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Park, Lee, Lee, Kim, Cho, Kwon, Park, Kim, Jin, Hur, Han, and Kim: Risk of Depression according to Cumulative Exposure to a Low-Household Income Status in Individuals with Type 2 Diabetes Mellitus: A Nationwide Population-Based Study
Original Article
Complications

Diabetes Metab J (Seoul) 2024;48(2):290-301.

Published online: 3 January 2024

DOI: https://doi.org/10.4093/dmj.2022.0299

Risk of Depression according to Cumulative Exposure to a Low-Household Income Status in Individuals with Type 2 Diabetes Mellitus: A Nationwide Population-Based Study

So Hee Park1, *, You-Bin Lee1, *, Kyu-na Lee2, Bongsung Kim3, So Hyun Cho4, So Yoon Kwon1, Jiyun Park5, Gyuri Kim1, Sang-Man Jin1, Kyu Yeon Hur1, Kyungdo Han3, Jae Hyeon Kim1, 6

1Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

2Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea

3Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea

4Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

5Division of Endocrinology and Metabolism, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea

6Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Korea

Corresponding authors: Jae Hyeon Kim https://orcid.org/0000-0001-5001-963X Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea E-mail: jaehyeon@skku.edu

Kyungdo Han https://orcid.org/0000-0002-6096-1263 Department of Statistics and Actuarial Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Korea E-mail: hkd917@naver.com

* So Hee Park and You-Bin Lee contributed equally to this study as first authors.

Received 23 August 2022       Accepted 7 February 2023

Copyright © 2024 Korean Diabetes Association

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

We aimed to identify the risk of incident depression according to cumulative exposure to a low-household income status in individuals with type 2 diabetes mellitus (T2DM).

Methods

For this retrospective longitudinal population-based cohort study, we used Korean National Health Insurance Service data from 2002 to 2018. Risk of depression was assessed according to cumulative exposure to low-household income status (defined as Medical Aid registration) during the previous 5 years among adults (aged ≥20 years) with T2DM and without baseline depression who underwent health examinations from 2009 to 2012 (n=2,027,317).

Results

During an average 6.23 years of follow-up, 401,175 incident depression cases occurred. Advance in cumulative number of years registered for medical aid during the previous 5 years from baseline was associated with an increased risk of depression in a dose-dependent manner (hazard ratio [HR], 1.44 [95% confidence interval (CI), 1.38 to 1.50]; HR, 1.40 [95% CI, 1.35 to 1.46]; HR, 1.42, [95% CI, 1.37 to 1.48]; HR, 1.46, [95% CI, 1.40 to 1.53]; HR, 1.69, [95% CI, 1.63 to 1.74] in groups with 1 to 5 exposed years, respectively). Insulin users exposed for 5 years to a low-household income state had the highest risk of depression among groups categorized by insulin use and duration of low-household income status.

Conclusion

Cumulative duration of low-household income status, defined as medical aid registration, was associated with an increased risk of depression in a dose-response manner in individuals with T2DM.

Keywords: Depression, Diabetes mellitus, type 2, Income, Social class

GRAPHICAL ABSTRACT

Highlights

• This is a nationwide, longitudinal, population-based study in adults with T2DM.
• Low income was associated with depression risk in this group.
• Duration of low-income states showed a dose-response relation to depression risk.
• Insulin users in low-income states are particularly susceptible to depression.

INTRODUCTION

Major depression is a severe recurrent disorder associated with reduced role functioning and quality of life, medical morbidity, and mortality [1]. In individuals with type 2 diabetes mellitus (T2DM), the prevalence of depression has been estimated to be almost double that in individuals without diabetes [2,3]. Furthermore, increased risks of psychiatric disorders, including depression and suicide attempts, have been reported in emerging adults with diabetes [4]. In people with diabetes, presence of depression has been associated with decreased quality of life, poor glycemic control, and higher risk of diabetes-related complications [5]. Therefore, for appropriate management of diabetes, it is necessary to identify risk factors for depression and provide preventive measures to susceptible populations [6].
Association between socioeconomic status (SES), including income, and depression is controversial, but in a meta-analysis of 51 studies, individuals with a low level of education or low income had a higher risk of depression [7]. The occurrence of depression has been associated with lower SES including income, even in individuals with diabetes [8]. However, most studies of the relationships between depression and income in people with diabetes used only cross-sectional data and prevalence instead of incidence to evaluate associations with depression [6,9-11]. These previous studies could therefore not clarify if there is a temporal relationship between exposure and outcome, and income status was only considered at a single time point. Therefore, the risk of incident depression in people with T2DM needs to be evaluated according to cumulative duration of exposure to a low-household income status in a representative cohort with repeated evaluation of household income and longer follow-up using a longitudinal study design.
Moreover, the requirement for insulin treatment might also affect the risk of depression among people with T2DM. More demanding diabetes care and increased responsibility of patients and their caregivers for treatment decisions associated with insulin treatment could theoretically increase psychological burden in patients with diabetes [12]. Also, requiring insulin treatment may reflect a more advanced disease in people with T2DM in the real world, which might be associated with increased risk of depression. A meta-analysis by Bai et al. [13] showed that patients with T2DM treated with insulin had more depressive syndromes than those who did not receive insulin therap.
Therefore, we aimed to identify the risk of incident depression according to cumulative exposure to low-household income status (defined as medical aid registration) in individuals with T2DM. The incidence of depression was also investigated according to groups categorized by cumulative exposure to low-household income status and the use of insulin to explore the combined effects of these two factors.

METHODS

Data sources

We used Korean National Health Insurance Service (KNHIS) data from January 2002 to December 2018. KNHIS is the single nationwide insurance provider controlled by the Korean government. It includes the entire population of Korea and comprises two major health care programs: National Health Insurance (NHI) and Medical Aid (MA) [14]. Approximately 97% of the population are covered by NHI, and the remaining 3% of the population with the lowest income are covered by MA [14]. From these anonymized KNHIS data, demographics, monthly household income, date of death, primary and secondary diagnoses classified by the International Classification of Diseases-10th Revision (ICD-10), prescriptions, procedures, and dates of hospital visits and hospitalizations for all Korean residents are available. Furthermore, the KNHIS recommends standardized health examinations at least every 2 years for its enrollees. The results of these examinations are compiled into preventive health screening datasets. These health examination results include smoking history, alcohol consumption, physical activity, anthropometric measurements such as height, weight, and waist circumference, blood pressure, and laboratory information, including lipid profiles, fasting plasma glucose level, and estimated glomerular filtration rate.
The Institutional Review Board (IRB) of Soongsil University approved this study (file number: SSU-202003-HR-201-01). An informed consent exemption was granted by the IRB because the researchers were provided anonymous, de-identified data from the KNHIS.

Study cohort, outcomes, and follow-up

In this retrospective, longitudinal, population-based cohort study, we included adults aged ≥20 years with T2DM who underwent at least one health examination between 2009 and 2012. T2DM was defined as having ≥one claim per year for the prescription of oral anti-diabetic medication under ICD-10 codes E11–14 or having a fasting plasma glucose level ≥126mg/dL, as in previous studies [15-17]. The time point of the last examination between 2009 and 2012 was considered to be the baseline. Individuals with missing data for at least one variable and those who had prescriptions for antidepressant or claims under ICD-10 codes F32–33 at or before baseline were excluded.
The primary endpoint of this study was newly diagnosed depression that was defined as a patient being diagnosed by a psychiatrist with a specific ICD-10 code (F32 [major depressive disorder, single episode] or F33 [major depressive disorder, recurrent]) [18]. The study population was followed from baseline until the date of death, onset of depression, or December 31, 2018, whichever came first.

Exposure to low-household income

Every year, the KNHIS evaluates the household income status of all registrants and decides whether to register for MA for the lowest income individuals (the lowest 3%). MA beneficiaries for a given year were considered to have been exposed to low-household income status. Individuals in the current study were categorized into six groups according to the number of years registered to MA beneficiaries during the 5 years prior to baseline (from 0 to 5 years).

Measurements and definitions

Questionnaires were used to collect information on smoking history, alcohol consumption, and regular exercise. Definition of heavy alcohol consumption [19], regular exercise [20], body mass index (BMI), hypertension [21], dyslipidemia [21], chronic kidney disease (CKD) [22], insulin use [23], and dementia [24] are summarized in Supplementary Table 1. Mental, behavioral, and neurodevelopmental disease and cancer were defined based on the corresponding ICD-10 diagnostic codes (Supplementary Table 1). The unawareness of diabetes was defined as having a fasting plasma glucose level ≥126mg/dL and having no claim for the prescription of oral anti-diabetic medication under ICD-10 codes E11–14. Lipid-lowering agents included statins, ezetimibe, and fibrates [25]. Blood tests, including plasma glucose and lipid profiles, were performed using intravenous samples collected after an overnight fast.

Statistical analysis

We used SAS software version 9.3 (SAS Institute, Cary, NC, USA) for statistical analyses. Baseline characteristics of the study population were assessed in six groups stratified by number of years exposed to a low-household income status during the 5 years prior to baseline. Continuous variables with normal distributions are presented as means±standard deviations and categorical data are presented as frequencies and percentages.
Incidence rate of depression was derived from the number of incident cases divided by the total follow-up duration (person-years). Kaplan-Meier curves were used to compare the cumulative incidence of depression according to duration of exposure to low-household income status in the six groups; the significance of differences among the six groups was evaluated using the log-rank test. Multivariable Cox regression analysis was performed to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for outcome incidence rates according to duration of exposure to low-household income status: unadjusted in model 1, adjusted for age and sex in model 2, adjusted for age, sex, smoking history, alcohol consumption, regular exercise, and presence of CKD in model 3, additionally adjusted for fasting plasma glucose level, and diabetes duration (≥5 years vs. <5 years) in model 4, and additionally adjusted for presence of mental, behavioral and neurodevelopmental disease, cancer, dementia, and use of metformin (MFM), sulfonylurea (SU), and insulin in model 5. In constructing these regression models, various risk factors for depression identified in previous studies were included as potential confounders [26,27].
HRs (95% CIs) for outcome incidence rates in participants with 1 or more years of exposure to low-household income status were compared with those with no exposure (reference) in subgroups classified by age (<65 years vs. ≥65 years), sex, current smoking, heavy alcohol consumption, regular exercise, presence of obesity (defied as a BMI ≥25 kg/m2 referring to obesity guidelines for the Korean population [28]), use of insulin, whether taking three or more oral anti-diabetic agents or not, diabetes duration (≥5 years vs. <5 years), the awareness of diabetes, fasting plasma glucose level (<140 mg/dL vs. ≥140 mg/dL), and the type of oral anti-diabetic agents. We evaluated the potential effect modification by these factors determining the subgroups and calculated P values for interactions.
To explore the potential effect modification by insulin use more thoroughly, HRs and 95% CIs for outcome incidence rates according to duration of exposure to low-household income status were calculated after stratifying the study population-based on insulin use, and P values for interactions were calculated. The study population was also divided into 12 groups according to insulin use and exposure duration to lowhousehold income status during the 5 years prior to baseline. To assess the combined effects of insulin use and cumulative exposure to low-household income status, HRs (95% CIs) for outcome incidence rates according to these 12 groups were calculated.

Sensitivity analyses

Sensitivity analysis was performed by excluding individuals who developed depression within 2 years after baseline.

RESULTS

Baseline characteristics of the study population

The study participants comprised a total of 2,027,317 adults (aged ≥20 years) with T2DM (Supplementary Fig. 1). Among them, 1,985,197 (97.92%) were never exposed to a low-household income state during the 5 years prior to baseline. The remaining 42,120 (2.08%) were exposed to a low-household income state for at least 1 year during the 5 years prior to baseline. Baseline characteristics are presented according to years exposed to a low-household income state (Table 1). Participants with a longer exposure to a low-household income status were more likely to have a higher prevalence of dyslipidemia, mental, behavioral, and neurodevelopmental disease, a higher proportion of insulin use, use of three or more oral anti-diabetic agents, MFM, dipeptidyl peptidase-4 inhibitor, lipid-lowering agents, longer-standing diabetes (diabetes duration ≥5 years), and be non-drinkers. In addition, this population was characterized by a lower proportion of the unawareness of diabetes in conjunction with a higher proportion of use of three or more oral anti-diabetic agents and decreasing trends in total and low-density lipoprotein cholesterol in conjunction with the use of lipid-lowering agents for dyslipidemia.

Risk of incident depression according to duration of exposure to a low-household income status

During the median 6.77 years of follow-up (12,635,025.87 person-years), 401,175 incident depression cases occurred. Cumulative incidence of depression according to duration of exposure to a low-household income state was expressed in the form of Kaplan-Meier curves (Fig. 1). When individuals who had never been exposed to a low-household income status were set as a reference, an increase in cumulative duration of exposure to a low-household income state during the 5 years prior to baseline was associated with an increased risk of depression in a dose-dependent manner (HR, 1.44 [95% CI, 1.38 to 1.50]; HR, 1.40 [95% CI, 1.35 to 1.46]; HR, 1.42 [95% CI, 1.37 to 1.48]; HR, 1.46 [95% CI, 1.40 to 1.53]; HR, 1.69 [95% CI, 1.63 to 1.74] in groups with 1 to 5 years of exposure, respectively, in the fully-adjusted model 5) (Table 2).

Subgroup analysis

HRs (95% CIs) for depression in participants with at least one exposure to a low-household income status were calculated in subgroups stratified by age (<65 years vs. ≥65 years), sex, current smoking, heavy alcohol consumption, regular exercise, obesity, insulin use, use of three or more oral anti-diabetic agents, diabetes duration (≥5 years vs. <5 years), the awareness of diabetes, fasting plasma glucose level (<140 mg/dL vs. ≥140 mg/dL), and the type of oral anti-diabetic agents, and compared with those of participants with no exposure to these conditions (Table 3, Fig. 2). Participants in all subgroups with at least 1 year of exposure to a low-household income status had a higher risk of depression than those without exposure. These associations were more prominent in people younger than 65 years of age, males, current smokers, heavy alcohol consumers, SU non-users (P for interaction <0.0001 for all of the above), and those with a diabetes duration of less than 5 years (P for interaction=0.0001).

Stratified analyses according to insulin use

After dividing study subjects into insulin users and insulin non-users, the HRs (95% CIs) of depression were analyzed according to duration of low-household income status (Supplementary Table 2). Regardless of insulin use, HRs were higher among those exposed to a low-household income status than those without exposure. Except for unadjusted model 1, other models demonstrated no significant effect modifications by insulin use (P for interaction 0.6320 in model 5). When we calculated the hazards of depression in 12 groups categorized by insulin use and years exposed to a low-household income state, HRs were the highest in insulin users with 5 years of exposure to a low-household income state (HR, 2.33; 95% CI, 2.16 to 2.51), followed by insulin users with 1 to 4 years of exposure compared to insulin non-users without exposure (reference) (Fig. 3). Insulin users without exposure to a low-household income state (HR, 1.32; 95% CI, 1.30 to 1.33) and insulin non-users with one year of exposure (HR, 1.44; 95% CI, 1.38 to 1.51) also had higher hazards of the primary outcome than the reference group.

Sensitivity analyses

Exclusion of individuals who developed depression within 2 years of baseline resulted in findings consistent with the main results (Supplementary Table 3).

DISCUSSION

This large-scale longitudinal study involving 2,027,317 adults with T2DM revealed a dose-response relationship between cumulative exposure to a low-household income state and the incidence of newly diagnosed depression. This result was consistent even after adjusting for potential confounders including demographic and lifestyle factors as well as category of diabetes duration, presence of mental, behavioral and neurodevelopmental disease, cancer, dementia, and use of MFM, SU, and insulin. Furthermore, consistent results were obtained in subgroup analyses after stratification by age, sex, current smoking, heavy alcohol consumption, regular exercise, presence of obesity, insulin use, taking three or more oral anti-diabetic agents, diabetes duration (≥5 years vs. <5 years), the awareness of diabetes, fasting glucose level, and the type of oral anti-diabetic agents. When study subjects were classified according to insulin use and duration of exposure to a low-household income state, insulin users with the most sustained exposure to a low-household income state had the highest risk of developing depression.
Previous studies have also suggested an association between low-household income and depression in adults with diabetes [6,11,29]. However, most of these previous studies were small cross-sectional studies that investigated the prevalence of depression in low-household income patient with diabetes [6,9-11]. In contrast to these cross-sectional studies, we performed a longitudinal study and demonstrated that the risk of incident depression in people with T2DM increased according to cumulative duration of exposure to a low-household income status. Our large-scale longitudinal study of the incidence of depression, rather than its prevalence, according to duration of exposure to a low-household income status in patients with T2DM allowed us to establish temporal relationship and demonstrate dose-response relationship between exposure and outcome.
In subgroup analysis, participants with at least 1 year of exposure to a low-household income status had a higher risk of depression in all subgroups than those without low income exposure. However, the excess hazard of depression from exposure to a low-household income state among adults with T2DM was more prominent in those under 65 years of age, males, current smokers, heavy alcohol consumers, and those with a diabetes duration of less than 5 years, SU non-users. Although underlying mechanisms cannot be exactly clarified in the current study, there are several possible explanations for these findings. First, regarding more prominent associations among adults under 65 years, older adults appear to react less to stressors [30] and they might be more protective against depression than younger adults after experiencing stressful conditions [31]. Second, with respect to the interaction by sex, males may be more vulnerable to low income than females. Similarly, a study from Denmark suggested that SES proxied by low income, unskilled blue-collar work, non-specific wage work and unemployment, increased suicide risk more prominently for men than for women [32]. Third, current smoking and heavy drinking, both of which are maladaptive health behaviors, may cause cumulative biopsychosocial vulnerability [33], and chronic stress associated with low-household income might have greater effects on the mental health of current smokers and heavy alcohol consumers. Fourth, with respect to interaction by diabetes duration, individuals with a diabetes duration of less than 5 years may have been affected more vulnerably by low-household income in a state of high distress and anxiety after recent diagnosis of diabetes. In a previous study that found substantially higher risks of psychiatric disorders and suicide attempts in adolescents and emerging adults with diabetes compared to those without diabetes, excess risk was most prominent in those individuals recently diagnosed with diabetes (duration of ≤2 years), indicating the possibility of elevated psychological distress in individuals with a recent diagnosis of diabetes [4]. Similarly, another study found an increased risk of psychiatric disorders and suicide attempts in children and adolescents with type 1 diabetes mellitus (T1DM) compared with their healthy siblings, and the highest risk of psychiatric disorders was noted within the first 6 months after being diagnosed with T1DM and declined with time [12]. Finally, consistent to a previous study that reported an association between high dose of SU and higher risk of depression [34], SU users non-exposed to low-household income status in our study had a higher incidence rate of depression than SU non-users. Excess risk of depression from exposure to low-household income status in SU users might be relatively less than SU non-users.
With regard to the baseline characteristic of the study subjects, the proportion of insulin use increased as duration of exposure to a low-household income state increased. Interestingly, at the same time, insulin users exposed to a low-household income state for the longest duration had the highest risk of incident depression. These results indicate that careful psychiatric evaluation and appropriate interventions to prevent and detect depression early should be provided to insulin users with low-household income. Severe depression unrecognized and untreated in individuals with diabetes is associated with lower adherence to medication, poor glycemic control, increased risk of complication, increased healthcare costs, and higher mortality rate [35]. Therefore, it is important that vulnerable individuals with diabetes in low-household income status, especially insulin users should be screened for depression, incorporating psychiatric healthcare for prevention and early detection of depression into diabetes care.
The strengths of this study are as follows. This is the first large-scale longitudinal study (n=2,027,317) to report the incidence of depression according to exposure to a low-household income state in adults with T2DM. By examining exposure as cumulative duration of exposure to a low-household income state over 5 years and not simply cross-sectional income status at a single time point, we were able to demonstrate a dose-response relationship between exposure and risk of depression. We used a representative nationwide cohort database managed by the Korean government that contains diverse demographic information, claims data, lifestyle factors, and laboratory results for large, nationwide population of Korea, which enabled adjustment for various potential confounders. Furthermore, consistent results were obtained in sensitivity and subgroup analyses.
This study also had several limitations. First, this was an observational study, making it inevitably impossible to determine causal relationships. However, at least, to maintain temporal relationship, those individuals who obtained prescriptions for antidepressants or had claims under depression codes at or before baseline were excluded. Furthermore, we examined duration of exposure to a low-household income state for the 5 years prior to baseline as opposed to after baseline. Second, even after adjusting for possible confounding factors, residual effects of unmeasured confounders may still have been present. For example, we could not adjust for glycated hemoglobin or other indicators of SES such as education because these factors were not available in the KNHIS dataset. Third, generalization of our findings to individuals with T1DM or those without diabetes or individuals of different ethnicities should be done with caution as we included only Korean adults with T2DM in this study.
In conclusion, cumulative duration of exposure to a low-household income status, defined as medical aid registration, was associated with an increased risk of depression in a dosedependent manner in individuals with T2DM. The requirement for insulin treatment was associated with an additional increase in the risk of depression in conjunction with advanced duration of exposure to a low-household income state. In particular, insulin users with sustained exposure to a low-household income state were most susceptible to incident depression. These findings suggest that strategies to prevent and detect depression early, including psychiatric evaluation and monitoring systems, should be provided more intensively to individuals with T2DM and a low income status, especially those using insulin.

SUPPLEMENTARY MATERIALS

Supplementary materials related to this article can be found online at https://doi.org/10.4093/dmj.2022.0299.

Supplementary Table 1.

Definitions of covariates
dmj-2022-0299-Supplementary-Table-1.pdf

Supplementary Table 2.

Hazard ratios and 95% confidence intervals for depression according to duration of exposure to a lowhousehold income in subgroups classified by insulin use
dmj-2022-0299-Supplementary-Table-2.pdf

Supplementary Table 3.

Hazard ratios and 95% confidence intervals for depression according to duration of exposure to a lowhousehold income after excluding individuals who developed depression within 2 years from baseline
dmj-2022-0299-Supplementary-Table-3.pdf

Supplementary Fig. 1.

Flow diagram of the study population. ICD-10, International Classification of Diseases-10th Revision.
dmj-2022-0299-Supplementary-Fig-1.pdf

Notes

CONFLICTS OF INTEREST

Sang-Man Jin has been associate editor of the Diabetes & Metabolism Journal since 2022. He was not involved in the review process of this article. Otherwise, there was no conflict of interest.

AUTHOR CONTRIBUTIONS

Conception or design: S.H.P., Y.B.L., K.H., J.H.K.

Acquisition, analysis, or interpretation of data: K.L., B.K., K.H.

Drafting the work or revising: S.H.P., Y.B.L., J.H.K.

Final approval of the manuscript: S.H.P., Y.B.L., K.L., B.K., S.H.C., S.Y.K., J.P., G.K., S.M.J., K.Y.H., K.H., J.H.K.

FUNDING

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1I1A1A0106118813) to Prof. Kyungdo Han. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

ACKNOWLEDGMENTS

This work was performed using data from the Korean National Health Insurance Service (KNHIS). We used the National Health Information Database constructed by the KNHIS, and the study results do not necessarily represent the opinion of the KNHIS.

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Fig. 1.
Cumulative incidence of depression according to the number of years of exposure to a low-household income.
dmj-2022-0299f1.tif
Fig. 2.
Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for depression in subjects exposed or not exposed to a low-household income status in subgroups. Adjusted for age, sex, smoking history, alcohol consumption, regular exercise, presence of chronic kidney disease, fasting plasma glucose, diabetes duration (≥5 years vs. <5 years), and presence of mental, behavioral and neurodevelopmental disease, cancer, dementia. MFM, metformin; SU, sulfonylurea; TZD, thiazolidinedione; DPP4i, dipeptidyl peptidase-4 inhibitor.
dmj-2022-0299f2.tif
Fig. 3.
Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for depression according to 12 groups categorized by insulin use and the number of years of exposure to a low-household income. Adjusted for age, sex, smoking history, alcohol consumption, regular exercise, presence of chronic kidney disease, fasting plasma glucose, diabetes duration (≥5 years vs. <5 years), presence of mental, behavioral and neurodevelopmental disease, cancer, dementia, and use of metformin and sulfonylurea.
dmj-2022-0299f3.tif
dmj-2022-0299f4.tif
Table 1.
Baseline characteristics of subjects according to years of exposure to a low-household income
Characteristic Duration of exposure to low-household income, yr
0 (n=1,985,197) 1 (n=7,862) 2 (n=7,629) 3 (n=8,044) 4 (n=6,601) 5 (n=11,984) P value P for trend
Age, yr 56.3±12.33 58.15±13.3 59.63±13.37 60.13±12.67 59.79±12.58 56.31±8.96 <0.0001 <0.0001
Male sex 1,282,720 (64.61) 3,906 (49.68) 3,471 (45.5) 3,563 (44.29) 2,894 (43.84) 5,860 (48.9) <0.0001 <0.0001
Current smoker 556,739 (28.04) 2,128 (27.07) 1,872 (24.54) 1,920 (23.87) 1,607 (24.34) 3,331 (27.8) <0.0001 <0.0001
Heavy alcohol consumption 219,216 (11.04) 651 (8.28) 543 (7.12) 560 (6.96) 451 (6.83) 840 (7.01) <0.0001 <0.0001
Regular exercise 415,454 (20.93) 1,237 (15.73) 1,207 (15.82) 1,309 (16.27) 1,080 (16.36) 1,925 (16.06) <0.0001 <0.0001
Body mass index, kg/m2 25.1±3.39 24.96±3.8 25±3.86 25.04±3.91 24.99±3.92 25.29±4.11 <0.0001 <0.0001
Waist circumference, cm 85.53±8.83 85±9.43 85.19±9.46 85.21±9.51 85.02±9.55 85.85±9.98 <0.0001 <0.0001
Systolic BP, mm Hg 129.22±15.79 128.95±16.76 128.94±16.53 128.87±16.71 128.59±16.63 126.91±16.53 <0.0001 <0.0001
Diastolic BP, mm Hg 79.34±10.29 78.79±10.5 78.65±10.33 78.57±10.38 78.38±10.5 77.95±10.4 <0.0001 <0.0001
Fasting plasma glucose, mg/dL 146.23±46.73 147.41±53.32 146.25±53.43 145.6±54.79 146.37±56.67 142.56±53.27 <0.0001 <0.0001
Insulin usea 140,139 (7.06) 897 (11.41) 1,008 (13.21) 1,170 (14.55) 921 (13.95) 1,800 (15.02) <0.0001 <0.0001
Diabetes duration ≥5 years 565,984 (28.51) 2,408 (30.63) 2,604 (34.13) 3,111 (38.67) 2,359 (35.74) 5,006 (41.77) <0.0001 <0.0001
Diabetes unawareness 848,952 (42.76) 2,549 (32.42) 2,270 (29.75) 1,909 (23.73) 1,495 (22.65) 2,427 (20.25) <0.0001 <0.0001
Oral anti-diabetic agents ≥3 266,013 (13.40) 1,399 (17.79) 1,458 (19.11) 1,825 (22.69) 1,548 (23.45) 2,858 (23.85) <0.0001 <0.0001
Type of oral anti-diabetic agents
 MFM 895,859 (45.13) 4,163 (52.95) 4,233 (55.49) 4,848 (60.27) 4,038 (61.17) 7,961 (66.43) <0.0001 <0.0001
 SU 782,992 (39.44) 3,744 (47.62) 3,718 (48.74) 4,434 (55.12) 3,644 (55.20) 6,210 (51.82) <0.0001 <0.0001
 TZD 122,299 (6.16) 519 (6.60) 510 (6.69) 624 (7.76) 559 (8.47) 853 (7.12) <0.0001 <0.0001
 DPP4i 161,049 (8.11) 776 (9.87) 810 (10.62) 1,008 (12.53) 886 (13.42) 2,397 (20.00) <0.0001 <0.0001
Dyslipidemia 785,882 (39.59) 3,378 (42.97) 3,329 (43.64) 3,782 (47.02) 3,191 (48.34) 6,217 (51.88) <0.0001 <0.0001
Lipid-lowering agents 589,342 (29.69) 2,678 (34.06) 2,687 (35.22) 3,178 (39.51) 2,689 (40.74) 5,519 (46.05) <0.0001 <0.0001
Total cholesterol, mg/dL 197.68±46.15 195.28±44.54 193.47±50.63 191.66±43.68 191.95±52.92 188.51±45.37 <0.0001 <0.0001
HDL-C, mg/dL 52.18±29.68 52.32±27.05 51.66±19.31 52.22±57.87 51.71±23.82 51.02±21.1 0.0005 0.0005
LDL-C, mg/dL 113.13±86.12 110.16±49.72 109.7±55.81 111±160.01 107.62±51.18 105.35±43.12 <0.0001 <0.0001
eGFR, mL/min/1.73 m2 85.68±36.5 84.11±34.03 83.37±39.21 82.97±34.64 83.55±35.22 86.96±34.81 <0.0001 <0.0001
CKD (eGFR <60 mL/min/1·73 m2) 202,864 (10.22) 1,183 (15.05) 1,309 (17.16) 1,345 (16.72) 1,147 (17.38) 1,624 (13.55) <0.0001 <0.0001
Mental, behavioral and neurodevelopmental disease 295,144 (14.87) 1,925 (24.48) 2,016 (26.43) 2,359 (29.33) 1,979 (29.98) 4,561 (38.06) <0.0001 <0.0001
Cancer 92,747 (4.67) 541 (6.88) 499 (6.54) 559 (6.95) 412 (6.24) 733 (6.12) <0.0001 <0.0001
Dementia 21,735 (1.09) 190 (2.42) 245 (3.21) 272 (3.38) 220 (3.33) 383 (3.20) <0.0001 <0.0001

Values are presented as mean±standard deviation or number (%).

BP, blood pressure; MFM, metformin; SU, sulfonylurea; TZD, thiazolidinedione; DPP4i, dipeptidyl peptidase-4 inhibitor; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease.

a Insulin use: A total of three or more prescriptions of insulin in the outpatient setting, and at least one prescription of insulin per year.

Table 2.
Hazard ratios and 95% confidence intervals for depression according to duration of exposure to a low-household income
Duration of exposure to low-household income, yr No. of events Follow-up duration, person-yr Incidence rate, /1,000 person-yr Model 1 Model 2 Model 3 Model 4 Model 5
0 (n=1,985,197) 388,260 12,419,053.22 31.26 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref)
1 (n=7,862) 2,319 43,013.90 53.91 1.73 (1.66–1.80) 1.52 (1.46–1.59) 1.51 (1.45–1.57) 1.52 (1.46–1.58) 1.44 (1.38–1.50)
2 (n=7,629) 2,298 40,574.43 56.64 1.82 (1.74–1.89) 1.50 (1.44–1.57) 1.49 (1.43–1.55) 1.49 (1.43–1.56) 1.40 (1.35–1.46)
3 (n=8,044) 2,563 42,150.37 60.81 1.95 (1.88–2.03) 1.57 (1.51–1.63) 1.55 (1.49–1.61) 1.55 (1.49–1.61) 1.42 (1.37–1.48)
4 (n=6,601) 2,102 34,036.14 61.76 1.98 (1.90–2.07) 1.61 (1.55–1.68) 1.60 (1.53–1.66) 1.60 (1.53–1.67) 1.46 (1.40–1.53)
5 (n=11,984) 3,633 56,197.81 64.65 2.08 (2.02–2.15) 2.03 (1.96–2.10) 1.99 (1.93–2.06) 1.96 (1.90–2.03) 1.69 (1.63–1.74)
P value <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
P for trend <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

Model 1: unadjusted; Model 2: adjusted for age and sex; Model 3: adjusted for age, sex, smoking history, alcohol consumption, regular exercise, and presence of chronic kidney disease (CKD); Model 4: adjusted for age, sex, smoking history, alcohol consumption, regular exercise, and presence of CKD, fasting plasma glucose, and diabetes duration (≥5 years vs. <5 years); Model 5: adjusted for age, sex, smoking history, alcohol consumption, regular exercise, and presence of CKD, fasting plasma glucose, diabetes duration (≥5 years vs. <5 years), presence of mental, behavioral and neurodevelopmental disease, cancer, dementia, and use of metformin, sulfonylurea, and insulin.

Table 3.
Adjusted hazard ratios and 95% confidence intervals for depression in subjects exposed or not exposed to a low-household income status in subgroups
Variable Subvariable Exposure to low-household income Number No. of events Follow-up duration, person-yr Incidence rate, /1,000 person-yr Adjusted HR (95% CI) P for interaction
Age, yr <65 No exposure 1,453,220 225,251 9,434,393.10 23.88 1 (ref) <0.0001
Exposure 27,365 7,272 143,951.38 50.52 1.75 (1.71–1.79)
≥65 No exposure 531,977 163,009 2,984,660.13 54.62 1 (ref)
Exposure 14,755 5,643 72,021.27 78.35 1.31 (1.27–1.34)
Sex Male No exposure 1,282,720 204,381 8,171,069.20 25.01 1 (ref) <0.0001
Exposure 19,694 5,264 100,142.76 52.57 1.76 (1.72–1.81)
Female No exposure 702,477 183,879 4,247,984.02 43.29 1 (ref)
Exposure 22,426 7,651 115,829.88 66.05 1.39 (1.36–1.42)
Current smoker No No exposure 1,428,458 305,727 8,866,653.85 34.48 1 (ref) <0.0001
Exposure 31,262 9,843 161,055.11 61.12 1.45 (1.42–1.48)
Yes No exposure 556,739 82,533 3,552,399.37 23.23 1 (ref)
Exposure 10,858 3,072 54,917.54 55.94 1.82 (1.76–1.89)
Heavy alcohol consumption No No exposure 1,275,516 283,333 7,833,125.89 36.17 1 (ref) <0.0001
Exposure 32,646 10,504 165,225.40 63.57 1.48 (1.45–1.51)
Yes No exposure 709,681 104,927 4,585,927.33 22.88 1 (ref)
Exposure 9,474 2,411 50,747.25 47.51 1.73 (1.66–1.80)
Regular exercise No No exposure 1,569,743 308,234 9,775,677.88 31.53 1 (ref) 0.0006
Exposure 35,362 10,860 180,732.78 60.09 1.50 (1.48–1.53)
Yes No exposure 415,454 80,026 2,643,375.34 30.27 1 (ref)
Exposure 6,758 2,055 35,239.87 58.31 1.64 (1.57–1.71)
Obesity No No exposure 1,09,83 203,990 6,238,987.25 32.70 1 (ref) 0.2212
Exposure 21,878 6,659 110,035.82 60.52 1.51 (1.47–1.55)
Yes No exposure 976,114 184,270 6,180,065.98 29.82 1 (ref)
Exposure 20,242 6,256 105,936.83 59.05 1.54 (1.50–1.58)
Insulin use No No exposure 1,845,058 347,968 11,630,440.19 29.92 1 (ref) 0.4292
Exposure 36,324 10,756 189,803.85 56.67 1.50 (1.47–1.53)
Yes No exposure 140,139 40,292 788,613.03 51.09 1 (ref)
Exposure 5,796 2,159 26,168.80 82.50 1.53 (1.47–1.60)
Oral anti-diabetic agents, n <3 No exposure 1,719,184 320,791 10,787,774.70 29.74 1 (ref) 0.1242
Exposure 33,032 9,811 171,122.28 57.33 1.53 (1.50–1.56)
≥3 No exposure 266,013 67,469 1,631,278.52 41.36 1 (ref)
Exposure 9,088 3,104 44,850.37 69.21 1.48 (1.43–1.53)
Diabetes duration, yr <5 No exposure 1,419,213 243,782 8,986,857.58 27.13 1 (ref) 0.0001
Exposure 26,632 7,858 141,654.82 55.47 1.57 (1.53–1.60)
≥5 No exposure 565,984 144,478 3,432,195.64 42.09 1 (ref)
Exposure 15,488 5,057 74,317.82 68.05 1.46 (1.42–1.50)
Diabetes awareness No No exposure 1,136,245 269,008 7,019,474.29 38.32 1 (ref) 0.0165
Exposure 31,470 10,392 157,703.94 65.90 1.49 (1.46–1.51)
Yes No exposure 848,952 119,252 5,399,578.93 22.09 1 (ref)
Exposure 10,650 2,523 58,268.71 43.30 1.57 (1.51–1.63)
Fasting plasma glucose, mg/dL <140 No exposure 1,138,384 233,730 7,047,975.87 33.16 1 (ref) 0.1343
Exposure 24,581 7,832 124,963.30 62.67 1.51 (1.47–1.54)
≥140 No exposure 846,813 154,530 5,371,077.36 28.77 1 (ref)
Exposure 17,539 5,083 91,009.35 55.85 1.55 (1.51–1.59)
MFM use No No exposure 1,089,338 180,015 6,891,046.07 26.12 1 (ref) 0.0330
Exposure 16,877 4,656 89,589.18 51.97 1.55 (1.51–1.60)
Yes No exposure 895,859 208,245 5,528,007.15 37.67 1 (ref)
Exposure 25,243 8,259 126,383.47 65.35 1.49 (1.46–1.52)
SU use No No exposure 1,202,205 197,453 7,528,563.45 26.23 1 (ref) <0.0001
Exposure 20,370 5,653 105,778.46 53.44 1.58 (1.54–1.62)
Yes No exposure 782,992 190,807 4,890,489.77 39.02 1 (ref)
Exposure 21,750 7,262 110,194.19 65.90 1.47 (1.43–1.50)
TZD use No No exposure 1,862,898 358,935 11,635,126.93 30.85 1 (ref) 0.9887
Exposure 39,055 11,834 200,301.15 59.08 1.52 (1.50–1.55)
Yes No exposure 122,299 29,325 783,926.29 37.41 1 (ref)
Exposure 3,065 1,081 15,671.50 68.98 1.52 (1.43–1.62)
DPP4i use No No exposure 1,824,148 354,588 11,462,576.12 30.93 1 (ref) 0.0505
Exposure 36,243 11,068 188,282.95 58.78 1.51 (1.48–1.54)
Yes No exposure 161,049 33,672 956,477.11 35.20 1 (ref)
Exposure 5,877 1,847 27,689.70 66.70 1.59 (1.52–1.66)

Adjusted for age, sex, smoking history, alcohol consumption, regular exercise, presence of chronic kidney disease, fasting plasma glucose, diabetes duration (≥5 years vs. <5 years), presence of mental, behavioral and neurodevelopmental disease, cancer, and dementia.

HR, hazard ratio; CI, confidence interval; MFM, metformin; SU, sulfonylurea; TZD, thiazolidinedione; DPP4i, dipeptidyl peptidase-4 inhibitor.

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