This study was based on data from the sixth KNHANES (KNHANES VI) conducted from 2014 to 2015 by the Korea Centers for Disease Control and Prevention (KCDC). KNHANES is a legal survey conducted annually on the level of health of the public, health-related awareness and behaviors, chronic diseases, and food and nutrition intake.

Among the participants of the KNHANES VI (2014-2015), 1827 people participated in the accelerometer survey, but 59 people were excluded due to loss of the accelerometer (9 people), nonwearers (47 people), and mechanical errors (3 people). A total of 1418 people were selected first, excluding 342 people who did not meet the minimum wearing time and number of days of the accelerometer used in the previous study for more than 10 hours a day, 4 days a week, and 8 people who did not respond to the health-related quality of life survey (EQ-5D). Among them, 1298 people were selected as participants for final analysis, excluding 2 pregnant women, 24 people receiving cancer treatment, and 94 people with osteoarthritis or rheumatoid arthritis that could affect their PA (Figure 1).

It was approved by the Research Ethics Review Committee of the KCDC (Approval No. 2013-12 EXP-03-5C, 2015-01-02-6C).

Tools to evaluate HRQoL include World Health Organization Quality of Life Brief Version (WHOQOL-BREF) [6], Quality of Well-Being Scale [22], 36-Item Short Form [23], and EQ-5D [24]. Among them, the reliability and validity of the Korean version of EQ-5D reliability and validity have been verified in several studies [25,26].

EQ-5D, a self-report questionnaire, was used for measurement of HRQoL. The survey questions were answered on a three-step scale (no problem, moderate problem, severe problem) with 5 questions: mobility, self-care, usual activity, pain/disability, and anxiety/depression. The KCDC calculated the EQ-5D index using the following formula to express it as a single index.

EQ-5D index = 1- (0.050+0.096×M2+0.418×M3+0.046×SC2+0.136×SC3+0.051×UA2 +0.208×UA3+0.037×PD2+0.151×PD3+0.043×AD2+ 0.158×AD3+0.050×N3)

Based on previous research methods [8], the EQ-5D index was divided into 2 groups, below average (low quality of life, low QoL) and above average (high quality of life, high QoL).

Data are presented as the mean (SD) for continuous variables, and presented as number and percent for categorical variables. We analyzed the study participants’ characteristics according to the EQ-5D index, using t test to compare continuous variables, chi-square test for categorical variables.

Additionally, adjusted odds ratio (OR) and 95% CIs for the risk of low HRQoL according to PA measured by the accelerometer and GPAQ were calculated using logistic regression after adjusting the socioeconomic variables (age, sex, marital status, education, employment, and income) for model 1, covariates in model 1 plus mental health-related variables (stress, subjective health status, and depression) for model 2.

All statistical analyses were performed using STATA (version 18.0; StataCorp) and P values of <.05 were considered to indicate statistical significance.

Table 1 shows the baseline characteristics of the below-average (low QoL) and above-average (high QoL) groups of the EQ-5D index. Age was significantly lower in the high QoL group. In addition, males, singles, highly educated people, office workers, and high-income earners were more common in the high QoL group. Those who usually feel less stress and those whose subjective health was good were more common in the high QoL group. There was no significant difference between the 2 groups in some health-related lifestyle variables such as smoking, drinking, and average sleep time. Among chronic disease-related variables, cardiovascular disease and diabetes were not significantly different between the 2 groups.

Table 2 presents PA measured by the accelerometer and GPAQ in the 2 groups divided by the average of the EQ-5D index. There were significantly more persons who met MVPA-AB ≥600 METs in the high QoL group (P<.10). There was no significant difference between high and low QoL groups for MVPA-AT and self-reported PA.

In Table 3, logistic regression analysis was performed to determine the correlation between HRQoL and PA measured by the accelerometer and GPAQ, and marked with an OR and 95% CI. Compared with the low QoL group, the crude OR of the HRQoL was 1.55 (95% CI 1.11-2.17) in MVPA-AB ≥600 METs. After adjusting for the socioeconomic variables (model 1), the OR of the HRQoL was 1.60 (95% CI 1.13-2.27). After adjusting model 1 for the mental health–related variables (model 2), the OR was 1.45 (95% CI 1.01-2.09), which weakened the statistical significance compared with model 1. There was no statistical significance between the 2 QoL groups for MVPA-AT and self-reported PA.

This study was designed to confirm the relationship between HRQoL and PA measured by an accelerometer using national survey data. As a result of the analysis, HRQoL was significantly associated with the group that engaged in more MVPA for at least 10 minutes, as measured by the accelerometer. However, there was no statistical significance with HRQoL for MVPA measured for at least 1 minute by the accelerometer. In the previous KNHANES, only self-report questionnaires were used to measure PA [8]. However, in the sixth KNHANES (2014-2015), PA measured with an accelerometer was provided, making it possible to conduct studies [28-30] like ours.

Our findings align with previous research demonstrating the beneficial effects of PA on HRQoL across various populations [31,32]. For example, multiple studies have reported that increased PA is associated with improved HRQoL. A study by Brown et al [16] found that adults who engaged in regular MVPA had significantly higher HRQoL scores compared to those who were inactive. Similarly, a review by Marquez et al [33] synthesized evidence from numerous studies and concluded that PA interventions can effectively enhance HRQoL across various populations. PA has been shown to enhance self-efficacy, physical self-esteem, and positive affect [32,34], which collectively contribute to improvements in HRQoL. Overall, our results are consistent with the majority of previous literature on the positive relationship between PA and HRQoL. This study further supports these findings by using objective measures of PA, thus providing a more accurate assessment of its impact on HRQoL.

This study can serve as a basis for recommending at least 10 minutes of MVPA to improve HRQoL. However, the phrase “at least 10 minutes” was deleted from the PA guidelines published by the US Department of Health and Human Services in 2018, as MVPA for less than 10 minutes can benefit health. Therefore, to compare this with other health-related variables not considered in this study, it is necessary to measure MVPA for at least 1 minute. Nevertheless, since the PA questionnaire used in the KNHANES specifies “usually continued PA for at least 10 minutes during a week,” it is more appropriate to compare it with PA for more than 10 minutes, as measured with an accelerometer in this study [35].

Earlier, it was mentioned that the GPAQ calculates PA that has been continued for at least 10 minutes, so it is appropriate to compare it with PA measured with an accelerometer for at least 10 minutes. However, previous studies [28,36-38] found no correlation between accelerometer data and the questionnaire's satisfaction with the PA guidelines, and the results were not consistent in this study as well. This inconsistency may arise because the questionnaire’s criteria for “PA continued for at least 10 minutes” are subjective or may include PA lasting less than 10 minutes. Additionally, there is a possibility of bias in the self-report questionnaire, as people engaging in MVPA may over-report their activity levels [37-39]. Furthermore, since the accelerometer was provided after filling out the questionnaire, the data measurement periods differ, and the GPAQ may misclassify location movement PA as MVPA without considering movement speed. Therefore, to measure PA more accurately, a specific method that can complement both approaches is necessary.

In previous studies [40-42], stress and subjective health status perception had a negative correlation with HRQoL, and in 1 study [43]; it was reported that stress had the greatest influence on the deterioration of women's QoL. In this study, when socioeconomic variables were corrected for the group with a lot of PA measured with an accelerometer, the statistical significance was stronger than before the correction. But when stress and subjective health status perception were additionally corrected, the degree of statistical significance decreased. Similar to previous studies, this can be interpreted as having a greater effect on stress and subjective health status perception on HRQoL.

This study has the following limitations. First, it is difficult to generalize the study results since it is a nonprobability sample composed of study subjects selected through convenience sampling. Second, variables including EQ-5D are investigated through a self-report questionnaire, so there is a possibility of social desirability bias, misclassification bias, and recall bias. Third, since it was conducted as an observational cross-sectional study, it is not possible to know the causal relationship between HRQoL and variables. Nevertheless, it is significant that the study was conducted using national health and nutrition survey data of about 1300 adults aged 19-64. Also, since it is a study using data obtained using an accelerometer, it has an advantage in being able to compare it with other domestic and foreign studies conducted in a similar way. Research using accelerometers began to increase in the 2000s, and since the beginning of 2010, nearly 100 related studies have been published annually [44,45]. In addition, the era has come when it is possible to measure PA using wearable devices such as smartphones and smart watches. It is thought that various follow-up studies using tools that can quantify PA are possible in the future. Based on this, we expect the growth of fields related to PA aimed at promoting health.

Our study shows the association between HRQoL and MVPA, which is significantly higher in the group with more PA for at least 10 minutes, using the KNHANES. The study emphasizes the need for promoting PA and interventions focusing specifically on continuing at least 10 minutes. We expect further interventional studies to focus on the specific PA time period such as occupational PA, leisure-time PA, and commuting PA.