Background: Lower socioeconomic status is often thought to be associated with an elevated risk of postpartum depression; however, this relationship exhibits noticeable heterogeneity between studies. The present study examined this relationship in Japan. Methods: Data were obtained from 90,194 mothers in an ongoing birth cohort of the Japan Environment and Children’s Study. Socioeconomic status was assessed based on the mothers’ highest education level during pregnancy. Postpartum depression was identified at 1 and 6 months postpartum based on an Edinburgh Postnatal Depression Scale score of ≥9, and analyses were also performed based on the sub-scores for anxiety, depression, and anhedonia symptoms. Logistic and generalized linear regression model analyses were used to calculate odds ratios for postpartum depression according to education level with the highest education group (≥16 years of education) defined as the reference group, while controlling for covariates in a stepwise fashion. Results: Univariate analysis revealed that a lower education level was associated with a higher prevalence of postpartum depression and related symptoms. Although these relationships weakened in the fully adjusted models, odds ratios for cases and related symptoms remained significant at 1 and 6 months postpartum. Among three symptom dimensions, the relationship was strongest and weakest in the depressive and anxiety symptoms, respectively. Conclusions: A lower education level was an independent risk factor for postpartum depression. In view of the low mobility of the education level, this finding suggests the potential importance of collecting information regarding education levels at the earliest opportunity.

Reflection photoplethysmography (PPG) using 530 nm (green) wavelength light has the potential to be a superior method for monitoring heart rate (HR) during normal daily life due to its relative freedom from artifacts. However, little is known about the accuracy of pulse rate (PR) measured by 530 nm light PPG during motion. Therefore, we compared the HR measured by electrocadiography (ECG) as a reference with PR measured by 530, 645 (red), and 470 nm (blue) wavelength light PPG during baseline and while performing hand waving in 12 participants. In addition, we examined the change of signal-to-noise ratio (SNR) by motion for each of the three wavelengths used for the PPG. The results showed that the limit of agreement in Bland-Altman plots between the HR measured by ECG and PR measured by 530 nm light PPG (±0.61 bpm) was smaller than that achieved when using 645 and 470 nm light PPG (±3.20 bpm and ±2.23 bpm, respectively). The ΔSNR (the difference between baseline and task values) of 530 and 470nm light PPG was significantly smaller than ΔSNR for red light PPG. In conclusion, 530 nm light PPG could be a more suitable method than 645 and 470nm light PPG for monitoring HR in normal daily life.

Cuffless blood pressure (BP) measurement is an all-inclusive term for a method that aims to measure BP without using a cuff. Recent cuffless technology has made it possible to estimate BP with reasonable accuracy. However, mainstream methods require an electrocardiogram and photoplethysmogram measurements, and frequent calibration procedures using a cuff sphygmomanometer. We therefore developed a far simpler cuffless method, using only heart rate (HR) and modified normalized pulse volume (mNPV) that can be measured using a smartphone, based on the knowledge that ln BP = ln cardiac output (CO) + ln total peripheral resistance (TPR), where CO and TPR are correlated with HR and mNPV, respectively. Here, we show that mean arterial pressure (MAP), systolic BP (SBP), and diastolic BP (DBP) could be estimated using the exponential transformation of linear polynomial equation, (a × ln HR) + (b × ln mNPV) + constant, using only a smartphone, with an accuracy of R > 0.70. This implies that our cuffless method could convert a large number of smartphones or smart watches into simplified sphygmomanometers.

Heart rate (HR) and normalized pulse volume (NPV) are physiological indices that have been used in a diversity of psychological studies. However, measuring these indices often requires laborious processes. We therefore developed a new smartphone program, named iPhysioMeter, that makes it possible to measure beat-by-beat HR and ln NPV using only a smartphone. We examined its accuracy against conventional laboratory measures. Mental stress tasks were used to alter HR and ln NPV in 12 participants. Bland–Altman analyses revealed negligible proportional bias for HR and ln NPV or for their change values, expressed as ΔHR and Δln NPV. However, a relatively large fixed bias did emerge for ln NPV, as well as a small one for Δln NPV, although both were within the limits of agreement. These findings suggest that iPhysioMeter can yield valid measures of the absolute level of HR and of relative changes in ln NPV.

Recent progress in information and communication technologies has made it possible to measure heart rate (HR) and normalized pulse volume (NPV), which are important physiological indices, using only a smartphone. This has been achieved with reflection mode photoplethysmography (PPG), by using a smartphone’s embedded flash as a light source and the camera as a light sensor. Despite its widespread use, the method of PPG is susceptible to motion artifacts as physical displacements influence photon propagation phenomena and, thereby, the effective optical path length. Further, it is known that the wavelength of light used for PPG influences the photon penetration depth and we therefore hypothesized that influences of motion artifact could be wavelength-dependant. To test this hypothesis, we made measurements in 12 healthy volunteers of HR and NPV derived from reflection mode plethysmograms recorded simultaneously at three different spectral regions (red, green and blue) at the same physical location with a smartphone. We then assessed the accuracy of the HR and NPV measurements under the influence of motion artifacts. The analyses revealed that the accuracy of HR was acceptably high with all three wavelengths (all rs > 0.996, fixed biases: −0.12 to 0.10 beats per minute, proportional biases: r = −0.29 to 0.03), but that of NPV was the best with green light (r = 0.791, fixed biases: −0.01 arbitrary units, proportional bias: r = 0.11). Moreover, the signal-to-noise ratio obtained with green and blue light PPG was higher than that of red light PPG. These findings suggest that green is the most suitable color for measuring HR and NPV from the reflection mode photoplethysmogram under motion artifact conditions. We conclude that the use of green light PPG could be of particular benefit in ambulatory monitoring where motion artifacts are a significant issue.

Background: Postpartum depression is a major mental health issue. It not only adversely affects the mother's quality of life, but also mother-infant bonding. However, the relationship between postpartum depression (at multiple points after childbirth) and mother-infant bonding failure one year after birth is not well understood. This study investigates the relationship between postpartum depression at 1-month and 6-month after birth and mother-infant bonding failure at 1 year after birth with a large cohort.Methods: Data from 83 109 mothers from the Japan Environment and Children's Study were analyzed. Mother-infant bonding 1-year after delivery was assessed using the Mother-to-Infant Bonding Scale Japanese version (MIBS-J). Postpartum depression was measured using the Edinburgh Postnatal Depression Scale (EPDS) at 1-month and 6-month after delivery. Twenty covariates during pregnancy and one month after delivery were controlled for deriving the odds ratios (ORs) describing postpartum depression to mother-infant bonding.Results: EPDS Total Score crude ORs and adjusted ORs against the MIBS-J Total Score at 1-month and 6-month after delivery were calculated. Crude ORs were 1.111 (95% CI 1.110–1.112) and 1.122 (95% CI 1.121–1.124) respectively. In the fully adjusted model, ORs were 1.088 (95% CI 1.086–1.089) and 1.085 (95% CI 1.083–1.087), respectively.Conclusions: This study demonstrated prospectively, in a large-scale cohort, that depression at multiple postpartum points, including associations with each EPDS and MIBS-J factors, may be a robust predictor of mother-infant bonding failure 1-year after birth.