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Nursing and Health Sciences (2014), 16, 461–467
Research Article
Factors associated with nonadherence to antihypertensive medication Su-Jin Cho, RN, MPH and Jinhyun Kim, PhD College of Nursing, Seoul National University, Seoul, Korea
Abstract
Hypertension is one of the most serious health problems in Korea. The purpose of this paper is to identify factors associated with self-reported nonadherence to an antihypertensive regimen. The data were obtained from the Korean Medical Panel 2008 and 2009 database, which were surveyed by the Korea Institute for Health and Social Affairs and National Health Insurance. We analyzed 5324 patients using multivariate logistic regression models. Self-reported nonadherence was used as a dependent variable and demographic, socioeconomic, and health status were included as independent variables to investigate the associated factors. Among the patients who were diagnosed with hypertension, 13.2% did not take their medicine as prescribed. Age and education attainment level were statistically significant. Younger and lower educational attainment groups were less likely to adhere to medication regimens and showed a tendency not to take their medicine as prescribed. There were no statistically significant variables in terms of health status. Our findings suggest that nurses in clinical and community settings should pay more attention to hypertensive patients who are young and less educated.
Key words
adherence, antihypertensive agent, chronic disease, hypertension, Korea.
INTRODUCTION Hypertension is one of the most pressing health problems in Korea. The prevalence of hypertension is as high as 24.6% of the Korean adult population, making it the most common chronic disease (Park et al., 2010). Hypertension is a major risk factor for cardiovascular and cerebrovascular diseases, which are the second and third leading causes of mortality in Korea (Statistics Korea, 2011). People with 10 mmHg higher systolic blood pressure (BP) or 20 mmHg higher diastolic BP have approximately a 100% higher risk of stroke or coronary artery than those with normal BP (Park et al., 2010). Therefore, one of the most effective ways to prevent cardiovascular and cerebrovascular diseases could be hypertension control. There are many ways to control BP, such as exercise, dietary, and medication therapy (Yang et al., 2010). Among them, adhering to a therapeutic regimen of medication is considered to be the most effective way to control blood pressure (Baune et al., 2005; Krousel-Wood et al., 2005; Burnier, 2006). Some evidence in Korea suggests that properly adhering to a medication regimen can prevent adverse outcomes related to hypertension. A poor adherence group showed a 2.2 times higher risk of morbidity, including instances of nephropathy, cerebrovascular disease, and cardiovascular disease (Park et al., 2010). This group was also 2.4
times more likely to be hospitalized in a year (Jang et al., 2008) compared to a group showing better adherence. To control BP is the most widespread program implemented by nurses at community health centers in Korea. Nurses are responsible for assessing medication-taking behavior (Ben-Natan & Noselozich, 2011) and play a main role in educating hypertensive patients to take medicine appropriately. This means that nurses are required to recognize factors associated with medication adherence to help patients with hypertension. Several studies have been conducted on the topic of antihypertensive medication adherence in Korea (Jang et al., 2008; Park et al., 2008a,b; 2010). Although there are a variety of factors related to medication adherence, numerous factors were omitted in most studies. Only one study (Park et al., 2008b) explored multiple factors through using health insurance claims data, but it did not consider socioeconomic aspects such as education and per capita income. Studies in Korea also did not identify whether patients in fact took their medicine or not due to limitations related to health insurance claims data. Therefore, this study was designed to identify factors, including demographic, socioeconomic, and healthstatus variables associated with self-reported nonadherence to antihypertensive regimen.
Literature review Correspondence address: Jinhyun Kim, College of Nursing, Seoul National University, 103 Daehak-ro, Jongro-gu, Seoul 110-799, Korea. Email: [email protected] Received 21 August 2013; revision received 17 March 2014; accepted 19 March 2014
© 2014 Wiley Publishing Asia Pty Ltd.
Medication adherence refers to the extent to which a patient acts in accordance with the prescribed interval and dose of a doi: 10.1111/nhs.12145
462
dosing regimen. In this context, nonadherence means missing medication doses in the context of ongoing use (Cramer et al., 2008). Adherence is determined by factors related to socioeconomic status, healthcare system, health condition, therapy, and patient-related factors (World Health Organization, 2003). Many studies consider demographic factors as distinct from socioeconomic factors (Lowry et al., 2005; Vawter et al., 2008; Braverman & Dedier, 2009; Friedman et al., 2010). Gender, age, ethnicity, and residential area were included as demographic factors related to medication adherence in several studies. A few studies reported that it was more probable for males than females to show adherence (Degli Esposti et al., 2002; Park et al., 2008b), while females showed greater adherence to antihypertensive medication regimens in other studies (Jokisalo et al., 2002; Hyre et al., 2007; Friedman et al., 2010). Old age is associated with better adherence in studies conducted in Pakistan (Hashmi et al., 2007), Korea (Park et al., 2008b), the USA (Hyre et al., 2007) and Finland (Jokisalo et al., 2002). Persistence and adherence were both lower in urban residents compared with rural residents in Canada (Friedman et al., 2010), whereas metropolitan residents had higher adherence levels than rural residents in Korea (Park et al., 2008b). Income, job type, insurance type, and education level as socioeconomic factors affect medication adherence as well. Adherence is increased in patients with higher incomes in Canada (Friedman et al., 2010), and groups composed of those in lower economic classes showed lower adherence rates in Portugal (Santa-Helena et al., 2010) and in the USA (Vawter et al., 2008). Persons working in the unskilled labor market were less likely to adhere to an antihypertensive medication regimen (Santa-Helena et al., 2010). Individuals with low education attainment levels tend to report unintentional nonadherence (Lowry et al., 2005; Uzun et al., 2009). A good relationship between patient and provider as a factor of the healthcare system improves medication adherence because healthcare professionals empower patients to become involved in their treatment (Fincham, 2007). As for factors of health condition, persons with disabilities, especially mobility and communication disabilities (Park et al., 2008a), depressive symptoms (Morris et al., 2006; Krousel-Wood et al., 2011), and mental function impairments (Vawter et al., 2008) showed inappropriate medication adherence behavior compared to those without such disabilities. In contrast, several studies found that medication adherence was better in patients with comorbidity as compared to those not showing comorbidity (Lagi et al., 2006; Shaya et al., 2009; Friedman et al., 2010). With regard to factors of therapy, patients prescribed with angiotensin-converting enzyme inhibitors showed better adherence than those taking beta-blockers or diuretics (Fitz-Simon et al., 2005; Friedman et al., 2010), and an increase in the number of pills and the required frequency were related to nonadherence (Bangalore et al., 2007). Regarding patient-related factors, beliefs about medication were related to medication adherence (Gregoire et al., 2006; Lewis et al., 2010) and behavioral attitudes, perceived © 2014 Wiley Publishing Asia Pty Ltd.
S-J. Cho and J. Kim
behavioral control, and subjective norms were positively related to intentions to self-administer medication in the elderly (Ben-Natan and Noselozich, 2011).
Purpose The purpose of this study was to identify factors among demographic, socioeconomic, and health-status factors affecting nonadherence in patients with hypertension.
METHODS Data sources This study used data from the Korean Medical Panel from 2008 and 2009. The Korean Medical Panel provides secondary data from that collected by the Korea Institute for Health and Social Affairs (KIHASA) and National Health Insurance (NHI). All researchers must submit research plans before given authority to use the data (Korea Institute for Health and Social Affairs & National Health Insurance, 2010). Authorization to access the data was granted by the KIHASA and NHI in 2011. The Korean Medical Panel surveyed all members of the households that were selected as representatives. The sample was randomly stratified by region from all households in Korea. The Korean Medical Panel surveyed 21 787 respondents of 7066 households in 2008 and 19 641 respondents of 6300 households in 2009 (Korea Institute for Health and Social Affairs & National Health Insurance, 2010). The survey in the first year was repeated in the second using the same questions. The numbers of respondents who reported that they had hypertension were 2783 in 2008 and 2800 in 2009. First, we excluded patients who had not visited clinics for a diagnosis and who had missing data, such as that related to medication adherence and/or job and income status. Due to this process, 109 (3.9%) respondents in 2008 and 128 (4.6%) respondents in 2009 were excluded. Next, we excluded patients who answered “no” to the question, “Do you take medicine that lowers your blood pressure?” Fifteen in 2008 and seven in 2009 were additionally excluded. Finally, 2659 (95.5%) in 2008 and 2665 (95.2%) in 2009 were included in the final analysis. Among them, 2230 of the patients were surveyed for both years.
Variables We defined nonadherence as to whether respondents in the analysis answered “no” to the question, “Do you take medicine according to an antihypertensive medication regimen?” The Korean Medical Panel asked patients who were diagnosed with hypertension by medical doctors and prescribed more than once. Regarding predictors, we applied the demographic, socioeconomic, and health-related factors as surveyed by the Korean Medical Panel. The demographic variables were gender (male, female), age (< 45, 45–64, 65–74, ≥ 75), living alone (yes, no), and residence (capital area, outside the capital area). The socioeconomic variables included
Nonadherence to antihypertensive regimen
insurance (health insurance, medical benefit), job status (none, temporary, permanent) and average annual income (< 4000, 4000–7999, 8000–11 999, ≥ 12 000 US dollars). Average annual income was calculated by dividing the total household income by the number of family members. The type of insurance was considered to be a health-systemrelated factor (World Health Organization, 2003), while it also represents the socioeconomic status of the respondent. Therefore, we included insurance type as a socioeconomic factor. We included disabilities (presence, no presence) and the number of comorbidities except hypertension (0, 1–2, ≥ 3) as health-status variables. Age, income, and the number of comorbidities were originally measured as continuous variables, but ultimately we grouped them as a categorized variable. One advantage of panel data is that it allows researchers to estimate the effects of changes of independent variables on dependent variables over time. However, we could not estimate these effects as the demographic, socioeconomic, and health status of patients typically does not change over a period of one year. For this reason, we included the survey year as a variable under the assumption that the predictors affect nonadherence independently despite the fact that many of the same people were surveyed in both 2008 and 2009.
Statistical analysis First, we ran a chi-square test to find the differences between the adherence and nonadherence groups. Next, multivariate logistic regression models were used to identify significant factors influencing nonadherence. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated, and P values that were below 0.05 were considered to be statistically significant. Demographic (Model 1), socioeconomic (Model 2), and health status (Model 3) variables were entered in order to determine which characteristics predict noncompliance best. We assessed the fit of the multivariate models using c statistics at each step.
RESULTS Among the patients who were diagnosed with hypertension, 702 (13.2%) reported not taking their antihypertensive medication as prescribed. There were 364 (13.7%) in 2008 and 338 (12.7%) in 2009. Table 1 shows the characteristics of the study population. More than half the patients were female aged 65 years and over. The educational attainment of approximately 50% was below middle school, and full-time workers accounted for only 30%. The patients had a mean monthly income of US $1600. Approximately 10% had one or more disabilities, and more than 80% had other chronic diseases apart from hypertension. There were significant differences found for the three variables of age, educational attainment, and job status between the adherence and nonadherence groups (Table 2). More than 20% of those aged < 45 reported they did not take their medicine as prescribed. There was a trend toward patients those with less education reporting a higher incidence of
463
Table 1.
Characteristics of the study population (n = 5324)
Characteristics Survey year 2008 2009 Gender Male Female Age < 45 45–64 65–74 ≥ 75 Residence Capital area Outside capital area Family Living alone Not living alone Insurance type Health insurance No health insurance Education Less than primary school Primary school Middle school High school Beyond high school Job Not economically active Full-time workers Temporary workers Annual income (US dollar) < 4 000 4 000–7 999 8 000–11 999 ≥ 12 000 Number of disabilities None More than one Number of chronic diseases 0 1–2 ≥3
N
%
2659 2665
49.9 50.1
2283 3041
42.9 57.1
299 2240 1891 894
5.6 42.1 35.5 16.8
1822 3502
34.2 65.8
660 4664
12.4 87.6
4942 382
92.8 7.2
889 1701 871 1385 478
16.7 31.9 16.4 26.0 9.0
2846 1436 1042
53.5 27.0 19.6
1034 1554 836 1900
19.4 29.2 15.7 35.7
4689 635
88.1 11.9
1037 2444 1843
19.5 45.9 34.6
nonadherence. The rate of nonadhering patients who were not economically active was lower than the rate of those who were. Age and gender were associated with nonadherence in the first model (Table 3). However, the statistical significance of gender disappeared after adjusting for the socioeconomic variables. Age increased the likelihood of medication adherence, but residence and whether or not a patient lived alone were not statistically significant. Furthermore, those with higher levels of educational attainment were more likely to be adherent than those with lower levels. However, there were no statistically significant differences related to insurance type, job status, or income. With regard to health status, there were no statistically significant variables in the analysis. © 2014 Wiley Publishing Asia Pty Ltd.
464
S-J. Cho and J. Kim
Table 2. Percentage of self-reported nonadherence demographic, socioeconomic, and health-status variables Characteristics Survey year 2008 2009 Gender Male Female Age < 45 45–64 65–74 ≥ 75 Residence Capital area Outside capital area Family Living alone Not living alone Insurance type Health insurance No health insurance Education Less than primary school Primary school Middle school High school Beyond high school Job Not economically active Full-time workers Temporary workers Annual income (US dollar) < 4 000 4 000–7 999 8 000–11 999 ≥ 12 000 Number of disabilities None More than one Number of chronic diseases 0 1–2 ≥3
by
N
Nonadherence (%)
P value
364 338
13.7 12.7
0.278
283 419
12.4 13.8
0.140
67 307 219 109
22.4 13.7 11.6 12.2
< 0.001
232 470
12.7 13.4
0.482
92 610
13.9 13.1
0.541
640 62
13.0 16.2
0.068
149 207 118 181 47
16.8 12.2 13.5 13.1 9.8
0.003
348 186 168
12.2 13.0 16.1
0.006
143 184 106 269
13.8 11.8 12.7 14.2
0.204
621 81
13.2 12.8
0.733
145 326 231
14.0 13.3 12.5
0.520
Demographic variables We noted that only age among the demographic variables was associated with nonadherence. Our findings thus support the results of previous studies. Many studies indicated that older people were more likely to be persistent or to adhere to taking their prescriptions (Jokisalo et al., 2002; Hyre et al., 2007). In fact, a one-year difference was associated with a rate of medication discontinuation that was 0.98 times greater (Degli Esposti et al., 2002). Recent research has also shown that those older than 55 years adhere to a refill schedule at higher rates than a younger group (Steiner et al., 2009). Patients who perceived hypertension as a risk tend to show greater adherence to an antihypertensive regimen (Gregoire et al., 2006). Older people tend to be more interested in health issues and perceive hypertension as a risk more than younger people, which make older people more adherent.We did not find statistically significant differences in adherence rates between groups by gender or residence. Our findings somewhat match those of previous studies in that some inconsistencies arose.
Socioeconomic variables
The c statistics result for Model 1 was 0.557. Adding the socioeconomic variables produced a value for this model of 0.596, but health-status variables did not improve it any further.
DISCUSSION The self-reported nonadherence rate was 13.2%, and age and education attainment were associated with self-reported nonadherence after adjusting for other variables. Younger patients with relatively less education were not likely to take their medicine as prescribed compared to those who were older and who had more education attainment. Apart from © 2014 Wiley Publishing Asia Pty Ltd.
age and education, the other variables, that is, demographic and socioeconomic variables, did not affect medication adherence. Factors pertaining to health status were not related to medication adherence, either.
We demonstrated that a lower education attainment level was associated with higher rates of nonadherence. Earlier research performed in the USA also showed that those with more education showed greater rates of medication adherence (Lowry et al., 2005). A study carried out in Finland explained the relationships between education and medication adherence as a result of an information seeking attitude, holding that higher education is associated with receiving more advice and information from a physician (Jokisalo et al., 2002). Further, a recent study found that the effects of education on medication adherence varied by sex, showing that lower educational attainment was associated with higher adherence in men but that lower educational attainment was related to lower adherence in women (Braverman & Dedier, 2009). However, the effects of education on medication adherence did not differ by gender in our additional analyses. According to our findings, other socioeconomic variables excluding education did not relate with nonadherence. On the other hand, insurance type and income were related to medication adherence in Portugal (Santa-Helena et al., 2010) and Canada (Friedman et al., 2010). Medication adherence increases with the utility and continuity of health care (Fincham, 2007). Since most treatments and prescriptions pertaining to hypertension are covered by health insurance or medical benefits in Korea, nonadherence appears to be unaffected by insurance type or income level in our study.
Health-status variables There were no statistically significant variables related to nonadherence among the health-status variables. A lack of
Nonadherence to antihypertensive regimen
465
Table 3. Odd ratios (OR) and 95% confidence intervals (CI) for factors associated with self-reported nonadherence
Characteristics Survey year 2008 2009 Gender Male Female Age < 45 45–64 65–74 ≥ 75 Residence Capital area Outside capital area Family Living alone Not living alone Insurance type Health insurance Not health insurance Education Less than primary school Primary school Middle school High school Beyond High school Job Not economically active Full-time workers Temporary workers Annual income (US dollar) < 4 000 4 000–7 999 8 000–11 999 ≥ 12 000 Disorder Not present Present Number of chronic diseases 0 1–2 ≥3 c-statistics Likelihood ratio chi-square (P value)
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Reference 0.92 (0.79–1.08)
Reference 0.91 (0.77–1.06)
Reference 0.91 (0.77–1.07)
Reference 1.19 (1.00–1.40)*
Reference 0.99 (0.82–1.21)
Reference 0.99 (0.82–1.21)
Reference 0.53 (0.39–0.71)* 0.43 (0.31–0.58)* 0.44 (0.31–0.62)*
Reference 0.46 (0.34–0.63)* 0.34 (0.24–0.48)* 0.33 (0.22–0.50)*
Reference 0.46 (0.34–0.64)* 0.34 (0.24–0.49)* 0.33 (0.22–0.50)*
Reference 1.07 (0.91–1.27)
Reference 1.00 (0.84–1.19)
Reference 1.00 (0.84–1.19)
Reference 0.89 (0.70–1.14)
Reference 0.96 (0.74–1.24)
Reference 0.96 (0.74–1.23)
Reference 1.26 (0.93–1.72)
Reference 1.27 (0.93–1.74)
Reference 0.64 (0.50–0.81)* 0.64 (0.48–0.86)* 0.55 (0.41–0.74)* 0.36 (0.23–0.54)*
Reference 0.64 (0.50–0.81)* 0.64 (0.47–0.86)* 0.55 (0.41–0.74)* 0.36 (0.23–0.54)*
Reference 1.03 (0.82–1.29) 1.23 (0.99–1.52)
Reference 1.03 (0.82–1.29) 1.23 (0.99–1.52)
Reference 0.86 (0.68–1.09) 0.93 (0.70–1.23) 1.06 (0.83–1.35)
Reference 0.86 (0.68–1.09) 0.93 (0.70–1.23) 1.06 (0.83–1.35) Reference 1.02 (0.80–1.32)
0.557 32.245 (< 0.001)
0.596 72.750 (< 0.001)
Reference 1.00 (0.80–1.25) 0.99 (0.77–1.27) 0.596 72.782 (< 0.001)
*P value
Nursing and Health Sciences (2014), 16, 461–467
Research Article
Factors associated with nonadherence to antihypertensive medication Su-Jin Cho, RN, MPH and Jinhyun Kim, PhD College of Nursing, Seoul National University, Seoul, Korea
Abstract
Hypertension is one of the most serious health problems in Korea. The purpose of this paper is to identify factors associated with self-reported nonadherence to an antihypertensive regimen. The data were obtained from the Korean Medical Panel 2008 and 2009 database, which were surveyed by the Korea Institute for Health and Social Affairs and National Health Insurance. We analyzed 5324 patients using multivariate logistic regression models. Self-reported nonadherence was used as a dependent variable and demographic, socioeconomic, and health status were included as independent variables to investigate the associated factors. Among the patients who were diagnosed with hypertension, 13.2% did not take their medicine as prescribed. Age and education attainment level were statistically significant. Younger and lower educational attainment groups were less likely to adhere to medication regimens and showed a tendency not to take their medicine as prescribed. There were no statistically significant variables in terms of health status. Our findings suggest that nurses in clinical and community settings should pay more attention to hypertensive patients who are young and less educated.
Key words
adherence, antihypertensive agent, chronic disease, hypertension, Korea.
INTRODUCTION Hypertension is one of the most pressing health problems in Korea. The prevalence of hypertension is as high as 24.6% of the Korean adult population, making it the most common chronic disease (Park et al., 2010). Hypertension is a major risk factor for cardiovascular and cerebrovascular diseases, which are the second and third leading causes of mortality in Korea (Statistics Korea, 2011). People with 10 mmHg higher systolic blood pressure (BP) or 20 mmHg higher diastolic BP have approximately a 100% higher risk of stroke or coronary artery than those with normal BP (Park et al., 2010). Therefore, one of the most effective ways to prevent cardiovascular and cerebrovascular diseases could be hypertension control. There are many ways to control BP, such as exercise, dietary, and medication therapy (Yang et al., 2010). Among them, adhering to a therapeutic regimen of medication is considered to be the most effective way to control blood pressure (Baune et al., 2005; Krousel-Wood et al., 2005; Burnier, 2006). Some evidence in Korea suggests that properly adhering to a medication regimen can prevent adverse outcomes related to hypertension. A poor adherence group showed a 2.2 times higher risk of morbidity, including instances of nephropathy, cerebrovascular disease, and cardiovascular disease (Park et al., 2010). This group was also 2.4
times more likely to be hospitalized in a year (Jang et al., 2008) compared to a group showing better adherence. To control BP is the most widespread program implemented by nurses at community health centers in Korea. Nurses are responsible for assessing medication-taking behavior (Ben-Natan & Noselozich, 2011) and play a main role in educating hypertensive patients to take medicine appropriately. This means that nurses are required to recognize factors associated with medication adherence to help patients with hypertension. Several studies have been conducted on the topic of antihypertensive medication adherence in Korea (Jang et al., 2008; Park et al., 2008a,b; 2010). Although there are a variety of factors related to medication adherence, numerous factors were omitted in most studies. Only one study (Park et al., 2008b) explored multiple factors through using health insurance claims data, but it did not consider socioeconomic aspects such as education and per capita income. Studies in Korea also did not identify whether patients in fact took their medicine or not due to limitations related to health insurance claims data. Therefore, this study was designed to identify factors, including demographic, socioeconomic, and healthstatus variables associated with self-reported nonadherence to antihypertensive regimen.
Literature review Correspondence address: Jinhyun Kim, College of Nursing, Seoul National University, 103 Daehak-ro, Jongro-gu, Seoul 110-799, Korea. Email: [email protected] Received 21 August 2013; revision received 17 March 2014; accepted 19 March 2014
© 2014 Wiley Publishing Asia Pty Ltd.
Medication adherence refers to the extent to which a patient acts in accordance with the prescribed interval and dose of a doi: 10.1111/nhs.12145
462
dosing regimen. In this context, nonadherence means missing medication doses in the context of ongoing use (Cramer et al., 2008). Adherence is determined by factors related to socioeconomic status, healthcare system, health condition, therapy, and patient-related factors (World Health Organization, 2003). Many studies consider demographic factors as distinct from socioeconomic factors (Lowry et al., 2005; Vawter et al., 2008; Braverman & Dedier, 2009; Friedman et al., 2010). Gender, age, ethnicity, and residential area were included as demographic factors related to medication adherence in several studies. A few studies reported that it was more probable for males than females to show adherence (Degli Esposti et al., 2002; Park et al., 2008b), while females showed greater adherence to antihypertensive medication regimens in other studies (Jokisalo et al., 2002; Hyre et al., 2007; Friedman et al., 2010). Old age is associated with better adherence in studies conducted in Pakistan (Hashmi et al., 2007), Korea (Park et al., 2008b), the USA (Hyre et al., 2007) and Finland (Jokisalo et al., 2002). Persistence and adherence were both lower in urban residents compared with rural residents in Canada (Friedman et al., 2010), whereas metropolitan residents had higher adherence levels than rural residents in Korea (Park et al., 2008b). Income, job type, insurance type, and education level as socioeconomic factors affect medication adherence as well. Adherence is increased in patients with higher incomes in Canada (Friedman et al., 2010), and groups composed of those in lower economic classes showed lower adherence rates in Portugal (Santa-Helena et al., 2010) and in the USA (Vawter et al., 2008). Persons working in the unskilled labor market were less likely to adhere to an antihypertensive medication regimen (Santa-Helena et al., 2010). Individuals with low education attainment levels tend to report unintentional nonadherence (Lowry et al., 2005; Uzun et al., 2009). A good relationship between patient and provider as a factor of the healthcare system improves medication adherence because healthcare professionals empower patients to become involved in their treatment (Fincham, 2007). As for factors of health condition, persons with disabilities, especially mobility and communication disabilities (Park et al., 2008a), depressive symptoms (Morris et al., 2006; Krousel-Wood et al., 2011), and mental function impairments (Vawter et al., 2008) showed inappropriate medication adherence behavior compared to those without such disabilities. In contrast, several studies found that medication adherence was better in patients with comorbidity as compared to those not showing comorbidity (Lagi et al., 2006; Shaya et al., 2009; Friedman et al., 2010). With regard to factors of therapy, patients prescribed with angiotensin-converting enzyme inhibitors showed better adherence than those taking beta-blockers or diuretics (Fitz-Simon et al., 2005; Friedman et al., 2010), and an increase in the number of pills and the required frequency were related to nonadherence (Bangalore et al., 2007). Regarding patient-related factors, beliefs about medication were related to medication adherence (Gregoire et al., 2006; Lewis et al., 2010) and behavioral attitudes, perceived © 2014 Wiley Publishing Asia Pty Ltd.
S-J. Cho and J. Kim
behavioral control, and subjective norms were positively related to intentions to self-administer medication in the elderly (Ben-Natan and Noselozich, 2011).
Purpose The purpose of this study was to identify factors among demographic, socioeconomic, and health-status factors affecting nonadherence in patients with hypertension.
METHODS Data sources This study used data from the Korean Medical Panel from 2008 and 2009. The Korean Medical Panel provides secondary data from that collected by the Korea Institute for Health and Social Affairs (KIHASA) and National Health Insurance (NHI). All researchers must submit research plans before given authority to use the data (Korea Institute for Health and Social Affairs & National Health Insurance, 2010). Authorization to access the data was granted by the KIHASA and NHI in 2011. The Korean Medical Panel surveyed all members of the households that were selected as representatives. The sample was randomly stratified by region from all households in Korea. The Korean Medical Panel surveyed 21 787 respondents of 7066 households in 2008 and 19 641 respondents of 6300 households in 2009 (Korea Institute for Health and Social Affairs & National Health Insurance, 2010). The survey in the first year was repeated in the second using the same questions. The numbers of respondents who reported that they had hypertension were 2783 in 2008 and 2800 in 2009. First, we excluded patients who had not visited clinics for a diagnosis and who had missing data, such as that related to medication adherence and/or job and income status. Due to this process, 109 (3.9%) respondents in 2008 and 128 (4.6%) respondents in 2009 were excluded. Next, we excluded patients who answered “no” to the question, “Do you take medicine that lowers your blood pressure?” Fifteen in 2008 and seven in 2009 were additionally excluded. Finally, 2659 (95.5%) in 2008 and 2665 (95.2%) in 2009 were included in the final analysis. Among them, 2230 of the patients were surveyed for both years.
Variables We defined nonadherence as to whether respondents in the analysis answered “no” to the question, “Do you take medicine according to an antihypertensive medication regimen?” The Korean Medical Panel asked patients who were diagnosed with hypertension by medical doctors and prescribed more than once. Regarding predictors, we applied the demographic, socioeconomic, and health-related factors as surveyed by the Korean Medical Panel. The demographic variables were gender (male, female), age (< 45, 45–64, 65–74, ≥ 75), living alone (yes, no), and residence (capital area, outside the capital area). The socioeconomic variables included
Nonadherence to antihypertensive regimen
insurance (health insurance, medical benefit), job status (none, temporary, permanent) and average annual income (< 4000, 4000–7999, 8000–11 999, ≥ 12 000 US dollars). Average annual income was calculated by dividing the total household income by the number of family members. The type of insurance was considered to be a health-systemrelated factor (World Health Organization, 2003), while it also represents the socioeconomic status of the respondent. Therefore, we included insurance type as a socioeconomic factor. We included disabilities (presence, no presence) and the number of comorbidities except hypertension (0, 1–2, ≥ 3) as health-status variables. Age, income, and the number of comorbidities were originally measured as continuous variables, but ultimately we grouped them as a categorized variable. One advantage of panel data is that it allows researchers to estimate the effects of changes of independent variables on dependent variables over time. However, we could not estimate these effects as the demographic, socioeconomic, and health status of patients typically does not change over a period of one year. For this reason, we included the survey year as a variable under the assumption that the predictors affect nonadherence independently despite the fact that many of the same people were surveyed in both 2008 and 2009.
Statistical analysis First, we ran a chi-square test to find the differences between the adherence and nonadherence groups. Next, multivariate logistic regression models were used to identify significant factors influencing nonadherence. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated, and P values that were below 0.05 were considered to be statistically significant. Demographic (Model 1), socioeconomic (Model 2), and health status (Model 3) variables were entered in order to determine which characteristics predict noncompliance best. We assessed the fit of the multivariate models using c statistics at each step.
RESULTS Among the patients who were diagnosed with hypertension, 702 (13.2%) reported not taking their antihypertensive medication as prescribed. There were 364 (13.7%) in 2008 and 338 (12.7%) in 2009. Table 1 shows the characteristics of the study population. More than half the patients were female aged 65 years and over. The educational attainment of approximately 50% was below middle school, and full-time workers accounted for only 30%. The patients had a mean monthly income of US $1600. Approximately 10% had one or more disabilities, and more than 80% had other chronic diseases apart from hypertension. There were significant differences found for the three variables of age, educational attainment, and job status between the adherence and nonadherence groups (Table 2). More than 20% of those aged < 45 reported they did not take their medicine as prescribed. There was a trend toward patients those with less education reporting a higher incidence of
463
Table 1.
Characteristics of the study population (n = 5324)
Characteristics Survey year 2008 2009 Gender Male Female Age < 45 45–64 65–74 ≥ 75 Residence Capital area Outside capital area Family Living alone Not living alone Insurance type Health insurance No health insurance Education Less than primary school Primary school Middle school High school Beyond high school Job Not economically active Full-time workers Temporary workers Annual income (US dollar) < 4 000 4 000–7 999 8 000–11 999 ≥ 12 000 Number of disabilities None More than one Number of chronic diseases 0 1–2 ≥3
N
%
2659 2665
49.9 50.1
2283 3041
42.9 57.1
299 2240 1891 894
5.6 42.1 35.5 16.8
1822 3502
34.2 65.8
660 4664
12.4 87.6
4942 382
92.8 7.2
889 1701 871 1385 478
16.7 31.9 16.4 26.0 9.0
2846 1436 1042
53.5 27.0 19.6
1034 1554 836 1900
19.4 29.2 15.7 35.7
4689 635
88.1 11.9
1037 2444 1843
19.5 45.9 34.6
nonadherence. The rate of nonadhering patients who were not economically active was lower than the rate of those who were. Age and gender were associated with nonadherence in the first model (Table 3). However, the statistical significance of gender disappeared after adjusting for the socioeconomic variables. Age increased the likelihood of medication adherence, but residence and whether or not a patient lived alone were not statistically significant. Furthermore, those with higher levels of educational attainment were more likely to be adherent than those with lower levels. However, there were no statistically significant differences related to insurance type, job status, or income. With regard to health status, there were no statistically significant variables in the analysis. © 2014 Wiley Publishing Asia Pty Ltd.
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S-J. Cho and J. Kim
Table 2. Percentage of self-reported nonadherence demographic, socioeconomic, and health-status variables Characteristics Survey year 2008 2009 Gender Male Female Age < 45 45–64 65–74 ≥ 75 Residence Capital area Outside capital area Family Living alone Not living alone Insurance type Health insurance No health insurance Education Less than primary school Primary school Middle school High school Beyond high school Job Not economically active Full-time workers Temporary workers Annual income (US dollar) < 4 000 4 000–7 999 8 000–11 999 ≥ 12 000 Number of disabilities None More than one Number of chronic diseases 0 1–2 ≥3
by
N
Nonadherence (%)
P value
364 338
13.7 12.7
0.278
283 419
12.4 13.8
0.140
67 307 219 109
22.4 13.7 11.6 12.2
< 0.001
232 470
12.7 13.4
0.482
92 610
13.9 13.1
0.541
640 62
13.0 16.2
0.068
149 207 118 181 47
16.8 12.2 13.5 13.1 9.8
0.003
348 186 168
12.2 13.0 16.1
0.006
143 184 106 269
13.8 11.8 12.7 14.2
0.204
621 81
13.2 12.8
0.733
145 326 231
14.0 13.3 12.5
0.520
Demographic variables We noted that only age among the demographic variables was associated with nonadherence. Our findings thus support the results of previous studies. Many studies indicated that older people were more likely to be persistent or to adhere to taking their prescriptions (Jokisalo et al., 2002; Hyre et al., 2007). In fact, a one-year difference was associated with a rate of medication discontinuation that was 0.98 times greater (Degli Esposti et al., 2002). Recent research has also shown that those older than 55 years adhere to a refill schedule at higher rates than a younger group (Steiner et al., 2009). Patients who perceived hypertension as a risk tend to show greater adherence to an antihypertensive regimen (Gregoire et al., 2006). Older people tend to be more interested in health issues and perceive hypertension as a risk more than younger people, which make older people more adherent.We did not find statistically significant differences in adherence rates between groups by gender or residence. Our findings somewhat match those of previous studies in that some inconsistencies arose.
Socioeconomic variables
The c statistics result for Model 1 was 0.557. Adding the socioeconomic variables produced a value for this model of 0.596, but health-status variables did not improve it any further.
DISCUSSION The self-reported nonadherence rate was 13.2%, and age and education attainment were associated with self-reported nonadherence after adjusting for other variables. Younger patients with relatively less education were not likely to take their medicine as prescribed compared to those who were older and who had more education attainment. Apart from © 2014 Wiley Publishing Asia Pty Ltd.
age and education, the other variables, that is, demographic and socioeconomic variables, did not affect medication adherence. Factors pertaining to health status were not related to medication adherence, either.
We demonstrated that a lower education attainment level was associated with higher rates of nonadherence. Earlier research performed in the USA also showed that those with more education showed greater rates of medication adherence (Lowry et al., 2005). A study carried out in Finland explained the relationships between education and medication adherence as a result of an information seeking attitude, holding that higher education is associated with receiving more advice and information from a physician (Jokisalo et al., 2002). Further, a recent study found that the effects of education on medication adherence varied by sex, showing that lower educational attainment was associated with higher adherence in men but that lower educational attainment was related to lower adherence in women (Braverman & Dedier, 2009). However, the effects of education on medication adherence did not differ by gender in our additional analyses. According to our findings, other socioeconomic variables excluding education did not relate with nonadherence. On the other hand, insurance type and income were related to medication adherence in Portugal (Santa-Helena et al., 2010) and Canada (Friedman et al., 2010). Medication adherence increases with the utility and continuity of health care (Fincham, 2007). Since most treatments and prescriptions pertaining to hypertension are covered by health insurance or medical benefits in Korea, nonadherence appears to be unaffected by insurance type or income level in our study.
Health-status variables There were no statistically significant variables related to nonadherence among the health-status variables. A lack of
Nonadherence to antihypertensive regimen
465
Table 3. Odd ratios (OR) and 95% confidence intervals (CI) for factors associated with self-reported nonadherence
Characteristics Survey year 2008 2009 Gender Male Female Age < 45 45–64 65–74 ≥ 75 Residence Capital area Outside capital area Family Living alone Not living alone Insurance type Health insurance Not health insurance Education Less than primary school Primary school Middle school High school Beyond High school Job Not economically active Full-time workers Temporary workers Annual income (US dollar) < 4 000 4 000–7 999 8 000–11 999 ≥ 12 000 Disorder Not present Present Number of chronic diseases 0 1–2 ≥3 c-statistics Likelihood ratio chi-square (P value)
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Reference 0.92 (0.79–1.08)
Reference 0.91 (0.77–1.06)
Reference 0.91 (0.77–1.07)
Reference 1.19 (1.00–1.40)*
Reference 0.99 (0.82–1.21)
Reference 0.99 (0.82–1.21)
Reference 0.53 (0.39–0.71)* 0.43 (0.31–0.58)* 0.44 (0.31–0.62)*
Reference 0.46 (0.34–0.63)* 0.34 (0.24–0.48)* 0.33 (0.22–0.50)*
Reference 0.46 (0.34–0.64)* 0.34 (0.24–0.49)* 0.33 (0.22–0.50)*
Reference 1.07 (0.91–1.27)
Reference 1.00 (0.84–1.19)
Reference 1.00 (0.84–1.19)
Reference 0.89 (0.70–1.14)
Reference 0.96 (0.74–1.24)
Reference 0.96 (0.74–1.23)
Reference 1.26 (0.93–1.72)
Reference 1.27 (0.93–1.74)
Reference 0.64 (0.50–0.81)* 0.64 (0.48–0.86)* 0.55 (0.41–0.74)* 0.36 (0.23–0.54)*
Reference 0.64 (0.50–0.81)* 0.64 (0.47–0.86)* 0.55 (0.41–0.74)* 0.36 (0.23–0.54)*
Reference 1.03 (0.82–1.29) 1.23 (0.99–1.52)
Reference 1.03 (0.82–1.29) 1.23 (0.99–1.52)
Reference 0.86 (0.68–1.09) 0.93 (0.70–1.23) 1.06 (0.83–1.35)
Reference 0.86 (0.68–1.09) 0.93 (0.70–1.23) 1.06 (0.83–1.35) Reference 1.02 (0.80–1.32)
0.557 32.245 (< 0.001)
0.596 72.750 (< 0.001)
Reference 1.00 (0.80–1.25) 0.99 (0.77–1.27) 0.596 72.782 (< 0.001)
*P value
