Warning: fopen(/home/virtual/epih/journal/upload/ip_log/ip_log_2024-12.txt): failed to open stream: Permission denied in /home/virtual/lib/view_data.php on line 95 Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 96 Physical activity level in Korean adults: the Korea National Health and Nutrition Examination Survey 2017
Skip Navigation
Skip to contents

Epidemiol Health : Epidemiology and Health

OPEN ACCESS
SEARCH
Search
Advanced Search
mobile menu button

Articles

Page Path
HOME > Epidemiol Health > Volume 41; 2019 > Article
Original Article
 Physical activity level in Korean adults: the Korea National Health and Nutrition Examination Survey 2017
Ki-Yong Anorcid
Epidemiol Health 2019;41:e2019047.
DOI: https://doi.org/10.4178/epih.e2019047
Published online: November 9, 2019

Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, AB, Canada

Correspondence: Ki-Yong An  Faculty of Kinesiology, Sport, and Recreation, University of Alberta, 1-115 University Hall, University of Alberta, Edmonton, AB T6G2H9, Canada  E-mail: kiyong1@ualberta.ca
• Received: September 10, 2019   • Accepted: November 9, 2019

©2019, Korean Society of Epidemiology

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

prev next
  • 36,877 Views
  • 261 Download
  • 22 Web of Science
  • 20 Crossref
  • 21 Scopus
Full Article

Download PDF Download PDF

  • OBJECTIVES
    This study investigated physical activity (PA) participation based on demographic, physical, and psychological variables in Korean adults.
  • METHODS
    Participants were divided into four groups (combined, aerobic only, resistance only, and neither) based on meeting the PA guidelines using moderate and vigorous PA time and resistance exercise frequency from the Korea National Health and Nutrition Examination Survey 2017. The association between meeting the PA guidelines and demographic, medical, fitness, lifestyle, and psychological variables were analyzed using complex samples crosstabs and a general linear model.
  • RESULTS
    Of the 5,820 Korean adults, 66.0% did not meet any of the guidelines. Among demographic factors, sex, age, marital status, income, education level, occupation, and employment status were associated with meeting the PA guidelines. Chronic disease prevalence, weight, waist circumference, body mass index, diastolic blood pressure, glucose, high-density lipoprotein and triglyceride levels, hand-grip strength, resting heart rate, and family history of chronic disease in the medical and fitness variables; frequency of drinking and eating breakfast, total calorie, water, protein, and fat intake in the lifestyle variables; and perceived stress, depression, suicidal thoughts, and quality of life in the psychological variables were associated with meeting PA guidelines.
  • CONCLUSIONS
    Most Korean adults participate in insufficient PA. Moreover, individuals who are socially underprivileged, have low-income or poor physical and mental health conditions participated in relatively less PA. Our findings suggest that government and individual efforts are required to increase PA and resolve health inequality in Korean adults.
  • Keywords: Exercise, Health equity, Sedentary behavior, Health, Adult
Exercise and physical activity (PA) that prevent obesity and various chronic diseases and improve anxiety and depression, are cost-effective ways to enhance physical and mental health without any side effects [1,2]. The World Health Organization (WHO) has targeted the reduction in the prevalence of physical inactivity as one of the goals of global action plan 2013-2020 and is working to decrease the population of people with insufficient PA worldwide [3]. With the increasing importance of PA, the USA, Canada, Australia, and several European countries develop PA guidelines at the national level to encourage people to participate in more PA [4-8]. Additionally, there has been extensive research to investigate the PA level nationwide to increase people’s engagement in PAs [9-13]. Similarly, an increasing interest in PA in Korea has led to various studies on PA, but since most studies target populations with a specific age, sex or disease and/or include different variables, it is difficult to compare the results and the findings are different between studies. Therefore, it is necessary to examine the general PA level in Korea and the association between PA and various correlates using representative data. Furthermore, since PA is influenced by various environmental, cultural, and social factors [14-17], it should be consistently monitored as these factors change. Nevertheless, few studies [18,19] have reported the PA level in Korean using representative data.
Therefore, the present study aims to investigate the PA participation in Korean adults based on meeting the WHO PA guidelines according to socio-demographic, medical-related and health-related, lifestyle, and psychological variables using the Korea National Health and Nutrition Examination Survey (KNHANES) 2017 dataset.
Data collection and participants
KNHANES is a nationwide health and nutrition survey conducted annually by trained specialists under the supervision of the Korea Centers for Disease Control and Prevention (KCDC). The survey consists of a health questionnaire survey, an examination survey, and a nutrition survey. The health questionnaire survey and examination surveys were conducted at mobile examination centers, while the nutrition survey was conducted by visiting the primary sampling unit in person. In the health questionnaire surveys, data for education, economic activity, disease prevalence, and healthcare utilization and the entire nutrition survey were collected by a face-to-face interview, and data for health behaviors including smoking and drinking were collected by self-reported questionnaires. Additionally, a health examination was conducted by direct measurement, observation, and specimen analysis. Of the total 8,127 participants of the 2017 survey, 5,820 adults aged 19 years and over who had responded to the PA survey were included in this study.
Physical activity assessment
The PA level was measured using the Korean version of the modified Global Physical Activity Questionnaire (GPAQ) developed by the WHO, which includes the categories of weekly walking and resistance exercise added to the original GPAQ. The aerobic PA level was calculated as the sum of all PAs during leisure time and at work. To calculate the time spent on moderate-to-vigorous aerobic physical activity (MVPA) in minutes, we first converted the time spent weekly on vigorous aerobic activity into minutes, doubled the amount considering the metabolic equivalents according to activity intensity and then added the time spent weekly on moderate aerobic activity minutes. Resistance exercise frequency was measured as the number of days in a week. The subjects were divided into the following four groups based on their compliance with the WHO guidelines on aerobic PA and resistance exercise, recommended to both adults aged 18-64 years and the elderly aged over 65 years: (1) Aerobic only (≥150 min/wk of moderate aerobic activity, ≥75 min/wk of vigorous aerobic activity, or an equivalent combination of the two), (2) Resistance only (at least 2 d/wk of resistance exercises, (3) Combined (meeting both aerobic and resistance exercise guidelines), and (4) Neither (meeting neither guidelines).
Assessment of correlates
We analyzed the subject’s compliance with the PA guidelines based on the socio-demographic, medical-related and health-related, lifestyle and psychological variables. The socio-demographic variables included sex, age, marital status, income, location, educational level, occupation, job status, a position at work, and employment status. The medical-related and health-related variables included chronic disease prevalence, cancer prevalence, weight, waist circumference (WC), body mass index (BMI), blood pressure, fasting glucose, total cholesterol (TC), high-density lipoprotein (HDL), triglyceride (TG) levels, hand-grip strength (the average of three measurements in the dominant hand) [20], resting heart rate (RHR), and family history of chronic disease. Lifestyle variables included smoking, drinking, sleep time, frequency of breakfast per week, total energy, water, carbohydrate, protein, and fat intake per day. Psychological variables included perceived stress, past history of depression lasting over two weeks, current depression prevalence, suicidal thoughts within the past year, past history of psychological counseling, and the five dimensions of health-related quality of life (HRQoL) such as mobility, self-care, usual activity, pain/discomfort, and anxiety/depression.
Statistical analysis
All statistical analyses were conducted using a complex sample analysis. We used the Complex Samples Crosstabs to analyze the relationship between correlates and compliance with PA guidelines for nominal variables and the complex samples general linear model (CSGLM) for continuous variables. In addition, we also used the CSGLM to analyze the group differences in moderate-to-vigorous PA time and resistance exercise frequency for each variable. For nominal variables with uneven distribution, we redefined the categories for analysis (e.g., marital status: not married vs. living together after marriage vs. separated/widowed/divorced after marriage; HRQoL: no problem vs. any problems). All analyses were conducted using SPSS version 25 (IBM Corp., Armonk, NY, USA).
Ethics statement
KNHANES has been conducting without approval by the research ethics review committee because it is considered the research for public welfare which is conducted by the Korean government since 2015.
Table 1 shows the association between compliance with the PA guidelines and the socio-demographic variables. Of the total participants, most were in the neither group (66.0%), followed by resistance only (15.7%), combined (9.8%), and aerobic only groups (8.5%). The subjects’ compliance with the PA guidelines showed a significant correlation with sex (p<0.001), age (p<0.001), marital status (p<0.001), total household income (p<0.001), education level (p<0.001), occupation (p<0.001), and employment status (p=0.010) among the socio-demographic variables. In particular, among females aged over 65 years, those living without their spouse after marriage, in the lowest income group and education level, and had labor job demonstrated the lowest level of MVPA and resistance exercise frequency, also contingent workers tended to have lower MVPA level than regular workers.
Table 2 shows the association between compliance with the PA guidelines and the medical-related and health-related variables. The subjects’ compliance with the PA guidelines was significantly associated with chronic disease (p<0.001), weight (p<0.001), WC (p=0.005), BMI (p=0.001), diastolic blood pressure (p<0.001), fasting glucose levels (p<0.001), HDL levels (p=0.001), TG levels (p<0.001), hand-grip strength (p<0.001), RHR (p<0.001), and family history of chronic disease (p=0.001). The MVPA level was relatively lower for those with ≥2 chronic diseases, ≥1 cancer type, and a WC ≥90 cm for males and ≥80 cm for females. On the other hand, participants in the obesity group (BMI≥25.0 kg/m2) compared to the underweight group (BMI<18.5 kg/m2) or those with a family history of chronic disease, showed higher MVPA levels. In addition, those with a WC of ≥90 cm for males and ≥80 cm for females compared to normal WC or a BMI≥25.0 kg/m2 compared to the normal or overweight groups participated in resistance exercise relatively less.
Table 3 shows the subjects’ compliance with the PA guidelines in association with their lifestyle variables. The subjects’ compliance with the PA guidelines showed a significant correlation with drinking (p<0.001) and daily intake of total energy (p<0.001), water (p<0.001), protein (p<0.001), and fat (p<0.001). The MVPA and resistance exercise levels were higher for those drinking more than twice a week than for those who have not been drinking in the past year.
Table 4 shows the subjects’ compliance with the PA guidelines in association with HRQoL and psychological variables. The subjects’ compliance with the PA guidelines showed a significant correlation with perceived stress (p=0.015), past history of depression lasting over two weeks (p<0.001), suicidal thoughts within one year (p=0.026), and HRQoL for mobility (p<0.001), self-care (p<0.001), daily activity (p<0.001), pain/discomfort (p<0.001), and anxiety/depression (p=0.002). Moreover, those with the highest stress levels, past history of depression lasting over two weeks, current depression, suicidal thoughts within one year and any problems with mobility, self-care, pain/discomfort, and anxiety/depression had lower levels of MVPA than others. The level of resistance exercise frequency was lower for those with the highest stress levels, depression lasting over two weeks, suicidal thoughts within a year and problems with mobility, self-care, daily activity, pain/discomfort, and anxiety/depression than those without.
This study analyzed the Korean adults’ compliance with PA guidelines in association with the socio-demographic, medical-related and health-related, lifestyle, and psychological variables. The results revealed several characteristics of PA participation among Korean adults. First, the Korean adults demonstrated very low compliance with the PA guidelines. Of the total participants analyzed, 66.0% failed to comply with neither aerobic exercise nor resistance exercise. According to Yang [19], the proportion of Korean adults with insufficient PA was 24.6% in 2008, which continued to increase and reached 42.9% by 2014. This is lower than the proportion of physically inactive adults worldwide reported in 2012, which was 31.1% [21]. Given the various benefits of PA on physical and mental health improvement [1,2], the government’s efforts are urgently required to encourage PA and create an environment for PA participation. Once the PA level increases, then it will not only improve public health but also reduce the costs of medical care.
Second, the PA level in Korean adults significantly differed depending on health inequality factors. Older females with lower income and education levels, in other words, a minority group, showed relatively lower compliance with the PA guidelines. These results imply that socioeconomic factors, as well as physiological factors, have a significant impact on healthy behavior. The difference in PA levels induced by such socioeconomic factors can trigger a vicious cycle of health inequality. Insufficient PA leads to chronic illnesses and weakened physical/mental health, which in turn leads to increased medical costs and limited socioeconomic activities due to illness that can easily circle back to physical inactivity and health inequality. To end this cycle, we need substantial and specific solutions like providing free education on PA in schools and health centers or media-based campaigns promoting PA participation.
Third, participants with a high risk of chronic diseases and poor mental health had lower PA levels than healthier participants, even though they needed PA more. Since the present study is a cross-sectional study, the causality between PA and the various correlates cannot be identified. In other words, it is possible either poor physical/mental health could cause physical inactivity or vice versa. In this study, however, we clarified the findings of previous studies that there is a significant relationship between PA and various chronic diseases [22,23], as well as mental health [24,25]. With the collective effort of medical professionals in emphasizing the importance of PA and recommending the appropriate level and method of PA in medical institutions, the PA levels of the Korean adults could be markedly increased.
Furthermore, the results of this study showed that the PA level was low not only in the obesity group but also in the underweight group. Previous studies have reported that both underweight and obese people have relatively higher mortality rates than people with normal weight [26,27]. Recently, people in Korea tend to prefer a skinny body shape and attempt extreme diets to reduce weight using unhealthy methods. To maintain good health conditions, efforts to increase PA levels must be accompanied by efforts to maintain healthy body weight.
Additionally, our findings are consistent with previous studies [28,29] that reported that physical fitness is associated with PA levels. Hand-grip strength is the only fitness factor in the KNHANES. There are a few factors related to lung function but they are inappropriate to present cardiopulmonary fitness and the abundance of missing values makes them difficult to be used for this study. RHR, another fitness-related factor used in this study is directly linked to aerobic exercise. Although we cannot deem RHR as an aerobic fitness factor without considering the age and fitness level of an individual, the fact that aerobic exercise increases cardiac output and decreases RHR suggests that it is possible to indirectly predict aerobic fitness by RHR. Moreover, since RHR is closely related to risk factors of various chronic diseases such as diabetes, cardiovascular diseases, and metabolic syndrome [30-32], it can act as an important health variable by itself. As physical fitness is highly linked to many health risks, the inclusion of aerobic fitness factors in the KNHANES will greatly help to monitor and examine the physical health of the Korean people.
Furthermore, we identified that a family history of chronic disease, drinking, and diet-related variables were associated with PA participation. Surprisingly, however, people with a family history of chronic disease, heavy drinking, and high-calorie intake tended to participate in more PA. It can be explained by the fact that a family history of chronic disease may motivate exercise, males tend to be heavier drinkers than females, and the overall energy intake in Korean adults is not that high. Nevertheless, further research and various statistical analyses are required to accurately interpret these relationships.
A limitation of this study is that it is a cross-sectional study with limited assessment variables (health-related fitness and medical variables). Our study, however, can provide basic data for PA research in Korean adults with its large sample size, analysis of correlations with various classifications of variables, the distinction between aerobic and resistance exercise guidelines, and most importantly, analysis of the latest data showing the overall PA participation among Korean adults.
In conclusion, this study investigated the PA levels in Korean adults in association with various correlates, which revealed that Korean adults participate in definitely low levels of PA. Moreover, PA engagement was not only associated with physiological factors such as sex, age, lifestyle, physical health-related variables, but also with diverse socioeconomic and environmental factors including health inequality-related factors. To improve public health in Korea, we need both the collective effort of the government, educational, and medical institutions and individual efforts to recognize the importance of PA and its practice.
Korean version is available at http://www.e-epih.org/.
epih-41-e2019047-supplementary.pdf

The author has no conflicts of interest to declare for this study.

AUTHOR CONTRIBUTIONS

All work was done by KYA.

None.
Table 1.
Association between PA and socio-demographic variables in Korean adults
Variables % Neither Resistance only Aerobic only Combined p-value PA1
MV (min/wk) Resistance (d/wk)
Total 4,021 [26,136,896 (66.0)] 880 [6,214,780 (15.7)] 436 [3,365,609 (8.5)] 483 [3,893,229 (9.8)] 83.5±4.0 0.82±0.03
Sex
 Male 49.6 1,532 [11,363,150 (57.9)] 521 [3,819,234 (19.4)] 216 [1,846,260 (9.4)] 299 [2,612,582 (13.3)] <0.001 109.5±6.61 1.09±0.041
 Female (reference) 50.4 2,489 [14,773,746 (74.0)] 359 [2,395,546 (12.0)] 220 [1,519,349 (7.6)] 184 [1,280,647 (6.4)] 57.9±3.7 0.56±0.03
Age (yr)
 19-44 45.4 1,306 [11,022,509 (61.3)] 313 [2,732,177 (15.2)] 204 [1,802,384 (10.0)] 256 [2,419,007 (13.5)] <0.001 111.7±6.61 0.86±0.041
 45-64 38.1 1,513 [9,964,925 (66.0)] 353 [2,473,339 (16.4)] 189 [1,372,764 (9.1)] 181 [1,285,525 (8.5)] 72.7±4.71 0.82±0.04
 ≥65 (reference) 16.5 1,201 [5,149,462 (78.8)] 214 [1,009,263 (15.4)] 43 [190,460 (2.9)] 46 [188,697 (2.9)] 30.9±4.9 0.71±0.05
Marital status
 Not married 23.8 585 [5,365,207 (56.9)] 170 [1,635,760 (17.3)] 89 [907,329 (9.6)] 151 [1,521,406 (16.1)] <0.001 126.6±10.41 1.04±0.061
 Married/live together 65.5 2,746 [17,288,916 (66.7)] 633 [4,142,231 (16.0)] 319 [2,291,515 (8.8)] 303 [2,197,358 (8.5)] 76.1±4.31 0.79±0.031
 Married/live separately (reference) 10.7 688 [3,469,540 (81.7)] 77 [436,789 (10.3)] 28 [166,765 (3.9)] 29 [174,465 (4.1)] 33.5±5.0 0.52±0.05
Income
 High 32.0 1,021 [7,396,851 (58.6)] 258 [1,962,602 (25.6)] 186 [1,509,455 (12.0)] 220 [1,745,228 (13.8)] <0.001 115.0±6.71 0.93±0.041
 Mid-high 29.7 1,054 [7,613,712 (65.0)] 265 [1,926,915 (16.4)] 135 [1,003,437 (8.6)] 134 [1,174,657 (10.0)] 85.2±7.11 0.84±0.041
 Mid-low 23.0 1,005 [6,309,395 (69.5)] 213 [1,459,465 (16.1)] 82 [620,262 (6.8)] 94 [688,379 (7.6)] 65.8±7.9 0.77±0.05
 Low (reference) 15.3 929 [4,718,458 (78.0)] 142 [843,942 (13.9)] 32 [220,666 (3.6)] 34 [269,728 (4.5)] 41.7±9.8 0.64±0.08
Location
 Urban 85.0 3,190 [21,891,690 (65.0)] 761 [5,391,430 (16.0)] 381 [2,933,863 (8.7)] 436 [3,447,515 (10.2)] 0.143 83.6±4.2 0.83±0.03
 Rural (reference) 15.0 831 [4,245,205 (71.4)] 119 [823,350 (13.8)] 55 [431,745 (7.3)] 47 [445,714 (7.5)] 82.8±13.4 0.77±0.10
Education level
 University/college 43.6 1,315 [10,021,785 (58.1)] 390 [3,007,345 (17.4)] 242 [2,009,433 (11.6)] 263 [2,213,219 (12.8)] <0.001 107.8±6.21 0.91±0.041
 High school 33.0 1,173 [8,459,210 (64.9)] 289 [2,105,752 (16.1)] 141 [1,088,624 (8.3)] 174 [1,389,891 (10.7)] 88.8±6.61 0.88±0.051
 Middle school 8.8 437 [2,565,852 (74.0)] 95 [565,882 (16.3)] 31 [163,266 (4.7)] 23 [173,569 (5.0)] 56.6±17.51 0.84±0.101
 Elementary school (reference) 14.6 1,088 [5,037,117 (87.1)] 105 [527,500 (9.1)] 22 [104,285 (1.8)] 23 [116,549 (2.0)] 16.0±2.5 0.42±0.04
Occupation
 Manager/profession 17.1 511 [3,927,068 (58.3)] 152 [1,231,194 (18.3)] 82 [724,036 (10.7)] 106 [859,419 (12.7)] <0.001 107.3±9.31 0.94±0.061
 Office job 12.9 404 [3,066,667 (60.3)] 114 [877,095 (17.3)] 67 [554,935 (10.9)] 70 [585,138 (11.5)] 93.1±8.71 0.88±0.081
 Inoccupation (housewife/students) 35.1 1,623 [9,293,231 (67.0)] 334 [2,110,621 (15.2)] 145 [1,088,174 (7.8)] 179 [1,376,645 (9.9)] 79.8±6.71 0.85±0.051
 Service industry 12.0 452 [3,124,938 (65.8)] 101 [764,866 (16.1)] 55 [394,778 (8.3)] 52 [464,145 (9.8)] 78.8±10.4 0.82±0.081
 Engineer 11.8 398 [3,195,767 (68.6)] 96 [731,258 (15.7)] 42 [322,911 (6.9)] 46 [410,697 (8.8)] 75.7±12.1 0.78±0.081
 Agriculture/forestry/fishery 3.2 237 [1,011,866 (79.0)] 27 [177,091 (13.8)] 11 [58,774 (4.6)] 4 [33,708 (2.6)] 55.3±22.3 0.49±0.08
 Labor (reference) 7.9 389 [2,451,315 (78.7)] 55 [309,273 (9.9)] 32 [196,644 (6.3)] 25 [155,998 (5.0)] 54.3±9.4 0.53±0.06
Job status
 Employed 65.0 2,393 [16,805,826 (65.4)] 546 [4,104,159 (16.0)] 291 [2,277,435 (8.9)] 304 [2,516,584 (9.8)] 0.582 85.6±4.9 0.80±0.03
 Unemployed (reference) 35.0 1,623 [9,293,231 (67.0)] 334 [2,110,621 (15.2)] 145 [1,088,174 (7.8)] 179 [1,376,645 (9.9)] 79.8±6.7 0.85±0.05
Position in work
 Employer/self-ownership 23.1 593 [3,827,031 (64.5)] 158 [1,112,280 (18.8)] 76 [523,433 (8.8)] 62 [468,944 (7.9)] 0.069 73.1±6.91 0.87±0.06
 Unpaid family worker 3.9 148 [757,704 (75.2)] 21 [139,975 (13.9)] 11 [65,065 (6.5)] 7 [44,828 (4.4)] 56.6±21.7 0.59±0.16
 Employee (reference) 73.0 1,652 [12,221,091 (65.1)] 367 [2,851,904 (15.2)] 204 [1,688,936 (9.0)] 235 [2,002,812 (10.7)] 91.1±5.8 0.79±0.04
Employment status 51.5
 Regular (permanent) worker 739 [5,975,330 (61.9)] 181 [1,515,160 (15.7)] 120 [1,009,134 (10.5)] 135 [1,155,242 (12.0)] 0.010 103.2±8.21 0.81±0.05
 Contingent worker (reference) 48.5 913 [6,245,760 (68.6)] 186 [1,336,744 (14.7)] 84 [679,802 (7.5)] 100 [847,570 (9.3)] 78.3±7.4 0.78±0.05

Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

PA, physical activity; MV, moderate to vigorous aerobic.

1 A p-value was calculated versus reference group.

* p<0.05.

Table 2.
Association between PA and medical- and health-related variables in Korean adults
Variables % Neither Resistance only1 Aerobic only1 Combined1 p-value PA1
MV (min/wk) Resistance (d/wk)
Chronic disease (n)2
 None 67.6 2,289 [17,014,375 (63.6)] 526 [4,052,075 (15.1)] 314 [2,546,704 (9.5)] 368 [3,149,127 (11.8)] <0.001 97.1±5.0* 0.84±0.03
 1 17.5 852 [4,760,985 (68.5)] 188 [1,204,742 (17.3)] 70 [491,257 (7.1)] 77 [492,554 (7.1)] 65.6±5.8* 0.82±0.05
 ≥2 (reference) 14.9 880 [4,361,535 (73.9)] 166 [957,962 (16.2)] 52 [327,648 (5.6)] 38 [251,548 (4.3)] 43.1±6.3 0.73±0.06
Cancer
 None 98.1 3,925 [25,592,704 (65.8)] 861 [6,113,361 (15.7)] 428 [3,321,728 (8.5)] 474 [3,847,068 (9.9)] 0.310 84.1±4.1* 0.82±0.03
 ≥1 (reference) 1.9 96 [544,192 (74.0)] 19 [101,418 (13.8)] 8 [43,881 (6.0)] 9 [46,161 (6.3)] 52.0±11.7 0.73±0.15
Weight (kg) - 64.0±0.3 66.0±0.5* 69.0±0.8* 68.0±0.7* <0.001 NA NA
Waist circumference (cm)3 81.9±0.3 81.7±0.4 82.6±0.6 80.1±0.6* 0.005 NA NA
 Normal 64.8 2,324 [15,815,041 (61.9)] 607 [4,372,279 (17.1)] 276 [2,196,212 (8.6)] 384 [3,152,120 (12.3)] <0.001 95.8±5.6* 0.95±0.03*
 Obesity (reference) 35.2 1,673 [10,152,017 (73.3)] 270 [1,821,628 (13.1)] 159 [1,165,309 (8.4)] 97 [719,334 (5.2)] 61.5±4.4 0.58±0.03
BMI (kg/m2)4 23.9±0.1 23.7±0.1 24.6±0.2* 23.7±0.2 0.001 NA NA
 Underweight 4.2 173 [1,238,618 (75.7)] 29 [207,971 (12.7)] 6 [43,594 (2.7)] 19 [145,125 (8.9)] <0.001 52.3±11.4* 0.64±0.12
 Normal weight 38.7 1,531 [10,038,066 (66.0)] 360 [2,533,130 (16.7)] 147 [1,139,104 (7.5)] 192 [1,499,179 (9.9)] 74.0±5.5 0.84±0.04*
 Overweight 22.6 880 [5,483,400 (61.5)] 215 [1,570,909 (17.6)] 97 [755,233 (8.5)] 129 [1,101,358 (12.4)] 105.4±10.1 1.03±0.06*
 Obesity (reference) 34.5 1,408 [9,153,730 (67.4)] 275 [1,894,259 (13.9)] 185 [1,420,723 (10.5)] 141 [1,118,727 (8.2)] 84.5±6.1 0.69±0.04
Blood pressure (mmHg)
 SBP - 117.6±0.4 117.1±0.7 116.8±0.8 115.4±0.7* 0.065 NA NA
 DBP - 75.2±0.2 76.2±0.5* 77.8±0.5* 75.9±0.5 <0.001 NA NA
Blood profile (mg/dL)
 Glucose - 100.7±0.5 99.3±0.7 97.3±0.9* 95.3±0.7* <0.001 NA NA
 TC - 194.1±0.8 191.0±1.6 196.1±2.3 191.6±1.8 0.135 NA NA
 HDL - 50.9±0.2 51.4±0.4 50.8±0.8 53.4±0.6* 0.001 NA NA
 TG - 137.1±2.3 133.4±4.5 149.9±7.2 117.6±4.6* <0.001 NA NA
Hand-grip strength (kg)5 - 28.4±0.2 32.6±0.4* 32.1±0.6* 35.4±0.6* <0.001 NA NA
RHR (beat/min) - 70.7±0.2 70.1±0.4 68.8±0.5* 67.8±0.6* <0.001 NA NA
Family history
 No 41.2 1,757 [11,352,364 (69.6)] 343 [2,337,394 (14.3)] 144 [1,123,515 (6.9)] 186 [1,489,851 (9.1)] 0.001 74.3±5.0* 0.79±0.04
 Yes (reference) 58.8 2,258 [14,756,927 (63.4)] 536 [3,872,066 (16.6)] 291 [2,238,249 (9.6)] 296 [2,393,505 (10.3)] 90.0±5.4 0.84±0.03

Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

PA, physical activity; MV, moderate to vigorous aerobic; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; HDL, high-density lipoprotein; TG, triglyceride; RHR, resting heart rate; NA, not applicable.

1 A p-value was calculated versus neither or reference group.

2 Chronic disease was counted except for cancer.

3 Waist circumference: obesity ≥90 cm for males and ≥80 cm for females.

4 BMI (kg/m2): underweight <18.5, 18.5≤ normal<23.0, 23.0≤overweight<25.0, obesity≥25.0.

5 Hand-grip strength values are the average of three measurements for the dominant hand (higher value is used for ambidextrous participants).

* p<0.05.

Table 3.
Association between PA and lifestyle variables in Korean adults
Variables % Neither Resistance only1 Aerobic only1 Combined1 p-value PA1
MV (min/wk) Resistance (d/wk)
Smoking
 No 79.1 3,301 [20,446,756 (65.2)] 723 [5,016,478 (16.0)] 365 [2,760,063 (8.8)] 402 [3,116,831 (9.9)] 0.294 84.5±4.5 0.83±0.03
 Yes (reference) 20.9 720 [5,690,140 (68.8)] 157 [1,198,301 (14.5)] 71 [605,546 (7.3)] 81 [776,398 (9.4)] 79.9±8.4 0.77±0.06
Drink
 Never/no within 1 yr 22.7 1,228 [6,710,410 (74.5)] 216 [1,334,565 (14.8)] 78 [517,954 (5.7)] 61 [446,184 (5.0)] <0.001 50.8±7.2* 0.64±0.05*
 ≤1/wk 53.0 1,936 [13,291,122 (63.3)] 453 [3,325,489 (15.8)] 244 [1,898,214 (9.0)] 299 [2,471,272 (11.8)] 93.3±5.2 0.87±0.03
 ≥2/wk (reference) 24.3 857 [6,135,364 (63.8)] 211 [1,554,726 (16.2)] 114 [949,440 (9.9)] 123 [975,773 (10.1)] 92.9±8.0 0.88±0.06
Sleeping time (hr)
 ≥7 63.3 2,544 [16,672,394 (66.7)] 533 [3,788,823 (15.2)] 274 [2,171,065 (8.7)] 291 [2,362,545 (9.5)] 0.326 80.8±4.9 0.80±0.03
 <7 (reference) 36.7 1,456 [9,372,539 (64.6)] 346 [2,421,614 (16.7)] 161 [1,190,699 (8.2)] 191 [1,525,436 (10.5)] 88.6±6.0 0.86±0.04
Frequency of breakfast (d/wk)2
 ≥5 59.6 2,438 [15,872,878 (66.7)] 519 [3,874,866 (16.3)] 232 [1,835,349 (7.7)] 248 [2,212,135 (9.3)] 0.174 75.9±4.7 0.85±0.04
 <5 (reference) 40.4 1,131 [10,384,185 (64.4)] 247 [2,503,065 (15.5)] 145 [1,536,873 (9.5)] 150 [1,689,054 (10.5)] 89.9±7.0 0.79±0.04
Energy intake (kcal/d)2 - 1,892.1±21.5 1,991.2±42.1* 2,028.2±51.7* 2,122.6±60.0* <0.001 NA NA
Water intake (g/d)2 - 1,053.1±17.1 1,149.5±35.7* 1,232.9±31.3* 1,303.5±37.0* <0.001 NA NA
Carbohydrate intake (g/d)2 - 294.9±3.0 306.2±5.6* 304.1±6.2 301.6±7.8 0.120 NA NA
Protein intake (g/d)2 - 70.5±1.0 75.3±2.2* 77.2±2.2* 85.9±3.0* <0.001 NA NA
Fat intake (g/d)2 - 44.4±0.9 47.7±1.4* 53.8±2.7* 57.2±2.7* <0.001 NA NA

Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

PA, physical activity; MV, moderate to vigorous aerobic; NA, not applicable.

1 A p-value was calculated versus neither or reference group.

2 Nutrition survey weighted data.

* p<0.05.

Table 4.
Association between PA and psychological variables in Korean adults
Variables % Neither Resistance only Aerobic only Combined p-value PA1
MV (min/wk) Resistance (d/wk)
Perceived stress
  Barely 13.9 655 [3,660,732 (66.7)] 151 [902,023 (16.4)] 61 [406,281 (7.4)] 74 [521,236 (9.5)] 0.015 77.4±8.6* 0.93±0.07*
A little 57.1 2,196 [14,384,886 (63.7)] 520 [3,711,842 (16.4)] 260 [2,006,379 (8.9)] 300 [2,469,255 (10.9)] 93.3±5.5* 0.90±0.03*
Much 24.5 951 [6,680,008 (68.9)] 180 [1,368,591 (14.1)] 101 [842,758 (8.7)] 97 [810,647 (8.4)] 71.8±5.4* 0.65±0.05
Very much (reference) 4.4 208 [1,349,238 (76.8)] 27 [212,170 (12.1)] 14 [110,190 (6.3)] 11 [85,222 (4.9)] 43.7±7.7 0.46±0.10
Depression over 2 wk
No 88.3 3,444 [22,616,189 (64.8)] 797 [5,621,820 (16.1)] 402 [3,106,487 (8.9)] 439 [3,547,657 (10.2)] <0.001 86.3±4.3* 0.85±0.03*
Yes (reference) 11.7 568 [3,467,406 (74.8)] 81 [572,806 (12.4)] 34 [259,121 (5.6)] 43 [338,703 (7.3)] 63.1±9.1 0.56±0.05
Current depression
No 97.9 3,902 [25,527,907 (65.9)] 856 [6,061,816 (15.6)] 431 [3,338,864 (8.6)] 478 [3,836,926 (9.9)] 0.170 84.5±4.1* 0.82±0.03
Yes (reference) 2.1 119 [608,989 (72.1)] 24 [152,964 (18.1)] 5 [26,745 (3.2)] 5 [56,303 (6.7)] 39.5±13.1 0.77±0.15
Thinking suicide for a year
No 95.3 3,782 [24,679,629 (65.5)] 841 [5,928,594 (15.7)] 421 [3,262,604 (8.7)] 474 [3,802,811 (10.1)] 0.026 85.5±4.2* 0.83±0.02*
Yes (reference) 4.7 230 [1,403,966 (75.6)] 37 [266,032 (14.3)] 15 [103,005 (5.5)] 8 [83,549 (4.5)] 44.8±12.8 0.57±0.11
Psychological counselling for a year
No 97.2 3,892 [25,359,835 (66.0)] 848 [5,992,457 (15.6)] 424 [3,288,442 (8.6)] 471 [3,795,700 (9.9) 0.710 84.3±4.1 0.82±0.03
Yes (reference) 2.8 122 [731,273 (66.4)] 30 [202,169 (18.4)] 12 [77,167 (7.0)] 11 [90,660 (8.2)] 57.8±14.3 0.76±0.12
HRQoL
Mobility
  No problem 89.9 3,335 [22,831,301 (64.1)] 792 [5,717,456 (16.1)] 418 [3,285,001 (9.2)] 464 [3,781,737 (10.6)] <0.001 89.5±4.3* 0.85±0.03*
Any problem (reference) 10.1 686 [3,305,595 (82.7)] 88 [497,323 (12.4)] 18 [80,608 (2.0)] 19 [111,492 (2.8)] 30.5±10.4 0.53±0.06
Self-care
No problem 97.3 3,831 [25,204,176 (65.4)] 861 [6,112,534 (15.9)] 432 [3,335,734 (8.7)] 478 [3,869,807 (10.0)] <0.001 85.2±4.1* 0.83±0.03*
Any problems (reference) 2.7 190 [932,719 (85.7)] 19 [102,246 (9.4)] 4 [29,875 (2.7)] 5 [23,422 (2.2)] 24.4±12.8 0.38±0.08
Usual activity
No problem 94.4 3,654 [24,352,985 (65.1)] 832 [5,963,909 (15.9)] 425 [3,267,270 (8.7)] 471 [3,813,986 (10.2)] <0.001 85.5±4.2 0.84±0.03*
Any problems (reference) 5.6 366 [1,778,745 (80.6)] 48 [250,870 (11.4)] 11 [98,339 (4.5)] 12 [79,243 (3.6)] 49.6±18.8 0.53±0.08
Pain/discomfort
No problem 79.1 2,970 [20,164,281 (64.4)] 691 [4,946,862 (15.8)] 353 [2,754,421 (8.8)] 420 [3,462,990 (11.1)] <0.001 89.6±4.5* 0.86±0.03*
Any problems (reference) 20.9 1,050 [5,969,824 (72.1)] 189 [1,267,918 (15.3)] 83 [611,188 (7.4)] 63 [430,239 (5.2)] 60.7±6.8 0.68±0.05
Anxiety/depression
No problem 92.9 3,634 [24,027,069 (65.3)] 813 [5,798,007 (15.8)] 411 [3,202,848 (8.7)] 464 [3,746,384 (10.2)] 0.002 86.8±4.3* 0.84±0.03*
Any problems (reference) 7.1 384 [2,104,134 (74.3)] 67 [416,773 (14.7)] 25 [162,760 (5.8)] 19 [146,845 (5.2)] 40.6±5.5 0.63±0.08

Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

PA, physical activity; MV, moderate to vigorous aerobic; HRQoL, health-related quality of life.

1 A p-value was calculated versus reference group.

* p<0.05.

  • 1. Sallis RE. Exercise is medicine and physicians need to prescribe it! Br J Sports Med 2009;43:3-4.ArticlePubMed
  • 2. Pedersen BK, Saltin B. Exercise as medicine - evidence for prescribing exercise as therapy in 26 different chronic diseases. Scand J Med Sci Sports 2015;25 Suppl 3:1-72.ArticlePubMed
  • 3. World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013-2020; 2013 [cited 2019 Sep 1]. Available from: https://apps.who.int/iris/handle/10665/94384.
  • 4. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007;39:1423-1434.ArticlePubMed
  • 5. Haskell WL, Kennedy M. The birth of physical activity guidelines for Americans. J Phys Act Health 2008;5:485-487.Article
  • 6. Tremblay MS, Carson V, Chaput JP, Connor Gorber S, Dinh T, Duggan M, et al. Canadian 24-hour movement guidelines for children and youth: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab 2016;41(6 Suppl 3):S311-S327.ArticlePubMed
  • 7. Egger G, Donovan RJ, Giles-Corti B, Bull F, Swinburn B. Developing national physical activity guidelines for Australians. Aust N Z J Public Health 2001;25:561-563.ArticlePubMed
  • 8. Kahlmeier S, Wijnhoven TM, Alpiger P, Schweizer C, Breda J, Martin BW. National physical activity recommendations: systematic overview and analysis of the situation in European countries. BMC Public Health 2015;15:133.ArticlePubMedPMCPDF
  • 9. Kahn JA, Huang B, Gillman MW, Field AE, Austin SB, Colditz GA, et al. Patterns and determinants of physical activity in US adolescents. J Adolesc Health 2008;42:369-377.ArticlePubMed
  • 10. Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008;40:181-188.ArticlePubMed
  • 11. Dowda M, Ainsworth BE, Addy CL, Saunders R, Riner W. Correlates of physical activity among U.S. young adults, 18 to 30 years of age, from NHANES III. Ann Behav Med 2003;26:15-23.ArticlePubMed
  • 12. Juneau CE, Potvin L. Trends in leisure-, transport-, and work-related physical activity in Canada 1994-2005. Prev Med 2010;51:384-386.ArticlePubMed
  • 13. Colley RC, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay MS. Physical activity of Canadian adults: accelerometer results from the 2007 to 2009 Canadian Health Measures Survey. Health Rep 2011;22:7-14.
  • 14. King AC, Castro C, Wilcox S, Eyler AA, Sallis JF, Brownson RC. Personal and environmental factors associated with physical inactivity among different racial-ethnic groups of U.S. middle-aged and older-aged women. Health Psychol 2000;19:354-364.ArticlePubMedPDF
  • 15. Humpel N, Owen N, Leslie E. Environmental factors associated with adults’ participation in physical activity: a review. Am J Prev Med 2002;22:188-199.ArticlePubMed
  • 16. Crespo CJ, Smit E, Andersen RE, Carter-Pokras O, Ainsworth BE. Race/ethnicity, social class and their relation to physical inactivity during leisure time: results from the Third National Health and Nutrition Examination Survey, 1988-1994. Am J Prev Med 2000;18:46-53.ArticlePubMed
  • 17. Marshall SJ, Jones DA, Ainsworth BE, Reis JP, Levy SS, Macera CA. Race/ethnicity, social class, and leisure-time physical inactivity. Med Sci Sports Exerc 2007;39:44-51.ArticlePubMed
  • 18. Yang YJ, Yoon YS, Oh SW, Lee ES. The amount of physical activity of Korean adults measured from the 2001 Korean National Health and Nutrition Survey. J Korean Acad Fam Med 2005;26:22-30 (Korean).
  • 19. Yang YJ. Current status of physical activity and policy proposals of the national level. Korean J Health Educ Promot 2016;33:47-54 (Korean).Article
  • 20. Shiratori AP, Iop Rda R, Borges Júnior NG, Domenech SC, Gevaerd Mda S. Evaluation protocols of hand grip strength in individuals with rheumatoid arthritis: a systematic review. Rev Bras Reumatol 2014;54:140-147.ArticlePubMed
  • 21. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet 2012;380:247-257.ArticlePubMed
  • 22. Warburton DE, Bredin SS. Health benefits of physical activity: a systematic review of current systematic reviews. Curr Opin Cardiol 2017;32:541-556.ArticlePubMed
  • 23. Kruk J. Physical activity in the prevention of the most frequent chronic diseases: an analysis of the recent evidence. Asian Pac J Cancer Prev 2007;8:325-338.PubMed
  • 24. Biddle SJ, Asare M. Physical activity and mental health in children and adolescents: a review of reviews. Br J Sports Med 2011;45:886-895.ArticlePubMed
  • 25. Penedo FJ, Dahn JR. Exercise and well-being: a review of mental and physical health benefits associated with physical activity. Curr Opin Psychiatry 2005;18:189-193.ArticlePubMed
  • 26. Katzmarzyk PT, Craig CL, Bouchard C. Original article underweight, overweight and obesity: relationships with mortality in the 13-year follow-up of the Canada Fitness Survey. J Clin Epidemiol 2001;54:916-920.ArticlePubMed
  • 27. Roh L, Braun J, Chiolero A, Bopp M, Rohrmann S, Faeh D, et al. Mortality risk associated with underweight: a census-linked cohort of 31,578 individuals with up to 32 years of follow-up. BMC Public Health 2014;14:371.ArticlePubMedPMCPDF
  • 28. Seco J, Abecia LC, Echevarría E, Barbero I, Torres-Unda J, Rodriguez V, et al. A long-term physical activity training program increases strength and flexibility, and improves balance in older adults. Rehabil Nurs 2013;38:37-47.ArticlePubMed
  • 29. Lim HJ, Seo SM. Physical fitness according to body fat and physical activity levels in women university students. J Korean Soc Living Environ Sys 2010;17:557-562 (Korean).
  • 30. Park H, Lee J, Kim JY, Kim DI, Jeon JY. Relationship between resting heart rate and prevalence of metabolic syndrome and type 2 diabetes mellitus in Korean adults: the fifth Korea National Health and Nutrition Examination Survey (2012). Korean J Obes 2015;24:166-174 (Korean).ArticlePDF
  • 31. Greenland P, Daviglus ML, Dyer AR, Liu K, Huang CF, Goldberger JJ, et al. Resting heart rate is a risk factor for cardiovascular and noncardiovascular mortality: the Chicago Heart Association Detection Project in Industry. Am J Epidemiol 1999;149:853-862.ArticlePubMedPDF
  • 32. Kristal-Boneh E, Silber H, Harari G, Froom P. The association of resting heart rate with cardiovascular, cancer and all-cause mortality. Eight year follow-up of 3527 male Israeli employees (the CORDIS Study). Eur Heart J 2000;21:116-124.ArticlePubMedPDF

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Physical activity and psychological adjustment among retirees: a systematic review
      Mehdi Sharifi, Davud Nodehi, Behzad Bazgir
      BMC Public Health.2023;[Epub]     CrossRef
    • 포토보이스를 활용한 베이비붐 세대 여성의 신체활동 참여 제약요인 탐색: 사회생태학적 모델을 기반으로＊
      우진 안, 채희 박
      The Korean Journal of Physical Education.2023; 62(1): 191.     CrossRef
    • Trajectory of physical activity frequency and cancer risk: Findings from a population-based cohort study
      Thi Phuong Thao Tran, Ngoc Minh Luu, Thi Tra Bui, Minji Han, Min Kyung Lim, Jin-Kyoung Oh
      European Review of Aging and Physical Activity.2023;[Epub]     CrossRef
    • Oral health of older Koreans by region and family status in 2020–2021
      Eun‐Jeong Kim, Do‐Hee Kim, Ra‐Gyeom Yu, Ye‐Jin Lee, Ye‐Jin Lee, Do‐Gyeong Im, Hye‐Ju Lee
      Gerodontology.2023;[Epub]     CrossRef
    • Effect of Short Bouts of Vigorous Stair Climbing on Cardiorespiratory Fitness in Women with Overweight and Obesity: A Pilot Feasibility Study
      Jeong Eun Yun, Xiaolin Wen, Minsub Han, Serim Cho, Jennifer L. Kuk, SoJung Lee
      Journal of Obesity & Metabolic Syndrome.2023; 32(4): 346.     CrossRef
    • Residential greenness and prevalence of chronic kidney disease: Findings from the China National Survey of Chronic Kidney Disease
      Ze Liang, Wanzhou Wang, Chao Yang, Yueyao Wang, Jiashu Shen, Pengfei Li, Lin Ma, Feili Wei, Rui Chen, Chenyu Liang, Shuangcheng Li, Luxia Zhang
      Science of The Total Environment.2022; 806: 150628.     CrossRef
    • Continuing regular physical activity and maintaining body weight have a synergistic interaction in improving survival: a population-based cohort study including 6.5 million people
      Chang-Hoon Lee, Kyung-Do Han, Da Hye Kim, Min-Sun Kwak
      European Journal of Preventive Cardiology.2022; 29(3): 547.     CrossRef
    • Health-Screening-Based Chronic Obstructive Pulmonary Disease and Its Effect on Cardiovascular Disease Risk
      Sang-Jun Lee, Sung-Soo Yoon, Myeong-Hoon Lee, Hye-Jun Kim, Yohwan Lim, Hyewon Park, Sun Jae Park, Seogsong Jeong, Hyun-Wook Han
      Journal of Clinical Medicine.2022; 11(11): 3181.     CrossRef
    • Relationship Between Protein Intake in Each Traditional Meal and Physical Activity: Cross-sectional Study
      Takae Shinto, Saneyuki Makino, Yu Tahara, Lyie Nitta, Mai Kuwahara, Ayako Tada, Nanako Abe, Mikiko Michie, Shigenobu Shibata
      JMIR Public Health and Surveillance.2022; 8(7): e35898.     CrossRef
    • Current Status of Physical Activity in South Korea
      Yoo Bin Seo, Yun Hwan Oh, Yun Jun Yang
      Korean Journal of Family Medicine.2022; 43(4): 209.     CrossRef
    • Physical Activity and Sedentary Time in Korean Adults before and during the COVID-19 Pandemic Using Data from the Korea National Health and Nutritional Examination Survey
      So Young Kim, Dae Myoung Yoo, Mi Jung Kwon, Ji Hee Kim, Joo-Hee Kim, Woo Jin Bang, Hyo Geun Choi
      Journal of Personalized Medicine.2022; 12(8): 1217.     CrossRef
    • Socioeconomic status relates to exercise habits and cardiorespiratory fitness among workers in the Tokyo area
      Tomoaki Matsuo, Rina So
      Journal of Occupational Health.2021;[Epub]     CrossRef
    • Modifiable Risk Factors for Cardiovascular Disease in Korea and Japan
      Ahmed Arafa, Hyeok-Hee Lee, Ehab S. Eshak, Kokoro Shirai, Keyang Liu, Jiaqi Li, Naharin Sultana Anni, Sun Young Shim, Hyeon Chang Kim, Hiroyasu Iso
      Korean Circulation Journal.2021; 51(8): 643.     CrossRef
    • Association between domain-specific physical activity and diabetes in Korean adults
      Eun-Byeol Lee, Sunghyun Hong, Jihee Min, Dong-Hyuk Park, Wonhee Cho, Sang-Hoon Suh, Hae-Dong Lee, Han-Joo Lee, Heejin Kimm, Sun Ha Jee, Eun Seok Kang, Dong Hoon Lee, Justin Y. Jeon
      Scientific Reports.2021;[Epub]     CrossRef
    • Trends in health behaviors over 20 years: findings from the 1998-2018 Korea National Health and Nutrition Examination Survey
      Soyeon Kim, Sunhye Choi, Jihee Kim, Suyeon Park, Young-Taek Kim, Ok Park, Kyungwon Oh
      Epidemiology and Health.2021; 43: e2021026.     CrossRef
    • When Much Is Too Much—Compared to Light Exercisers, Heavy Exercisers Report More Mental Health Issues and Stress, but Less Sleep Complaints
      Sanobar Golshani, Ali Najafpour, Seyed Sepehr Hashemian, Nasser Goudarzi, Fatemeh Shahmari, Sanam Golshani, Masthaneh Babaei, Kimia Firoozabadi, Kenneth M. Dürsteler, Annette Beatrix Brühl, Jalal Shakeri, Serge Brand, Dena Sadeghi-Bahmani
      Healthcare.2021; 9(10): 1289.     CrossRef
    • Association of occupation with the daily physical activity and sedentary behaviour of middle-aged workers in Korea: a cross-sectional study based on data from the Korea National Health and Nutrition Examination Survey
      Joo Hye Sung, Se Rhim Son, Seol-Hee Baek, Byung-Jo Kim
      BMJ Open.2021; 11(11): e055729.     CrossRef
    • Immunogenicity after Second ChAdOx1 nCoV-19 (AZD1222) Vaccination According to the Individual Reactogenicity, Health Status and Lifestyle
      Hyunji Choi, Sun-Min Lee, Seungjin Lim, Kyung-Hwa Shin, Taeyun Kim, Won-joo Kim, Misook Yun, Seung-Hwan Oh
      Vaccines.2021; 9(12): 1473.     CrossRef
    • The association between spatial access to physical activity facilities within home and workplace neighborhoods and time spent on physical activities: evidence from Guangzhou, China
      Ye Liu, Xiaoge Wang, Suhong Zhou, Wenjie Wu
      International Journal of Health Geographics.2020;[Epub]     CrossRef
    • Uric acid level and kidney function: a cross-sectional study of the Korean national health and nutrition examination survey (2016–2017)
      Hye Jin Joo, Gyu Ri Kim, Dong-Woo Choi, Jae Hong Joo, Eun-Cheol Park
      Scientific Reports.2020;[Epub]     CrossRef

    Related articles
    Physical activity level in Korean adults: the Korea National Health and Nutrition Examination Survey 2017
    Physical activity level in Korean adults: the Korea National Health and Nutrition Examination Survey 2017
    Variables % Neither Resistance only Aerobic only Combined p-value PA1
    MV (min/wk) Resistance (d/wk)
    Total 4,021 [26,136,896 (66.0)] 880 [6,214,780 (15.7)] 436 [3,365,609 (8.5)] 483 [3,893,229 (9.8)] 83.5±4.0 0.82±0.03
    Sex
     Male 49.6 1,532 [11,363,150 (57.9)] 521 [3,819,234 (19.4)] 216 [1,846,260 (9.4)] 299 [2,612,582 (13.3)] <0.001 109.5±6.61 1.09±0.041
     Female (reference) 50.4 2,489 [14,773,746 (74.0)] 359 [2,395,546 (12.0)] 220 [1,519,349 (7.6)] 184 [1,280,647 (6.4)] 57.9±3.7 0.56±0.03
    Age (yr)
     19-44 45.4 1,306 [11,022,509 (61.3)] 313 [2,732,177 (15.2)] 204 [1,802,384 (10.0)] 256 [2,419,007 (13.5)] <0.001 111.7±6.61 0.86±0.041
     45-64 38.1 1,513 [9,964,925 (66.0)] 353 [2,473,339 (16.4)] 189 [1,372,764 (9.1)] 181 [1,285,525 (8.5)] 72.7±4.71 0.82±0.04
     ≥65 (reference) 16.5 1,201 [5,149,462 (78.8)] 214 [1,009,263 (15.4)] 43 [190,460 (2.9)] 46 [188,697 (2.9)] 30.9±4.9 0.71±0.05
    Marital status
     Not married 23.8 585 [5,365,207 (56.9)] 170 [1,635,760 (17.3)] 89 [907,329 (9.6)] 151 [1,521,406 (16.1)] <0.001 126.6±10.41 1.04±0.061
     Married/live together 65.5 2,746 [17,288,916 (66.7)] 633 [4,142,231 (16.0)] 319 [2,291,515 (8.8)] 303 [2,197,358 (8.5)] 76.1±4.31 0.79±0.031
     Married/live separately (reference) 10.7 688 [3,469,540 (81.7)] 77 [436,789 (10.3)] 28 [166,765 (3.9)] 29 [174,465 (4.1)] 33.5±5.0 0.52±0.05
    Income
     High 32.0 1,021 [7,396,851 (58.6)] 258 [1,962,602 (25.6)] 186 [1,509,455 (12.0)] 220 [1,745,228 (13.8)] <0.001 115.0±6.71 0.93±0.041
     Mid-high 29.7 1,054 [7,613,712 (65.0)] 265 [1,926,915 (16.4)] 135 [1,003,437 (8.6)] 134 [1,174,657 (10.0)] 85.2±7.11 0.84±0.041
     Mid-low 23.0 1,005 [6,309,395 (69.5)] 213 [1,459,465 (16.1)] 82 [620,262 (6.8)] 94 [688,379 (7.6)] 65.8±7.9 0.77±0.05
     Low (reference) 15.3 929 [4,718,458 (78.0)] 142 [843,942 (13.9)] 32 [220,666 (3.6)] 34 [269,728 (4.5)] 41.7±9.8 0.64±0.08
    Location
     Urban 85.0 3,190 [21,891,690 (65.0)] 761 [5,391,430 (16.0)] 381 [2,933,863 (8.7)] 436 [3,447,515 (10.2)] 0.143 83.6±4.2 0.83±0.03
     Rural (reference) 15.0 831 [4,245,205 (71.4)] 119 [823,350 (13.8)] 55 [431,745 (7.3)] 47 [445,714 (7.5)] 82.8±13.4 0.77±0.10
    Education level
     University/college 43.6 1,315 [10,021,785 (58.1)] 390 [3,007,345 (17.4)] 242 [2,009,433 (11.6)] 263 [2,213,219 (12.8)] <0.001 107.8±6.21 0.91±0.041
     High school 33.0 1,173 [8,459,210 (64.9)] 289 [2,105,752 (16.1)] 141 [1,088,624 (8.3)] 174 [1,389,891 (10.7)] 88.8±6.61 0.88±0.051
     Middle school 8.8 437 [2,565,852 (74.0)] 95 [565,882 (16.3)] 31 [163,266 (4.7)] 23 [173,569 (5.0)] 56.6±17.51 0.84±0.101
     Elementary school (reference) 14.6 1,088 [5,037,117 (87.1)] 105 [527,500 (9.1)] 22 [104,285 (1.8)] 23 [116,549 (2.0)] 16.0±2.5 0.42±0.04
    Occupation
     Manager/profession 17.1 511 [3,927,068 (58.3)] 152 [1,231,194 (18.3)] 82 [724,036 (10.7)] 106 [859,419 (12.7)] <0.001 107.3±9.31 0.94±0.061
     Office job 12.9 404 [3,066,667 (60.3)] 114 [877,095 (17.3)] 67 [554,935 (10.9)] 70 [585,138 (11.5)] 93.1±8.71 0.88±0.081
     Inoccupation (housewife/students) 35.1 1,623 [9,293,231 (67.0)] 334 [2,110,621 (15.2)] 145 [1,088,174 (7.8)] 179 [1,376,645 (9.9)] 79.8±6.71 0.85±0.051
     Service industry 12.0 452 [3,124,938 (65.8)] 101 [764,866 (16.1)] 55 [394,778 (8.3)] 52 [464,145 (9.8)] 78.8±10.4 0.82±0.081
     Engineer 11.8 398 [3,195,767 (68.6)] 96 [731,258 (15.7)] 42 [322,911 (6.9)] 46 [410,697 (8.8)] 75.7±12.1 0.78±0.081
     Agriculture/forestry/fishery 3.2 237 [1,011,866 (79.0)] 27 [177,091 (13.8)] 11 [58,774 (4.6)] 4 [33,708 (2.6)] 55.3±22.3 0.49±0.08
     Labor (reference) 7.9 389 [2,451,315 (78.7)] 55 [309,273 (9.9)] 32 [196,644 (6.3)] 25 [155,998 (5.0)] 54.3±9.4 0.53±0.06
    Job status
     Employed 65.0 2,393 [16,805,826 (65.4)] 546 [4,104,159 (16.0)] 291 [2,277,435 (8.9)] 304 [2,516,584 (9.8)] 0.582 85.6±4.9 0.80±0.03
     Unemployed (reference) 35.0 1,623 [9,293,231 (67.0)] 334 [2,110,621 (15.2)] 145 [1,088,174 (7.8)] 179 [1,376,645 (9.9)] 79.8±6.7 0.85±0.05
    Position in work
     Employer/self-ownership 23.1 593 [3,827,031 (64.5)] 158 [1,112,280 (18.8)] 76 [523,433 (8.8)] 62 [468,944 (7.9)] 0.069 73.1±6.91 0.87±0.06
     Unpaid family worker 3.9 148 [757,704 (75.2)] 21 [139,975 (13.9)] 11 [65,065 (6.5)] 7 [44,828 (4.4)] 56.6±21.7 0.59±0.16
     Employee (reference) 73.0 1,652 [12,221,091 (65.1)] 367 [2,851,904 (15.2)] 204 [1,688,936 (9.0)] 235 [2,002,812 (10.7)] 91.1±5.8 0.79±0.04
    Employment status 51.5
     Regular (permanent) worker 739 [5,975,330 (61.9)] 181 [1,515,160 (15.7)] 120 [1,009,134 (10.5)] 135 [1,155,242 (12.0)] 0.010 103.2±8.21 0.81±0.05
     Contingent worker (reference) 48.5 913 [6,245,760 (68.6)] 186 [1,336,744 (14.7)] 84 [679,802 (7.5)] 100 [847,570 (9.3)] 78.3±7.4 0.78±0.05
    Variables % Neither Resistance only1 Aerobic only1 Combined1 p-value PA1
    MV (min/wk) Resistance (d/wk)
    Chronic disease (n)2
     None 67.6 2,289 [17,014,375 (63.6)] 526 [4,052,075 (15.1)] 314 [2,546,704 (9.5)] 368 [3,149,127 (11.8)] <0.001 97.1±5.0* 0.84±0.03
     1 17.5 852 [4,760,985 (68.5)] 188 [1,204,742 (17.3)] 70 [491,257 (7.1)] 77 [492,554 (7.1)] 65.6±5.8* 0.82±0.05
     ≥2 (reference) 14.9 880 [4,361,535 (73.9)] 166 [957,962 (16.2)] 52 [327,648 (5.6)] 38 [251,548 (4.3)] 43.1±6.3 0.73±0.06
    Cancer
     None 98.1 3,925 [25,592,704 (65.8)] 861 [6,113,361 (15.7)] 428 [3,321,728 (8.5)] 474 [3,847,068 (9.9)] 0.310 84.1±4.1* 0.82±0.03
     ≥1 (reference) 1.9 96 [544,192 (74.0)] 19 [101,418 (13.8)] 8 [43,881 (6.0)] 9 [46,161 (6.3)] 52.0±11.7 0.73±0.15
    Weight (kg) - 64.0±0.3 66.0±0.5* 69.0±0.8* 68.0±0.7* <0.001 NA NA
    Waist circumference (cm)3 81.9±0.3 81.7±0.4 82.6±0.6 80.1±0.6* 0.005 NA NA
     Normal 64.8 2,324 [15,815,041 (61.9)] 607 [4,372,279 (17.1)] 276 [2,196,212 (8.6)] 384 [3,152,120 (12.3)] <0.001 95.8±5.6* 0.95±0.03*
     Obesity (reference) 35.2 1,673 [10,152,017 (73.3)] 270 [1,821,628 (13.1)] 159 [1,165,309 (8.4)] 97 [719,334 (5.2)] 61.5±4.4 0.58±0.03
    BMI (kg/m2)4 23.9±0.1 23.7±0.1 24.6±0.2* 23.7±0.2 0.001 NA NA
     Underweight 4.2 173 [1,238,618 (75.7)] 29 [207,971 (12.7)] 6 [43,594 (2.7)] 19 [145,125 (8.9)] <0.001 52.3±11.4* 0.64±0.12
     Normal weight 38.7 1,531 [10,038,066 (66.0)] 360 [2,533,130 (16.7)] 147 [1,139,104 (7.5)] 192 [1,499,179 (9.9)] 74.0±5.5 0.84±0.04*
     Overweight 22.6 880 [5,483,400 (61.5)] 215 [1,570,909 (17.6)] 97 [755,233 (8.5)] 129 [1,101,358 (12.4)] 105.4±10.1 1.03±0.06*
     Obesity (reference) 34.5 1,408 [9,153,730 (67.4)] 275 [1,894,259 (13.9)] 185 [1,420,723 (10.5)] 141 [1,118,727 (8.2)] 84.5±6.1 0.69±0.04
    Blood pressure (mmHg)
     SBP - 117.6±0.4 117.1±0.7 116.8±0.8 115.4±0.7* 0.065 NA NA
     DBP - 75.2±0.2 76.2±0.5* 77.8±0.5* 75.9±0.5 <0.001 NA NA
    Blood profile (mg/dL)
     Glucose - 100.7±0.5 99.3±0.7 97.3±0.9* 95.3±0.7* <0.001 NA NA
     TC - 194.1±0.8 191.0±1.6 196.1±2.3 191.6±1.8 0.135 NA NA
     HDL - 50.9±0.2 51.4±0.4 50.8±0.8 53.4±0.6* 0.001 NA NA
     TG - 137.1±2.3 133.4±4.5 149.9±7.2 117.6±4.6* <0.001 NA NA
    Hand-grip strength (kg)5 - 28.4±0.2 32.6±0.4* 32.1±0.6* 35.4±0.6* <0.001 NA NA
    RHR (beat/min) - 70.7±0.2 70.1±0.4 68.8±0.5* 67.8±0.6* <0.001 NA NA
    Family history
     No 41.2 1,757 [11,352,364 (69.6)] 343 [2,337,394 (14.3)] 144 [1,123,515 (6.9)] 186 [1,489,851 (9.1)] 0.001 74.3±5.0* 0.79±0.04
     Yes (reference) 58.8 2,258 [14,756,927 (63.4)] 536 [3,872,066 (16.6)] 291 [2,238,249 (9.6)] 296 [2,393,505 (10.3)] 90.0±5.4 0.84±0.03
    Variables % Neither Resistance only1 Aerobic only1 Combined1 p-value PA1
    MV (min/wk) Resistance (d/wk)
    Smoking
     No 79.1 3,301 [20,446,756 (65.2)] 723 [5,016,478 (16.0)] 365 [2,760,063 (8.8)] 402 [3,116,831 (9.9)] 0.294 84.5±4.5 0.83±0.03
     Yes (reference) 20.9 720 [5,690,140 (68.8)] 157 [1,198,301 (14.5)] 71 [605,546 (7.3)] 81 [776,398 (9.4)] 79.9±8.4 0.77±0.06
    Drink
     Never/no within 1 yr 22.7 1,228 [6,710,410 (74.5)] 216 [1,334,565 (14.8)] 78 [517,954 (5.7)] 61 [446,184 (5.0)] <0.001 50.8±7.2* 0.64±0.05*
     ≤1/wk 53.0 1,936 [13,291,122 (63.3)] 453 [3,325,489 (15.8)] 244 [1,898,214 (9.0)] 299 [2,471,272 (11.8)] 93.3±5.2 0.87±0.03
     ≥2/wk (reference) 24.3 857 [6,135,364 (63.8)] 211 [1,554,726 (16.2)] 114 [949,440 (9.9)] 123 [975,773 (10.1)] 92.9±8.0 0.88±0.06
    Sleeping time (hr)
     ≥7 63.3 2,544 [16,672,394 (66.7)] 533 [3,788,823 (15.2)] 274 [2,171,065 (8.7)] 291 [2,362,545 (9.5)] 0.326 80.8±4.9 0.80±0.03
     <7 (reference) 36.7 1,456 [9,372,539 (64.6)] 346 [2,421,614 (16.7)] 161 [1,190,699 (8.2)] 191 [1,525,436 (10.5)] 88.6±6.0 0.86±0.04
    Frequency of breakfast (d/wk)2
     ≥5 59.6 2,438 [15,872,878 (66.7)] 519 [3,874,866 (16.3)] 232 [1,835,349 (7.7)] 248 [2,212,135 (9.3)] 0.174 75.9±4.7 0.85±0.04
     <5 (reference) 40.4 1,131 [10,384,185 (64.4)] 247 [2,503,065 (15.5)] 145 [1,536,873 (9.5)] 150 [1,689,054 (10.5)] 89.9±7.0 0.79±0.04
    Energy intake (kcal/d)2 - 1,892.1±21.5 1,991.2±42.1* 2,028.2±51.7* 2,122.6±60.0* <0.001 NA NA
    Water intake (g/d)2 - 1,053.1±17.1 1,149.5±35.7* 1,232.9±31.3* 1,303.5±37.0* <0.001 NA NA
    Carbohydrate intake (g/d)2 - 294.9±3.0 306.2±5.6* 304.1±6.2 301.6±7.8 0.120 NA NA
    Protein intake (g/d)2 - 70.5±1.0 75.3±2.2* 77.2±2.2* 85.9±3.0* <0.001 NA NA
    Fat intake (g/d)2 - 44.4±0.9 47.7±1.4* 53.8±2.7* 57.2±2.7* <0.001 NA NA
    Variables % Neither Resistance only Aerobic only Combined p-value PA1
    MV (min/wk) Resistance (d/wk)
    Perceived stress
      Barely 13.9 655 [3,660,732 (66.7)] 151 [902,023 (16.4)] 61 [406,281 (7.4)] 74 [521,236 (9.5)] 0.015 77.4±8.6* 0.93±0.07*
    A little 57.1 2,196 [14,384,886 (63.7)] 520 [3,711,842 (16.4)] 260 [2,006,379 (8.9)] 300 [2,469,255 (10.9)] 93.3±5.5* 0.90±0.03*
    Much 24.5 951 [6,680,008 (68.9)] 180 [1,368,591 (14.1)] 101 [842,758 (8.7)] 97 [810,647 (8.4)] 71.8±5.4* 0.65±0.05
    Very much (reference) 4.4 208 [1,349,238 (76.8)] 27 [212,170 (12.1)] 14 [110,190 (6.3)] 11 [85,222 (4.9)] 43.7±7.7 0.46±0.10
    Depression over 2 wk
    No 88.3 3,444 [22,616,189 (64.8)] 797 [5,621,820 (16.1)] 402 [3,106,487 (8.9)] 439 [3,547,657 (10.2)] <0.001 86.3±4.3* 0.85±0.03*
    Yes (reference) 11.7 568 [3,467,406 (74.8)] 81 [572,806 (12.4)] 34 [259,121 (5.6)] 43 [338,703 (7.3)] 63.1±9.1 0.56±0.05
    Current depression
    No 97.9 3,902 [25,527,907 (65.9)] 856 [6,061,816 (15.6)] 431 [3,338,864 (8.6)] 478 [3,836,926 (9.9)] 0.170 84.5±4.1* 0.82±0.03
    Yes (reference) 2.1 119 [608,989 (72.1)] 24 [152,964 (18.1)] 5 [26,745 (3.2)] 5 [56,303 (6.7)] 39.5±13.1 0.77±0.15
    Thinking suicide for a year
    No 95.3 3,782 [24,679,629 (65.5)] 841 [5,928,594 (15.7)] 421 [3,262,604 (8.7)] 474 [3,802,811 (10.1)] 0.026 85.5±4.2* 0.83±0.02*
    Yes (reference) 4.7 230 [1,403,966 (75.6)] 37 [266,032 (14.3)] 15 [103,005 (5.5)] 8 [83,549 (4.5)] 44.8±12.8 0.57±0.11
    Psychological counselling for a year
    No 97.2 3,892 [25,359,835 (66.0)] 848 [5,992,457 (15.6)] 424 [3,288,442 (8.6)] 471 [3,795,700 (9.9) 0.710 84.3±4.1 0.82±0.03
    Yes (reference) 2.8 122 [731,273 (66.4)] 30 [202,169 (18.4)] 12 [77,167 (7.0)] 11 [90,660 (8.2)] 57.8±14.3 0.76±0.12
    HRQoL
    Mobility
      No problem 89.9 3,335 [22,831,301 (64.1)] 792 [5,717,456 (16.1)] 418 [3,285,001 (9.2)] 464 [3,781,737 (10.6)] <0.001 89.5±4.3* 0.85±0.03*
    Any problem (reference) 10.1 686 [3,305,595 (82.7)] 88 [497,323 (12.4)] 18 [80,608 (2.0)] 19 [111,492 (2.8)] 30.5±10.4 0.53±0.06
    Self-care
    No problem 97.3 3,831 [25,204,176 (65.4)] 861 [6,112,534 (15.9)] 432 [3,335,734 (8.7)] 478 [3,869,807 (10.0)] <0.001 85.2±4.1* 0.83±0.03*
    Any problems (reference) 2.7 190 [932,719 (85.7)] 19 [102,246 (9.4)] 4 [29,875 (2.7)] 5 [23,422 (2.2)] 24.4±12.8 0.38±0.08
    Usual activity
    No problem 94.4 3,654 [24,352,985 (65.1)] 832 [5,963,909 (15.9)] 425 [3,267,270 (8.7)] 471 [3,813,986 (10.2)] <0.001 85.5±4.2 0.84±0.03*
    Any problems (reference) 5.6 366 [1,778,745 (80.6)] 48 [250,870 (11.4)] 11 [98,339 (4.5)] 12 [79,243 (3.6)] 49.6±18.8 0.53±0.08
    Pain/discomfort
    No problem 79.1 2,970 [20,164,281 (64.4)] 691 [4,946,862 (15.8)] 353 [2,754,421 (8.8)] 420 [3,462,990 (11.1)] <0.001 89.6±4.5* 0.86±0.03*
    Any problems (reference) 20.9 1,050 [5,969,824 (72.1)] 189 [1,267,918 (15.3)] 83 [611,188 (7.4)] 63 [430,239 (5.2)] 60.7±6.8 0.68±0.05
    Anxiety/depression
    No problem 92.9 3,634 [24,027,069 (65.3)] 813 [5,798,007 (15.8)] 411 [3,202,848 (8.7)] 464 [3,746,384 (10.2)] 0.002 86.8±4.3* 0.84±0.03*
    Any problems (reference) 7.1 384 [2,104,134 (74.3)] 67 [416,773 (14.7)] 25 [162,760 (5.8)] 19 [146,845 (5.2)] 40.6±5.5 0.63±0.08
    Table 1. Association between PA and socio-demographic variables in Korean adults

    Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

    PA, physical activity; MV, moderate to vigorous aerobic.

    A p-value was calculated versus reference group.

    p<0.05.

    Table 2. Association between PA and medical- and health-related variables in Korean adults

    Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

    PA, physical activity; MV, moderate to vigorous aerobic; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; HDL, high-density lipoprotein; TG, triglyceride; RHR, resting heart rate; NA, not applicable.

    A p-value was calculated versus neither or reference group.

    Chronic disease was counted except for cancer.

    Waist circumference: obesity ≥90 cm for males and ≥80 cm for females.

    BMI (kg/m2): underweight <18.5, 18.5≤ normal<23.0, 23.0≤overweight<25.0, obesity≥25.0.

    Hand-grip strength values are the average of three measurements for the dominant hand (higher value is used for ambidextrous participants).

    p<0.05.

    Table 3. Association between PA and lifestyle variables in Korean adults

    Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

    PA, physical activity; MV, moderate to vigorous aerobic; NA, not applicable.

    A p-value was calculated versus neither or reference group.

    Nutrition survey weighted data.

    p<0.05.

    Table 4. Association between PA and psychological variables in Korean adults

    Values are presented as unweighted number [estimated number (%)] or mean±standard deviation.

    PA, physical activity; MV, moderate to vigorous aerobic; HRQoL, health-related quality of life.

    A p-value was calculated versus reference group.

    p<0.05.

    Table 1.

    Table 2.

    Table 3.

    Table 4.

    Epidemiol Health : Epidemiology and Health
    © Korean Society of Epidemiology.
    TOP