INTRODUCTION
Over the past few decades, the average human life expectancy has increased ever in the world. The world’s population is aging faster than it did in the past, with 9.3% of the population aged 65 or older in 2020, and projected to reach 17.0% by 2050 [1]. Increasing population aging has far-reaching consequences such as declining productivity, intergenerational inequality, and the burden of public finances, which various countries around the globe face a variety of challenges relating to the aging population [2].
Many under-represented issues in the lives of older adults have been neglected due to the fact that they span multiple domains; pain is one of the issues. Sensations of pain are transmitted to the brain through the spinal cord, which is more noticeable among the aging population and can produce more pain as the older adults’ nervous system adapts to these changes [3,4]. However, pain in old age is hardly understood, and it occur on a routine basis without being adequately evaluated. Since pain is such a common issue, the idea of embracing it as a natural part of aging among people is prevalent in our society [4,5]. Older people may regard their pain as incurable and may lead to not seeking appropriate medical treatment [6]. As such, it is hard to manage pain efficiently when individuals or society recognize that increased pain is a typical symptom of getting older.
With this insight, the International Association for the Study of Pain (IASP) was founded in 1973 to lead diverse pain studies [7]. IASP defined pain as “An unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage [8],” and it has been adopted by several experts, including the WHO. In this revised definition after 1979, pain cannot be inferred as sensory activity alone, but it must be viewed from the perspective of the person experiencing pain, by emphasizing the negative social and psychological effects of pain. In other words, regardless of a physical injury, it was emphasized that comprehension should not be compromised for those who are experiencing subjective pain. In spite of pain appearing in all age groups, the theme of the 2019 Global Year of Advocacy was chosen to highlight the needs of the aging population, who are exposed to high vulnerability and potential risks.
The risk of pain in the aging population has also been reported academically. Pain is estimated to occur in 45%-90% of the aging population [9-11]; the lack of awareness of pain [10], the age difference of the study subjects [12], and different measurements [13] all contribute to the wide disparity in prevalence. However, significant evidence of pain with increasing age has been consistently reported [14,15]. In addition to the risk of difficulty in daily living activities [16] and disability [17], pain in old age, if not properly treated, may increase the possibility of chronic pain [18] and may aggravate symptoms such as depression [19,20].
Although there are significant differences in pain according to gender and marital status, it is reported that the higher the age and the longer the pain period, the greater the negative impact on life. Although there are substantial disparities in pain according to gender and marital status, it is reported that the older one gets and the longer the pain lasts, the worse the influence on one’s life becomes [16]. Furthermore, since pain increases societal responsibility and burden, a thorough investigation of how pain affects and impacts older adults is required.
Growing life expectancy has resulted in increased academic interest in pain in the aging population, and epidemiology studies focused on the quality of life among older adults have flourished. Most attention has traditionally been paid to the prevalence of depression among older individuals. It was the results of studies examining not only the effects of depression on older people, but also factors that contribute to depression among older adults, including gender [21], age [22], socioeconomic status [23], and living alone [21].
Particularly, it has been reported that there is a strong relationship between depression and pain in older adults. While the dynamics of pain and depression are similar, the fact that depression is a consequence of pain over time facilitates a better understanding of the mechanisms behind pain and depression among older adults [20,24,25]. Williamson and Schulz [26] (1995) have identified evidence of age differences and the prevalence of distinct persistent pain among older adults. This indicates that the effect of aging on an individual’s pain experience is fairly complex, suggesting that a comprehensive examination of pain changes is required.
Yet, it is difficult to find studies that examine how a change in the type of pain affects depression in older adults. In spite of some studies that have examined the variability of pain [19], it is surprising that studies on the correlation between pain and depression have been overlooked. The longitudinal relationship between the types of pain changes and depression in old age will be essential when establishing long-term strategies for coping with pain-psychological effects among older adults. Furthermore, considering the fact that pain negatively affects older adults, an in-depth review should be undertaken by categorizing changes in pain. Hence, the purpose of this study is to identify the types of pain changes that affect older Koreans 65 years and over, as well as their effects on depression.
To accomplish this research purpose, the research questions set in this study are as follows. First, how do pain changes affect old people (over 65)? Secondly, how does the type of pain change in older adults affect depressive symptom?
METHODS
Data
We analyzed the Korean Longitudinal Study of Aging (KLoSA) data collected from 2010 to 2018 to understand the effects of pain changes on depression among older adults. KLoSA is a representative panel survey of Koreans that aims to measure and understand the health and socio-economic conditions of older Koreans and to provide basic evidence for the development of effective socio-economic policies. A total of 1,359 participants, aged 65 or older at the time of the 3rd year of the study, estimated the change in pain from 2010 (3rd) to 2018 (7th) were analyzed. All methods were performed in accordance with the Declaration of Helsinki. This report was exempted from approval by the institutional review boards (IRB) of the Clinical Research Ethics Committee of Semyung University (IRB number: 2022-03-004). Every participant gave written informed consent prior to their participation in the study.
Pain
The independent variable in this study was pain, which comprised 13 items (head, shoulder, arm, wrist, finger, chest, stomach, waist, hip, leg, knee, ankle, toe). The pain was rated on a 5-point scale, with 1 representing slight pain, 3 representing moderate pain, 5 representing very severe pain, and 0 representing no pain; a higher score corresponds to a greater level of pain. The pain variable was utilized by averaging a total of 13 items.
Depressive symptoms
The Center for Epidemiological Studies-Depression Scale (CES-D10) was used to assess depression. The CES-D scale was developed by Randolff (1977). KLoSA uses the Korean version of CES-D10 is used to measure depression, which consists of ten shortened items. For each item, participants were asked to answer questions about feelings and behaviors they experienced during the past week, with 1 point indicating that, “I thought that for a while, but I did not feel that way (less than a day),” and “Sometimes, I felt that way (between 1 and 2 days)” was worth 2 points. “I have thought like this often (about 3-4 days)” was considered as 3 points, and “I have thought like that always (about 5-7 days)” indicated 4 points. As part of the KLoSA, depression scores were derived by calculating the following factors. First, if the value of each item was 1, it was recoded as a 0, and if it was 2-4, it was recoded as a 1, and the sum of each item’s scores was calculated as the final depression score. Depression scores range from 0 to 10, and higher scores indicate a greater degree of depressive symptoms. When targeting older individuals, the optimal cutoff for CES-D10 was found to be 4 points (sensitivity 100%, specificity 92%) for CES-D10 [27]. While scores of 3 or below can be classified as no depression and scores of 4 or above as depression present, in this study, CES-D10 was used as a continuous variable to examine the level of depressive symptoms rather than simply determining the presence of depression. The CES-D10 used in this study had a Cronbach’s alpha of 0.824.
Covariates
For analysis, we used sex, age, household annual income, educational background, residential area, and whether the participants lived alone as covariates. The sex of each participant was divided into male and female, and age and household income were used as continuous variables. In particular, it was log-transformed for a normal distribution of household annual income. Residential areas are divided into urban and rural areas, and three levels of educational attainment are created: elementary school graduates, middle school graduates, and high school graduates.
Statistical analysis
The data analysis of this study was conducted using SPSS 27.0 (IBM Corp.) and M-plus 8.0 (Muthén & Muthén), with the following method and procedure. First, descriptive statistical analysis was conducted to identify the demographic characteristics of the target population as well as the characteristics of major variables. Secondly, a latent growth model was performed to estimate the overall change in pain, assuming one group. We used Tucker-Lewis index (TLI), comparative fit index (CFI), and root mean square error of approximation (RMSEA) to evaluate model fit, considering the sensitivity of the model to the sample size and the simplicity of the model. Thirdly, growth mixture modeling was used to categorize the types of pain changes. In the mixed growth model, the optimal number of types of pain changes was determined through p-values for Akiakie’s information criteria (AIC), Bayesian information criteria (BIC), sample-size adjusted BIC (SSABIC), Entropy, and bootstrapped likelihood ratio test (BLRT). Moreover, Jung and Wickrama28 (2008) noted that all types should comprise at least 5% of the sample size; the analysis was conducted with the consideration that at least 5% of the total sample had to form a group in order for it to be classified as a group. To determine the demographic characteristics of each type of pain change in older adults, the χ2 test and independent sample ttest were conducted. Finally, multiple regression analysis was performed to examine the effect of pain change types on depressive symptoms among older adults.
RESULTS
Descriptive statistics
The study included 424 males (31.2%) and 935 females (68.8%), with a higher proportion of females, with an average age of 72.56 years (standard deviation [SD]=5.36). The average household income was USD $13,093.23 (SD=12,688.75). In terms of educational attainment, 980 people (72.1%) graduated from elementary school, 171 people (12.6%) from middle school, and 208 people (15.3%) from high school. In the residential area, there were 907 people (66.7%) in the city, 452 people (33.3%) in the rural area, 1,127 people (82.9%) living alone, and 232 people (17.1%) living with someone. The average pain score increased from 0.33 points in 2010 (SD=0.41) to 0.45 points in 2018 (SD=0.43) based on a descriptive statistical analysis of major variables. Depressive symptom was evaluated as an average of 2.35 points out of 10 (SD=2.39) (Table 1).
Change and typology of pain in older adult
Prior to moving forward with the growth-mixed model, a latent growth model was conducted to understand how pain within an aging population changes over time. Both the nogrowth model and linear model were examined, respectively to compare their fit. The results showed that the no-growth model was not appropriate; while, the linear model with χ2=71.389 (p<0.001), CFI=0.978, TLI=0.978, RMSEA=0.067 was appropriate. Therefore, the linear growth model was chosen (Table 2). As a result of estimating the growth-mixed model based on the linear growth model, the fit of each model in 3 classes was found to be more appropriate than classes 1, 2, 4; it was lower in AIC, BIC, and SSABIC, and the Entropy was closer to 1. In addition, BLRT was significant in 2 and 3 classes. Nevertheless, class 3 was not suitable since one group contained less than 5% of the samples. Therefore, when the model fit criteria were taken into account comprehensively, the class 2 was deemed as the most appropriate and selected as the final model (Table 3).
We have classified the pain changes of older adults into two categories and named each category according to the characteristics of the pain change pattern. Close to 0 percent of cases were classified as low-stable in the first group from 2010 to 2018, and 1,194 of them (87.9%) represent this group. One hundred sixty-five cases (12.1%) were classified as the High increasing group, which showed a continuous pain increase from 2010 to 2018 (Figure 1).
Characteristics of older adults according to pain change patterns
Based on the result in Table 4, the difference in demographic attributes of older adults by the pain change type; sex (χ2=19.257, p<0.001), annual household income (t=4.080, p<0.001), educational attainment (χ2=21.492, p<0.001), and residential area (χ2=4.566, p<0.05) appeared to have a statistical significance. There was a high female ratio in both low-stable type and high-increasing, but the female ratio of the high-increasing type (83.6%) was much higher than the female ratio of the low-stable type (66.8%). In the case of household annual income, the low-stable type (M=13,525.73, SD=12,947.00) was significantly higher than the high-increasing type (M=9,963.5715, SD=10,129.61). For educational attainment, it was confirmed that the low-stable type had a relatively higher level of education than the high-increasing type, and in the residential area, it was confirmed that the low-stable type had a higher proportion of urban residence than the high-increasing type.
Association between different types of pain change and depressive symptoms in older adult
In Table 5, a multiple regression analysis was performed to examine the relationship between the type of pain change and depressive symptoms among older adults. The explanatory power (R2) of the independent variable for depressive symptoms was 12.7%(R2=0.127), and the research model was confirmed to be suitable (F=12.974, p<0.001). In the results of the analysis, age (B=0.055, p<0.001) and residential area (B=-0.537, p<0.001) were found to be significant control variables for depressive symptoms. In other words, a person who is older and living in an urban area is more likely to be depressed than a person living in a rural area. On the other hand, age, household income, educational attainment, and living alone did not affect depressive symptoms significantly. Depressive symptoms showed a stronger relationship among the high-increasing type of pain than the low-stable type (B=0.844, p<0.001).
DISCUSSION
The purpose of this study is to categorize changes in pain in Korean older adults in the longitudinal dimension and to elucidate the effect of each type on depressive symptoms. For this purpose, data from 2010 to 2018 of 1,359 65-year-olds in Korea were analyzed using KLoSA data. As the main analysis methods, latent growth and growth mixed models were used to derive types, and the impact of the pain change types on depressive symptoms was confirmed by multiple regression analysis.
First, pain changes among older adults were finally classified into two types. These are the low-stable type (n=1,194, 87.9%) and the high-increasing type (n=165, 12.1%). Although the incidence of pain among older adults is generally reported to increase with age [14,15,29], this longitudinal study showed that there are two types of pain in older adults. Upon examining the differences in demographic characteristics based on type, the high-increasing type had a higher percentage of women, lower income, relatively low educational attainment, and a higher percentage of rural residents than the low-stable type. This is consistent with the results of previous studies that not only the prevalence of pain gradually increases but also the pain area and intensity, among female older adults than in male older adults [30] and among older people with lower socioeconomic status (education, income, occupation) [31]. This characteristic of the high-increasing type with a high pain-related risk indicates that the more vulnerable the group is, the more likely it is to suffer from pain.
Further, in an analysis of the effect of the finally derived types of pain change on depressive symptoms, it was found that depressive symptom levels were higher in the case of the high-increasing type than in the case of the low-stable type. This supports previous studies that high pain aggravates de-pressive symptoms [19,20,25]. This study confirmed once again that pain affects not only physical difficulties but also deteriorates mental health such as depression.
Based on the results of this study, it is vital to take a proactive stance toward pain. It may be expected that the degree or scope of the pain may increase if cannot be adequately managed in old age. In addition, pain also affects people’s quality of life, such as depression. However, invisible pain is often considered an inevitable part of aging [4], and older adults often show a tendency to not actively seek medical assistance [6]. With the recognition that pain is also a disease [32], it is necessary to approach it as an active treatment target [33], furthermore, it is necessary to find a way to prevent the aggravation of pain. Since the causes of pain in old age are extremely diverse and complex, prevention is difficult, therefore, various efforts and discussions regarding early treatment and pain management will be required [16].
In particular, it is important to note that the longitudinal pain change patterns identified in this study among older adults—specifically, the low-stability and high-increase types—are significantly associated with depressive symptoms. The high-increase type is likely to include more women, individuals with low income, lower education levels, and a higher proportion of rural residents. This result highlights social inequalities in pain management and raises questions about the medical mechanisms involved for socioeconomically vulnerable aging populations. In this study, the high-increase type exhibited higher initial pain levels compared to the low-stability type, suggesting a potential cycle where pain leads to disability or poverty, which in turn aggravateschronic pain [34]. Additionally, despite the fact that South Korea, the background of the study participants, has a universal health insurance system in place, imbalances according to socioeconomic status have emerged. In this context, Atkins and Mukhida [35] (2022) reviewed studies on the relationship between socioeconomic status and pain management and found that even with universal health insurance or government-supported insurance programs, individuals with lower socioeconomic status do not receive equal prescriptions in the pain management process. It has been pointed out that various influencing variables such as reduced access to treatment, the possibility of burden of specific treatment, and low health literacy of patients can affect treatment, such as reduced access to specific drug treatment or reduced possibility of meeting related specialists in the case of individuals with low socioeconomic status or low regional income. Furthermore, the bias and stereotypes of medical service providers can lead to discriminatory treatment recommendations for patients with low socioeconomic status [36]. Considering both structural characteristics and the individual traits of vulnerable groups, it is important to pay attention to interventions that are designed to help vulnerable groups with a high risk of pain obtain effective pain management. There are several limitations to this study. This study utilized data from KLoSA’s 3rd (2010) to 7th (2018) surveys, while the 1st (2006) and 2nd (2008) surveys were not included. Due to an increase in dropout cases due to death, we excluded them to ensure a sufficient number of subjects for the longitudinal study. Also, because the data on pain and depressive symptoms were obtained from self-reporting of the elderly, the data may tend to be underestimated. Due to limitations of secondary data, continuity and severity of pain, such as acute and chronic pain, could not be considered.
In conclusion, the significance of this study lies in the fact that it reiterated the importance of early pain diagnosis and intervention by identifying the types of pain changes in older adults and analyzing their effects on depressive symptom. Additionally, this study emphasizes the importance of setting a healthcare policy for vulnerable populations with a high risk of pain in older adults by integrating restorative interventions for older adults in the high-increasing group. To this end, follow-up studies that clarify the specific mechanisms related to socioeconomic factors and pain management and treatment are essential. Additionally, prospective studies are needed with consideration of the severity and continuity of acute and chronic pain.
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