Osteoprotective knowledge in a multiethnic epilepsypopulation.

Abstract: Antiepileptic drugs (AEDs) are known to cause bone loss. People with epilepsy have twice the fracture rate of nonepilepsy populations. Osteoprotective knowledge related to calcium and exercise has not been assessed in people with epilepsy. The Osteoporosis Knowledge Test (OKT), a validated,

24-item test, was administered to 94 epilepsy patients (28 males and 66 females) to measure knowledge of risk factors for osteoporosis and strategies for prevention related to calcium and exercise. The mean age of participants was 45 years with an average AED exposure of 20 years. Fifty participants were Caucasian and 44 were non-Caucasian. No significant differences related to age or gender for the OKT were found. One-way analysis of variance (ANOVA) of ethnicity showed that non-Caucasians had much lower calcium (F = 8.15, p = .005) and exercise (F = 7.71, p = .007) knowledge. The total mean OKT score was 11.71 (4.92), reflecting a correct response rate of 49%. In previous studies of nonepilepsy populations, the mean OKT score ranged from 7.83 to 21.8, with a correct response ranging from 32.9% to 90.8%. Independent t tests of the individual OKT questions revealed specific knowledge deficiencies in the areas of risk factors, exercise, and reasons for calcium supplementation for non-Caucasians. Results of this study reveal that people with epilepsy, who are at greater risk for metabolic bone loss, have lower knowledge scores for calcium and exercise than nonepilepsy populations of various ages and genders. Culturally relevant epilepsy materials and programs may improve knowledge and adoption of preventative behavior.

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An estimated 1.5 million people suffer a bone disease-related fracture annually in the United States (U.S. Department of Health and Human Services, 2004). Costs for the treatment of incident osteoporotic fractures were estimated to be $34 billion in 2004 (Vanness & Tosteson, 2005). Two large cohort studies found double the fracture incidence in people with epilepsy when compared to a nonepilepsy population (Gaitatzis, Carroll, Majeed, & Sander, 2004; Souverein et al., 2005).

Studies have demonstrated that bone loss can occur after as little as 2 years of antiepileptic drug (AED) exposure (Chung & Ahn, 1994). Pack and colleagues (2003) found that people with epilepsy who take enzyme-inducing AEDs are prone to significant loss of bone mass, based on current World Health Organization guidelines. Only 42% had normal bone density compared to the 84% expected in the normal population (Pack et al., 2003). Bone loss in epilepsy is often thought to be the result of vitamin D deficiency, secondary to use of enzyme-inducing AEDs (Pack, 2003). Results of studies of the effects on bone of antiepileptic drugs that are not enzyme inducing, such as valproic acid and lamotrigine, have been mixed (Pack et al., 2005; Sato et al., 2001; Sheth et al., 1995). In a previous investigation of bone health in people with epilepsy (African American = 74, Caucasian = 57, and Latino = 27) that was conducted in our clinic setting, African Americans had the worst T-scores on dual-energy X-ray absorptiometry (DEXA), followed by Caucasians and Latinos. In addition, T-scores and bone mineral density measurements suggest bone loss is similar across both age and gender (Elliott, Jacobson, & Haneef, 2007).

A survey by the Epilepsy Action organization (Epilepsy Action, 2003) found that 75% of members reported never being told that osteoporosis and osteomalacia were possible side effects of long-term (>5 years) use of AEDs. Those who were informed of bone health issues reported their epilepsy specialist as the primary information source (Epilepsy Action, 2003). In another study, more than 90% of patients reported wanting more information about epilepsy, and 75% reported they were not given enough information about AED side effects (Jain, Patterson, & Morrow, 1993). Furthermore, a study of practice patterns in neurologists found that few evaluate their patients for AED-induced bone loss (Valmadrid, Voorhees, Litt, & Schneyer, 2001).

Up to 95% of total bone development is completed by the age of 18 years (Schettler & Gustafson, 2004). Adequate calcium intake in adolescence can result in a 5% to 10% difference in peak bone mass, which may reduce the risk of hip fracture in old age by 50% (Council on Scientific Affairs, American Medical Association, 1997). Calcium intake among youth ages 9-18 years was found to be 1,180 mg/day for Caucasians, 896 mg/day for Hispanics (Novotny et al., 2003), and 697-882 mg/day for African Americans (Fulgoni et al., 2007). The Institute of Medicine, Food and Nutrition Board recommends 1,300 mg of calcium daily for adolescents ages 9-18 years, 1,000 mg for adults ages 19-50 years, and 1,200 mg for those older than 50 years of age (Greer, Krebs, & Committee on Nutrition, 2006).

Regular, weight-bearing physical activity increases muscle and bone strength, increases lean muscle, and decreases body fat (U.S. Department of Health and Human Services, 2000). Rates of leisure-time physical inactivity for adult males have been estimated as 18.4% for Caucasians, 27% for African Americans, and 32.5% for Hispanics. For women, inactivity rates are even higher: 21.6% for Caucasians, 33.9% for African Americans, and 39.6% for Hispanics (Centers for Disease Control and Prevention, 2005).

Forty percent of surveyed people with epilepsy reported no physical activity in the past month and 34% were obese (Kobau et al., 2004). A majority of people with epilepsy had no adverse effects from exercise, and up to 36% have reported that regular exercise contributed to better seizure control (Nakken, 1999). Although most people with epilepsy had little to no exercise, they believed exercise may improve their medical treatment (Arida et al., 2003).

Osteoporosis Knowledge

Osteoporosis knowledge scores are not significantly associated with calcium intake or minutes of weight-bearing exercise (Terrio & Auld, 2002). Overall, level of education seemed to be the best predictor of knowledge scores (Terrio & Auld). Race and culture are important factors for predicting differences in knowledge and behavior for numerous health issues, although these differences have been less emphasized in osteoporosis-related knowledge and preventive behaviors (Larkey, Day, Houtkooper, & Renger, 2003). Less than 10% of African American and Hispanic women took in adequate daily calcium, and only 13% took calcium supplements; they also perceived osteoporosis to be less of a threat than breast cancer, heart disease, diabetes, and Alzheimer disease (Geller & Derman, 2001).

In older men ([greater than or equal to] 65 years of age), 71% failed an osteoporosis knowledge test. Only one-third engaged in twice-weekly weight-bearing exercise, and a meager 1.4% reported getting 1,500 mg of calcium daily (Sedlak, Doheny, & Estok, 2000). This is of concern when the rate of fracture-related mortality, 1 year after a hip fracture, is double in men compared to women (Olszynski et al., 2004). Males on AEDs have been found to have a 1.8% annual loss of bone-mineral density, yielding a 2.5-fold increased prevalence of bone loss at the hip when compared to the healthy U.S. male population (Andress et al., 2002).

Studies of osteoporosis educational programs in various populations have shown significant increases in specific knowledge related to exercise and calcium intake (Chan, Kwong, Zang, & Wan, 2007; Sedlak, Doheny, Estok, & Zeller, 2005; Sedlak, Doheny, & Jones, 1998). Programs including content on (1) identification of osteoporosis risk factors, (2) identification of potential consequences of osteoporosis, and (3) strategies to prevent osteoporosis, including exercise and maintenance of daily calcium requirements, have been effective in increasing knowledge for groups of health professionals (Piaseu, Belza, & Mitchell, 2001; Ziccardi, Sedlak, & Doheny, 2004) and men (Tung & Lee, 2006).

Currently, osteoporosis knowledge has not been investigated in people with epilepsy. As part of a larger study, we found exercise knowledge related to osteoporosis to be a predictor of increased adoption of preventative behaviors such as dietary calcium intake and physical exercise (Elliott, Seals, & Jacobson, 2007). It would be beneficial for nurses and other health educators to understand similarities and differences in calcium and exercise knowledge among males and females, as well as various age groups, ethnicities, and education levels. The U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion (n.d.) recommends that epidemiology, demographics, behavior, culture, and attitude be considered when taking steps to improve the usability of health information. They also recommend that materials and messages reflect the age, social and cultural diversity, language, and literacy skills of the intended users. In the case of osteoprotective behaviors, such as diet and exercise, culturally adapted messages and materials have a greater impact (Kreuter et al., 2005). By looking at specific knowledge deficiencies by ethnicity, more effective patient education could be developed and provided to people with epilepsy who are at risk for accelerated bone loss due to use of AEDs. This potential for improvement is especially important in light of previous research that has found that non-Caucasians get less dietary calcium (Geller & Derman, 2001), take calcium supplements less frequently (Wei, Jackson, & Herbers, 2003), exercise less frequently (Geller & Derman), and are screened three times less for osteoporosis (Mudano et al., 2003) than Caucasians.

Methods

Ninety-four epilepsy clinic patients over the age of 18 years participated in the study. Participants were recruited from the department of neurology outpatient clinic at Temple University School of Medicine. Data collection took place during a 6-month period. Inclusion criteria included patients ages 18 years or older with a diagnosis of epilepsy. Exclusion criteria included patients with mental retardation, learning disability, Alzheimer disease, dementia, or schizophrenia. Of the 225 patients invited to participate in the survey, 83 patients were approached during their clinic visits and 142 patients (not scheduled for office visits in the near term) were mailed surveys; 98 were Caucasians (44%), 85 African Americans (38%), 34 Latino (15%), and 8 Asian or other (<1%). The response rate to our questionnaire was 42%. Of those approached during a clinic visit, 27 (33%) completed surveys, and of those who were mailed surveys, 67 (47%) completed and mailed them back. The Temple University Institutional Review Board approved this study, and written informed consent was obtained from each participant.

Instruments

Participants completed a questionnaire containing the Osteoporosis Knowledge Test (OKT) and a demographic form related to epilepsy and bone health. The OKT is a 24-item multiple-choice test designed by Kim, Horan, and Gendler (1991) to measure knowledge of risk factors for osteoporosis and strategies for prevention related to exercise and calcium (Redman, 2003). The OKT, as displayed in Table 1, has four sections of questions for the identification of risk factors, appropriate exercise patterns, foods high in calcium, and reasons for taking calcium supplements. There are two subscales for the OKT: exercise (questions 1-16) and calcium (questions 1-9 and 17-24). The OKT exercise subscale internal consistency coefficient using Cronbach's alpha was .69. The OKT calcium subscale internal consistency coefficient, using Cronbach's alpha, was .72. Validity of the OKT was evaluated by factor analysis and discriminant function analysis (Kim et al., 1991). The OKT has been validated in Persian (Baheiraei, Ritchie, Eisman, & Nguyen, 2005) and Chinese (Lee & Lai, 2006) populations in addition to male populations (Sedlak et al., 2000). With a possible range of scores from 0 to 24, higher scores indicate greater knowledge. Poor to moderate knowledge (mean scores = 15.1-17.8) on the OKT has been found among men and women in various age groups (Werner, 2005).

Each participant also completed a demographic questionnaire (Table 2). Information requested included age, gender, ethnicity, marital status, education, yearly income, working status, height, weight, smoking and alcohol use, bone fracture history, family history of osteoporosis, calcium and multivitamin use, age at time of epilepsy diagnosis, number and type of AEDs presently taken, seizure frequency, insurance status, prescription coverage, and driving status. Missing demographic items were gathered from the clinic chart when necessary. Participant confidentiality was maintained by the use of an assigned, study-specific identification number. A Spanish translation of the OKT, provided by the questionnaire developers, was used for patients whose primary language was Spanish. The informed consent form, Health Insurance Portability and Accountability Act (HIPAA) form, demographic questionnaire, and correspondence were also translated into Spanish and verified by two native speakers for accuracy.

Results

Demographics

This study examined an adult epilepsy population with a mean age of 45 years (SD = 12.9, range 19 to 78 years); 28 (30%) were male and 66 (70%) female. Males were underrepresented based on a demographic analysis of inpatient and outpatient contacts for 2002-2004, where 54% of patients being seen for seizures or epilepsy were male and 46% were female. Participants included both young and old people and those newly diagnosed with epilepsy. Age and yearly income were recoded into three groups for analysis, and number of years of education was recoded into two groups. Fifty participants were Caucasian, 32 were African American, and 12 were Latino. The average length of AED exposure was 20 years (SD = 13.9, range 1 to 50). Forty-one participants (44%) reported taking a calcium supplement. Demographic variables are summarized in Table 2.

Osteoporosis Knowledge

A one-way analysis of variance (ANOVA) of the subscales for the OKT was performed based on various demographic factors (Table 3). Ethnicity was recoded as Caucasian or non-Caucasian for this analysis. No significant differences related to age or gender for either exercise or calcium knowledge were found. One-way ANOVA of ethnicity found non-Caucasians had much lower knowledge for calcium (F = 8.15, p = .005) and exercise (F = 7.71, p = .007). Participants reporting more than 12 years of education had higher knowledge scores for calcium (F = 39.25, p = .000) and exercise (F = 17.09, p = .000). Participants reporting an income above $30,000 had higher levels of knowledge for calcium (F = 3.93, p = .024) and exercise (F = 3.46, p = .037).

Participants who were seizure-free for longer than 1 year also had higher knowledge related to calcium (F = 6.76, p = .002) and exercise (F = 3.59, p = .032) compared to those reporting seizures within the past year. Significant differences in calcium knowledge were noted for individuals previously diagnosed with bone loss (F = 4.98, p = .028). In addition, for those reporting a family history of osteoporosis, knowledge was higher for calcium (F = 5.58, p = .005) and exercise (F = 6.23, p = .003). Participants taking calcium supplements had higher knowledge for calcium (F = 5.35,p = .023) but not for exercise. No significant differences were found related to fracture history.

OKT Results in Previous Studies

Table 4 displays the results of previous studies using the OKT in various populations as a means of comparison. The descriptive statistics for the current study found mean (standard deviation) scores of 7.16 (3.39) for the OKT exercise subscale, 8 (3.68) for the OKT calcium subscale, and 11.71 (4.92) for the total score. The mean OKT total score corresponds to a correct response rate of 48.8%. The mean scores displayed in Table 4 are significantly lower than those for all but two of the previous studies in nonepilepsy participants (N = 790).

Bivariate Pearson Correlation Analysis

Pearson correlations were performed to determine the relationship between the osteoporosis knowledge subscales and various demographic and clinical factors. Ethnicity was negatively correlated with both exercise (r = -.28, p = .007) and calcium (r = -.29, p = .005) knowledge. Education was positively correlated with exercise (r = .40, p = .000) and calcium (r = .55, p = .000) knowledge. Yearly income was also positively correlated with exercise (r = .28, p = .017) and calcium (r = .28, p = .015) knowledge. A diagnosis of bone loss (r = .23, p = .028) and calcium supplement use (r = .23, p = .023) were also positively correlated with calcium knowledge.

Knowledge by Ethnicity

Although education and income were more strongly correlated with knowledge than was ethnicity, the following discussion focuses on ethnicity because the ultimate goal is to tailor clinic educational messages, and it is recommended that such customization efforts focus on cultural differences. Therefore, we chose to do analyses using two-tailed independent Student's t tests to review correct answers on the OKT in relation to ethnicity (coded as Caucasian and non-Caucasian; see Table 1). For all but two knowledge questions (numbers 10 and 20), fewer non-Caucasians answered correctly. More Caucasians (66%) than non-Caucasians (45%) answered question 1 correctly, namely, that eating a diet low in milk products is a risk factor for osteoporosis (t = 2.03, p = .046). For question 2, regarding whether a woman in menopause is at greater risk, 64% of Caucasians answered correctly versus only 17% of the non-Caucasians (t = 2.51, p = .014). More Caucasians (68%) than non-Caucasians (48%) correctly identified, on question 5, that having a grandmother or mother with osteoporosis is a risk factor (t = 2.01, p = .047).

For question 9, knowledge of exercise as a protective factor, 74% of Caucasians versus only 43% of non-Caucasians answered correctly (t = 3.17, p = .002). For question 11, only 14% of non-Caucasians versus 29% of Caucasians identified bicycling as a more protective form of exercise compared to yoga or housecleaning (t = 2.61, p = .011). For question 22, significantly more Caucasians (42%) versus non-Caucasians (11%) correctly identified 800 mg or more a day as the recommended amount of daily calcium (t = 3.49, p = .001). For question 24, more Caucasians (74%) identified the best reason for taking a calcium supplement ("If a person does not get enough calcium from the diet") compared to non-Caucasians (52%), based on the Student's t test (t = 2.22, p = .029).

Overall Knowledge Deficiencies

In the identification of risk factors, few participants in either group recognized that having "big bones" was protective (question 3) or that white women (question 6) and women who have who have had their ovaries removed (question 7) are at an increased risk for osteoporosis. Exercise knowledge, overall, was low in both groups. Deficiencies are apparent in identifying exercises that are weight bearing (questions 10-16), such as walking, bicycling, and aerobic dancing, as well as the appropriate length and intensity of exercise. Overall, participants performed fairly well in identifying foods high in calcium, with the exception of question 18, "Which of these is a good source of calcium: watermelon, corn, or canned sardines": less than 25% identified sardines as the correct answer. Also, few individuals were aware of the recommended daily amounts of calcium (> 800 mg) or how many glasses of milk an adult must drink to meet the recommended amount of calcium (two or more glasses daily).

Discussion

To our knowledge, this is the first study of people with epilepsy to focus on assessment of knowledge of calcium and exercise in relation to AED-induced osteoporosis. The medical literature during the past 20 years has established a strong link between several antiepileptic medications and metabolic bone loss (Pack, 2003); however, past studies have primarily emphasized determining, for various populations, which AEDs are worse for bone density. Prevention has focused on recommendations for DEXA screening and supplementation with calcium and vitamin D (Pack, Gidal, & Vazquez, 2004). Lifestyle recommendations, such as exercise and dietary calcium, often receive cursory mention. It is encouraging to see that the population in this study reported taking calcium supplements more frequently than in previous investigations, for example, that by Geller and Derman (2001).

The scores of participants in this study (mean OKT score = 11.71) were similar to the descriptive data from the OKT test designers (mean OKT score = 11.45; Table 4). People with epilepsy, however, had lower scores on the subscales (mean OKT calcium = 8.00 and mean OKT exercise = 7.16) than the scores reported by the test designers (mean OKT calcium = 11.74 and mean OKT exercise = 11.16). Because the validation study of the OKT was completed in 1991, one likely explanation is that significant educational gains have been made from public health messages during the past 16 years. Overall, however, compared to previous studies in various populations (N = 790; Table 4), people with epilepsy knew significantly less about osteoporosis. Participants did perform bettor than older Chinese men in one recent study (mean OKT calcium = 4.42 and mean OKT exercise = 5.73; Lee & Lai, 2006).

Results from the current investigation support a previous knowledge study of non-Caucasian women (not using the OKT) in which only one-third knew that postmenopausal status increased a woman's risk for osteoporosis. In addition, less than one-third knew that long-term steroid use, small body frame, lack of sunlight and vitamin D, oophorectomy, and amenorrhea were also risk factors. Most women believe incorrectly that being African American or Hispanic is protective for osteoporosis. Although African American and Latina women do have somewhat higher bone mass compared to Caucasian women, all groups have similar patterns of bone loss 5 years after menopause (Geller & Derman, 2001). In addition, the rate of hip fracture increases exponentially after age 70 in African American and Latina women compared to Caucasian women (Karagas, Lu-Yao, Barrett, Beach, & Baron, 1996).

Because osteoporosis knowledge has been positively correlated with prevention intention, age, and calcium intake (Chang, Chen, Chen, & Chung, 2003), much needs to be done to bridge the information gap between healthcare practitioners and their patients. As with other chronic health conditions such as diabetes or asthma, people with epilepsy need to receive ethnically relevant communication and educational materials from their healthcare practitioner. Such materials should be tailored to not only improve knowledge but also to enhance patients' confidence in their ability (self-efficacy) to perform the recommended behaviors.

The differences found for calcium knowledge, based on ethnicity, may possibly be attributable to lactose intolerance in African Americans and Hispanics, because dietary recommendations for calcium typically focus on dairy consumption (Jackson & Savaiano, 2001; Larkey et al., 2003). Approximately 75% of the world's adult populations have a genetically limited ability to digest lactose. In the United States, primary lactose intolerance is reported to occur in 15% of Caucasians, 53% of Mexican Americans, 100% of Native Americans, 80% of African Americans, and 90% of Asian Americans (Jarvis & Miller, 2002). There is evidence, however, that African American adolescents can adapt to a dairy-rich diet (Jarvis & Miller).

The problem of dietary calcium for those with lactose intolerance may also be approached by pointing out that there are other foods high in calcium, including vegetables, fish, beans, and nuts and seeds, that may be better dietary choices for those who cannot digest dairy products. People who decide not to consume dairy products because of cultural preference or lactose intolerance also need to rely more heavily on calcium-enriched foods and supplements to meet their daily requirements. Culturally relevant food diaries are needed for ethnically diverse populations. The OKT, although it has been used in non-Caucasian populations, may need to be adapted to assess more culturally relevant factors because dietary staples vary widely among African Americans, Latinos, and Asian Americans.

Because exercise also is an important osteoprotective behavior, concerns that affect people's willingness to exercise also should be addressed. In urban areas, people often report feeling it is unsafe to exercise in their neighborhood. They may, however, have access to the local YMCA, high school gym, or community center. To assist in the adoption of exercise behavior, patients must overcome the fear of seizures during physical exercise. The lack of understanding among many health professionals about epilepsy must also be addressed because unnecessary restriction of physical activity can have a profound effect on bone health, as well as on mortality, morbidity, and quality of life. Exercise participation recommendations should be reviewed with regard to seizure control, medications, proper diet, rest, and the close monitoring of AED levels. If these aspects are taken into account, then people with epilepsy can participate in most types of physical activity, including some contact sports (Howard, Radloff, & Sevier, 2004).

In people with epilepsy, age and gender appear to have little impact on knowledge related to osteoporosis, compared with such socioeconomic factors as minority status, years of education, and yearly income. This finding supports the medical literature for nonepilepsy populations (Werner, 2005). It was somewhat unexpected that men had OKT scores similar to those of women, because osteoporosis is often thought to be a "female" disease. However, this finding may be due to the much smaller number of males completing the survey. Education of people with epilepsy needs to address the fact that bone loss from AEDs affects both men and women and that the target learning needs for men may be different from those for women.

In a survey of young women, the respondents ranked what sources they would most likely use to learn about osteoporosis: 28% chose magazines, handouts, and brochures as their first choice, and 18% preferred a short 5-minute talk during an office medical visit (Kasper, Peterson, & Allegrante, 2001). Minority women, on the other hand, preferred talking with their healthcare practitioner over receiving printed materials (Geller & Derman, 2001). A review of osteoporosis coverage in women's magazines and newspaper articles found that risk factors were outlined in most articles; however, much of the information was ambiguous and incomplete (Wallace & Ballard, 2003). Educational videos have been shown to improve patient knowledge in a study population that included Caucasian (86%), African American (10.5%), and Asian (3.5%) participants (Kulp, Rane, & Bachmann, 2004).

For people to become engaged in the behavior change process, they must not only become aware of a particular health problem and the recommended precautions through knowledge-based interventions, they must also know whether their current behavior meets the recommended guidelines (Blalock, 2005). Providing feedback to women about calcium intake decreased the percentage of people who had never thought about osteoporosis by 23% in one prospective study, although the action-based plan (those who have decided to adopt preventative behaviors) was not associated with changes in knowledge or beliefs (Blalock et al., 2000). Therefore, people who have never thought about osteoporosis are likely to benefit the most from nutrition education aimed at increasing confidence in their abilities to adopt osteoprotective behaviors (Brug, Glanz, & Kok, 1997).

The use of a brief assessment tool such as the one developed by Blalock, Norton, Patel, Cabral, and Thomas (2003) may help practitioners assess patients' calcium intake within the short time frame of an office appointment. Nurses and health educators knowledgeable about osteoprotective concepts may help facilitate the adoption of osteoprotective behaviors. For example, they can recommend such primary prevention measures as nutritional supplementation, diet, and exercise as ways of reducing AED-induced metabolic bone changes. Such education would help improve risk communication, prevention, and treatment for people with epilepsy.

For people with childhood exposure to AEDs or more than 5 years of adult AED use (especially enzyme-inducing AEDs), and for women older than 50 years of age (regardless of length of AED use), a DEXA scan should be performed periodically (Pack et al., 2004). It has been found that unfavorable DEXA screening results increase the adoption of preventative behaviors such as use of calcium supplements (Patel et al., 2003) and exercise (Marci, Anderson, Viechnicki & Greenspan, 2000). In this study, having a present diagnosis of bone loss was significant only for calcium knowledge, and there were no significant differences in those with a history of fracture. This pattern is cause for concern, because 40% of participants reported experiencing a previous fracture. Given the overall safety of calcium (with vitamin D) supplementation and many forms of exercise for those with epilepsy, these preventative actions continue to be important osteoprotective recommendations for this population.

A final consideration is selection of AEDs. Because efficacy is generally similar among the various AEDs, prescribing patterns may be different depending on insurance status, concomitant medications, comorbidities, and child-bearing potential. Enzyme-inducing AEDs are more likely to be used as first-line treatment when patients are uninsured, underinsured, or on public assistance. However, because seizure control takes precedence over other concerns, it is not particularly likely that a nurse practitioner or a physician would change a patient's seizure medication simply on the basis that it negatively impacts bone health.

Study Limitations

This investigation was completed at one urban medical center without the use of a control population. To determine whether people with epilepsy truly have a knowledge deficiency regarding osteoprotective factors, it would be necessary to compare them with nonepilepsy patients of similar educational backgrounds and ethnicities. Such a study would allow for analyses controlling for these factors. The previous use of the OKT in more than 700 nonepilepsy patients does, however, provide a strong case for a range of scores to expect.

Because patients at a tertiary academic medical center are often more refractory to treatment, the differences we found may be higher when compared with a well-controlled epilepsy population seen only by primary care practitioners. In this study, we looked at the effects of seizure frequency on knowledge to provide an idea of what these differences may be. To strengthen our comparisons, however, it would have been helpful to assess exercise frequency and dietary calcium intake through a food frequency questionnaire.

The low overall response rate of 42% may be due in part to the length of the survey. Because this questionnaire was part of a larger study that involved a total of 146 questions (Elliott, Jacobson, & Seals, 2006), we felt additional questionnaires may have resulted in less participation or missing data. Only five patients verbally declined to participate, but many more failed to return the survey despite being given a self-addressed stamped envelope. This lack of response may be due to issues of low literacy in our population. Several participants were assisted by the researcher after their clinic visits to overcome difficulties with readability of the questions. Opportunities to address this issue with those patients receiving a mailed survey were much lower. Also, more women (n = 66) completed surveys than men (n = 28), which is not unexpected because osteoporosis is associated more with women in the media. This research is also limited by its cross-sectional nature. However, because no prior studies of osteoporosis knowledge in the epilepsy population exist, it is a useful starting point. Recommendations for future research include the development and evaluation of osteoprotective educational materials specific to epilepsy, as well as assessments of current dietary and exercise habits among people with epilepsy.

The OKT was developed in 1991 when there was a different recommended daily allowance (RDA) for calcium. The OKT should be revised to reflect the current RDA for calcium, which is mentioned in the background section.

Summary

Overall, this study contributes to the understanding of patient knowledge related to bone loss in people with epilepsy. Age and gender appear to have little impact on knowledge related to osteoporosis when compared with such socioeconomic factors as ethnicity, years of education, and yearly income. People with epilepsy had significantly lower levels of knowledge about risk factors, dietary calcium, and exercise patterns related to osteoporosis when compared with previous studies of nonepilepsy populations using the same questionnaire. These knowledge deficiencies are even more apparent in non-Caucasian populations. Minority status may place people at a disadvantage for adopting prevention recommendations related to exercise and calcium. Osteoprotective educational messages need to be tailored to multiethnic populations for maximum impact.

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Questions or comments about the article may be directed to John O. Elliott, MPH, at John.Elliott@osumc.edu. He is a clinical research data manager in the Department of Neurology at the Comprehensive Epilepsy Center at The Ohio State University, Columbus, OH.

Brenda F. Seals, PhD MPH, is an executive director and research associate at the Native American Cancer Initiative, Inc., Pine, CO.

Mercedes P. Jacobson, MD, is the director of the Comprehensive Epilepsy Center in the Department of Neurology at the Temple University School of Medicine, Philadelphia, PA.

Table 1. Osteoporosis Knowledge Test Results by Ethnicity

    Question                     Likelihood of Getting Osteoporosis

 1. Eating a diet low in milk    More likely *, less likely, nothing
    products                     to do with, don't know
 2. Being menopausal; "change    More likely *, less likely, nothing
    of life"                     to do with, don't know
 3. Having big bones             More likely, less likely *, nothing
                                 to do with, don't know
 4. Eating a diet high in dark   More likely, less likely *, nothing
    green leafy vegetables       to do with, don't know
 5. Having a mother or           More likely *, less likely, nothing
    grandmother who has          to do with, don't know
    osteoporosis
 6. Being a white woman with     More likely *, less likely, nothing
    fair skin                    to do with, don't know
 7. Having ovaries surgically    More likely *, less likely, nothing
    removed                      to do with, don't know
 8. Taking cortisone             More likely *, less likely, nothing
    (steroids, e.g.,             to do with, don't know
    prednisone) for a long
    time
 9. Exercising on a regular      More likely, less likely *, nothing
    basis                        to do with, don't know
10. Which of the following       Swimming, walking briskly *, doing
    exercises is the best way    kitchen chores, don't know
    to reduce a person's
    chance of getting
    osteoporosis?
11. Which of the following       Bicycling *, yoga, housecleaning,
    exercises is the best way    don't know
    to reduce a persons chance
    of getting osteoporosis?
12. How many days a week do      1 day a week, 2 days a week, 3 or
    you think a person should    more days a week *, don't know
    exercise to strengthen
    the bones?
13. What is the least amount     Less than 15 minutes, 20 to 30
    of time a person should      minutes *, more than 45 minutes,
    exercise on each occasion    don't know
    to strengthen the bones?
14. Exercise makes bones         Just a little faster, so fast that
    strong, but it must be       talking is not possible, much faster
    hard enough to make          but talking is possible *, don't know
    breathing:
15. Which of the following       Jogging or running for exercise *,
    exercises is the best way    golfing using golf cart, gardening,
    to reduce a person's         don't know
    chance of getting
    osteoporosis?
16. Which of the following       Bowling, doing laundry, aerobic
    exercises is the best way    dancing *, don't know
    to reduce a person's
    chance of getting
    osteoporosis?
17. Which of these is a good     Apple, cheese *, cucumber, don't know
    source of calcium?
18. Which of these is a good     Watermelon, corn, canned sardines *,
    source of calcium?           don't know
19. Which of these is a good     Chicken, broccoli *, grapes,
    source of calcium?           don't know
20. Which of these is a good     Yogurt *, strawberries, cabbage,
    source of calcium?           don't know
21. Which of these is a good     Ice cream *, grapefruit, radishes,
    source of calcium?           don't know
22. Which of the following is    100-300 mg daily, 400-600 mg daily,
    the recommended amount of    800 mg or more daily *, don't know
    calcium intake for an
    adult?
23. How much milk must an        1/2 glass daily, 1 glass daily, 2 or
    adult drink to meet the      more glasses daily *, don't know
    recommended amount of
    calcium?
24. Which of the following is    If a person skips breakfast, if a
    the best reason for taking   person does not get enough calcium
    a calcium supplement?        from diet *, if a person is over 45
                                 years old, don't know

                                             Number (%) Correct Answers

                                 Caucasian   Non-Caucasian   p Value **
    Question                     (n = 50)      (n = 44)

 1. Eating a diet low in milk     33 (66)         20 (45)       .046
    products
 2. Being menopausal; "change     32 (64)         17 (38)       .014
    of life"
 3. Having big bones               7 (14)          6 (13)       .960

 4. Eating a diet high in dark    24 (48)         18 (41)       .495
    green leafy vegetables
 5. Having a mother or            34 (68)         21 (48)       .047
    grandmother who has
    osteoporosis
 6. Being a white woman with       9 (18)          6 (14)       .569
    fair skin
 7. Having ovaries surgically     10 (20)          5 (11)       .259
    removed
 8. Taking cortisone              15 (30)         11 (25)       .593
    (steroids, e.g.,
    prednisone) for a long
    time
 9. Exercising on a regular       37 (74)         19 (43)       .002
    basis
10. Which of the following        22 (44)         23 (52)       .428
    exercises is the best way
    to reduce a person's
    chance of getting
    osteoporosis?
11. Which of the following        29 (58)         14 (32)       .011
    exercises is the best way
    to reduce a persons chance
    of getting osteoporosis?
12. How many days a week do       39 (78)         11 (70)       .408
    you think a person should
    exercise to strengthen
    the bones?
13. What is the least amount      33 (66)         26 (59)       .495
    of time a person should
    exercise on each occasion
    to strengthen the bones?
14. Exercise makes bones          15 (30)          7 (16)       .110
    strong, but it must be
    hard enough to make
    breathing:
15. Which of the following        33 (66)         24 (55)       .261
    exercises is the best way
    to reduce a person's
    chance of getting
    osteoporosis?
16. Which of the following        28 (56)         24 (55)       .889
    exercises is the best way
    to reduce a person's
    chance of getting
    osteoporosis?
17. Which of these is a good      42 (84)         33 (75)       .283
    source of calcium?
18. Which of these is a good      12 (24)          8 (18)       .497
    source of calcium?
19. Which of these is a good      30 (60)         27 (61)       .894
    source of calcium?
20. Which of these is a good      42 (84)         36 (82)       .782
    source of calcium?
21. Which of these is a good      35 (70)         25 (57)       .188
    source of calcium?
22. Which of the following is     21 (42)          5 (11)       .001
    the recommended amount of
    calcium intake for an
    adult?
23. How much milk must an         31 (62)         22 (50)       .246
    adult drink to meet the
    recommended amount of
    calcium?
24. Which of the following is     37 (74)         23 (52)       .029
    the best reason for taking
    a calcium supplement?

* Indicates correct answer.

** Based on two-tailed independent Student's t test. Developed by
Katherine Kim, PhD, Mary Horan, PhD, and Phyllis Gendler, PhD. (1991).
Used with permission.

Table 2. Demographics of Participants (N = 94)

Variables                                    n (%)

Gender
Female                                       66 (70)
Male                                         28 (30)

Ethnicity
Caucasian                                    50 (53)
African American                             32 (34)
Latino                                       12 (13)

Marital status
Single                                       48 (51)
Married                                      33 (35)
Separated/divorced/widowed                   13 (14)

Employment status
Full time                                    26 (28)
Part time                                    11 (12)
Not working                                  57 (60)

Yearly income
Under $10,000                                29 (31)
$10,000-$30,000                              24 (26)
Greater than $30,000                         22 (23)
Missing                                      19 (20)

Miscellaneous
Has prescription coverage                    72 (77)
On medical assistance                        36 (38)
Presently has a driver's license             38 (40)

Medical history
History of fracture                          37 (39)
Diagnosed with bone loss                     24 (26)
Taking an osteoporosis medication            13 (14)
Family history of osteoporosis               17 (18)
Presently taking calcium                     41 (44)

Last reported seizure
Within past 1 month                          42 (45)
Between 2 and 12 months                      27 (29)
More than 12 months                          25 (26)

Present number of antiepileptic drugs (a)
One                                          46 (49)
Two                                          33 (35)
Three                                        13 (14)
Four                                          1 (1)

(a) Data obtained from 93 participants.

Table 3. Osteoporosis Scales by Select Demographics-Mean
Scores (SD) (N = 94)

                                       OKT Exercise
Variables                         n    (Items 1-16)

Age (years)
18-34                             25   6.4 (3.0)
35-49                             34   7.4 (3.7)
50+                               35   7.4 (3.4)

Gender
Male                              28   6.7 (2.8)
Female                            66   7.4 (3.6)

Ethnicity
Caucasian                         50   8.0 (3.4) **
Non-Caucasian                     44   6.2 (3.1) **

Years of education (a)
<12 years                         55   6.2 (3.1) ***
>12 years                         37   8.9 (3.1) ***

Yearly income (b)
Under $10,000                     29   6.8 (3.5) *
$10,001-$30,000                   24   7.2 (2.9) *
More than $30,000                 22   9.1 (3.0) *

Last seizure
Within past 1 month               42   6.2 (2.8) *
Between 2 and 12 months           27   7.4 (3.7) *
More than 12 months               25   8.4 (3.6) *

Diagnosis of bone loss
No                                70   6.9 (3.1)
Yes                               24   8.0 (4.2)

History of fracture (c)
No                                56   7.1 (3.7)
Yes                               37   7.3 (2.9)

Family history of osteoporosis
Don't know                        17   5.9 (2.8) **
No                                60   6.9 (3.3) **
Yes                               17   9.5 (3.1) **

Taking a calcium supplement
No                                53   6.7 (3.2)
Yes                               41   7.8 (3.6)

                                     OKT Calcium       Total Score
Variables                         (Items 1-9,17-24)    (Items 1-24)

Age (years)
18-34                               7.2 (2.8)          10.6 (4.1)
35-49                               8.1 (4.4)          11.6 (5.6)
50+                                 8.5 (3.5)          12.6 (4.7)

Gender
Male                                7.3 (3.7)          11.1 (4.3)
Female                              8.3 (3.7)          11.9 (5.2)

Ethnicity
Caucasian                           8.9 (3.7) **       13.0 (4.9) **
Non-Caucasian                       6.9 (3.4) **       10.3 (4.5) **

Years of education (a)
<12 years                           6.5 (2.9) ***      10.1 (4.2) ***
>12 years                          10.5 (3.0) ***      14.6 (4.2) ***

Yearly income (b)
Under $10,000                       7.5 (3.9) *        11.3 (5.3)
$10,001-$30,000                     7.7 (3.3) *        11.5 (4.1)
More than $30,000                  10.1 (3.4) *        14.3 (4.5)

Last seizure
Within past 1 month                 6.6 (2.8) **       10.4 (4.0) *
Between 2 and 12 months             8.4 (4.3) **       11.9 (5.7) *
More than 12 months                 9.8 (3.4) **       13.8 (4.8) *

Diagnosis of bone loss
No                                  7.5 (3.3) *        11.1 (4.4)
Yes                                 9.4 (4.3) *        13.4 (6.1)

History of fracture (c]
No                                  7.9 (3.8)          11.6 (5.3)
Yes                                 8.2 (3.6)          11.9 (4.4)

Family history of osteoporosis
Don't know                          6.3 (3.3) **        9.6 (4.2) **
No                                  7.8 (3.5) **       11.4 (4.7) **
Yes                                10.3 (3.9) **       14.8 (5.1) **

Taking a calcium supplement
No                                  7.3 (3.6) *        10.7 (4.6) *
Yes                                 8.9 (3.6) *        13.0 (5.0) *

Note. OKT = Osteoporosis Knowledge Test.

(a) Data obtained from 92 participants.

(b) Data obtained from 75 participants.

(c) Data obtained from 93 participants.

* p <.05. ** p<.01. *** p <.001.

Table 4. Osteoporosis Knowledge Test Scores in Previous
Studies--Means (SD)

                    Sample
Author (Year)        Size     Population Description

Kim et al. (1991)   N = 201   U.S., women, age > 35
Sedlak et           N = 31    U.S., college women, age > 18
al. (1998)                    Intervention = 18

                              Control = 13

Sedlak et                     U.S., women
al. (2000)          N = 31    Intense (three sessions, 3-week
                              period)
                              College, age < 25
                    N = 35    Intermediate (one 3-hour
                              session)
                              Community, age 22-83
                    N = 18    Brief (one 45-minute session)
                              Nurses, age 35-49

Piaseu et           N = 100   Thai, women, 1st year nursing
al. (2001)                    students, age 17-21
                              Intervention = 50 (3-hour
                              session)

                              Control = 50

Ziccardi et         N = 194   U.S., nursing students
al. (2004)                    Men = 11, women = 183

Tung & Lee          N = 128   Chinese, men, age > 18
(2006)
                              All participants = 128
                              Intervention = 64
                              Control = 64

Lee & Lai           N = 52    Chinese, men, age > 60
(2006)

Current study       N = 94    Persons with epilepsy, age > 18
(2007)                        Men = 28, women = 66

                     Exercise     Calcium (Items   Total Score
Study Type         (Items 1-16)   1-9, 17-24)      (Items 1-24)

Cross-sectional    11.16 (2.80)   11.74 (3.01)     11.45 (2.91)
Experimental
  Pretest                                          15.50 (3.03)
  Posttest                                         20.83 (1.47)
  Pretest                                          14.53 (3.31)
  Posttest                                         15.77 (3.14)
Experimental
  Pretest                                          15.09
  Posttest                                         18.71
  Pretest                                          15.08
  Posttest                                         18.75
  Pretest                                          17.82
  Posttest                                         20.88
  Experimental
  Pretest           8.9 (1.8)      8.8 (2.3)       12.7 (2.5)
  Posttest         14.6 (1.1)     15.5 (1.5)       21.8 (1.8)
  Pretest           9.2 (2.1)      8.7 (2.1)       13.0 (2.7)
  Posttest          9.1 (1.7)      8.9 (1.9)       13.1 (2.4)
Cross-sectional
Sophomores = 86     9.8 (2.2)     10.9 (2.3)       15.3
Seniors = 108      12.1 (1.8)     12.1 (1.8)       18.7
Randomized
controlled trial
  Pretest                                          10.8 (3.52)
  Posttest                                         15.03
  Posttest                                         11.30
Cross-sectional     5.73 (3.64)    4.42 (3.42)      7.83 (5.12)
Cross-sectional     7.16 (3.39)    8.00 (3.68)     11.71 (4.92)

Study Type         % Correct   p Value

Cross-sectional      47.7
Experimental
  Pretest            64.6
  Posttest           86.8      NR
  Pretest            60.5
  Posttest           65.7      NR
Experimental
  Pretest            62.8
  Posttest           77.9      p < .001
  Pretest            62.8
  Posttest           78.1      p < .01
  Pretest            74.2
  Posttest           87.0      p < .001
  Experimental
  Pretest            52.9
  Posttest           90.8      p < .01
  Pretest            54.2
  Posttest           54.6      NS
Cross-sectional
Sophomores = 86      63.7
Seniors = 108        77.9
Randomized
controlled trial
  Pretest            45.0
  Posttest           62.6      p < .001
  Posttest           47.1      NS
Cross-sectional      32.6
Cross-sectional      48.8

Note. NR = not reported; NS = not significant.