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Son, Heo, Hyun, and Kwak: Effects of Marital Status and Income on Hypertension: The Korean Genome and Epidemiology Study (KoGES)

ABSTRACT

Objectives:

This study aimed to analyze the associations of income, marital status, and health behaviors with hypertension in male and female over 40 years of age in the Korea.

Methods:

The data were derived from the Korean Genome and Epidemiology Study (KoGES; 4851-302) which included 211 576 participants. To analyze the relationships of income, marital status, and health behaviors with hypertension in male and female over 40 years of age, multiple logistic regression was conducted with adjustments for these variables.

Results:

The prevalence of hypertension increased linearly as income decreased. The odds ratio for developing hypertension in people with an income of <0.5 million Korean won (KRW) compared to ≥6.0 million KRW was 1.55 (95% confidence interval [CI], 1.25 to 1.93) in the total population, 1.58 (95% CI, 1.27 to 1.98) in male, and 1.07 (95% CI, 0.35 to 3.28) in female. The combined effect of income level and marital status on hypertension was significant. According to income level and marital status, in male, low income and divorce were most associated with hypertension (1.76 times; 95% CI, 1.01 to 3.08). However, in female, the low-income, married group was most associated with hypertension (1.83 times; 95% CI, 1.71 to 1.97).

Conclusions:

The results of this study show that it is necessary to approach male and female marital status separately according to income in health policies to address inequalities in the prevalence of hypertension.

INTRODUCTION

Hypertension is a major risk factor for non-communicable diseases, such as cardiovascular diseases, diabetes, and chronic kidney disease [1]. The prevalence of hypertension increased from 24.5% in 2007 in Korea to 27.2% in 2019 [2], and the rate pISSN 1975-8375 eISSN 2233-4521 of hypertension control is below 50%, indicating the need to manage hypertension risk factors in Korea [3].
Socioeconomic status (SES) is associated with a high prevalence of hypertension [4]. Demographic factors (e.g., age or sex), socioeconomic factors (e.g., income, marital status, education, etc.), and health behavior factors (smoking, drinking, body mass index [BMI], etc.) are well-known risk factors associated with hypertension [5]. Marital status was an important risk factor for hypertension in previous studies, and the results of studies on the relationship between marital status and hypertension were not consistent [6-9]. In studies such as that of Defianna et al. [5], socioeconomic factors and sex differences in marital status were observed to affect hypertension risk.
Many international studies have reported relationships be tween hypertension control and socioeconomic levels, but there are few studies related to hypertension control in Korea, and those studies are limited to research on mortality according to some socioeconomic levels [10]. A previous study found that marital status was not associated with hypertension control [10]. However, the results of Lim [10] were different from those of previous studies [11,12]. The results of previous studies showed that hypertension control was high in married subjects—that is, those living with a spouse [11] regardless of race and age. Shah and Cook [12] reported that people living alone did not have well-controlled hypertension. In some Korean studies, income was associated with all causes of hypertension, increases in cardiovascular mortality and cardiovascular events [13], as well as hypertension diagnoses [14].
Although income was reported to have a large effect on hypertension [13,15-20], few Korean studies have investigated the effect of marriage on hypertension, especially the correlation between marriage and income, have been reported. We need to figure out how the interactions of socio-political issues such as income and marriage affect hypertension. It is also necessary to consider marital status by subdividing it into groups of married, unmarried, separated, divorced, and those with deceased spouses. The purpose of this study was to investigate how the income, marital status, and health behavior factors of male and female over 40 years of age were correlated.
The hypotheses of this study were: (1) the prevalence rate of hypertension is associated with demographic characteristics, income, marital status, and health behaviors, and (2) marital status and income level affect the prevalence of hypertension more than health behavior risk factors.

METHODS

Research Materials and Targets

The data in this study were obtained from the Korean Genome and Epidemiology Study (KoGES; 4851-302), National Institute of Health, Korea Disease Control and Prevention Agency, Korea. The population-based cohorts in the KoGES, including the KoGES Ansan and Ansung study, the KoGES Health Examinee Study, and the KoGES Cardiovascular Disease Association Study, consisted of community-dwellers and male and female participants, aged ≥40 years at baseline recruited from the national health examinee registry. The purpose of the KoGES survey data was to identify lifestyle, diet, and environmental factors in people between the ages of 40 and 69 with chronic diseases in rural and medium sized city populations.
A total of 211 576 participants were collected by the KoGES as the general cohort between 2001 and 2013. Finally, 210 413 were included in this study, excluding 1163 who did not respond to information from demographic characteristics, income, marital status, and health behavior factors.

Hypertension

The definition of hypertension in this study was a measured systolic blood pressure of over 140 mmHg or diastolic blood pressure of 90 mmHg, or when the participant was diagnosed with hypertension by a physician.

Demographic characteristics

The demographic characteristics included sex (male and female) and age (40-44, 45-49, 50-54, 55-59, 60-64 years, and over).

Income level

The income level was investigated as the average monthly income of the family, and was divided into <0.500 million Korean won (KRW), 0.500-0.999 million KRW, <1.000-1.499 million KRW, 1.500-1.999 million KRW, 2.000-2.999 million KRW, 3.000-3.999 million KRW, and ≥6.000 million KRW.

Marital status

The current marital status was categorized by the response to the question “What is your current marital status?” Participants were divided into married, unmarried, separated, divorced, deceased spouse, and other groups.

Health behavior factors

The health behaviors were smoking, drinking, and BMI. Smoking was investigated through the question “Have you ever smoked?” The responses were divided into “no,” “yes (past smoker),” and “yes (current smoker).” Pack-years were classified as 1-9, 10-19, 20-39, 40-59, and 60 or more.” Drinking was investigated through the question “Haven’t you ever consumed alcohol?” The responses were divided into “yes” or “no (past drinking),” and “no (current drinking)”. Total alcohol consumption (g/day) was obtained by the consumption of alcoholic beverages including makgeolli, beer, jeongjong (cheongju), wine, soju, and liquor. The density of ethanol is 0.7893 g/mL, and the alcohol concentration (%) was 6% in Juru makgeolli, 4.5% in beer, 15% in jeongjong (cheongju), 13% in wine, 22% in soju, and 40% in liquor. The alcohol intake was calculated according to the following formula: drinking frequency×one drink×alcohol content (g/drink). The total alcohol intake was classified as 0.05-0.09, 1.00-9.99, 10.00-19.99, and 20.00-29.99 g/day, or more. BMI is a statistical index that uses a person’s weight and height to provide an estimate of body fat and is a value obtained by dividing a person’s weight (kg) by his or her height (m2). A BMI of <18.5 kg/m2 was considered underweight, normal was 18.5-22.9 kg/m2, pre-obese was 23.0-24.9 kg/m2, and stage 1 obesity was 25.0-29.9 kg/m2. Stage 2 obesity was classified as a BMI of 30.0-34.9 kg/m2, and stage 3 obesity was classified as over 35.0 kg/m2 [21].

Statistical Analysis

The prevalence of hypertension was analyzed according to the demographic characteristics, income levels, marital status, and health behavior factors of the study population. Logistic regression was used to analyze the effects of income level, marital status, and health behaviors on hypertension among male and female, adjusting for age, health behavior (smoking, alcohol, and BMI), and nutrition, and the odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Trend analysis using the likelihood ratio test was conducted in relation to the relationship between demographic characteristics and income level, marital status, and health behaviors of patients with hypertension. All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA).

Ethics Statement

This study was approved by the Kangwon National University Institutional Review Board (approval No. KWNUIRB-2021-02-002) and performed in accordance with the principles of the Declaration of Helsinki.

RESULTS

The Prevalence of Hypertension According to Demographic Characteristics, Income Level, Marital Status, and Health Behavior Factors

The prevalence of hypertension was 19.28% in the total study population, 16.74% in female and 23.94% in male. Older people showed a higher prevalence of hypertension, with the highest at 29.78% for those aged 65 years or older.
Lower income levels were associated with a higher prevalence of hypertension. The prevalence of hypertension was 12.51% for those with an income of over 6.0 million KRW, while it was 29.67% for those with an income below 0.5 million KRW (male, 18.37% and 32.14%; female, 8.14% and 28.66%, respectively). The prevalence of hypertension was the lowest among unmarried people at 15.04% (male, 21.58%; female, 10.80%), followed by 25.63% for those with a deceased spouse, and 19.79% for separated and 16.81% for divorced individuals (male, 28.41%, 26.92%, and 26.31%; female, 25.43%, 17.13, and 13.69%, respectively).
In terms of health behavior factors, the prevalence of hypertension was 24.40% in past smokers, 20.28% in current smokers, and 24.57% in ≥60 pack-year smokers. The prevalence was 29.12% in the ≥30.00 g/day total alcohol group and 19.26% in the stage 3 obesity group. The prevalence of hypertension was higher in male and the older age, lower-income level, deceased spouse, divorced, presently drinking, higher total alcohol intake (g/day), and stage 3 obesity groups (Table 1).

The Relationship of Demographic Characteristics and Income Levels, Marital Status, and Health Behaviors in People With Hypertension

The OR for hypertension among male was 1.98 (95% CI, 1.60 to 2.45) compared to female. The OR for developing hypertension in people with an income of <0.5 million KRW compared to ≥6.0 million KRW was 1.55 (95% CI, 1.25 to 1.93) in the total population, 1.58 (95% CI, 1.27 to 1.98) in male, and 1.07 (95% CI, 0.35 to 3.28) in female. The risk of hypertension related to marital status was higher for those who were separated, divorced, and those with deceased spouses. The risk of hypertension related to health behaviors was higher among those with past and present smoking, higher pack-years, current drinking, higher total alcohol intake (g/day), and stage 3 obesity. In further tests for trend (likelihood ratio tests), we identified trends in the association with income for male (p for trend<0.001), female (p for trend<0.001), and the total population (p for trend <0.001) (Table 2).
The OR of hypertension was 1.58 (95% CI, 1.30 to 1.96) in the total population, 1.61 (95% CI, 1.28 to 2.01) in male, and 0.93 (95% CI, 0.31 to 2.83) in female with an income of <0.5 million KRW compared to those with ≥6.0 million KRW. The effect of income on hypertension was stronger in male than female. The trends in the association with income for male (p for trend <0.001), female (p for trend<0.001), and the total population (p for trend<0.001) were also identified using Test for trend (likelihood ratio tests) (Table 3).
Regarding the relationship between marital status and hypertension, divorce showed the most strongest association, with 1.30 times (95% CI, 1.04 to 1.62) higher odds of hypertension in the total population and 1.40 times (95% CI, 1.10 to 1.79) in male. However, the marital status of female had a weaker association with hypertension than that of male. In the case of single male, there was a 1.27 times (95% CI, 1.02 to 1.57) higher likelihood of hypertension, but in female, there was no significant correlation with being single, at 0.99 times (95% CI, 0.49 to 1.97). In the association between marital status and hypertension, when a spouse died, the association with hypertension increased in the other spouse (total group: unadjusted OR, 1.48; 95% CI, 1.43 to 1.54), and this association was attenuated (OR, 1.23; 95% CI, 1.18 to 1.28) when adjusted for sex and age. The health behavior variables and nutritional variables did not significantly attenuate this association. Finally, when all sex, age, nutrition, and health behavior variables were adjusted, the OR was 1.29 (95% CI, 0.95 to 1.74). Thus, as a result of adjusting several covariates in the relationship between marital status and high blood pressure, sex and age acted more as confounding variables than the health behavior and nutrition variables (Table 4).
According to the income level and marital status in the total population, hypertension was associated with an income of ≥3.0 million KRW and having a deceased spouse (2.69 times; 95% CI, 1.13 to 6.40). Hypertension was also associated with an income of 1.0 million KRW to <3.0 million KRW and being unmarried (1.58 times; 95% CI, 1.24 to 2.02), and an income of <1.0 million KRW and being separated (4.92 times; 95% CI, 1.50 to 16.19). In male, low income and divorce were most associated with hypertension (1.76 times; 95% CI, 1.01 to 3.08). However, in female, the low-income, married group was most associated with hypertension (1.83 times; 95% CI, 1.71 to 1.97]). Further test for trend (likelihood ratio tests) showed trends in the association between income and marital status, for male (p for trend<0.001), female (p for trend<0.001), and the total population (p for trend<0.001) (Table 5).

DISCUSSION

The key result of this study is that the association between income level and marital status and hypertension was stronger in male than in female. Divorce was most influential in the overall population and for male, whereas female was less strongly affected by marriage. The association between marital status and hypertension was strongest in the lower-income group. Low-income groups showed the strongest overall impact of separation on hypertension, whereas divorce in male, and being married in female were most strongly associated with hypertension.

The Prevalence Rate of Hypertension

The countries with the lowest prevalence of hypertension in female are Switzerland (17%), Peru (18%), Canada (20%), and Taiwan and Spain (21%), whereas, for male, it is Eritrea (22%) and Peru (23%), and Bangladesh and Canada (24%) [22]. In this study, the prevalence of hypertension in female in Korea was 16.74% in female and 23.94% in male.

Income Level and Hypertension

Currently, studies on the relationship between income level and hypertension [13,19,20,23] and the relationship between marital status and hypertension [5-9] are being conducted. In this study, the risk of hypertension was found to be higher in the low-income group, and the effect was stronger in male. The relationship between average monthly income and hypertension remained statistically significant even after adjustments for sex, age, health behaviors, and nutritional factors. Similar to this study, in domestic studies, a low-income level was related to the risk of hypertension [15,16], and low SES combined with education and income level was also reported as a risk factor for hypertension [17].
In an international study, for each increase in SES, the risk of hypertension increased by 1.31 times [24]. There was no difference in hypertension between male with higher and lower economic statuses, whereas female showed a 1.6-2.6 times higher risk of hypertension than the low or middle-economic groups [18]. Female with poor SES had a 1.67 times higher risk of hypertension, unlike what was found in this study because of the more sedentary lifestyle and less physically active workers [5].
Low SES may increase sympathetic nervous system activity due to occupational and financial stress, increasing the risk of hypertension [25]. Hypertension risk factors associated with low SES include health care access and the quality of care [26], the lack of early screening and access to medicine [27,28], poor living conditions, social support, emotional stress [29], high salt consumption [30], and a diet low in vegetables [31,32]. For example, the proportion of hypertension increased with decreasing levels of individual patient wealth [19,20]. Other studies showed that the prevalence of hypertension increased with lower SES (education, occupation, and social environment) [18], as well as education and income [17].
We found that although income was a factor influencing hypertension, lower income was a more important risk factor in male. The income level was an important determinant of cardiovascular mortality in the treatment of hypertension [13], suggesting the need to establish policies suitable for health equity to prevent health inequalities in low-income groups in Korea.

Marital Status and Hypertension

Single male have a higher risk of hypertension than married male, and unmarried female have a lower risk of hypertension than married female; thus, health status differs according to marital status and sex [6]. The prevalence of hypertension was higher in married female or female who were separated, divorced or widowed than in female living together with their spouses, and the prevalence of hypertension differed according to marital status and sex [8]. Economic difficulties and low SES, as well as divorce or a deceased spouse, were important risk factors for hypertension in female [5].
The marital status that most strongly affected hypertension was divorce. No Korean studies have investigated the risk of hypertension according to marital status. However, some studies have reported results different from those in this study, finding that the risk of hypertension was 1.76 times higher [33] in unmarried and single groups and 2.34 times higher [24] in married individuals.
In this study, divorce had a strong association with high blood pressure in male. However, in female, marital status did not show a statistically significant association with hypertension. The results of this study are different from the reported effects of marital status and sex on hypertension. In a study on the effect of male marital status on hypertension, unmarried male had a high risk of hypertension [6,9]. A study on the effect of female’s marital status on hypertension found that separation, divorce, and a deceased spouse affected hypertension in female [8]. In some studies, divorced female had a higher risk of hypertension [6].

The Combined Effect of Income Level and Marital Status on Hypertension

When looking at the combined effect of income level and marital status, low income (<1.0 million KRW) and separation had the greatest impact on hypertension in the entire population, whereas low-income and divorce in male and low-income and married status in female were most associated with hypertension. Similar to our study, a previous study found a higher incidence of hypertension in male with a prior spouse than in unmarried and married male, with additional effects of employment status and educational background [7]. In an Indonesian study, female were economically highly dependent on male, and being divorced and poor were found to be important risk factors for hypertension in female, unlike our study, in which being poor and married were identified as risk factors for hypertension in female [5]. In this study, as a result of confirming the interaction effect that combines income and marital status as socioeconomic factors affecting high blood pressure, in male, lower income levels were associated with stronger the interactions between income, marital status, and hypertension. In the future, based on the results of this study, individualized intervention studies for each group with low socioeconomic factors are needed to prevent health inequality from occurring.
Metabolic risk factors such as high systolic blood pressure, high lactate dehydrogenase and cholesterol levels, and high BMI have historically been viewed as problems in high-income settings, but now a trend toward increased exposure to these metabolic risk factors is also being seen in middle-income and low-income settings [34]. Some reports have stated that health behavior factors affected hypertension [34-39], but it is necessary to understand the magnitude of the influence of health behavioral variables on the relationship between socioeconomic factors and hypertension. Singh et al. [24] suggested that female, unmarried people, young people, and highly educated people avoid all kinds of addictions, including tobacco and alcohol, which are risk factors for hypertension. SES is an important determinant of health status and the outcome of various diseases, and low SES, which contributes to chronic stress such as discrimination, crime, noise, and other risk factors affects the prevalence of health problems [40]. In our study, marriage in female and divorce in male with low-income levels were also found to be important risk factors for hypertension. Economic hardship and poor marital status may contribute to chronic stress and affect hypertension. Prior studies have reported that health behavior factors affected hypertension [34-39]. Smoking and drinking in male have been correlated with poor control of hypertension [38], and in another study, smoking [35,36], drinking, and BMI were associated with the presence of hypertension [37,39].
However, it is necessary to understand the difference between marital status and sex in how health behavior variables affect the relationship between socioeconomic factors and hypertension. Health care policies should be established that consider health equity, including socioeconomic factors such as marital status and income level. A limitation of this study is that the variables related to the prevalence of hypertension used in this study were self-reported, which may have led to under-reporting or over-reporting due to recall errors affecting the subject’s questionnaire entry process. Despite these limitations, it is meaningful that this study used long-term cohort data from a large group of ≥210 000 people for 10 years, and the risk of developing hypertension varied depending on demographic characteristics such as sex, age, income level, and marital status. In addition, this study is makes a meaningful contribution by confirming the interaction effect of combined income and marital status with socioeconomic factors affecting hypertension. In this study, ORs were calculated through various analyses to identify influencing factors such as income, marriage, and sex. In the future, it will be necessary to develop a customized intervention program according to sex with adequate consideration of income level and marital status.

DATA AVAILABILITY

Data in this study were from the Korean Genome and Epidemiology Study (KoGES; 4851-302), National Research Institute of Health, Centers for Disease Control and Prevention, Ministry for Health and Welfare, Republic of Korea.

CONFLICT OF INTEREST

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

Notes

FUNDING
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant No. HI19C1320). This study was supported by 2016 Research Grant from Kangwon National University (No. 520160280). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03035890).

ACKNOWLEDGEMENTS

We thank the Department of Genome Dynamics of the Centers for Disease Control and Prevention for providing raw data.

Notes

AUTHOR CONTRIBUTIONS
Conceptualization: Son M. Data curation: Son M. Formal analysis: Son M. Funding acquisition: Son M. Methodology: Son M, Heo YJ. Project administration: Son M. Visualization: Son M, Heo YJ. Writing – original draft: Son M, Heo YJ. Writing – review & editing: Son M, Heo YJ, Hyun HJ, Kwak HJ.

Table 1.
Prevalence of hypertension according to demographic characteristics, income level, marital status, and health behavior factors
Variables Total Hypertension Male Hypertension Female Hypertension
Total 210 413 40 575 (19.28) - - - -
Demographic characteristics
 Sex
  Female 136 008 22 761 (16.74) - - - -
  Male 74 405 17 814 (23.94) - - - -
  Total 210 413 40 575 (19.28) - - - -
 Age (y)
  40-44 36 621 3751 (10.24) 12 651 2238 (17.69) 23 970 1513 (6.31)
  45-49 36 887 5329 (14.45) 11 581 2467 (21.30) 25 306 2862 (11.31)
  50-54 42 842 7604 (17.79) 13 432 3050 (22.71) 29 310 4554 (15.54)
  55-59 35 285 7545 (21.38) 12 313 3100 (25.18) 22 972 4445 (19.35)
  60-64 30 112 7779 (25.83) 11 807 3226 (27.32) 18 305 4553 (24.87)
  ≥65 28 766 8567 (29.78) 12 621 3733 (29.58) 16 145 4834 (29.94)
  Total 210 413 40 575 (19.28) 74 405 17 814 (23.94) 136 008 22 761 (16.74)
Socioeconomic factors
 Income (1000 korean won)
  ≥6000 12 425 1554 (12.51) 5301 974 (18.37) 7124 580 (8.14)
  4000-5999 24 807 3316 (13.37) 9650 1886 (19.54) 15 157 1430 (9.43)
  3000-3999 31 034 4575 (14.74) 11 823 2417 (20.44) 19 211 2158 (11.23)
  2000-2999 36 293 6233 (17.17) 13 460 2978 (22.12) 22 833 3255 (14.26)
  1500-1999 18 996 3673 (19.34) 7006 1706 (24.35) 11 990 1967 (16.41)
  1000-1499 17 704 3940 (22.25) 6000 1653 (27.55) 11 704 2287 (19.54)
  500-999 13 486 3563 (26.42) 4205 1345 (31.99) 9281 2218 (23.90)
  <500 15 181 4504 (29.67) 4402 1415 (32.14) 10 779 3089 (28.66)
  Total 169 926 31 358 (18.45) 61 847 14 374 (23.24) 108 079 16 984 (15.71)
 Marital status
  Married 182 631 34 457 (18.87) 68 997 16 407 (23.78) 113 634 18 050 (15.88)
  unmarried 4210 633 (15.04) 1654 357 (21.58) 2556 276 (10.80)
  Separated 1243 246 (19.79) 338 91 (26.92) 905 155 (17.13)
  Divorced 5002 841 (16.81) 1239 326 (26.31) 3763 515 (13.69)
  Deceased spouse 14 135 3623 (25.63) 968 275 (28.41) 13 167 3348 (25.43)
  Others 1751 477 (27.24) 712 234 (32.87) 1039 243 (23.39)
  Total 208 972 40 277 (19.27) 73 908 17 690 (23.94) 135 064 22 587 (16.72)
Health behaviors
 Smoking
  No 150 162 27 126 (18.06) 20 381 5229 (25.66) 129 781 21 897 (16.87)
  Yes (past) 30 873 7534 (24.40) 29 079 7274 (25.01) 1794 260 (14.49)
  Yes (currently) 27 910 5660 (20.28) 24 610 5241 (21.30) 3300 419 (12.70)
  Total 208 945 40 320 (19.30) 74 070 17 744 (23.96) 134 875 22 576 (16.74)
 Total smoking amount, pack (y)
  1-9 6862 1163 (16.95) 5388 1001 (18.58) 1474 162 (10.99)
  10-19 8579 1644 (19.16) 8047 1590 (19.76) 532 54 (2.34)
  20-39 11 838 2418 (20.43) 11 570 2382 (20.59) 268 36 (13.43)
  40-59 2937 661 (22.51) 2907 655 (22.53) 30 6 (20.00)
  ≥60 993 244 (24.57) 985 241 (24.47) 8 3 (37.50)
  Total 31 209 6130 (19.64) 28 897 2869 (20.31) 2312 261 (11.29)
 Drinking
  Yes 105 870 18 923 (17.87) 15 237 3009 (19.75) 90 633 15 914 (17.56)
  No (past) 9521 2074 (21.78) 6245 1441 (23.07) 3276 633 (19.32)
  No (current) 93 717 19 339 (20.64) 52 602 13 302 (25.29) 41 115 6037 (14.68)
  Total 209 108 40 336 (19.29) 74 084 17 752 (23.96) 135 024 22 584 (16.73)
 Total alcohol intake (g/day)
  0.05-0.09 11 166 1763 (15.79) 1910 369 (19.32) 9256 1394 (15.06)
  1.00-9.99 42 317 7293 (17.23) 18 296 3944 (21.56) 24 021 3349 (13.94)
  10.00-19.99 12 362 2811 (22.74) 9122 2304 (25.26) 3240 507 (15.65)
  20.00-29.99 9379 2377 (25.34) 7951 2120 (26.66) 1428 257 (18.00)
  ≥30.00 15 085 4392 (29.12) 13 792 4136 (29.99) 1293 256 (19.80)
  Total 90 309 18 636 (20.64) 51 071 12 873 (25.21) 39 238 5763 (14.69)
 Body mass index
  Underweight 3787 370 (9.11) 1182 166 (14.04) 2605 204 (7.83)
  Normal 76 104 9693 (12.74) 21 986 3907 (17.77) 54 118 5486 (10.69)
  Pre-obese stage 57 397 10 609 (18.48) 21 584 4865 (22.54) 35 813 5744 (16.04)
  Stage 1 obesity 65 589 17 207 (26.23) 27 385 7993 (29.19) 38 204 9214 (24.12)
  Stage 2 obesity 6314 2306 (36.52) 1907 760 (39.85) 4407 1546 (35.08)
  Stage 3 obesity 447 197 (44.07) 77 34 (44.16) 370 163 (44.05)
  Total 209 638 40 382 (19.26) 74 121 17 725 (23.91) 135 517 22 657 (16.72)

Values are presented as number or number (%).

Table 2.
Relationships of demographic characteristics, income level, marital status, and health behavior factors with hypertension
Variables Hypertension patients
Male
Female
n Unadjusted Adjusted1 n Unadjusted Adjusted1 n Unadjusted Adjusted1
Total 40 575
Demographic characteristics
Sex
Female 22 761 1.00 (reference) 1.00 (reference) - - - - - -
Male 17 814 1.57 (1.53, 1.60) 1.98 (1.60, 2.45) - - - - - -
Total 40 575
Age (y)
40-44 3751 1.00 (reference) 1.00 (reference) 2238 1.00 (reference) 1.00 (reference) 1513 1.00 (reference) 1.00 (reference)
45-49 5329 1.48 (1.42, 1.55) 1.11 (0.98, 1.25) 2467 1.26 (1.18, 1.34) 1.08 (0.95, 1.23) 2862 1.89 (1.77, 2.02) 1.66 (0.93, 2.98)
50-54 7604 1.90 (1.82, 1.98) 1.20 (1.06, 1.35) 3050 1.37 (1.29, 1.45) 1.18 (1.05, 1.33) 4554 2.73 (2.57, 2.90) 1.49 (0.83, 2.67)
55-59 7545 2.38 (2.29, 2.49) 1.28 (1.13, 1.45) 3100 1.57 (1.47, 1.66) 1.28 (1.12, 1.45) 4445 3.56 (3.35, 3.79) 1.24 (0.59, 2.62)
60-64 7779 3.05 (2.93, 3.19) 1.35 (1.18, 1.55) 3226 1.75 (1.65, 1.66) 1.32 (1.15, 1.52) 4553 4.91 (4.62, 5.23) 1.97 (0.82, 4.75)
≥65 8567 3.72 (3.56, 3.88) 1.42 (1.21, 1.65) 3733 1.95 (1.84, 2.07) 1.38 (1.18, 1.61) 4834 6.34 (5.96, 6.75) 2.50 (0.85, 7.37)
Total 40 575 17 814 22 761
Socioeconomic factors
Income (unit 1000 KRW)
≥6000 1554 1.00 (reference) 1.00 (reference)2 974 1.00 (reference) 1.00 (reference)3 580 1.00 (reference) 1.00 (reference)4
4000-5999 3316 1.08 (1.01, 1.15) 1.30 (1.13, 1.50) 1886 1.08 (0.99, 1.18) 1.30 (1.13, 1.51) 1430 1.18 (1.06, 1.30) 1.24 (0.48, 3.23)
3000-3999 4575 1.21 (1.14, 1.29) 1.45 (1.26, 1.67) 2417 1.14 (1.05, 1.24) 1.46 (1.27, 1.69) 2158 1.43 (1.30, 1.57) 0.81 (0.31, 2.11)
2000-2999 6233 1.45 (1.37, 1.54) 1.49 (1.30, 1.72) 2978 1.26 (1.16, 1.37) 1.52 (1.32, 1.75) 3255 1.88 (1.71, 2.06) 0.66 (0.25, 1.70)
1500-1999 3673 1.68 (1.57, 1.79) 1.54 (1.31, 1.81) 1706 1.43 (1.31, 1.56) 1.54 (1.31, 1.82) 1967 2.21 (2.01, 2.44) 1.14 (0.43, 3.00)
1000-1499 3940 2.00 (1.88, 2.14) 1.58 (1.32, 1.89) 1653 1.69 (1.54, 1.85) 1.60 (1.33, 1.92) 2287 2.74 (2.49, 3.02) 1.09 (0.42, 2.84)
500-999 3563 2.51 (2.35, 2.68) 1.62 (1.30, 2.01) 1345 2.09 (1.90, 2.30) 1.60 (1.28, 2.01) 2218 3.54 (3.21, 3.91) 1.53 (0.54, 4.32)
<500 4504 2.95 (2.77, 3.15) 1.55 (1.25, 1.93) 1415 2.11 (1.92, 2.31) 1.58 (1.27, 1.98) 3089 4.53 (4.12, 4.98) 1.07 (0.35, 3.28)
Total 31 358 14 374 16 984
Marital status
Married 34 457 1.00 (reference) 1.00 (reference) 16 407 1.00 (reference) 1.00 (reference) 18 050 1.00 (reference) 1.00 (reference)
Unmarried 633 0.76 (0.70, 0.83) 1.11 (0.90, 1.38) 357 0.88 (0.78, 0.99) 1.14 (0.91, 1.43) 276 0.64 (0.57, 0.73) 0.94 (0.46, 1.89)
Separated 246 1.06 (0.92, 1.22) 1.35 (0.82, 2.23) 91 1.18 (0.93, 1.50) 1.23 (0.70, 2.14) 155 1.09 (0.92, 1.30) 1.63 (0.64, 4.15)
Divorced 841 0.87 (0.81, 0.94) 1.25 (0.99, 1.57) 326 1.15 (1.01, 1.30) 1.34 (1.05, 1.71) 515 0.84 (0.76, 0.92) 0.93 (0.57, 1.52)
Deceased spouse 3623 1.48 (1.43, 1.54) 1.15 (0.83, 1.59) 275 1.27 (1.11, 1.46) 1.29 (0.90, 1.86) 3348 1.81 (1.73, 1.88) 0.95 (0.54, 1.65)
Others 477 1.48 (1.43, 1.54) 1.83 (1.23, 2.72) 234 1.57 (1.34, 1.84) 1.98 (1.32, 2.97) 243 1.62 (1.40, 1.87) 0.46 (0.06, 3.54)
Total 40 277 17 690 22 587
Health behavior
Smoking
No 27 126 1.00 (reference) 1.00 (reference) 5229 1.00 (reference) 1.00 (reference) 21 897 1.00 (reference) 1.00 (reference)
Yes (past) 7534 1.46 (1.42, 1.51) 0.86 (0.81, 0.91) 7274 0.97 (0.93, 1.01) 0.89 (0.83, 0.94) 260 0.84 (0.73, 0.95) 0.60 (0.45, 0.79)
Yes (currently) 5660 1.15 (1.12, 1.19) 0.78 (0.73, 0.82) 5241 0.78 (0.75, 0.82) 0.77 (0.72, 0.82) 419 0.72 (0.65, 0.80) 0.78 (0.65, 0.92)
Total 40 320 17 744 22 576
Total smoking amount, pack (y)
1-9 1163 1.00 (reference) 1.00 (reference) 1001 1.00 (reference) 1.00 (reference) 162 1.00 (reference) 1.00 (reference)
10-19 1644 1.16 (1.07, 1.26) 1.06 (0.96, 1.18) 1590 1.08 (0.99, 1.18) 1.08 (0.97, 1.20) 54 0.92 (0.66, 1.27) 0.81 (0.54, 1.21)
20-39 2418 1.26 (1.16, 1.36) 1.03 (0.92, 1.14) 2382 1.14 (1.05, 1.23) 1.04 (0.93, 1.15) 36 1.26 (0.85, 1.85) 0.90 (0.55, 1.49)
40-59 661 1.42 (1.28, 1.58) 1.02 (0.87, 1.19) 655 1.28 (1.14, 1.42) 1.04 (0.89, 1.21) 6 2.03 (0.82, 5.03) 0.87 (0.24, 3.17)
≥60 244 1.60 (1.36, 1.87) 1.03 (0.81, 1.30) 241 1.42 (1.21, 1.67) 1.02 (0.81, 1.30) 3 4.86 (1.15, 20.53) 1.87 (0.20, 17.37)
Total 6130 2869 261
Drinking
Yes 18 923 1.00 (reference) 1.00 (reference) 3009 1.00 (reference) 1.00 (reference) 15 914 1.00 (reference) 1.00 (reference)
No (past) 2074 1.28 (1.22, 1.35) 1.16 (1.00, 1.35) 1441 1.22 (1.14, 1.31) 1.17 (1.00, 1.36) 633 1.13 (1.03, 1.23) 1.11 (0.55, 2.27)
No (currently) 19 339 1.20 (1.17, 1.22) 1.61 (1.46, 1.78) 13 302 1.38 (1.32, 1.44) 1.63 (1.47, 1.80) 6037 0.81 (0.78, 0.84) 1.55 (1.08, 2.23)
Total 40 336 17 752 22 584
Total alcohol intake (g/day)
0.05-0.09 1763 1.00 (reference) 1.00 (reference) 369 1.00 (reference) 1.00 (reference) 1394 1.00 (reference) 1.00 (reference)
1.00-9.99 7293 1.11 (1.05, 1.18) 1.13 (0.90, 1.42) 3944 1.15 (1.02, 1.29) 1.07 (0.85, 1.35) 3349 0.91 (0.85, 0.98) 3.38 (0.78, 14.65)
10.00-19.99 2811 1.57 (1.47, 1.68) 1.36 (1.08, 1.73) 2304 1.41 (1.25, 1.60) 1.31 (1.03, 1.67) 507 1.05 (0.94, 1.17) 3.27 (0.71, 15.06)
20.00-29.99 2377 1.81 (1.69, 1.94) 1.50 (1.18, 1.89) 2120 1.52 (1.34, 1.72) 1.44 (1.13, 1.83) 257 1.24 (1.07, 1.43) 3.74 (0.82, 17.08)
≥30.00 4392 2.19 (2.06, 2.33) 1.74 (1.39, 2.20) 4136 1.79 (1.59, 2.02) 1.67 (1.32, 2.11) 256 1.39 (1.20, 1.62) 4.42 (0.96, 20.32)
Total 18 636 12 873 5763
Body mass index
Underweight 3787 0.74 (0.67, 0.83) 0.78 (0.52, 1.17) 1182 0.76 (0.64, 0.89) 0.81 (0.54, 1.23) 2605 0.71 (0.61, 0.82) 0.41 (0.05, 3.12)
Normal 76 104 1.00 (reference) 1.00 (reference) 21 986 1.00 (reference) 1.00 (reference) 54 118 1.00 (reference) 1.00 (reference)
Pre, obese stage 57 397 1.56 (1.51, 1.60) 1.42 (1.28, 1.57) 21 584 1.35 (1.29, 1.41) 1.38 (1.25, 1.54) 35 813 1.60 (1.53, 1.66) 2.96 (1.75, 5.01)
Stage 1 obesity 65 589 2.44 (2.37, 2.51) 2.05 (1.87, 2.26) 27 385 1.91 (1.83, 1.99) 2.02 (1.84, 2.23) 38 204 2.66 (2.56, 2.75) 3.11 (1.86, 5.21)
Stage 2 obesity 6314 3.94 (3.73, 4.17) 3.33 (2.73, 4.06) 1907 3.07 (2.78, 3.38) 3.39 (2.77, 4.15) 4407 4.51 (4.22, 4.83) 2.51 (0.80, 7.94)
Stage 3 obesity 447 5.40 (4.47, 6.52) 3.77 (1.84, 7.71) 77 3.66 (2.33, 5.75) 4.08 (1.87, 8.88) 370 6.58 (5.35, 8.09) 2.80 (0.32, 24.67)
Total 209 638 74 121 135 517

Values are presented as odds ratio (95% confidence interval).

KRW, Korean won.

1 Sex, age, socioeconomic factors (income, marital status), health behavior (smoking, drinking, body mass index), and nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

2 Test for trend (likelihood ratio tests) (△-2logL=962.754, △df=7, p<0.001).

3 Test for trend (likelihood ratio tests) (△-2logL=916.403, △df=7, p<0.001).

4 Test for trend (likelihood ratio tests) (△-2logL=60.995, △df=7, p<0.001).

Table 3.
The strong inverse linear relationship between income level and hypertension
Variables Hypertension patients, n Unadjusted Sex, age adjusted1 Health behavior adjusted2 Nutrition adjusted3 Sex, age, health behavior adjusted4 Sex, age, nutrition adjusted5 Sex, age, health behavior, nutrition adjusted6
Income (unit: 1000 KRW)
≥6000 1554 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)7
4000-5999 3316 1.08 (1.01, 1.15) 1.12 (1.05, 1.19) 1.28 (1.11, 1.47) 1.07 (1.00, 1.14) 1.29 (1.12, 1.48) 1.10 (1.03, 1.18) 1.30 (1.26, 1.50)
3000-3999 4575 1.21 (1.14, 1.29) 1.22 (1.15, 1.30) 1.45 (1.26, 1.65) 1.19 (1.11, 1.26) 1.45 (1.27, 1.66) 1.20 (1.13, 1.28) 1.45 (1.26, 1.67)
2000-2999 6233 1.45 (1.37, 1.54) 1.39 (1.31, 1.48) 1.56 (1.37, 1.79) 1.41 (1.32, 1.49) 1.54 (1.35, 1.76) 1.35 (1.27, 1.44) 1.50 (1.30, 1.72)
1500-1999 3673 1.68 (1.57, 1.79) 1.50 (1.41, 1.61) 1.65 (1.42, 1.92) 1.59 (1.49, 1.70) 1.59 (1.37, 1.85) 1.44 (1.34, 1.54) 1.55 (1.31, 1.82)
1000-1499 3940 2.00 (1.88, 2.14) 1.72 (1.61, 1.84) 1.97 (1.68, 2.30) 1.86 (1.74, 1.99) 1.87 (1.60, 2.19) 1.62 (1.51, 1.73) 1.59 (1.33, 1.91)
500-999 3563 2.51 (2.35, 2.68) 2.05 (1.92, 2.19) 2.22 (1.86, 2.65) 2.25 (2.10, 2.41) 2.04 (1.70, 2.44) 1.87 (1.74, 2.00) 1.65 (1.33, 2.05)
<500 4504 2.95 (2.77, 3.15) 2.24 (2.30, 2.40) 2.35 (1.96, 2.81) 2.57 (2.41, 2.75) 2.09 (1.74, 2.52) 2.00 (1.86, 2.14) 1.58 (1.30, 1.96)
Total 31 358
Male
≥6000 974 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)8
4000-5999 1886 1.08 (0.99, 1.18) 1.08 (1.00, 1.18) 1.28 (1.11, 1.47) 1.08 (0.99, 1.18) 1.28 (1.11, 1.48) 1.08 (1.00, 1.18) 1.30 (1.13, 1.50)
3000-3999 2417 1.14 (1.05, 1.24) 1.14 (1.05, 1.24) 1.46 (1.28, 1.68) 1.13 (1.04, 1.23) 1.47 (1.28, 1.68) 1.13 (1.03, 1.23) 1.47 (1.27, 1.69)
2000-2999 2978 1.26 (1.16, 1.37) 1.22 (1.13, 1.33) 1.60 (1.40, 1.83) 1.23 (1.13, 1.34) 1.57 (1.37, 1.79) 1.19 (1.09, 1.29) 1.52 (1.32, 1.76)
1500-1999 1706 1.43 (1.31, 1.56) 1.34 (1.22, 1.46) 1.69 (1.45, 1.97) 1.40 (1.28, 1.53) 1.60 (1.37, 1.86) 1.30 (1.18, 1.42) 1.55 (1.32, 1.83)
1000-1499 1653 1.69 (1.54, 1.85) 1.52 (1.39, 1.67) 2.05 (1.75, 2.41) 1.60 (1.45, 1.76) 1.89 (1.60, 2.22) 1.43 (1.30, 1.58) 1.61 (1.34, 1.93)
500-999 1345 2.09 (1.90, 2.30) 1.81 (1.64, 2.00) 2.30 (1.91, 2.76) 1.97 (1.78, 2.18) 2.02 (1.68, 2.44) 1.69 (1.53, 1.88) 1.63 (1.30, 2.04)
<500 1415 2.11 (1.92, 2.31) 1.77 (1.61, 1.95) 2.43 (2.02, 2.92) 1.95 (1.76, 2.16) 2.09 (1.73, 2.52) 1.64 (1.48, 1.82) 1.61 (1.28, 2.01)
Total 14 374
Female
≥6000 580 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)9
4000-5999 1430 1.16 (1.06, 1.30) 1.19 (1.07, 1.32) 1.31 (0.52, 3.33) 1.16 (1.04, 1.28) 0.90 (0.35, 2.28) 1.17 (1.05, 1.29) 1.25 (0.48, 3.25)
3000-3999 2158 1.43 (1.30, 1.57) 1.37 (1.24, 1.50) 0.93 (0.37, 2.35) 1.39 (1.26, 1.54) 0.65 (0.26, 1.66) 1.34 (1.21, 1.47) 0.80 (0.31, 2.09)
2000-2999 3255 1.88 (1.70, 2.06) 1.64 (1.50, 1.80) 0.71 (0.28, 1.81) 1.80 (1.64, 1.98) 1.14 (0.45, 2.93) 1.60 (1.45, 1.76) 0.66 (0.25, 1.69)
1500-1999 1967 2.21 (2.01, 2.44) 1.76 (1.60, 1.94) 1.23 (0.48, 3.15) 2.05 (1.85, 2.26) 1.22 (0.49, 3.03) 1.66 (1.50, 1.83) 1.10 (0.42, 2.89)
1000-1499 2287 2.74 (2.49, 3.02) 2.00 (1.82, 2.21) 1.35 (0.54, 3.33) 2.50 (2.26, 2.75) 1.22 (0.49, 3.03) 1.87 (1.70, 2.07) 1.03 (0.40, 2.65)
500-999 2218 3.54 (3.21, 3.91) 2.35 (2.13, 2.60) 1.92 (0.76, 4.87) 3.03 (2.74, 3.35) 1.60 (0.62, 4.10) 2.10 (1.89, 2.33) 1.34 (0.48, 3.72)
<500 3089 4.53 (4.12, 4.98) 2.61 (2.36, 2.87) 2.03 (0.80, 5.16) 3.67 (3.35, 4.08) 1.49 (0.57, 3.94) 2.27 (2.05, 2.51) 0.93 (0.31, 2.82)
Total 16 984

Values are presented as odds ratio (95% confidence interval).

KRW, Korean won; BMI, body mass index.

1 Sex, age, adjusted.

2 Health behavior (smoking, drinking, BMI), adjusted.

3 Nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

4 Sex, age and health behavior (smoking, drinking, BMI), adjusted.

5 Sex, age and nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

6 Sex, age, nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), and health behavior (smoking, drinking, BMI), adjusted.

7 Test for trend (likelihood ratio tests) (△, 2logL=975.408, △df=7, p<0.001).

8 Test for trend (likelihood ratio tests) (△, 2logL= 929.174, △df=7, p<0.001).

9 Test for trend (likelihood ratio tests) (△, 2logL= 59.395, △df=7, p<0.001).

Table 4.
Relationships between marital status and hypertension
Variables Hypertension patients, n Unadjusted Sex, age adjusted1 Health behavior adjusted2 Nutrition adjusted3 Sex, age, health behavior adjusted4 Sex, age, nutrition adjusted5 Sex, age, health behavior, nutrition adjusted6
Marital status
Married 34 457 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Unmarried 633 0.76 (0.70, 0.83) 1.03 (0.94, 1.12) 1.00 (0.82, 1.21) 0.77 (0.71, 0.85) 1.20 (0.99, 1.47) 1.02 (0.94, 1.12) 1.24 (1.00, 1.52)
Separated 246 1.06 (0.92, 1.22) 1.09 (0.95, 1.26) 1.14 (0.73, 1.78) 1.10 (0.95, 1.28) 1.21 (0.78, 1.90) 1.14 (0.98, 1.32) 1.31 (0.80, 2.15)
Divorced 841 0.87 (0.81, 0.94) 1.00 (0.93, 1.08) 1.04 (0.84, 1.28) 0.89 (0.83, 0.96) 1.20 (0.97, 1.48) 1.02 (0.94, 1.10) 1.30 (1.04, 1.62)
Deceased spouse 3623 1.48 (1.43, 1.54) 1.23 (1.18, 1.28) 1.38 (1.06, 1.80) 1.39 (1.33, 1.45) 1.35 (1.03, 1.77) 1.20 (1.15, 1.26) 1.29 (0.95, 1.74)
Others 477 1.48 (1.43, 1.54) 1.44 (1.29, 1.60) 1.95 (1.34, 2.85) 1.60 (1.44, 1.79) 1.87 (1.28, 2.74) 1.45 (1.30, 1.62) 1.93 (1.30, 2.84)
Total 40 277
Male
Married 16 407 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Unmarried 357 0.88 (0.78, 0.99) 1.10 (0.98, 1.25) 1.06 (0.87, 1.28) 0.89 (0.79, 1.00) 1.24 (1.01, 1.52) 1.10 (0.97, 1.24) 1.27 (1.02, 1.57)
Separated 91 1.18 (0.93, 1.50) 1.18 (0.93, 1.51) 1.04 (0.63, 1.71) 1.21 (0.94, 1.56) 1.03 (0.62, 1.70) 1.21 (0.94, 1.56) 1.17 (0.67, 2.02)
Divorced 326 1.46 (1.01, 1.30) 1.22 (1.07, 1.39) 1.25 (1.00, 1.58) 1.14 (1.00, 1.30) 1.30 (1.03, 1.64) 1.21 (1.06, 1.38) 1.40 (1.10, 1.79)
Deceased spouse 275 1.27 (1.11, 1.46) 1.07 (0.93, 1.24) 1.57 (1.16, 2.13) 1.24 (1.07, 1.44) 1.36 (1.00, 1.84) 1.06 (0.92, 1.24) 1.28 (0.91, 1.81)
Others 234 1.57 (1.34, 1.84) 1.46 (1.24, 1.71) 2.09 (1.41, 3.09) 1.54 (1.31, 1.81) 1.95 (1.32, 2.88) 1.46 (1.24, 1.71) 2.06 (1.39, 3.07)
Total 17 690
Female
Married 18 050 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Unmarried 276 0.64 (0.57, 0.73) 0.86 (0.76, 0.98) 0.69 (0.31, 1.55) 0.65 (0.57, 0.75) 0.84 (0.37, 1.90) 0.86 (0.75, 0.98) 0.99 (0.49, 1.97)
Separated 155 1.09 (0.92, 1.30) 1.03 (0.86, 1.22) 2.34 (0.90, 6.08) 1.13 (0.94, 1.35) 2.30 (0.88, 6.04) 1.08 (0.90, 1.29) 1.81 (0.72, 4.57)
Divorced 515 0.84 (0.76, 0.92) 0.90 (0.82, 1.00) 0.77 (0.45, 1.34) 0.87 (0.79, 0.96) 0.79 (0.46, 1.37) 0.93 (0.84, 1.03) 0.97 (0.61, 1.56)
Deceased spouse 3348 1.81 (1.73, 1.88) 1.09 (1.05, 1.14) 1.42 (0.79, 2.55) 1.62 (1.55, 1.69) 1.11 (0.60, 2.03) 1.08 (1.03, 1.13) 1.22 (0.76, 1.98)
Others 243 1.62 (1.40, 1.87) 1.45 (1.25, 1.68) 0.83 (0.11, 6.55) 1.63 (1.40, 1.89) 0.82 (0.10, 6.46) 1.48 (1.27, 1.72) 0.51 (0.07, 3.83)
Total 22 587

Values are presented as odds ratio (95% confidence interval).

BMI, body mass index.

1 Sex, age, adjusted.

2 Health behavior (smoking, drinking, BMI), adjusted.

3 Nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

4 Sex, age and health behavior (smoking, drinking, BMI), adjusted.

5 Sex, age and nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

6 Sex, age, health behavior (smoking, drinking, BMI), and nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

Table 5.
Relationships between income level and marital status
Income (unit: 1000 KRW) Marital status Total
Male
Female
Unadjusted Sex, age adjusted1 Sex, age, health behavior nutrition adjusted2,3 Unadjusted Age adjusted4 Age, health behavior nutrition adjusted5,6 Unadjusted Age adjusted3 Age, health behavior nutrition adjusted5,7
≥3000 Married 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Unmarried 0.62 (0.45, 0.86) 0.75 (0.54, 1.05) 0.91 (0.51, 1.61) 0.79 (0.30, 0.79) 0.56 (0.34, 0.91) 0.89 (0.49, 1.63) 0.83 (0.53, 1.28) 0.96 (0.62, 1.50) 1.06 (0.68, 1.65)
Separated 0.89 (0.83, 1.86) 0.92 (0.44, 1.94) 1.74 (0.36, 8.32) 1.17 (0.43, 3.16) 1.20 (0.45, 3.24) 1.95 (0.40, 9.60) 0.73 (0.23, 2.37) 0.69 (0.21, 2.23) 0.67 (0.21, 2.21)
Divorced 1.08 (0.77, 1.53) 1.11 (0.78, 1.56) 1.33 (0.67, 2.61) 1.02 (0.63, 4.64) 1.05 (0.65, 1.70) 1.33 (0.65, 2.72) 1.19 (0.72, 1.97) 1.14 (0.69, 1.89) 1.29 (0.77, 2.15)
Deceased spouse 1.37 (1.07, 1.76) 1.18 (0.91, 1.51) 2.69 (1.13, 6.40) 1.47 (0.82, 2.65) 1.32 (0.73, 2.39) 2.16 (0.81, 5.77) 1.91 (1.45, 2.53) 1.15 (0.86, 1.52) 1.05 (0.78, 1.42)
Others 1.79 (1.26, 2.54) 1.51 (1.06, 2.16) 2.18 (0.86, 5.52) 1.34 (0.83, 2.18) 1.26 (0.78, 2.04) 2.20 (0.87, 5.57) 2.31 (1.38, 3.86) 1.89 (1.13, 3.18) 1.84 (1.06, 3.20)
1000-2999 Married 1.43 (1.38, 1.48) 1.31 (1.26, 1.35) 1.25 (1.15, 1.36) 1.24 (1.18, 1.30) 1.18 (1.12, 1.24) 1.26 (1.15, 1.37) 1.75 (1.66, 1.84) 1.48 (1.40, 1.56) 1.36 (1.28, 1.43)
Unmarried 1.13 (1.00, 1.27) 1.31 (1.17, 1.47) 1.58 (1.24, 2.02) 1.13 (0.97, 1.32) 1.28 (1.09, 1.49) 1.65 (1.28, 2.12) 1.10 (0.92, 1.32) 1.22 (1.02, 1.47) 1.28 (1.06, 1.55)
Separated 1.36 (1.09, 1.69) 1.31 (1.05, 1.64) 1.35 (0.74, 2.47) 1.35 (0.95, 1.92) 1.31 (0.92, 1.85) 1.41 (0.75, 2.66) 1.65 (1.25, 2.19) 1.37 (1.03, 1.82) 1.41 (1.05, 1.90)
Divorced 1.05 (0.94, 1.19) 1.12 (0.99, 1.26) 1.55 (1.17, 2.04) 1.27 (1.06, 1.53) 1.29 (1.07, 1.55) 1.74 (1.29, 2.35) 1.17 (1.00, 1.37) 1.09 (0.93, 1.27) 1.11 (0.94, 1.31)
Deceased spouse 1.71 (1.57, 1.85) 1.50 (1.38, 1.63) 1.47 (0.95, 2.28) 1.58 (1.24, 2.01) 1.35 (1.06, 1.72) 1.68 (1.06, 2.68) 2.53 (2.31, 2.77) 1.54 (1.40, 1.69) 1.37 (1.24, 1.52)
Others 2.22 (1.91, 2.58) 1.85 (1.59, 2.15) 2.42 (1.50, 3.91) 1.95 (1.57, 2.41) 1.75 (1.41, 2.17) 2.55 (1.57, 4.15) 2.58 (2.08, 3.20) 2.05 (1.65, 2.55) 1.89 (1.50, 2.38)
<1000 Married 2.70 (2.59, 2.82) 1.97 (1.88, 2.06) 1.35 (1.15, 1.59) 1.99 (1.87, 2.12) 1.65 (1.54, 1.77) 1.36 (1.15, 1.60) 3.79 (3.57, 4.03) 2.27 (2.13, 2.43) 1.83 (1.71, 1.97)
Unmarried 1.48 (1.22, 1.79) 1.45 (1.19, 1.76) 0.85 (0.40, 1.81) 1.42 (1.06, 1.90) 1.45 (1.09, 1.94) 0.82 (0.36, 1.85) 1.72 (1.32, 2.24) 1.43 (1.09, 1.86) 1.27 (0.94, 1.71)
Separated 2.03 (1.56, 2.64) 1.77 (1.36, 2.32) 4.92 (1.50, 16.19) 1.90 (1.16, 3.12) 1.65 (1.01, 2.71) 2.30 (0.40, 13.33) 2.71 (1.98, 3.72) 1.92 (1.40, 2.65) 1.72 (1.23, 2.41)
Divorced 1.81 (1.58, 2.07) 1.74 (1.52, 1.99) 1.83 (1.14, 2.92) 2.10 (1.62, 2.71) 1.92 (1.48, 2.48) 1.76 (1.01, 3.08) 2.30 (1.95, 2.71) 1.80 (1.52, 2.12) 1.54 (1.29, 1.84)
Deceased spouse 2.64 (2.46, 2.82) 2.10 (1.95, 2.26) 1.13 (0.62, 2.06) 1.97 (1.54, 2.53) 1.57 (1.22, 2.02) 1.36 (0.68, 2.73) 4.02 (3.72, 4.35) 2.08 (1.91, 2.26) 1.74 (1.59, 1.91)
Others 3.50 (2.76, 4.45) 2.63 (2.06, 3.36) 1.44 (0.45, 4.64) 3.01 (2.09, 4.34) 2.51 (1.74, 3.62) 1.86 (0.54, 6.44) 4.33 (3.14, 5.97) 2.89 (2.08, 4.01) 2.43 (1.70, 3.45)

Values are presented as odds ratio (95% confidence interval).

KRW, Korean won.

1 Sex, age adjusted.

2 Sex, age, health behavior (smoking, drinking, body mass index), and nutrition (energy, protein, fat, carbohydrates, calcium, phosphorus, iron, potassium, vitamin A, sodium, vitamin B1, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, retinol, carotene, ash, fiber, vitamin E, cholesterol), adjusted.

3 Test for trend (likelihood ratio tests) (△-2logL=995.218, △df=17, p<0.001).

4 Age adjusted.

5 Age, health behavior nutrition adjusted.

6 Test for trend (likelihood ratio tests) (△-2logL=944.668, △df=17, p<0.001).

7 Test for trend (likelihood ratio tests) (△-2logL=70.461, △df=16, p<0.001).

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