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Keywords:

  • Migraine;
  • Diabetes;
  • Comorbidities

Summary

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

Purpose: The negative impact of epilepsy is disproportionate to its prevalence. Our objectives were to determine if health-related behaviors (HRBs) and health status differ between patients with epilepsy, migraine, or diabetes.

Methods: The 2001–2005 Canadian Community Health Survey (N = 400,055) was used to explore health status and HRBs in patients with epilepsy, migraine, and diabetes and in the general population. Weighted estimates of association were produced as proportions with 95% confidence intervals (CIs). Logistic regression was used to explore the association between demographic variables and HRBs in epilepsy.

Results: The prevalence of active epilepsy, migraine, and diabetes was 0.6%, 8.4%, and 3.8%, respectively. Those with epilepsy and diabetes were more likely than migraineurs to perceive their health as poor and to be physically inactive. Obesity and comorbidities were more likely in all chronic conditions studied compared to the general population. Those with epilepsy or migraine were significantly more likely to smoke compared to the general population or to those with diabetes. Those with epilepsy were more likely to ever have consumed more than 12 alcoholic drinks per week. Health monitoring did not differ between groups. In the logistic regression analysis, epilepsy was associated with physical inactivity and lower alcohol consumption in the past 12 months compared to the general population.

Discussion: Our study demonstrated that those with epilepsy have a poorer pattern of HRBs and poorer health status compared to the general population. Screening for and managing comorbidities, and promoting exemplary HRBs, should improve overall health and quality-of-life in those with epilepsy.

Epilepsy is one of the most common neurologic disorders, with a worldwide prevalence of ∼1% (Wiebe et al., 1999; Tellez-Zenteno et al., 2004). In Canada, 16,000 people receive a diagnosis of epilepsy every year, and at any given time, 190,000 people have active epilepsy requiring medical attention (Tellez-Zenteno et al., 2004). Importantly, the negative impact of epilepsy is disproportionate to its prevalence (Murray et al., 1994). People with epilepsy have lower quality-of-life, family function, and social support as compared to other chronically ill individuals (Wiebe et al., 1999; Kobau et al., 2008). Those with epilepsy tend to have more disability days and limitations in activities, and lower annual income than all other groups, including the chronically ill (Wiebe et al., 1999; Kobau et al., 2008). Furthermore, epilepsy is more likely to be associated with medical and psychiatric comorbidities compared to the general population (Tellez-Zenteno et al., 2005, 2007). Modifiable factors contributing to the negative impact of epilepsy present opportunities for beneficial interventions. It is, therefore, of value to investigate any potential underlying contributors to the impact of this condition, such as health status and health-related behaviors (HRBs).

Health status refers to “the state of health of a person or population assessed with reference to morbidity, impairments, anthropological measurements, mortality, and indicators of functional status and quality of life” (ECHP, 1999). HRBs, on the other hand, refer to actions of an individual, group, or organization that relate to, and have impact on, disease prevention, health maintenance, health improvement, or the restoration of health (modified from (Gochman, 1982)). In the context of an individual, examples of negative behaviors include smoking and excessive alcohol consumption. Involvement in physical activity and obtaining appropriate screening tests are examples of positive behaviors. Appreciating the patterns of health status and HRBs in people with epilepsy, and understanding how they differ from people without epilepsy, may allow caregivers to target interventions to minimize the negative impact of epilepsy.

There are few population-based studies examining HRBs in individuals with epilepsy in a comprehensive fashion (Kobau et al., 2004; Strine et al., 2005; Kobau et al., 2007; Elliott et al., 2008; Ferguson et al., 2008; Kobau et al., 2008). However, there are no published population-based studies comparing HRBs in people with epilepsy to people with other chronic conditions such as migraine or diabetes. For this reason, it is unclear whether the negative health impact of epilepsy has specific features or merely represents nonspecific aspects of chronic diseases. This distinction is critical to the development of ameliorative strategies, which may need to be epilepsy-specific.

Our primary objectives were to determine if health status and HRBs in epilepsy differ from those of the general population, and to determine if these variables are similar to those of people with other chronic conditions, namely, migraine and diabetes. We chose these two chronic conditions because, like epilepsy, they affect all age groups and usually require chronic therapy. In addition, migraine is an episodic condition, as is epilepsy. Our secondary objective was to determine if patterns of HRBs in people with epilepsy are associated with any sociodemographic variables.

We hypothesized that people with epilepsy would have poorer health status and lower levels of health-related behaviors compared to the general population, but similar to those with other chronic conditions (i.e., migraine and diabetes).

Methods

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

Subjects

The Canadian Community Health Survey (CCHS) is a national population-based survey of the health status and health behaviors of Canadian adolescents and adults. CCHS cycles 1.1, 2.1, and 3.1 were administered between 2000 and 2005, each over a 2-year collection cycle. CCHS 1.1 included subjects ages 12 years and older, whereas cycles 2.1 and 3.1 included subjects 15 years and older. The CCHS uses a multistage stratified cluster design combined with random sampling methods to select a representative sample of the Canadian population, excluding people living on Indian Reserves or Crown lands, clientele of institutions, Canadian Armed Forces, and people living in some remote regions. For a comprehensive review of the CCHS, please refer to a separate publication (Beland, 2002). Ethics approval was obtained for this study.

Survey design

The survey responders were interviewed whenever possible in person at their homes by trained or experienced interviewers using computer-assisted interview methods. Both single items and multiple-item questions are included in the CCHS. Telephone interviews were permitted only when travel was prohibitive or the respondent refused to conduct the interview in person. Using validated, targeted instruments, the survey explores a large number of health-related areas and behaviors, as well as family function, social function, and sociodemographic variables (CCHS, 2009). The survey was developed in consultation with key users of health information, and its design and conduct have been validated by Statistics Canada (CCHS, 2009). The response rate for cycles 1.1, 2.1, and 3.1 was 85%, and pooled data from these three surveys provided a sample size of 400,055 individuals.

Diagnosis of chronic conditions

The CCHS respondents were read a list of chronic medical conditions and asked whether they had been diagnosed with one of these conditions by a health professional. The exact wording of the item was: “Now, I’d like to ask you about certain chronic health conditions which you may have. We are interested in long-term conditions which are expected to last or have already lasted six months or more and that have been diagnosed by a health professional.” This was followed by: “Do you have epilepsy?” A list of chronic conditions followed, and subjects were periodically reminded of the requirements for a diagnosis by a health professional.

Variables studied

The variables we examined were: (1) demographic variables (age, gender, marital status, income, and educational attainment); (2) health status variables including self-reported health status, body mass index (BMI) (for those older than 18), and comorbid health conditions; and (3) HRB variables such as participation in screening tests [PAP smears, prostate-specific antigen (PSA) testing, and mammography], physical activity level, consumption of fruits and vegetables, cigarette smoking and alcohol consumption. Physical activity was determined using the physical activity index, which represents the average daily energy expended on leisure time physical activity, expressed in kilocalories (kcal) per kilogram (kg) body weight per day (d). Physical inactivity was defined as an average energy expenditure of <1.5 kcal/kg/day.

Statistical analysis

The CCHS uses a complex sampling strategy that involves both stratification and clustering. Weighted estimates were produced as proportions (representing prevalence) with 95% confidence intervals (CIs). Estimates of association (odds ratio, or OR) between epilepsy and selected HRBs were generated using logistic regression analysis adjusting for age, gender, education, and personal income. We ensured that there were no clinically significant differences between each CCHS survey cycle before combining the results of the three consecutive surveys.

Results

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

Baseline demographics

A total of 400,055 individuals were successfully interviewed for the CCHS cycles included in the current study. There were 2,555 individuals with epilepsy, 39,797 with migraine, and 22,432 with diabetes. Active epilepsy had a weighted prevalence of 0.6%, migraine 8.4%, and diabetes 3.8%. Individuals with epilepsy and migraine were slightly younger than those with diabetes. Among those with epilepsy, there were equal numbers of males and females. People with epilepsy were less likely to be in a personal relationship. Those with epilepsy, migraine, or diabetes were less likely to attain university level education and were more likely to obtain trade qualifications compared to the general population, with epilepsy showing the lowest proportion of postsecondary attainment and lowest personal income (Table 1).

Table 1.   Sociodemographic variables
 General populationEpilepsyMigrainesDiabetes
400,0552,55539,79722,432
  1. aRepresents proportion in percentage (%) with 95% confidence interval (CI).

Demographic information
 Age, years
  Mean ± SD45.4 ± 20.243 ± 17.741.1 ± 16.862.9 ± 14.7
  Median44434065
Sexa
 Female50.7 (50.5–51.0)50.9 (47.9–53.8)71.4 (70.7–72.1)46.9 (45.9–48.0)
Marital statusa
 Married/common law58.4 (58.2–58.6)48.0 (45.0–50.9)59.7 (58.9–60.4)67.6 (66.7–68.6)
 Widowed/separated/divorced11.7 (11.6–11.8)13.6 (11.8–15.4)12.1 (11.6–12.5)22.6 (21.8–23.4)
 Single29.9 (29.7–30.1)38.4 (35.6–41.2)28.2 (27.6–28.9) 9.8 (9.2–10.3)
Education, highest level attaineda
 No postsecondary degree, certificate, or diploma14.7 (14.5–15.0)18.8 (15.2–22.5)15.3 (14.6–16.0)12.1 (11.9–13.9)
 Trades certificate or college diploma48.7 (48.3–49.0)54.3 (49.5–59.0)51.8 (50.7–52.8)56.9 (55.3–58.5)
 University36.6 (36.3–36.9)26.9 (22.6–31.2)32.9 (31.9–33.9)30.2 (28.6–31.8)
Income (in Canadian dollars)
 Best estimate of personal income in the past 12 months (mean, SD, median)32,857.5522,807.7028,353.7727,706.51
34,491.4625,574.3728,466.0028,564.34
25,000.0015,000.0022,000.0020,000.00

Health status

More than 30% (33.4%, 95% CI 30.5–36.3) of those with epilepsy rated their general health as “fair/poor” compared to 11.5% (11.4–11.6) of the general population and 19.3% (18.8–19.9) of migraineurs. People with diabetes were more likely than all other groups to rate their health as “fair/poor” (40.8% with 95% CI 39.7–41.8), although only slightly worse than those with epilepsy. Almost 20% (19.1% with 95% CI 16.6–21.6) of people with epilepsy had a BMI 30, compared to 15.4% (15.3–15.6) of the general population and 18.0% (17.4–18.6) of migraineurs, whereas people with diabetes had the highest prevalence of obesity (37.1%, 95% CI 36.0–38.3) (Table 2 and Fig. 1).

Table 2.   Health status
 General populationEpilepsyMigrainesDiabetes
400,0552,55539,79722,432
  1. All represent proportions (%) with 95% confidence intervals.

General health
 Excellent/Very Good/Good88.5 (88.4–88.6)66.6 (63.7–69.5)80.7 (80.1–81.2)59.2 (58.2–60.3)
 Fair/Poor11.5 (11.4–11.6)33.4 (30.5–36.3)19.3 (18.8–19.9)40.8 (39.7–41.8)
Body Mass Index
 Obese, BMI ≥3015.4 (15.3–15.6)19.1 (16.6–21.6)18.0 (17.4–18.6)37.1 (36.0–38.3)
 Not obese84.6 (84.4–84.7)80.9 (78.4–83.4)82.0 (81.4–82.6)62.9 (61.7–64.0)
Comorbidities
 Thyroid condition5.3 (5.2–5.4)9.1 (7.4–10.9)7.6 (7.2–8.0)10.8 (10.2–11.4)
 Arthritis16.2 (16.0–16.3)23.9 (21.5–26.4)22.7 (22.1–23.3)37.8 (36.8–38.8)
 Migraines10.1 (9.6–10.3)19.0 (16.8–21.3)8.4 (7.8–9.0)
 Diabetes4.5 (4.5–4.6)6.1 (4.5–7.6)3.8 (3.5–4.1)
 Epilepsy0.6 (0.6–0.6)1.1 (0.9–1.2)0.8 (0.6–1.0)
 Stroke1.1 (1.0–1.1)5.6 (4.5–6.8)1.5 (1.3–1.7)5.0 (4.6–5.5)
 Crohn’s disease/colitis2.8 (2.7–2.8)5.5 (4.2–6.7)6.1 (5.7–6.4)4.4 (4.0–4.8)
 Asthma8.4 (8.2–8.5)12.3 (10.5–14.2)14.8 (14.3–15.4)10.1 (9.5–10.8)
image

Figure 1.   Proportion of respondents with epilepsy, migraine, or diabetes by health status and health-related behavior variables.

Download figure to PowerPoint

Comorbidities

Those with epilepsy, migraine, or diabetes were more likely to have a somatic comorbidity compared to the general population. Migraine was more common in those with epilepsy than in the general population, and epilepsy was more common in migraineurs than in the general population. Stroke was more common in those with epilepsy (5.6%, 95% CI 4.5–6.8) and diabetes (5.0%, 95% CI 4.6–5.5) than the other two groups. Just over 12% (10.5–14.2) of people with epilepsy had asthma compared to 14.8% (14.3–15.4) of migraineurs, 10.1% (9.5–10.8) of people with diabetes, and 8.4% (8.2–8.5) of the general population. Prevalence of arthritis was highest in the group with diabetes; however, arthritis was also significantly more common in those with epilepsy 23.9% (21.5–26.4) or migraine 22.7% (22.1–23.3) than in the general population 16.2% (16.0–16.3). Colitis and thyroid conditions were more common in those with epilepsy, migraine, or diabetes compared to the general population (Table 2).

Physical activity

Approximately 60% of those with epilepsy or diabetes were physically inactive compared to approximately 50% of the general population and 50% of those with migraine. In the logistic regression analysis adjusting for age, gender, education, and income, those with epilepsy were 1.4 times more likely (OR 1.4, 95% CI 1.1–1.7) to be physically inactive compared to the general population (Table 3 and Fig. 1).

Table 3.   Negative health-related behaviors
 General populationEpilepsyMigrainesDiabetes
400,0552,55539,79722,432
  1. All represent proportions (%) with 95% confidence intervals.

Physical Activity Index
 Inactive49.7 (49.5–50.0)58.3 (55.1–61.4)51.6 (50.9–52.4)62.1 (61.0–63.1)
 Active/moderate50.3 (50.0–50.5)41.7 (38.6–44.9)48.4 (47.6–49.1)37.9 (36.9–39.0)
Smoking
 Current smoker23.6 (23.3–23.8)28.1 (25.6–30.6)28.4 (27.8–29.1)17.7 (16.9–18.4)
Alcohol
 Had a drink in the past 12 months? Yes77.3 (77.1–77.5)57.6 (54.6–60.5)76.8 (76.1–77.4)62.2 (61.2–63.3)
 Frequency of 5 or more drinks in past 12 months
   Never53.7 (53.5–54.0)56.4 (52.4–60.3)58.2 (57.3–59.0)71.1 (69.9–72.3)
   Less than once a month24.9 (24.7–25.1)25.5 (22.0–29.0)25.8 (25.1–26.6)17.0 (16.0–18.0)
   Once a month7.2 (7.1–7.4)5.8 (3.4–8.3)6.1 (5.7–6.5)3.6 (3.1–4.1)
   2 to 3 times a month6.1 (6.0–6.3)4.3 (2.8–5.9)4.5 (4.1–4.8)3.2 (2.7–3.6)
   Once a week or more than once a week8.0 (7.8–8.1)7.9 (5.9–10.0)5.4 (5.0–5.8)5.2 (4.6–5.7)
  Did you ever regularly drink more than 12 drinks a week? Yes18.2 (17.7–18.7)25.0 (19.5–30.4)17.9 (16.5–19.4)21.7 (20.2–23.2)

Fruit and vegetable consumption and screening tests

The prevalences of fruit and vegetable consumption, screening for pap smears, mammograms, and PSA testing were not significantly different between the groups (Table 4).

Table 4.   Positive health-related behaviors
 General populationEpilepsyMigrainesDiabetes
400,0552,55539,79722,432
  1. All represent proportions (%) with 95% confidence interval.

  2. PSA, prostate-specific antigen.

Daily fruit and vegetable consumption
 ≥5 servings per day40.2 (39.9–40.4)38.6 (35.3–41.9)40.4 (39.6–41.3)42.2 (41.0–43.4)
 <5 per day59.8 (59.6–60.1)61.4 (58.1–64.7)59.6 (58.7–60.4)57.8 (56.6–59.0)
PAP test
 Ever had a PAP test? Yes87.1 (86.8–87.3)84.4 (80.7–88.1)90.5 (89.8–91.1)86.0 (84.9–87.1)
When was the last time?
 <3 years ago81.1 (80.9–81.4)80.3 (77.1–83.5)84.2 (83.5–84.9)63.4 (61.9–64.8)
 >3 years ago18.9 (18.6–19.1)19.7 (16.5–22.9)15.8 (15.1–16.5)36.6 (35.2–38.1)
PSA test (males ≥40 years)
 Ever had a PSA test? Yes43.3 (42.7–44.0)44.2 (36.5–51.9)37.5 (34.9–40.1)59.0 (56.9–61.2)
  When was the last time?
   <2 years ago88.0 (87.4–88.6)82.7 (73.7–91.7)89.7 (87.2–92.2)88.9 (87.3–90.5)
   >2 years ago12.0 (11.4–12.6)17.3 (8.3–26.3)10.3 (7.8–12.8)11.1 (9.5–12.7)

Cigarette smoking and alcohol consumption

The proportion of smokers in the epilepsy group was 28.1% (25.6–30.6) and in migraineurs was 28.4% (27.8–29.1), compared to 23.6% (23.3–23.8) in the general population and 17.7% (16.9–18.4) in those with diabetes. Those with epilepsy or diabetes were less likely to have had a drink in the previous 12 months compared to the general population and those with migraines, although people with epilepsy were more likely to have ever regularly had more than 12 drinks per week. In the logistic regression adjusted for age, gender, education, and income, those with epilepsy had the same odds of being a current smoker (OR 1.2, 95% CI 0.9–1.5) as the general population, but were less likely to have had a drink in the past year (OR 0.5, 95% CI 0.4–0.6) (Table 3 and Fig. 1).

Discussion

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

We explored health status and HRBs in those with epilepsy compared to those with migraine or diabetes, and compared to the general population, using a large validated population-based survey in Canadians. Overall, those with epilepsy were more likely to have poorer health status and a poorer pattern of HRBs compared to the general population, except for screening procedures (mammography, Pap smears, and PSA testing) and fruit and vegetable consumption, which were not significantly different between groups. Compared to people with migraine or diabetes, certain measures of health status and HRBs were poorer in those with epilepsy.

Prevalence of chronic conditions

In this study, the prevalence of active epilepsy was 0.6%, similar to two previous Canadian studies (Wiebe et al., 1999; Tellez-Zenteno et al., 2004) and comparable to, although slightly smaller than, estimates from large population-based studies in the United States, which ranged from 0.7–1.0% (CDC, 2001; Kobau et al., 2004, 2007, 2008; Elliott et al., 2008; Ferguson et al., 2008). The slight variability may be attributable to differences in case definitions and ascertainment methods. The prevalence of migraine was 8.4% and diabetes 3.8%.

Health status

Having epilepsy was significantly associated with poorer self-perceived health status compared to the general population, consistent with existing literature. In several population-based samples from the United States, patients with epilepsy were more than twice as likely to report “fair” or “poor” health status, as well as more overall dissatisfaction with life, than those without epilepsy (CDC, 2001; Kobau et al., 2004, 2007; Elliott et al., 2008; Kobau et al., 2008). Poorer self-perceived health status among those with epilepsy may be due to a higher prevalence of comorbidities. When comparing chronic disease groups, we found that although people with diabetes are most likely to rate their health as “fair” or “poor,” those with epilepsy are much more likely to do so than migraineurs; further study is warranted to investigate contributing factors.

Comorbidities

Having epilepsy was significantly associated with a higher prevalence of most comorbidities examined compared to the general population, consistent with prior studies (Tellez-Zenteno et al., 2005; Elliott et al., 2008; Kobau et al., 2008). Not only is there a high prevalence of chronic comorbid conditions, but the incidence of new health problems is also higher (van den Broek & Beghi, 2004). In addition, we, and others, have previously shown a high prevalence of psychiatric comorbidities in patients with epilepsy (Tellez-Zenteno et al., 2005; Kobau et al., 2006; Tellez-Zenteno et al., 2007). Physicians should regularly screen for physical and psychological comorbidities in patients with epilepsy to improve prevention and management.

Few studies have compared somatic comorbid conditions in people with epilepsy to people with other chronic conditions. In a cross-sectional study from general practice that examined comorbidities in certain conditions including migraine and epilepsy, Nuyen et al. (2006) found that the comorbidities most strongly associated with epilepsy were stroke, other neurologic disorders, schizophrenia/other psychotic disorders, and congenital abnormalities. Our population-based study showed that stroke is more common in people with epilepsy and diabetes than in migraineurs, not a surprising finding given that stroke is the leading cause of symptomatic epilepsy in adults and that diabetes is a risk factor for stroke (Hauser et al., 1993). Colitis, arthritis, and thyroid conditions were more common in all groups compared to the general population; we do not have a clear explanation for this difference. In contrast to the study by Nuyen et al. (2006), we found that migraine was more common in those with epilepsy and epilepsy more common in migraineurs than in the general population. This is consistent with a growing body of literature focusing on the comorbid nature and common pathophysiologic mechanisms of epilepsy and migraine, a review of which is beyond the scope of this paper (Ludvigsson et al., 2006; De Simone et al., 2007; Rogawski, 2008). Prevalence studies such as ours can highlight disease associations but cannot determine causality.

Obesity

The prevalence of obesity was higher in those with epilepsy than in the general population, consistent with several population-based and small group studies in the United States (Steinhoff et al., 1996; Kobau et al., 2004, 2007, 2008), but contrary to others that found no significant difference (Strine et al., 2005; Nuyen et al., 2006; Elliott et al., 2008; Ferguson et al., 2008). People with epilepsy are less physically active than those without epilepsy, which may be the largest contributing factor to higher prevalence of obesity. Anticonvulsant medications can stimulate appetite and cause sedation and lethargy, thereby contributing to decreased activity and weight gain (Ben-Menachem, 2007). Interestingly, a recent study concluded that the prevalence of obesity is higher even in newly diagnosed, untreated children with epilepsy compared to children without epilepsy (Daniels et al., 2009). There is also a higher prevalence of psychiatric comorbidities in people with epilepsy, which may lead to unhealthy coping behaviors as well as psychotropic drug-related weight gain (Linde et al., 2004).

Health-related behaviors

Physical activity

Having epilepsy was significantly associated with a lower prevalence of physical activity compared to the general population, confirming previous studies (Steinhoff et al., 1996; Kobau et al., 2004; Strine et al., 2005; Kobau et al., 2007; Elliott et al., 2008; Ferguson et al., 2008; Kobau et al., 2008). The difference remained even after adjusting for age, gender, education, and income, suggesting that the difference was not influenced by those sociodemographic variables. People with epilepsy were found to be less active than those with migraine but similarly inactive compared to people with diabetes. People with epilepsy participate less in sports, have poorer levels of fitness, and are more obese than those without epilepsy, despite positive attitudes toward physical activity similar to that of controls, and despite a general feeling of good health (Steinhoff et al., 1996; Jalava & Sillanpaa, 1997). The stigma associated with epilepsy may limit participation in activity and some people with epilepsy continue to be discouraged from exercise participation due to concerns of injury (Arida et al., 2003). Comorbidities such as heart disease, arthritis, and depression may also limit participation in exercise. Epilepsy in some individuals is secondary to stroke or trauma, conditions that, by themselves, can result in physical or cognitive limitations to participation. Physical activity has also been found to reduce seizure frequency and level of subjective health complaints (Eriksen et al., 1994). Clinician encouragement of physical activity is, therefore, likely to improve a number of health aspects for people with epilepsy.

Smoking

In our study, people with epilepsy had a higher prevalence of smoking compared to the general population, although this relationship did not persist after adjusting for age, gender, education, and income. Small studies have reported no difference in smoking prevalence (Jalava & Sillanpaa, 1997; Strine et al., 2005), whereas several large population-based studies from the United States have found a higher prevalence of smoking in people with epilepsy. (Kobau et al., 2004, 2007; Elliott et al., 2008; Ferguson et al., 2008; Kobau et al., 2008). Given the nature of the studies mentioned, including ours, we are unable to rule out confounding factors such as comorbid depression as a predictor of smoking, but we were able to adjust for education and income.

The proportion of smokers in the epilepsy group was similar to migraineurs. People with migraine and people with epilepsy a have higher prevalence of psychiatric comorbidity than the general population (Tellez-Zenteno et al., 2007) and people with psychiatric illness have poorer coping mechanisms, such as smoking (Murphy et al., 2003; Linde et al., 2004). The proportion of smokers in the epilepsy group was higher than those with diabetes. The differences among the groups may speak to the success of physician and community education programs about stroke prevention and risk factor reduction in diabetes. It has been shown that physician advice can improve smoking cessation (Lemmens et al., 2008). Physicians who care for patients with epilepsy should take the opportunity to discuss smoking cessation with their patients.

Alcohol consumption

Use of alcohol has been variously reported in the literature as being higher, no different, or lower in the epilepsy group (Jalava & Sillanpaa, 1997; Hillbom et al., 2003; Kobau et al., 2004; Strine et al., 2005; Elliott et al., 2008; Ferguson et al., 2008; Kobau et al., 2008). Our study found that people with epilepsy had lower levels of alcohol consumption in the past year compared to the general population. People with diabetes also reported drinking less than the general population. Patients with epilepsy may be heeding routine physician advice regarding the relationships between alcohol and seizures and between alcohol and antiepileptic medications. People with diabetes may also be responding to education regarding stroke-risk reduction. If this is the case, it points to the potential benefit of other education programs around exercise, obesity, and smoking. There is still opportunity for further education, as the prevalence of alcohol use remains significant. We found that 5% of people with epilepsy drink at least five drinks per day, whereas current guidelines for “low risk” drinking are fewer than 14 drinks per week for men and less than 9 per week for women (CAMH 2009).

Positive health behaviors

The prevalences of fruit and vegetable consumption and of accessing screening health tests in our study were similar for those with and without epilepsy. Few studies have examined preventive health measures in those with epilepsy and the results have been mixed. The proportion of those going for routine health checkups, receiving the influenza vaccination, having a Pap smear, screening for HIV and prostate cancer, and consuming sufficient fruits and vegetables were similar among those with and without epilepsy (Kobau et al., 2004; Elliott et al., 2008; Kobau et al., 2008). Ferguson et al. (2008) reported that fewer people with epilepsy had seen a dentist in the past year compared with the general population, whereas Kobau et al. (2004) and Elliott et al. (2008) found no difference. Although Kobau et al. (2004) found that fewer patients with epilepsy compared to the general population had received a mammogram, Elliott et al. (2008) found no difference. In the 2006 Ohio BRFSS, prevalence of sigmoidoscopy/colonoscopy was significantly higher in those with a history of epilepsy compared to the general population (Elliott et al., 2008); however, Kobau et al. (2004) found no difference. Our study lends further credence to the similarity between people with epilepsy and the general population with respect to positive health behaviors.

Study limitations

Our study had several strengths, including a population-based ascertainment and a very large sample size. However, our study was subject to several limitations. First, self-reporting of epilepsy is subject to potential bias. The survey respondent is open to recall and response biases. Respondents were asked specifically about conditions diagnosed by a health professional, but the reported cases of epilepsy were not verified by a physician. Prevalence might be overestimated by people reporting nonepileptic seizures or seizures related to alcohol abuse; however, the prevalence of nonepileptic seizures is low and, given the large sample size, unlikely to have significantly skewed the results. Prevalence might be underestimated due to misdiagnosis of epilepsy and due to people’s reluctance to disclose their condition. It has been shown that people are less likely to disclose sensitive information in interviewer-administered surveys than in self-administered surveys (Link et al., 2006) and that 16–23% of people with epilepsy may not disclose their disorder at all (Dalrymple & Appleby, 2000). However, although both epilepsy and HRBs may not be accurately measured, as long as misclassification of one does not depend on the other, the direction of bias will be toward the null. Therefore, the positive results are not threatened by this type of bias; in fact, they are probably more extreme than they appear (Kleinbaum et al., 1982). Second, it is possible that there were unobserved factors affecting HRBs, such as comorbid psychopathology, for which we did not control. Third, the CCHS survey excludes people living on Indian Reserves or Crown lands, clientele of institutions, Canadian Armed Forces, some remote regions and households without a landline. Therefore, findings are not generalizable to these groups. Fourth, the study design was cross-sectional so no causal association among variables can be inferred. Fifth, although our study improved on similar works by including people younger than 18 years of age, the CCHS is limited to those older than 12 years for cycle 1.1 and older than 15 years for cycles 2.1 and 3.1. The pediatric population is not widely represented. Further studies in this particular population are warranted.

Conclusions

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

This is, to our knowledge, the first large population-based study comparing both HRBs and health status in those with epilepsy to those with other chronic conditions (migraine and diabetes). Our study demonstrates that, overall, those with epilepsy have poorer health status and a poorer pattern of HRBs compared to the general population. Compared to people with other chronic conditions, certain measures of health status and HRBs are poorer in those with epilepsy.

Our findings extend evidence of the substantial negative impact of epilepsy on adults living in the community. Knowing the health behaviors of patients with epilepsy allows the clinician to target care and promote exemplary HRBs such as exercise participation. Physicians treating people with epilepsy must monitor for and treat comorbid conditions and their risk factors. In addition, there is a need to link patients with epilepsy to social services such as public transportation and employment services. A multidimensional approach to the care of patients with epilepsy should prevent avoidable illnesses and injuries, improve overall health, and as a result improve quality-of-life in those with epilepsy. The results presented here help to identify priorities for planning of multidisciplinary services and programs aimed at improving the health of people with epilepsy.

Acknowledgments

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

Dr. Nathalie Jetté holds new investigator salary awards from the Canadian Institutes of Health Research and the Alberta Heritage Foundation for Medical Research (Population Health Investigator). Dr. Scott Patten holds a Senior Scholar salary award from the Alberta Heritage Foundation for Medical Research. Amy Metcalfe holds a doctoral award in Genetics (Ethics, Law and Society) from the Canadian Institutes of Health Research and a studentship award from the Canadian Institutes of Health Research Strategic Training Program in Maternal Fetal Newborn Health. Dr. Samuel Wiebe is supported by the Alberta Heritage Foundation for Medical Research and holds the Kinsmen Chair of Pediatric Neurosciences.

These analyses were based on data collected by Statistics Canada. However, the results and interpretations presented in this paper do not represent the opinions of Statistics Canada.

We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

Disclosure

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References

None of the authors has any conflicts of interest to disclose

References

  1. Top of page
  2. Summary
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgments
  8. Disclosure
  9. References