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Original Article
Determinants of Poor Self-rated Health in Korean Adults With Diabetes
Hwi-Won Lee1,2, Minkyo Song1,2, Jae Jeong Yang1,3, Daehee Kang1,2,4
Journal of Preventive Medicine and Public Health 2015;48(6):287-300.
Published online: October 23, 2015
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  • 18 Scopus

1Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea

2Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea

3Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul,Korea

4Cancer Research Institute, Seoul National University, Seoul,Korea

Corresponding author: Daehee Kang, MD, PhD  103 Daehak-ro, Jongno-gu, Seoul 03080, Korea  Tel: +82-2-740-8407, Fax: +82-2-747-4830 E-mail:
• Received: July 31, 2015   • Accepted: October 21, 2015

Copyright © 2015 The Korean Society for Preventive Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Objectives:
    Self-rated health is a measure of perceived health widely used in epidemiological studies. Our study investigated the determinants of poor self-rated health in middle-aged Korean adults with diabetes.
  • Methods:
    A cross-sectional study was conducted based on the Health Examinees Study. A total of 9759 adults aged 40 to 69 years who reported having physician-diagnosed diabetes were analyzed with regard to a range of health determinants, including sociodemographic, lifestyle, psychosocial, and physical variables, in association with self-rated health status using multivariate logistic regression models. A p-value <0.05 was considered to indicate statistical significance.
  • Results:
    We found that negative psychosocial conditions, including frequent stress events and severe distress according to the psychosocial well-being index, were most strongly associated with poor self-rated health (odds ratio [OR]Frequent stress events, 5.40; 95% confidence interval [CI], 4.63 to 6.29; ORSevere distress, 11.08; 95% CI, 8.77 to 14.00). Moreover, younger age and being underweight or obese were shown to be associated with poor self-rated health. Physical factors relating to participants’ medical history of diabetes, such as a younger age at diagnosis, a longer duration of diabetes, insulin therapy, hemoglobin A1clevels of 6.5% or more, and comorbidities, were other correlates of poor reported health.
  • Conclusions:
    Our findings suggest that, in addition to medical variables, unfavorable socioeconomic factors, and adverse lifestyle behaviors, younger age, being underweight or obese, and psychosocial stress could be distinc factors in predicting negative perceived health status in Korean adults with diabetes.
Perceptions of health are currently considered to encompass both physical and psychological dimensions. Self-rated health (SRH) is a self-reported health measure that is valid and widely used in epidemiological studies to assess an individual’s integrated perception of health, which may be inaccessible to an external observer [1-3]. Despite the subjective nature of this concept, it can aid in the global assessment of health in terms of biological, psychological, and social dimensions, which may be more sensitive than external measures of health for monitoring overall health [1]. In fact, SRH has been shown to predict a range of health outcomes, spanning from morbidity and mortality to future health care use [4,5].
According to a report by the Organization for Economic Cooperation and Development (OECD), Korea ranked 33rd out of 34 OECD member states in perceived health status of the population [6]. Less than half of the total population (36.8%) reported being in good health, far below the OECD average of 69.0%. A wide range of factors may have influenced those results, and it is imperative that greater emphasis be placed on public health and disease prevention in order to improve population health. Such efforts can begin with specific populations at the local level.
Diabetes has emerged as a new epidemic, with approximately 382 million people living with diabetes globally [7]. In recent years, the proportion of type 2 diabetes has increased, especially in Asia, making this region the epicenter of the diabetes epidemic [7]. Korea is not free from this global phenomenon, with 12.4% of adults 30 years and older diagnosed with diabetes. This trend continues, with a twofold growth of the diabetic population expected over the next 40 years [8].
So far, only a handful of studies has investigated the association between perceived health status and chronic diseases, such as diabetes, within the Korean population. Some studies have found independent associations between diseases such as hypertension and non-fatal musculoskeletal disorders and poor SRH [9,10]. Most studies regarding SRH, however, have been conducted in the general Korean population, rendering it unfeasible to identify factors representative of people with chronic conditions [11,12]. It is necessary to determine the factors associated with negative perceived health among specific subgroups. This study thus aimed to identify the factors associated with poor SRH in diabetic middle-aged Korean adults.
This study was based on a large-scale genomic cohort study, the Health Examinees (HEXA) Study. Described elsewhere in detail, the HEXA Study was launched to investigate the risk factors for major chronic diseases, ranging from epidemiological characteristics and genomic features to gene-environment interactions [13].
Study Population
A total of 162 142 subjects aged 40 to 69 years participated in the HEXA Study between 2004 and 2012. In addition to respondents who answered ‘yes’ to a question about physician-diagnosed diabetes in the self-reported survey, only those who were 30 years or older at the time of diabetes diagnosis were included in order to limit the possibility of including cases of type 1 diabetes (n=10 112) [3,14]. Subjects were also excluded due to missing information about SRH (n=84) or a history of depression (n=269). Since a number of studies has argued that depression is closely correlated with poor SRH, we excluded respondents with depression in order to eliminate the potential influence on the evaluation of SRH by depressed individuals in relation to variables of interest [3,15]. A total of 9759 respondents comprised the final subjects of our analysis (Figure 1).
Self-rated Health
SRH was assessed with a single question: ‘How do you evaluate your current health status?’ Participants were asked to choose a response from a five-category Likert scale (very healthy, healthy, normal, unhealthy, or very unhealthy). Following common procedure, we grouped the answers into a dichotomous variable of ‘good’ (very healthy, healthy, and normal) and ‘poor’ (unhealthy and very unhealthy) [16].
Domains of Health Determinants
The factors presumed to be correlated with SRH were grouped into different domains: sociodemographic factors, lifestyle factors, psychosocial conditions, anthropometric indices, and physical conditions (Supplemental Table 1). The physical domain of health focused on diabetes history and status as well as comorbid conditions.
The sociodemographic factors included sex and age. Age was divided into intervals of 40 to 49 years, 50 to 59 years, and 60 to 69 years. Marital status was defined as married or not married. Educational attainment was classified as less than a high school diploma, a high school diploma to some college, or a bachelor’s degree and higher. Occupation types were classified as non-manual labor, manual labor, and not in the work force. Income was categorized based on the monthly salary in units of 1000 Korean won (<2000, 2000 to 4000 or ≥4000), which is approximately equivalent to units of 1 US dollar.
Lifestyle factors included smoking, alcohol consumption, and physical activity. Smoking status and alcohol consumption were classified as never, past, or current. The physical activity variable was defined by classifying participants as either regular exercisers or non-exercisers, where regular exercisers referred to those who engaged in regular, sweat-inducing exercise.
The psychosocial variables included the frequency of mental and/or physical stress experienced during the past month (not at all, sometimes, or frequent). The psychosocial well-being index (PWI), a measure of mental health focusing on the psychosocial aspect of stress [17,18], was used to define three groups: positive well-being, moderate distress, and severe distress. Sleep duration was categorized as <6, 6 to 8, 8 to 10 or ≥10 h/d.
The anthropometric indices included body mass index (BMI) and waist circumference (WC). Respondents were classified into five BMI groups based on the weight range associated with a minimal risk of death in Asian populations: underweight (<22.5 kg/m2), normal weight (22.6 to 25.0 kg/m2), overweight (25.1 to 27.1 kg/m2), pre-obese (27.6 to 30.0 kg/m2), or obese (>30.0 kg/m2) [19]. Central obesity was defined as a WC ≥90 cm in men and ≥80 cm in women, as suggested by global organizations such as the International Diabetes Federation [20,21].
In the physical domain, subjects’ diabetes history and status were queried and the following variables were extracted: age of diagnosis, duration of the disease, current treatment status, treatment type, fasting blood sugar (FBS) level, and hemoglobin A1c (HbA1c) level. The age of diagnosis was presented as a mean (±standard deviation [SD]) value and was also divided into dichotomous groups of <50 vs. ≥50 years [8]. The duration of diabetes was classified as <5, 5 to 10, or ≥10 years. The current treatment status included no treatment necessary, currently under treatment, or treatment neglected or never treated. The treatment types were divided into lifestyle modification, oral medication, or insulin therapy. As an indicator of diabetes control, FBS was categorized into <126 mg/dL vs. ≥126 mg/dL. A subgroup analysis was conducted on subjects who provided information about their HbA1c levels (n=3689). As an indicator of long-term diabetes control status, HbA1c was categorized as <6.5% vs. ≥6.5%.
The HEXA Study surveyed information on participants’ personal medical histories and medication usage. Based on self-reports, nine diseases and conditions were evaluated in our study: hypertension, hyperlipidemia, stroke, myocardial infarction, gastrointestinal diseases, liver diseases, diseases of the joints and bones, respiratory diseases, and cancer.
Statistical Analysis
Selected characteristics for the two SRH groups (good vs. poor) were compared using the Student’s t-test for continuous variables and the chi-square test for categorical variables. All results were considered statistically significant at a p-value<0.05. Logistic regression analyses were performed to identify factors that were significantly associated with poor SRH. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Three models were included in the overall analysis. Model 1 was adjusted for sex and age. Model 2 was adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level) and lifestyle factors (smoking status, alcohol consumption, and physical activity). Model 3 was adjusted for the covariates in model 2 as well as psychosocial conditions (stress events, PWI score, and sleep duration) and anthropometry (BMI and WC). All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA).
The basic characteristics of the study subjects are presented in Table 1. Our study included more women (51.6%) than men, and the older age group (60 to 69 years) comprised almost half of the diabetic population (46.4%). Most of the subjects were married (87.3%) and were not in the work force (51.0%). The plurality of respondents were current drinkers (41.8%), more than half (59.2%) were regular exercisers, and 15.7% were smokers. Most of the subjects reported experiencing moderate distress (73.0%), but more than half (53.5%) of the subjects did not report mental and/or physical stress during the past month. Approximately 57% of the respondents slept six to eight hours per day on average. The mean±SD values of BMI and WC were 24.9±3.1 kg/m2 and 85.6±8.4 cm, respectively. The mean±SD FBS value was 134.1±44.7 mg/dL and the mean HbA1c level was 7.3±1.4%.
The ORs of poor SRH according to multiple domains of health determinants are presented in Table 2. Sociodemographic factors had a significant impact in the fully adjusted model, with the exception of income level. Poor SRH was significantly associated with female gender (OR, 1.26; 95% CI, 1.09 to 1.46), not being married or living with a partner (OR, 1.17; 95% CI, 1.02 to 1.34), and unemployment (OR, 1.36; 95% CI, 1.15 to 1.61). The most prominent association was observed with educational attainment, as the likelihood of reporting poor SRH increased with a lower level of education (p for trend <0.01). The lifestyle factors of smoking and lack of regular physical activity were also significantly associated with increased odds of poor SRH. Age and alcohol, however, were inversely associated with poor SRH, with the odds of poor SRH gradually decreasing in older age groups (p for trend=0.01). Psychosocial conditions such as frequent stress events and severe distress, based on PWI scores, showed the strongest associations with poor SRH, with frequent stress events accounting for a 5.40-fold increase in the odds of poor SRH (95% CI, 4.63 to 6.29) and severe distress being associated with an 11.08-fold increase in the odds of poor SRH (95% CI, 8.77 to 14.00), even after full adjustment for covariates. While stress events and PWI status were associated with higher odds of poor SRH (p for trend <0.01), sleep duration showed a J-shaped association with poor SRH. BMI presented a U-shaped association, in which subjects at both ends of the BMI spectrum (underweight and obese) were marginally more likely to report poor SRH (ORUnderweight, 1.13; 95% CI, 1.00 to 1.28, ORObese, 1.22; 95% CI, 1.00 to 1.49).
The details of the associations between poor SRH and physical health variables dealing with participants’ medical history of diabetes and comorbidities are shown in Table 3. FBS did not show a significant association with poor SRH, but a younger age at the time of diagnosis, a diabetes duration of 5 to 10 years and ≥10 years, current treatment, and receiving insulin therapy were all variables found to be significantly associated with increased odds of poor SRH. In fact, a 1.46-fold increased likelihood of poor SRH was found in subjects who were diagnosed at a younger age (95% CI, 1.30 to 1.63), and ORs of 1.27 (95% CI, 1.14 to 1.44) and 1.62 (95% CI, 1.44 to 1.82) were found in respondents with diabetes durations of 5 to 10 years and ≥10 years, respectively. Compared to subjects for whom treatment was unnecessary, respondents currently undergoing treatment (OR, 2.03; 95% CI, 1.44 to 2.85) and having never received treatment or having neglected their treatment (OR, 1.58; 95% CI, 1.10 to 2.27) had higher odds of poor SRH. Respondents who received insulin therapy in addition to oral medication and/or lifestyle modification had a higher likelihood of poor SRH (OR, 2.62; 95% CI, 1.79 to 3.82) compared to those who engaged in lifestyle modification only.
A significant association was found between each comorbid condition and poor SRH (Table 3). Diseases associated with a higher likelihood of poor health were stroke (OR, 2.57; 95% CI, 1.85 to 3.57), gastrointestinal diseases (OR, 2.25; 95% CI, 1.68 to 3.02), and myocardial infarction (OR, 2.03; 95% CI, 1.65 to 2.48). Additionally, the odds of poor SRH increased as the number of comorbid conditions increased (p for trend <0.01).
A subgroup analysis was conducted on 3689 subjects who provided information about their HbA1c levels (Table 4). Compared to the reference group with an HbA1c level <6.5%, those with higher HbA1c levels had increased odds of poor SRH (OR, 1.21; 95% CI, 1.02 to 1.43).
The present study was conducted to explore various domains of health determinants possibly associated with poor SRH among diabetic adults in Korea. After adjusting for sociodemographic, lifestyle, psychosocial factors, and anthropometric indices, the associations between poor SRH and a number of characteristics remained statistically significant. Specifically, the psychosocial domain of health, including stress events and PWI scores, were observed to have greater impact on SRH than other types of health determinants. Factors such as low sociodemographic status, adverse lifestyle behaviors, and disease history were also significantly associated with poor SRH.
In our study of the Korean diabetic population, variables representative of psychosocial distress were found to be strongly associated with an increased likelihood of poor SRH. These results are consistent with prior studies of diabetic populations in other nations demonstrating SRH to be strongly related to emotional well-being [15,22]. The strong association between poor SRH and psychological measures may be due to reasons specific to the diabetic population, since emotional distress occurs as a result of the severity of diabetes and the resulting burden of self-care [23]. When dealing with the demands of the disease, many people with diabetes may become emotionally overwhelmed, frustrated, and discouraged—an emotional reaction now understood as diabetes-related distress [24]. In a study by Jones et al. [25] of people with diabetes, approximately half of the study subjects (50.1%) reported that living with diabetes took up too much mental and physical energy every day. In a study conducted by de Groot et al. [26], reduced well-being and mental health problems were found to be more prevalent among people with type 2 diabetes than in the general population.
Certain sociodemographic factors, such as younger age, female gender, and low educational attainment, were also associated with poor SRH, echoing the findings of prior studies on diabetic populations [23,27-29]. The positive association between poor SRH and younger age deserves particular attention because the opposite association is observed in the general population [12]. This phenomenon may be explained in several ways. First, the notion of social comparison explains that older people are more likely to normalize physical discomfort by attributing it to aging rather than poor health [30]. Second, experiences and perceptions of diabetes differ by age, and the physical and psychological burdens appear to be generally greater in middle-aged subjects, even though older diabetic patients tend to have poorer control of the disease [31]. Our subgroup analyses (data not shown) showed that the oldest age group (60 to 69 years) had the greatest number of comorbidities. The middle-aged group (40 to 49 years) had the least overall prevalence of disease, but the highest odds of poor SRH.
Another finding in our diabetic population was that past drinkers had higher odds of poor SRH. Badawi et al. [3] proposed that never or past drinkers who are diabetic abstain from alcohol due to health reasons. In fact, we found in a separate analysis (data not shown) that never or past drinkers were more likely than current drinkers to have been undergoing current treatment, receiving insulin therapy, to have had diabetes for more than 10 years, and to have had more than one comorbid condition (p<0.01). They also had significantly higher mean HbA1c levels, which reflect the severity of diabetes.
The physical domain of health was strongly associated with SRH. Of a range of variables addressing participants’ medical history and diabetes status, all except FBS were significantly associated with SRH. Our findings are supported by those of a prior study of diabetic patients, in which disease severity, including insulin use (OR, 2.0; 95% CI, 1.7 to 2.3) and a duration of diabetes of ≥20 years (OR, 1.3; 95% CI, 1.1 to 1.6), was associated with an increased likelihood of fair or poor health [29]. Likewise, another study reported that one in five people with diabetes responded that taking diabetes medication interfered with their ability to live a normal life, resulting in a greater distress or a negative evaluation of their emotional well-being [25]. Moreover, Delahanty et al. [23] showed that compared to those who received diet or oral medication therapy, patients who underwent insulin therapy scored the highest in the assessment of diabetes-related emotional distress (Problem Areas in Diabetes scale (points±SD): 14.6±1.7 [diet] vs. 18.6±1.3 [oral medication] vs. 23.6±1.7 [insulin]).
Comorbid conditions were also found to be positively associated with poor SRH to varying extents. Moreover, this association strengthened as the number of comorbidities increased. An association between comorbidities and the odds of poor SRH has also been found in another diabetic population (OR, 4.3; 95% CI, not shown) [28].
Since a limited number of studies have been published evaluating SRH in diabetic populations, we could not contextualize some of our results, including the role of sleep duration and marital status as health determinants of poor SRH specific to people with diabetes. We found that our results regarding sleep duration were not significantly different from studies based on the general population in Korea [12] and Australia [32], which found positive associations between poor SRH and short and long sleep durations. Not being married is also a significant correlate of poor SRH that may not be specific to the diabetic population [33,34]. However, Zheng and Thomas [35] pointed out the possibility of married people misestimating their health status in the positive direction; caution is thus warranted when interpreting SRH according to marital status. Further studies are needed to clarify the association between marital status and poor SRH. The adverse lifestyle behaviors of smoking and being physically inactive were also significantly associated with poor SRH, which is consistent both with studies on diabetic populations and with studies of the general population [2,3,28,29].
Marginally significant associations were found between poor SRH and both underweight and obese status. Studies of non-Asian populations have failed to find an association between poor SRH and low BMI; in those studies, fair or poor health was only found to be related to obesity [3,28,29]. A possible explanation for this discrepancy is that insulin resistance in Asian populations occurs at a BMI level considered to be within the normal range for Western populations (23.0 to 24.0 kg/m2) [36]. Japanese researchers showed that underweight (BMI <18.5 kg/m2)was associated with a 1.32-fold increased risk of diabetes in older males (95% CI, 1.12 to 1.56) and a 1.31-fold increase in older females (95% CI, 1.07 to 1.60) [37]. Moreover, weight loss is a symptom of diabetes [38]. The question of whether low BMI is associated with poor SRH as a symptom reflecting disease severity remains unresolved.
All of our variables—dependent and independent—were obtained from self-reported data, which may have compromised the validity due to recall bias. It is also important to keep in mind that the direction of causality could not be determined due to the cross-sectional nature of the present study.
Despite these limitations, our study has the strength of including a large sample of diabetic subjects. Using the HEXA questionnaire, we were able to conduct a comprehensive analysis of SRH by assessing a broad range of factors, from sociodemographic variables to physical health. Moreover, as this is one of the few studies of SRH and diabetes in the Korean population, the findings of this study add to our understanding of the association between low SRH and diabetes in a developed, non-Western society. Lastly, we limited our subjects to type 2 diabetic patients in order to identify the factors associated with negative perceptions of health among people with a specific health condition.
SRH is a widely used tool that is a strong predictor for mortality and morbidity, even in relation to diabetes [27,39]. In the present study, we identified factors with a significant relationship to poor SRH among the adult diabetic population in Korea. Although caution is warranted in interpreting the results, we found that multiple domains of health determinants were associated with poor SRH, most notably the psychosocial domain. Further studies are needed to investigate the underlying mechanisms connecting the psychosocial conditions, known variables, and unmeasured residual variables with SRH.
Negative perceived health status itself elicits adverse health outcomes in conditions such as diabetes. In our study, several domains of health determinants, ranging from sociodemographic to psychosocial and physical, were associated with poor SRH. Our findings suggest that younger age, underweight or obesity, and adverse psychosocial conditions could be factors that distinctively predict negative perceived health status in Korean adults with diabetes. As these factors may contribute both directly and indirectly to the exacerbation of diabetes via SRH, further studies are needed to explore the underlying mechanism. Meanwhile, strategies such as focusing attention on specific groups (middle-aged and/or underweight and obese adults) or routinely screening for stress may be suggested to improve the SRH—and eventually the overall prognosis—of people with diabetes.
This study was supported by the National Genome Research Institute, Korea Centers for Disease Control and Prevention. The authors would like to thank all participants and members of the HEXA Study Group.

Conflict of Interest

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

Supplemental Table 1.
List and description of variables1
Figure 1.
Flow diagram showing selection of study subjects. HEXA, Health Examinees.
Table 1.
Basic characteristics of the study population1 (n=9759)
n (%)
Sociodemographic factors
 Male 4721 48.4
 Female 5038 51.6
Age (y)
 40-49 1339 13.7
 50-59 3892 39.9
 60-69 4528 46.4
Marital status2
 Married 8523 87.3
 Not married 1212 12.4
Educational attainment
 Bachelor's degree or higher 1768 18.1
 High school diploma to college3 3414 35.0
 Less than high school diploma 4467 45.8
Occupation type
 Non-manual labor 1496 15.3
 Manual labor 3109 31.9
 Not in work force4 4974 51.0
 ≥4000 1500 15.4
 2000-4000 3020 31.0
 <2000 3766 38.6
Lifestyle factors
 Current smokers 1532 15.7
 Current drinkers 4083 41.8
 Regular exercisers 5774 59.2
Psychosocial conditions
 Stress events
  Not at all 5217 53.5
  Often 3505 35.9
  Frequent 936 9.6
 PWI score (mean±SD, points)6 17 8.3
 PWI status
  Positive well-being 1043 10.7
  Moderate distress 7121 73.0
  Severe distress 1274 13.1
 Sleep duration (h/d)
  <6 1307 13.4
  6-8 5603 57.4
  8-10 2560 26.2
  ≥10 248 2.5
 BMI (mean±SD, kg/m2) 24.9 3.1
 WC (mean±SD, cm) 85.6 8.4
Indicators of DM control
 FBS (mean±SD, mg/dL) 134.1 44.7
 HbA1c (mean±SD, %) 7.3 1.4

SD, standard deviation; SRH, self-rated health; PWI, psychosocial well-being; BMI, body mass index; WC, waist circumference; FBS, fasting blood sugar; HbA1c, hemoglobin A1c; DM, diabetes mellitus; SD, standard deviation.

1 Unknown values are not shown, but were included in statistical models.

2 Married includes married or living with a partner; not married includes single, divorced, separated, or widowed.

3 College includes a vocational certificate, associate’s degree, or some years of college-level education without completion of a degree.

4 Not in work force refers to housewives, students, or the unemployed.

5 Income refers to monthly salary in Korean won (unit: 1000 won).

6 PWI scores: ≤8, positive well-being; 9-26, moderate distress; ≥27, severe distress.

Table 2.
ORs (95% CIs) of poor SRH according to selected correlates of the study population1 (n=9759)
Model 12 Model 23 Model 34
Good (n=6530) Poor (n=3229)
Sociodemographic factors
  Male 3472 53.2 1249 38.7 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Female 3058 46.8 1980 61.3 1.80 (1.65, 1.96)* 1.41 (1.22, 1.63)* 1.26 (1.09, 1.46)*
 Age (y)
  40-49 884 13.5 455 14.1 1.00 (reference) 1.00 (reference) 1.00 (reference)
  50-59 2607 39.9 1285 39.8 0.94 (0.82, 1.07) 0.84 (0.73, 0.97)* 0.84 (0.73, 0.97)*
  60-69 3039 46.5 1489 46.1 0.94 (0.83, 1.07) 0.74 (0.64, 0.85)* 0.73 (0.63, 0.85)*
  p for trend 0.48 <0.01 0.01
 Marital status5
  Married 5823 89.2 2700 83.6 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Not married 692 10.6 520 16.1 1.39 (1.23, 1.58)* 1.26 (1.11, 1.44)* 1.17 (1.02, 1.34)*
 Educational attainment
  Bachelor's degree or higher 1376 21.1 392 12.1 1.00 (reference) 1.00 (reference) 1.00 (reference)
  High school diploma to college6 2376 36.4 1038 32.2 1.39 (1.21, 1.60)* 1.31 (1.14, 1.51)* 1.29 (1.12, 1.50)*
  Less than high school diploma 2703 41.4 1764 54.6 1.94 (1.69, 2.23)* 1.65 (1.43, 1.92)* 1.58 (1.36, 1.84)*
  p for trend <0.01 <0.01 <0.01
 Occupation type
  Non-manual labor 1146 17.6 350 10.8 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Manual labor 2138 32.7 971 30.1 1.37 (1.18, 1.58)* 1.05 (0.89, 1.23) 1.02 (0.87, 1.21)
  Not in work force7 3118 47.8 1856 57.5 1.55 (1.34, 1.80)* 1.34 (1.14, 1.58)* 1.36 (1.15, 1.61)*
  ≥4000 1103 16.9 397 12.3 1.00 (reference) 1.00 (reference) 1.00 (reference)
  2000-4000 2161 33.1 859 26.6 1.05 (0.91, 1.21) 0.91 (0.79, 1.05) 0.93 (0.80, 1.08)
  <2000 2355 36.1 1411 43.7 1.55 (1.35, 1.78)* 1.14 (0.98, 1.33) 1.14 (0.98, 1.33)
  p for trend 0.05 0.02 0.64
Lifestyle factors
  Never smokers 3919 60.0 2207 68.4 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Past smokers 1528 23.4 544 16.9 1.08 (0.93, 1.26) 1.09 (0.93, 1.27) 1.13 (0.97, 1.33)
  Current smokers 1068 16.4 464 14.4 1.25 (1.07, 1.46)* 1.19 (1.01, 1.39)* 1.19 (1.01, 1.40)*
 Alcohol drinking
  Never drinkers 3118 47.8 1876 58.1 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Past drinkers 420 6.4 247 7.7 1.35 (1.13, 1.62)* 1.27 (1.06, 1.53)* 1.18 (0.97, 1.43)*
  Current drinkers 2984 45.7 1099 34.0 0.82 (0.73, 0.91)* 0.79 (0.70, 0.88)* 0.76 (0.68, 0.85)*
 Physical activity
  Regular exercisers 4100 62.8 1674 51.8 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Non-exercisers 2425 37.1 1552 48.1 1.51 (1.39, 1.65)* 1.40 (1.28, 1.53)* 1.28 (1.17, 1.41)*
Psychosocial conditions
 Stress events
  Not at all 4029 61.7 1188 36.8 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Sometimes 2118 32.4 1387 43.0 2.12 (1.93, 2.33)* 2.07 (1.88, 2.27)* 2.07 (1.88, 2.28)*
  Frequent 326 5.0 610 18.9 5.88 (5.05, 6.83)* 5.44 (4.67, 6.34)* 5.40 (4.63, 6.29)*
  p for trend <0.01 <0.01 <0.01
 PWI status9
  Positive well-being 922 14.1 121 3.8 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Moderate distress 5042 77.2 2079 64.4 2.98 (2.45, 3.63)* 2.91 (2.39, 3.55)* 2.58 (2.11, 3.15)*
  Severe distress 357 5.5 917 28.4 17.92 (14.29, 22.48)* 15.95 (12.69, 20.04)* 11.08 (8.77, 14.00)*
  p for trend <0.01 <0.01 <0.01
 Sleep duration (h/d)
  <6 802 12.3 505 15.6 1.37 (1.21, 1.56)* 1.31 (1.15, 1.48)* 1.17 (1.03, 1.34)*
  6-8 3886 59.5 1717 53.2 1.00 (reference) 1.00 (reference) 1.00 (reference)
  8-10 1681 25.7 879 27.2 1.17 (1.06, 1.30)* 1.11 (1.00, 1.22)* 1.14 (1.03, 1.27)*
  ≥10 138 2.1 110 3.4 1.79 (1.38, 2.32)* 1.59 (1.22, 2.07)* 1.58 (1.20, 2.08)*
  p for trend 0.18 0.34 0.26
 Body mass index (kg/m2)
  Underweight (≤22.5) 1355 20.8 730 22.6 1.16 (1.04, 1.31)* 1.16 (1.03, 1.30)* 1.13 (1.00, 1.28)*
  Normal (22.6-25.0) 2267 34.7 1013 31.4 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Overweight (25.1-27.5) 1813 27.8 899 27.8 1.13 (1.01, 1.26)* 1.10 (0.99, 1.23)* 1.09 (0.97, 1.22)*
  Pre-obese (27.5-30.0) 757 11.6 359 11.1 1.05 (0.90, 1.21) 1.01 (0.87, 1.18) 0.98 (0.84, 1.15)
  Obese (>30.0) 326 5 219 6.8 1.38 (1.14, 1.67)* 1.29 (1.06, 1.56)* 1.22 (1.00, 1.49)*
  No central obesity 3090 47.3 1367 42.3 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Central obesity10 3309 50.7 1774 54.9 1.07 (0.98, 1.17) 1.00 (0.91, 1.09) 1.02 (0.91, 1.15)

Values are presented as number (%) or OR (95% CI).

SRH, self-rated health; PWI, psychosocial well-being; BMI, body mass index; WC, waist circumference; OR, odds ratio; CI, confidence interval.

1 Unknown values are not shown, but were included in statistical models.

2 Model 1, adjusted for sex and age.

3 Model 2, adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level) and lifestyle factors (smoking status, alcohol consumption, and physical activity).

4 Model 3, fully adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level), lifestyle factors (smoking status, alcohol consumption, and physical activity), psychosocial conditions (stress events, PWI score, and sleep duration), and anthropometry (BMI and WC).

5 Married includes married or living with a partner; not married includes single, divorced, separated, or widowed.

6 College includes a vocational certificate, associate’s degree, or some years of college-level education without completion of a degree.

7 Not in work force refers to housewives, students, or the unemployed.

8 Income refers to monthly salary in Korean won (unit: 1000 won).

9 PWI scores: ≤8, positive well-being; 9-26, moderate distress; ≥27, severe distress.

10 Central obesity refers to a waist circumference of ≥90 cm in men and ≥80 cm in women.

* p<0.05.

Table 3.
ORs (95% CIs) for poor SRH according to diabetes history, diabetes status, and comorbidity status1 (n=9759)
Model 12 Model 23 Model 34
Good (n=6530) Poor (n=3229)
Diabetes history and status
 DM diagnosis age (y)
  ≥50 4123 63.1 1875 58.1 1.00 (reference) 1.00 (reference) 1.00 (reference)
  < 50 2407 36.9 1354 41.9 1.38 (1.24, 1.54)* 1.42 (1.27, 1.58)* 1.46 (1.30, 1.63)*
 DM duration (y)
  <5 2593 39.7 1083 33.5 1.00 (reference) 1.00 (reference) 1.00 (reference)
  5-10 1632 25.0 821 25.4 1.21 (1.08, 1.35)* 1.23 (1.10, 1.38)* 1.27 (1.14, 1.44)*
  ≥10 1564 24.0 950 29.4 1.52 (1.36, 1.70)* 1.55 (1.39, 1.74)* 1.62 (1.44, 1.82)*
  Unknown 741 11.4 375 11.6
 Current treatment status
  No treatment necessary 174 2.7 48 1.5 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Currently under treatment 5523 84.6 2827 87.6 1.91 (1.38, 2.64)* 2.03 (1.46, 2.82)* 2.03 (1.44, 2.85)*
  Treatment neglected/never treated 833 12.8 354 11.0 1.61 (1.14, 2.28)* 1.66 (1.17, 2.35)* 1.58 (1.10, 2.27)*
 Treatment type5
  Lifestyle modification only6 157 2.8 57 2.0 1.00 (reference) 1.00 (reference) 1.00 (reference)
  Oral meds±lifestyle 4009 72.6 1798 63.6 1.22 (0.89, 1.66) 1.17 (0.85, 1.60) 1.26 (0.91, 1.76)
  Insulin±oral meds±lifestyle 234 4.2 228 8.1 2.65 (1.86, 3.79)* 2.43 (1.69, 3.50)* 2.62 (1.79, 3.82)*
  Unknown 1123 20.3 744 26.3
 Fasting blood sugar (mg/dL)
  < 126 3353 51.4 1628 50.4 1.00 (reference) 1.00 (reference) 1.00 (reference)
  ≥126 3025 46.3 1539 47.7 1.07 (0.98, 1.17) 1.08 (0.99, 1.18) 1.08 (0.99, 1.18)
  Unknown 152 2.3 62 1.9
Comorbidity status
 Comorbid diseases7
  Hypertension 2560 39.2 1508 46.7 1.37 (1.26, 1.50)* 1.41 (1.29, 1.54)* 1.46 (1.33, 1.61)*
  Hyperlipidemia 786 12.0 561 17.4 1.45 (1.29, 1.64)* 1.57 (1.39, 1.78)* 1.57 (1.38, 1.78)*
  Stroke 77 1.2 90 2.8 2.76 (2.02, 3.77)* 2.57 (1.87, 3.52)* 2.57 (1.85, 3.57)*
  Myocardial infarction 247 3.8 220 6.8 2.10 (1.73, 2.54)* 2.10 (1.73, 2.55)* 2.03 (1.65, 2.48)*
  Gastrointestinal diseases 94 1.4 115 3.6 2.50 (1.89, 3.31)* 2.48 (1.87, 3.29)* 2.25 (1.68, 3.02)*
  Liver diseases 147 1.5 124 1.3 1.87 (1.46, 2.39)* 1.87 (1.46, 2.40)* 1.78 (1.37, 2.31)*
  Diseases of the joints and bones 279 4.3 330 10.2 2.18 (1.84, 2.59)* 2.11 (1.77, 2.50)* 1.98 (1.66, 2.37)*
  Respiratory diseases 40 0.6 38 1.2 2.22 (1.41, 3.48)* 1.89 (1.19, 2.98)* 1.69 (1.06, 2.71)*
  Cancer 61 0.9 58 1.8 1.93 (1.34, 2.78)* 1.83 (1.26, 2.65)* 1.85 (1.26, 2.71)*
 No. of diseases
  None (DM only) 3263 50.0 1208 37.4 1.00 (reference) 1.00 (reference) 1.00 (reference)
  DM+one condition 2416 37.0 1225 37.9 1.39 (1.26, 1.53)* 1.42 (1.29, 1.57)* 1.48 (1.33, 1.64)*
  DM+two or more conditions 851 13.0 796 24.7 2.54 (2.25, 2.86)* 2.65 (2.34, 3.00)* 2.69 (2.36, 3.07)*
  p for trend <0.01 <0.01 <0.01

Values are presented as number (%) or OR (95% CI).

SRH, self-rated health; DM, diabetes mellitus; OR, odds ratio; CI, confidence interval.

1 Unless the values comprised a significant percentage of the total, unknown values are not shown, but were included in the statistical models.

2 Model 1, adjusted for sex and age.

3 Model 2, adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level) and lifestyle factors (smoking status, alcohol consumption, and physical activity).

4 Model 3, fully adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level), lifestyle factors (smoking status, alcohol consumption, and physical activity), psychosocial conditions (stress events, PWI score, and sleep duration), and anthropometry (body mass index and waist circumference).

5 Treatment type refers to those categorized as ‘currently under treatment’.

6 Lifestyle modification only refers to diet and/or exercise regimens.

7 Gastrointestinal diseases include ulcer diseases and chronic gastritis; liver diseases include acute, chronic, and fatty liver disease; diseases of the joints and bones include arthritis and osteoporosis; respiratory diseases include asthma and pulmonary tuberculosis.

* p<0.05.

Table 4.
ORs (95% CIs) for poor SRH according to HbA1c as an indicator of long-term DM control (n=3689)
Model 11 Model 22 Model 33
Good (n=2576) Poor (n=1113)
Indicator of long-term DM control
 HbA1c (mean±SD) 7.2 1.3 7.4 1.5 1.13 (1.08, 1.19)* 1.11 (1.05, 1.17)* 1.11 (1.06, 1.17)*
 HbA1c (%)
  <6.5 812 31.5 294 26.4 1.00 (reference) 1.00 (reference) 1.00 (reference)
  ≥6.5 1764 68.5 819 73.6 1.24 (1.06, 1.45)* 1.21 (1.04, 1.43)* 1.21 (1.02, 1.43)*

Values are presented as number (%) or odds ratio (95% CI).

SRH, self-rated health; DM, diabetes mellitus; HbA1c, hemoglobin A1c; OR, odds ratio; CI, confidence interval; SD, standard deviation.

1 Model 1, adjusted for sex and age.

2 Model 2, adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level) and lifestyle factors (smoking status, alcohol consumption, and physical activity).

3 Model 3, fully adjusted for sociodemographic factors (sex, age, marital status, education level, employment status, and income level), lifestyle factors (smoking status, alcohol consumption, and physical activity), psychosocial conditions (stress events, PWI score, and sleep duration), and anthropometry (body mass index and waist circumference).

* p<0.05.

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Figure & Data



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