If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
Metabolic syndrome is an important cluster of coronary heart disease risk factors. However, it remains unclear to what extent metabolic syndrome is associated with demographic and potentially modifiable lifestyle factors among Korean persons with physical disabilities. This study aimed to determine the prevalence and influencing factors of metabolic syndrome among persons with physical disabilities using the Korean National Health Insurance Service–National Sample Cohort.
Methods
The Adult Treatment Panel III criteria were used to define metabolic syndrome influencing factors and prevalence, which were evaluated in a representative sample from the 2013 Korean National Health Insurance Service–National Sample Cohort database. Characteristics were compared based on frequency using the χ2 test. The associations between metabolic syndrome and its risk factors were estimated using logistic multivariable regression analysis.
Results
Metabolic syndrome was detected in 31.5% of the surveyed persons with physical disabilities. Female sex, age of ≥65 years, smoking, greater alcohol consumption, physical inactivity, higher body mass index, and a family history of diabetes were associated with increased risks of metabolic syndrome.
Conclusion
The major risk factors for metabolic syndrome among persons with physical disabilities were obesity and older age. Performing physical activity was associated with a lower risk of metabolic syndrome. Therefore, we recommend using a continuous obesity management program and physical activity to prevent metabolic syndrome among persons with physical disabilities.
Accidents, disasters, and diseases have caused the number of South Korean persons with disabilities to increase from 1,449,496 in 2000 to 2,726,910 in 2014, along with an increase in the prevalence of disability from 4.5% in 2005 to 5.5% in 2014 [
]. Despite increased social interest in the health of disabled persons, their mortality rate is four times higher than that of the general population [
]. With the exception of cancer, cardiocerebrovascular diseases are the leading cause of death among these individuals (530 deaths/year), which is more than five times higher than the corresponding rate among the general population [
]. Based on these results, it may be possible to reduce the mortality rate among disabled persons by preventing or managing chronic diseases that can cause cardiocerebrovascular diseases.
Metabolic syndrome is a clustering of 3–5 medical conditions, which are abdominal obesity, decreased high-density lipoprotein cholesterol (HDL-C), increased triglycerides, high blood pressure, and high blood sugar [
]. In addition, disabled persons have a 2.30 times higher risk of high blood pressure, a 3.90 times higher risk of diabetes, and a 6.50 times higher risk of cardiovascular diseases [
Health disparities among adults with developmental disabilities, adults with other disabilities, and adults not reporting disability in North Carolina.
]. Nevertheless, despite their apparently greater risk of metabolic syndrome, there are insufficient data regarding the prevalence of metabolic syndrome among disabled persons. Furthermore, there are limited data among the South Korean population, with only one study revealing the prevalence of metabolic syndrome (43.2% among disabled persons who were aged ≥40 years in 2005) [
Disparities in health-risk behaviors, preventive health care utilizations, and chronic health conditions for people with disabilities: The Korean national health and nutrition examination survey.
]. Moreover, the prevalence of metabolic syndrome is expected to continue increasing based on the prevalence of high blood pressure and diabetes, as well as changes toward a lifestyle with high-fat diets and limited exercise [
]. Therefore, additional research is needed to better understand the effects of metabolic syndrome on disabled persons.
As metabolic syndrome is associated with an elevated risk of mortality because of its various complications (e.g., heart disease and stroke), it is necessary to accurately identify the population-level characteristics of metabolic syndrome [
]. Thus, some studies have examined this topic and revealed that the risk of metabolic syndrome is affected by social factors, such as education, occupation, and marital status [
Persons with physical disabilities are defined as individuals with physical function disabilities in the external body structure as a result of congenital and acquired causes. These persons account for 52.4% of the total disabled population in South Korea [
]. These persons face physical challenges, negative emotions, social maladjustment, severed relationships, and physical function decline as a result of their sudden disability [
], which are associated with the risk of metabolic syndrome. Therefore, this study aimed to investigate the prevalence and influencing factors of metabolic syndrome among persons with physical disabilities. The results will provide basic data that are required to establish metabolic syndrome education and intervention programs for disabled persons.
Methods
Study design
This secondary data analysis study investigated the prevalence and influencing factors of metabolic syndrome among persons with physical disabilities using Korean National Health Insurance Service (NHIS) data [
The data were used in accordance with the data provision and processing procedures of the NHIS. The NHIS sample cohort was created in 2002 to support academic studies of national health, medical treatments, and diseases. The database includes 1,025,340 persons, who represented 2.2% of the 46,605,433 eligible persons in 2002 and were extracted using proportional distributions. The database includes information regarding eligibility, health-care utilization, national health screening results, and health-care providers. The present study evaluated the eligibility data, which include demographic characteristics, and the national health screening data, which include the results of health behavior surveys and the main results of health screenings for individuals who were eligible for health insurance and medical care. In 2013, 234,428 of the 1,014,730 eligible persons had available national health screening data. Among the 234,428 persons, 13,181 persons were disabled, including 8,246 persons with physical disabilities. The present study evaluated data from 8,237 persons with disabilities, after excluding nine persons with missing data that were required to estimate the metabolic syndrome index.
Ethical considerations
This study's protocol was approved by the Institutional Review Board of Dong-A University (Approval no. 201704-HR-012-02).
Measurements
Demographic characteristics
The demographic data included sex, age, income level, and severity of disability. Age was categorized as 20–44 years, 45–64 years, and ≥65 years. Income level was categorized into eleven groups, which were subsequently reclassified as levels 0–2, 3–7, and 8–10. Severity of disability was divided into severe disabilities (grades 1–2) and mild disabilities (grades 3–7).
Metabolic syndrome
The metabolic syndrome criteria were based on the outcomes of a meeting between several major organizations attempting to unify their criteria [
Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity.
]. However, a World Health Organization report (“Asia-Pacific Perspective: Redefining Obesity and its Treatment”) recommends using waist circumference values of ≥90 cm for Asian men and ≥80 cm for Asian women [
]. Thus, for the present study, the criteria for diagnosing metabolic syndrome were (1) waist circumference of ≥90 cm for men and ≥80 cm for women, (2) triglyceride levels of ≥150 mg/dL, (3) HDL-C levels of <40 mg/dL for men and <50 mg/dL for women, (4) blood pressure of ≥130/85 mmHg, and (5) fasting blood glucose levels of ≥100 mg/L.
Health behaviors and characteristics
Health behaviors and characteristics were defined as smoking habits, drinking habits, physical activity habits, body mass index (BMI), and a family history of cardiovascular disease. Smoking was evaluated based on total pack-years (PYs), and was categorized as 0 PYs, 0–15 PYs, 15–30 PYs, and >30 PYs. Drinking was calculated by multiplying the number of drinking days per week and the amount of alcohol consumed per day, based on the amount of alcohol contained in one serving of Soju (50 mL, 250 g of alcohol per liter of Soju) [
]. Drinking amounts per week were categorized as 0 g, 0–200 g, 200–400 g, and >400 g. Physical activity was calculated and classified in accordance with the criteria of the International Physical Activity Questionnaire [
], which assigns weights of 8.0 metabolic equivalents of task (MET) per minute for intense activities, 4.0 MET per minute for moderate activities, and 3.3 MET per minute for light activities, such as walking. The number of activities per week was multiplied by the activity time (minute) and MET weight to calculate the total weekly value, which was categorized as Category 1 (inactive), Category 2 (minimally active, at least 600 MET-minute/week through intense physical activity for >20 minute on 3 days/week or moderately/light physical activity for ≥30 minute on 5 days/week), or Category 3 [health-enhancing physical activity (HEPA), at least 3,000 MET-minute/week through physical activity on all 7 days]. BMI was categorized as underweight (<18.5 kg/m2), normal weight (18.5–22.9 kg/m2), and obese (≥23 kg/m2) [
]. A family history of cardiovascular disease was identified based on a self-reported family history of high blood pressure or diabetes.
Data analysis
The data were analyzed using IBM SPSS software 23.0 (SPSS Inc., Chicago, IL, USA). Differences were considered statistically significant at p < 0 <.05. Metabolic syndrome components were reported as number and frequency and were compared between the various demographic and health behavior categories using the χ2 test. Binary logistic regression analysis was performed using the significant variables in the univariate analyses, and the results were reported as odds ratios and 95% confidence intervals.
Results
Prevalence and diagnostic counts of metabolic syndrome components
The prevalence of the metabolic syndrome components was 46.9% for high blood pressure, 43.1% for high blood sugar, 40.7% for abdominal obesity, 34.1% for high triglycerides, and 24.7% for high HDL-C (Table 1). Among the eligible persons with disabilities, 15.1% of the persons had no components, 25.8% had one component, 27.6% had two components, 19.8% had three components, 9.4% had four components, and 2.3% had five components (Figure 1).
Table 1Prevalence According to Each Component of Metabolic Syndrome (N = 8,237).
Each component of metabolic syndrome
Category
n
%
Waist circumference [≥90 cm (male), ≥80 cm (female)]
Differences in metabolic syndrome according to demographic characteristics and health behaviors
Table 2 shows the various metabolic syndrome components among the different demographic categories. The overall prevalence of metabolic syndrome was 31.5% among disabled persons, with women having a higher prevalence than men (37.8% vs. 27.5%, respectively). The prevalence increased at older ages, with prevalence of 22.1% at 20–44 years, 28.3% at 46–64 years, and 39.4% at >65 years. The prevalence exhibited a U-shaped trend according to income, with prevalence of 31.1% for levels 0–2, 29.5% for levels 3–7, and 34.0% for levels 8–10. The prevalence was 28.1% among persons with severe disabilities and 31.8% among persons with mild disabilities, although this difference was not statistically significant.
Table 2Prevalence of Metabolic Syndrome Among Persons With Physical Disabilities According to Demographic Characteristics (N = 8,237).
Table 3 shows the various metabolic syndrome components among the different health behavior categories. The prevalence of metabolic syndrome was 33.7% among nonsmokers (0 PYs), 25.8% for 0–15 PYs, 28.2% for 15–30 PYs, and 33.4% for >30 PYs. The prevalence was 33.4% among nondrinkers (0 g/week), 26.3% for <200 g/week, 32.6% for 200–400 g/week, and 34.3% for >400 g/week. The prevalence was 32.9% in the inactive group, 29.9% in the minimally active group, and 27.4% in the HEPA group. The prevalence was 6.1% in the underweight group, 13.0% in the normal weight group, and 40.9% in the obese group. The prevalence was 30.1% among persons without a family history of high blood pressure and 34.4% among persons with a family history of high blood pressure. The prevalence was 30.0% among persons without a family history of diabetes and 36.6% among persons with a family history of diabetes.
Table 3Prevalence of Metabolic Syndrome Among Persons With Physical Disabilities According to Health Behaviors (N = 8,237).
Variables
Classifications
Prevalence
Metabolic syndrome
χ2
p
No, n (%)
Yes, n (%)
Total
31.5
5,640 (100.0)
2,597 (100.0)
Smoking (pack-year)
0
33.7
3,112 (55.2)
1,582 (60.9)
39.36
<.001
<15
25.8
1,039 (18.4)
361 (13.9)
15–30
28.2
860 (15.2)
338 (13.0)
>30
33.4
629 (11.2)
316 (12.2)
Alcohol use/week (g/wks)
0
33.4
3,238 (57.5)
1,627 (62.7)
37.91
<.001
<200
26.3
1,591 (28.2)
567 (21.9)
200–400
32.6
495 (8.8)
239 (9.2)
>400
34.3
308 (5.5)
161 (6.2)
Physical activity
Inactive
32.9
3,357 (59.5)
1,647 (63.5)
13.35
.001
Minimally
29.9
1,749 (31.0)
746 (28.8)
Health enhancing
27.4
533 (9.5)
201 (7.7)
BMI (kg/m2)
<18.5
6.1
216 (3.8)
14 (0.5)
683.89
<.001
18.5–22.9
13.0
2,146 (38.1)
321 (21.4)
≥23
40.9
3,274 (58.1)
2,262 (87.1)
Family history of BP
0
30.1
3,077 (82.0)
1,326 (79.0)
7.06
.008
1
34.4
674 (18.0)
353 (21.0)
Family history of DM
0
30.0
3,211 (88.0)
1,373 (84.5)
12.50
<.001
1
36.6
436 (12.0)
252 (15.5)
BMI = body mass index; BP = blood pressure; DM = diabetes mellitus.
The results of the binary logistic regression analysis are shown in Table 4. The factors influencing metabolic syndrome among persons with physical disabilities were sex, age, smoking, drinking, physical activity, BMI, and a family history of diabetes. Women had a 1.66 times higher risk of metabolic syndrome than men. The risk of metabolic syndrome was 2.14 times higher for the ages of ≥65 years than for the ages of 20–44 years. Compared to nonsmokers, the risks were 1.23 times higher for persons with <15 PYs, 1.31 times higher for persons with 15–30 PYs and 1.52 times higher for persons with >30 PYs. Compared to nondrinkers, the risks were 1.60 times higher for 200–400 g of alcohol per week and 1.63 times higher for >400 g/week. Compared to the physically inactive group, the minimally active group had a 0.80 times lower risk of metabolic syndrome and the HEPA group had a 0.75 times lower risk of metabolic syndrome. Compared to normal weight persons, the risks were 4.67 times higher for obese persons. Compared to no family history, a family history of diabetes was associated with a 1.45 times higher risk of metabolic syndrome.
Table 4Factors Influencing Metabolic Syndrome Among Persons With Physical Disabilities.
Variables
Classifications
Adjusted OR
CI
p
Sex
Male
1
Female
1.66
1.39–1.99
<.001
Age (yr)
20–44
1
45–64
1.22
0.99–1.50
.055
≥65
2.14
1.71–2.67
<.001
Income
0–2
1
3–7
0.83
0.69–0.98
.035
8–10
0.93
0.78–1.11
.462
Smoking (pack-year)
0
1
<15
1.23
1.01–1.52
.045
15–30
1.31
1.05–1.63
.015
>30
1.52
1.19–1.93
.001
Alcohol use/week (g/wks)
0
1
<200
0.98
0.83–1.16
.851
200–400
1.60
1.26–2.02
<.001
>400
1.63
1.23–2.16
.001
Physical activity
Inactive
1
Minimally
0.80
0.69–0.92
.003
Health enhancing
0.75
0.59–0.95
.019
BMI (kg/m2)
18.5–22.9
1
<18.5
0.52
0.26–1.06
.074
≥23
4.67
3.94–5.54
<.001
Family history of BP
0
1
1
1.07
0.88–1.29
.464
Family history of DM
0
1
1
1.45
1.17–1.79
<.001
BMI = body mass index; BP = blood pressure; CI = confidence interval; DM = diabetes mellitus; OR = odds ratio.
The prevalence of metabolic syndrome was 31.5% among persons with physical disabilities, which is lower than the prevalence of 43.1% among disabled persons that was reported by Ko et al. [
Disparities in health-risk behaviors, preventive health care utilizations, and chronic health conditions for people with disabilities: The Korean national health and nutrition examination survey.
Disparities in health-risk behaviors, preventive health care utilizations, and chronic health conditions for people with disabilities: The Korean national health and nutrition examination survey.
] was higher than the overall prevalence from the present study, which evaluated disabled persons who were aged ≥20 years. The present study also revealed component prevalence of 46.9% for high blood pressure, 43.1% for high blood sugar, and 40.7% for abdominal obesity, which are noticeably different from the prevalence of 32.9% for high blood pressure, 25.1% for high blood sugar, and 31.7% for abdominal obesity among nondisabled persons [
]. Thus, it appears that metabolic syndrome and its components are more prevalent among persons with physical disabilities, compared to nondisabled persons. However, it is important to note that the criteria for metabolic syndrome are diverse and continuously evolving, and those studies frequently use different diagnostic criteria [
The present study revealed that the factors influencing metabolic syndrome among disabled persons were sex, age, smoking, drinking, physical activity, BMI, and a family history of diabetes. Women had 1.66 times higher risk of metabolic syndrome than men, and similar results were observed in Hsu et al.'s study of intellectually disabled persons [
]. In addition, the risk of metabolic syndrome is significantly higher among women aged >50 years than among men aged >50 years, because estrogen deficiency during menopause leads to increased abdominal obesity and decreased HDL-C levels [
]. Therefore, women who are aged >50 years and physically disabled require management of their blood lipid levels and obesity to prevent metabolic syndrome.
The risk of metabolic syndrome increased by 2.14 times at ages of ≥65 years. Similar results were observed by Park et al. [
], who reported that the risk was 6.07 times higher at the ages of ≥60 years than at the ages of 20–39 years. Age-related increases in abdominal obesity and blood pressure appear to significantly influence the prevalence of metabolic syndrome [
]. Therefore, metabolic syndrome management programs that are implemented for high-risk groups during early adulthood may be effective in preventing the development of metabolic syndrome and cardiocerebrovascular diseases.
Compared to nonsmokers, smokers exhibited a dose-dependent increase in the risk of metabolic syndrome. Similarly, Jung et al. [
] reported a 1.45 times higher risk of metabolic syndrome at greater amounts of smoking. In addition, smoking is associated with trends toward higher triglyceride levels and lower HDL-C levels in the blood [
], which suggests that smoking cessation is needed to reduce the risk of metabolic syndrome or to ameliorate existing metabolic syndrome. However, the risk of metabolic syndrome persists after smoking cessation because of increased body weight that is caused by increased carbohydrate intake and fasting insulin resistance [
]. Therefore, exercise and diet therapy should be incorporated to prevent weight gain at the start of smoking cessation.
Compared to the nondrinking group, the group that consumed ≥200 g of alcohol per week (2.3 bottles of Soju) had an increased risk of metabolic syndrome. Kim et al. [
] have also reported that the risk of metabolic syndrome is 1.47 times higher for persons who consume >30 g/day on average than for nondrinking persons. Furthermore, the risk of high blood pressure increases at >200 g of alcohol consumption per week, and there is a 5 times higher risk of abdominal obesity at 400 g/week [
]. Increased alcohol consumption is associated with dose-dependent increased risks of low HDL-C, abdominal obesity, high triglycerides, high blood pressure, and high blood sugar, which lead to a higher prevalence of metabolic syndrome [
]. Moreover, disabled persons have a higher risk of alcohol abuse and dependency than nondisabled persons, which is related to their physical pain, activity limitations, problems with self-image, social discrimination, anxiety, and depression [
]. Therefore, disabled persons who excessively consume alcohol require active intervention.
Compared to the physically inactive group, the minimally active group had a 0.80 times lower risk of metabolic syndrome and the HEPA group had a 0.75 times lower risk of metabolic syndrome. Jung et al. [
] also reported that physical inactivity was associated with a 1.70 times higher risk of metabolic syndrome (vs. a group that performed physical activity at least 5 days/week), and Kim et al. [
] reported that their HEPA group had a 0.65 times lower risk of metabolic syndrome than their inactive group. In this context, physical activity can prevent metabolic syndrome because it reduces abdominal obesity and triglycerides levels and increases HDL-C levels [
]. Therefore, various strategies should be considered to promote physical activity among disabled persons, such as providing information regarding physical activities, developing and implementing of life sports programs, building related infrastructure, and supporting club members and leaders. In addition, even minimal activity among disabled persons can help reduce the risk of metabolic syndrome. Therefore, it may be useful to help disabled persons, who may not be able to perform prolonged physical activity, understand that walking is a good aerobic physical activity and to encourage them to perform walking or bodily movement that is customized to their physical condition.
Among disabled persons, BMI was the most significant factor influencing metabolic syndrome, with a 4.67 times higher risk of metabolic syndrome for obese persons than for normal weight persons. Similarly, Park et al. [
] reported that the risk of metabolic syndrome is 20.35 times higher for obese persons than for normal weight persons. Furthermore, 67.1% of disabled persons with metabolic syndrome are obese, and the risk of metabolic syndrome increased sharply in the obese group, which highlights the importance of weight control in preventing and managing metabolic syndrome. Physical disabilities can be caused by inactivity and muscle atrophy, which leads to physiological changes in body composition and energy metabolism and subsequently to obesity [
]. However, preventing and managing obesity can be difficult because disabled persons feel uncomfortable performing and subsequently avoid health-promoting behaviors, such as physical activity [
]. Therefore, active education regarding the risks of obesity may be useful for changing the perceptions regarding activity among disabled persons, as well as interventions that target regular health examinations, periodic physical activity programs, appropriate eating habits, and stress management programs.
In the present study, a family history of diabetes was associated with an increased risk of metabolic syndrome. Jung et al. [
] have also reported that a family history of diabetes was associated with a 1.50 times higher risk of metabolic syndrome. These findings suggest that genetic and family factors play important roles in the development of metabolic syndrome and highlight the need for regular health examinations and management among disabled persons with a family history of diabetes.
The majority of disabled persons have chronic diseases that are related to their limited physical functions and are vulnerable to the risk of metabolic syndrome. As few studies have examined metabolic syndrome among disabled persons, the present study provides useful information regarding the prevalence and influencing factors of metabolic syndrome among persons with physical disabilities. However, the present study also has several limitations. First, the data were obtained from an NHIS cohort of disabled persons, and it is likely that these individuals had an interest in health, which raises the possibility that the findings may not reflect the overall population of disabled Korean persons. However, it is possible that this risk was minimized because the NHIS provides the health examinations free of charge. Second, the study used a cross-sectional design, which precludes any interpretation of the causality of the associations that were observed. Thus, it may be useful to evaluate these associations using a longitudinal cohort study. Third, despite examining many of the known factors that influence metabolic syndrome, the present study did not examine psychological influencing factors (e.g., stress and subjective health status) and type of physical disability because they are not included in the NHIS health information survey. Therefore, further studies are needed to examine these factors. Nevertheless, the present study provided basic data for the development and implementation of health behavior education and intervention programs, which could help prevent and manage metabolic syndrome among persons with physical disabilities.
Conclusion
The present study used NHIS data to determine the prevalence and influencing factors of metabolic syndrome among Korean persons with physical disabilities. The prevalence in this population was 31.5%, and the influencing factors were female sex, age of ≥65 years, smoking, consuming ≥200 g of alcohol per week, physical activity, obesity, and a family history of diabetes. The most significant risk factors were obesity and older age, while a protective effect was observed among individuals who performed physical activity. Therefore, early detection and treatment of obesity through regular checkups, implementation of programs that target eating habits and physical activities, and support to perform regular physical activity are recommended for preventing metabolic syndrome among persons with physical disabilities. However, given the inherent limitations of this cross-sectional study, longitudinal studies are needed to verify the factors influencing metabolic syndrome among persons with physical disabilities and to examine the psychological variables that were not examined in the present study.
Conflicts of interest
The authors declare no conflict of interests.
Acknowledgments
This study was supported by Dong-A university research grant.
References
Kim S.
Lee Y.
Hwang J.
Oh M.
Lee M.
Lee N.
et al.
2014 disabled survey report.
Korea Institute for Health and Social Affairs,
Sejong2014 Dec: 2014-2073 (Report No.: Policy Report)
Health disparities among adults with developmental disabilities, adults with other disabilities, and adults not reporting disability in North Carolina.
Disparities in health-risk behaviors, preventive health care utilizations, and chronic health conditions for people with disabilities: The Korean national health and nutrition examination survey.
Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity.
30498-X&id=gr1.jpg){kind=link}