Sleep, physical activity, and sedentary behaviors as factors related to depression and health-related quality of life among older women living alone: a population-based study

Study design and participants

We performed secondary data analysis and employed data from the 2014, 2016, 2018, and 2020 Korea National Health and Nutrition Examination Survey (KNHANES), which is an ongoing survey. The KNHANES is a nationally representative, cross-sectional survey of health status, health behaviors, food, and nutrition. The reason for selecting data from specific years (2014, 2016, 2018, and 2020) was that depression—an essential variable in this study—was assessed during these years. We obtained the data from the Korea Disease Control and Prevention Agency; researchers can download de-identified data from the website without any specific process to request information. This survey used multistage stratified cluster sampling. Once districts for the KNHANES were selected from the districts for the “National Population and Housing Census,” households eligible for the survey were selected after checking the household members. There was little possibility that the same participants were selected in consecutive waves because double-checking was conducted when selecting survey districts and households, even though sampling was performed separately in every survey. A total of 31,051 participants took part in the KNHANES in the years we scrutinized (2014, 2016, 2018, 2020); we excluded participants younger than 65, those who were male, those living with others, and those with at least one missing data element of the variables assessed in this study. Approximately 30.8% of the unweighted sample was excluded because of missing data. Detailed information is provided in supplemental Table 1. We included a total of 794 OWLA; the detailed process of participant selection is depicted in Fig. 1.

Fig. 1figure 1

Flow diagram of participants selection

VariablesPredisposing factors

Predisposing factors refer to inherent socio-demographic characteristics such as age, gender, and marital status [21]. We included age and education level in this study as predisposing factors. All questionnaires for the variables included in this study variables are presented in supplemental Table 2.

Enabling factors

Enabling factors refer to organizational and financial characteristics that allow people to use medical services and achieve health outcomes [21]. We included equivalent income and economic activity as enabling factors. Equivalized income was represented as a numerical variable according to the population’s calculated household income quintile: low, lower-middle, middle, upper-middle, and high. Economic activity status was assessed using the question, “Have you ever done paid work for one hour or more, or unpaid work for more than 18 h, in the past week?” The answers were either yes or no.

Need factors

Need factors are physiological and psychological factors related to disability or health that cause an individual to require medical services; they include subjective or objective health status [20]. Need factors are more closely tied to health outcomes or the need to use medical services compared to other factors, such as predisposing and enabling factors. We selected variables such as multimorbidity, subjective health status, activity limitation, and perceived stress as need factors. In the present study, multimorbidity refers to the number of chronic diseases that currently have among 31 chronic illnesses, including hypertension, dyslipidemia, ischemic heart disease, stroke, diabetes, thyroid disease, cancer, hepatitis B or C, osteoporosis, osteoarthritis, pulmonary tuberculosis, and asthma. To assess SHS, participants were asked to rate their health on a 5-point scale: (1) very poor, (2) poor, (3) fair, (4) good, and (5) very good. Activity limitation was assessed using a single question: “Do you currently have restrictions in daily life or social activities because of health problems or a physical or mental disability?” The answers were yes or no. Perceived stress was evaluated using a single question: “Are you feeling stressed out in daily life?” Participants rated perceived stress on a 4-point scale (1 = little, 2 = a little bit, 3 = a lot, 4 = very much); thus, a high score indicated a high level of stress.

Health behaviors

Sleep, physical activity, and sedentary behaviors as health behaviors were assessed using a self-reported questionnaire. Participants were asked about their average sleep duration on weekdays and weekends, and the average sleep duration per day was calculated [25,26,27]. In the present study, physical activity and sedentary behaviors were assessed using the Global Physical Activity Questionnaire (GPAQ) [28], developed by the World Health Organization, which is a reliable and valid tool to assess physical activity. The tool collects information regarding moderate-to-vigorous physical activity involved in work, transportation, and recreation. Two variables, assessed in MET minutes per week, representing moderate-intensity physical activity and vigorous-intensity physical activity as continuous variables were generated according to the GPAQ analysis guidelines. Sedentary behavior was also assessed using the GPAQ questionnaire; respondents were asked about the average time in minutes spent sitting or lying down per day, except for sleep.

Depression

The Patient Health Questionaire-9 (PHQ-9) is a self-report questionnaire developed to promote the diagnosis of mental illness in primary care [29]. The PHQ-9 is a reliable and valid tool consisting of 9 items, each of which is rated on a 4-point Likert scale. The items ask how frequently specific symptoms occur to diagnose a depressive disorder, ranging from 0 to 3 (0 = not at all, 1 = several days, 2 = more than half of the days, 3 = nearly every day). A high score indicates a high level of depressive symptoms, with scores ranging from 0 to 27. Cronbach’s alpha is 0.81, and test–retest reliability is 0.89 [30]; therefore, the reliability of the Korean version of the PHQ-9 has been supported. Concurrent validity of the instrument was verified in a previous study [30].

Health-related quality of life

HRQoL was measured using the EuroQol 5-Dimension (EQ5D), which is a standardized instrument. The EQ5D is divided into five domains (mobility, usual activity, self-care, pain/discomfort, and anxiety/depression). Responses are rated on a scale of 1 to 3, with 1 indicating no problem, 2 denoting some problems, and 3 implying extreme problems [31]. The EQ5D score was calculated as a single number between 0 (as bad as being dead) and 1 (full health) through weights for health status, with a higher score signaling better quality of life. We used the EQ5D index; hence, we converted all answers to an index using weights developed based on the South Korean population [32]. The reliability and validity of the Korean version of the EQ5D have been demonstrated in prior studies [33].

Ethical considerations

The Institutional Review Board (IRB) of the Korea Disease Control and Prevention Agency reviewed and approved the 2014 (2013-12EXP-03-5C), 2018 (2018–01-03-P-A), and 2020 (018–01-03-2C-A) surveys, whereas the 2016 survey was not reviewed by the IRB to obtain ethical permission. However, the survey was initiated by the government, and the Bioethics and Safety Act guarantees this survey is for the public good, regardless of IRB permission. All participants received detailed information prior to being involved in this national survey, including the survey purposes, process, and the possibility of their anonymized data being provided to other researchers. Informed consent was obtained from all participants and researchers can access the anonymized KNHANES dataset without further request. Therefore, this secondary data analysis study was exempted from review by the board of ethics at the author’s affiliated institution.

Statistical analysis

Multistage stratified cluster sampling was used to ensure the characteristics of a nationally representative sample. Thus, 4-year sample weights were computed for complex sample analysis according to the guidelines of KNHANES 8, developed by the Korea Disease Control and Prevention Agency [34]. Characteristics of complex sampling—such as strata, clusters, and sampling weights—were considered throughout the analytical process. Descriptive analysis to present the participants’ characteristics was conducted such that continuous variables were expressed as means and standard errors, and categorical variables were presented as unweighted numbers and weighted counts. Complex-sample hierarchical regression analysis was performed to verify the association between factors based on Andersen’s model and depression. We also investigated the relationship between these factors and HRQoL among OWLA. According to Andersen’s model, we entered factors as blocks such as predisposing factors, enabling factors, need factors, and health behaviors factors in the regression model, step-by-step. We did not find any multicollinearity through checking the variance inflation factor (VIF, 1.01–1.64). Significance was defined as p < 0.05. We performed all statistical analyses using SPSS software, Version 26 (IBM Corp., Armonk, NY, US).

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