The association between night eating syndrome and health-related quality of life in Korean adults: a nationwide study

Data from the 2019 Korea Community Health Survey (KCHS) were used for the analyses. The KCHS is a cross-sectional study conducted by the Korea Centers for Disease Control and Prevention (KCDC) that includes a large, nationally representative sample of the Korean population selected using a two-stage sampling method in which primary sampling units are first selected and followed by households through systematic sampling. In-person interviews were conducted in the 254 local districts of Korea, in which the target population of each area is about 900 residents aged 19 years or older. Further details regarding the KCHS have been previously published [13].

All variables were collected on the KCHS survey administered to the entire study sample nationwide. However, information on NES, measured using the Night Eating Questionnaire (NEQ), was collected only for residents of the Gyeonggi province. The NEQ was initially administered on a trial basis in the Gyeonggi province before it was implemented to investigate episodes of night eating nationwide. The Gyeonggi province was selected because it is the most populous region of Korea, physically surrounds the capital city Seoul, consists of both large, urban cities and rural regions, and is known for its demographically, socioeconomically, and geographically diverse population that largely resembles the characteristics of the entire Korean population. Thus, this study used information collected from this province in the KCHS.

The dependent variable was HRQoL, measured using the Korean version of the 3-level EQ-5D Index (EQ-5D-3L), introduced by the EuroQol Group, and has commonly been used to measure the quality of life [14]. The validity (Pearson correlation = 0.716, p-value < 0.001) and reliability (intraclass correlation coefficient = 0.652) of the index used have been verified [15]. This index is composed of five factors, namely mobility (M), self-care (SC), usual activities (UA), pain/discomfort (PD), and anxiety/depression (AD). Individuals are inquired whether they have no problems (level = 1), some problems (level = 2), or extreme problems (level = 3) for all the five components listed above. The formula to derive a composite score, published by the Korea Centers for Disease Control and Prevention is as follows [14]:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{EQ}} - {\text{5D}}\,{\text{index}}\, = \,{1}{-}\left( {0.0{5}\, + \,0.0{96}*{\text{M2}}\, + \,0.{418}*{\text{M3}}\, + \,0.0{46}*{\text{SC2}}\, + \,0.{136}*{\text{SC3}}\, + \,0.0{51}*{\text{UA2}}\, + \,0.{2}0{8}*{\text{UA3}}\, + \,0.0{37}*{\text{PD2}}\, + \,0.{151}*{\text{PD3}}\, + \,0.0{43}*{\text{AD2}}\, + \,0.{158}*{\text{AD3}}\, + \,0.0{5}*{\text{N3}}} \right)$$\end{document}EQ-5Dindex=1-0.05+0.096∗M2+0.418∗M3+0.046∗SC2+0.136∗SC3+0.051∗UA2+0.208∗UA3+0.037∗PD2+0.151∗PD3+0.043∗AD2+0.158∗AD3+0.05∗N3

In this index, if an individual has some problems (level = 2) in mobility (M), a value of ‘1’ is inserted into ‘M2’ in the formula above. If not, a value of ‘0’ is inserted instead. Similarly, if an individual has extreme problems (level = 3) in self-care (SC), a value of ‘1’ is inserted into ‘SC3’ in the formula above. If not, a value of ‘0’ is inserted. Likewise, this same method is applied for each of the components listed in the formula above to gain a composite score. Lastly, a score of “1” is inserted into N3 if an individual has reported having extreme problems for any of the five components listed above. The maximum score of the EQ-5D index is ‘1,’ which indicates the best health state [16]. The values have been multiplied by 100 for easier interpretation and visualization.

The variable of interest in the study was NES, which was measured using the Korean version of the NEQ. The NEQ is a 14-item questionnaire that is used to measure the behavioral and psychological symptoms of NES. Responses were rated on a 5-point Likert scale, and a cutoff score of 25 was used to indicate the presence of NES [17]. The validity and reliability of the Korean version of the NEQ have been previously confirmed [18], and NES has been successfully evaluated using this questionnaire in previous research [19].

The study used several demographic, socioeconomic, and health-related variables as covariates, including sex (male or female), age (19–29, 30–39, 40–49, 50–59, 60–69, or ≥ 70 years), education level (none, elementary school, middle school, high school, or college or above), income (quartiles), job type (professional or administrative position, office work, sales and service, agriculture and fishery, blue collar work or simple labor, or none), region (urban or rural), smoking (no or yes), monthly alcohol use (no or yes), moderate-to-vigorous physical exercise (no or yes), body mass index (BMI; underweight, normal, or obese), attempt to control body weight (no or yes), hypertension (no or yes), diabetes mellitus (no or yes), daily sleep duration (less than 6 h per day, 6 to 8 h per day, or over 8 h per day), sleep disturbance (no or yes), perceived stress (no or yes), subjective health status (no or yes), and depressive mood (no or yes). BMI was categorized into underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 25.0), and obesity (BMI ≥ 25.0). Daily sleep duration was measured using an open-ended question, “How many hours do you sleep on average?” Daily sleep duration was categorized as < 6 h, 6 to 8 h, and > 8 h per day based on previous research [20, 21]. Short sleepers included participants who slept less than 6 h per day and long sleepers who slept above 8 h per day [20]. Sleep disturbance was measured based on the question, “Did you experience difficulties in falling or staying asleep or sleeping too much in the past 2 weeks?”

T-tests and ANOVAs were used to measure the general characteristics of the study population. The participants’ mean characteristics and HRQoL scores by their sociodemographic, economic, and health-related characteristics were calculated. Cohen’s d and partial eta-squared (η²), an effect-size measure, was calculated. These values estimate the degree of association for the sample. For Cohen’s d, small, medium, and large effect sizes are 0.2, 0.5, and ≥ 0.8, whereas 0.01, 0.06, and ≥ 0.14 are suggested for partial eta-squared [22]. Cohen’s d is calculated as Cohen’s d = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{{M}_{1} - {M}_{2}}{{S}_{pooled}}$$\end{document}M1-M2Spooled, where Spooled = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sqrt{\frac{\left({n}_{1}-1\right){S}_{1}^{ 2} + ({n}_{2}-1){S}_{2}^{ 2}}{{n}_{1}+ {n}_{2}-2}}$$\end{document}n1-1S12+(n2-1)S22n1+n2-2. M1, S1, and n1 are the mean, standard deviation, and sample size of Group 1. M2, S2, and n2 represent the same measures for Group 2. In addition, partial eta-squared is calculated as η²partial = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{{SS}_{effect}}{ {SS}_{effect}+ {SS}_{error}}$$\end{document}SSeffectSSeffect+SSerror, where SSeffect and SSerror represent the sum of squares of effect and the sum of squared of error, respectively. Multivariable linear regression analyses assessed the association between NES and HRQoL. A subgroup analysis was conducted based on daily sleep duration. All analyses were performed after adjusting for covariates. All analyses were two-tailed and statistical significance was set at p < 0.05. Analyses were conducted using the SAS 9.4 software (SAS Institute, Cary, NC, USA).

This study was conducted in accordance with the Declaration of Helsinki. The KCHS used in the analyses were publicly available data which had been deidentified and fully anonymized before its release. This study was included on the review list pursuant to Article 2.2 of the Enforcement Rule of Bioethics and Safety Act in Korea, since the data used were exempted from IRB review.

This study has some limitations. First, as this study had a cross-sectional design, any interpretations that infer causality should be made with caution. Second, only residents of the Gyeonggi province were included in this study because the NEQ variable was inquired on this subset of the study population in the 2019 KCHS survey. However, the findings can be generalized to an extent to other regions because the Gyeonggi province is the most populous region of Korea and includes a diverse population that resides in both urban and rural areas. Third, the analytic results could have been underestimated since ceiling effects have been reported for the EQ-5D index. Last, daily sleep duration was measured using self-reports in the KCHS. Despite such limitations, this study is unique because it is the first to analyze the association between NES and HRQoL in the general population of Korea.

Below is the link to the electronic supplementary material. Supplementary file1 (DOCX 16 KB)