INTRODUCTION
According to the World Health Organization, injuries caused by external forces, including traffic accidents, falls, industrial accidents, violence, and poisoning, result in approximately 3.5∼4.0 million deaths worldwide annually [1]. In Korea, approximately 26,000 deaths and 2.88 million cases of injuries occurred in 2022[2]. Although approximately two-thirds of patients with severe injuries survive hospitalization, 26.0% experience severe disabilities that prevent basic daily activities, and the overall disability rate reaches 67.2%[3]. However, many individuals return to daily life after treatment, while a subset continues to experience lingering symptoms or psychosocial difficulties during the recovery period.
Injuries (including poisoning) go beyond structural bodily damage, causing physical, psychological, and social impairments that collectively diminish patients' health-related quality of life (HRQoL). Pain, mobility restrictions, and sleep disturbances may persist for months or years in some individuals. Anxiety, depression, and post-traumatic stress disorder (PTSD) may also develop following injuries, and these conditions have been associated with poorer HRQoL and prolonged recover [4-7]. Moreover, postinjury challenges, including failure to return to work, limited social participation, and social withdrawal, can diminish social functioning and heighten economic and social burdens [7,8]. Consequently, recovery trajectories are frequently nonlinear, with initial improvements followed by subsequent declines [7,9,10]. Anxiety, depression, and PTSD frequently develop following physical injuries, and these conditions are closely linked to poorer HRQoL and longer recovery periods [7,11,12].
HRQoL describes individuals' evaluation of their life situation within their cultural and value environment, taking into consideration their goals, expectations, and concerns. It encompasses physical and mental health, independence, social interactions, environmental conditions, and spiritual or religious elements [11,13]. In clinical practice, treatment outcomes and functional recovery alone are inadequate to represent patients' overall well-being; therefore, HRQoL has become a key indicator of patient-centered recovery [9,14].
Previous studies have identified various HRQoL determinants. Physical factors include subjective health perception, activity limitation, body mass index (BMI), hemoglobin (Hb), physical activity level, and C-reactive protein (CRP), with CRP reflecting stress and long-term HRQoL decline-associated inflammatory responses [9,12,15,16]. Psychological factors, including depression, stress, and anxiety, frequently comorbid with PTSD, are closely associated with reduced HRQoL [7,17-19]. Furthermore, sociodemographic factors, including sex, age, income, education level, and residential area, significantly influence HRQoL, with females, older adults, and individuals with lower socioeconomic or educational status reporting lower HRQoL [20-25].
Domestic and international studies have reported that patients with injuries generally exhibit lower HRQoL than the general population; however, most studies have focused on acute outcomes, including mortality or functional recovery, with limited attention to post-discharge HRQoL [5,8,14,21,26]. Given that HRQoL may remain impaired even after acute treatment and discharge, understanding correlates of HRQoL in community-dwelling adults with recent treatment experience is important for nursing and public health interventions. In Korea, although the Health-Related Quality of Life Instrument with 8 Items (HINT-8) has been applied to measure HRQoL, comprehensive analyses among physical injury survivors remain scarce [11,17,20,24,27].
Accordingly, the analysis was based on data collected in the 2023 Korea National Health and Nutrition Examination Survey (KNHANES). This study assessed how physical (subjective health perception, BMI, Hb, activity limitation, and CRP), psychological (depression, anxiety, and stress), and sociodemographic factors (sex, age, economic status, education level, and residential area) contribute to HINT-8-measured HRQoL among adults with accident or poisoning treatment experience in the past year. The findings are anticipated to provide evidence for nursing interventions and public health policies aimed at improving recovery and HRQoL among adults with accident or poisoning treatment experience.
METHODS
1. Study Design
This study conducted a secondary analysis of the 2023 KNHANES dataset using a cross-sectional descriptive approach.
2. Participants
Participants were 354 adults aged ≥19 years who participated in the 2023 KNHANES and responded "Yes" to the question, "Have you received treatment at a hospital, clinic, or emergency room due to an accident or poisoning in the past year?" This item does not differentiate inpatient admission from outpatient or emergency care, nor does it provide details on the type, intent, or severity of the accident or poisoning. Because this item captures treatment experience within the past year, the timing of the accident or poisoning event relative to the survey and whether the condition had resolved at the time of measurement could not be determined. The following were the exclusion criteria: aged <19 years, provided incomplete responses to relevant items, did not complete the HINT-8 or key independent variables, or were aged ≥80 years. After applying these criteria, the final sample comprised 354 participants, and the detailed selection process is illustrated in the participant flow diagram (Figure 1). Participants aged≥80 years were excluded because age is top-coded in KNHANES for the oldest-old, and thus the exact age (in years) cannot be determined. This precluded using age as a continuous predictor and limited interpretability of age-related effects in the regression models.
Figure 1.
Flow diagram of participant selection from the 2023 Korea National Health and Nutrition Examination Survey dataset.
G*Power calculations indicated that a minimum of 199 participants was required for multiple regression (f2=0.15, ⍺=0.05, 15 predictors, power=0.95). The actual sample of 354 participants exceeded this requirement.
3. Measurements
1) Health-related quality of life
HRQoL was measured using the HINT-8 instrument, which is administered as part of the KNHANES survey. The HINT-8, a standardized domestic HRQoL measurement tool, was jointly developed by the National Health Insurance Service and the Korea Evidence-Based Healthcare Collaborating Agency [27]. It encompasses eight items across the following four subdomains: physical, mental, social, and positive health. The HINT-8 uses a 4-point response scale, with lower scores indicating higher HRQoL levels. In this study, participants' HINT-8 scores were calculated using the standard formula, yielding a range of 0.132∼1, where values closer to 1 indicate better health. In this study, the reliability of the HINT-8 was high (intra-class correlation coefficient=0.85, p<.001) [27].
2) Physical factors
Participants' subjective perception of their health was measured using the question, "How would you rate your health in general?" The response options comprised five levels from "Very good" to "Very bad," and the scale was dichotomized into "Good or above" and "Below average" for analytical purposes. BMI was calculated from participants' height and weight and analyzed as a continuous variable. Hb levels were obtained from the anemia test in the blood test results. Activity limitation was measured using a yes/no question asking, "Are you currently restricted in your daily or social activities because of health problems or physical or mental disabilities?" Systemic inflammation was evaluated using serum high-sensitivity C-reactive protein (hsCRP) levels.
3) Psychological Factors
Anxiety symptoms were evaluated using the seven-item General Anxiety Disorder-7 (GAD-7), a broadly employed screening tool for generalized anxiety disorder [28]. For assessing anxiety, participants reported symptom severity over the previous 2 weeks using a four-point rating scale (0∼3), with higher ratings signifying more severe anxiety [28]. Stress was evaluated using the item, "How much stress do you usually feel in your daily life?" and rated on a four-point scale: "Very much," "Much," "A little," and "Almost none." For analysis, stress scores were dichotomized into "Very stressed" (scores 1∼2) and "Little stressed" (scores 3∼4). Depression was assessed using a single-item question asking whether, in the past year, participants had felt sad or hopeless for two or more consecutive weeks to an extent that impaired their daily functioning. Responses were dichotomized as either "Yes" or "No."
4) Sociodemographic factors
Age was considered a continuous variable, and sex was categorized as either male or female. Economic status was calculated from household income and classified into four quartile levels. For analytic purposes, these levels were subsequently collapsed into the following two categories: "low to lower middle" and "upper middle to high." Education level was determined by the highest degree achieved and was dichotomized into "high school or below" and "college or above." Employment status was classified as either "employed" or "unemployed"(e.g., homemakers, students, and others). Participants were categorized on the basis of their marital status into "married" and "single/divorced/widowed." Residential area was analyzed by administrative districts, with dong representing urban areas and eup/myeon representing rural areas.
4. Data Analysis
All analyses were performed using Statistical Package for the Social Sciences version 29.0, applying procedures suitable for complex survey data, including sampling weights, strata, and cluster variables. Complex sample descriptive analyses were conducted for summarizing sociodemographic characteristics and study variables using frequencies, percentages, means, and standard deviations. Complex sample x2 tests were employed for comparing HRQoL across categorical variables, and complex sample t-tests were applied for examining HRQoL differences across continuous variables. Complex-sample linear regression analysis was performed to identify factors influencing HRQoL, with sociodemographic, physical, and psychological factors as independent variables. Multicollinearity was assessed using tolerance and variance inflation factor values, with tolerance values greater than 0.10 and VIF values less than 10 considered acceptable. The tolerance values ranged from 0.40 to 0.93, and the VIF values ranged from 1.08 to 2.48, indicating no evidence of multicollinearity. Independence of residuals was evaluated using the Durbin-Watson statistic (DW=2.00), indicating no evidence of autocorrelation. Linearity and homoscedasticity were assessed by inspecting standardized residual-versus-predicted value plots; no substantial curvilinear or funnel-shaped patterns were observed. Normality was examined using a histogram and normal P-P plot of standardized residuals, which showed that the residuals were approximately normally distributed. Therefore, no major violations of the regression assumptions were identified. The significance level was set at ⍺=0.05.
5. Ethical considerations
The KNHANES is a national survey conducted under Article 16 of the National Health Promotion Act to evaluate the health behaviors, prevalence of chronic diseases, and nutritional status across the Korean population. The Korea Disease Control and Prevention Agency's Institutional Review Board (IRB) approved the 2023 survey (approval number: 2022-11-16-R-A).
C University's IRB exempted this secondary data analysis from ethical review (approval number: 202506-SB-100-01).
RESULTS
1. Sociodemographic Factors
Of the participants, 81.6% and 18.4% lived in urban (dong) and rural (eup/myeon) areas, respectively. Males and females accounted for 46.9% and 53.1%, respectively, with a mean age of 51.55±15.95 years. Income was "low to lower-middle" in 42.7% and "upper-middle to high" in 57.3%. Education levels were 59.0% high school or below and 41.0% college or above. Employment status was 31.0% unemployed and 69.0% employed. Married participants comprised 77.1%, whereas 22.9% were single, divorced, or widowed (Table 1).
Table 1.
Factors Characteristics and HRQoL of Participants (N=354)
2. Physical Health Factors
Regarding subjective health, 70.9% and 29.1% rated their health as "very poor to fair" and "good to very good," respectively. Most participants (90.1%) stated no activity limitations, whereas 9.9% reported limitations in daily or social activities. The mean hsCRP level, BMI, and Hb level were 1.38±3.71 mg/L, 24.51±4.07 kg/m2, and 13.87±1.38 g/dL, respectively (Table 1).
3. Mental Health Factors
The mean GAD-7 score was 2.44±3.52. Of the participants, 88.7% responded "No" and 11.3% "Yes" to prolonged depressive symptoms, indicating that most did not experience depression spanning two or more consecutive weeks. Regarding stress, 72.3% and 27.7% reported low and high stress levels, respectively (Table 1).
4. Health-Related Quality of Life
The mean HINT-8 index was 0.80±0.01, indicating that participants had a relatively high HRQoL level, as higher HINT-8 values reflect better health status (Table 1).
5. Differences in HRQoL
HRQoL was significantly associated with several variables across domains: age (t=-2.13, p=.035) and employment status (t=-2.37, p=.019) in the sociodemographic domain; subjective health perception (t=-4.94, p<.001), hsCRP (t=-3.43, p=.001), and activity limitation (t=2.20, p=.029) in the physical health domain; and GAD-7 anxiety scores (t=-5.32, p<.001) and perceived stress (t=2.34, p=.021) in the psychological domain (Table 2).
Table 2.
Differences in Health-Related Quality of Life (N=354)
6. Correlations among Continuous Variables
Pearson correlation analysis was conducted to examine the relationships among continuous variables. HRQoL was significantly negatively correlated with age (r=-.20, p<.001), hsCRP (r=-.29, p<.001), and GAD-7 scores (r=-.50, p<.001) (Table 3).
7. Factors Influencing Health-Related Quality of Life
Employment status (p=.019), age (p=.035), subjective health perception (p<.001), activity limitation (p=.029), hsCRP (p=.001), perceived stress (p=.021), and anxiety (p<.001) were identified as significant predictors of HRQoL, with the regression model explaining 41.8% of the variance (Table 4).
Table 4.
Factors Influencing Health-Related Quality of Life (N=354)
DISCUSSION
This study investigated factors associated with HRQoL in adults with accident or poisoning treatment experience in the past year using nationally representative KNHA NES data. The complex-sample linear regression analysis revealed employment status, age, subjective health perception, activity limitation, hsCRP, perceived stress, and anxiety (GAD-7) as significant determinants of HRQoL, explaining 41.8% of the variance. These results highlight the multifactorial determinants of HRQoL following accident- or poisoning-related treatment experience and emphasize the interplay between physical and psychological health [7,8,29].
Unemployment was associated with lower HRQoL, underscoring the significance of economic stability, social connectedness, and role fulfillment among adults with past year accident- or poisoning-related treatment experience [4,29]. Older age predicted reduced HRQoL, suggesting functional decline and social role transitions [7,8]. Participants reporting below-average subjective health or activity limitations demonstrated lower HRQoL, indicating that self-perceived health and functional capacity are crucial determinants of overall well-being [6-8,29-31].
Higher hsCRP levels were associated with poorer HR QoL in this study. Because hsCRP was measured at the survey time and the timing of the accident or poisoning event cannot be determined, this finding should be interpreted as an association rather than evidence of acute postinjury inflammation affecting HRQoL. Elevated systemic inflammation, including higher CRP levels, has been associated with adverse mental health outcomes in prior studies, which may partly explain the observed association with HRQoL [12,16], potentially through various mechanisms, including central nervous system inflammation, microglial activation, and symptom-specific effects on fatigue, anxiety, and avoidance behaviors [12]. Monitoring inflammatory biomarkers, including CRP, may support tailored rehabilitation strategies.
Psychological factors, including perceived stress and anxiety, were strongly associated with lower HRQoL, indicating the pervasive impact of chronic stress and anxiety on physical and emotional functioning. Early psychological assessment and prompt psychosocial interventions are crucial for mitigating mental health sequelae that may follow accident- or poisoning-related treatment and improving HRQoL [7,8,21].
By contrast, residential area, sex, education, income, marital status, BMI, Hb level, and past-year 2-week depressive episodes were not significant predictors of HR QoL. Although several sociodemographic variables showed significant differences in bivariate analyses, these associations were attenuated in the multivariable model after adjusting for correlated physical and psychological factors, suggesting confounding and shared variance among predictors. The lack of sex variations aligns with domestic studies but differs from international findings, suggesting that cultural and social contexts can shape how sex affects HRQoL [7,8,21]. Although BMI and Hb level were not significant determinants, individualized factors, including muscle mass, body image, and functional recovery, may be more relevant QoL determinants in injury- or poisoning-related treatment recipients [18].
Based on these results, clinical and nursing implications can be drawn. First, HRQoL assessment should be multidimensional, integrating physical, functional, and psychological indicators rather than solely focusing on disease presence. Second, the significance of CRP suggests that biological markers can inform objective biomarker-based evaluation and tailored care planning. Third, stress and anxiety management should be systematically incorporated into postinjury care, including nurse-led counseling and psychosocial support programs. Fourth, functional recovery, muscle mass, and body image should guide personalized rehabilitation and nursing interventions, as BMI alone may insufficiently reflect postinjury health status. Lastly, cultural and social contexts should be considered in sex-specific QoL analyses, highlighting the significance of context-sensitive assessment and intervention strategies.
This study had some limitations. First, the cross-sectional design and secondary data analysis restricted causal inference and control over measurement. Second, accident-or poisoning-related treatment experience in the past year was identified using a single yes/no item and did not provide information on the type, intent, severity, timing, or resolution of the accident or poisoning event, nor did it differentiate inpatient admission from outpatient or emergency care. therefore, causal interpretations should be avoided and temporality could not be established. Because adults aged ≥80 years were excluded due to top-coded age information in KNHANES, the findings may not be generalizable to the oldest-old population. Lastly, the exclusive use of quantitative data and a single HRQoL measure (HINT-8) may have limited the capture of psychosocial and emotional experiences. Because depressive symptoms were measured using a single dichotomous item in KNHANES, whereas anxiety was assessed with the validated GAD-7, the depth and precision of psychological measurement were uneven, which may have led to misclassification, affected the estimates for depressive symptoms, and warrants cautious interpretation and future studies using validated multi-item depression scales (e.g., PHQ-9). To comprehensively evaluate HRQoL determinants among adults with accident- or poisoning-related treatment experience in the past year, future research should employ longitudinal designs, detailed injury phenotyping, temporally specific biomarker assessments, and mixed-method approaches.
CONCLUSION
This study identified key sociodemographic, physical, and psychological factors impacting HRQoL among adults with accident or poisoning treatment experience in the past year using KNHANES 2023 data. The findings, explaining 41.8% of HRQoL variance, highlight the significance of integrated multidimensional approaches to postinjury management. Specifically, employment, subjective health perception, functional limitations, systemic inflammation (CRP), and mental health indicators collectively influence QoL, offering empirical evidence for nurse-led interventions and multidisciplinary rehabilitation strategies. Overall, this study provides a holistic framework for elucidating postinjury HRQoL, informing evidence-based interventions to improve recovery outcomes among adults treated for accidents or poisoning in the past year.
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