This study looked at ADHD traits in 1240 regular-staff workers in Japan, aged 20 to 69. All were university graduates, and they were not a patient sample. There were 620 men and 620 women, with 248 people in each age decade. Data were collected online in March 2019. Traits were measured with a short six-item self-report screener.
With all factors taken into account, higher trait scores went with being male and being younger. They also went with lower household income, more frequent midnight meals, and not feeling rested after sleep. Longer working hours, snacking and short sleep were linked after adjusting for sex and age, but not once everything was considered. Job position mattered only under one type of analysis. Drinking, smoking and free-time exercise showed no clear link, though, adjusting only for sex and age, less free-time exercise went with higher inattention trait scores. The authors say the results match earlier studies of adults diagnosed with ADHD.
The authors note limits. An online survey may favor people at ease online. The screener was an older, less accurate version, though it was reported to catch 84.2% of DSM-5 cases. Self-reports may underestimate traits, and the authors call for clinical interviews in future work.
The authors suggest that certain background characteristics may predict high ADHD traits in workers, that such workers should be helped, and that assessing these traits may help prevent related health decline, without saying who should assess or how to help.
The numbers Stats and what the terms mean
The statistics behind the plain-language claims above.
- Suzuki, 2023: average trait score by sex after full adjustment, males, 7.15±0.11 versus females, 6.60±0.11 (p = 0.001).
- Suzuki, 2023: average trait score by age after full adjustment, ages 20 to 29, 7.38±0.18 down to ages 60 to 69, 6.55±0.18 (trend p < 0.001).
- Suzuki, 2023: average trait score by yearly household income after full adjustment, under 4 million yen, 7.20±0.18 versus 12 million yen or more, 6.48±0.21 (trend p = 0.009).
- Suzuki, 2023: average trait score by midnight meals after full adjustment, every day, 7.70±0.35 versus 0 to 2 days/week, 6.76±0.08 (trend p < 0.001).
- Suzuki, 2023: average trait score by rest from sleep after full adjustment, no rest, 7.64±0.32 versus enough rest, 6.70±0.20 (trend p = 0.007).
- Suzuki, 2023: working time, snacks and sleeping hours after full adjustment, p = 0.070, 0.073 and 0.551.
- Suzuki, 2023: working time, snacks and sleeping hours after sex and age adjustment only, p = 0.035, 0.003 and 0.004.
- Suzuki, 2023: occupational position in nonparametric analyses, p = 0.007.
- Suzuki, 2023: less free-time physical activity and higher inattention trait scores, sex and age adjusted, p = 0.004.
- Source not named in the extract: how well the older screener with revised DSM-5 scoring detects DSM-5 cases, sensitivity 84.2% and specificity 89.5%. What the terms mean:
- Mean±SE is the average score, followed by its standard error, which shows how precise that average is.
- p is the chance of seeing a result this strong if there were no real link.
- Trend p tests whether scores rise or fall steadily across ordered groups, such as age bands or income levels.
- Full adjustment means all the other measured factors were taken into account at the same time.
- Nonparametric analyses compare groups without assuming the scores follow a bell-shaped spread.
- DSM-5 is the current edition of the standard manual used to define ADHD and other conditions.
- Sensitivity is the share of true cases the screener catches.
- Specificity is the share of people without the condition whom the screener correctly rules out.
Source: Suzuki T, Wada K, Nakazato M, et al.. Associations Between Adult Attention-Deficit/Hyperactivity Disorder (ADHD) Traits and Sociodemographic Characteristics in Japanese Workers. Neuropsychiatric Disease and Treatment (2023). doi:10.2147/NDT.S398478