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Asian J Kinesiol > Volume 27(4); 2025 > Article
Kim, Kim, Lim, and Ryu: Time Trends in Leisure-Time Physical Activity and Health-Related Quality of Life Among American Adults: A Time-Varying Analysis Using the Behavioral Risk Factor Surveillance System, 2018-2023

Abstract

OBJECTIVES

The purpose of this study is to examine time trends in Health-Related Quality of Life (HQoL) among U.S. adults and to analyze the time-varying associations between Leisure-Time Physical Activity (LTPA) and HQoL.

METHODS

This study utilized data from the Behavioral Risk Factor Surveillance System (BRFSS) collected between 2018 and 2023. For the trend analysis of HQoL, a weighted intercept-only linear Time-Varying Effect Model (TVEM) was employed. To examine the temporal association between LTPA and HQoL, a weighted logistic TVEM was applied. Furthermore, a weighted logistic TVEM was used to assess the moderating effect of sex (male vs. female) on the relationship between LTPA and HQoL.

RESULTS

A total of 1,883,016 U.S. adults were included in the analysis. The mean number of unhealthy days increased from 2018 to 2019, reaching 8.83 days, then declined to 7.45 days in 2020. By late 2023, the mean number of unhealthy days reached its highest level over the study period at 9.06 days. From 2018 to 2023, the association between LTPA and HQoL remained stable over time. After adjusting for time-invariant covariates, a significant association between engaging in LTPA and better HQoL was confirmed. Additionally, sex-stratified analysis revealed that both men and women exhibited the strongest association in 2018. However, no statistically significant sex-based moderation effect was observed.

CONCLUSIONS

The findings of this study confirmed that the mean number of unhealthy days among U.S. adults showed a fluctuating pattern from 2018 to 2023, with the highest levels observed in late 2023. Throughout the study period, LTPA was consistently associated with higher odds of reporting better HQoL, and this association remained stable across time with no evidence of sex-stratified moderation. These findings highlight the potential public health relevance of maintaining regular LTPA to support perceived well-being during periods of societal disruption.

Introduction

Physical activity is defined as any bodily movement that leads to energy expenditure through skeletal muscle [1], and is primarily categorized into Leisure-Time Physical Activity (LTPA) and occupational physical activity [2]. Participation in LTPA has increased, driven by factors such as enhancements in physical and physiological fitness [3] and the pursuit of enjoyment [4-6]. It has been demonstrated to offer a range of health benefits, including improvement on mental health [7], and reductions in the risk of chronic disease [8], cardiovascular disease [9], and stroke [10]. In contrast, although occupational physical activity involves comparable levels of energy expenditure, it has been associated with an increased risk of chronic diseases [7] and cardiovascular disease [11], and appears to have limited effects on physical fitness [12]. These observed differences in health outcomes may be attributed to variations in the context, intensity, recovery capacity, and level of autonomy associated with the type of physical activity. In this regard, the consistent health advantages observed with LTPA, as opposed to occupational physical activity, underscore its critical role in the broader relationship between physical activity and health.
Meanwhile, Health-Related Quality of Life (HQoL) is a comprehensive concept that serves as an indicator of an individual’s overall well-being by evaluating physical function, psychological state, and social interactions. It is influenced by various factors, comprising physical health, personal beliefs, mental well-being, social relationships, and environmental conditions [13]. This concept is widely applied across diverse fields, including physical therapy, geriatric health evaluations, and clinical research, as it enables a holistic understanding of an individual’s health status by monitoring health conditions, predicting mortality, and evaluating treatment effectiveness [14-16].
A previous longitudinal study by Wendel-Vos et al. [17] examining the relationship between LTPA and HQoL found that LTPA was associated with the mental components of HQoL. In addition, the study by Vuillemin et al. [18] demonstrated that individuals who met the public health recommendations for LTPA exhibited notably higher scores in the vitality dimension of HQoL. Similarly, research by Tessier et al. [19] indicated that changes in LTPA were associated with mental health and vitality, key components of the mental aspect of HQoL, regardless of sex. Therefore, these findings suggest that LTPA has a positive influence on the psychological components of HQoL.
Recent social and environmental changes have continuously influenced physical activity patterns, which could significantly impact HQoL. In particular, advancements in digital technology, changes in work environments, and lifestyle shifts following the COVID-19 pandemic have become major contributors to the decline in physical activity levels [20]. The extensive integration of telecommuting and virtual education has compelled numerous individuals to engage predominantly in a sedentary lifestyle throughout the day, thereby resulting in a substantial decline in levels of physical activity and negatively impacting HQoL. Most previous studies have focused primarily on scrutinizing the relationship between LTPA and HQoL, with a shortage of investigations exploring the trend of the relationship between those modifications.
Overall, our study addressed three main aims to identify trend of the relationship between LTPA and HQoL on U.S. adults. Specifically, the first aim was to examine temporal trends in HQoL across years. The second aim was to ascertain whether the association between LTPA and HQoL differs across time. The final aim was to examine whether sex moderates the time-varying association. The present study utilized Time-Varying Effect Modeling (TVEM), which represents an extension of linear regression. The TVEM is a statistical approach that allows for the estimation of regression coefficients as continuous functions of time, facilitating the examination of how these coefficients change over time [21]. This model is beneficial for detecting temporal variations in the levels of outcomes and the associations between variables of interest [22].

Methods

Study Design and Participants

The Behavioral Risk Factor Surveillance System (BRFSS) data for the years 2018-2023 that were made publicly available were used in this cross-sectional study. BRFSS represents the most extensive, population-centered, and nationally conducted computer-assisted telephone interview survey, which systematically gathers data concerning risk-related behaviors and preventive health practices throughout the United States [23-25]. BRFSS serves as a valuable resource for assessing the advancements of health policies and monitoring the effectiveness of public health initiatives [26]. Additional details on the BRFSS methodology for data collection are available on the Centers for Disease Control and Prevention (CDC) website (www.cdc.gov/brfss/index.html). In the 2018-2023 BRFSS cycles, the analysis included adults aged 18 years and older, resulting in a total sample of 1,883,016 individuals.

Measurement of Leisure-Time Physical Activity

LTPA was measured based on participants’ responses to the question, “During the past 30 days, other than your regular job, did you do any physical activity or exercise?”. Response options were “Yes” or “No,” and individuals who answered “Yes” were classified as engaging in LTPA.

Measurement of Health-Related Quality of Life

HQoL was assessed using two self-reported questions. Participants were asked: (1) “Now, thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?” and (2) “Now, thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?”.
For time trend analyses, HQoL was operationalized as the total number of physically and mentally unhealthy days reported over the past 30 days, with a logical maximum capped at 30 days (range: 0-30). A higher score indicates lower HQoL.
For logistic regression models examining the association between LTPA and HQoL, we constructed a dichotomous HQoL indicator. Participants were classified as having high HQoL if the total number of unhealthy days was <14 days, and low HQoL if the number was ≥14 days, consistent with prior epidemiologic studies using this threshold to identify HQoL impairment [27-29]. Odds ratios were calculated to estimate the likelihood of reporting high HQoL according to LTPA participation status.

Data Analysis

All statistical analyses were performed using SURVEY procedures in SAS version 9.4 (SAS Institute, Inc., Cary, NC) to consider the sample weights, stratification, and clustering of the complex sampling design to ensure nationally representative estimates. For the TVEM analyses, the %Weighted TVEM SAS macro was utilized, incorporating sampling weights to account for the population-based national sample.
Our study analysis was conducted in three phases. First, we utilized a weighted intercept-only linear TVEM to estimate the trend in HQoL. In this model, the intercept was indicative of the anticipated mean HQoL score. Second, we used weighted logistic TVEM to assess the time-varying relationship between LTPA and HQoL. This association was statistically significant at p <0.05 when time-specific 95% confidence interval (CI) did not overlap with the line at one. Third, with weighted logistic TVEM we further examined the moderating effect of sex (male vs. female) on the associations between LTPA and HQoL. Sex can be considered a significant moderator of the association only if the 95% CIs of the coefficients estimated separately for each sex do not overlap when plotted together. In addition, the P-spline approach was used in all TVEM models, allowing for the automatic selection of the best form for each coefficient function that is established over time.
Invariant covariates such as sex, age, and race/ethnicity were added in the second and third models. In this study, Sex was coded as a binary variable (1 = male, 2 = female). Age was categorized into six groups: 18-24 years, 25-34 years, 35-44 years, 45-54 years, 55-64 years, and 65 years or older. Racial categories were defined based on the available survey responses, including White, Black or African American, American Indian or Alaskan Native, Asian, Native Hawaiian or other Pacific Islander and other. However, due to the absence of a consistent ethnicity variable across all years of the dataset, Hispanic or Latino ethnicity could not be separately identified. Hispanic individuals therefore may have been included within other racial categories but were not analyzed as a distinct ethnic group.

Ethics Statement

This study utilized publicly accessible, de-identified datasets derived from the BRFSS, conducted by the CDC. As the dataset does not contain any personally identifiable information and is open to the public, Institutional Review Board (IRB) approval and informed consent were not necessary for this secondary analysis.

Results

Demographic Information

<Table 1> shows the weighted demographic characteristics. Overall, the demographic characteristics, including sex, age group, race/ethnicity, and participating LTPA were similar across the BRFSS cycles. The weighted sex proportions range was similar to both males (48.96%-49.58%) and females (50.42%-51.04%) across the respective cycles. The weighted age group proportions ranges were stable across the BRFSS cycles: 18-24 years (6.50%-7.70%), 25-34 years (13.71%-16.21%), 35-44 years (15.53%-17.09%), 45-54 years (16.40%-17.39%), 55-64 years (18.43%-19.57%), and 65 or older (24.11%-31.58%). The range of weighted race/ethnicity proportions depends on the respective cycles: White (76.11%-81.75%), Black or African American (10.29%-13.11%), American Indian or Alaskan Native (1.32%-1.94%), Asian (3.46%-4.84%), Native Hawaiian or other Pacific Islander (0.40%-0.69%) and other (0.72%-5.75%) proportions were similar. Participating in LTPA was also relatively consistent over the cycles. The weighted percentage of participants who engaged in LTPA ranged from 76.20% to 79.51%, while those who did not participate ranged from 20.49% to 23.80%.

Time trends in health-related quality of life

The estimated mean number of unhealthy days was calculated using weighted intercept-only linear TVEM and are shown in <Figure 1>. As <Figure 1> shows, the number of unhealthy days seemed to change with time. The highest burden was observed in late 2023, with a peak of 9.06 days (95% CI: 8.77-9.35), indicating poorer HQoL in that period. From 2018 to 2019, there was a gradual increase, reaching a local high of 8.83 days (95% CI: 8.57-9.09). A relative improvement was observed in 2020, when the number dropped to 7.45 days (95% CI: 7.35-7.56).

Time-varying association between leisure-time physical activity and health-related quality of life

The time-varying association between LTPA and HQoL among U.S. adults from 2018 to 2023 was estimated using weighted logistic TVEM and is displayed in <Figure 2>. As <Figure 2> shows, the estimated relationship between LTPA and HQoL does not appear to change over time.
As shown by 95% CIs that do not overlap with one (see the red line in <Figure 2>), we found a statistically significant association between LTPA and HQoL from 2018 to 2023 after controlling for time-invariant covariates. That is, individuals who had LTPA were found to have a better HQoL. For example, participating in LTPA was associated with about 2 times increased odds of better HQoL.

Time-varying association between leisure-time physical activity and health-related quality of life in Sex

<Figure 3> shows the association between LTPA and HQoL in U.S. adults from 2018 to 2023, controlling for time-invariant covariates and stratified by sex (male vs. female). The estimated ORs peaked in 2018 for men (OR = 2.43, 95% CI = 2.22-2.66) and in 2018 for women (OR = 2.53, 95% CI = 2.42-2.65). Although minor differences in the timing of peak OR were found, no statistically significant sex-based moderation effect was observed. The association between LTPA and HQoL remained consistent across sexes throughout the study period, suggesting that sex did not serve as a moderator in this association.

Discussion

This study examined temporal trends in self-reported unhealthy days in U.S. adults and investigated the trend of the relationship between LTPA and HQoL over time. Among U.S. adults, the mean number of unhealthy days increased between 2018 and 2019, peaking at 8.83 days. By 2020, this number declined to 7.45 days, potentially reflecting a short-term improvement in perceived health. However, it subsequently rose again, reaching a peak of 9.06 days at the end of 2023, indicating a lower overall HQoL in the post-pandemic period.
The association between LTPA and HQoL among U.S. adults from 2018 to 2023 did not appear to change over time, and when analyzed after controlling for time-invariant covariates, we found a statistically significant association between LTPA and HQoL. Furthermore, when the association between LTPA and HQoL from 2018 to 2023 was analyzed by sex, the strongest associations were observed in 2018 for both men and women. However, no statistically significant sex-based moderation was found.
The trend in self-reported unhealthy days among U.S. adults showed an increase from 2018-2019, followed by decline around 2020, and then a gradual rise again, peaking at the end of 2023. Notably, the U.S. Department of Health and Human Services (HHS) declared a public health emergency due to COVID-19, and by April 2023, over 140 million U.S. COVID-19 cases have been reported by CDC. The temporary decline in unhealthy days observed around 2020 may reflect changes in health perception or reporting behavior during the early stages of the pandemic. In contrast, the sustained increase through 2023, despite the official end of the public health emergency in 2023, may reflect long-term negative impacts of the COVID-19 pandemic. This trend aligns with previous findings. Hay et al. [30] reported lockdowns, social distancing, and fear of infection were associated with declines in HQoL.
In the results of the association between LTPA and HQoL over time, we showed that the association did not change over time and that there was a statistically significant association between LTPA and HQoL after controlling for time-invariant covariates. According to the previous studies, Vuillemin et al. [18] found that participants who met Public Health Recommendations (PHRs) for LTPA had better HQoL than those who did not, and Tessier et al. [19] found that participants who increased their LTPA over three years had higher HQoL. Furthermore, White et al. [31] also found that physical activity affects self-efficacy, which in turn affects mental health, a component of HQoL. These previous studies support our findings that the association between LTPA and HQoL is statistically significant.
The association between LTPA and HQoL by sex from 2018 to 2023 was analyzed. While the estimated odds ratios were highest in 2018 for both males and females, the overall trends between sexes were largely parallel, and the 95% CI overlapped throughout the study period. This indicates that no statistically significant sex-based moderation was observed, suggesting the association is known to exist regardless of sex. This is consistent with the findings of Brown, Carroll, Workman, Carlson & Brown [32], who also reported that the association between physical activity and HQoL did not vary significantly by sex.
This study has the following limitations. First, the BRFSS is a telephone interview survey, so there may be under- or over-reporting of LTPA and HQoL measures. Second, the data does not track individual longitudinal data; therefore, independent samples must be compared yearly, limiting the ability to explain causal relationships over time. Lastly, we were unable to separately analyze Hispanic or Latino individuals due to the absence of a consistent ethnicity variable across all study years. This may have led to the misclassification of Hispanic participants within other racial categories, thereby restricting the generalizability of our findings to this important population subgroup. Despite these limitations, this study is significant in utilizing responses from a large-scale health survey targeting hundreds of thousands of people across the United States and using continuous data for six years.

Conclusions

This study investigated the trend of HQoL in U.S. adults across time and the temporal relationship between LTPA and HQoL. The mean number of unhealthy days increased from 2018 to 2019, declined around 2020, and then rose again, reaching its highest level in late 2023. This pattern partially overlaps with the COVID-19 pandemic period, suggesting that large-scale societal events may coincide with fluctuations in perceived health status.
Across the years, participation in LTPA was consistently associated with higher odds of reporting better HQoL, and this association remained stable throughout the pandemic period, with no evidence of moderation by sex. While causal inferences cannot be drawn from this observational data, the robustness of this association underscores the potential value of maintaining regular LTPA as part of public health strategies aimed at supporting perceived well-being during societal challenges.

Notes

Funding

This work was supported by a 2-Year Research Grant of Pusan National University.

Conflicts of Interest

The authors have no conflicts of interest to declare for this study.

Figure 1.

Time trends in estimated means number of unhealthy days across 2018-2023 among U.S. adults.

Note: The solid black line (i.e., Unhealthy days) represents the estimated mean number of unhealthy days reported in the past 30 days, plotted by year. Higher values indicate poorer health-realted qualty of life (HqoL). Possible range from 0 to 30, with 0 indicating no unhealthy days and 30 indicating every day in the past month was reported as physically or mentally unhealthy. The dashed black lines around the time-varying estimates represent 95% CI. The lower dashed line represents the lower bound of the 95% CI (UnhealthyDays_K), and the upper dashed line represents the upper bound (UnhealthyDays_U).
ajk-2025-27-4-25f1.jpg
Figure 2.

Estimated tiem-varying association between leisure-time physical activtiy and health realted quality of life among U.Us. adults form 2018 to 2023, controlling for time-invariant covariates.

Note: The solid black line (i.e., Association) represents the estimated time-varying odds ratio for the association between leisure-time physical activity (LTPA) and high health-realted quality of life (HQoL), defined as having fewer than 14 unhealthy days during the past 30 days. Higher odds ration values indicate greater odds of reporting high HqoL among individuals who engaged in LTPA, compared to those who did not. The dashed balck lines represent 95% CI. The lower dashed line represents the lower bound of the 95% CI (Association_L) and the upper dashed line represents the upper bund (Association_U). Association is considered significant if there is non-overlapping 95% CI with the solid red line.
ajk-2025-27-4-25f2.jpg
Figure 3.

Estimated time-varying association between leisure-time physical activity and health-related quality of life among U.S. adluts from 2018 to 2023, controlling for time-invariant covariates, separately for male (gray line) and female (black line).

Note: The solid gray and black lines represents the estimated time-varying odds ratio for the association between leisure-time physical activity (LTPA) and high health-related quality of life (HqoL), defined as having fewer than 14 unhealthy days during the past 30 days, for male aand females, respectively. The lower dashed line represents the lower bound of the 95% CI (Association_L) and the upper dashed linerepresents the upper bound (Association_U). Sex renge at which their 95% CI do not overlap between groups indicate a statistically significant moderation.
ajk-2025-27-4-25f3.jpg
Table 1.
Weighted demographic characteristics across the evaluated cycles. (2018–2023 BRFSS; N=1,883,016)
Characteristic 2018 (n=328,346) 2019 (n=302,165) 2020 (n=299,486) 2021 (n=307,195) 2022 (n=320,755) 2023 (n=325,069)
Sex (%)
 Male 49.58 (49.24-49.93) 49.14 (48.82-49.47) 49.22 (48.82-49.62) 49.44 (49.05-49.83) 48.96 (48.66-49.27) 49.43 (49.12-49.75)
 Female 50.42 (50.07-50.76) 50.86 (50.53-51.18) 50.78 (50.38-51.18) 50.56 (50.17-50.95) 51.04 (50.73-51.34) 50.57 (50.25-50.88)
Age group (%)
 18 to 24 7.44 (7.24-7.64) 7.51 (7.33-7.70) 7.70 (7.46-7.94) 7.22 (7.00-7.45) 6.50 (6.34-6.67) 6.55 (6.39-6.72)
 25 to 34 15.84 (15.56-16.13) 15.14 (14.89-15.40) 16.21 (15.88-16.54) 15.19 (14.90-15.50) 14.22 (13.99-14.45) 13.71 (13.49-13.93)
 35 to 44 15.65 (15.39-15.91) 15.62 (15.37-15.87) 15.53 (16.23-16.84) 17.09 (16.79-17.40) 16.11 (15.88-16.34) 15.80 (15.58-16.03)
 45 to 54 17.39 (17.13-17.66) 16.76 (16.52-17.01) 17.02 (16.72-17.31) 17.12 (16.83-17.42) 16.83 (16.60-17.06) 16.40 (16.18-16.63)
 55 to 64 19.57 (19.31-19.83) 19.57 (19.32-19.82) 18.78 (18.49-19.08) 18.58 (18.29-18.88) 18.75 (18.51-18.99) 18.43 (18.21-18.67)
 65 or older 24.11 (23.85-24.38) 25.39 (25.14-25.65) 23.76 (23.46-24.07) 24.78 (24.47-25.10) 27.59 (27.33-27.85) 31.58 (31.30-31.86)
Race/Ethnicity (%)
 White 78.87 (78.56-79.17) 78.75 (78.46-79.03) 77.11 (76.75-77.47) 76.15 (75.80-76.50) 79.66 (79.40-79.92) 81.75 (81.48-82.01)
 Black or African American 10.93 (10.69-11.16) 10.29 (10.08-10.51) 10.67 (10.43-10.92) 10.78 (10.54-11.01) 13.11 (12.88-13.33) 11.84 (11.61-12.08)
 American Indian or Alaskan Native 1.94 (1.85-2.04) 1.88 (1.79-1.97) 1.94 (1.82-2.07) 1.92 (1.81-2.04) 1.84 (1.76-1.92) 1.32 (1.25-1.39)
 Asian 3.50 (3.34-3.66) 3.46 (3.32-3.61) 4.66 (4.44-4.89) 4.84 (4.64-5.06) 3.99 (3.86-4.11) 3.86 (3.73-4.00)
 Native Hawaiian or other Pacific Islander 0.50 (0.46-0.55) 0.46 (0.42-0.50) 0.49 (0.44-0.54) 0.56 (0.51-0.61) 0.69 (0.65-0.73) 0.40 (0.36-0.44)
 Other 4.26 (4.11-4.42) 5.16 (5.01-5.31) 5.13 (4.94-5.33) 5.75 (5.54-5.96) 0.72 (0.65-0.78) 0.83 (0.77-0.89)
LTPA
 Yes 78.01 (77.79-78.35) 76.20 (75.92-76.47) 79.51 (79.19-79.82) 78.84 (78.53-79.16) 77.69 (77.44-77.94) 78.93 (78.67-79.18)
 No 21.93 (21.65-22.21) 23.80 (23.53-24.08) 20.49 (20.18-20.81) 21.16 (20.84-21.47) 22.31 (22.06-22.56) 21.07 (20.82-21.33)

Note. BRFSS = Behavioral Risk Factor Surveillance System; LTPA = Leisure-Time Physical Activity.

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