The association between midlife lifestyle and psychiatrist-diagnosed depression later in life: Who in your family reduces the risk of depression?
Participants of the prospective study based on Japan Public Health Center (JPHC study) in 2014-2015, living in the catchment area of Saku Public Health Center in Nagano Prefecture, were invited to a survey on mental health. The JPHC study was initiated in five public health centers (PHC) in Japan for cohort I in 1990 . A self-administered questionnaire on demographic information, lifestyle characteristics, and social factors was distributed to noninstitutionalized residents aged 40–59 in 1990 and followed up 5, 10, and 15 years after the first survey. (response rate: 74–81%) were performed.
There were 12,219 participants (6,172 men and 6,047 women) in the baseline survey. After excluding 3392 participants because they left the study area, died or did not answer these last questionnaires during the follow-up, we selected the remaining 8827 people. We invited participants to participate in a mental health survey. A total of 1299 out of 8827 participants (14.7%) responded to the mental health screening. We further excluded 21 participants due to incomplete data for the family configuration questionnaires and 24 participants with a history of depression in the mental health screening questionnaires. The remaining 1254 participants (529 men and 725 women) aged 64 to 84 were included in the analysis. An organizational chart of study participants is shown in Fig. 1.
The question about the individual’s family configuration in the baseline questionnaire was: “Do you live with anyone (spouse, child(ren), parent(s), others, alone) together now?” According to Japanese culture, “others” are considered other members of the family; siblings, grandparents, uncles, aunts, cousins, in-laws, etc. The same question was repeated for each follow-up survey. In the present study, we used a questionnaire from 1990, and only 15 people (five men and ten women) living alone participated; we were therefore unable to analyze them as explanatory variables.
With respect to background, we followed participants from 1990 until screening in 2014-2015 and recorded participants’ conditions, including survival and medical status, in catchment areas of Saku City. We assessed cancer incidence using medical records from each hospital in the study area. We asked for a history of depression, diabetes mellitus, stroke and myocardial infarction by the self-administered questionnaire of this mental health survey. All other covariates except background (smoking status, alcohol frequency, sleep duration, and occupation) were queried as part of the baseline survey in 1990.
Certificate of depression
Board-certified psychiatrists assessed all participants in this mental health screening. First, we administered the Center for Epidemiological Scale-Depression (CES-D) [21, 22] and the Patient Health Questionnaire-9 (PHQ-9) [23, 24] screening tests at the same time. Second, well-trained, board-certified psychiatrists interviewed participants with reference to CES-D and PHQ-9 scores. Finally, psychiatrists assessed whether the participant had been diagnosed with MDD based on criteria from the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV). [19, 20] and reached consensus for the final diagnosis when each psychiatrist’s diagnosis was different.
If a patient experiences depressive symptoms, they are not always diagnosed with depression. . Mild cognitive impairment (MCI), dementia and pseudo-dementia may be associated with similar symptoms [25,26,–27]. It is often difficult for general practitioners to distinguish MDD from others, and patients sometimes have overlapping diseases [25, 28]. Well-trained, board-certified psychiatrists met with the 1,299 participants, confirmed their self-report questionnaires, and assessed whether the participants currently met DSM-IV criteria for MDD after considering whether their depressive symptoms caused a clinically significant distress or impairment. .
Logistic regression analyzes were performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) of MDD associated with family configuration. We adjusted for age (years, continuous) and gender in the first model and adjusted for other lifestyle and medical history factors in the second model. These factors included smoking status (never, former, current), frequency of alcohol consumption (rarely, 1-3 times per month, 1-2 times per week, 3-4 times per week, 5-6 times per week, daily), sleep duration (≤4 h, 5–9 h, ≥10 h), occupation (professionals, managers, white collars and blue collars) and education (primary education, lower secondary, upper secondary, post – secondary), history of cancer (yes or no), stroke (yes or no), myocardial infarction (yes or no) and diabetes mellitus (yes or no). The rate of missing values was less than 0.2–1.4%. Missing data were assumed to be randomly missing (MAR), and we used multiple imputations to handle missing data of confounding variables using the “mouse” package in R software. All variables in the set of data used in this study were included in the imputation model. Results from five imputed data sets were combined by averaging, and standard errors were adjusted to reflect both intra-imputation variability and inter-imputation variability in the pooling phase. . The level of statistical significance was set at α = 0.05 (two-tailed). All statistical analyzes were performed using R software (version 3.5.3; https://www.r-project.org/).