The Association Between Occupational Factors, Depression, and Health-Related Quality of Life in Military Women in Republic of Korea: A Cross-Sectional Study



Background: Health-related quality of life (HRQOL) is an important concept to consider both individuals' ability to manage their daily lives and health status across the lifespan. Despite this variable's importance, there is a lack of clarification on the factors associated with HRQOL, especially for military women. The aim of this study was to examine factors associated with HRQOL of military women in the Korea Army.

Methods: This cross-sectional study included 196 participants who were currently within their 5-year service period. Differences in HRQOL according to general and occupational factors were analyzed using the independent t-test and analysis of variance. Multiple linear regression analysis was performed to identify factors associated with the HRQOL of women serving as military junior officers.

Results: The mean score for the physical component summary (PCS) of HRQOL was 56.0±5.8, and that for the mental component summary (MCS) of HRQOL was 47.2±10.0. For depression, the mean score was 5.4±5.2, whereas 19.4% of the participants scored more than 10 out of 27 points, which means moderate to severe. No variables showed statistically significant relationships with the PCS. However, significant relationships with the MCS were found for rank (β = -3.63, p <. 001), duty time (β = -4.93, p = .029), perceived stress (β = -0.61, p <. 001), and depression (β = -0.90, p <. 001).

Conclusions: Although depression levels were not severe, it was a significant factor of HRQOL and thus the need for depression screening and regular depression management in women serving in the ROK Army to improve their HRQOL. Considering these results, nursing officers should conduct frequent testing related to mental health and take steps to manage high-risk groups. This study also contributes to the literature by providing basic data for the establishment of an appropriate health service environment and systematic health management policies.


Military women in the Republic of Korea (ROK) comprise officers and non-commissioned officers serving in the field through voluntary enlistment; the Ministry of National Defense stated that it planned to increase the proportion of female soldiers, who accounted for about 3.5% of all military officers in 2010, to 8.8% by 2020 [1]. In general, military junior officers are personnel with a service period of less than 5 years, and this group accounts for about 70% of military officers in their 20s and 30s [2]. This age group encompasses the transition from adolescence to adulthood and is among the healthiest periods in the life cycle [3]. This period is also characterized by extensive variation in individual health promotion activities, such as eating habits and physical activity, depending on the individual's personal choices [4], and in particular, since most female military junior officers are women of childbearing age, they are required to consider aspects of their reproductive health. Accordingly, the Ministry of National Defense is making efforts to create a healthy working environment and to establish policies for military women by identifying high-priority health problems and vulnerable groups through comprehensive studies of overall health conditions, medical institution use, and women's health [5].

As the definition of health has been extended from simply the absence of disease to the concept of complete well-being in recent years, researchers have taken an increasing interest in health-related quality of life (HRQOL), a concept that considers an individual’s ability to manage his or her daily life and a person’s health status across the lifespan [6,7]. Measurements of HRQOL are important methodological tools for routine monitoring, especially when providing healthcare for vulnerable groups [8]. With the recent increase in interest in HRQOL, numerous studies have been conducted in diverse populations differing in terms of gender and age groups [6,9,10]. Those studies have shown that high self-efficacy, stress management, formation of a desirable eating attitude, and appropriate physical activity are important factors that improve HRQOL at the individual level [3].

For female military junior officers serving in the ROK, it has been confirmed that distinctive characteristics of the armed forces, such as rank, length of service, working hours, number of overtime hours, and working areas, are related to health-promoting activities [11]. These results suggest that both systematic health care policies at the organizational level and individual issues should be considered when formulating strategies for improving Korean female military junior officers’ HRQOL [11]. In addition, since most Korean female military junior officers are in their childbearing age, specific attention should be paid to aspects of reproductive health [9,11]. Therefore, for establishing strategies to improve the HRQOL of female military junior officers, both individual-level health promotion activities and women’s normal health problems according to their life cycle should be considered in light of the distinctive features of the military environment.

 Nevertheless, there was a lack of research that explored the factors that affect soldiers’ HRQOL [10,11], especially with appropriate consideration of both individual health promotion activities and women’s life cycle in the unique environment of the military. Therefore, the purpose of this study was to identify factors associated with HRQOL among female military junior officers serving in the ROK Army.

Materials And Methods

Study Design and Sample

This cross-sectional study was conducted in November 2019. The subjects of this study were 196 military women. The inclusion criteria were military women who currently served in the ROK Army with a service period within 5 years and voluntarily chose to participate in this study after receiving an explanation of the purposes and goals of the research.

 Because military women work throughout the nation and the proportion of military women in each division is only approximately 5%, the survey was conducted in an online and mobile format. By cooperating with official announcements and text messages, we encouraged participation in the survey. The recruitment notice included a description of the purpose and methods of this study, the conditions for participants, the benefits and risks of this study, the discontinuation of voluntary participation, and the assurance of anonymity for the study participants.

Those who fulfilled the inclusion criteria and voluntarily agreed to participate in the study were provided a link for the online survey. Screening questions were also presented on the first screen of the online survey to ensure that participants met the selection criteria. If all criteria were met, the participant completed the survey after viewing and an explanation stating that completing the survey was considered as constitute agreement to participate in this study. All participants received a gift card for completing the survey.

 The average response time for this survey was about 15 minutes. In accordance with institutional review board (IRB) approval (IRB approval number: Y-2019-0162), a protocol was put in place to ensure that the researcher was notified of responses anonymously and that the respondents’ phone numbers were not transmitted to the researcher.

In order to prevent duplicate responses from the same participants and to ensure that the survey was not distributed beyond the intended participants, researchers monitored survey participation twice a day.


The research instrument was a self-reported survey questionnaire that consisted of 116 questions, including 36 questions about HRQOL, 7 questions about physical activity, 10 questions about stress, 26 questions about attitudes to eating, 10 questions about self-efficacy, 9 questions about depression, and 18 questions about general and occupational characteristics. The original authors approved the use of the relevant tools, the validity and reliability of which have been demonstrated in previous studies.

Dependent variables

Health-related Quality of Life: HRQOL was the dependent variable of this study. The Korean version of the Short-Form 36 Health Survey Questionnaire version 2.0 is a self-evaluation scale used to measure HRQOL [12], and consists of 36 items that measure eight health domains: physical function, role limitations due to physical problems, bodily pain, general health perception, vitality, social functioning, role limitations related to emotional problems, and general mental health. The score for each domain ranges from 0 to 100, with higher scores indicating better HRQOL. These domains can be categorized into the physical component summary (PCS) and mental component summary (MCS). PCS and MCS scores are represented on a standardized scale (as a T score with a mean of 50 and standard deviation [SD] of 10). The internal consistency of the PCS and MCS was quantified using Cronbach’s α, with values of 0.78 and 0.60, respectively.

Independent variables

Physical activity: The Korean version of the International Physical Activity Questionnaire (IPAQ) was used to estimate participants’ level of physical activity during the previous 7 days [13]. The items of the IPAQ are structured to provide a domain-specific score for walking, moderate-intensity, and vigorous-intensity activity. The results are presented as the estimated energy expenditure in metabolic equivalent-minutes per week (MET hours/week). The number of MET hours/week for a specific activity is computed by multiplying the MET value for the activity (3.3 for walking, 4.0 for moderate-intensity activity, and 8.0 for vigorous-intensity activity) by the number of hours spent on that activity [13].

Stress: The Korean version of the Perceived Stress Scale was applied to assess the degree to which respondents perceived their lives to be unpredictable and uncontrollable over the past month [14]. The PSS consists of 10 items, and higher scores indicate more severe stress. The internal consistency of the questionnaire was confirmed by a Cronbach’s α of 0.88 in this study.

Attitude to eating: Disordered eating in participants was assessed using the Korean version of Eating Attitudes Test-26 (EAT-26) questionnaire. The EAT-26 questionnaire includes 26 items in 4 domains: (i) self-control of eating and bulimic symptom, (ii) preoccupation with being thinner, (iii) food preoccupation, and (iv) dieting [15,16]. Each item is responded to on a 6-point Likert scale, but not all positions on the scale are scored. Each item is given a score of zero for ‘sometimes,’ ‘rarely,’ and ‘never’; a score of 1 for ‘often’; a score of 2 for ‘usually’; and a score of 3 for ‘always.’ The total score ranges from 0 to 78, with higher scores indicating that a respondent is at a higher risk of eating disorders. The internal consistency of the questionnaire was shown by a Cronbach’s α of 0.87 in this study.

Self-efficacy: The Korean adaptation of the General Self-Efficacy Scale was used to measure self-efficacy [17]. It consists of 10 items concerning self-confidence and is measured on 4-point Likert scale. Each question was answered with scores from ‘not at all true’ (1) to ‘exactly true’ (4). The total score ranges from 10 to 40, with higher scores indicating better self-efficacy. The internal consistency of the questionnaire was demonstrated by a Cronbach’s α of 0.89 in this study.

Depression: The Korean version of the Patient Health Questionnaire-9 (PHQ-9) was applied to assess the degree of depression [18]. PHQ-9 is a self-evaluation scale used to measure mental health at primary health care centers [19]. It consists of 9 items assessing the frequency with which patients have experienced depressive thoughts or feelings over the prior two weeks. The severity of depressive disorder is considered mild for scores ranging from 5 to 9 and moderate to severe for score from 10 or more [18]. The internal consistency of the questionnaire was shown by a Cronbach’s α of 0.90 in this study.

General and occupational characteristics: The following general characteristics were analyzed: age, body mass index (BMI), religion, education level, marital status, living with spouse, age at menarche, regularity of the menstrual cycle, length of the menstrual cycle, pregnancy and delivery experience, and history of oral contraception use. BMI classification used for Asian populations [20]. The occupational characteristics were rank, branch, duration of service, working area, duty time, service type, and number of overtime days.

Data Analysis

The collected data were statistically processed using the SPSS version 25 (IBM Corp., Armonk, NY, USA). Descriptive statistics were calculated for participants’ characteristics. The differences in HRQOL were analyzed using the independent t-test and analysis of variance. Multiple linear regression analysis was conducted to identify factors significantly associated with HRQOL among military women. A two-tailed probability value of p < 0.05 was considered to indicate statistical significance.


Differences in health-related quality of life according to participants’ general and occupational characteristics

Table 1 presents participants’ general and occupational characteristics. Questionnaire responses from 196 participants were analyzed. The mean age of the participants was 25.2±2.2 years, and their mean BMI was 21.8±2.3 kg/m2, with 74.0% of participants having a BMI in the normal range (18.5 to 23.0 kg/m2) [20]. The percentage of married respondents was 12.2%, and 66.7% of the married military women lived with their spouses or children. All of the participants responded that they currently had menstrual cycles and 48 (26.5%) indicated that they experienced menstrual irregularity. Approximately one-quarter of participants had taken oral contraceptive pills (25.5%), for an average of 5.1±6.7 months. The most common reason for taking oral contraceptive pills was for menstrual suppression during dispatch and training (42.0%), followed by temporary contraception (32.0%) and therapeutic purposes for a disease (26.0%). There were 69 (35.2%) non-commissioned officers and 127 (64.8%) officers, distributed among combat, technical and administrative, and specialized branches (39.3%, 20.9%, and 39.8%, respectively). The average number of overtime days per month was 7.7±8.2.

In this study, PCS and MCS scores are represented on a standardized scale (as a T score with a mean of 50 and SD of 10). Significant differences were found in the PCS score according to BMI (F = 2.68, p = .048). The married military women reported significantly higher MCS scores than the unmarried military women (51.4 and 46.6, respectively, p = .027). Among the married military women, the MCS score was significantly different according to whether respondents lived with their spouses (t = -2.77, p = .025). Significant differences in the MCS score were found according to rank, with officers reporting significantly lower scores than non-commissioned officers (45.9 and 49.4, respectively, p = .018). A higher number of overtime days per month was associated with a lower MCS score (r = -0.16, p = .023).

Descriptive statistics for research variables

Table 2 presents descriptive statistics for HRQOL and the other variables evaluated in the questionnaire. The scores of the two main domains, PCS and MCS, were 56.0±5.8 and 47.2±10.0, respectively. Each domain was converted to a score of 0-100 points, with higher scores indicating better HRQOL. The highest score was reported for the physical function domain (92.2±14.2) and the lowest score for vitality (58.5±20.2).

When the participants were categorized according to the criteria for IPAQ, 18.9% were inactive, 49.0% were minimally physical active, and 32.1% engaged in a health-enhancing level of physical activity. The mean scores for perceived stress, attitudes to eating, and self-efficacy were 18.0±6.2, 9.4±9.3, and 29.0±4.2, respectively. The mean score of depression was 5.4±5.2, and 19.4% had a total score of more than 10 (moderate to severe).

Factors associated with health-related quality of life

Table 3 presents the results of multiple linear regression to identify factors associated with the participants’ HRQOL. The values of R2 and adjusted R2, which indicate the goodness of fit of the model [21], were .101 and .047 for PCS and .635 and .613 for MCS, respectively. No factors had a statistically significant effect on PCS scores, while rank, duty time, perceived stress, and depression were all statistically significantly associated with MCS scores.

The average MCS score of officers was 3.63 lower than that of non-commissioned officers (t = -3.68, p <.001). In the past month, those who worked at night had lower MCS scores than those who worked during the day (t = -2.20, p = .029). Higher levels of perceived stress were associated with lower MCS scores (t = -5.76, p <.001); each 1-unit increase in stress led to a 0.61-point decrease in the MCS score after controlling for other variables (p < .001).


The findings of this study provide important information about HRQOL among women serving in the ROK Army. Approximately 7,550 military women currently serve in the ROK Army [22]. Although the number of military women in the ROK is increasing, research on them remains insufficient [5]. Furthermore, limited research has focused exclusively on particular rank or branch, ; therefore, this study is meaningful in that it provides basic data for understanding HRQOL among Korean female military junior officers, who account for 70% of military women.

A survey of 196 Korean female military junior officers showed that the PCS score was 56.0 points, which is higher than the score of 50.7 points reported for female college students of the same age and the score of 48.4 points reported for nurses [9,23]. In previous studies [12,24,25], several factors, including stress, attitude to eating, depression, BMI, smoking experience, and chronic disease, influenced the PCS. However, no variables significantly influenced the PCS in this study. This is most likely because soldiers engage in individual health behaviors through regular physical training and medical check-ups every year, and receive systematic health management to address physical aspects of quality of life.

The average MCS score was 47.2 points; although this value is higher than that of 45.3 points reported for female college students and 40.2 points for nurses of the same age [9,23], it is lower than 50 points, which is the average T-score suggested by the tool. Therefore, further measures are needed to improve the mental aspect of HRQOL among Korean female military junior officers. Rank, duty time, perceived stress, and depression affected the MCS in the current study. The MCS score of officers was 3.63 points lower than that of non-commissioned officers. This may reflect the different duty characteristics between officers and non-commissioned officers [26]. In addition, officers are promoted through a pyramid structure, which poses difficulties in terms of competitiveness, a discriminatory retirement age, a lack of job security, and individual military professional development [27]. Differences in rank can correspond to individual-level stress, which affects the MCS. Duty time also affected the MCS, as the MCS score of female military junior officers who mainly worked at night in the past month was 4.93 points lower than those who worked during the day. Military officers are assigned work according to the purpose of the mission, field training, and vigilance, which may cause irregular eating habits and sleep patterns, thereby predisposing individuals to negative health outcomes. Previous studies have found that night-shift workers were more vulnerable in terms of health and HRQOL than day-shift workers, corroborating the results of this study [28].

Stress and depression are also known to have a negative effect on MCS, as was confirmed in this study [26,28]. In a previous study [26], the quality of life of married military women was lower when they were not living with their families, had no support system, or experienced high stress in the workplace. There results suggest that working conditions need to be addressed in order to improve HRQOL among Korean female military junior officers. Currently, the ROK Army operates a joint childcare center to support work-family balance and strives to resolve psychological conflicts that cause stress and depression for military women by securing replacement personnel for those who have taken leave [22]. Finally, depression had a negative effect on the MCS. These results are partially consistent with previous studies [29]. In the U.S. military, based on the National Defense Authorization Act (NDAA), which has been strengthened since 2012, the Army has been required to perform mandatory screening tests for all soldiers each year through existing regular medical check-ups [30]. Considering that the depressing proportion of female officers is twice that of civilians of the same age and female officers have higher depression scores than male officers [29,31], it should be a priority to identify vulnerable groups through depression screening tests. To manage high-risk groups, the ROK Army needs to pay attention to the identification and systematic management of depression where indicated.

In conclusion, the ROK Army should continue to seek various ways to improve the MCS in order to resolve the mental difficulties faced by female military junior officers. There is currently no separate mental health program for female military junior officers in the ROK Army. Existing mental health programs focus on post-traumatic stress disorder [32], as such, insufficient research and interventions have been implemented to improve the MCS as part of HRQOL. Furthermore, different factors influence quality of life between male soldiers and junior female officers, including social support, adjustment to military service, physical environment, and health behaviors [33].

Our research has the following limitations. First, it is difficult to determine causality because this study is based on cross-sectional data obtained from a survey. Reporting bias may have been present because all variables were measured by self-report questionnaires from respondents. Second, since the period of service was limited to less than 5 years, these findings do not reflect changes in rank and service, making it difficult to generalize the results of this study to the entire ROK Army.

Despite these limitations, this study has the following strengths. First, in contrast to previous studies conducted mainly among male soldiers, this study assessed HRQOL and analyzed the factors that influenced it among Korean female military junior officer. Second, occupational and female-specific characteristics were considered in addition to general characteristics. For women, it is meaningful to consider these factors because psychological well-being is closely related with employment, marriage, pregnancy, and childcare, necessitating individualized research and interventions [34]. Third, we identified factors with negative and positive effects on the MCS. These findings are helpful in identifying which types of support should be focused on and which interventions should be implemented to improve the MCS.


Many previous studies have shown that stress and depression have negative effects on the MCS. Therefore, this study was conducted to suggest measures to improve the MCS among Korean female military junior officers. In particular, stress and depression showed significant associations with the MCS.

According to this study, we suggest that the ROK Army should consider the risk factors identified herein and provide early intervention and management for high-risk groups. First, programs are needed to identify and manage risk factors that cause stress, and an appropriate organizational atmosphere within the military must be created to promote such training programs. Second, depression screening tests should be required for early management by classifying individuals at a high risk of depression as a vulnerable group. Finally, given the high proportion of depression, it is suggested that regular HRQOL surveys are needed for members of the ROK Army, including female military junior officers.

List Of Abbreviations

ROK Republic of Korea

HRQOL Health-related quality of life

IRB institutional review board

PCS physical component summary

MCS mental component summary

SD standard deviation

IPAQ International Physical Activity Questionnaire

MET metabolic equivalent

EAT-26 Eating Attitudes Test-26

PHQ-9 Patient Health Questionnaire-9

BMI body mass index

NDAA National Defense Authorization Act


Ethics approval and consent to participate Our research protocol was submitted for consideration, commenting, guidance and approval to the institutional review board of Yonsei University and accepted before the study began (IRB approval number: Y-2019-0162).

Consent for publication Not applicable.

Availability of data and materials All data generated or The data supporting the findings of this study are not publicly available due to security of ROK army.

Competing interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.

Authors’ contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Eunji Kwon and Jeongok Park. The first draft of the manuscript was written by Eunji Kwon and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. This manuscript is a condensed form of the first author's master’s thesis from Yonsei University.

Acknowledgements The authors acknowledge the military women who participated in this study for their sincere responses to the survey.


  1. Ministry of National Defense. The act on human resources management. Accessed 29 January 2021.
  2. Hong C. The Phenomenological Analysis of Gender Equality Perception of Woman Junior Officers in the Army. The Quarterly Journal of Defense Policy Studies. 2014;30(3):199-226.
  3. Helmer SM, Krämer A, Mikolajczyk RT. Health-related locus of control and health behaviour among university students in North Rhine Westphalia, Germany. BMC Res Notes. 2012;5(1):703-10.
  4. Lim HJ, Seo SM. Physical Fitness according to Body Fat and Physical Activity Levels in Women University Students. J. Korean Soc. Living Environ. Sys. 2010;17(5):557-62.
  5. Yoon WS, Seok W, Lee SY, Hwang JS, Ann EG, Choi MS, et al. Health status of ROK military women. Journal of the Korean Military Medical Association. 2016;47(1):149-72.
  6. Kim AK. Yangsaeng and Health Related Quality of Life (HRQOL) in Middle Aged Women. Korean J Women Health Nurs. 2010;16(3):297-306.
  7. Lee GH, Kim CH, Shin HC, Park YW, Sung EJ. The Relation of Physical Activity to Helath Related Quality of Life. Korean Journal of Family Medicine. 2007;28(6):451-9.
  8. Centers for Disease Control and Prevention. Health-related quality of life (HRQOL). Accessed 29 January 2021.
  9. Cha BK. Factors Affecting Health-Related Quality of Life in Women Undergraduates. J Korean Acad Fundam Nurs. 2013;20(4):400-9.
  10. Herrold AA, Pape TL, Li X, Jordan N. Association Between Alcohol Craving and Health-Related Quality of Life Among Veterans With Co-occurring Conditions. Mil Med. 2017;182(7):e1712-e1717.
  11. Yoo MR, Choi JA, Hyun HS, Kim KW. A Study of Health Status and Health Behavior among the Military Officers in thier 20s and 30s. Korean Journal of Military Nursing Research. 2009;27(1):122-38.
  12. Maruish ME. User's manual for the SF-36v2 Health Survey. 3rd ed. Lincoln (RI): Quality Metric Incorporated; 2011.
  13. International Physical Activity Qustionnaire Group. IPAQ scoring protocol. Accessed 29 January 2021.
  14. Lee J, Shin C, Ko YH, Lim J, Joe SH, Kim S, et al. The Reliability and Validity Studies of the Korean Version of the Perceived Stress Scale. Korean Journal of Psychosomatic Medicine. 2012;20(2):127-34.
  15. Rhee MK, Lee YH, Park SH, Sohn CH, Chung YC, Hong SK, et al. A Standardization Study of the Korean Version of Eating Attitudes Test-26 I: Reliability and Factor Analysis. Korean Journal of Psychosomatic Medicine. 1998;6(2):155-75.
  16. Garner DM. Pathogenesis of anorexia nervosa. Lancet. 1993;341:1631-40.
  17. Lee YM, Schwarzer R, Jerusalem M. Korean Adaptation of the General Self-Efficacy Scale. Accessed 29 January 2021.
  18. Lee S, Huh Y, Kim J, Han C. Finding Optimal Cut Off Points of the Korean Version of the Patient Health Questionnaire-9 (PHQ-9) for Screening Depressive Disorders. Mood and Emotion. 2014;12(1):32-6.
  19. Spitzer RL, Kroenke K, Williams JB, Patient Health Questionnaire Primare Care Study Group. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. JAMA. 1999;282(18):1737-44.
  20. WHO expert consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157-63.
  21. Walker DA, Smith TJ. Nine Pseudo R2 Indices for Binary Logistic Regression Models. J Mod Appl Stat Methods. 2016;15(1):848-54.
  22. Ministry of National Defense. 2018 Defense White Paper. Accessed 29 January 2021.
  23. Kim K, Choi S. Influence of Nurses' Sense of Coherence on Their Stress and Quality of Life. J Korean Acad Nurs Adm. 2011;17(4):493-507.
  24. Rakovac M, Pedisic Z, Pranic S, Greblo Z, Hodak D. Sociodemographic and Lifestyle Correlates of Health-Related Quality of Life in Croatian University Students. Appl Res Qual Life. 2012;8(4):493-509.
  25. Leow MK, Griva K, Choo R, Wee HL, Thumboo J, Tai ES, et al. Determinants of Health-Related Quality of Life (HRQoL) in the Multiethnic Singapore Population–A National Cohort Study. PLoS One. 2013;8(6):e67138.
  26. Oh YR. Effects of work-family conflict and job stress on married female soldiers’ quality of life : A case of female officers’ in the South Korea Army [dissertation]. [Seoul]: Seoul National University; 2015. 55 p.
  27. Choi BS, Mun Y. Policy Alternatives Analysis on Army Officer Personnel Management System. Korean policy sciences review. 2006;10(1):51-78.
  28. Yun JY, Ham OK, Cho IS, Lim JY. Effects of Health Promoting Behaviors and Mental Health Status of Shift and Non-Shift Nurses on Quality of Life. J Korean Public Health Nurs. 2012;26(2):268-79.
  29. Kwag BG, Park JC, Lee W, Chang SH, Chun DH. The Relationship between Depression and Health-Related Quality of Life in Korean Adult: Using 2014 Korea National Health and Nutrition Examination Survey Data. Korean Journal of Family Practice. 2018:8(2);236-43.
  30. U. S. Army. 2014 National Depression Awareness Month. Accessed 29 January 2021.
  31. Woo SY, Kim HJ, Kim BR, Ahn HC, Jang BN, Park EC. Support from superiors reduces depression in Republic of Korea military officers. BMJ Mil Health. 2020 Feb 27.
  32. Angkaw AC, Haller M, Pittman JO, Nunnink SE, Norman SB, Lemmer JA, et al. Alcohol-Related Consequences Mediating PTSD Symptoms and Mental Health–Related Quality of Life in OEF/OIF Combat Veterans. Mil Med. 2015;180(6):670-5.
  33. Kim Y, Oh E. Health Behavior and Quality of Life among Korean Navy. Journal of Military Nursing Research, 2015;33(1):53-66.
  34. Park YR, Son YJ. Relationship of Satisfaction with Appearance, Self-Esteem, Depression, and Stress to Health Related Quality of Life in Women across the Lifespan. J Korean Acad Fundam Nurs. 2009;16(3):353.


Table 1. Differences in health-related quality of life according to general and occupational characteristics (N=196)



n (%) or

Mean ± SD

Health-Related Quality of Life

Physical Component Summary

t or F or r


Mental Component Summary

t or F or r


Mean ± SD

Mean ± SD

General characteristics

Age (years)


0.05 (.519)

0.14 (.056)

Body mass index (kg/m²)


7 (3.6)


2.68 (.048)


0.07 (.978)


145 (74.0)




21 (10.7)




23 (11.7)





101 (51.5)


1.33 (.184)


-0.13 (.896)


95 (48.5)




≤High school

9 (4.5)


1.16 (.316)


0.43 (.648)


45 (23.0)




142 (72.5)



Marital status


172 (87.8)


-1.06 (.290)


-2.22 (.027)


24 (12.2)



Living situation (n=24)

With spouse

16 (66.7)


-1.94 (.086)


-2.77 (.025)

Without spouse

8 (33.3)



Women’s characteristics

Age at menarche (years)


-0.05 (.476)

0.01 (.914)

Menstrual cycle (n=181)


133 (73.5)


0.98 (.327)


0.14 (.891)


48 (26.5)



Length of menstrual cycle (n=181)


0.06 (.399)

0.01 (.914)

Pregnancy experience


10 (5.1)


-0.25 (.806)


-1.38 (.169)


186 (94.9)



Number of pregnancies (n=10)


7 (70.0)


0.20 (.849)


-2.99 (.023)

2 or more

3 (30.0)



Delivery experience


8 (4.1)


-0.08 (.933)


-1.53 (.127)


188 (95.9)



Age at first birth (n=8)


-0.20 (.638)

-0.58 (.134)

History of oral contraceptive use 


50 (25.5)


0.81 (.419)


-1.15 (.251)


146 (74.5)



Duration of oral contraceptive use (month)


-0.04 (.669)

-0.15 (.159)

Occupational characteristics


Non-commissioned officer

69 (35.2)


-0.88 (.382)


2.39 (.018)


127 (64.8)





77 (39.3)


0.19 (.830)


0.05 (.949)

Technical & Administrative

41 (20.9)




78 (39.8)



Duration of service (month)


0.10 (.171)

0.12 (.088)

Working area

Urban area

94 (48.0)


0.56 (.576)


1.17 (.243)

Rural area

102 (52.0)



Duty time

Day time

164 (83.7)


0.82 (.444)


1.03 (.358)

Night time

9 (4.6)



Shift work

23 (11.7)



Service type

Short-term service

80 (40.8)


0.96 (.385)


0.23 (.793)

Extended service

44 (22.5)



Long-term service

72 (36.7)



Number of overtime days


-0.06 (.391)

-0.16 (.023)

Table 2. Descriptive statistics of the research variables (N=196)



Possible range


Health-Related Quality of Life





Physical function



Role limitations due to physical problems



Bodily pain



General health perception








Social functioning



Role limitations due to emotional problems



General mental health



Physical activity

Category 1 (inactive)

37 (18.9)

Category 2 (minimal physical activity)

96 (49.0)

Category 3 (health-enhancing physical activity)

63 (32.1)

MET (min/week)

Total physical activity


Walking activity


Moderate activity


Vigorous activity


Sitting activity per day(minutes)


Perceived stress



Attitudes to eating



Self-control of eating and bulimic symptom


Preoccupation with being thinner


Food preoccupation










0-4 (Normal)

106 (54.1)

5-9 (Mild depression)

52 (26.5)

10≤ (Moderate to severe depression)

38 (19.4)

PCS: physical component summary; MCS: mental component summary; MET: metabolic equivalent.

Table 3. Factors Associated with Health-Related Quality of Life (N=196)


Health-Related Quality of Life

Physical Component


Mental Component Summary







General and occupational characteristics


Marital status










Military rank (reference=

non-commissioned officer)









Duty time (reference=daytime)

Night time









Shift work









Number of overtime days









Physical activity (reference=

category 2; minimal physical activity) 

Category 1 (inactive)









Category 3 (health-enhancing physical activity)









Perceived stress









Attitudes to eating





























Adjusted R²






SE: standard error.