Single awakening salivary measurements provide reliable estimates of morning cortisol levels in pregnant women

A rapid, non-invasive method for fatigue detection based on voice information

Fatigue results from a series of physiological and psychological changes due to continuous energy consumption. It can affect the physiological states of operators, thereby reducing their labor capacity. Fatigue can also reduce efficiency and, in serious cases, cause severe accidents. In addition, it can trigger pathological-related changes. By establishing appropriate methods to closely monitor the fatigue status of personnel and relieve the fatigue on time, operation-related injuries can be reduced. Existing fatigue detection methods mostly include subjective methods, such as fatigue scales, or those involving the use of professional instruments, which are more demanding for operators and cannot detect fatigue levels in real time. Speech contains information that can be used as acoustic biomarkers to monitor physiological and psychological statuses. In this study, we constructed a fatigue model based on the method of sleep deprivation by collecting various physiological indexes, such as P300 and glucocorticoid level in saliva, as well as fatigue questionnaires filled by 15 participants under different fatigue procedures and graded the fatigue levels accordingly. We then extracted the speech features at different instances and constructed a model to match the speech features and the degree of fatigue using a machine learning algorithm. Thus, we established a method to rapidly judge the degree of fatigue based on speech. The accuracy of the judgment based on unitary voice could reach 94%, whereas that based on long speech could reach 81%. Our fatigue detection method based on acoustic information can easily and rapidly determine the fatigue levels of the participants. This method can operate in real time and is non-invasive and efficient. Moreover, it can be combined with the advantages of information technology and big data to expand its applicability.

Associations between maternal awakening salivary cortisol levels in mid-pregnancy and adverse birth outcomes

PURPOSE

Elevated levels of maternal cortisol have been hypothesized as the intermediate process between symptoms of depression and psychosocial stress during pregnancy and adverse birth outcomes. Therefore, we examined associations between cortisol levels in the second trimester of pregnancy and risks of three common birth outcomes in a nested case-control study.

METHODS

This study was embedded in the PRIDE Study (n = 3,019), from which we selected all cases with preterm birth (n = 64), low birth weight (n = 49), and small-for-gestational age (SGA; n = 65), and 260 randomly selected controls, among the participants who provided a single awakening saliva sample in approximately gestational week 19 in 2012-2016. Multivariable linear and logistic regression was performed to assess the associations between continuous and categorized cortisol levels and the selected outcomes.

RESULTS

We did not observe any associations between maternal cortisol levels and preterm birth and low birth weight. However, high cortisol levels (≥ 90th percentile) seemed to be associated with SGA (adjusted odds ratio 2.1, 95% confidence interval 0.9-4.8), in particular among girls (adjusted odds ratio 3.7, 95% confidence interval 1.1-11.9, based on eight exposed cases) in an exploratory analysis.

CONCLUSION

The results of this study showed no suggestions of associations between maternal awakening cortisol levels in mid-pregnancy and adverse birth outcomes, except for an increased risk of SGA.

Questionnaires and salivary cortisol to measure stress and depression in mid-pregnancy

The hypothalamic-pituitary-adrenal axis, with cortisol as its final metabolite, has been proposed as a potential underlying biological mechanism for associations between depression and stress symptoms during pregnancy and adverse perinatal outcomes. In this study, we explored associations between salivary cortisol as a potential biomarker for stress and depressive symptoms and several self-completed psychological measurement scales among pregnant women. In total, 652 pregnant women participating in the PRegnancy and Infant DEvelopment (PRIDE) Study completed the Edinburgh Depression Scale (EDS), Patient Health Questionnaire-2 (PHQ-2), Pregnancy-Related Anxiety Questionnaire-Revised (PRAQ-R), and Tilburg Pregnancy Distress Scale (TPDS) and collected a single awakening salivary cortisol sample around gestational week 17. Odds ratios, Spearman’s correlation coefficients (ρ_s) and Cohen’s Kappa coefficients (κ) were calculated to examine the associations between the EDS, PHQ-2, PRAQ-R, TPDS, and maternal cortisol levels. The overall correlation coefficient between the score on the EDS and the salivary cortisol level was 0.01 (p = 0.89) with κ = -0.01 (95% confidence interval [CI] -0.08–0.06). We did not observe agreement between the PHQ-2 and cortisol levels either (κ = 0.06 (95% CI -0.02–0.14)). The results for the PRAQ-R and TPDS were similar with overall correlations with maternal cortisol levels of ρ_s = 0.01 (p = 0.81) and ρ_s = 0.06 (p = 0.35) and agreements of κ = 0.02 (95% CI -0.06–0.09) and κ = -0.02 (95% CI -0.11–0.07), respectively. Maternal awakening salivary cortisol levels and measures of maternal psychological distress, anxiety, depressive symptoms, and pregnancy-related anxiety, assessed by self-completed questionnaires, did not seem to be related in mid-pregnancy.

The PRIDE Study: Evaluation of online methods of data collection

BACKGROUND

Large birth cohort studies are extremely valuable in assessing associations between early life exposures and long-term outcomes. Establishing new birth cohorts is challenging due to declining participation rates. Online methods of data collection may increase feasibility, but have not been evaluated thoroughly.

OBJECTIVE

The primary objective of the ongoing PRegnancy and Infant DEvelopment (PRIDE) Study is to identify exposures during pregnancy and in early life that may affect short-term or long-term health of mother and/or child. In this manuscript, we aimed to evaluate methods of recruitment and online data collection applied.

POPULATION

Dutch women aged ≥18 years in early pregnancy.

DESIGN

Prospective cohort study.

METHODS

Initially, only prenatal care providers recruited participants, but alternative recruitment methods were added as a result of disappointing participation rates, including collaboration with "Moeders voor Moeders" (organisation that visits women in early pregnancy) and Facebook advertisements. Data on demographic characteristics, obstetric history, maternal health, life style factors, occupational exposures, nutrition, pregnancy complications, and infant outcomes are primarily collected through Web-based questionnaires at multiple time points during and after pregnancy. Additional data collection components include paternal questionnaires, blood and saliva sampling, and linkage to medical records.

PRELIMINARY RESULTS

By September 2019, 9573 women were included in the PRIDE Study, of which 1.3% completed paper-based questionnaires. Mean age of the women analysed was 30.6 years, 71.1% had a high level of education, 57.2% were primiparae, and mean gestational age at enrolment was 9.9 (range 3, 37) weeks, with slight differences between recruitment methods. Pregnancy outcome was known for 89.8%. Retention rate at 6 months after the estimated date of delivery was estimated at 70%. Multiple validation studies conducted within the PRIDE Study indicated high data quality.

CONCLUSION(S)

Although challenging and time-consuming, online methods for recruitment and data collection may enable the establishment of new birth cohort studies.