Introduction

The growing older adult population worldwide is increasing the prevalence of dementia. The number of people with dementia (PwDs) globally is projected to increase from 50 million in 2020 to 82 million in 2030 and 152 million in 2050 (Alzheimer's Disease International et al., 2020). In Korea, the number of PwDs among adults aged ≥ 65 years in 2020 was 840,000 and is expected to exceed three million by 2050 (Ministry of Health and Welfare & Central Dementia Center, 2022). Dementia is a neurodegenerative disease associated with various problems, including cognitive decline, speech dysfunction, and behavioral and psychological symptoms (Cerejeira et al., 2012; Sato et al., 2018), that make it difficult for PwDs to perform independent activities of daily living and necessitate continuous nursing care (Khanassov et al., 2021; Prince et al., 2016). In general, family members are the primary source of care for PwDs, with many PwDs cared for at home (Andreakou et al., 2016).

In Korea, PwDs are generally cared for by their adult children. However, the number of spouses taking care of PwDs has been rising because of the increasing prevalence of nuclear families and other changes to the traditional family structure (Jang & Yi, 2017; Park et al., 2015). The percentage of spouses serving as family caregivers rose from 37.7% to 56.6% between 2014 and 2019 and is expected to rise further (Statistics Korea, 2019). Considering these changes in the reality of support, having a multifaceted understanding of spousal caregiving is of the utmost importance.

Providing care to a PwD significantly affects caregivers in multiple dimensions, including physical, psychological, social, and economic. Poor sleep quality decreases immune function and overall quality of life, especially in spouses serving as primary caregivers. Considering that these spouses are also older individuals, their experience caring for PwDs is inherently different from that of caregivers who are the adult children of PwDs.

A study on the caregiving experience that considered caregiver characteristics found role burden, psychological distress, economic issues, and health problems to be higher (Park et al., 2015) and health-related quality of life to be lower (Kim & Yeo, 2012) in spouses than in adult children. This situation is limited not only to the difficulties faced by caregivers but also to the quality of life of PwDs. Therefore, active, effective, and differentiated support measures that consider the characteristics of spouse caregivers are required.

Sleep quality is one of the health issues experienced by family caregivers of PwDs (Polenick et al., 2018; Wilson et al., 2019). Sleep disturbances have been found in two thirds of family caregivers of PwDs (Liang et al., 2020; Peng et al., 2019). In particular, spouse primary caregivers tend to experience greater sleep disturbance because they not only live with PwDs but also sleep beside them (Gao et al., 2019). These sleep disturbances may be further exacerbated by psychosocial factors such as caregiving-related burden, depression, and anxiety, which worsen sleep quality (Peng et al., 2019; Smyth et al., 2020). Furthermore, old age, fatigue, and chronic diseases have also been reported to affect sleep quality among family caregivers of PwDs (Chiu et al., 2014; Smyth et al., 2020; von Känel et al., 2012).

In particular, if changes in sleep patterns because of aging are not adequately managed, sleep disorders may occur. This issue is further complicated by the fact that older adults rarely perceive or recognize sleep disturbance as a problem. Moreover, as they lack sufficient temporal and economic resources for self-care, these older adults may neglect their own health because of the immediate care needs of the PwD under their care (Simpson & Carter, 2013). Consequently, caregivers of PwDs are at a higher risk of experiencing poor sleep quality (Peng et al., 2019).

Poor sleep quality is associated with decreased immune function and increased risk of chronic diseases such as hypertension, diabetes (Hoyt et al., 2021; von Känel et al., 2006, 2010), cognitive decline (Surani et al., 2015), poor quality of life (Lippe et al., 2021), and early institutionalization in long-term care facilities (Chang & Schneider, 2010). Diabetes and hypertension are associated with reduced sleep quality because of metabolic syndrome, nocturnal hypoglycemia, peripheral neuropathy, and sleep apnea (Shantsila et al., 2021). Moreover, cognitive decline is closely related to increased stress hormone cortisol and amyloid deposition because of poor sleep quality (Joo et al., 2021).

On the basis of the above, an assessment of the relevant factors of sleep quality among family caregivers of PwDs is necessary to facilitate effective early intervention and preventive actions. Therefore, this study was designed to assess sleep quality in spouses caring for PwDs and to determine the effect of care provision on their sleep quality. This study hypothesized that (a) sleep quality in spouses of PwDs is poorer than that in spouses of patients without dementia and (b) caregiving affects sleep quality even after adjusting for health status.

Methods Study Design

This secondary analysis was conducted using a cross-sectional study design. Data for this study were obtained from the 2018 Korean Community Health Survey (KCHS), a nationwide health survey conducted by the Korea Disease Control and Prevention Agency that provides population-based statistics for constructing and assessing national healthcare plans (Joo et al., 2021; Kang et al., 2015). The KCHS was performed by trained interviewers who visited the selected sample households and conducted computer-assisted individual interviews with adults aged 19 years or older.

Participants

The participants in this study were adults aged 40 years and older living with their spouses. The spouse caregiver of a PwD was defined as an individual living with and providing care to a PwD as a spouse. The exclusion criteria were spouse caregivers caring for presenile dementia and spouses of PwDs living in long-term care facilities. The control group included individuals who were living with spouses who did not have a diagnosis of dementia. The details of the participant selection procedure are shown in Figure 1.

Figure 1.:

Flowchart of Participant's Selection

Ethical Considerations

This study was approved by the institutional review board (IRB No. HYUIRB-202108-014). The KCHS raw data were obtained from a publicly available database, which is freely accessible online at http://chs.cdc.go.kr. The KCHS raw data, in accordance with the Korean Personal Information Protection Act and Statistics Act, do not include personal information or identifiers.

Measures Propensity score matching covariates

Seven sociodemographic and health-related characteristics were selected as variables for propensity score matching (PSM) for the spouse caregivers in the PwD and control groups. For sociodemographic variables, the selected variables were age, gender, educational level, monthly household income, and employment. For health-related characteristics, the selected variables were diabetes mellitus and hypertension. As these variables are not modifiable through nursing care or nursing interventions, they were controlled statistically using PSM.

Health-related variables

Variables adopted in this study to represent the health-related characteristics of participants were depressive symptoms, obesity, smoking, alcohol intake, self-rated health status, and subjective cognitive decline.

Depressive symptoms were measured using the Korean version of the Patient Health Questionnaire-9 (PHQ-9), a self-report scale for screening depression based on Diagnostic and Statistical Manual of Mental Disorders (4th ed.) criteria. Respondents are asked to rate each item on the PHQ-9 using a 4-point Likert-type scale (0–3), with total possible scores ranging from 0 to 27 and higher scores indicating more severe depressive symptoms. The PHQ-9 has been validated for use in older Korean adults, and a total score of 5 has been suggested as the optimal cutoff for screening for clinical depression (Han et al., 2008). In this study, the Cronbach's alpha for the PHQ-9 was .93. The participants were classified as either obese or nonobese (≥ 25 and <24.9 kg/m2, respectively) based on the body mass index criterion published by the World Health Organization Western Pacific Regional Office (Lim et al., 2017). In addition, the participants were classified based on smoking status (smoker or nonsmoker), alcohol intake (less than once a month or more than once a month), and self-rated health status (poor, fair, or good).

Subjective cognitive decline was defined as the respondent either perceiving worsening cognitive functions or experiencing increased frequency of confusion or memory problems during the past 12 months (Jessen et al., 2014). In this study, subjective cognitive decline was determined based on the answer to the following question: “Have you experienced more frequent or severe disorientation or memory loss during the last year?” The allowed responses were “yes” and “no” only (Joo et al., 2021).

Sleep quality

Sleep quality was measured using the Korean version of the Pittsburgh Sleep Quality Index (PSQI), which assesses sleep quality and patterns over a 1-month period (Sohn et al., 2012). The PSQI has been widely used in population-based and clinical studies and consists of 19 items and the following seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction. Each component may be scored from 0 to 3, and the global score for overall sleep quality is calculated by summing all of the components for a total possible index score ranging from 0 to 21. PSQI global scores > 8.5 indicate poor sleep quality in Korean populations, and this cutoff score was adopted in this study (Sohn et al., 2012). The Cronbach's alpha for the PSQI in this study was .87.

Data Analysis

Statistical analyses were conducted using SPSS 23.0 (IBM Inc., Armonk, NY, USA) and the R program (www.r-project.org/). To avoid selection bias because of confounding covariates, the 1:3 nearest neighbor PSM with a caliper value set at 0.1 was performed using the R program (Ho et al., 2011). The 1:1 matching strategy has a disadvantage in that if the propensity scores of the control group and the retreatment groups are dissimilar, the data of a large number of treatment groups are eliminated. Therefore, 1:n (treatment group to control group) matching has better power than 1:1 matching in PSM. However, the increase in power is insignificant if matching is performed with 1:5 or more (Rosenbaum, 2020). This problem can be compensated for by adequately setting the caliper width. Therefore, we set the PSM ratio as 1:3 (spouse caregivers of the PwD group to nonspouse caregivers of PwDs) with a caliper width of 0.1. In studies using nearest-neighbor matching with the fixed caliper width method in the medical and nursing science field, the caliper range varied from 0.01 to 0.6 (Austin, 2009). Therefore, we set the caliper width as 0.1 and performed calculated propensity without replacement.

Multivariate logistic regression analysis was performed to identify the effects of caregiving on the sleep quality of the caregivers. A two-tailed p < .05 was considered to be statistically significant.

Results Participant Characteristics From Unadjusted Data and Propensity Score-Matched Data

The sociodemographic and health-related characteristics of the participants according to caregiving provisions are shown in Table 1. The spouse caregivers of the PwD (experimental) group was relatively older and less educated, had more unemployed members, and had a lower average household income than the spouse caregivers of people without dementia (control) group (p < .001). Furthermore, the spouse caregivers of the PwD group experienced diabetes mellitus and hypertension more frequently (p < .001). Many differences in distribution patterns between the two groups were apparent before PSM. After PSM, similar distribution patterns appeared, and no significant intergroup differences in terms of covariates were observed, thus confirming the appropriateness of using this matching approach.

Table 1. - Between-Group Comparison of Baseline Characteristics, Pre- and Post-Propensity Score Matching Variable Unadjusted Data Propensity Score-Matched Data Control
(n = 57,694) Spouse Caregivers of PwDs (n = 356) p Control
(n = 1,068) Spouse Caregivers of PwDs (n = 356) p n % n % n % n % Age (years; M and SD) 66.0 9.8 76.5 7.4 < .001 76.2 7.0 76.5 7.4 .571 Gender .794 .878  Male 28,690 47.7 180 50.6 536 50.2 180 50.6  Female 29,004 50.3 176 49.4 532 49.8 176 49.4 Educational level < .001 .762  ≤ Primary school 23,741 41.1 241 67.7 740 69.3 241 67.7  Middle school 10,896 18.9 59 16.6 172 16.1 59 16.6  High school 15,132 26.2 39 11.0 118 11.0 39 11.0  ≥ College 7,925 13.7 17 4.8 38 3.6 17 4.8 Monthly household income (USD; M and SD) < .001 .565  < 1,000 12,458 21.6 184 51.7 565 52.9 184 51.7  1,000–1,990 16,335 28.3 122 34.3 380 35.6 122 34.3  2,000–2,990 11,080 19.2 30 8.4 80 7.5 30 8.4  ≥ 3,000 17,821 30.9 20 5.6 43 4.0 20 5.6 Employment < .001 .810  Employed 32,988 57.2 100 28.1 291 27.2 100 28.1  Unemployed 24,706 42.8 256 71.9 777 72.8 256 71.9 Diabetes mellitus < .001 1.000  No 48,136 83.4 268 75.3 804 75.3 268 75.3  Yes 9,558 16.6 88 24.7 264 24.7 88 24.7 Hypertension < .001 .926  No 33,479 58.0 158 44.4 469 43.9 158 44.4  Yes 24,215 42.0 198 55.6 599 56.1 198 55.6

Note. PwDs = people with dementia; USD = U.S. dollar.

Comparison of Health Status Between the Two Groups After Propensity Score Matching

The post-PSM health-related characteristics of the control and experimental groups are presented in Table 2. Obesity, smoking, and alcohol intake were not significantly differences between the two groups. However, when the total score on the PHQ-9 was classified using a cutoff score of 5 points, the depression rate was 20.7% in the control group and 35.1% in the spouse caregivers of the PwD (experimental) group, representing a significant difference (χ2 = 30.18, p < .001). Furthermore, there were more instances of poor self-rated health status in the experimental group (χ2 = 9.13, p = .010), and the rate of subjective cognitive decline was 33.2% in the control group and 47.2% in the experimental group, representing a significant difference (χ2 = 22.36, p < .001).

Table 2. - Between-Group Comparison of Health Status and Health Behaviors, Post-Propensity Score Matching (PSM; N = 1,424) Variable After PSM Control (n = 1,068) Spouse Caregivers of PwDs (n = 356) χ2 p n % n % Depressive symptoms 30.18 < .001  Not depressed 847 79.3 231 64.9  Depressed (PHQ-9 ≥ 5) 221 20.7 125 35.1 Obesity 3.46 .068  Nonobese 705 66.0 254 71.3  Obese (BMI ≥ 25) 363 43.0 102 28.7 Smoking 0.08 .784  Smoker 92 8.6 29 8.1  Nonsmoker 976 91.4 327 91.9 Alcohol intake 0.96 .347  Less than once a month 813 76.1 280 78.7  More than once a month 255 23.9 76 21.3 Self-rated health status 9.13 .010  Poor 468 43.9 188 52.8  Fair 386 36.1 113 31.7  Good 214 20.0 55 15.4 Subjective cognitive decline 22.36 < .001  No 713 66.8 188 52.8  Yes 355 33.2 168 47.2

Note. PwDs = people with dementia; PHQ-9 = Patient Health Questionnaire-9; BMI = body mass index.

Comparison of Sleep Quality Between the Two Groups After Propensity Score Matching

The PSQI global score was 6.24 (SD = 3.68) for the control group and 7.03 (SD = 4.00) for the experimental group, which was significantly higher. When the PSQI global score was 8.5 points, the poor sleeper rate was 24.2% for the control group and significantly higher for the experimental group (33.4%; χ2 = 11.79, p = .001). There were significant intergroup differences in PSQI dimension scores for subjective sleep quality (χ2 = 9.85, p = .020), sleep latency (χ2 = 14.64, p = .002), habitual sleep efficiency (χ2 = 11.19, p = .011), use of sleep medication (χ2 = 12.05, p = .007), and daytime dysfunction (χ2 = 29.93, p < .001; as shown in Table 3).

Table 3. - Between-Group Comparison of Sleep Quality (N = 1,424) Variable Control (n = 1,068) Spouse Caregivers of PwDs (n = 356) χ2 or t p n % n % Global PSQI score (M and SD) 6.24 3.68 7.03 4.00 3.27 .001 Good sleeper 810 75.8 258 66.6 11.79 .001 Poor sleeper (PSQI > 8.5) 237 24.2 119 33.4 PSQI subdomain  Subjective sleep quality 9.85 .020   0 (very good) 143 13.4 30 8.4   1 (fairly good) 611 57.2 199 55.9   2 (fairy bad) 257 24.1 99 27.8   3 (very bad) 57 5.3 28 7.9  Sleep latency (score) 14.64 .002   0 (0) 386 36.1 135 37.9   1 (1–2) 344 32.2 79 22.2   2 (3–4) 184 17.2 78 21.9   3 (5–6) 154 14.4 64 18.0  Sleep duration (hours) 2.33 .508   0 (> 7) 247 23.1 87 24.4   1 (6–7) 270 25.3 98