The effects of diabetes on mental health in South Korean adults

Abstract

BACKGROUND:

The changes in dietary habits can affect mental health problems, such as depressive disorder, due to the occurrence of diabetes.

OBJECTIVE:

This study aimed to determine the effects of diabetes on mental health (Patient Health Questionnaire-9: PHQ-9).

METHODS:

A secondary data analysis of cross-sectional design based on the raw data from KNHANES VII-1 was performed, which were disclosed by MOHW and KCDC. Of 8,150 respondents, 5,661 respondents aged $\geqslant$ 20 years were included, thus excluding 2,489 respondents. Data were analyzed using an SPSS version 20.0 program.

RESULTS:

The respondents scored high for diabetes diagnosis status (3.65), suicide planning status for a year (8.56), mental problem counseling for a year (7.80), and the degree of daily stress awareness (8.27) in PHQ-9. They scored higher for suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness than for diabetes diagnosis status in PHQ-9. Positive correlation was found among diabetes diagnosis status, suicide planning status for a year, mental problem counseling for a year, and daily stress awareness in PHQ-9 ( $p<$ 0.01). Diabetes diagnosis status ( $p<$ 0.01), suicide planning status for a year ( $p<$ 0.001), mental problem counseling for a year ( $p<$ 0.001), and the degree of daily stress awareness ( $p<$ 0.001) affected PHQ-9.

CONCLUSION:

PHQ-9 for screening depressive disorder based on diabetes diagnosis status had low scoring distribution. However, because diabetes diagnosis status significantly affected PHQ-9 for depression screening, it is necessary to pay attention to health care related to diabetes. Further research should be conducted on the association with diverse causes of the low scoring distribution in PHQ-9 in relation to diabetes.

Keywords

Diabetes mental health PHQ-9 stress mental problem counseling

1. Introduction

KDA [1] and Park [2] indicated that diabetes could be divided into Types 1 and 2; the former is caused by insulin deficiency and the latter is caused by inefficient insulin, which involves excessive calorie intake due to wrong dietary habits, reduced exercise, and stress. They noted that Type 1 diabetes is insulin-dependent and Type 2 diabetes is non-insulin-dependent [1]. Aljasem et al. [3] and Osborn et al. [4] contended that diabetes was correlated with depression and health awareness.

Oquendo et al. [5] noted that depression led to a seven-fold increase in the risk of suicide attempt. Groot et al. [6] contended that depression, anxiety disorder, and behavioral disorder affected Types 1 and 2 diabetes. Lamers et al. [7] noted that emotional well-being could predict long-term prognoses of physical disease. Aljasem et al. [3] indicated that psychological variables were regarded as predictors of diabetes management, which included depression, social support, and self-efficacy. Osborn et al. [4] contended that health awareness affected self-management of diabetes and glycemic control through the association with social support. This can imply that health awareness affects diabetes, which then affects mental health.

Prince et al. [8] noted that mental illness might increase the risk of infectious and non-infectious diseases and cause unintentional injury. In contrast, Shapiro et al. [9] found that the participants in a mental health and stress management program became less depressed and less anxious, used positive coping skills, and became more competent in resolving role conflicts.

Groot et al. [10] found that Type 1 diabetics with the medical history of depression made poorer glycemic control than those without mental illness and Type 2 diabetics with the medical history of depression made poorer control than those without mental illness. In addition, Gavard et al. [11] divided previous studies into controlled and uncontrolled ones to determine the association between diabetes and depression. In diabetes samples, the rate of depression ranged from 8.5% to 27.3% for controlled studies and from 11.0% to 19.9% for uncontrolled ones. The rate of clinically significant depressive symptoms ranged from 21.8% to 60.0% for controlled studies and from 10.0% to 28.0% (19.6% on average) for uncontrolled ones.

Previous studies were conducted using Patient Health Questionnaire-9 (PHQ-9) for efficient mental health care [12, 13, 14, 15, 16] and what is common among them is the need of efficient mental health care. PHQ-9 is composed of nine items, each of which is scored 0–3, with the total score ranging from 0 to 27. Those scoring $\geqslant$ 10 in PHQ-9 are considered to have depressive disorder. Because depressive and behavioral disorders can affect diabetes, which is the theme of this study, as well as other types of disease, it is necessary to develop efficient health care programs.

This study aimed to determine the association between diabetes and mental health on the basis of the raw data disclosed by the Ministry of Health and Welfare (MOHW) and the Korea Centers for Disease Control and Prevention (KCDC) [17]. The changed dietary habits can increase the occurrence of diabetes, which can possibly affect mental health problems, such as depressive disorder, in the society of today, which becomes diversified. The raw data were obtained from three types of research: health surveys, physical examination surveys, and nutrition surveys. This study aimed to use the items concerning diabetes and mental health in the health surveys to determine the association between diabetes and mental health. The ultimate goal was to provide basic data that could help develop health care programs to prevent diabetes and mental health problems (stress and depressive disorder) and lead a psychologically and physically comfortable life.

2. Methods

2.1 Design of the study

This study is a secondary data analysis of cross-sectional design to determine the “association between diabetes and mental health” on the basis of the raw data from the Korea National Health and Nutrition Examination Survey (KNHANES VII-1), which were disclosed by MOHW and KCDC [17].

2.2 Subjects

The subjects were chosen using two-step stratified cluster sampling, which is to make primary and secondary samples of districts and households on the basis of the recent data from the Population and Housing Census. Some households were sampled and the data from those members aged $\geqslant$ 1 year who met the requirements of qualification were used. In 2014, 10,806 persons from 3,840 households in 192 districts were potential respondents to the survey; 8,150 persons (75.4%) participated in the survey.

Of the 8,150 participants in KNHANES VII-1, the data from 5,661 respondents, who were all aged $\geqslant$ 20, were included in the study (Table 1). Participants were excluded if they were aged $\leqslant$ 19 years, gave no answer, poorly completed the questionnaire, or had missing data. The 5,661 participants were analyzed to determine the association between diabetes and mental health in adults.

Table 1
Subjects

		Diabetes diagnosis status (5,661)				$\chi^{2}$	$p$
		Yes: 572 (10.1)		No: 5,089 (89.9)
Gender	Male	270	(11.1)	2156	(88.9)	4.912	0.027 ${}^{*}$
	Female	302	(9.3)	2993	(90.7)
Age	20’s	–		606	(100.0)	528.316	0.000 ${}^{***}$
	30’s	9	(0.9)	1,022	(99.1)
	40’s	41	(3.8)	1,037	(96.2)
	50’s	107	(10.3)	943	(89.7)
	60’s	173	(18.0)	797	(82.0)
	70’s $\leqslant$	242	(25.6)	703	(74.4)
Household income	Low	228	(21.3)	842	(78.7)	199.784	0.000 ${}^{***}$
	Mid low	140	(10.0)	1,256	(90.0)
	Mid high	115	(7.4)	1,446	(92.6)
	High	89	(5.4)	1,545	(94.6)
Occupation	Managers & professionals.	30	(4.0)	715	(96.0)	113.045	0.000 ${}^{***}$
	Clerks	20	(3.3)	581	(96.7)
	Sales & service workers	53	(7.2)	681	(92.8)
	Agricultural & fishery workers	36	(15.3)	199	(84.7)
	Skilled workers & manual workers	113	(10.7)	948	(89.3)
	Unemployed (housewives & students)	320	(14.0)	1,965	(86.0)

${}^{*}p<$ 0.05, ${}^{***}p<$ 0.001.

2.3 Tools or instruments

This study used the raw data from Korea Health Statistics 2016: KNHANES VII-1, as disclosed by MOHW and KCDC [17]. The guidelines for using the raw data from KNHANES were composed of three items: health surveys, physical examination surveys, and nutrition surveys. Of these, the current study used health surveys. Health surveys can be divided into household surveys, health-related interviews, and health behavior surveys. Household surveys (using interview) are conducted for the number of household members, household type, and household income in a single adult within a household. Health-related interviews are performed for morbidity, healthcare use, restraints on activity, education and economic activity, physical activity, and so on. Health behavior surveys are conducted for smoking, alcohol intake, mental health, a sense of safety, oral health, and so on. The items concerning diabetes and mental health were drawn from the health surveys to conduct this study. The instruments in this study are presented in Table 2.

Table 2
Instrument composition

	Contents
Health survey	• Household survey • Health-related interview • Health behavior survey	• Household survey: Number of household members, household income, etc. • Health-related interview: Morbidity (diabetes, hypertension, heart disease, cancer, etc.), healthcare use, restraint on activity, education and economic activity, physical activity, etc. • Health behavior survey: Smoking, alcohol intake, mental health, a sense of safety, oral health, etc.
Physical examination survey	Blood test, oral examination, pulmonary function test, etc.
Nutrition survey	Dietary life survey, food safety survey, food intake survey, etc.

Contents

Health survey

•

Household survey

•

Health-related interview

•

Health behavior survey

•

Household survey: Number of household members, household income, etc.

•

Health-related interview: Morbidity (diabetes, hypertension, heart disease, cancer, etc.), healthcare use, restraint on activity, education and economic activity, physical activity, etc.

•

Health behavior survey: Smoking, alcohol intake, mental health, a sense of safety, oral health, etc.

Physical examination survey

Blood test, oral examination, pulmonary function test, etc.

Nutrition survey

Dietary life survey, food safety survey, food intake survey, etc.

2.4 Variable used in the study

The variables in this study included socio-demographic-, diabetes-, and mental health-related variables. The socio-demographic variables were gender, age, household income, and occupation, as presented in Table 3.

Table 3
Composition of socio-demographic variables

	Contents
Socio-economic	Gender	Male, female
characteristics	Age	20’s, 30’s, 40’s, 50’s, 60’s, 70’ $\leqslant$
	Household income	Low, mid low, mid high, high
	Occupation	Managers and professionals, clerks, sales and service workers, agricultural and fishery workers, skilled workers and manual workers, unemployed (housewives and students)

The diabetes-related variables were diabetes diagnosis status and diabetes treatment status. The variables related to mental health were stress – degree of stress awareness, suicide planning status for a year, and mental problem counseling for a year – and PHQ-9 for screening depression in terms of depressive disorder.

Stress awareness and PHQ-9 were rated on a Likert scale. For stress awareness, the scores ranged from 1 to 4 – 1 feel almost no stress, 2 feel some stress, 3 feel much stress, and 4 feel a lot of stress – with a higher score meaning a higher level of stress. PHQ-9 was rated on a Likert scale with the scores ranging from 0 to 3: 0 not at all, 1 almost every day, 2 more than a week, and 3 almost every day. PHQ-9 is composed of nine items, with the total score ranging from 0 to 27; those scoring $\geqslant$ 10 are considered to have depressive disorder. Higher scores in PHQ-9 are more strongly correlated with depressive disorder. Composition of the variables related to diabetes and mental health are presented in Table 4.

Table 4

Composition of variables related to diabetes and mental health

	Contents
Diabetes		Diabetes diagnosis status	Yes, no
		Diabetes treatment status	Yes, no
Mental health	Stress	Degree of usual stress awareness	Feel almost no stress, feel some stress, feel much stress, feel a lot of stress
		Suicide planning status for a year	Yes, no
		Mental problem counseling for a year	Yes, no

Depressive disorder

{}^{*}

– Patient Health Questionnaire-9 (PHQ-9)

Feel almost no interest or joy in working

Feel down, depressed, or frustrated

Hardly fall asleep, awake from sleep repetitively, or oversleep

Feel tired or helpless

Lose appetite or overeat

Feel like being a loser or having disappointed myself and my family

Have difficulty in concentrating on newspaper or TV

So slow in moving or speaking that others can recognize it. or the opposite

Think that I’d better die or try to injury myself

•

Fraction of scoring $\geqslant$ 10 out of 27 in PHQ-9 ${}^{**}$

•

For depressive disorder, 9 items in PHQ-9 related to depression.

•

PHQ-9 has a four-point scale – 0 none, 1 for several days, 2 for more than a week, and 3 almost every day – with the total score ranging from 0 to 27

${}^{*}$ Han et al. Validation of the Patient Health Questionnaire-9 (PHQ-9) Korean version in the Elderly Population, 2008. ${}^{**}$ An et al., Standardization of the Korean version of Screening Tool for Depression (Patient Health Questionnaire-9, PHQ-9), 2013.

Figure 1.

Procedure of research.

2.5 Procedure and analysis

This study performed secondary data analysis to determine the “association between diabetes and mental health” on the basis of the raw data from KNHANES. The procedure involved theme selection, literature review and data collection, request for data (KNHANES VII-1), review of raw data from KNHANES VII-1, extraction of items concerning diabetes and mental health among raw data, and result analysis (Fig. 1). For ethical consideration, this study has been exempted from approval by the Institutional Review Board (IRB) in C University (Human-006-20180913-1st). The data were analyzed using an SPSS version 20.0 program to obtain results. Specifically, cross-tabulation analysis, $t$ -test, ANOVA, correlation analysis, and regression analysis were performed. The significance level was set at $p<$ 0.05.

3. Results

3.1 Diabetes treatment status by general characteristics

Diabetes treatment status by the general characteristics is presented in Table 5. Age was correlated with diabetes treatment status in all the age groups except those in their twenties. Those in their fifties, sixties, and seventies or over were more likely to have diabetes treated than to get no treatment. Those in their seventies or over, followed by those in their sixties and fifties, were most likely to have diabetes treated, which was statistically significant ( $p<$ 0.001). The remaining items, such as gender, household income, and occupation, had no significant effect.

Table 5
Diabetes treatment status by general characteristics

		Diabetes treatment status (572)				$\chi^{2}$	$p$
		Yes: 534 (93.4)		No: 38 (6.6)
Gender	Male	249	(92.2)	21	(7.8)	1.061	0.303
	Female	285	(94.4)	17	(5.6)
Age	20’s	–		–		19.968	0.001 ${}^{***}$
	30’s	6	(66.7)	3	(33.3)
	40’s	35	(85.4)	6	(14.6)
	50’s	99	(92.5)	8	(7.5)
	60’s	169	(97.7)	4	(2.3)
	70’s $\leqslant$	225	(93.0)	17	(7.0)
Household income	Low	210	(92.1)	18	(7.9)	2.917	0.405
	Mid low	129	(92.1)	11	(7.9)
	Mid high	111	(96.5)	4	(3.5)
	High	84	(94.4)	5	(5.6)
Occupation	Managers and professionals	29	(96.7)	1	(3.3)	1.389	0.925
	Clerks	19	(95.0)	1	(5.0)
	Sales and service workers	48	(90.6)	5	(9.4)
	Agricultural and fishery workers	34	(94.4)	2	(5.6)
	Skilled workers and manual workers	105	(92.9)	8	(7.1)
	Unemployed (housewives and students)	299	(93.4)	21	(6.6)

${}^{***}p<$ 0.001.

3.2 Differences in Patient Health Questionnaire-9 (PHQ-9) by general characteristics

The differences in PHQ-9 by the general characteristics are presented in Table 6. PHQ-9 is composed of nine items, each of which is scored 0–3, with the total score ranging from 0 to 27. Those scoring $\geqslant$ 10 in PHQ-9 are considered to have depressive disorder.

Table 6
Differences in Patient Health Questionnaire-9 (PHQ-9) by general characteristics

		Patient Health Questionnaire-9 (PHQ-9)
		N	M	S.D	t/F	$p$
Gender	Male	2,426	2.10	3.302	$-$ 10.723	0.000 ${}^{***}$
	Female	3,235	3.19	4.119
Age	20’s	606	3.21	3.810	9.452	0.000 ${}^{***}$
	30’s	1,031	2.93	3.641
	40’s	1,078	2.28	3.263
	50’s	1,041	2.38	3.520
	60’s	960	2.66	4.155
	70’s $\leqslant$	945	3.14	4.478
Household income	Low	1,070	3.96	5.222	56.073	0.000 ${}^{***}$
	Mid low	1,396	2.82	3.861
	Mid high	1,561	2.44	3.391
	High	1,634	2.11	2.787
Occupation	Managers and professionals	745	2.10	2.810	23.670	0.000 ${}^{***}$
	Clerks	601	2.27	3.169
	Sales and service workers	734	2.73	3.554
	Agricultural and fishery workers	235	2.08	3.231
	Skilled workers and manual workers	1,061	2.20	3.268
	Unemployed (housewives and students)	2,285	3.35	4.504

${}^{***}p<$ 0.001.

Women (3.19) scored higher in PHQ-9 than men (2.10) ( $p<$ 0.001). The respondents in their twenties (3.12) scored highest, followed by those in their seventies and over (3.14) and thirties (2.93) ( $p<$ 0.001); the group with less household income (3.96) scored higher ( $p<$ 0.001). The unemployed (3.35) scored highest, followed by salespersons and service providers (2.73) and clerks (2.27) ( $p<$ 0.001).

Although no one had any characteristic of depressive disorder with the score $\geqslant$ 10 in PHQ-9, efforts should be made to relieve depression in relation to occupation.

3.3 Differences in PHQ-9 by diabetes and stress

The differences in PHQ-9 by diabetes and stress are presented in Table 7. The group diagnosed with diabetes (3.65) scored higher in PHQ-9 than the group not diagnosed with diabetes (2.62) ( $p<$ 0.001). The group having a suicide plan for a year (8.56) scored higher than the group having no such plan (2.62) ( $p<$ 0.001).

Table 7
Differences in Patient Health Questionnaire-9 (PHQ-9) by diabetes and stress

		Patient Health Questionnaire-9 (PHQ-9)
		N	M	S.D	t/F	$p$
Diabetes diagnosis status	Yes	572	3.65	4.996	6.132	0.000 ${}^{***}$
	No	5,089	2.62	3.660
Diabetes treatment status	Yes	534	3.64	5.031	$-$ 0.142	0.887
	No	38	3.76	4.547
Suicide planning status for a year	Yes	99	8.56	6.915	15.613	0.000 ${}^{***}$
	No	5,562	2.62	3.669
Mental problem counseling for a year	Yes	198	7.80	6.336	19.615	0.000 ${}^{***}$
	No	5463	2.54	3.574
Degree of usual stress awareness	Feel almost no stress	938	1.16	2.279	465.291	0.000 ${}^{***}$
	Feel some stress	3,208	2.03	2.882
	Feel much stress	1,222	4.43	4.409
	Feel a lot of stress	293	8.27	6.220

${}^{***}p<$ 0.001.

The group getting mental problem counseling for a year (7.80) scored higher in PHQ-9 than the group getting no such counseling (2.54) ( $p<$ 0.001); the group most likely to feel stress on a daily basis (8.27) scored about eight times higher in PHQ-9 than the group feeling almost no stress (1.16) ( $p<$ 0.001).

Overall, diabetes (3.65), a suicide plan for a year (8.56), mental problem counseling for a year (7.80), and the degree of daily stress awareness (8.27) led to higher scores in PHQ-9. The respondents scored closer to 10 for suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness than for diabetes diagnosis status in PHQ-9. It is therefore necessary to develop relevant preventive mental health care programs.

3.4 Correlation with variables

The correlation between diabetes and the variables of PHQ-9 are presented in Table 8. PHQ-9 was positively correlated with diabetes diagnosis status ( $p<$ 0.01), suicide planning status for a year ( $p<$ 0.01), mental problem counseling for a year ( $p<$ 0.01), and the degree of daily stress awareness ( $p<$ 0.01).

Table 8
Correlation with variables

	PHQ-9 scores	Diabetes treatment status
Diabetes diagnosis status ${}^{\#}$	0.081 ${}^{**}$	0.963 ${}^{**}$
Suicide planning status for a year ${}^{\#}$	0.203 ${}^{**}$	0.045 ${}^{**}$
Mental problem counseling for a year ${}^{\#}$	0.252 ${}^{**}$	0.021
Degree of usual stress awareness	0.418 ${}^{**}$	$-$ 0.052 ${}^{**}$

${}^{\#}$ Conversion into dummy variables, ${}^{**}p<$ 0.01.

Diabetes treatment status was positively correlated with diabetes diagnosis status ( $p<$ 0.01) and suicide planning status for a year ( $p<$ 0.01) and was negatively correlated with the degree of daily stress awareness ( $p<$ 0.01).

3.5 Effects of diabetes and stress on PHQ-9

Multiple regression analysis was performed to determine the effects of diabetes and stress on PHQ-9. The dependent variable was PHQ-9 – 0 not at all, 1 several days, 2 more than a week, and 3 almost every day – with a higher score being more likely to be regarded as depressive disorder. The independent variables were diabetes diagnosis status, diabetes treatment status, suicide planning status for a year, mental problem counseling for a year, and stress awareness. All the independent variables but the degree of stress awareness were converted into dummy variables. The results of the analysis are presented in Table 9.

Table 9
Effects of diabetes and stress on PHQ-9

	Patient Health Questionnaire-9 (PHQ-9)
	B	S.E	$\beta$	$t$	$p$
Diabetes diagnosis status ${}^{\#}$	1.591	0.545	0.125	2.923	0.003 ${}^{**}$
Diabetes treatment status ${}^{\#}$	$-$ 0.433	0.561	$-$ 0.033	$-$ 0.772	0.440
Suicide planning status for a year ${}^{\#}$	4.115	0.343	0.141	11.985	0.000 ${}^{***}$
Mental problem counseling for a year ${}^{\#}$	3.550	0.247	0.170	14.381	0.000 ${}^{***}$
Degree of usual stress awareness	1.959	0.060	0.385	32.625	0.000 ${}^{***}$

$R=$ 0.490, $R2=$ 0.240, $F=$ 356.846, $p=$ 0.000 Durbin-Watson $=$ 1.896. ${}^{\#}$ Conversion into dummy variables, ${}^{**}p<$ 0.01, ${}^{***}p<$ 0.001.

The group diagnosed with diabetes was more likely to affect PHQ-9 for depression screening ( $\beta=$ 0.125, $t=$ 2.923, $p<$ 0.01). The group having a suicide plan was more likely to affect PHQ-9 for depression screening ( $\beta=$ 0.141, $t=$ 11.985, $p<$ 0.001). The group getting mental problem counseling for a year was more likely to affect PHQ-9 for depression screening ( $\beta=$ 0.170, $t=$ 14.381, $p<$ 0.001). The group more aware of stress was more likely to affect PHQ-9 for depression screening ( $\beta=$ 0.385, $t=$ 32.625, $p<$ 0.001). The influence on depression screening in PHQ-9 accounted for 24.0%, with no significant effect on diabetes treatment status.

Diabetes diagnosis status, suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness significantly affected PHQ-9 for depression screening.

4. Discussion

This study aimed to determine the effects of diabetes on mental health problems (stress and depressive disorder). The results showed that diabetes diagnosis status, suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness significantly affected PHQ-9 for depression screening. In PHQ-9 for determining depressive disorder in screening depression, however, diabetes diagnosis status with the score of 3.65 failed to be included in the group at risk of depressive disorder. Suicide planning status for a year (8.56), mental problem counseling for a year (7.80), and the degree of daily stress awareness (8.27) were at risk of depressive disorder with the score closer to 10 in PHQ-9. To put these results together, diabetes diagnosis status failed to score high in PHQ-9 for determining depressive disorder directly. This is considered to be correlated with many different variables. However, since the group diagnosed with diabetes scored higher in PHQ-9 than the group not diagnosed with diabetes, it is necessary to continuously run relevant preventive programs.

Groot et al. [6] noted that diabetes was correlated with depression and depressive symptoms, which seems to be consistent with this study. However, they made no analysis of PHQ-9 and could therefore induce variation in interpretation of the result analysis. Gavard et al. [11] noted that the prevalence of depression for diabetics had not been proved in comparison with other physical conditions. They imply that diabetes is correlated with depressive disorder but indicate the possible occurrence of depressive disorder due to many different variables, instead of presenting proven evidence. It is similar to the finding of this study that diabetes diagnosis status affected PHQ-9 but failed to get a score $\geqslant$ 10 for depressive disorder. In contrast, Aljasem et al. [3] noted that psychological self-efficacy contributed to self-management of diabetes. This seems to imply that emotional well-being can contribute to positive treatment for diabetes.

Lett [18], Melvyn et al. [19], and Prociow and Crowe [20] suggested the need of health care and mental health programs based on new medical and mobile technologies. They seemed to put emphasis on the contribution to patients’ surgical health care or internal mental health care. Lamers et al. [7] emphasized that emotional well-being contributed to recovery and survival and Prince [8] noted that “there is no health without mental health”. Both studies seem to imply that emotional stability can reduce depressive and behavioral disorders.

This study found that diabetes diagnosis status, suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness significantly affected PHQ-9. However, since diabetes diagnosis status failed to get high scoring distribution in PHQ-9, it is necessary to continuously run mental health care programs.

5. Conclusions

In PHQ-9, the scores $\geqslant$ 10 are screened for depression. However, while suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness got scores closer to 10, diabetes diagnosis status with the score of 3.65 failed to be included in the group at immediate risk of depressive disorder in PHQ-9. It can be considered that diabetes is likely to cause depressive disorder, depending on many different variables.

In addition, the group diagnosed with diabetes showed higher scoring distribution in PHQ-9 than the group not diagnosed with diabetes. Diabetes diagnosis status significantly affected PHQ-9 for depression screening. It is therefore necessary to continuously activate relevant programs with the objective of preventing depressive disorder from being caused by diabetes. Further research should be conducted on the association with diverse causes of the low scoring distribution in PHQ-9 in relation to diabetes.

Footnotes

Conflict of interest

None to report.

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The effects of diabetes on mental health in South Korean adults

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Methods

2.1 Design of the study

2.2 Subjects

Table 1 Subjects

Table 2 Instrument composition

Table 3 Composition of socio-demographic variables

3. Results

3.1 Diabetes treatment status by general characteristics

Table 5 Diabetes treatment status by general characteristics

Table 6 Differences in Patient Health Questionnaire-9 (PHQ-9) by general characteristics

Table 7 Differences in Patient Health Questionnaire-9 (PHQ-9) by diabetes and stress

Table 8 Correlation with variables

Table 9 Effects of diabetes and stress on PHQ-9

5. Conclusions

Footnotes

Conflict of interest

References

Table 1
Subjects

Table 2
Instrument composition

Table 3
Composition of socio-demographic variables

Table 5
Diabetes treatment status by general characteristics

Table 6
Differences in Patient Health Questionnaire-9 (PHQ-9) by general characteristics

Table 7
Differences in Patient Health Questionnaire-9 (PHQ-9) by diabetes and stress

Table 8
Correlation with variables

Table 9
Effects of diabetes and stress on PHQ-9