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Published in final edited form as: J Appl Gerontol. 2013 Jun 11;34(7):844–857. doi: 10.1177/0733464813490247

Correlates of Health-Related Quality of Life Among Korean Immigrant Elders

Jong-Eun Lee 1, Miyong T Kim 2, Hae-Ra Han 3
PMCID: PMC4511715  NIHMSID: NIHMS707010  PMID: 24652887

Abstract

Health-related quality of life (HRQOL) is a key clinical outcome, particularly for individuals with chronic conditions such as hypertension (HTN). While no previous research has examined contributors to HRQOL among Asian Americans in the United States, this study was conducted to identify correlates of HRQOL in hypertensive Korean immigrant elders (≥ 60 years of age) to address the gap. A total of 440 Korean elders with HTN participated in the study. The hierarchical regression model for HRQOL explained 32.8% of the variance. Female gender (β = .109, p = .036), a greater number of comorbid conditions (β = .183, p = .000), lower social support (β = −.240, p = .000), and greater depressive symptoms (β = .402, p = .000) were associated with poorer HRQOL. Depression was the most potent correlate of HRQOL among elderly Korean Americans (KA) with HTN. Future intervention should consider managing depression as an essential component of comprehensive HTN care for this minority population.

Keywords: health-related quality of life (HRQOL), hypertension (HTN), depression, elderly, Korean Americans (KA)

Introduction

Health-related quality of life (HRQOL) describes a person’s general well-being, which encompasses biophysical and psychological factors, symptoms, functioning, and general health perceptions (Trevisol, Moreira, Kerkhoff, Fuchs, & Fuchs, 2011; Wilson & Cleary, 1995). HRQOL is an important clinical outcome—particularly for individuals with chronic conditions such as hypertension (HTN)—which affects more than one in four adults in the United States and worldwide. According to a survey of 8,303 adults in the United States (Hayes, Denny, Keenan, Croft, & Greenlund, 2008), individuals with HTN are more likely to report poor HRQOL than are those without HTN. Similarly, elderly patients with HTN report worse HRQOL compared to those without HTN (Banegas et al., 2007). In turn, studies have revealed that poor HRQOL results in poor adherence to medication taking (Holt, Muntner, Joyce, Webber, & Krousel-Wood, 2010) and poor HTN control (Ogunlana, Adedokun, Dairo, & Odunaiya, 2009).

Several studies have reported correlates of HRQOL among the elderly with HTN. In these studies, depression, and certain demographic- and disease-related characteristics (e.g., older age, female gender, HTN medication, comorbidity) were associated with poor HRQOL (Heyworth, Hazell, Linehan, & Frank, 2009; Holt et al., 2010; Michalsen et al., 2001; Rueda & Pérez-García, 2006; Ucan & Ovayolu, 2010). In particular, depression has been a consistent risk factor for poor HRQOL in patients with HTN (Heyworth et al., 2009; Holt et al., 2010; Michalsen et al., 2001; Rueda & Pérez-García, 2006; Ucan & Ovayolu, 2010). Few studies indicate that social support may play a protective role in promoting HRQOL in the presence of depressive symptoms. For example, Strine et al. (2009) found that a feeling of inadequate social support was associated with depression and poor HRQOL. Likewise, Huang et al. (2010) presented that higher social support was significantly less likely to improve depression than those without social support among chronic heart disease patients. One study suggested social support as a possible modifiable risk factor for HRQOL among elderly with HTN (Michalsen et al., 2001). While these studies offer some insights as to potential contributors to HRQOL among elderly, to the best of our knowledge, no previous study looked specifically at potential contributors to HRQOL among Asian immigrant elders with HTN. We found one study (Mui et al., 2007) in which HRQOL among Korean immigrant elderly was compared with the U.S. population norms for SF-36; however, the study did not specifically look at HTN patients, nor did it investigate correlates of HRQOL.

Korean American (KA) elderly are predominantly first-generation immigrants (U.S. Census Bureau, 2009). A previous epidemiological study has shown a higher prevalence of HTN (32% vs. 29%) among KAs (M. T. Kim, Kim, Juon, & Hill, 2000) than in the general U.S. population (Hayes et al., 2008). The rate was particularly high among KA elderly, when compared to that of Chinese American elderly of the same age (71% vs. 53%; Hsu, Mao, & Wey, 2010; M. T. Kim, Juon, Hill, Post, & Kim, 2001). In the case of underserved populations such as KA elderly who have limited resources and network for support, it is important to identify the possible mechanism(s) by which HRQOL can be promoted, particularly among those who are at risk for poor HRQOL. To this end, the aim of this study was to identify correlates of HRQOL, with a particular focus on social support and depression. We hypothesized that social support would positively correlate with HRQOL whereas depression would have an inverse relationship with HRQOL in KA elders with HTN.

Method

Study Design and Participants

Baseline data were obtained from a community-based, randomized clinical trial designed to promote HTN control among KA elderly in the Baltimore-Washington Metropolitan Area. Potential participants were identified via announcements at ethnic churches and senior centers in the target region. Eligibility criteria were: (a) self-identified as a first-generation KA, (b) ≥ 60 years of age, (c) systolic blood pressure (BP) ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg or on antihypertensive medication, and (d) no cognitive impairment, based on the Korean version of Mini-Mental State Exam (K-MMSE; Kang, Na, & Han, 1997). A total of 440 eligible participants completed the baseline assessment and were included in this analysis.

Procedure

After all study procedures were approved by the Institutional Review Board, eligible KA elderly who agreed to participate in this study were assessed at baseline via face-to-face interview by trained bilingual research staff. Participants needed about 40 to 50 min to complete the questionnaire. Body weight, height, and BP were also measured. BP was measured three times using the A&D UA-767 (A&D Company, Ltd, Tokyo, Japan) according to published guidelines (Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure, 2003). All three readings were taken after the participant had been seated for 5 min. Baseline BP was calculated by averaging the second and third readings. BP control was defined as blood pressure < 140/90 mm Hg (Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure, 2003).

Measures

The baseline survey included questions about demographic characteristics which were all self-reported, such as age, gender, years of education, years in the United States, and disease-related factors (e.g., years of HTN, antihypertensive medication, and comorbidity). In addition, several established instruments were used to measure psychosocial variables and HRQOL in the study sample. Every study instrument, including the study questionnaire, was made available in Korean because all of our study participants were monolingual.

Social support was measured by the Personal Resource Questionnaire (PRQ) 85-Part 2 (Weinert, 1987), a 25-item, 7-point (1–7) Likert-type scale. A higher score indicates a higher level of perceived social support. The PRQ 85-Part 2 has been validated in KAs with the original scale developer (H. R. Han, Kim, & Weinert, 2002). The alpha coefficient of the scale was 0.91 in this sample.

The severity of depressive symptoms was measured using the Patient Health Questionnaire (PHQ)-9 (Kroenke, Spitzer, & Williams, 2001). The PHQ-9 is based on the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV), and has nine items scored from 0 (not at all) to 3 (nearly every day). Participants were asked whether they experienced any symptom(s) over the past 2 weeks. Total scores range from 0 to 27. KA elderly were categorized as having depressive symptoms when the PHQ-9 score was ≥ 5 (Kroenke et al., 2001). The validity and reliability of the PHQ-9 have been reported in primary care and obstetrical and gynecological patients (Kroenke et al., 2001) and Korean elders (Donnelly & Kim, 2008; C. Han et al., 2008). The alpha coefficient of the scale was 0.80 in the KA sample.

HRQOL was assessed by using a modified version of the HTN Battery of Scales-Reduced Version, which was designed to measure HRQOL in adults with HTN (Nelsen, Himmelberger, Morrison, Berger, & Markson, 1999). It consists of 40 items, including psychological well-being (7 items) and symptom bother (33 items) domains. Psychological well-being items (e.g., “During the last month, were you generally tense or did you feel any tension?”) are scored on a 6-point Likert-type scale (e.g., 1 = “I never felt tense or any tension” to 6 = “Yes, extremely tense, most of time”), while the symptom bother scale includes 1 = yes or 0 = no responses. Total scores can range from 7 to 40 for the psychological well-being subscale and from 0 to 33 for the symptom bother subscale, with a higher score indicating lower HRQOL. The HRQOL instrument has been validated (Nelsen et al., 1999). The original English version was translated into Korean and then back-translated into English. We used an expert panel to confirm content validity of the translated version. The alpha coefficient of the translated version was 0.84 in the KA elderly.

Data Analysis

Descriptive statistics, including means, standard deviation, and percentages, were used to summarize the study variables. Pearson’s correlation coefficients were computed to examine the relationships between study variables. Hierarchical regression was conducted to examine the significant contribution of each group of variables in explaining HRQOL. Age, gender, years of education, and length of stay in the United States were entered as covariates in the first step. In Step 2, disease-related factors—including years of HTN, antihypertensive medication taking status, comorbidity, BP control—were entered into the regression model, followed by psychosocial variables (social support and depression) in Step 3. All analyses were 2-tailed; p values < .05 were considered statistically significant.

Results

Sample Characteristics

Table 1 summarizes the characteristics of the sample. The mean age of the participants was 70.9 (± 5.5) years, with the majority being female (69.5%). The participants had an average of 11.1 (± 4.3) years of education and had lived in the United States for 24.1 (± 11.0) years. The mean duration of HTN diagnosis was 9.6 (± 8.9) years; 83.9% were taking antihypertensive medication. About three fourths of the respondents (75.9%) had comorbid conditions (e.g., diabetes, hyperlipidemia). Fewer than half (44.8%) had controlled BP (i.e., BP < 140/90 mm Hg). The mean item score of social support was 5.2 (± 0.9) and more than one in five (21.1%) reported depressive symptoms (PHQ-9 score ≥ 5). The sample had a mean item score of 2.3 (± 0.7) points for psychological well-being, indicating a generally high level of well-being. While the majority of the study sample reported eight or more unpleasant symptoms (mean ± SD = 8.2 ± 5.6), there was no significant difference in the number of symptom bothers reported between those on antihypertensive medication and those not on medication (8.3 ± 5.6 and 7.2 ± 5.1, respectively, p = .117).

Table 1.

Sample Characteristics (N = 440).

N (%) / Mean ± SD
Age (range 60–89), year 70.9 ± 5.5
Female, % 306 (69.5)
Years of education (range 0–25) 11.1 ± 4.3
Years in the United States (range, < 1–48) 24.1 ± 11.0
Years of HTN (range, < 1–50) 9.6 ± 8.9
On antihypertensive medication, % 369 (83.9)
Comorbidity, % 334 (75.9)
BP control, %† 197 (44.8)
Social support (range 1.9–7.0) 5.2 ± 0.9
Depression, %†† 93 (21.1)
QoL (range, 1.0–5.1) 2.3 ± 0.7
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Note: QoL = Quality of life. HTN = Hypertension.

†

(systolic blood pressure) SBP < 140 mm Hg and (Diastolic blood pressure) DBP < 90 mm Hg

††

Defined by a score on the PHQ-9 of 5 points or more

Bivariate Analysis of the Study Variables

Table 2 presents Pearson’s correlation coefficients among the study variables. Being female (r = 0.16, p = .001), having fewer years of education (r = −0.13, p = 0.007), comorbidity (r = 0.18, p = .000), low social support (r =−.45, p = .000), and high depression scores (r = .49, p = .000) were significantly correlated with poorer HRQOL. Age, years in the United States, years of HTN, taking antihypertensive medication, and BP control were not significantly associated with HRQOL in bivariate analysis.

Table 2.

Correlations of the Variables (N = 440).

Variables 1 2 3 4 5 6 7 8 9 10 11
1. Age 1 −.112* −.134** .123** .143** .078 .159** −.009 .073 −.084 −.091
2. Gender −.112* 1 −.376** −.100* −.014 .072 .078 .069 .072 .149** .155**
3. Years of education −.134** −.376** 1 .116* −.036 .024 −.046 .049 .122* −.117* −.128**
4. Years in united States .123** −.100* .116* 1 .154** .148** .059 .033 .035 −.057 −.053
5. Years of hypertension (HTN) .143 −.014 −.036 .154** 1 .337** .114* −.020 .034 −.013 .061
6. Taking antihypertensive medication .078 .072 .024 .148** .337** 1 .186** .370** .012 .061 .052
7. Comorbidity .159** .078 −.046 .059 .114* .186** 1 .112* −.024 .096* .180**
8. BP control −.009 .069 .049 .033 −.020 .370** .112* 1 .034 .026 −.021
9. Social support .073 .072 .122* .035 .034 .012 −.024* .034 1 −.286** −.444**
10. Depression −.084 .149** −.117* −.057 −.013 .061 .096* .026 −.286** 1 .489**
11. QoL −.091 .155** −.128** −.053 .061 .052 .180** −.021 −.444** .489** 1
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Note: QoL = Quality of Life.

*

p ≤ .05.

**

p ≤ .01

Correlates of HRQOL

Table 3 shows the results of hierarchical regression analysis related to HRQOL. The final model explained 32.8% of the variance. In Steps 1 and 2, gender (β = .109, p = .036) and comorbidity (β = .183, p = .000) emerged as significant correlates of HRQOL. In the final step, social support (β =−.240, p = .000) and depressive symptoms (β = .402, p = .000) were predictive of HRQOL after accounting for sociodemographic and disease-related characteristics in Steps 1 and 2. Thus, being female, a greater number of comorbid conditions, lower social support, and higher depression were associated with poorer HRQOL in the sample of KA elders with HTN.

Table 3.

Hierarchical Regression Analysis Predicting Quality of Life (N = 437).

Predictors b SE b β Adjusted R2 R2 change
Step 1 .039*** .039**
  Age −.011 .006 −.089
  Gender .159 .076 .109*
  Year of education −.015 .008 −.098
  Years in United States −.001 .003 −.020
Step 2 .079** .040***
  Years of hypertension (HTN) .004 .004 .048
  Taking antihypertensive medication .069 .100 .038
  Comorbidity .287 .076 .183***
  BP (blood pressure) control −.073 .069 −.054
Step 3 .328*** .249***
  Social support −.389 .069 −.240***
  Depression .659 .069 .402***
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Note:

*

p ≤ .05.

**

p ≤ .01.

***

p ≤ .001

Age, gender, years of education, and years in United States were controlled.

Taking antihypertensive medication: Yes = 1, No = 0

Comorbidity: Yes = 1, No = 0

BP control: Yes = 1, No = 0

Depression: PHQ-9 score ≥ 5 = 1, < 5 = 0

Discussion

We found a depression rate of 21% in our sample, as measured by the PHQ-9. This rate is lower than that reported in another sample of community-residing KA elderly (27%) using the same instrument (Donnelly & Kim, 2008) and also lower than that reported in the general U.S. elderly population (26%; Li, Friedman, Conwell, & Fiscella, 2007). One possible explanation is that our study sample was recruited from ethnic churches and senior centers, where study participants can have frequent and regular social contact with others; therefore, the prevalence of depression might have been unusually low. Nevertheless, given that depression negatively influences HTN self-care behaviors such as adherence to antihypertensive medication and dietary regimens (M. T. Kim, Han, Hill, Rose, & Roary, 2003; Siegel, Lopez, & Meier, 2007), it is still important to identify and incorporate effective strategies to minimize the effects of depression in patients with HTN. Integrated care interventions such as individualized education and telephone monitoring have been shown to produce significant improvement in terms of depression and adherence behaviors in hypertensive patients (Bogner & de Vries, 2008).

More than three quarters of our sample of KA elderly reported one or more comorbid conditions, and the comorbidity was negatively associated with HRQOL at bivariate level. The result is consistent with a previous study of hypertensive patients in which comorbid conditions negatively affected HRQOL (Aydemir, Ozdemir, & Koroglu, 2005). Elderly with multiple comorbid conditions have to deal with polypharmacy (Frutos Bernal, Martín Corral, & Galindo Villardón, 2011). In addition, a sense of burden with regard to the daily management and treatment of multiple chronic conditions, worries about increased health care costs or adverse drug reactions, and challenges regarding medication adherence have been reported in elderly patients with comorbidity (Elliott, 2009; Hsu et al., 2010). All these factors can adversely contribute to HRQOL.

Little research has been done to examine the relationship between social support and HRQOL in HTN patients. In our sample of KA elderly with HTN, we observed a direct correlation between social support and HRQOL; higher social support was associated with better HRQOL. Previous studies have found that diabetic patients who have a high level of satisfaction with social support report better HRQOL (Misra & Lager, 2008; Tang, Brown, Funnell, & Anderson, 2008). The protective role of social support in the presence of negative life adversities has been well documented. For example, in a study of Korean immigrants, greater social support was associated with less depression (Shin, Han, & Kim, 2007). Likewise, diabetic patients without depression were more likely to report receiving social support, compared to those with major depression (Egede, Grubaugh, & Ellis, 2010). Together, the findings suggest the importance of social support as part of an effective intervention program to promote HRQOL among individuals with chronic conditions such as HTN. Indeed, intervention studies focusing on social support have proven effective in promoting weight loss, lowering blood pressure, and improving adherence to antihypertensive medication among HTN patients (Bosworth et al., 2008; Criswell, Weber, Xu, & Carter, 2010; Stevens et al., 2001).

There are a number of potential limitations to consider in interpreting the results of this study. First, we used a convenience sample; the study participants were generally healthy and mobile, given that they were all recruited from Korean ethnic churches and senior centers. Hence, the results might not be generalizable to less mobile KAs or other elderly populations with different cultural backgrounds. Likewise, most of our study participants were churchgoers. Ethnic churches provide a source of social support for immigrants, as has often been reported in the literature (Leach & Schoenberg, 2008). Therefore, it is possible that the level of social support in our sample was overestimated to some extent. Some studies found that more religious involvement (e.g., church attendance) was associated with lower depression (Huang, Hsu, & Chen, 2012; Patel, Shah, Peterson, & Kimmel, 2002), larger social networks, and greater perceived quality of support (Bradley, 1995; Ellison & George, 1994). There is counter evidence, however, that religious involvement is inversely associated with greater depression in some elders (Braam et al., 2004). Future research is warranted to explore whether religious involvement plays a role in the relationships between social support, depression, and HRQOL among Korean elderly. While low income has been associated with depression among Korean immigrant elderly (Lee & Holm, 2012), we were unable to include income in the regression equation due to large missing data. Finally our data were cross-sectional in nature and hence no causal relationship can be established.

In conclusion the study contributes to our understanding of the association between social support, depression, and HRQOL among hypertensive immigrant KA elders. In particular, our findings highlight the importance of depression management as an essential component of comprehensive HTN care for hypertensive KA elderly and suggest the potential utility of social support as a way to minimize the negative impact of depression on HRQOL. Future research should focus on developing and applying effective depression management and social support strategies to improve HRQOL in this minority population. Mobilizing social network support (e.g., socializing with friends, neighbors, or group activities) available in a church setting (B. J. Kim, Sangalang, & Kihl, 2012) could be a particularly useful strategy to decrease depression and improve HRQOL in KA elderly, as a majority of KA regularly attend ethnic church.

Acknowledgments

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by NHLBI grant R01 HL085567. Editorial support was provided by Dr. Deborah McClellan through the Johns Hopkins University School of Nursing Center for Excellence for Cardiovascular Health in Vulnerable Populations (P30 NR011409). This study was supported by a grant from the National Heart, Lung, and Blood Institute (R01 HL085567, Clinical Trials Registry NCT00406614).

Biographies

Jong-Eun Lee is Assistant Professor at the Catholic University of Korea College of Nursing where she teaches community health nursing.

Miyong T. Kim is Professor of Nursing and Director of the Center for Excellence for Cardiovascular Health in Vulnerable Populations at the Johns Hopkins University School of Nursing.

Hae-Ra Han is Associate Professor and Director of the PhD Program at the Johns Hopkins University School of Nursing.

Footnotes

The study was approved by the Institutional Review Board of the university (IRB protocol #NA_00003250).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

  1. Aydemir O, Ozdemir C, Koroglu E. The impact of co-morbid conditions on the SF-36: A primary-care-based study among hypertensive. Archives of Medical Research. 2005;36(2):136–141. doi: 10.1016/j.arcmed.2004.12.009. [DOI] [PubMed] [Google Scholar]
  2. Banegas JR, López-García E, Graciani A, Guallar-Castillón P, Gutierrez-Fisac JL, Alonso J, Rodríguez-Artalejo F. Relationship between obesity, hypertension and diabetes, and health-related quality of life among the elderly. European Journal of Cardiovascular Prevention and Rehabilitation. 2007;14:456–462. doi: 10.1097/HJR.0b013e3280803f29. [DOI] [PubMed] [Google Scholar]
  3. Bogner HR, de Vries HF. Integration of depression and hypertension treatment: A pilot, randomized controlled trial. Annals of Family Medicine. 2008;6:295–301. doi: 10.1370/afm.843. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bosworth HB, Olsen MK, Neary A, Orr M, Grubber J, Svetkey L, Oddone EZ. Take Control of Your Blood Pressure (TCYB) study: A multifactorial tailored behavioral and educational intervention for achieving blood pressure control. Patient Education and Counseling. 2008;70:338–347. doi: 10.1016/j.pec.2007.11.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Braam AW, Hein E, Deeg DJ, Twisk JW, Beekman AT, Van Tilburg W. Religious involvement and 6-year course of depressive symptoms in older Dutch citizens: Results from the Longitudinal Aging Study Amsterdam. Journal of Aging and Health. 2004;16:467–489. doi: 10.1177/0898264304265765. [DOI] [PubMed] [Google Scholar]
  6. Bradley DE. Religious involvement and social resources: Evidence from the data set “Americans’ changing lives”. Journal for the Scientific Study of Religion. 1995;34:259–267. [Google Scholar]
  7. Criswell TJ, Weber CA, Xu Y, Carter BL. Effect of self-efficacy and social support on adherence to antihypertensive drugs. Pharmacotherapy. 2010;30:432–441. doi: 10.1592/phco.30.5.432. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Donnelly PL, Kim KS. The Patient Health Questionnaire (PHQ-9K) to screen for depressive disorders among immigrant Korean American elderly. Journal of Cultural Diversity. 2008;15(1):24–29. [PubMed] [Google Scholar]
  9. Egede LE, Grubaugh AL, Ellis C. The effect of major depression on preventive care and quality of life among adults with diabetes. General Hospital Psychiatry. 2010;32:563–569. doi: 10.1016/j.genhosppsych.2010.08.002. [DOI] [PubMed] [Google Scholar]
  10. Elliott WJ. Improving outcomes in hypertensive patients: Focus on adherence and persistence with antihypertensive therapy. Journal of Clinical Hypertension. 2009;11:376–382. doi: 10.1111/j.1751-7176.2009.00138.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Ellison CG, George LK. Religious involvement, social ties, and social support in a southeastern community. Journal for the Scientific Study of Religion. 1994;33:46–61. [Google Scholar]
  12. Frutos Bernal E, Martín Corral JC, Galindo Villardón P. Factors related to polypharmacy in the non-institutionalised elderly. Analysis of the subsample of the National Survey of Health 2006 for the elderly in Castile-Leon. Revista Española de Geriatría y Gerontología. 2011;46:303–306. doi: 10.1016/j.regg.2011.03.002. [DOI] [PubMed] [Google Scholar]
  13. Han C, Jo SA, Kwak JH, Pae CU, Steffens D, Jo I, Park MH. Validation of the Patient Health Questionnaire-9 Korean version in the elderly population: The Ansan Geriatric study. Comprehensive Psychiatry. 2008;49(2):218–223. doi: 10.1016/j.comppsych.2007.08.006. [DOI] [PubMed] [Google Scholar]
  14. Han HR, Kim MT, Weinert C. The psychometric evaluation of Korean translation of the personal resource questionnaire 85-part 2. Nursing Research. 2002;51:309–316. doi: 10.1097/00006199-200209000-00007. [DOI] [PubMed] [Google Scholar]
  15. Hayes DK, Denny CH, Keenan NL, Croft JB, Greenlund KJ. Health-related quality of life and hypertension status, awareness, treatment, and control: National Health and Nutrition Examination Survey, 2001–2004. Journal of Hypertension. 2008;26:641–647. doi: 10.1097/HJH.0b013e3282f3eb50. [DOI] [PubMed] [Google Scholar]
  16. Heyworth IT, Hazell ML, Linehan MF, Frank TL. How do common chronic conditions affect health-related quality of life? British Journal of General Practice. 2009;59:e353–e358. doi: 10.3399/bjgp09X453990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Holt EW, Muntner P, Joyce CJ, Webber L, Krousel-Wood MA. Health-related quality of life and antihypertensive medication adherence among older adults. Age and Aging. 2010;39:481–487. doi: 10.1093/ageing/afq040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hsu YH, Mao CL, Wey M. Antihypertensive medication adherence among elderly Chinese Americans. Journal of Transcultural Nursing. 2010;21:297–305. doi: 10.1177/1043659609360707. [DOI] [PubMed] [Google Scholar]
  19. Huang CY, Hsu MC, Chen TJ. An exploratory study of religious involvement as a moderator between anxiety, depressive symptoms and quality of life outcomes of older adults. Journal of Clinical Nursing. 2012;21(5–6):609–619. doi: 10.1111/j.1365-2702.2010.03412.x. [DOI] [PubMed] [Google Scholar]
  20. Huang CY, Hsu MC, Hsu SP, Cheng PC, Lin SF, Chuang CH. Mediating roles of social support on poststroke depression and quality of life in patients with ischemic stroke. Journal of Clinical Nursing. 2010;19(19–20):2752–2762. doi: 10.1111/j.1365-2702.2010.03327.x. [DOI] [PubMed] [Google Scholar]
  21. Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure. The seventh report of the joint national committee on detection, evaluation, and treatment of high blood pressure. Washington, DC: NIH Publications; 2003. [Google Scholar]
  22. Kang YW, Na DL, Han SH. A Validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients. Journal of the Korean Neurological Association. 1997;15:300–308. [Google Scholar]
  23. Kim BJ, Sangalang CC, Kihl T. Effects of acculturation and social network support on depression among elderly Korean immigrants. Aging & Mental Health. 2012;16:787–794. doi: 10.1080/13607863.2012.660622. [DOI] [PubMed] [Google Scholar]
  24. Kim MT, Han HR, Hill MN, Rose L, Roary M. Depression, substance use, adherence behaviors, and blood pressure in urban hypertensive black men. Annals of Behavioral Medicine. 2003;26(1):24–31. doi: 10.1207/S15324796ABM2601_04. [DOI] [PubMed] [Google Scholar]
  25. Kim MT, Juon HS, Hill MN, Post W, Kim KB. Cardiovascular disease risk factors in Korean American elderly. Western Journal of Nursing Research. 2001;23:269–282. doi: 10.1177/01939450122045140. [DOI] [PubMed] [Google Scholar]
  26. Kim MT, Kim KB, Juon HS, Hill MN. Prevalence and factors associated with high blood pressure in Korean Americans. Ethnicity & Disease. 2000;10:364–374. [PubMed] [Google Scholar]
  27. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine. 2001;16:606–613. doi: 10.1046/j.1525-1497.2001.016009606.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Leach CR, Schoenberg NE. Striving for control: Cognitive, self-care, and faith strategies employed by vulnerable black and white older adults with multiple chronic conditions. Journal of Cross-Cultural Gerontology. 2008;23:377–399. doi: 10.1007/s10823-008-9086-2. [DOI] [PubMed] [Google Scholar]
  29. Lee YM, Holm K. Stressors related to depression among elderly Korean immigrants. Issues in Mental Health Nursing. 2012;33(1):52–58. doi: 10.3109/01612840.2011.618965. [DOI] [PubMed] [Google Scholar]
  30. Li C, Friedman B, Conwell Y, Fiscella K. Validity of the Patient Health Questionnaire 2 (PHQ-2) in identifying major depression in older people. Journal of the American Geriatrics Society. 2007;55:596–602. doi: 10.1111/j.1532-5415.2007.01103.x. [DOI] [PubMed] [Google Scholar]
  31. Michalsen A, Wenzel RR, Mayer C, Broer M, Philipp T, Dobos GJ. Quality of life and psychosocial factors during treatment with antihypertensive drugs. A comparison of captopril and quinapril in geriatric patients. Herz. 2001;26:468–476. doi: 10.1007/pl00002050. [DOI] [PubMed] [Google Scholar]
  32. Misra R, Lager J. Predictors of quality of life among adults with type 2 diabetes mellitus. Journal of Diabetes and its Complications. 2008;22:217–223. doi: 10.1016/j.jdiacomp.2006.09.002. [DOI] [PubMed] [Google Scholar]
  33. Mui AC, Kang SY, Kang D, Domanski MD. English language proficiency and health-related quality of life among Chinese and Korean immigrant elders. Health & social Work. 2007;32(2):119–127. doi: 10.1093/hsw/32.2.119. [DOI] [PubMed] [Google Scholar]
  34. Nelsen LM, Himmelberger DU, Morrison A, Berger ML, Markson LE. Quality-of-life questionnaire for patients taking antihypertensive medication. Clinical Therapeutics. 1999;21:1771–1787. doi: 10.1016/S0149-2918(99)80055-1. [DOI] [PubMed] [Google Scholar]
  35. Ogunlana MO, Adedokun B, Dairo MD, Odunaiya NA. Profile and predictor of health-related quality of life among hypertensive patients in south-western Nigeria. BMC Cardiovascular Disorders. 2009;9:25. doi: 10.1186/1471-2261-9-25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Patel SS, Shah VS, Peterson RA, Kimmel PL. Psychosocial variables, quality of life, and religious beliefs in ESRD patients treated with hemodialysis. American Journal of Kidney Diseases. 2002;40:1013–1022. doi: 10.1053/ajkd.2002.36336. [DOI] [PubMed] [Google Scholar]
  37. Rueda B, Pérez-García AM. A prospective study of the effects of psychological resources and depression in essential hypertension. Journal of Health Psychology. 2006;11(1):129–140. doi: 10.1177/1359105306058868. [DOI] [PubMed] [Google Scholar]
  38. Shin HS, Han HR, Kim MT. Predictors of psychological well-being amongst Korean immigrants to the United States: A structured interview survey. International Journal of Nursing Studies. 2007;44:415–426. doi: 10.1016/j.ijnurstu.2006.04.007. [DOI] [PubMed] [Google Scholar]
  39. Siegel D, Lopez J, Meier J. Antihypertensive medication adherence in the Department of Veterans Affairs. American Journal of Medicine. 2007;120(1):26–32. doi: 10.1016/j.amjmed.2006.06.028. [DOI] [PubMed] [Google Scholar]
  40. Stevens VJ, Obarzanek E, Cook NR, Lee IM, Appel LJ, Smith West D, Cohen J. Long-term weight loss and changes in blood pressure: Results of the Trials of Hypertension Prevention, phase II. Annals of Internal Medicine. 2001;134(1):1–11. doi: 10.7326/0003-4819-134-1-200101020-00007. [DOI] [PubMed] [Google Scholar]
  41. Strine TW, Kroenke K, Dhingra S, Balluz LS, Gonzalez O, Berry JT, Mokdad AH. The associations between depression, health-related quality of life, social support, life satisfaction, and disability in community-dwelling US adults. Journal of Nervous and Mental Disease. 2009;197(1):61–64. doi: 10.1097/NMD.0b013e3181924ad8. [DOI] [PubMed] [Google Scholar]
  42. Tang TS, Brown MB, Funnell MM, Anderson RM. Social support, quality of life, and self-care behaviors among African Americans with type 2 diabetes. Diabetes Educator. 2008;34:266–276. doi: 10.1177/0145721708315680. [DOI] [PubMed] [Google Scholar]
  43. Trevisol DJ, Moreira LB, Kerkhoff A, Fuchs SC, Fuchs FD. Health-related quality of life and hypertension: A systematic review and meta-analysis of observational studies. Journal of Hypertension. 2011;29(2):179–188. doi: 10.1097/HJH.0b013e328340d76f. [DOI] [PubMed] [Google Scholar]
  44. U.S. Census Bureau. 2007–2009 American Community Survey 3-Year Estimates. 2009 Retrieved from http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ACS&_submenuId=&_lang=en&_ts=
  45. Ucan O, Ovayolu N. Relationship between diabetes mellitus, hypertension and obesity, and health-related quality of life in Gaziantep, a central south-eastern city in Turkey. Journal of Clinical Nursing. 2010;19(17–18):2511–2519. doi: 10.1111/j.1365-2702.2010.03295.x. [DOI] [PubMed] [Google Scholar]
  46. Weinert C. A social support measure: PRQ 85. Nursing Research. 1987;36:273–277. [PubMed] [Google Scholar]
  47. Wilson IB, Cleary PD. Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. Journal of the American Medical Association. 1995;273(1):59–65. [PubMed] [Google Scholar]

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