Literature DB >> 29253031

Gender-specific factors associated with the use of mental health services for suicidal ideation: Results from the 2013 Korean Community Health Survey.

Mina Kim1,2, Young-Hoon Lee3,4.   

Abstract

This study examined gender-specific factors associated with the use of mental health services (MHS) for suicidal ideation (SI). We included data on 6,768 males and 12,475 females who had experienced SI over the past year from the nationwide 2013 Korean Community Health Survey. These individuals were grouped as MHS users for SI if they had received professional counseling at medical institutions, professional counseling agencies, or community health centers for SI-related problems. Their information on sociodemographic factors, socio-familial relationships, health behaviors, and health status were included as exposures in a logistic regression analysis. Of the 19,243 individuals, 7.0% of the males and 10.5% of the females used MHS for SI treatment. For males with SI, living in an urban area, being a widower, and having unhealthy behaviors (frequent alcohol consumption and infrequent walking) were associated with underuse of MHS. For females with SI, frequent contact with friends, low level of religious activity, and good self-rated health were associated with underuse of MHS. For both males and females, those who were younger, completed higher education, and experienced depression/suicide attempts in the past year were more likely to use MHS for SI. These findings suggest that gender-specific factors should be used to inform suicide prevention strategies.

Entities:  

Mesh:

Year:  2017        PMID: 29253031      PMCID: PMC5734709          DOI: 10.1371/journal.pone.0189799

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Suicide is one of the most important public health issues in the world. Suicide rates vary widely across countries, and Korea has twice as high of a suicide rate compared with other Organization for Economic Cooperation and Development countries [1]. Korea’s suicide rate was 26.5 deaths per 100,000 people and was the fifth leading cause of death in 2015 [1]. Although most people with suicidal ideation (SI) do not die by suicide, SI is closely related to suicide attempts, and these suicidal behaviors are positively related to death by suicide [2]. Therefore, linking people with SI to appropriate mental health services (MHS) is an important strategy for preventing suicide. Studies have found that the majority of people at high risk for suicide do not use any form of MHS [3]. Suicide-related characteristics differ depending on gender. In almost all countries, males have a higher suicide rate than that of females [4], but females attempt suicide more often than do males [5]. Gender-specific associated factors should be considered in the prevention and management of suicide attempts, and the gender-specific factors underlying the use of MHS for SI should also be investigated. Previous studies have examined the associations between socioeconomic factors and use of MHS for SI [3,6-8]. However, there is a lack of research on the differences in factors related to the use of MHS by gender [9]. A Korean study reported that only 8.2% of adults with SI have used MHS for their mental health problems, and revealed the socioeconomic factors related to the use of MHS in the population with SI from the National Health Survey [10]. However, the small sample, limited independent variables, and the lack of an analysis by gender prevented a comprehensive understanding of the use of MHS among the general population with SI. Therefore, the purpose of this study was to provide information for establishing improved and customized suicide prevention policies by identifying gender-specific factors associated with the use of MHS for SI and by examining gender-specific barriers for those seeking help from MHS.

Methods

Study population

The Korean Community Health Survey (KCHS) conducted by the Korea Centers for Disease Control and Prevention is a nationwide survey that has been carried out annually since 2008 by trained surveyors using a computer-assisted personal interviewing method. Multistage, stratified, and random sampling was used to select representative households in 253 local Korean communities based on resident registration information resulting from surveying an average of 900 individuals from each local community. This study used data from the 2013 KCHS collected from August 16, 2013 to October 31, 2013. A total of 228,781 individuals (102,722 males and 106,059 females) aged ≥ 19 years participated in the 2013 survey. The 2013 KCHS provides population-based estimates of health indicators, including health status, morbidity, health service use, and health behaviors using a standardized questionnaire consisting of 258 questions. After excluding participants with missing data regarding sociodemographic variables, socio-familial relationships, health behaviors, and health status, 19,243 subjects (6,768 males and 12,475 females) who had experienced SI over the past year were included in the final analysis. This study was conducted in accordance with the Declaration of Helsinki guidelines. Written informed consent was obtained from all participants in the KCHS. The study protocol was approved by the Institutional Review Board of Wonkwang University Hospital (WKUH 2017-05-018).

Outcome and variables measurements

Suicide-related behaviors, including SI, suicide attempts, and use of MHS for SI, were evaluated using a questionnaire. SI was defined as having had thoughts of wanting to die in the past year. The use of MHS for SI included subjects who had received professional counseling at a medical institution, professional counseling agency, or community health center for SI-related problems in the past year. Information on each subject’s sociodemographic factors, socio-familial relationships, health behaviors, and health status was collected using a questionnaire. A detailed description of the variables used in this study is provided in Table 1.
Table 1

Independent variables used in this study.

VariableQuestionCategory
Sociodemographic factors
 GenderWhat is your gender?Male or female
 Age groupWhat is your age?19–44, 45–64, 64–74, or ≥75 years
 Residence typeWhere is your residence?Urban or rural
 Marital statusHave you ever been married (including a de facto marriage)?Which of the following is your current marital status?(1) I have a spouse and we live together(2) I have a spouse but we do not live together(3) No spouse due to death(4) No spouse due to divorceNever married, married, divorced/separated, or widowed
 Household compositionWhich of the following is your household type?Living alone, single generation, two generations, or three generations
 Education levelWhere did you go to school?Did you graduate from school?No formal education, primary school, middle or high school, or college and higher
 Monthly household incomeWhat was your average monthly household income in the past year, including wages, real estate income, pensions, interest, government subsidies, and allowances for relatives or children?≤1, 1.01–2, 2.01–4, or ≥4.01 million won
 Employment statusWhat is your occupation? Please list the specific type of work.Employed, unemployed, or housewife/student
 National Basic Livelihood Security statusDoes your household currently receive National Basic Livelihood Security?Recipient or non-recipient
Socio-familial relationships
 Contact with familyHow often do you see or contact your closest relatives (including your family)?<1 time or ≥1 time per month
 Contact with neighborsHow often do you see or contact your closest neighbors?<1 time or ≥1 time per month
 Contact with friendsHow often do you see or communicate with your closest friends (except your neighbors)?<1 time or ≥1 time per month
 Religious activitiesDo you participate in religious activities once per month or more?<1 time or ≥1 time per month
 Activities with friendsDo you regularly participate in activities with friends once per month or more?<1 time or ≥1 time per month
 Leisure activitiesDo you participate regularly in leisure activities at least once per month?<1 time or ≥1 time per month
 Charitable activitiesDo you participate in charitable activities once per month or more?<1 time or ≥1 time per month
Health behaviors and health status
 Smoking statusHave you smoked more than 5 packs (100 cigarettes) during your life?Do you smoke now?(1) I smoke every day(2) Sometimes I smoke(3) I smoked in the past but I do not smoke nowNever, former, or current smoker
 Frequency of alcohol useHave you ever drunk more than one drink in your life?Have you been drinking for the last year?How often do you drink alcohol?None, ≤1, 2–3, or ≥4 times per week
 Walking activityHow many days did you walk for at least 10 minutes at a time in the last week?≤2 or ≥3 times per week
 Sleep durationHow many hours a day do you usually sleep?≤6, 7–8, or ≥9 h per day
 Self-rated healthWhat do you think about your health?Good, fair, or poor
 Perceived daily stressHow often do you feel stressed in your daily life?Low or high
 Experience of depressed moodHave you ever felt sad or desperate for more than two consecutive months during the past year to the extent that it interferes with your daily life?No or yes
 Number of chronic diseasesHave you been diagnosed with any of the following diseases: obesity, hypertension, diabetes, dyslipidemia, stroke, myocardial infarction, angina pectoris, osteoarthritis, osteoporosis, asthma, or hepatitis B?≤2 and ≥3
 Diagnosis of depressionHave you been diagnosed with depression?No or yes
 Suicide attemptsHave you attempted suicide in the last year?No or yes

Statistical analysis

The participants’ characteristics were compared according to gender using the chi-square test. After adjusting for all of the evaluated covariates, the adjusted odds ratio (aOR) with 95% confidence interval (CI) of using MHS for SI were subjected to multivariate logistic regression analysis. Logistic regression analyses were performed separately for males and females. All statistical analyses were performed using SPSS Statistics for Windows ver. 22.0 (IBM Co., Armonk, NY, USA). A P-value < 0.05 was considered significant.

Results

Sample characteristics by gender

Characteristics according to gender are presented in Table 2. Of the 19,243 subjects who had experienced SI, 1,780 (9.3%) received professional counseling for SI, which was a significantly higher proportion in females (10.5%) than in males (7.0%). There were significant differences in age group, residence type, marital status, household composition, education level, monthly household income, and employment status between the genders; no significant difference in National Basic Livelihood Security (NBLS) status according to gender was observed. Compared with males, females contacted their family and neighbors more frequently and participated in religious activities more often. In contrast, males contacted their friends more frequently and participated more often in activities with friends and leisure than females. A greater proportion of males than females were current or past smokers and males tended to drink more frequently, but walk less frequently. Sleep duration and self-rated health status differed significantly according to gender. Compared with males, the proportions with high perceived daily stress, experienced depressive mood, having more than three chronic diseases, and diagnosis of depression were higher in females. The proportion of suicide attempts was higher in males (4.6%) than in females (3.9%).
Table 2

Comparison of variables according to gender.

VariableMales[n = 6,768]Females[n = 12,475]P
Dependent variable
 Mental health service for suicidal ideation<0.001
  Non-use6,297 (93.0)11,166 (89.5)
  Use471 (7.0)1,309 (10.5)
Sociodemographic factors
 Age group0.019
  19–44 years1,714 (25.3)3,303 (26.5)
  45–64 years2,541 (37.5)4,775 (38.3)
  65–74 years1,487 (22.0)2,513 (20.1)
  ≥75 years1,026 (15.2)1,884 (15.1)
 Residence type<0.001
  Urban3,581 (52.9)7,059 (56.6)
  Rural3,187 (47.1)5,416 (43.4)
 Marital status<0.001
  Married4,510 (66.6)7,380 (59.2)
  Never married1,020 (15.1)1,118 (9.0)
  Divorced/separated773 (11.4)1,075 (8.6)
  Widowed465 (6.9)2,902 (23.3)
 Household composition<0.001
  Living alone1,049 (15.5)2,248 (18.0)
  Single generation2,301 (34.0)3,377 (27.1)
  Two generations2,901 (42.9)5,597 (44.9)
  Three generations517 (7.6)1,253 (10.0)
 Education level<0.001
  No formal education334 (4.9)1,902 (15.2)
  Primary school1,544 (22.8)3,431 (27.5)
  Middle or high school3,201 (47.3)4,842 (38.8)
  College or higher1,689 (25.0)2,300 (18.4)
 Monthly household income0.034
  ≤1 million won2,646 (39.1)4,768 (38.2)
  1.01–2 million won1,473 (21.8)2,595 (20.8)
  2.01–4 million won1,652 (24.4)3,099 (24.8)
  4.01 million won997 (14.7)2,013 (16.1)
 Employment status<0.001
  Employed4,181 (61.8)5,659 (45.4)
  Unemployed2,462 (36.4)1,571 (12.6)
  Housewife or student125 (1.8)5,245 (42.0)
 National Basic Livelihood Security0.113
  Non-recipient6,191 (91.5)11,493 (92.1)
  Recipient577 (8.5)982 (7.9)
Socio-familial relationships
 Contact with family<0.001
  <1 time per month1,821 (26.9)2,441 (19.6)
  ≥1 time per month4,947 (73.1)10,034 (80.4)
 Contact with neighbors<0.001
  <1 time per month2,302 (34.0)3,446 (27.6)
  ≥1 time per month4,466 (66.0)9,029 (72.4)
 Contact with friends0.006
  <1 time per month2,081 (30.7)4,077 (32.7)
  ≥1 time per month4,687 (69.3)8,398 (67.3)
 Religious activities<0.001
  <1 time per month5,492 (81.1)8,340 (66.9)
  ≥1 time per month1,276 (18.9)4,135 (33.1)
 Activities with friends0.007
  <1 time per month3,641 (53.8)6,962 (55.8)
  ≥1 time per month3,127 (46.2)5,513 (44.2)
 Leisure activities<0.001
  <1 time per month5,374 (79.4)10,676 (85.6)
  ≥1 time per month1,394 (20.6)1,799 (14.4)
 Charitable activities0.893
  <1 time per month6,413 (94.8)11,815 (94.7)
  ≥1 time per month355 (5.2)660 (5.3)
Health behaviors and health status
 Smoking status<0.001
  Never smokers1,149 (17.0)11,113 (89.1)
  Former smokers2,472 (36.5)533 (4.3)
  Current smokers3,147 (46.5)829 (6.6)
 Frequency of alcohol use<0.001
  None1,867 (27.6)5,623 (45.1)
  ≤1 time per week2,266 (33.5)5,550 (44.5)
  2–3 times per week1,266 (18.7)946 (7.6)
  ≥4 times per week1,369 (20.2)356 (2.9)
 Walking activity0.002
  ≤2 times per week2,834 (41.9)4,939 (39.6)
  ≥3 times per week3,934 (58.1)7,536 (60.4)
 Sleep duration<0.001
  ≤6 h per day3,493 (51.6)6,990 (56.0)
  7–8 h2,818 (41.6)4,934 (39.6)
  ≥9 h per day457 (6.8)551 (4.4)
 Self-rated health<0.001
  Poor2,884 (42.6)5,662 (45.4)
  Fair2,406 (35.5)4,703 (37.7)
  Good1,478 (21.8)2,110 (16.9)
 Perceived daily stress<0.001
  Low3,001 (44.3)4,955 (39.7)
  High3,767 (55.7)7,520 (60.3)
 Experience of depressed mood<0.001
  No4,799 (70.9)8,146 (65.3)
  Yes1,969 (29.1)4,329 (34.7)
 Number of chronic diseases<0.001
  ≤25,653 (83.5)9,233 (74.0)
  ≥31,115 (16.5)3,242 (26.0)
 Diagnosis of depression<0.001
  No6,171 (91.2)10,657 (85.4)
  Yes597 (8.8)1,818 (14.6)
 Suicide attempt(s)0.009
  No6,454 (95.4)11,994 (96.1)
  Yes314 (4.6)481 (3.9)

Gender-specific factors predicting the use of MHS for SI

Univariate analyses showed that among males, sociodemographic factors (age group, residence type, marital status, household composition, education level, employment status, and NBLS), socio-familial relationships (contact with family, contact with neighbors, religious activity, and activities with friends), and health behaviors and health status (smoking status, frequency of alcohol use, walking activity, self-rated health, perceived daily stress, experience of depressed mood, number of chronic diseases, diagnosis of depression, and suicide attempts) were significantly associated with the use of MHS for SI. Among females, sociodemographic factors (age group, residence type, marital status, education level, employment status, and NBLS), socio-familial relationships (contact with family, contact with neighbors, religious activity, activities with friends, leisure activities, and charitable activities), and health behaviors and health status (smoking status, walking activity, sleep duration, self-rated health, perceived daily stress, experience of depressed mood, diagnosis of depression, and suicide attempts) were significantly associated with the use of MHS for SI (data not shown). Fully adjusted gender-specific relationships between the use of MHS for SI and sociodemographic factors, socio-familial relationships, and health behaviors and health status, as determined by logistic regression analysis, are presented in Tables 3 (males) and 4 (females). After full adjustment, the decreasing trend in the ORs for the use of MHS with increasing age remained significant for both genders. Compared with those aged 19–44 years, the aORs (95% CI) for use of MHS among those aged 45–64, 65–74, and ≥75 years were 0.59 (0.41–0.84), 0.54 (0.34–0.88), and 0.36 (0.19–0.67), respectively, for males and 0.85 (0.69–1.07), 0.67 (0.50–0.90), and 0.56 (0.38–0.82), respectively, for females. Males living in urban areas had a lower OR for using MHS than did males living in rural areas (aOR = 0.77, 95% CI = 0.59–0.99). After adjusting for related variables, the significant associations between marital status and use of MHS in the unadjusted model were no longer significant. Meanwhile, in the fully adjusted model, compared with married persons, use of MHS was significantly higher in widowers (aOR = 0.44, 95% CI = 0.23–0.88) but not in widows. The least-educated subjects (no formal education) had a lower OR for using MHS among both males (aOR = 0.39, 95% CI = 0.16–0.91) and females (aOR = 0.48, 95% CI = 0.33–0.70) compared with the most-educated subjects (college or higher). No significant association between employment status, NBLS and use of MHS was observed in either gender after adjustment for related factors.
Table 3

Factors predictive of the use of mental health services for suicidal ideation by logistic regression analysis among males.

VariablesFully adjusted OR (95% CI)P
Sociodemographic factors
 Age group
  19–44 years1.00
  45–64 years0.59 (0.41–0.84)0.004
  65–74 years0.54 (0.34–0.88)0.013
  ≥75 years0.36 (0.19–0.67)0.001
 Residence type
  Rural1.00
  Urban0.77 (0.59–0.99)0.048
 Marital status
  Married1.00
  Never married1.24 (0.85–1.83)0.268
  Divorced/separated1.27 (0.83–1.93)0.271
  Widowed0.44 (0.23–0.88)0.019
 Household composition
  Living alone0.80 (0.53–1.20)0.273
  Single generation0.83 (0.59–1.16)0.268
  Two generations1.00
  Three generations0.95 (0.59–1.55)0.841
 Education level
  College or higher1.00
  Middle or high school0.73 (0.54–0.98)0.036
  Primary school0.74 (0.49–1.13)0.163
  No formal education0.39 (0.16–0.91)0.030
 Employment status
  Housewife or student1.00
  Employed0.82 (0.40–1.68)0.582
  Unemployed0.99 (0.47–2.09)0.980
 National Basic Livelihood Security
  Non-recipient1.00
  Recipient1.30 (0.89–1.92)0.177
Socio-familial relationships
 Contact with family
  <1 time per month1.00
  ≥1 time per month1.18 (0.90–1.55)0.228
 Contact with neighbors
  <1 time per month1.00
  ≥1 time per month1.17 (0.88–1.54)0.280
 Religious activity
  <1 time per month1.00
  ≥1 time per month1.17 (0.88–1.56)0.281
 Activities with friends
  <1 time per month1.00
  ≥1 time per month1.07 (0.83–1.39)0.583
Health behaviors and health status
 Smoking status
  Never smokers1.00
  Former smokers0.85 (0.60–1.21)0.367
  Current smokers0.88 (0.63–1.22)0.430
 Frequency of alcohol use
  None1.00
  ≤1 time per week0.97 (0.71–1.33)0.850
  2–3 times per week0.77 (0.52–1.16)0.212
  ≥4 times per week0.58 (0.39–0.86)0.007
 Walking activity
  ≥3 times per week1.00
  ≤2 times per week0.70 (0.55–0.90)0.005
 Self-rated health
  Poor1.00
  Fair0.78 (0.57–1.05)0.102
  Good0.77 (0.54–1.11)0.165
 Perceived daily stress
  Low1.00
  High1.25 (0.96–1.63)0.098
 Experience of depressed mood
  No1.00
  Yes2.18 (1.70–2.79)<0.001
 Number of chronic diseases
  ≤21.00
  ≥31.15 (0.83–1.58)0.403
 Diagnosis of depression
  No1.00
  Yes29.95 (23.38–38.36)<0.001
 Suicide attempts
  No1.00
  Yes2.31 (1.58–3.39)<0.001
OR, odds ratio; CI, confidence interval
Table 4

Factors predicting of the use of mental health services for suicidal ideation by logistic regression analysis among females.

VariablesFully adjusted OR (95% CI)P
Sociodemographic factors
 Age group
  19–44 years1.00
  45–64 years0.85 (0.69–1.07)0.150
  65–74 years0.67 (0.50–0.90)0.007
  ≥75 years0.56 (0.38–0.82)0.003
 Residence type
  Rural1.00
  Urban0.98 (0.83–1.15)0.793
 Marital status
  Married1.00
  Never married1.28 (0.96–1.70)0.094
  Divorced/separated0.91 (0.70–1.17)0.455
  Widowed0.85 (0.68–1.07)0.160
 Education level
  College or higher1.00
  Middle or high school0.91 (0.73–1.14)0.426
  Primary school0.69 (0.52–0.92)0.012
  No formal education0.48 (0.33–0.70)<0.001
 Employment status
  Housewife or student1.00
  Employed0.85 (0.72–1.01)0.061
  Unemployed1.05 (0.82–1.36)0.692
 National Basic Livelihood Security
  Non-recipient1.00
  Recipient0.97 (0.75–1.26)0.828
Socio-familial relationships
 Contact with family
  <1 time per month1.00
  ≥1 time per month0.94 (0.78–1.14)0.544
 Contact with neighbors
  <1 time per month1.00
  ≥1 time per month0.93 (0.78–1.11)0.427
 Contact with friends
  <1 time per month1.00
  ≥1 time per month0.80 (0.68–0.95)0.011
 Religious activity
  <1 time per month1.00
  ≥1 time per month1.28 (1.09–1.49)0.002
 Activities with friends
  <1 time per month1.00
  ≥1 time per month1.01 (0.86–1.19)0.910
 Leisure activities
  <1 time per month1.00
  ≥1 time per month1.19 (0.96–1.47)0.112
 Charitable activities
  <1 time per month1.00
  ≥1 time per month1.31 (0.96–1.78)0.087
Health behaviors and health status
 Smoking status
  Never smokers1.00
  Former smokers0.86 (0.60–1.23)0.406
  Current smokers0.88 (0.67–1.15)0.343
 Walking activity
  ≥3 times per week1.00
  ≤2 times per week0.92 (0.79–1.07)0.284
 Sleep duration
  ≤6 h per day1.07 (0.92–1.25)0.372
  7–8 h1.00
  ≥9 h per day1.04 (0.74–1.48)0.822
 Self-rated health
  Poor1.00
  Fair0.98 (0.82–1.17)0.829
  Good0.78 (0.61–0.99)0.043
 Perceived daily stress
  Low1.00
  High1.03 (0.88–1.22)0.697
 Experience of depressed mood
  No1.00
  Yes2.15 (1.85–2.50)<0.001
 Diagnosis of depression
  No1.00
  Yes27.43 (23.55–31.95)<0.001
 Suicide attempts
  No1.00
  Yes3.12 (2.40–4.06)<0.001
OR, odds ratio; CI, confidence interval
After adjusting for related variables, more religious activity (aOR = 1.28, 95% CI = 1.09–1.49) was positively associated, and more contact with friends (aOR = 0.80, 95% CI = 0.68–0.95) was negatively associated with the use of MHS in females. However, none of the socio-familial factors showed an association in males after full adjustment. Compared with non-drinkers, the OR of using MHS was lower in males who drank ≥ 4 times/week in the fully adjusted model (aOR = 0.58, 95% CI = 0.39–0.86). Although walking activity was negatively associated with the use of MHS in both genders in the unadjusted model, only males who walked less had a lower likelihood of using MHS after full adjustment (aOR = 0.70, 95% CI = 0.55–0.90). After adjusting for related factors, the OR for using MHS was greater in females with good health (aOR = 0.78, 95% CI = 0.61–0.99) than in those with poor health. After adjusting for related factors, the OR for using MHS among those who experienced depressed mood was significantly higher (2.18-fold, 95% CI = 1.70–2.79) in males and (2.15-fold, CI = 1.85–2.50) higher in females compared with those who did not experience depressed mood. The OR for using MHS was significantly higher among males (aOR = 29.95, 95% CI = 23.38–38.36) and females (aOR = 27.43, 95% CI = 23.55–31.95) who were diagnosed with depression compared with those who were not diagnosed with depression. Males (aOR = 2.31, 95% CI = 1.58–3.39) and females (aOR = 3.12, 95% CI = 2.40–4.06) who had attempted suicide had a higher OR for using MHS compared with those who had not attempted suicide.

Discussion

Among the community-dwelling general population with SI, this study examined gender-specific associations between sociodemographic factors, socio-familial relationships, health behaviors, and health status with use of MHS. Significant relationships were observed between using MHS and residence type, marital status, frequency of alcohol use, and walking activity in males, whereas contact with friends, religious activity, and self-rated health were significantly associated with use of MHS in females. In contrast, our findings showed that age, education level, experience of depressed mood, depression diagnosis, and suicide attempts were associated with the use of MHS for SI in males and females. In a review of 12 studies, the utilization rate of professional mental health providers by people with SI, suicide plans, and/or suicide attempts during the past year was approximately 29.5% [3]. We defined the use of MHS as professional counseling at a medical institution, professional counseling agency, or community health center for SI-related problems. Especially, in this study, the use of mental health counseling only included counseling received from visiting a mental health professional and did not include telephone or internet counseling. In addition, only SI-related issues, and no other mental health problems, were included in the definition of the use of MHS for SI. In this study, 7.0% of males and 10.5% of females (9.3% in total) used MHS for SI, which is slightly higher than the rate reported in a previous Korean study [10]. Previous studies have consistently reported that age is an important predictor of using MHS for SI [8,10]. Older people are less sensitive to psychiatric symptoms, whereas younger people are more aware of the need for MHS [11,12]. Similar to previous studies, the present study identified that age and use of MHS for SI were inversely associated in males and females, although the magnitude of the association was greater in males. Education level, which is an important indicator of socioeconomic status, was positively associated with the use of MHS for SI in both genders in the present study. A previous study reported that education level was not a significant determinant of utilizing MHS in males or females [9], but other studies have shown a significant association between education level and the use of MHS for SI [8,10,13]. Highly educated people generally use MHS because they are less stigmatized about mental illness and have a positive attitude toward the effectiveness of treatment for mental illness [14,15], whereas those with lower levels of education are more economically burdened by MHS and are less aware of mental illness problems and treatment, resulting in limited use of MHS [15,16]. In addition, older age and lower education levels are related to less knowledge about suicide, which may affect seeking help for SI [17]. Marital status, especially widowed or divorced, has a greater influence on suicide mortality in males than females [18,19]. In addition, our previous study identified that widowed, divorced, or separated males attempted suicide significantly more frequently than did married males, but widowed, divorced, or separated females attempted suicide significantly less frequently than did married females [20]. In the present study, the frequency of MHS use was significantly lower in widowers compared with married persons, indicating that widowers are vulnerable to suicide in Korea. Death or divorce of a spouse is a significant risk factor for suicide in both genders, but the impact on females is somewhat weaker, because females continue to receive support through social and family connections even after losing their spouse [21]. In addition, traditional male gender roles, including greater levels of strength and independence, often prevent them from seeking help for suicidal feelings and depression [22]. A Korean study reported that the risk of not using MHS was 2.75-fold higher for widows than for married people, but the results were not evaluated by gender [10]. Two Canadian studies in adults with SI reported an association between marital status and use of MHS [8,9]. One study found a significantly higher use of MHS in unmarried and divorced people than in married people [8], while the other study reported that marital status and use of MHS were not related in males or females [9]. Social interaction and religious involvement are independently related to suicide [23]. One study showed that the incidence of suicide decreases with increasing social integration, indicating that higher levels of social integration are associated with protection against suicide in females [24]. In our study, less contact with friends and greater religious activities were significantly related to the use of MHS for SI in females only. These results are difficult to explain. However, determining the extent of involvement in a range of social relationships may provide useful information for assessing suicidal risk and establishing a tailored strategy [24]. It is possible that females with a better social support system may seek help from people around them rather than seeking help through MHS, while males do not seek such help. Further research is needed on the gender-specific associations between socio-familial relationships and the use of MHS. In this study, unhealthy behaviors, such as frequent drinking and lack of exercise, were significantly associated with not using MHS for SI in males, but not in females. Although not significant on multivariate analysis, the univariate analysis showed a significant association between current smoking and MHS use in males. To the best of our knowledge, no previous studies have examined gender-specific associations between health-related behaviors and MHS utilization by adults with SI. Unlike females, males who engage in unhealthy behaviors are more likely not to use MHS; thus, preventing suicide among males may require healthcare policies and societal concern to encourage the use of MHS for SI in males who are behaving in an unhealthy manner. Depression is an important risk factor for suicide [25]. Previous studies have shown that depression, psychiatric disorders, and psychiatric distress are important underlying factors for MHS use [8-10,26]. Our study found that a diagnosis of depression, experience of depressed mood, and suicide attempts were independently associated with the use of MHS in both genders, of which depression was the most potent factor in the use of MHS. Some limitations should be considered when interpreting the results of this study. First, due to the cross-sectional design, this study could not derive causal relationships. Second, information on SI, suicide attempts, and the use of MHS was collected retrospectively, so recall bias may have occurred. Third, although socio-familial relationships were included in our analysis, the distribution of community resources such as medical institutions and community health centers, access to healthcare facilities, and regional cultural differences that affect the use of MHS were not included [13]. Fourth, attitudes and stigma about mental illness or MHS use were not evaluated. Promoting a positive attitude and reducing the stigma associated with the use of MHS in the general public may facilitate seeking the help of mental health professionals. Lastly, although this study included a large number of samples, statistical significance can be influenced by sample size and the variance of variables between the genders. Despite these limitations, in this study, we analyzed data from a national health survey and assessed a representative large-scale general population. In addition, multiple covariates, such as socioeconomic information, socio-familial relationships, health behaviors, and health status, were investigated simultaneously according to gender.

Conclusions

This study identified gender-specific factors associated with the use of MHS in the general Korean population with SI. These findings suggest that gender-specific factors should be used to inform suicide prevention strategies. Further studies are required to demonstrate gender-specific causal relationships between MHS utilization and related factors in individuals with SI.
  25 in total

Review 1.  Suicide: a 15-year review of the sociological literature. Part I: cultural and economic factors.

Authors:  S Stack
Journal:  Suicide Life Threat Behav       Date:  2000

Review 2.  The depressed patient and suicidal patient in the emergency department: evidence-based management and treatment strategies.

Authors:  Bernard Chang; David Gitlin; Ronak Patel
Journal:  Emerg Med Pract       Date:  2011-09

Review 3.  Youth suicide risk and preventive interventions: a review of the past 10 years.

Authors:  Madelyn S Gould; Ted Greenberg; Drew M Velting; David Shaffer
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2003-04       Impact factor: 8.829

4.  Socioeconomic status and self-reported barriers to mental health service use.

Authors:  Leah Steele; Carolyn Dewa; Kenneth Lee
Journal:  Can J Psychiatry       Date:  2007-03       Impact factor: 4.356

5.  Marital status and suicide in the National Longitudinal Mortality Study.

Authors:  A J Kposowa
Journal:  J Epidemiol Community Health       Date:  2000-04       Impact factor: 3.710

6.  Gender differences in health service use for mental health reasons in community dwelling older adults with suicidal ideation.

Authors:  Helen-Maria Vasiliadis; Sarah Gagné; Natalia Jozwiak; Michel Préville
Journal:  Int Psychogeriatr       Date:  2012-12-05       Impact factor: 3.878

7.  Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication.

Authors:  Philip S Wang; Michael Lane; Mark Olfson; Harold A Pincus; Kenneth B Wells; Ronald C Kessler
Journal:  Arch Gen Psychiatry       Date:  2005-06

8.  Perceived need and help-seeking in adults with mood, anxiety, or substance use disorders.

Authors:  Ramin Mojtabai; Mark Olfson; David Mechanic
Journal:  Arch Gen Psychiatry       Date:  2002-01

9.  Long-term suicide risk of depression in the Lundby cohort 1947-1997--severity and gender.

Authors:  L Brådvik; C Mattisson; M Bogren; P Nettelbladt
Journal:  Acta Psychiatr Scand       Date:  2008-01-10       Impact factor: 6.392

10.  Gender-Specific Factors Associated with Suicide Attempts among the Community-Dwelling General Population with Suicidal Ideation: the 2013 Korean Community Health Survey.

Authors:  Mina Kim; Gyung Jae Oh; Young Hoon Lee
Journal:  J Korean Med Sci       Date:  2016-12       Impact factor: 2.153

View more
  1 in total

1.  Gender-specific factors related to suicidal ideation among community-dwelling stroke survivors: The 2013 Korean Community Health Survey.

Authors:  Mina Kim; Young-Hoon Lee
Journal:  PLoS One       Date:  2018-08-02       Impact factor: 3.240

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.