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HOME > J Prev Med Public Health > Volume 53(6); 2020 > Article
Original Article
Effects of Income Level on the Association Between Hypertension and Depression: 2010-2017 Korea National Health and Nutrition Examination Survey
San Kangorcid, Hyeon Chang Kimorcid
Journal of Preventive Medicine and Public Health 2020;53(6):439-446.
DOI: https://doi.org/10.3961/jpmph.20.337
Published online: October 8, 2020
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Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea

Corresponding author: Hyeon Chang Kim, MD, PhD Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea E-mail: hckim@yuhs.ac
• Received: July 17, 2020   • Revised: September 16, 2020   • Accepted: September 18, 2020

Copyright © 2020 The Korean Society for Preventive Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Objectives
    This study analyzed the associations of hypertension (HTN) with symptoms and diagnosis of depression by income level among Korean adults.
  • Methods
    This study was based on the 2010-2017 Korea National Health and Nutrition Examination Survey data; a total of 29 425 adults (aged 20 years or older) were analyzed. HTN was defined as a systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or use of hypertensive medications. Depression symptoms were evaluated based on a questionnaire about depression-related symptoms. A depression diagnosis was defined based on questionnaire responses indicating that a participant had been diagnosed with depression. Household income was divided into higher or lower income ranges based on the median income of the participants. Multiple logistic regression analyses were performed to assess the associations between HTN and depression symptoms/diagnosis in the higher-income and lower-income groups.
  • Results
    In the higher-income group, the odds ratio (OR) for the association between HTN and depression symptoms was 1.15 (95% confidence interval [CI], 0.97 to 1.37), and the OR for the association between HTN and depression diagnosis was 1.41 (95% CI, 1.13 to 1.76). In the lower-income group, the OR for the association between HTN and depression symptoms was 1.18 (95% CI, 1.04 to 1.34), whereas the OR for the association between HTN and depression diagnosis was 0.82 (95% CI, 0.70 to 0.97).
  • Conclusions
    The associations of HTN with symptoms and diagnosis of depression differed by income level.
The global prevalence of hypertension (HTN) in 2010 was 31.1%, corresponding to approximately 1.39 billion people with HTN [1]. A study using the Korea National Health and Nutrition Examination Survey (KNHANES) between 2010 and 2014 reported that the lifetime prevalence of HTN in Koreans was 34.6% in male and 30.8% in female [2]. The World Health Organization reported that the prevalence of depression worldwide was 4.4% in 2015 [3]. According to a study published in 2017, the point prevalence of depression in Korea was 6.7% [4].
Recently, many studies have sought to explain the connection between physical and mental diseases. Cardiovascular disease was reported to be associated with severe mental illness [5]. A study using Australia’s National Survey of Mental Health and Wellbeing reported that patients with chronic conditions such as diabetes, asthma, coronary artery disease, stroke, cancer, and arthritis had a higher prevalence of affective or anxiety disorders than those who did not. Previous studies have found significant associations between HTN and depression [6-8].
Associations between socioeconomic factors and various diseases have also been reported in many studies [9-11]. A higher risk of HTN in the lower socioeconomic class was found; this association was especially remarkable among female [12]. An analysis of the association between socioeconomic status (SES) and HTN was also conducted in the Korean population, and it was found that female with a lower household income had a higher incidence of HTN [13]. In addition, previous studies have reported associations between SES and depression [14]. One study found a higher incidence of major depressive episodes in people with a lower household or individual income [15]. Although there is a significant association between HTN and depression, the association between these 2 diseases by income level has not been analyzed.
Persons with low SES may under-report their health problems [16]. In addition, depression under-reporting can be assessed by comparing the number of patients with symptoms of depression to those who have been diagnosed with depression [17]. This study investigated whether there was a difference in the association between HTN and depression based on income level, and whether the difference was consistent for both depression-related variables (symptoms and diagnosis).
Study Population
Our study used KNHANES data from 2010 to 2017. The KNHANES is a national program for assessing the health status of the Korean population. The KNHANES uses a complex, multi-stage probability sample design, which represents the total Korean population excluding institutionalized persons [18]. In the analysis of the association between HTN and depression symptoms/depression diagnosis, 13 954 participants under 20 years old, 2297 participants who did not have blood pressure (BP) measurements, 811 non-responders to the question on depression symptoms, and 14 923 non-responders to the questions on depression diagnosis were excluded from the total of 61 410 participants; the remaining 29 425 participants were analyzed.
Measurements
HTN was defined as systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg based on the BP measurements or the use of an antihypertensive medication. Three measurements were made, and the second and the third measurements were averaged to determine BP.
In this study, a questionnaire related to depression was selected from the EuroQol- 5 dimension (EQ-5D), a measure of the quality of life, as an indicator of depression symptoms. The questionnaire measures health on the day of the survey and can be answered in three ways: “I am not anxious or depressed,” “I am somewhat anxious or depressed,” and “I am very anxious or depressed.” This questionnaire asked about both depression and anxiety. However, a previous study reported that patients with depression were more likely to report problems on this questionnaire than those with anxiety [19]. In this study, participants responding “I am somewhat anxious or depressed” and “I am very anxious or depressed” were classified as having depression. Information on participants’ history of physician-diagnosed depression was obtained from a questionnaire that asked whether a participant has been diagnosed with depression in the past.
Covariables included age, body mass index (BMI), household income, occupation, smoking, alcohol drinking, weekly walking days, and diabetes diagnosis. Because the prevalence of HTN increases with age, an age-adjusted analysis was performed. Participants were stratified by age into 3 groups: 20-39 years, 40-59 years, and ≥60 years. BMI was calculated as weight divided by height squared. The stratification criteria for BMI were as follows: <20.0 kg/m2, 20.0-<25.0 kg/m2, and ≥25.0 kg/m2. Household income was divided into higher or lower based on the median income of the study participants. Participants were classified by occupation into three categories: white collar employment, blue collar employment, and unemployed. Smoking was categorized based on lifetime experience (yes or no). People who reported having smoked fewer than 100 cigarettes were regarded as never smokers. Alcohol drinkers were defined as people who reported drinking alcohol at least once a month in the last 1 year. As an assessment of physical activity, weekly walking days were quantified as the number of days that a person walked for at least 10 minutes at a time, and were classified into 0-1 d/wk, 2-3 d/wk, 4-5 d/wk, and 6-7 d/wk.
Statistical Analysis
The distribution of HTN and covariables according to the presence or absence of depression symptoms and depression diagnosis was assessed. Before carrying out the regression analysis, the variance inflation factor was calculated to test the multicollinearity of independent variables, and there was no multicollinearity in the model used in this study. The association between HTN and depression symptoms or diagnosis was assessed through multiple logistic regression analyses. The analyses were performed by assigning weights considering the complex sampling design. Male and female were separately analyzed because differences according to sex were found in previous studies of the association between HTN and depression [20,21]. SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA) was used for all analyses in this study.
Ethics Statement
The study protocol was approved by the Institutional Review Board of the Yonsei University College of Medicine (approval No. Y-2020-0102).
Among the participants with depression symptoms, 34.6% had HTN, while 25.7% of those without depression symptoms had HTN. Among those who were diagnosed with depression, 30.6% had HTN, while HTN was present in 26.5% of those without a depression diagnosis. Among the participants with depression symptoms, 40.9% were in the higher-income group and 59.1% were in the lower-income group. Among those who were diagnosed with depression, 44.6% were in the higher-income group and 55.4% were in the lower-income group (Table 1).
Table 2 shows the distribution of depression symptoms and diagnoses according to the characteristics of HTN and covariables before dividing the population by income level; in addition, it also shows the results of the regression analysis between HTN and depression. Among the participants with HTN, 15.0% had depression symptoms and 6.9% had a depression diagnosis. In male, 8.1% had depression symptoms and 3.4% had a depression diagnosis. In female, 14.7% had depression symptoms and 8.3% had a depression diagnosis. In the lower-income group, 16.9% had depression symptoms and 8.1% had a depression diagnosis. In the higher-income group, 8.0% had depression symptoms and 4.5% had a depression diagnosis. Before adjusting for the covariables, the odds ratio (OR) for the association between HTN and depression symptoms was 1.53 (95% confidence interval [CI], 1.41 to 1.67), and the OR for the association between HTN and depression diagnosis was 1.23 (95% CI, 1.09 to 1.38). After adjusting for the covariables, the OR for the association between HTN and depression symptoms was 1.18 (95% CI, 1.07 to 1.30), and the OR for the association between HTN and depression diagnosis was 1.02 (95% CI, 0.89 to 1.17).
Table 3 shows the associations of depression symptoms and depression diagnoses with HTN after dividing the study population based on household income. The OR for the association between HTN and depression symptoms was 1.15 (95% CI, 0.97 to 1.37) in the higher-income group, and 1.18 (95% CI, 1.04 to 1.34) in the lower-income group. The OR for the association between HTN and depression diagnosis was 1.41 (95% CI, 1.13 to 1.76) in the higher income group and 0.82 (95% CI: 0.70 to 0.97) in the lower income group. HTN was positively associated with depression symptoms, regardless of income level, although the strength of the association varied in the total, male, and female population. However, the association between HTN and depression diagnosis showed opposite directions according to income level. The two conditions were positively associated in the higher-income group, but inversely associated in the lower-income group. When the study group was stratified by educational level, statistically non-significant but similar results were obtained (Supplemental Material 1). The associations of other covariables with depression symptoms and depression diagnosis by income level are also presented in the Supplemental Materials 1-6.
In this study of nationally representative data, a positive association was found between HTN and depression symptoms in both the higher-income and lower-income groups. However, HTN and depression diagnosis showed a positive association in the higher-income group, but an inverse association in the lower-income group.
Previous studies on the association between HTN and depression, or on the influence of SES on these two diseases, were the basis for this study. A cohort study reported that the incidence of HTN was significantly higher in people with depression or anxiety [22]. The risk of depression was also shown to be higher in people with treated HTN. A cross-sectional study that analyzed elderly individuals showed a positive association between HTN and clinically significant symptoms of depression [6]. Another previous study reported that the effects of the sympathetic nervous system might be the cause of the positive association between HTN and depression [23]. A study conducted in the United States and Japan reported a higher risk of depression symptoms in groups with lower household income [24]. In addition, a previous study reported that the risk of a depression diagnosis was higher in groups with relatively few financial assets [25].
Although previous studies focused on the overall association between HTN and depression, this study analyzed the association by categorizing depression into symptoms and diagnosis. In addition, this study divided the population by income level, and found that the association between HTN and depression in the higher-income group was consistently positive, while conflicting relationships were found in the lower-income group.
It is thought that the different relationships found in this study between HTN and depression symptoms or diagnosis reflect a relatively low prevalence of depression diagnoses in the lower-income group. Based on the results of previous studies that reported a positive association between HTN and depression, the prevalence of depression diagnoses in the higher-income group may be at an appropriate level.
There may be two reasons for the lower prevalence of depression diagnoses in the lower-income group. One reason may that the lower-income group may lack of awareness of depression, thereby reducing the detection rate of depression and, as a result, lowering the prevalence of depression diagnoses. A previous study reported a lack of knowledge concerning symptoms of depression in individuals with a low SES [26]. Second, the lower-income group may have less access to healthcare than the higher-income group. A meta-analysis reported that low SES was associated with poor access to healthcare services [27]. A study concerning major depression reported that major depression disorder tended to be underdiagnosed in racial minorities as compared to whites [28]. In our study, an inverse association between HTN and depression was found in the lower-income group due to the relatively low detection rate of depression in that group.
Low-income individuals with HTN may be less likely to seek out medical care than high-income individuals. For patients with a physical disease such as HTN, prevention of depression is especially crucial.
A limitation of this study is recall bias, which may have affected the self-reported history of a depression diagnosis. Another potential limitation is residual confounding, although we adjusted for several factors that could affect the association between HTN and depression, such as biological characteristics, socioeconomic characteristics, health behavior, and comorbidity history. This study is also a cross-sectional analysis, and it was therefore not possible to assess the sequential association between major variables. In this study, depression symptoms were measured using 1 of the 5 questionnaires of the EQ-5D, a tool for measuring quality of life; further studies could be done using other tools for assessing depression.
HTN and depression are significantly associated with each other, and socioeconomic factors are also closely related to the two diseases [14,29]. In light of the results of this study, it is necessary to carefully evaluate depression in patients with HTN, especially in low-income persons; and policies related to improving medical access are needed for these patients.
Supplemental materials are available at https://doi.org/10.3961/jpmph.20.337.
Supplemental Material 1.
Association of hypertension with depression symptoms and diagnosis by educational level
jpmph-20-337-suppl1.docx
Supplemental Material 2.
Factors associated with depression symptoms by income: total
jpmph-20-337-suppl2.docx
Supplemental Material 3.
Factors associated with depression diagnosis by income: total
jpmph-20-337-suppl3.docx
Supplemental Material 4.
Factors associated with depression symptoms by income: male
jpmph-20-337-suppl4.docx
Supplemental Material 5.
Factors associated with depression diagnosis by income: male
jpmph-20-337-suppl5.docx
Supplemental Material 6.
Factors associated with depression symptom by income: female
jpmph-20-337-suppl6.docx
Supplemental Material 7.
Factors associated with depression diagnosis by income: female
jpmph-20-337-suppl7.docx

CONFLICT OF INTEREST

The authors have no conflicts of interest associated with the material presented in this paper.

FUNDING

None.

None.

AUTHOR CONTRIBUTIONS

Conceptualization: SK. Data curation: SK. Formal analysis: SK. Funding acquisition: None. Methodology: SK. Project administration: HCK. Visualization: HCK. Writing – original draft: SK. Writing – review & editing: HCK.

Table 1.
Distribution of individual characteristics in the study population
Characteristics Depression symptoms
Depression diagnosis
Yes (n = 3874) No (n = 25 551) p-value Yes (n = 1996) No (n = 27 429) p-value
Hypertension diagnosis
 No 2281 (65.4) 17 676 (74.3) <0.001 1247 (69.4) 18 710 (73.5) <0.001
 Yes 1593 (34.6) 7875 (25.7) 749 (30.6) 8719 (26.5)
Sex
 Male 1092 (33.0) 10 867 (49.1) <0.001 417 (26.6) 11 542 (48.5) <0.001
 Female 2782 (67.0) 14 684 (50.9) 1579 (73.4) 15 887 (51.5)
Age (y)
 20-39 730 (27.8) 7214 (36.8) <0.001 365 (27.5) 7579 (36.3) <0.001
 40-59 1197 (36.5) 9952 (41.6) 725 (42.4) 10 424 (40.9)
 ≥60 1947 (35.7) 8385 (21.6) 906 (30.1) 9426 (22.8)
Body mass index (kg/m2)
 <20.0 551 (15.2) 3116 (12.9) 0.003 233 (12.9) 3434 (13.2) 0.184
 20.0-<25.0 1990 (51.2) 13 920 (53.8) 1055 (51.4) 14 855 (53.6)
 ≥25.0 1333 (33.6) 8515 (33.3) 708 (35.7) 9140 (33.2)
Household income
 Low 2477 (59.1) 10 834 (38.2) <0.001 1153 (55.4) 12 158 (39.7) <0.001
 High 1377 (40.9) 14 613 (61.8) 827 (44.6) 15 163 (60.3)
Occupation
 White collar 780 (24.7) 9285 (40.8) <0.001 386 (24.4) 9679 (39.9) <0.001
 Blue collar 785 (19.9) 6088 (23.8) 398 (20.3) 6475 (23.5)
 Unemployed 2285 (55.4) 10 077 (35.4) 1208 (55.3) 11 154 (36.6)
Smoking
 No 2619 (65.2) 16 045 (59.5) <0.001 1432 (65.5) 17 232 (59.8) <0.001
 Yes 1210 (34.8) 9332 (40.5) 548 (34.5) 9994 (40.2)
Alcohol drinking
 No 2193 (51.2) 11 809 (41.3) <0.001 1242 (55.3) 12 760 (41.6) <0.001
 Yes 1640 (48.8) 13 576 (58.7) 738 (44.7) 14 478 (58.4)
Weekly walking days (d/wk)
 0-1 1240 (29.8) 6243 (23.2) <0.001 569 (27.4) 6914 (23.7) 0.003
 2-3 877 (23.3) 5885 (23.0) 471 (23.9) 6291 (23.0)
 4-5 640 (16.9) 4785 (19.1) 316 (16.3) 5109 (19.0)
 6-7 1091 (30.0) 8531 (34.7) 627 (32.4) 8995 (34.3)
Diabetes diagnosis
 No 3350 (88.9) 23 260 (93.0) <0.001 1752 (90.2) 24 858 (92.7) <0.001
 Yes 524 (11.1) 2291 (7.0) 244 (9.8) 2571 (7.3)

Values are presented as number (%).

Table 2.
Factors associated with depression symptoms and diagnosis
Variables Total (n) Depression symptoms
Depression diagnosis
n (%) Unadjusted OR (95% CI) Adjusted OR (95% CI) n (%) Unadjusted OR (95% CI) Adjusted OR (95% CI)
Hypertension diagnosis
 No 19 957 2281 (10.4) 1.00 (reference) 1.00 (reference) 1247 (5.7) 1.00 (reference) 1.00 (reference)
 Yes 9468 1593 (15.0) 1.53 (1.41, 1.67) 1.18 (1.07, 1.30) 749 (6.9) 1.23 (1.09, 1.38) 1.02 (0.89, 1.17)
Sex
 Male 11 959 1092 (8.1) 1.00 (reference) 1.00 (reference) 417 (3.4) 1.00 (reference) 1.00 (reference)
 Female 17 466 2782 (14.7) 1.96 (1.80, 2.15) 2.01 (1.74, 2.31) 1579 (8.3) 2.61 (2.28, 2.98) 3.34 (2.71, 4.11)
Age (y)
 20-39 7944 730 (9.0) 1.00 (reference) 1.00 (reference) 365 (4.6) 1.00 (reference) 1.00 (reference)
 40-59 11 149 1197 (10.3) 1.17 (1.04, 1.30) 1.14 (1.01, 1.28) 725 (6.2) 1.38 (1.20, 1.60) 1.30 (1.12, 1.52)
 ≥60 10 332 1947 (17.8) 2.19 (1.97, 2.43) 1.31 (1.15, 1.50) 906 (7.8) 1.75 (1.51, 2.03) 1.07 (0.89, 1.28)
Body mass index (kg/m2)
 <20.0 3667 551 (13.4) 1.23 (1.09, 1.39) 1.22 (1.07, 1.38) 233 (5.9) 1.02 (0.85, 1.21) 0.92 (0.77, 1.09)
 20.0-<25.0 15 910 1990 (11.1) 1.00 (reference) 1.00 (reference) 1055 (5.8) 1.00 (reference) 1.00 (reference)
 ≥25.0 9848 1333 (11.7) 1.06 (0.97, 1.16) 1.03 (0.94, 1.14) 708 (6.4) 1.13 (1.00, 1.27) 1.15 (1.01, 1.30)
Household income
 Low 13 311 2477 (16.9) 2.33 (2.14, 2.54) 1.81 (1.65, 1.98) 1153 (8.1) 1.89 (1.68, 2.12) 1.51 (1.33, 1.73)
 High 15 990 1377 (8.0) 1.00 (reference) 1.00 (reference) 827 (4.5) 1.00 (reference) 1.00 (reference)
Occupation
 White collar 10 065 780 (7.4) 1.00 (reference) 1.00 (reference) 386 (3.8) 1.00 (reference) 1.00 (reference)
 Blue collar 6873 785 (9.9) 1.38 (1.22, 1.57) 1.15 (1.01, 1.32) 398 (5.2) 1.43 (1.20, 1.69) 1.37 (1.15, 1.65)
 Unemployed 12 362 2285 (17.0) 2.58 (2.32, 2.86) 1.81 (1.60, 2.03) 1208 (8.8) 2.49 (2.17, 2.86) 1.89 (1.63, 2.20)
Smoking
 No 18 664 2619 (12.5) 1.00 (reference) 1.00 (reference) 1432 (6.5) 1.00 (reference) 1.00 (reference)
 Yes 10 542 1210 (10.1) 0.78 (0.72, 0.86) 1.32 (1.15, 1.51) 548 (5.2) 0.78 (0.69, 0.88) 1.89 (1.57, 2.27)
Alcohol drinking
 No 14 002 2193 (14.0) 1.00 (reference) 1.00 (reference) 1242 (7.8) 1.00 (reference) 1.00 (reference)
 Yes 15 216 1640 (9.8) 0.78 (0.72, 0.86) 1.01 (0.92, 1.11) 738 (4.6) 0.58 (0.52, 0.64) 0.81 (0.71, 0.91)
Weekly walking days (d/wk)
 0-1 7483 1240 (14.4) 1.49 (1.33, 1.66) 1.36 (1.21, 1.53) 569 (6.9) 1.22 (1.05, 1.41) 1.08 (0.93, 1.26)
 2-3 6762 877 (11.7) 1.17 (1.04, 1.32) 1.13 (1.00, 1.28) 471 (6.2) 1.10 (0.94, 1.27) 1.02 (0.87, 1.19)
 4-5 5425 640 (10.4) 1.02 (0.90, 1.15) 1.01 (0.89, 1.15) 316 (5.2) 0.91 (0.77, 1.07) 0.88 (0.74, 1.03)
 6-7 9622 1091 (10.2) 1.00 (reference) 1.00 (reference) 627 (5.7) 1.00 (reference) 1.00 (reference)
Diabetes diagnosis
 No 26 610 3350 (11.2) 1.00 (reference) 1.00 (reference) 1752 (5.9) 1.00 (reference) 1.00 (reference)
 Yes 2815 524 (17.2) 1.65 (1.46, 1.86) 1.14 (1.00, 1.30) 244 (7.9) 1.39 (1.18, 1.64) 1.08 (0.90, 1.30)

OR, odds ratio; CI, confidence interval.

Table 3.
Association of HTN with depression symptoms and diagnosis by income level
Variables Higher-income
Lower-income
Total (n) Depression symptoms
Depression diagnosis
Total (n) Depression symptoms
Depression diagnosis
n (%) OR (95% CI) n (%) OR (95% CI) n (%) OR (95% CI) n (%) OR (95% CI)
Total
No HTN 12 234 1014 (8.3) 1.00 (reference) 580 (4.7) 1.00 (reference) 7797 1277 (16.4) 1.00 (reference) 675 (8.7) 1.00 (reference)
HTN 3880 383 (9.9) 1.15 (0.97, 1.37) 263 (6.8) 1.41 (1.13, 1.76) 5638 1220 (21.6) 1.18 (1.04, 1.34) 494 (8.8) 0.82 (0.70, 0.97)
Male
No HTN 4747 262 (5.5) 1.00 (reference) 112 (2.3) 1.00 (reference) 2946 348 (11.8) 1.00 (reference) 149 (5.1) 1.00 (reference)
HTN 2091 128 (6.1) 1.01 (0.75, 1.37) 61 (2.9) 1.13 (0.74, 1.72) 2222 360 (16.2) 1.48 (1.17, 1.87) 99 (4.5) 0.80 (0.55, 1.15)
Female
No HTN 7487 752 (10.0) 1.00 (reference) 468 (6.3) 1.00 (reference) 4851 929 (19.2) 1.00 (reference) 526 (10.8) 1.00 (reference)
HTN 1789 255 (14.3) 1.27 (1.03, 1.58) 202 (11.3) 1.59 (1.22, 2.07) 3416 860 (25.2) 1.03 (0.89, 1.20) 395 (11.6) 0.82 (0.68, 0.99)

All covariables (sex, age, body mass index, occupation, smoking, alcohol drinking, weekly walking days, diabetes diagnosis) are adjusted.

HTN, hypertension; OR, odds ratio; CI, confidence interval.

  • 1. Mills KT, Bundy JD, Kelly TN, Reed JE, Kearney PM, Reynolds K, et al. Global disparities of hypertension prevalence and control: a systematic analysis of population-based studies from 90 countries. Circulation 2016;134(6):441-450.ArticlePubMedPMC
  • 2. Choi HM, Kim HC, Kang DR. Sex differences in hypertension prevalence and control: analysis of the 2010-2014 Korea National Health and Nutrition Examination Survey. PLoS One 2017;12(5):e0178334.ArticlePubMedPMC
  • 3. World Health Organization. Depression and other common mental disorders: global health estimates. 2017 [cited 2020 Jul 1]. Available from: https://www.who.int/mental_health/management/depression/prevalence_global_health_estimates/en/.
  • 4. Shin C, Kim Y, Park S, Yoon S, Ko YH, Kim YK, et al. Prevalence and associated factors of depression in general population of Korea: results from the Korea National Health and Nutrition Examination Survey, 2014. J Korean Med Sci 2017;32(11):1861-1869.ArticlePubMedPMC
  • 5. DE Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen D, Asai I, et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 2011;10(1):52-77.ArticlePubMedPMC
  • 6. Maatouk I, Herzog W, Böhlen F, Quinzler R, Löwe B, Saum KU, et al. Association of hypertension with depression and generalized anxiety symptoms in a large population-based sample of older adults. J Hypertens 2016;34(9):1711-1720.ArticlePubMed
  • 7. Choi MN, Lee EH. Relationships of depression symptom, self-esteem, and stress to health-related quality of life in patients with hypertension registered to a community health center. J Korean Public Health Nurs 2015;29(2):165-176. (Korean).ArticlePDF
  • 8. Rubio-Guerra AF, Rodriguez-Lopez L, Vargas-Ayala G, Huerta-Ramirez S, Serna DC, Lozano-Nuevo JJ. Depression increases the risk for uncontrolled hypertension. Exp Clin Cardiol 2013;18(1):10-12.PubMedPMC
  • 9. Kanjilal S, Gregg EW, Cheng YJ, Zhang P, Nelson DE, Mensah G, et al. Socioeconomic status and trends in disparities in 4 major risk factors for cardiovascular disease among US adults, 1971-2002. Arch Intern Med 2006;166(21):2348-2355.ArticlePubMed
  • 10. Evans DA, Hebert LE, Beckett LA, Scherr PA, Albert MS, Chown MJ, et al. Education and other measures of socioeconomic status and risk of incident Alzheimer disease in a defined population of older persons. Arch Neurol 1997;54(11):1399-1405.ArticlePubMed
  • 11. Seligman HK, Schillinger D. Hunger and socioeconomic disparities in chronic disease. N Engl J Med 2010;363(1):6-9.ArticlePubMed
  • 12. Leng B, Jin Y, Li G, Chen L, Jin N. Socioeconomic status and hypertension: a meta-analysis. J Hypertens 2015;33(2):221-229.ArticlePubMed
  • 13. Baek TH, Lee HY, Lim NK, Park HY. Gender differences in the association between socioeconomic status and hypertension incidence: the Korean Genome and Epidemiology Study (KoGES). BMC Public Health 2015;15: 852.ArticlePubMedPMCPDF
  • 14. Burns JK, Tomita A, Lund C. Income inequality widens the existing income-related disparity in depression risk in post-apartheid South Africa: evidence from a nationally representative panel study. Health Place 2017;45: 10-16.ArticlePubMedPMC
  • 15. Wang JL, Schmitz N, Dewa CS. Socioeconomic status and the risk of major depression: the Canadian National Population Health Survey. J Epidemiol Community Health 2010;64(5):447-452.ArticlePubMed
  • 16. Jones RK, Kost K. Underreporting of induced and spontaneous abortion in the United States: an analysis of the 2002 National Survey of Family Growth. Stud Fam Plann 2007;38(3):187-197.ArticlePubMed
  • 17. Lyness JM, Cox C, Curry J, Conwell Y, King DA, Caine ED. Older age and the underreporting of depressive symptoms. J Am Geriatr Soc 1995;43(3):216-221.ArticlePubMed
  • 18. Kim Y. The Korea National Health and Nutrition Examination Survey (KNHANES): current status and challenges. Epidemiol Health 2014;36: e2014002.ArticlePubMedPMCPDF
  • 19. Supina AL, Johnson JA, Patten SB, Williams JV, Maxwell CJ. The usefulness of the EQ-5D in differentiating among persons with major depressive episode and anxiety. Qual Life Res 2007;16(5):749-754.ArticlePubMedPDF
  • 20. Penninx BW, Guralnik JM, Mendes de Leon CF, Pahor M, Visser M, Corti MC, et al. Cardiovascular events and mortality in newly and chronically depressed persons >70 years of age. Am J Cardiol 1998;81(8):988-994.ArticlePubMed
  • 21. Haukkala A, Konttinen H, Uutela A, Kawachi I, Laatikainen T. Gender differences in the associations between depressive symptoms, cardiovascular diseases, and all-cause mortality. Ann Epidemiol 2009;19(9):623-629.ArticlePubMed
  • 22. Jonas BS, Franks P, Ingram DD. Are symptoms of anxiety and depression risk factors for hypertension? Longitudinal evidence from the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study. Arch Fam Med 1997;6(1):43-49.ArticlePubMed
  • 23. Scalco AZ, Scalco MZ, Azul JB, Lotufo Neto F. Hypertension and depression. Clinics (Sao Paulo) 2005;60(3):241-250.ArticlePubMedPDF
  • 24. Inaba A, Thoits PA, Ueno K, Gove WR, Evenson RJ, Sloan M. Depression in the United States and Japan: gender, marital status, and SES patterns. Soc Sci Med 2005;61(11):2280-2292.ArticlePubMed
  • 25. Muntaner C, Eaton WW, Diala C, Kessler RC, Sorlie PD. Social class, assets, organizational control and the prevalence of common groups of psychiatric disorders. Soc Sci Med 1998;47(12):2043-2053.ArticlePubMed
  • 26. von dem Knesebeck O, Mnich E, Daubmann A, Wegscheider K, Angermeyer MC, Lambert M, et al. Socioeconomic status and beliefs about depression, schizophrenia and eating disorders. Soc Psychiatry Psychiatr Epidemiol 2013;48(5):775-782.ArticlePubMedPDF
  • 27. Lorant V, Deliège D, Eaton W, Robert A, Philippot P, Ansseau M. Socioeconomic inequalities in depression: a meta-analysis. Am J Epidemiol 2003;157(2):98-112.ArticlePubMedPDF
  • 28. Shao Z, Richie WD, Bailey RK. Racial and ethnic disparity in major depressive disorder. J Racial Ethn Health Disparities 2016;3(4):692-705.ArticlePubMedPDF
  • 29. Lloyd-Sherlock P, Beard J, Minicuci N, Ebrahim S, Chatterji S. Hypertension among older adults in low- and middle-income countries: prevalence, awareness and control. Int J Epidemiol 2014;43(1):116-128.ArticlePubMedPMCPDF

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