (2017) 28–34
31
Table 2 Crude analysis of the association among sociodemographic, clinic, behavioral and health variables and dependent variables (n = 101). Control variables
Dependent variables Quality of life
Side effect of medication
Depression
State anxiety
Trait anxiety
p
p
p
p
p
β CI 95%
β CI 95%
β CI 95%
β CI 95%
β CI 95%
0.001a – 5.86 (2.33; 9.39) –
0.004a – 2.33 (0.75; 3.91) –
b0.001a – 2.76 (1.42; 4.11) –
0.027 – 1.65 (0.19; 3.12) –
Skin color White Black Brown Marital status Single Married Widowed Divorced Schooling (years)
0.05 – −7.10 (−14.21; −0.00) 0.027 −0.24 (−0.44; −0.02) 0.05a – −4.82 (−13.74; 4.10) −8.96 (−18.37; 0.46) 0.022 – −6.25 (−14.26; 1.76) −9.57 (−24.84; 5.70) −13.51 (−28.78; 1.75) –
–
–
–
–
–
–
–
Number of children 0 1 2 3 or more Income (minimum salaries)
0.028 – −8.57 (−19.38; 2.25) −17.79 (−27.93; −7.65) −3.17 (−14.39; 8.05) –
0.02 – 5.01 (−0.72; 10.74) 8.92 (3.94; 13.91) 1.48 (−4.51; 7.48) –
0.04 – 0.43 (−2.09; 2.96) 3.30 (0.93; 5.67) 1.20 (−1.42; 3.82) –
0.01a – 0.67 (−1.09; 2.43) 2.40 (0.54; 4.26) 0.009a – −0.01 (−1.58; 1.56) 2.86 (−0.12; 5.84) 3.86 (0.87; 6.84) 0.05a −0.18 (−0.36; 0.00) –
Occupation Unemployed Employed Retired Student Welfare Yes No Number of seizures during life N15 seizures ≤15 seizures
0.002 – 9.57 (0.61; 18.53) 5.94 (−5.44; 17.32) 17.01 (8.05; 25.96) 0.01a – −10.96 (−19.28; −2.64) 0.001 – 12.59 (5.29; 19.89)
–
Duration of epilepsy ≤15 years N15 years Seizure type Generalized Focal Focal secondarily generalized Unknown Etiology Idiopathic Symptomatic Unknown Treatment Monotherapy Polytherapy Active epilepsy No Yes Seizure control Controlled Not always controlled Not controlled Smoking Never Ex-smoker Smoker Quality of sleep
Sex Male Female Age (years)
Stress a
–
– –
–
–
0.001a −0.002 (−0.003; −0.00) –
–
–
–
–
0.003a – −5.84 (−9.61; −2.06)
–
0.034 – −1.63 (−3.13; −0.12)
0.045 – −7.51 (−14.84; −0.18) –
–
–
–
–
0.050a – 3.73 (−1.82; 9.28) 5.1 (0.12; 10.08) –
0.064 – 0.62 (−3.69; 4.92) 2.42 (0.51; 4.34) −0.28 (−4.17; 3.61) 0.077a – 1.72 (−0.74; 4.18) 2.09 (−0.14; 4.32) –
0.05 – 1.44 (−0.01; 2.88) –
0.045 – −1.57 (−3.11; −0.03) –
0.012 – 4.97 (1.13; 8.80) b0.001 – 6.67 (2.39; 10.95) 7.80 (3.35; 12.24) –
b0.001a 1.79 (1.34; 2.25) b0.001a 0.63 (0.40; 0.87)
0.005 – −11.22 (−18.98; −3.47) b0.001a – −13.82 (−21.08; −6.57) 0.007 – −9.85 (−18.77; −0.93) −11.20 (−20.28; −2.13) 0.012a – −3.40 (−12.52; 5.72) −14.29 (−24.93; −3.65) b0.001a −3.33 (−4.31; −2.35) b0.001a −1.28 (−1.74; −0.82)
–
–
–
–
–
–
0.006a – 2.37 (0.68; 4.05) 0.04 – 2.18 (0.09; 4.27) 1.83 (−0.30; 3.95) –
–
0.002 – 2.21 (0.43; 3.99) 2.58 (0.77; 4.39) –
0.021 – 1.86 (0.29; 3.44) 0.025 – 1.80 (−0.05; 3.66) 1.91 (0.02; 3.80) –
b0.001a 0.58 (0.33; 0.83) b0.001a 0.31 (0.21; 0.41)
b0.001a 0.46 (0.25; 0.68) b0.001a 0.23 (0.14; 0.33)
b0.001a 0.44 (0.22; 0.67) b0.001a 0.26 (0.16; 0.35)
Remained associated after multiple linear regression model analysis (p ≤ 0.2).
positive linear trend between groups of physical activity (insufficiently active β = 7.31; active β = 10.05 compared with the inactive group). The linear regression model explained 67% of quality of life scores (R2
= 0.67). In the adjusted analysis, the linear regression model predicted 64% of side effects of medication scores (R2 = 0.64). Further, was observed in the active subjects less 4.62 points in side effects scores (β
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Table 3 Simple and multiple linear regression of dependent variables according to physical activity levels (n = 101).
Dependent variable
Predictor
Quality of life
Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active
Side effect of medication
Depression
State anxiety
Trait anxiety
Crude
Adjusted
β CI 95%
p
R2
b0.001
0.10
– 6.11 (−2.24; 14.45) 17.46 (9.65; 25.27)
β CI 95%
p
R2
0.001a
0.67
0.014b
0.64
0.033a
0.55
0.004a
0.60
0.066a
0.34
– 7.31 (1.11; 13.51) 10.05 (4.12; 15.97) 0.01
0.06
– −0.71 (−4.86; 3.44) −8.66 (−12.71; −4.61)
– 0.43 (−2.80; 3.67) −4.62 (−8.06; −1.17) 0.046
0.03
– −0.17 (−2.13; 1.80) −2.90 (−4.73; −1.06)
– −0.53 (−2.25; 1.20) −2.80 (−4.55; −1.04) 0.014
0.05
– −2.59 (−4.23; −0.95) −2.59 (−4.23; −0.95)
– −1.54 (−3.06; −0.03) −1.98 (−3.33; −0.62) 0.015
0.05
– −1.42 (−3.25; 0.40) −2.47 (−3.99; −0.55)
– −1.04 (−2.67; 0.59) −1.44 (−3.00; 0.12)
R2: change in the percentage of the variance of the dependent variable explained by the predictor before and after excluding the effect of the control variables. The control variables for regression analysis are shown in Table 2. a Linear trend. b Heterogeneity.
= −4.62; p = 0.014). There was a linear trend in which the depression score is reduced when the physical activity levels increase (p = 0.033) in the adjusted analysis. The individuals from the active group presented approximately a three point lower score in depression in comparison to the inactive group (β = −2.80). For the state anxiety variable, even controlling for confounding variables, the physical activity variable remained associated. The higher the physical activity level, the lower the anxiety state scores (p b 0.004). Nevertheless, the trait anxiety did not remain associated in the adjusted analysis (p = 0.066). 4. Discussion The present study aimed to investigate the association among leisure-time and commuting physical activity levels and several health outcomes (quality of life, medication side effects, depression and state and trait anxiety) in PWE. These people commonly present worse health habits when compared with the general population [36], showing high smoking prevalence [36] and reduced levels of physical activity [14,15] and fitness [37,13]. These life conditions for PWE may be associated with a higher prevalence of psychiatric morbidities such as depression and anxiety [3,21], which lead to a low quality of life. The main finding of the study was that the improvement in health conditions of individuals with epilepsy was associated with physical activity. Even after the adjusted analysis, and controlling for confounding variables (such as sex, age, number of seizures, seizure type, duration of epilepsy, sleep quality, stress levels, among others), physical activity was still associated with improved scores in all analyzed health outcomes (except trait anxiety). 4.1. Quality of life Regarding quality of life, the study shows a linear trend between the groups. The higher the level of physical activity, the higher the quality of life, which increased by 10% for physically active individuals (β = 10.05). A former study by McAuley et al. [22] corroborate with our finding. The authors carried out a randomized clinical trial for 12 weeks with adults with epilepsy divided into two groups: an intervention group (performing physical exercise) and a controlled group (without
exercise). The total score for quality of life improved in the intervention group but it was not altered in the control group. 4.2. Depression and anxiety Results from the present study show associations between physical activity levels and anxiety state and depression, not only in the crude analysis but also in the adjusted one. The trait anxiety did not remain associated after regression analysis. These findings agree with studies previously carried out in PWE [20,21]. De Lima et al. [21] compared PWE with individuals without the disease and found higher scores for depression and anxiety among PWE. Although physical activity levels were not different between the groups, leisure-time physical inactivity may predict 31% of depression levels and 26% of anxiety levels in the epileptic group. Han et al. [20] compared physically active epileptic individuals with physically inactive ones and found an association in the crude analysis showing that active individuals presented reduced depression levels, whereas the adjusted analysis showed that physical inactivity alone may predict anxiety. There are several mechanisms supporting the positive changes promoted by physical activity on mental health. These mechanisms are divided into: psychological (distraction, social interaction, self-efficacy, expectations for changes and pleasure in the activities), physiological (thermogenic and brain blood flow), and neurophysiological (monoamines, cerebral lateralization and endorphins) [38]. In this regard, physical activity may have increased endorphin levels and this increase is associated with reduction in anxiety and depression, vigor, wellbeing and increased levels of euphoria[39]. Another explanation for this phenomenon is the monoamine hypothesis which suggests that physical activity level increases the serotonin and norepinephrine levels which are decreased in depressed people, indicating an improvement in humor profile [40,41]. 4.3. Side effects of medication Regarding the side effects of antiepileptic medication, studies which evaluated the effect of physical activity were not found. The results presented in this study indicate that there was a five point reduction in the total score of side effects for active group individuals. In a recent study, Noble et al. [42] questioned the priorities of epilepsy treatment using a
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questionnaire directed to patients themselves and to the caregivers. From the 10 mentioned priorities, improvement in quality of life and side effect reduction from medications are among the top five for both (patients and caregivers). Improvement in quality of life and reduction of medication side effects are in the first and second positions, respectively, according to the caregivers. Therefore, the results are very relevant, considering a positive association between physical activity practice and the abovementioned priorities. The results help to fill a knowledge gap, because Saadi et al. [43] showed that there is a need for further studies evaluating the quality of life of PWE in low- and middle-income countries. The findings from the present study showed physical activity as a nonpharmacological alternative to improve health and life conditions of individuals with epilepsy. As a result, quality of life is improved, medication side effects are reduced, and anxiety and depression levels are reduced. In addition to all the benefits mentioned above, studies on rats [44] and humans [45,23] have shown that physical exercise may also contribute to control epileptic seizures. This is the first study in Brazil to analyze a linear trend for physical activity levels regarding health outcomes in PWE. From a methodological point of view, the standardization for data collection as well as the careful choice of statistical tests should be highlighted to achieve the aims of the research. 4.4. Limitations Although there is a biological plausibility of an association between the physical activity and health variables [17,22], this cross-sectional study is not an ideal design to verify the cause and effect relationship. Another limitation was regarding the instruments used to assess depression, quality of sleep and stress levels, which were validated only for adults and the elderly. However, validated instruments for adolescents which aim at measuring these variables are unknown. As a result, more studies are needed, mainly randomized clinical trials, to establish a more precise relationship between cause and effect. 5. Conclusion Physical activities, such as, leisure-time and commuting, are associated with health outcomes. The higher the physical activity level, the higher the scores for quality of life in addition to reducing depression, anxiety state and medication side effects scores. To sum up, physical activity regarding the analyzed domains may be a nonpharmacological treatment to improve health and life conditions of PWE. Funding sources The research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector. Conflict of interest The authors declare no conflicts of interest. Acknowledgments The authors thank the Faculty of Medicine of the Federal University of Pelotas for the authorization for the data collection. We would like to thank the subjects who volunteered their time to participate in this study. References [1] Thurman DJ, Beghi E, Begley CE, Berg AT, Buchhalter JR, Ding D, et al. Standards for epidemiologic studies and surveillance of epilepsy. Epilepsia 2011;52:2–26.
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Modification in body weight associated with antiepileptic drugs. Arq Neuropsiquiatr 2010;68:277–81. [9] Petty SJ, O'Brien TJ, Wark JD. Anti-epileptic medication and bone healthy. Osteoporos Int 2007;18:129–42. [10] Zeng K, Wang X, Xi Z, Yan Y. Adverse effects of carbamazepine, phenytoin, valproate and lamotrigine monotherapy in epileptic adult Chinese patients. Cli Neurol Neurosurg 2010;112:291–5. [11] Pimentel J, Tojal R, Morgado J. Epilepsy and physical exercise. Seizure 2015;25: 87–94. [12] Capovilla G, Kaufman KR, Perucca E, Moshé SL, Arida RM. Epilepsy, seizures, physical exercise, and sports: a report from the ILAE Task Force on Sports and Epilepsy. Epilepsia 2016;57:6–12. [13] Jalava M, Sillanpää M. Physical activity, health-related fitness, and health experience in adults with childhood-onset epilepsy: a controlled study. Epilepsia 1997;38:424–9. [14] Nakken KO. Physical exercise in outpatients with epilepsy. Epilepsia 1999;40: 643–51. [15] Wong J, Wirrel E. Physical activity in children/teens with epilepsy compared with that in their siblings without epilepsy. Epilepsia 2006;47:631–9. [16] Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzik PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012;380:219–29. [17] Conn VS. Depressive symptom outcomes of physical activity interventions: metaanalysis findings. Ann Behav Med 2010;39:128–38. [18] Khanzada FJ, Soomro N, Khan SZ. Association of physical exercise on anxiety and depression amongst adults. J Coll Phys Surg Pak 2015;25:546–8. [19] Pucci GCMF, Rech CR, Fermino RC, Reis RS. Association between physical activity and quality of life in adults. Rev Saúde Pública 2012;46:166–79. [20] Han K, Choi-Kwon S, Lee S. Leisure time physical activity in patients with epilepsy in Seoul, South Korea. Epilepsy Behav 2011;20:321–5. [21] de Lima C, de Lira CAB, Arida RM, Andersen LM, Matos G, Guilhoto LMFF, et al. Association between leisure time, physical activity, and mood disorder levels in individuals with epilepsy. Epilepsy Behav 2013;28:47–51. [22] McAuley JW, Long L, Heise J, Kirby T, Buckworth J, Lehman KJ, et al. A prospective evaluation of the effects of a 12-week outpatient exercise program on clinical and behavioral outcomes in patients with epilepsy. Epilepsy Behav 2001;2:592–600. [23] Häfele CA, Freitas MP, Rombaldi AJ. Physical exercise effects on epilepsy in humans: a systematic review. Rev Neuroscien 2015(23):328–36. [24] Kvalsund MP, Birbeck GL. Epilepsy care challenges in developing countries. Curr Opin Neurol 2012;25:179–86. [25] Silva TI, Marques CM, Alonso NB, Azevedo AM, Westphal-Guitti AC, Caboclo LOSF, et al. Translation and cross-cultural adaptation of the Quality of Life in Epilepsy-31 (QOLIE-31). J Epilepsy Clin Neurophysiol 2006;12:107–10. [26] Barbosa FD, Guerreiro MM, Souza EAP. The Brazilian version of the Quality of Life in Epilepsy Inventory for Adolescents: translation, validity, and reliability. Epilepsy Behav 2008;13:218–22. [27] Gilliam FG, Fessler AJ, Baker G, Vahle V, Carter J, Attarian H. Systematic screening allows reduction of adverse antiepileptic drug effects: a randomized trial. Neurology 2004;62:23–7. [28] Gilliam FG, Barry JJ, Hermann BP, Meador KJ, Vahle V, Kanner AM. Rapid detection of major depression in epilepsy: a multicentre study. Lancet Neurol 2006;5:399–405. [29] Fioravanti-Bastos ACM, Cheniaux E, Landeira-Fernandez J. Development and validation of a short-form version of the Brazilian State–Trait Anxiety Inventory. Psicol: Reflex Crit 2011;24:485–94. [30] Farias Junior JC, Lopes AS, Mota J, Santos MP, Ribeiro JC, Hallal PC. Validade e reprodutibilidade de um questionário para medida de atividade física em adolescentes: uma adaptação do Self-administered Physical Activity Checklist. Rev Bras Epidemiol 2012;15:198–210. [31] Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381–95. [32] Hallal PC, Gomez LF, Parra DC, Lobelo F, Mosquera J, Florindo AA, et al. Lessons learned after 10 years of IPAQ use in Brazil and Colombia. J Phys Act Health 2010;7:259–64. [33] World Health Organization. Global recommendations on physical activity for healthGeneva ; 2010. [34] Bertolazi AN. Tradução, adaptação cultural e validação de dois instrumentos de avaliação do sono: Escala de Sonolência de Epworth e Índice de Qualidade do Sono Pittsburgh [Dissertação]. Porto Alegre: Faculdade de Medicina, Universidade Federal do Rio Grande do Sul; 2008. [35] Reis RS, Hino AA, Añez CR. Perceived stress scale: reliability and validity study in Brazil. J Health Psychol 2010;15:107–14. [36] Elliot JO, Lu B, Moore JL, McAuley JW, Long L. 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Contents lists available at ScienceDirect
Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh
Are physical activity levels associated with better health outcomes in people with epilepsy? César Augusto Häfele ⁎, Matheus Pintanel Freitas, Marcelo Cozzensa da Silva, Airton José Rombaldi Escola Superior de Educação Física, Universidade Federal de Pelotas, RS, Brazil Programa de Pós-Graduação em Educação Física, Universidade Federal de Pelotas, RS, Brazil Grupo de Estudos em Epidemiologia da Atividade Física, Universidade Federal de Pelotas, RS, Brazil School of Physical Education, Federal University of Pelotas, Rua Luís de Camões, 625, 96055630 Pelotas, RS, Brazil
a r t i c l e
i n f o
Article history: Received 16 January 2017 Revised 19 April 2017 Accepted 22 April 2017 Available online xxxx Keywords: Mental health Seizure Epilepsy Physical activity Behavior
a b s t r a c t The aim of the study was to investigate the association of physical activity in three categories (inactive, insufficiently active and active) with health outcomes in people with epilepsy. The dependent variables and the instruments used in the study were: a) quality of life — measured by Quality of Life in Epilepsy-31 for adults and Quality of Life in Epilepsy for Adolescents, b) side effects of medication — measured by Adverse Events Profile, c) depression — measured by Neurological Disorders Depression Inventory for Epilepsy, and d) state and trait anxiety — measured by State–Trait Anxiety Inventory. Physical activity levels were analyzed using the International Physical Activity Questionnaire (IPAQ) for adults in the commuting and leisure domains and Physical Activity Questionnaire for Adolescents (PAQ-A). Simple and multiple linear regression was used in the statistical analysis. The cross-sectional study with one hundred and one individuals was conducted in Pelotas/RS, Brazil, at the Neurology Clinic of the Faculty of Medicine of the Federal University of Pelotas. In the crude analysis, physical activity was positively associated with quality of life (p b 0.001) and negatively associated with depression (p = 0.046), state of anxiety (p = 0.014), trait of anxiety (p = 0.015) and side effect of medication (p = 0.01). In addition, physical activity levels explained 10% of the quality of life (R2 = 0.10). In the adjusted analysis, physical activity remained associated with side effect of medication (p = 0.014) and was not associated with trait anxiety (p = 0.066). However, quality of life showed a positive linear trend (p = 0.001) while depression (p = 0.033) and anxiety state (p = 0.004) showed a negative trend according to physical activity levels. Physical activity was associated with health outcomes, and can be a nonpharmacological treatment in people with epilepsy for improving health and life conditions. © 2017 Elsevier Inc. All rights reserved.
1. Introduction Epilepsy is a neurological disease which affects around 65 million people in the world [1]. Fisher et al. [2] proposed that this disease is characterized by a brain disorder defined by any of the following conditions: (1) at least two unprovoked seizures occurring in an interval longer than 24 h; (2) one unprovoked seizure and a risk greater than 60% of a new seizures; and (3) diagnosis of an epilepsy syndrome. When compared to the general population, people with epilepsy (PWE) show higher levels of depression and anxiety [3], which leads to a reduction in the quality of life scores [4–6]. In addition, the drugs used in the treatment of the disease, despite promoting significant seizure control [7], cause several side effects such as: weight gain [8], reduction in bone ⁎ Corresponding author at: Rua Luís de Camões, 625, 96055630 Pelotas, RS, Brazil. E-mail addresses: [email protected] (C.A. Häfele), [email protected] (M.P. Freitas), [email protected] (M.C. da Silva), [email protected] (A.J. Rombaldi).
http://dx.doi.org/10.1016/j.yebeh.2017.04.038 1525-5050/© 2017 Elsevier Inc. All rights reserved.
mineral density [9], fatigue/tiredness, gastrointestinal disorders, appetite reduction, and hand shaking, among others [10]. Historically, PWE have been advised against participation in physical exercise and sports, mainly because of overprotection, fear, and ignorance about the risks and benefits of physical activity practice [11]. However, a number of studies reported that these activities may have a positive influence on the frequency and severity of seizures. Thus, recommendations in clinical practice and attitudes toward sports and epilepsy have changed considerably [11,12]. Recently, The Task Force on Sports and Epilepsy developed a consensus paper with general guidance concerning participation in physical exercise and sports for PWE. These suggestions are directed to physicians and other health care professionals involved in the treatment of PWE [12]. Studies, which compare physical activity levels and physical fitness among PWE and the general population, concluded that PWE had worse physical fitness and a greater number of individuals who never performed any physical activity [13,14]. In addition, a study, which compared teens with epilepsy to their siblings without epilepsy, found that
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teens with epilepsy participated less in sports activities than their control siblings [15]. Physical activity practice promotes several health benefits. In 2012, in a Lancet physical activity series, Lee et al. [16] reported that if physical inactivity levels were reduced by 25%, around 1.3 million deaths would be avoided each year. In addition to the benefits regarding chronic diseases, it is well known that physical activity practice reduces the levels of depression [17] and anxiety [18] in the general population, thus, improving quality of life [19]. Studies evaluating the association between physical activity practice and depression/anxiety in PWE reported positive results for the physically active [20,21]. A different study evaluating the influence of physical activity in the quality of life of PWE showed that the group which performed physical activity improved the general scores in this aspect and the control group did not show any alteration [22]. It is well known that PWE show worse health scores and undoubtedly, physical activity plays an important role in improving these scores in the general population [16–18]. However, few studies on this topic were found [20,23], mainly in low- and middle-income countries [21] where approximately 80% of PWE are living [24]. Therefore, the aim of this study was to verify the association between physical activity levels (inactive, insufficiently active and active) with scores regarding quality of life, depression, anxiety and side effects of medication in PWE. 2. Materials and methods 2.1. Participants A cross-sectional study was carried out aiming at determining the influence of physical activity on different health outcomes in PWE. The study was conducted in Pelotas, southern Brazil, at the neurology clinic of the Faculty of Medicine of the Federal University of Pelotas. One hundred and one individuals (101) between 12 and 75 years diagnosed with epilepsy participated in the study. Data collection was carried out for five months, from December 1st 2015 to April 30th 2016. 2.2. Procedure First, the director of the Medicine Faculty was contacted to obtain authorization for data collection. After which a visit was made to the clinic with the purpose of meeting the staff. Data collection was carried out as follows: first, using the records of the neurology clinic in 2015, patients with epilepsy were diagnosed. Following this procedure a telephone contact was made with these individuals explaining the aims of the research and inviting them to take part. Second, at neurological service days, the researcher accessed the patient records prior to consultation to verify those who were diagnosed with epilepsy. While the patients waited for their consultation, the researcher invited them to participate in the study. This procedure was not conducted for first-time patients. In this case, the researcher waited for the consultation and if the doctor diagnosed the patient with epilepsy, he/she would invite him/her for the study. 2.3. Demographic and epilepsy data questionnaires 2.3.1. Dependent variables The following continuous dependent variables were used in the present study: a) quality of life, measured using Quality of Life in Epilepsy Inventory-31 for adults (QOLIE-31) [25] and Quality of Life in Epilepsy Inventory for Adolescents (QOLIE-AD-48) [26]. The QOLIE-31 is made up of 31 questions distributed into seven domains: general quality of life, seizure worry, emotional wellness, energy and fatigue, cognitive function, social functioning and medication effects. On the other hand, QOLIE-AD-48 is made up of 48 questions distributed into eight domains: epilepsy impact, memory and concentration, attitude toward epilepsy, physical functioning, epilepsy stigma, social support, scholar behavior,
29
and health perception. Both instruments generated a continuous total score ranging from zero to 100. The higher the score, the higher the quality of life. This study used only the total score from both questionnaires. b) Side effects: the Adverse Effects Profile (AEP) scale is made up of 19 questions which were answered using a Likert-type scale; individuals with scores ranging from 19 to 76 and individuals above 45 points are considered at higher risk of side effects [27]. c) Depression was measured using the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) which consists of six questions generating a continuous score ranging from six to 24 points. Scores higher than or equal to 15 indicate a diagnosis of depression [28]; d) Anxiety: the short version of the State–Trait Anxiety Inventory (STAI) was used. The questionnaire is divided in two instruments, one assesses the anxiety status (STAI-S-6) and the other the anxiety traits (STAI-T-6). Each one consists of six questions ranging from six to 24 points. The higher the scores, the higher the state and anxiety traits [29]. 2.3.2. Independent variable To measure physical activity in adolescents and adults, the Physical Activity Questionnaire for Adolescents (PAQ-A) [30] and the International Physical Activity Questionnaire (IPAQ) [31] — long version, were respectively used. The IPAQ measures physical activity levels for a normal week in the domestic, leisure, commuting and work domains. However, this study only used the leisure and commuting domains, as the domestic and work domains seemed overestimated [32]. In the present study, the physical activity variable was categorized as follows: a) adults — inactive (less than 10 min of physical activity per week), insufficiently active (10 min or more per week and less than 150 min per week) and active (150 min or more of physical activity per week). b) Adolescents: inactive (0 min of physical activity per week), insufficiently active (more than 0 min and less than 300 min per week) and active (300 min or more of physical activity per week). Additionally, to calculate the scores for the IPAQ domains, minutes of vigorous physical activity were multiplied by two. The same process was followed for PAQ-A, in which sports were considered vigorous physical activities and, as a result, the reported time was also multiplied by two. The physical activity scores for leisure and commuting were added. As a cut-off point for the individuals considered active, recommendations from the World Health Organization (WHO) of 300 min of physical activity per week for adolescents and 150 min for adults in a week were used [33]. 2.3.3. Control variables The following variables were collected: 1) sociodemographic — sex (male/female), age (years), skin color (white, black, brown), marital status (single, married, widower, divorced), schooling (years), number of children (zero, one, two, three or more), income (reais), occupation (employed, unemployed, student or retired), and on social welfare (yes/no); 2) clinic — number of seizures during lifetime (≤15 seizures, N15 seizures), seizure type (generalized, focal, focal secondarily generalized or unknown), etiology of seizures (idiopathic, symptomatic or unknown) duration of epilepsy (≤ 15 years, N15 years), treatment (monotherapy/polytherapy), active epilepsy (yes/no) and seizure control (controlled, not always controlled, not controlled); 3) behavioral — smoking (never, ex-smoker, smoker); 4) health related — quality of sleep assessed by the Pittsburgh Sleep Quality Index (PSQI), containing 19 questions distributed in seven domains: subjective quality of the sleep, sleep latency, sleep duration, sleep efficiency, sleep disorders, drug-induced sleep use and diurnal disorder. Each item ranges from zero to three making up a total score of 21. The scores between zero and four indicate good sleep quality, scores between five and 10 show bad sleep quality and a score above 10 a sleep disorder is characterized [34]; stress levels — measured using Perceived Stress Scale (PSS-10), made up of 10 items regarding the situation in the last 30 days. Each item is answered according to the Likert scale ranging from zero (never) to four (very
30
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frequent). The scores range from zero to forty and the higher the score, the higher the individual perceived stress [35].
Table 1 General characteristics of people with epilepsy according physical activity levels (n = 101). Characteristics
2.4. Ethical procedure The study was analyzed and approved by the Ethical Committee from the Physical Education College of the Federal University of Pelotas under protocol numbered 1.231.971. The participants of the study were informed of the protocol and provided written consent. For individuals younger than 18 years, the participants' parents signed the consent form. 2.5. Statistical analysis Epidata software 3.1 was used to build up a dataset which was doubleentered and after checking for error, transfer of the dataset to Stata 13.1 was carried out. Descriptive statistics were used to characterize the sample (mean, standard deviation, median, interquartilic range and relative frequency). To verify the association of physical activity levels according to the control variables, analysis of variance (ANOVA) was used with post-hoc Bonferroni for parametric variables, and Kruskal–Wallis with Dun post-hoc for the non-parametric variables. Categorical variables were analyzed by Chi-squared tests. The visual histogram inspection along with the Shapiro–Wilk test to check the dependent variable normality and the Bartlet test to check variance homogeneity were used. All dependent variables were considered parametric. Simple linear regression was used for the crude analysis of all dependent variables according to physical activity levels. Adjusted analysis by multiple linear regression was conducted including sociodemographic, clinic, behavioral and health variables which the crude association with each dependent variables was p ≤ 0.05. The variables which were included in the model were removed one at a time (variables with higher p values) up to a point in which all included variables showed a p ≤ 0.2 value. The significance level was set at p b 0.05. 3. Results The characteristics of the sample study according to physical activity levels are shown in Table 1. Most of the independent variables do not present differences according to physical activity levels. Physical activity was associated with occupation. The active group showed better quality of sleep compared with the inactive and insufficiently active groups. Table 2 shows the crude association among dependent and control variables that were taken for regression analysis. Fifteen control variables were associated with quality of life and six variables remain associated after the adjusted regression analysis (skin color, welfare, active epilepsy, smoking, quality of sleep and stress). In the crude analysis, the dependent variable side effect of medication was associated with eight control variables and five variables remained associated after adjusted regression analysis (sex, number of seizures, etiology of seizure, quality of sleep and stress). Depression was associated with eight control variables in the crude analysis and five variables remained associated after adjusted regression analysis (sex, etiology of seizure, active epilepsy, quality of sleep and stress). After crude analysis, the state anxiety variable was associated with 10 control variables and seven variables remained associated (sex, skin color, marital status, schooling, income, quality of sleep and stress) after adjusted regression analysis. Finally, the trait anxiety variable was associated with six control variables and two variables remained associated after adjusted regression analysis (quality of sleep and stress). Table 3 shows the results of the crude and adjusted analyses among physical activity levels and dependent variables. In the crude analysis all dependent variables were associated with physical activity levels: depression (p = 0.046), anxiety state (p = 0.014), anxiety trait (p = 0.015), side effects of medication (p = 0.01) and quality of life (p b 0.001). In the crude analysis, physical activity levels could predict 10% of the quality of life score (R2 = 0.10) — individuals in the active group increased 17
Age (years) Schooling (years) Income (Reais) Sex (%) Male Female Skin color (%) White Black Brown Occupation (%) Student Employed Unemployed Retired Marital status (%) Single Married Widowed Divorced Number of children (%) 0 1 2 3 or more Welfare (%) Yes No Seizure type (%) Generalized Focal Focal secondarily generalized Unknown Etiology (%) Idiopathic Symptomatic Unknown Number of seizure during life (%) ≤15 seizures N15 seizures Duration of epilepsy (%) ≤15 years N15 years Treatment (%) Monotherapy Polytherapy Active epilepsy (%) Yes No Seizure control (%) Controlled Not always controlled Not controlled Smoking (%) Never Ex-smoker Smoker Quality of sleep Stress
Physical activity Inactive
Insufficiently active
Active
p value
35 ± 17 8±4 788 (0–1.200)
32 ± 17 7±3 788 (400–1.200)
31 ± 17 8±4 788 (600–1.200)
0.57α 0.82α 0.66†
51.4 48.7
42.9 57.1
55.6 44.4
70.2 13.5 16.2
50.0 25.0 25.0
55.6 27.8 16.7
13.5 32.4 35.1 18.9
32.1 17.9 42.9 7.1
44.4 33.3 11.1 11.1
46.0 43.2 8.1 2.7
60.7 21.4 3.6 14.3
69.4 22.2 5.6 2.8
62.2 13.5 13.5 10.8
57.1 10.7 28.6 3.6
69.4 11.1 2.8 16.7
27.0 73.0
32.1 67.9
11.1 88.9
26.2 50.0 57.6
28.6 50.0 21.2
45.2 00.0 21.2
40.0
40.0
20.0
22.7 54.2 42.1
22.7 16.7 36.8
54.5 29.2 21.0
0.61£
0.41£
0.01£
0.13£
0.10£
0.09£
0.05£
0.04£
0.58£ 33.3 66.7
33.3 66.7
44.1 55.9
48.6 51.4
53.9 46.1
57.1 42.9
57.6 42.4
57.1 42.9
81.3 18.8
70.3 29.7
78.6 21.4
55.6 44.4
48.6 25.7 25.7
44.0 32.0 24.0
75.0 11.1 13.9
59.5 21.6 18.9 8.1 ± 3.2 22.1 ± 6.5
78.6 10.7 10.7 8.3 ± 3.4 22.1 ± 7.6
69.4 22.2 8.3 6.4 ± 2.7a 19.5 ± 7.2
0.81£
0.07£
0.14£
0.09£
0.44£
0.03α 0.26α
Results are expressed as mean ± SD (parametric variables), median and interquartile range (nonparametric variables) and relative frequency (%) (categorical variables). Statistical tests: analysis of variance with Bonferroni post-hoc (α), Kruskal–Wallis with Dun post-hoc (†) and Chi-squared (£). a Statistically significant difference between groups (p b 0.05).
points when compared to the inactive group (β = 17.46). In the adjusted analysis, even after controlling for all control variables, physical activity levels were still associated with quality of life (p = 0.001), showing a
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31
Table 2 Crude analysis of the association among sociodemographic, clinic, behavioral and health variables and dependent variables (n = 101). Control variables
Dependent variables Quality of life
Side effect of medication
Depression
State anxiety
Trait anxiety
p
p
p
p
p
β CI 95%
β CI 95%
β CI 95%
β CI 95%
β CI 95%
0.001a – 5.86 (2.33; 9.39) –
0.004a – 2.33 (0.75; 3.91) –
b0.001a – 2.76 (1.42; 4.11) –
0.027 – 1.65 (0.19; 3.12) –
Skin color White Black Brown Marital status Single Married Widowed Divorced Schooling (years)
0.05 – −7.10 (−14.21; −0.00) 0.027 −0.24 (−0.44; −0.02) 0.05a – −4.82 (−13.74; 4.10) −8.96 (−18.37; 0.46) 0.022 – −6.25 (−14.26; 1.76) −9.57 (−24.84; 5.70) −13.51 (−28.78; 1.75) –
–
–
–
–
–
–
–
Number of children 0 1 2 3 or more Income (minimum salaries)
0.028 – −8.57 (−19.38; 2.25) −17.79 (−27.93; −7.65) −3.17 (−14.39; 8.05) –
0.02 – 5.01 (−0.72; 10.74) 8.92 (3.94; 13.91) 1.48 (−4.51; 7.48) –
0.04 – 0.43 (−2.09; 2.96) 3.30 (0.93; 5.67) 1.20 (−1.42; 3.82) –
0.01a – 0.67 (−1.09; 2.43) 2.40 (0.54; 4.26) 0.009a – −0.01 (−1.58; 1.56) 2.86 (−0.12; 5.84) 3.86 (0.87; 6.84) 0.05a −0.18 (−0.36; 0.00) –
Occupation Unemployed Employed Retired Student Welfare Yes No Number of seizures during life N15 seizures ≤15 seizures
0.002 – 9.57 (0.61; 18.53) 5.94 (−5.44; 17.32) 17.01 (8.05; 25.96) 0.01a – −10.96 (−19.28; −2.64) 0.001 – 12.59 (5.29; 19.89)
–
Duration of epilepsy ≤15 years N15 years Seizure type Generalized Focal Focal secondarily generalized Unknown Etiology Idiopathic Symptomatic Unknown Treatment Monotherapy Polytherapy Active epilepsy No Yes Seizure control Controlled Not always controlled Not controlled Smoking Never Ex-smoker Smoker Quality of sleep
Sex Male Female Age (years)
Stress a
–
– –
–
–
0.001a −0.002 (−0.003; −0.00) –
–
–
–
–
0.003a – −5.84 (−9.61; −2.06)
–
0.034 – −1.63 (−3.13; −0.12)
0.045 – −7.51 (−14.84; −0.18) –
–
–
–
–
0.050a – 3.73 (−1.82; 9.28) 5.1 (0.12; 10.08) –
0.064 – 0.62 (−3.69; 4.92) 2.42 (0.51; 4.34) −0.28 (−4.17; 3.61) 0.077a – 1.72 (−0.74; 4.18) 2.09 (−0.14; 4.32) –
0.05 – 1.44 (−0.01; 2.88) –
0.045 – −1.57 (−3.11; −0.03) –
0.012 – 4.97 (1.13; 8.80) b0.001 – 6.67 (2.39; 10.95) 7.80 (3.35; 12.24) –
b0.001a 1.79 (1.34; 2.25) b0.001a 0.63 (0.40; 0.87)
0.005 – −11.22 (−18.98; −3.47) b0.001a – −13.82 (−21.08; −6.57) 0.007 – −9.85 (−18.77; −0.93) −11.20 (−20.28; −2.13) 0.012a – −3.40 (−12.52; 5.72) −14.29 (−24.93; −3.65) b0.001a −3.33 (−4.31; −2.35) b0.001a −1.28 (−1.74; −0.82)
–
–
–
–
–
–
0.006a – 2.37 (0.68; 4.05) 0.04 – 2.18 (0.09; 4.27) 1.83 (−0.30; 3.95) –
–
0.002 – 2.21 (0.43; 3.99) 2.58 (0.77; 4.39) –
0.021 – 1.86 (0.29; 3.44) 0.025 – 1.80 (−0.05; 3.66) 1.91 (0.02; 3.80) –
b0.001a 0.58 (0.33; 0.83) b0.001a 0.31 (0.21; 0.41)
b0.001a 0.46 (0.25; 0.68) b0.001a 0.23 (0.14; 0.33)
b0.001a 0.44 (0.22; 0.67) b0.001a 0.26 (0.16; 0.35)
Remained associated after multiple linear regression model analysis (p ≤ 0.2).
positive linear trend between groups of physical activity (insufficiently active β = 7.31; active β = 10.05 compared with the inactive group). The linear regression model explained 67% of quality of life scores (R2
= 0.67). In the adjusted analysis, the linear regression model predicted 64% of side effects of medication scores (R2 = 0.64). Further, was observed in the active subjects less 4.62 points in side effects scores (β
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Table 3 Simple and multiple linear regression of dependent variables according to physical activity levels (n = 101).
Dependent variable
Predictor
Quality of life
Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active Physical activity levels Inactive Insufficiently active Active
Side effect of medication
Depression
State anxiety
Trait anxiety
Crude
Adjusted
β CI 95%
p
R2
b0.001
0.10
– 6.11 (−2.24; 14.45) 17.46 (9.65; 25.27)
β CI 95%
p
R2
0.001a
0.67
0.014b
0.64
0.033a
0.55
0.004a
0.60
0.066a
0.34
– 7.31 (1.11; 13.51) 10.05 (4.12; 15.97) 0.01
0.06
– −0.71 (−4.86; 3.44) −8.66 (−12.71; −4.61)
– 0.43 (−2.80; 3.67) −4.62 (−8.06; −1.17) 0.046
0.03
– −0.17 (−2.13; 1.80) −2.90 (−4.73; −1.06)
– −0.53 (−2.25; 1.20) −2.80 (−4.55; −1.04) 0.014
0.05
– −2.59 (−4.23; −0.95) −2.59 (−4.23; −0.95)
– −1.54 (−3.06; −0.03) −1.98 (−3.33; −0.62) 0.015
0.05
– −1.42 (−3.25; 0.40) −2.47 (−3.99; −0.55)
– −1.04 (−2.67; 0.59) −1.44 (−3.00; 0.12)
R2: change in the percentage of the variance of the dependent variable explained by the predictor before and after excluding the effect of the control variables. The control variables for regression analysis are shown in Table 2. a Linear trend. b Heterogeneity.
= −4.62; p = 0.014). There was a linear trend in which the depression score is reduced when the physical activity levels increase (p = 0.033) in the adjusted analysis. The individuals from the active group presented approximately a three point lower score in depression in comparison to the inactive group (β = −2.80). For the state anxiety variable, even controlling for confounding variables, the physical activity variable remained associated. The higher the physical activity level, the lower the anxiety state scores (p b 0.004). Nevertheless, the trait anxiety did not remain associated in the adjusted analysis (p = 0.066). 4. Discussion The present study aimed to investigate the association among leisure-time and commuting physical activity levels and several health outcomes (quality of life, medication side effects, depression and state and trait anxiety) in PWE. These people commonly present worse health habits when compared with the general population [36], showing high smoking prevalence [36] and reduced levels of physical activity [14,15] and fitness [37,13]. These life conditions for PWE may be associated with a higher prevalence of psychiatric morbidities such as depression and anxiety [3,21], which lead to a low quality of life. The main finding of the study was that the improvement in health conditions of individuals with epilepsy was associated with physical activity. Even after the adjusted analysis, and controlling for confounding variables (such as sex, age, number of seizures, seizure type, duration of epilepsy, sleep quality, stress levels, among others), physical activity was still associated with improved scores in all analyzed health outcomes (except trait anxiety). 4.1. Quality of life Regarding quality of life, the study shows a linear trend between the groups. The higher the level of physical activity, the higher the quality of life, which increased by 10% for physically active individuals (β = 10.05). A former study by McAuley et al. [22] corroborate with our finding. The authors carried out a randomized clinical trial for 12 weeks with adults with epilepsy divided into two groups: an intervention group (performing physical exercise) and a controlled group (without
exercise). The total score for quality of life improved in the intervention group but it was not altered in the control group. 4.2. Depression and anxiety Results from the present study show associations between physical activity levels and anxiety state and depression, not only in the crude analysis but also in the adjusted one. The trait anxiety did not remain associated after regression analysis. These findings agree with studies previously carried out in PWE [20,21]. De Lima et al. [21] compared PWE with individuals without the disease and found higher scores for depression and anxiety among PWE. Although physical activity levels were not different between the groups, leisure-time physical inactivity may predict 31% of depression levels and 26% of anxiety levels in the epileptic group. Han et al. [20] compared physically active epileptic individuals with physically inactive ones and found an association in the crude analysis showing that active individuals presented reduced depression levels, whereas the adjusted analysis showed that physical inactivity alone may predict anxiety. There are several mechanisms supporting the positive changes promoted by physical activity on mental health. These mechanisms are divided into: psychological (distraction, social interaction, self-efficacy, expectations for changes and pleasure in the activities), physiological (thermogenic and brain blood flow), and neurophysiological (monoamines, cerebral lateralization and endorphins) [38]. In this regard, physical activity may have increased endorphin levels and this increase is associated with reduction in anxiety and depression, vigor, wellbeing and increased levels of euphoria[39]. Another explanation for this phenomenon is the monoamine hypothesis which suggests that physical activity level increases the serotonin and norepinephrine levels which are decreased in depressed people, indicating an improvement in humor profile [40,41]. 4.3. Side effects of medication Regarding the side effects of antiepileptic medication, studies which evaluated the effect of physical activity were not found. The results presented in this study indicate that there was a five point reduction in the total score of side effects for active group individuals. In a recent study, Noble et al. [42] questioned the priorities of epilepsy treatment using a
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questionnaire directed to patients themselves and to the caregivers. From the 10 mentioned priorities, improvement in quality of life and side effect reduction from medications are among the top five for both (patients and caregivers). Improvement in quality of life and reduction of medication side effects are in the first and second positions, respectively, according to the caregivers. Therefore, the results are very relevant, considering a positive association between physical activity practice and the abovementioned priorities. The results help to fill a knowledge gap, because Saadi et al. [43] showed that there is a need for further studies evaluating the quality of life of PWE in low- and middle-income countries. The findings from the present study showed physical activity as a nonpharmacological alternative to improve health and life conditions of individuals with epilepsy. As a result, quality of life is improved, medication side effects are reduced, and anxiety and depression levels are reduced. In addition to all the benefits mentioned above, studies on rats [44] and humans [45,23] have shown that physical exercise may also contribute to control epileptic seizures. This is the first study in Brazil to analyze a linear trend for physical activity levels regarding health outcomes in PWE. From a methodological point of view, the standardization for data collection as well as the careful choice of statistical tests should be highlighted to achieve the aims of the research. 4.4. Limitations Although there is a biological plausibility of an association between the physical activity and health variables [17,22], this cross-sectional study is not an ideal design to verify the cause and effect relationship. Another limitation was regarding the instruments used to assess depression, quality of sleep and stress levels, which were validated only for adults and the elderly. However, validated instruments for adolescents which aim at measuring these variables are unknown. As a result, more studies are needed, mainly randomized clinical trials, to establish a more precise relationship between cause and effect. 5. Conclusion Physical activities, such as, leisure-time and commuting, are associated with health outcomes. The higher the physical activity level, the higher the scores for quality of life in addition to reducing depression, anxiety state and medication side effects scores. To sum up, physical activity regarding the analyzed domains may be a nonpharmacological treatment to improve health and life conditions of PWE. Funding sources The research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector. Conflict of interest The authors declare no conflicts of interest. Acknowledgments The authors thank the Faculty of Medicine of the Federal University of Pelotas for the authorization for the data collection. We would like to thank the subjects who volunteered their time to participate in this study. References [1] Thurman DJ, Beghi E, Begley CE, Berg AT, Buchhalter JR, Ding D, et al. Standards for epidemiologic studies and surveillance of epilepsy. Epilepsia 2011;52:2–26.
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