Abstract
Background
Research has produced conflicting findings on whether ADHD is associated with financial debt. Moreover, as yet, there has been little research on this association in non-Western settings. To address this deficit, this cross-sectional study examined the association between ADHD symptoms and debt in the Japanese general population.
Methods
Data were used from an online sample of 3,717 adults aged ≥ 18 years old. A single-item question was used to assess debt. ADHD symptoms were measured with the Adult ADHD Self-Report Scale (ASRS) Screener. Information was also collected on demographic characteristics and mental health.
Results
In a fully adjusted logistic regression analysis, ADHD symptoms (as a continuous score) were significantly associated with debt in the total sample (OR: 1.04, 95%CI: 1.01–1.07). In sex-stratified analyses, ADHD symptoms were associated with debt in women (OR: 1.06, 95%CI: 1.01–1.10), while the association was of borderline statistical significance in men (OR: 1.04, 95%CI: 1.00-1.07, p = .053). When the analysis was stratified by age, ADHD symptoms were significantly associated with debt in adults aged 18 to 34 (OR: 1.10, 95%CI: 1.04–1.16) and 60 and above (OR: 1.09, 95%CI: 1.02–1.16) but not in those aged 35 to 59 (OR: 1.01, 95%CI: 0.97–1.05).
Conclusion
ADHD symptoms are associated with debt in Japanese adults. More research is needed to determine the causes and consequences of debt in adults with ADHD.
Keywords: ADHD, Anxiety, Debt, Depression, Japan
Introduction
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterized by a persistent pattern of inattention and/or hyperactivity-impulsivity [1] that has been estimated to persist from childhood in 2.58% of adults globally, while 6.76% of individuals meet the symptom criteria for ADHD in adulthood, regardless of childhood onset [2]. Together with its associated features such as emotional dysregulation [3, 4] and cognitive impairment [5], ADHD has been linked to a range of detrimental outcomes in adulthood. For example, adults with ADHD are more likely to encounter difficulties in their personal relationships [6, 7] and in the occupational sphere, with studies linking ADHD to lower levels of employment/more days of unemployment [8, 9] and an increased prevalence of receiving sick pay or a disability pension [10]. Relatedly, research has also found that adults with ADHD/ADHD symptoms experience greater financial difficulties such as having problems managing/saving money [6], engage in riskier financial behaviors [11], and report higher levels of financial stress [12].
In connection with this, the current study will examine the association between ADHD symptoms and one financial outcome – being in debt – among adults in Japan. There is a range of factors which suggest that ADHD/ADHD symptoms might be important for debt. In particular, research has shown that adults with ADHD have lower incomes and less money to spend each month [13], are more likely to use pawn services [14], and buy on impulse [6, 13]. Indeed, a diagnosis of ADHD has been linked to compulsive buying in college students [15], while another study found that ADHD symptoms were elevated in individuals with compulsive buying disorder [16]. In addition, research has highlighted that adults with ADHD have problems with financial decision-making [13] and in relation to their financial knowledge and skills [17], while worse financial decision-making may be reflected in the association between ADHD symptoms and poorer portfolio returns in online stock trading [18]. Despite this, studies that have examined the ADHD/ADHD symptoms-financial debt association have produced conflicting findings showing both no association [19–21] and that an ADHD diagnosis [13] and a higher ADHD symptom score [14] are linked to higher levels of debt. It is uncertain why findings have differed between studies and whether this reflects methodological differences in the categorization of ADHD/ADHD symptoms or debt, differences in the types of debt examined, or other factors such as the age of the study samples. It has been suggested, for example, that the comparatively young age of participants in previous studies may help explain the mixed findings among adults [13].
Examining the association between ADHD symptoms and debt in Japanese adults may be particularly instructive. Until now, there has been comparatively little research focused on adult ADHD in Japan, with a recent study suggesting that there may be a large number of undiagnosed and thus untreated adults with ADHD in this setting [22]. In terms of debt, this may be important as there is some indication that the level of financial debt has grown sharply in Japan in recent years [23], with a recent report stating that by the end of March 2022 there were 1.16 million people with multiple unpayable loans, with an average combined debt of ¥544,000 ($4,469) [24]. Given that a recent study also found that ADHD symptoms are elevated in Japanese workers with low as compared to high household incomes [25], it is possible that individuals with ADHD/ADHD symptoms may be disproportionately exposed to debt and its negative consequences in this setting.
Thus, this study has two main aims. First, to examine whether there is an association between ADHD symptoms and financial debt in Japanese adults. A focus on symptoms is warranted in light of the results from a recent study which showed that the relationship between ADHD symptoms in childhood and financial outcomes in adulthood is not limited to those with the most severe symptoms but rather exists across the range of ADHD symptom scores [26]. Second, given that there is some evidence that the forms and levels of debt can vary between both men and women [27] and different age groups [28, 29], we will also perform stratified analyses that examine whether the association between ADHD symptoms and debt differs by sex and age group.
Methods
Study participants
Cross-sectional data were obtained from an online survey of the Japanese general population. The survey was performed in March 2023 by a Japanese market research company that focuses on the healthcare sector. Based on past studies of mental health in Japan, the aim was to obtain a sample of approximately 3,000 individuals. In the initial phase, almost 23,000 people were randomly chosen from the company’s online panel of the Japanese general consumer population and invited to participate in the survey. In line with several previous studies [30, 31], in the current study, the main inclusion criterion was that participants should be adults, i.e., aged ≥ 18 years old. In terms of the male-female distribution of the sample, it had to be representative of the Japanese general population in terms of age and sex. Moreover, participants had to be sampled from each of Japan’s 47 prefectures. After the data collection phase was complete, the final sample consisted of 3,717 participants. Ethical approval for the study was provided by the ethics committee at the National Center of Neurology and Psychiatry, Tokyo, Japan (approval number: A2022-096). The study was carried out in accordance with the 1964 Declaration of Helsinki and its subsequent amendments. All participants provided informed consent before their inclusion in the study.
Measures
ADHD symptoms were assessed with the Adult ADHD Self-Report Scale (ASRS) Screener [32, 33]. This six-item screening scale inquires about symptoms of inattention and hyperactivity in the past six months using five response options: never (scored 0), rarely (1), sometimes (2), often (3), very often (4). The total scale score can range from 0 to 24, with higher scores indicating increased ADHD symptoms. This score was used as a continuous variable in this study. Cronbach’s alpha for the scale was 0.87. Financial debt was assessed with a single-item question that specifically asked, “Do you have any financial debts?” with a yes/no answer option. This item obtained information on the self-reported presence of debt regardless of the type or amount. As no formal definition of debt was provided, responses likely reflect participants’ subjective interpretation of ongoing financial obligations.
Previous literature was used as a guide when choosing study covariates. Specifically, information was obtained on a variety of sociodemographic variables. Besides sex (male, female), participants also provided details of their age, which was subsequently divided into three categories, 18–34, 35–59 and 60 and above. This categorization not only reflects different life stages (i.e., young adulthood, middle age and older adulthood), but is also appropriate given that there is evidence, as mentioned above, that the prevalence and level of debt varies over the life course [29, 34]. In terms of education, respondents were categorized as having either a higher education (two-year college, university, graduate school) or less than a higher education (junior high school, high school, specialized vocational high school). For marital status, respondents were categorized as being either married/cohabiting, single (never married), or divorced/widowed. Participants also provided details of their household income in millions of yen (132.93 JPY = 1 USD at the time of the survey). This was subsequently divided into three categories: (i) < 4 million; (ii) 4 < 10 million; (iii) ≥ 10 million; as many respondents did not answer this question, and given our desire to keep the analytic sample as large as possible, an additional (iv) ‘missing’ category was created. In addition, participants were also asked, “How has your household’s economic situation changed during the past year?” with three response options, unchanged, improved, or worsened. Self-rated health was categorized as being either good/very good, fair, or poor/very poor. Problematic alcohol use was assessed with the four-item CAGE questionnaire [35], which inquires about different aspects of problematic drinking such as needing to cut down on drinking. The total scale score can range from 0 to 4. Using the established cut-off point, in the current study a score of ≥ 2 was used to categorize cases of problematic alcohol use [36]. Cronbach’s alpha was 0.68 for the scale. For smoking status, participants were categorized as either never smokers, former smokers, or current smokers; this final category consisted of daily and non-daily smokers, with information also being collected from daily smokers on the number of cigarettes they smoked per day.
In addition, as common mental disorders are also prevalent in individuals with ADHD [37] and have also been linked to debt [38], information was collected on two mental health variables. Past two-week depressive symptoms were assessed with the nine-item Patient Health Questionnaire (PHQ-9) [39]. The total scale score ranges from 0 to 27, with higher scores indicating more depressive symptoms. This measure had a high degree of reliability in the current study (Cronbach’s alpha was 0.89). Past two-week anxiety symptoms were assessed with the seven-item Generalized Anxiety Disorder-7 (GAD-7) scale [40]. The total scale score ranges from 0 to 21, with higher scores indicating increased anxiety. Cronbach’s alpha for the scale was 0.92.
Statistical analysis
Descriptive statistics of the study sample stratified by debt status were first calculated. Chi-square and Mann-Whitney U tests were used to examine differences between variable categories or scores. Logistic regression was then used to examine the association between ADHD symptoms and financial debt. Six models were used to examine this association. Model 1 examined the unadjusted association between ADHD symptoms and debt. Subsequent models were additionally adjusted for the sociodemographic variables (sex, age, education, marital status, household income) (Model 2); household financial situation in the past year (Model 3); self-rated health (Model 4); and problematic alcohol use and smoking status (Model 5). The fully adjusted Model 6 included the same variables as in Model 5 together with anxiety and depressive symptoms. Using the same analytic model-building process just described, we next performed sex- and age-stratified analyses to determine if the ADHD symptoms-debt association varied across different subgroups of the population.
All analyses were performed with the IBM SPSS statistical package, version 24. Results are presented as odds ratios (OR) with 95% confidence intervals (CI). All analyses were adjusted for location. The level of statistical significance was p < 0.05 (two-tailed).
Results
The sample consisted of 3,717 individuals with a mean (SD) age of 52.7 (18.3) years (range 18 to 89), with slightly more females than males (51.5% vs. 48.5%). Financial debt was prevalent in the study sample (17.7%, N = 659). When the study sample was stratified by debt status, there were significant differences across nearly all of the variables (Table 1). In particular, the mean ADHD symptom score was significantly higher in individuals with debt compared to those without debt (6.0 vs. 4.7).
Table 1.
Sample characteristics by financial debt
| Total | No debt | Debt | p-value* | ||
|---|---|---|---|---|---|
| N (%) | N (%) | N (%) | |||
| ADHD symptoms (M (SD)) | 4.9 (4.0) | 4.7 (3.9) | 6.0 (4.4) | < 0.001 | |
| 3,717 (100) | 3,058 (82.3) | 659 (17.7) | |||
| Sex | < 0.001 | ||||
| Male | 1,804 (48.5) | 1,388 (76.9) | 416 (23.1) | ||
| Female | 1,913 (51.5) | 1,670 (87.3) | 243 (12.7) | ||
| Age | < 0.001 | ||||
| 18–34 | 727 (19.6) | 587 (80.7) | 140 (19.3) | ||
| 35–59 | 1,531 (41.2) | 1,151 (75.2) | 380 (24.8) | ||
| ≥ 60 | 1,459 (39.3) | 1,320 (90.5) | 139 (9.5) | ||
| Education | 0.010 | ||||
| Higher education | 2,335 (62.8) | 1,950 (83.5) | 385 (16.5) | ||
| < Higher education | 1,382 (37.2) | 1,108 (80.2) | 274 (19.8) | ||
| Marital status | 0.010 | ||||
| Married/cohabiting | 2,259 (60.8) | 1,826 (80.8) | 433 (19.2) | ||
| Single (never married) | 1,026 (27.6) | 860 (83.8) | 166 (16.2) | ||
| Divorced/widowed | 432 (11.6) | 372 (86.1) | 60 (13.9) | ||
| Household income (yen) | < 0.001 | ||||
| 4- < 10 million | 1,416 (38.1) | 1,122 (79.2) | 294 (20.8) | ||
| ≥ 10 million | 272 (7.3) | 206 (75.7) | 66 (24.3) | ||
| < 4 million | 1,178 (31.7) | 1,006 (85.4) | 172 (14.6) | ||
| Missing | 851 (22.9) | 724 (85.1) | 127 (14.9) | ||
| Household finances | < 0.001 | ||||
| Unchanged | 1,906 (52.4) | 1,669 (87.6) | 237 (12.4) | ||
| Improved | 269 (7.4) | 200 (74.3) | 69 (25.7) | ||
| Worsened | 1,463 (40.2) | 1,119 (76.5) | 344 (23.5) | ||
| Self-rated health | 0.439 | ||||
| Good/very good | 1,662 (44.9) | 1,379 (83.0) | 283 (17.0) | ||
| Fair | 1,438 (38.9) | 1,179 (82.0) | 259 (18.0) | ||
| Poor/very poor | 601 (16.2) | 485 (80.7) | 116 (19.3) | ||
| Problematic alcohol use | < 0.001 | ||||
| No | 3,252 (87.5) | 2,719 (83.6) | 533 (16.4) | ||
| Yes | 465 (12.5) | 339 (72.9) | 126 (27.1) | ||
| Smoking status | < 0.001 | ||||
| Never smoker | 2,292 (61.7) | 1,969 (85.9) | 323 (14.1) | ||
| Former smoker | 786 (21.1) | 640 (81.4) | 146 (18.6) | ||
| Current smoker | 639 (17.2) | 449 (70.3) | 190 (29.7) | ||
| Anxiety symptoms (M (SD)) | 3.2 (4.3) | 3.0 (4.1) | 4.4 (4.7) | < 0.001 | |
| 3,717 (100) | 3,058 (82.3) | 659 (17.7) | |||
| Depression symptoms (M (SD)) | 4.9 (5.1) | 4.6 (5.0) | 6.2 (5.5) | < 0.001 | |
| 3,717 (100) | 3,058 (82.3) | 659 (17.7) | |||
*Chi-square and Mann-Whitney U tests were used to assess outcomes
ADHD: Attention-deficit/hyperactivity disorder
M: Mean; SD: Standard deviation
In Model 1 of the logistic regression analysis, there was a statistically significant association between ADHD symptoms and financial debt in the total sample (OR: 1.08, 95%CI: 1.06–1.11, p < .001) (Table 2). Adjusting the analysis for the sociodemographic variables (Model 2), changes in the household’s financial situation (Model 3), self-rated health (Model 4), health risk behaviors (problematic alcohol use and smoking) (Model 5) and the mental health variables (depression and anxiety symptoms) in Model 6 slightly attenuated this association. In the fully adjusted analysis, ADHD symptoms continued to be significantly associated with financial debt (OR: 1.04, 95%CI: 1.01–1.07, p = .004).
Table 2.
Association between ADHD symptoms and financial debt among adults in Japan (N = 3,635)
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | ||
|---|---|---|---|---|---|---|---|
| OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | ||
| ADHD symptoms | 1.08 (1.06–1.11)*** | 1.07 (1.05–1.09)*** | 1.05 (1.03–1.08)*** | 1.05 (1.03–1.08)*** | 1.05 (1.03–1.08)*** | 1.04 (1.01–1.07)** | |
| Sex (Female) | 0.47 (0.39–0.57)*** | 0.46 (0.38–0.56)*** | 0.46 (0.38–0.56)*** | 0.53 (0.43–0.64)*** | 0.52 (0.43–0.64)*** | ||
| Age | |||||||
| 18–34 | Ref. | Ref. | Ref. | Ref. | Ref. | ||
| 35–59 | 1.11 (0.87–1.42) | 1.06 (0.83–1.37) | 1.07 (0.83–1.37) | 1.03 (0.80–1.34) | 1.03 (0.80–1.34) | ||
| ≥ 60 | 0.34 (0.25–0.46)*** | 0.34 (0.25–0.46)*** | 0.34 (0.25–0.47)*** | 0.35 (0.25–0.47)*** | 0.36 (0.26–0.49)*** | ||
| Education | |||||||
| < Higher education | 1.46 (1.21–1.76)*** | 1.44 (1.19–1.75)*** | 1.45 (1.19–1.75)*** | 1.38 (1.14–1.67)** | 1.37 (1.13–1.66)** | ||
| Marital status | |||||||
| Married/cohabiting | Ref. | Ref. | Ref. | Ref. | Ref. | ||
| Single (never married) | 0.55 (0.43–0.69)*** | 0.55 (0.44–0.71)*** | 0.56 (0.44–0.71)*** | 0.57 (0.45–0.72)*** | 0.56 (0.44–0.72)*** | ||
| Divorced/widowed | 0.96 (0.70–1.32) | 0.95 (0.69–1.31) | 0.95 (0.69–1.31) | 0.92 (0.66–1.27) | 0.92 (0.66–1.27) | ||
| Household income (yen) | |||||||
| 4 < 10 million | Ref. | Ref. | Ref. | Ref. | Ref. | ||
| ≥ 10 million | 1.18 (0.86–1.63) | 1.31 (0.94–1.82) | 1.31 (0.94–1.82) | 1.28 (0.92–1.78) | 1.27 (0.91–1.77) | ||
| < 4 million | 0.87 (0.69–1.10) | 0.82 (0.64–1.03) | 0.82 (0.64–1.03) | 0.83 (0.66–1.06) | 0.83 (0.65–1.05) | ||
| Missing | 0.82 (0.64–1.05) | 0.81 (0.63–1.05) | 0.82 (0.63–1.05) | 0.84 (0.66–1.09) | 0.84 (0.65–1.08) | ||
| Household finances | |||||||
| Unchanged | Ref. | Ref. | Ref. | Ref. | |||
| Improved | 1.71 (1.23–2.36)** | 1.70 (1.23–2.36)** | 1.67 (1.20–2.32)** | 1.65 (1.19–2.30)** | |||
| Worsened | 2.06 (1.70–2.51)*** | 2.07 (1.70–2.51)*** | 2.01 (1.65–2.45)*** | 1.99 (1.63–2.43)*** | |||
| Self-rated Health | |||||||
| Good/very good | Ref. | Ref. | Ref. | ||||
| Fair | 0.99 (0.81–1.21) | 0.98 (0.80–1.20) | 0.97 (0.79–1.19) | ||||
| Poor/very poor | 0.99 (0.75–1.29) | 0.98 (0.75–1.28) | 0.93 (0.70–1.24) | ||||
| Problematic alcohol use | 1.07 (0.83–1.37) | 1.05 (0.81–1.35) | |||||
| Smoking status | |||||||
| Never smoker | Ref. | Ref. | |||||
| Former smoker | 1.18 (0.93–1.50) | 1.19 (0.93–1.51) | |||||
| Current smoker | 1.64 (1.29–2.07)*** | 1.64 (1.30–2.08)*** | |||||
| Anxiety symptoms | 1.01 (0.98–1.05) | ||||||
| Depression symptoms | 1.01 (0.98–1.04) | ||||||
OR: Odds ratio; CI: Confidence interval; Ref: Reference category. All models were adjusted for location
**p < .01, ***p < .001
The results from the sex- and age-stratified analyses are presented in Table 3. Similar associations were observed for men and women in Models 1 to 5 with ADHD symptoms being significantly associated with financial debt in both men (OR: 1.05, 95%CI: 1.02–1.08, p = .001) and women (OR: 1.07, 95%CI: 1.03–1.11, p = .001) in Model 5. In the fully adjusted Model 6, which further included anxiety and depression symptoms, the magnitude of the association remained comparable for men (OR: 1.04, 95%CI: 1.00-1.07, p = .053) and women (OR: 1.06, 95%CI: 1.01–1.10, p = .021). Although the association in men did not reach conventional statistical significance (p = .053), the size of the association was largely unchanged from earlier models (see Table 3 for the full results). Indeed, when the analysis was repeated in the total sample with the inclusion of an ADHD symptoms x sex interaction term, there was no evidence that the strength of the association with debt differed by sex (OR = 1.03, 95%CI: 0.98–1.07, p = .265) (data not tabulated). This indicates that increases in ADHD symptoms were associated with similar increases in the odds of financial debt for men and women.
Table 3.
Sex- and age-specific analyses of the association between ADHD symptoms and financial debt among Japanese adults
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | |
|---|---|---|---|---|---|---|
| OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | |
| Sex | ||||||
| Men (N = 1,772) | ||||||
| ADHD symptoms | 1.07 (1.04–1.10)*** | 1.06 (1.04–1.09)*** | 1.05 (1.02–1.08)*** | 1.05 (1.02–1.08)** | 1.05 (1.02–1.08)** | 1.04 (1.00-1.07)† |
| Women (N = 1,863) | ||||||
| ADHD symptoms | 1.10 (1.06–1.14)*** | 1.08 (1.04–1.11)*** | 1.06 (1.02–1.10)** | 1.06 (1.03–1.11)** | 1.07 (1.03–1.11)** | 1.06 (1.01–1.10)* |
| Age | ||||||
| 18–34 (N = 683) | ||||||
| ADHD symptoms | 1.09 (1.05–1.13)*** | 1.09 (1.05–1.14)*** | 1.09 (1.04–1.14)*** | 1.09 (1.04–1.14)*** | 1.09 (1.04–1.14)*** | 1.10 (1.04–1.16)** |
| 35–59 (N = 1,505) | ||||||
| ADHD symptoms | 1.04 (1.01–1.07)* | 1.04 (1.01–1.07)** | 1.03 (1.00-1.06)† | 1.03 (1.00-1.06)† | 1.03 (1.00-1.06)† | 1.01 (0.97–1.05) |
| ≥ 60 (N = 1,447) | ||||||
| ADHD symptoms | 1.14 (1.08–1.20)*** | 1.13 (1.07–1.19)*** | 1.11 (1.05–1.17)*** | 1.11 (1.05–1.18)*** | 1.11 (1.05–1.18)*** | 1.09 (1.02–1.16)** |
Model 1 examined the bivariate association between ADHD symptoms and debt; Model 2 was additionally adjusted for sex, age, education, marital status and household income; Model 3 was additionally adjusted for household financial situation; Model 4 was additionally adjusted for self-rated health; Model 5 was additionally adjusted for problematic alcohol use and smoking status; Model 6 was additionally adjusted for anxiety and depressive symptoms. All models were adjusted for location
OR: Odds ratio; CI: Confidence interval
*p < .05, **p < .01, ***p < .001, †p < .10 (exact p-values: Men, Model 6: p = .053; adults aged 35–59, Model 3: p = .064; Model 4: p = .051; Model 5: p = .067)
When the analysis was stratified by age, there were some differences between the age groups. Specifically, in the bivariate Model 1 the OR for the association between ADHD symptoms and financial debt was higher in younger (OR: 1.09, 95%CI: 1.05–1.13, p < .001) and older adults (OR: 1.14, 95%CI: 1.08–1.20, p < .001) than in middle-aged adults (OR: 1.04, 95%CI: 1.01–1.07, p = .012). Moreover, the more modest association between ADHD symptoms and debt observed among adults aged 35–59 in Model 1 and Model 2 became non-significant in Model 3 (OR: 1.03, 95%CI: 1.00-1.06, p = .064). In the fully adjusted Model 6, ADHD symptoms were significantly associated with financial debt in both adults aged 18–34 (OR: 1.10, 95%CI: 1.04–1.16, p = .001) and those aged 60 and above (OR: 1.09, 95%CI: 1.02–1.16, p = .008). To test whether the association between ADHD symptoms and debt differed across the age groups, we repeated the analysis of the total sample while including an ADHD x age group interaction term. This was statistically significant (Wald X² = 10.18, df = 2, p = .006), with the results showing that the association was stronger in younger and older adults compared with those aged 35–59 (data not tabulated). This suggests that ADHD symptoms are more strongly related to debt in earlier and later adulthood, whereas the association is weaker at midlife.
As a sensitivity analysis, we also used logistic regression to examine whether ADHD symptoms were associated with debt when using an ASRS score of 14 and above to categorize cases, as this is commonly used as a screening cut-off to indicate elevated ADHD symptoms or possible ADHD warranting further investigation. Using this criterion, 2.4% (N = 87) of the analytic sample were categorized as having higher ADHD symptoms. In a fully adjusted logistic regression analysis that used the same model-building process as applied previously, an ASRS score ≥ 14 was associated with significantly higher odds of financial debt (OR: 1.70, 95%CI: 1.01–2.85, p = .047) (data not tabulated).
Discussion
This study used data from an online sample of over 3,700 Japanese adults to examine the association between ADHD symptoms and financial debt. Descriptive statistics showed that debt was prevalent in the study sample and that individuals who were in debt had a significantly higher ADHD symptom score. Results from a fully adjusted logistic regression analysis further confirmed the existence of an association by showing that ADHD symptoms were associated with significantly higher odds of financial debt in the total sample. Moreover, in sex- and age-stratified analyses, similar results were obtained as ADHD symptoms were associated with debt in women and men (where the latter association was of borderline statistical significance) and in younger and older adults, whereas there was no association in middle-aged adults. These findings should, however, be viewed with some caution, given that financial debt was assessed using a single-item measure that did not distinguish between different types or characteristics of debt.
The observed association between ADHD symptoms and debt should be interpreted in light of previous research, which has yielded conflicting results, with some studies finding no association [19–21] and others reporting that ADHD is linked to financial debt [13, 14]. Indeed, one study indicated that among young adults aged 19–25 who had been diagnosed with hyperactivity in childhood, the association might vary depending on the type of debt, as although there were no differences in terms of credit card debt, the hyperactive (vs. control) group owed significantly more money to other people ($949 vs. $412) [41]. It is uncertain why results have varied across studies. As this latter study indicates, it might be related to differences in the types of debt assessed. Alternatively, a recent study, which found that individuals with increased ADHD symptomatology did not have higher levels of debt, suggested that the association might be stronger in clinical samples with more severe ADHD symptoms [21]. While the results of the current study seemingly contradict the idea that this association is necessarily stronger in clinical samples, it is possible that other factors might be involved. For example, in one study mother-rated ADHD symptom scores at ages 4–14 were not associated with credit card debt in young adults (average age 27.0 years). However, when the analysis was stratified by symptom type, an association was observed between hyperactive-impulsive symptoms, but not inattention symptoms and credit card debt [26]. Thus, more research is needed in different settings, which focuses on different forms of debt and different presentations of ADHD to better delineate the ADHD/ADHD symptoms-debt association.
It is possible that a variety of potentially co-occurring factors might help explain why individuals with ADHD/ADHD symptoms have an increased likelihood of being in debt. For example, one study found that young adults diagnosed with ADHD in childhood had monthly salaries that were 37% lower at age 30 compared to those of control subjects [42], while a recent register-based study from Sweden showed that the incomes of individuals with ADHD were on average 17% lower [9]. In terms of debt, it is possible that the effects of low income are further exacerbated by deficits in financial skills and knowledge. In particular, studies have found that individuals with ADHD have more difficulty understanding financial information [43], find it more difficult to identify financial problems and their associated risks/benefits [13], and have reduced knowledge of their own income/assets, as well as less access to financial advice/counseling [17]. Moreover, the fact that ADHD/ADHD symptoms have also been linked to impulsive/compulsive buying [13, 15, 16] might also be important for debt. Indeed, it is possible to imagine a range of scenarios that might result in increased debt in this population. For example, the fact that adults with ADHD seem to have difficulty saving money [6] might not only be explained by their lower incomes but also by the finding that they are more likely to be fired from their jobs and/or experience unemployment [44], which might also result in a greater need to borrow money when they are without work.
Previous research with general population samples has suggested that there may be sex and age differences in the levels and forms of debt [27–29]. This was also observed in the current study, where men and middle-aged adults had a higher prevalence of debt than their counterparts. However, in sex-stratified analyses, the associations between ADHD symptoms and debt were similar in men and women as seen in the size of the ORs and also shown by the results of the interaction analysis. In age-stratified analyses there was a strong association between ADHD symptoms and debt in younger and older adults. The finding that ADHD symptoms were linked to debt in adults aged 18–34 accords with the results from some [26, 41], but not all studies [19, 42] that have followed children diagnosed with ADHD or having higher ADHD symptom levels into early adulthood. Some of the factors noted above may underlie the association between ADHD symptoms and debt in young adults. For example, individuals in this age range are still establishing credit histories, and ADHD-related impulsivity may exert a stronger influence on early borrowing (e.g., credit cards, consumer debt) and spending, while difficulties arising from such things as lower income and unstable employment may further heighten the risk of debt. Regarding older adults, there has been much less research conducted on the role of ADHD in this population, even though many older adults may have elevated ADHD symptoms [45]. Nonetheless, our finding does seem to accord with that from a study among older adults with ADHD, with a mean age of 66 years, many of whom reported being in a poorer financial position due to impulsive spending and an inability to manage debt across the life course [46].
The absence of an association between ADHD symptoms and debt in middle-aged adults was unexpected, given prior research linking ADHD symptoms negatively to full-time employment and positively to financial stress in this age range [12]. One possible explanation is that the overall debt burden is highest at midlife [29] as a result of such things as mortgages and family obligations, so that individuals with ADHD symptoms might not stand out from their peers to the same extent as in younger or older age groups. This could also help account for the lower odds observed in those aged 35–59 in the unadjusted analysis. Alternatively, it is possible that in the context of high and normative levels of debt in middle age, the lack of an association might partly reflect the fact that this study focused on ADHD symptoms rather than diagnosed ADHD, for which financial and occupational impairments might be more pronounced.
The results of this study should be considered in light of several limitations. Information was obtained on financial debt using a single-item question. However, no information was collected on whether respondents had single or multiple debts, the monetary value of the debt, whether the debt was secured or unsecured, or concerning the length of time individuals had been in debt. Moreover, the item did not define what should be regarded as ‘any financial debts’ or whether this referred to, e.g., any outstanding debts, long-term debt, or debt perceived as being problematic. As a result, respondents may have used differing thresholds when deciding and reporting whether they had debts. Having more detailed information on the form and other aspects of the debt would have helped us to better understand the association between ADHD symptoms and debt. Further, for our main measures, we relied on self-reports. In terms of debt, this may have been problematic as there is some evidence that debt may be underreported [47], possibly as a result of socially desirable responding. Similarly, there is also some indication that adults with ADHD may underreport their own symptoms compared with the results obtained from clinical evaluations [48]. In addition, it is also possible that important variables were not included in the analysis. For example, we did not examine factors such as financial literacy, impulsive purchasing behaviors, or employment stability, which may be relevant to understanding the association between ADHD symptoms and debt. Indeed, survey data suggest, that levels of financial literacy may be relatively low in Japan compared with some other developed countries [49]. It should also be noted that the data were drawn from an online survey, which can sometimes be non-representative of the underlying population because of issues of self-selection and/or other demographic differences relative to the general population [50]. As such, caution is warranted in generalizing these findings beyond the study sample. Finally, although ADHD is a neurodevelopmental disorder that typically emerges in childhood [51], the cross-sectional design of this study precludes conclusions about the temporal relationship between ADHD symptoms and debt in adulthood and does not allow for causal inference. The observed association may reflect a bidirectional relationship between financial strain and self-reported ADHD symptoms, or be influenced by unmeasured socioeconomic factors.
In conclusion, this study found that ADHD symptoms were significantly associated with financial debt in a large sample of Japanese adults. This association is relevant in light of previous research indicating that financial difficulties may be elevated among adults with ADHD and have been linked to serious adverse outcomes, including legal action related to unpaid obligations and heightened suicide risk [17, 52]. Overall, the results suggest that financial difficulties may be an important correlate of ADHD symptoms and underscore the need for further research to clarify the nature and implications of this association. In addition, these findings may help to raise awareness among clinicians of potential financial vulnerability among adults presenting with elevated ADHD symptoms. This is relevant given evidence that debt and debt-related worry are associated with poorer mental health [53], and that broader socioeconomic disadvantage is linked to worse treatment outcomes in adults with mental disorder [54]. Finally, future research in Japan should examine whether culturally specific attitudes towards debt influence the ADHD-debt association, as recent survey data indicate generally cautious and conditional attitudes towards borrowing among Japanese adults [55].
Acknowledgements
N/A.
Author contributions
Conceptualization, A. St.; methodology, A. St., A. Sh., T. S.; formal analysis, A. St.; data curation, A. Sh.; writing – original draft preparation, A. St.; writing – review and editing, A. Sh., V. R., J. I., T. S.; funding acquisition, T. S. All authors have reviewed and agreed to the submission of the manuscript.
Funding
AMED Grants (22dk0307114, 25dk0307137), and Intramural Research Grant (6 − 1) for Neurological and Psychiatric Disorders of the National Center of Neurology and Psychiatry to T.S. The funders had no role in any aspect of this research study.
Data availability
The datasets generated and/or analyzed during the current study are not publicly available due to the terms of the data provision contract but are available from the first author upon reasonable request.
Declarations
Ethics approval and consent to participate
The ethics committee at the National Center of Neurology and Psychiatry, Tokyo, Japan gave permission for the survey (approval number: A2022-096). The study was carried out in accordance with the 1964 Declaration of Helsinki and its subsequent amendments. All participants provided informed consent before their inclusion in the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Andrew Stickley, Email: amstick66@gmail.com.
Tomiki Sumiyoshi, Email: sumiyot@ncnp.go.jp.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available due to the terms of the data provision contract but are available from the first author upon reasonable request.