The Effects of Injury on Depression and Mental Health of South Korean Adults

 

Young-Chul Lee¹, Sang-Sub Park²

¹Dept. Fire Safety Management, Seojeong College, 1049-56, Hwahap-ro, Yongam-ri, Eunhyeon-myeon,

Yangju-si, Gyeonggi-do, 11429, South Korea

²Dept. Department, Emergency Medical Technology, Chungcheong University,38 Wolgok-Gil Gangnae-Myeon, Heungdeok-Gu, Cheongju-Si, Chungcheongbuk-Do,28171, South Korea

 

ABSTRACT:

Background/Objectives: This study aimed to determine the effects of injury experience on depression and mental health of adults. Methods/Statistical analysis: This study used the raw data from Korea Health Statistics 2014: Korea National Health and Nutrition Examination Survey (KNHANES VI-2). The respondents aged <20 years and those giving no response were excluded from this study. The subjects were screened in two phases. Congruity in individual ID, household ID, research district, gender, age, household income, education level, and occupation was examined in the process of screening and 4,755 persons were finally selected. Of the 4,755 persons, only 358 were reviewed for injury and depression diagnosis status. An SPSS Version 18.0 WIN program was used to analyze the data. Findings: The more household income (approx. 1.5 times; p<.01) and the higher education level (approx. 1.5 times; p<.01), the higher level of one-year experience of injury. As for occupation, technical service affected one-year experience of injury (p<.01). As for injury type, laceration/stab/amputation affected depression diagnosis status. As for injury intention, an accident was more likely to affect depression diagnosis status than intentional self-injury and violence. As for injury intention, intentional self-injury and violence (1.84 points) more adversely affected mental health than accidents (1.39) (p<.05). Improvements: Injury experience affected depression diagnosis status and mental health. In solving this problem, it is necessary to reinforce both mental health education programs and treatment and management programs.

 

 

 

 

1. INTRODUCTION:

Injury may infrequently or never occur in life. Injury may not occur only once but be repeated due to several causes¹. Young men aged 20-24 years were more likely to experience repeated injury. Injury type is related to penetrating wounds and machines². Injury is a cause of the burden of disease and work deficit and puts a greater burden on outpatients as well as on inpatients³.

 

Depressive symptoms can affect motor skills and increase psychological anxiety⁴. Material disorder is correlated with post-traumatic stress disorder⁵. Alcohol intake negatively affected mental health⁶. Violence affected depression among the symptoms of mental disease⁷. Depression affects mental health in diverse ways: motor skills, materials, alcohol intake, violence, and so on.

 

Emotional well-being can predict long-term prognoses of physical disease. That is, emotional improvement can improve the prognoses of physical disease⁸. Depression can put one at 7 times higher risk of a suicidal attempt⁹.Mental disease can increase the risk of contagious and non-contagious diseases and lead to unintended injury¹⁰. That is, an emotional state can either improve or worsen physical health status.

 

Participants in a mental health and stress management program become less depressed and anxious, use positive coping skills, and become better at resolving role conflicts¹¹. In treating depression and promoting mental health, it is necessary to reinforce efficient education and treatment/management programs. This study aimed to determine the effects of injury on depression and mental health.

 

However, little research has been conducted on the association between injury and depression and mental health in South Korea. For this reason, the raw data from the Ministry of Health and Welfare (MOHW) and the Korea Centers for Disease Control and Prevention (CDC)¹² were used. Depression and other mental conditions may develop suddenly or slowly. This study aimed to determine the correlation between injury and depression diagnosis status and mental health and help improve the quality of life. It intends to make a plan for treating depression and other mental diseases caused by injury and provide basic data related to mental health programs.

 

2. MATERIALS AND METHODS:

2.1. Research tools:

This study aimed to determine the effects of injury occurrence on mental health. It used the raw data from Korea Health Statistics 2014: KNHANES VI-2 of MOHW and CDC¹². To obtain the results, the raw data were reviewed in terms of such areas as injury and mental health.

 

To determine the effects of injury on mental health of adults, only the persons aged ≥20 years were included in this study. Those aged <20 years were excluded. Two groups of raw data were used: basic DB (health examination) and injury and healthcare. There were 7,550 persons in basic DB (health examination) and 6,888 in the area of injury and healthcare.

 

To obtain the results, two groups of raw data were composed: basic DB (health examination) and injury and healthcare. Two-phase screening was performed to build a group of analysis data. Of the 7,550 persons in basic DB (health examination), 5,906 were screened in the first phase, with the exception of 1,644 who were aged <20 years or made no answer. Of the 6,888 persons in the area of injury and healthcare, 5,370 were screened in the first phase, with the exception of 1,518 who were aged <20 years or made no answer.

of the 5,906 persons in basic DB (health examination), 4,755 were screened in the second phase, with the exception of 1,151 who made no answer to the questions about individual ID, household ID, research district, gender, age, household income, education level, and occupation, who had missing data, and who were overlapped. Of the 5,370 respondents in the area of injury and healthcare, 4,755 were screened in the second phase, with the exception of 615 who made no answer to the questions about individual ID, household ID, research district, gender, age, household income, education level, and occupation, who had missing data, and who were overlapped.

 

Congruity in individual ID and household ID between the two groups was examined in the process of two-phase screening in basic DB (health examination) and the area of injury and healthcare and 4,755 persons were finally selected. Only 358 persons answering to the questions about injury experience and depression diagnosis status were reviewed.

 

This study used the following variables: the socio-economic variables included gender, age, household income, education level, and occupation; the injury-related variables included injury experience, injury season, and injury type; and the variables related to mental health included depression diagnosis experience and mental health. Mental health was examined in a four-point likert scale with nine items, with a higher score meaning worse mental health: 0 none, 1 for several days, 2 for a week or longer, and 3 almost every day.

 

This study used the raw data from KNHANES. Approval was obtained from the Institutional Review Board (IRB) in C University before data collection. It was performed on the basis of exemption as a result of deliberation for approval (Human-005-20161031-1st).

 

2.2. Analysis method:

An SPSS Version 18.0 WIN program was used to analyze the data. Specifically, χ2, t-test, ANOVA, multiple regression analysis, and dichotomous logistic regression were performed. The significance level was set at p<.05.

 

3. RESULTS:

3.1. Differences in one-year experience of injury by socio-demographic characteristics:

The differences in injury experience by the socio-demographic characteristics are as in Table 1. For the recent single year, 7.5% experienced injury (Yes) and 92.5% had no experience of injury (No).

 

Those at the middle and high levels of household income (31.0%) were statistically significantly more likely to experience an accident over the recent single year (p<.05). As for education level, high school graduates (30.4%) were statistically significantly more likely to experience an accident over the recent single year (p<.05). As for occupation, the unemployed (39.9%) and technical service providers (15.1%) were statistically significantly more likely to experience an accident over the recent single year (p<.05). No significant difference was found in the other items.

 

 

Table 1; Differences in one-year experience of injury by socio-demographic characteristics

*p<.05

 

 

3.2. Effects of socio-demographic characteristics on injury experience:

Dichotomous logistic regression was used to determine the effects of the socio-demographic characteristics on injury experience. Dichotomous logistic regression is used when a dependent variable is binary. The independent variables included gender, age, household income, education level, and occupation. For analysis, they were changed into dummy variables. The results are presented in Table 2.

 

Those at the middle and low (approx. 1.4 times; p<.01) and high (approx. 1.5 times; p<.01) levels of household income were more likely to experience injury over the recent single year. As for education level, college graduates (approx. 1.5 times; p<.01) were more likely to experience injury over the recent single year. As for occupation, technical service affected injury occurrence over the recent single year (p<.01).

 

3.3. Differences in depression diagnosis status by injury characteristics:

The differences in depression diagnosis status by the injury characteristics are as in Table 3. 7.5% (N=358) of a total of 4,755 persons answered to the question about depression diagnosis status. Of these persons (N=358), 6.4% were depressed and 93.6% were not depressed. No statistically significant difference was found in any item.

 

 

 

 

Table 2; Effects of socio-demographic characteristics on injury experience

Category		B	Odds Ratio	p	95% Confidence interval
					lower	upper
Gender#	Male		1.00
	Female	.005	1.005	.965	.807	1.251
Age#	20-29		1.00
	30-39	.290	1.336	.171	.882	2.025
	40-49	.420	1.521	.054	.992	2.333
	50-59	.055	1.057	.782	.715	1.562
	60≤	.075	1.078	.681	.753	1.543
Household income#	Low		1.00
	Mid low	.332	1.394	.040*	1.015	1.915
	Mid high	.130	1.139	.391	.846	1.532
	High	.404	1.498	.013*	1.090	2.058
Education level#	Elementary school graduates		1.00
	Junior high school graduates	.243	1.275	.206	.875	1.859
	High school graduates	.303	1.354	.031*	1.028	1.785
	University graduates≤	.420	1.521	.004**	1.146	2.019
Occupation#	Manager & professional		1.00
	Office worker	-.052	.949	.843	.569	1.584
	Service provider	-.245	.783	.291	.497	1.233
	Agriculture, forestry, & fishery worker	-.352	.704	.216	.403	1.227
	Technical service provider	-.762	.467	.001***	.301	.722
	Manual laborer	-.311	.733	.211	.450	1.192
	Unemployed (housewife/student)	-.199	.819	.296	.564	1.190

*p<.05, **p<.01, ***p<.001

# An independent variable is changed into a dummy variable. A dependent variable is one-year experience of injury.

 

 

Table 3; Differences in depression diagnosis status by injury characteristics

Category		Depression diagnosis(358)#		χ2	p
		Yes : 23(6.4)	No : 335(93.6)
Number of injuries	1	22(95.7)	315(94.0)	.103	.749
	2≤	1(4.3)	20(6.0)
Injury season	Spring	5(21.7)	82(24.5)	1.230	.746
	Summer	5(21.7)	100(29.3)
	Autumn	6(26.1)	78(23.3)
	Winter	7(30.4)	7522.4)
Injury type	Transportation accident	6(26.1)	81(24.2)	.082	.994
	Fall/slip/bump.	12(52.2)	183(54.6)
	Laceration/stab/amputation/penetrating wound.	2(8.7)	26(7.8)
	Others	3(13.0)	45(13.4)
Treatment institution	ER	3(13.0)	52(15.5)	1.250	.535
	Hospital/Clinic outpatient	15(65.2)	179(53.4)
	Hospital/Clinic hospitalization	5(21.7)	104(31.0)
Injury intention	Unexpected accident	22(95.7)	331(98.8)	1.554	.212
	intentional self-injury/ violence	1(4.3)	4(1.2)

# Of a total of 4,755 persons, only 358 answering to questions about injury characteristics were analyzed.

 

3.4. Effects of injury characteristics on depression diagnosis status:

Dichotomous logistic regression was used to determine the effects of the injury characteristics on depression diagnosis status. The dependent variable was depression diagnosis status. The independent variables were the number of injuries, injury season, injury type, injury treatment institution, and injury intention. For analysis, they were changed into dummy variables. The results are presented in Table 4.

 

As for injury season, summer was insignificantly more likely to affect depression diagnosis status (1.1 times). As for injury type, laceration/stab/amputation wounds were insignificantly more likely to affect depression diagnosis status. As for injury intention, an accident was insignificantly more likely to affect depression diagnosis status than intentional self-injury and violence.

 

3.5. Differences in mental health by injury characteristics:

The differences in mental health by the injury characteristics are as in Table 5. As for injury intention, intentional self-injury and violence (1.84) was statistically significantly more likely to adversely affect mental health than accidents (1.39) (p<.05). No significant difference was found in the other items.

 

Table 4; Effects of injury characteristics on depression diagnosis status

Category		B	Odds Ratio	p	95% Confidence interval
					lower	upper
Number of injuries#	1		1.00
	2≤	-.231	.794	.316	.505	1.247
Injury season #	Spring		1.00
	Summer	.105	1.111	.820	.448	2.754
	Autumn	-.325	.722	.448	.312	1.674
	Winter	-.519	.595	.196	.271	1.306
Injury type#	Transportation accident		1.00
	Fall/slip/bump.	-.377	.686	.248	.362	1.301
	Laceration/stab/amputation/penetrating wound.	.894	2.444	.169	.683	8.745
	Others	-.487	.614	.319	.236	1.601
Treatment institution#	ER		1.00
	Hospital/Clinic outpatient	-.412	.662	.137	.385	1.139
	Hospital/Clinic hospitalization	.143	1.154	.757	.466	2.858
Injury intention#	Unexpected accident		1.00
	intentional self-injury/ violence	-.178	.837	.440	.533	1.315

# An independent variable is changed into a dummy variable. A dependent variable is depression diagnosis status.

# Of a total of 4,755 persons, only 358 answering to questions about injury characteristics were analyzed.

 

Table 5; Differences in mental health by injury characteristics

Category		Mental health(N:358)#
		M	S.D	t/F	p
Number of injuries#	1	1.402	.496	.628	.530
	2≤	1.333	.308
Injury season #	Spring	1.384	.490	.225	.879
	Summer	1.404	.422
	Autumn	1.373	.461
	Winter	1.430	.585
Injury type#	Transportation accident	1.358	.417	2.414	.066
	Fall/slip/bump.	1.454	.540
	Laceration/stab/amputation/penetrating wound.	1.234	.257
	Others	1.335	.453
Treatment institution#	ER	1.434	.480	.324	.724
	Hospital/Clinic outpatient	1.380	.492
	Hospital/Clinic hospitalization	1.411	.483
Injury intention#	Unexpected accident	1.391	.483	-2.072	.039*
	intentional self-injury/ violence	1.844	.601

*p<.05# Of a total of 4,755 persons, only 358 answering to questions about injury characteristics were analyzed.

 

 

 

 

4. CONCLUSION:

This study aimed to determine the effects of injury on depression and mental health of adults. As for injury intention, intentional self-injury and violence and accidents adversely affected mental health. As for injury type, laceration/stab/amputation affected depression diagnosis status. As for injury intention, an accident was more likely to affect depression diagnosis status than intentional self-injury and violence.

 

The following suggestions can be made to treat depression and restore mental health. First, it is necessary to reinforce mental health education programs. Accidents and intentional self-injury may cause one to experience post-traumatic stress disorder. Education is a way of helping treat depression and restore mental health. Second, it is necessary to reinforce mental health treatment and management programs. This is a way of realizing sustainable, long-term recovery in case of adverse effects on depression and other mental conditions. The efforts to reinforce mental health education and treatment/management programs are expected to help develop preventive programs.

 

This study has some limitations: first, the group aged <20 years was excluded in determining depression diagnosis status and mental health; second, those who were aged ≥20 years and were incongruous in terms of individual ID, household ID, research district, gender, age, household income, education level, and occupation were excluded from analysis. Care should be taken to generalize the results in comparing with other studies. Nevertheless, these results are expected to help develop systems for education and treatment related to depression and mental health.

 

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Accepted on 16.07.2017          © RJPT All right reserved