Relationship between metabolic and anthropometric maternal parameters and the fetal autonomic nervous system

Pre-pregnancy obesity, defined as a body mass index (BMI) greater than or equal to 30 kg/m2, can have adverse effects on the health of newborns and can also lead to metabolic, cardiovascular and neurological diseases in the offspring as they grow older. In the area of fetal origins and disease in adult life, a large number of studies have reported a critical role for maternal weight and metabolism before or during gestation in shaping the health of their offspring. Maternal obesity is recognised as a major modifiable contributor to obesity and metabolic syndrome in offspring, but the underlying factors remain unclear. The fetal autonomic nervous system (ANS) is subject to programming during developmental periods and is considered one of the processes by which early programming of disease can take place. The main goal of the present work was to use the fetal heart rate (HR) and heart rate variability (HRV) as proxies for the fetal ANS to study the effects of metabolic and anthropometric maternal (MAM) parameters before and during gestation on the fetuses of healthy, normoglycemic mothers. A total of 184 women in their second/third trimesters of uncomplicated pregnancies were included in this study. Pre-pregnancy BMI and maternal weight gain during pregnancy were recorded. In a subsample (n = 104), maternal insulin sensitivity was measured during an oral glucose tolerance test. Fetal HR and HRV were determined by magnetic recording in all subjects. The influence of pre-pregnancy BMI, maternal weight gain and maternal insulin sensitivity on fetal HR and HRV was evaluated. Associations between MAM parameters and maternal HR and HRV were also assessed. ANCOVA, partial correlation and mediation analysis were applied, all of which were adjusted for gestational age, gender and parity. A regression on fetal HR using a machine learning approach was tested to explore which maternal factor is the driving factor programming the fetal ANS. Four models were tested: Linear regression, Regression Tree, Support Vector Machine and Random Forest. The fetal HR was higher in fetuses of mothers with high pre-pregnancy BMI (overweight/obese) than in mothers with normal weight. The fetal HRV was lower in mothers with high weight gain than in mothers with normal weight gain. The fetal HR was negatively correlated with maternal weight gain and maternal insulin sensitivity. Pre-pregnancy BMI was positively correlated with fetal high frequency and negatively correlated with low frequency and the low to high frequency ratio. Maternal weight gain was associated indirectly with birth weight through fetal HR, while maternal insulin sensitivity was associated with fetal HR through fetal HRV. Separately, fetal HRV was associated with birth weight through the fetal HR. The Random Forest ensemble tree-based model outperformed linear regression as the fetal HR regression model. Fetal HR can be predicted using the following nine relevant variables (sorted from the most important to the least important): pre-pregnancy BMI, gender, maternal fasting insulin, maternal insulin sensitivity, gravidity, maternal age, maternal fasting glucose, gestational age and maternal weight gain. Pre-pregnancy BMI appeared to be the major factor predicting fetal HR. In conclusion, the fetal ANS is sensitive to maternal metabolic and anthropometric influences, and particularly maternal weight before pregnancy. These findings support the concept of the “Developmental Origin of Health and Disease” and increase our knowledge about the importance of the intrauterine environment in the programming of the ANS and the possible programming of disease in later life

Physicians Treating Physicians: Information and Incentives in Childbirth

This paper provides new evidence on the interaction between patient information and physician financial incentives. Using rich microdata on childbirth, we compare the treatment of physicians when they are patients with that of comparable nonphysicians. We also exploit the presence of HMO-owned hospitals to determine how the treatment gap varies with providers' financial incentives. Consistent with induced demand, physicians are approximately 10 percent less likely to receive a C-section, with only a quarter of this effect attributable to differential sorting. While financial incentives affect the treatment of nonphysicians, physician-patients are largely unaffected. Physicians also have better health outcomes. (JEL D83, I11, J16, J44

From the Cradle to the Labor Market? The Effect of Birth Weight on Adult Outcomes

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Inside the War on Poverty: The Impact of Food Stamps on Birth Outcomes

This paper evaluates the health impact of a signature initiative of the War on Poverty: the roll out of the modern Food Stamp Program (FSP) during the 1960s and early 1970s. Using variation in the month the FSP began operating in each U.S. county, we find that pregnancies exposed to the FSP three months prior to birth yielded deliveries with increased birth weight, with the largest gains at the lowest birth weights. These impacts are evident with difference-in-difference models and event study analyses. Estimated impacts are robust to inclusion of county fixed effects, time fixed effects, measures of other federal transfer spending, state by year fixed effects, and county-specific linear time trends. We also find that the FSP rollout leads to small, but statistically insignificant, improvements in neonatal infant mortality. We conclude that the sizeable increase in income from Food Stamp benefits improved birth outcomes for both whites and African Americans, with larger impacts for births to African American mothers.

Human Health Engineering Volume II

In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being

Ultrasound image processing in the evaluation of labor induction failure risk

Labor induction is defined as the artificial stimulation of uterine contractions for the purpose of vaginal birth. Induction is prescribed for medical and elective reasons. Success in labor induction procedures is related to vaginal delivery. Cesarean section is one of the potential risks of labor induction as it occurs in about 20% of the inductions. A ripe cervix (soft and distensible) is needed for a successful labor. During the ripening cervical, tissues experience micro structural changes: collagen becomes disorganized and water content increases. These changes will affect the interaction between cervical tissues and sound waves during ultrasound transvaginal scanning and will be perceived as gray level intensity variations in the echographic image. Texture analysis can be used to analyze these variations and provide a means to evaluate cervical ripening in a non-invasive way

Proceedings of the International Workshop on 'Combined Environmental Exposure: Noise, Air Pollutants and Chemicals'

The issue of combined exposure to noise, air pollution and chemicals has raised recently the interest of several bodies of the European Commission such as DG Environment, DG SANCO and DG Research in the context of the EC 7th Framework Programme. There are open questions whether prevailing environmental concentrations of air pollutants and chemicals can lead to ototoxic health impacts. Therefore this issue needs to be thoroughly explored and investigated to help the EC to revise the existing standards and guidelines concerning combined exposure to noise, air pollutants and chemicals. The aim of the workshop was to review and discuss the existing scientific evidence whether prevailing environmental exposures to single and concomitant agents together with noise could lead to ototoxic or other health impacts. The final aim was to identify the research needs and to give recommendations for research and policy making in the EU level. It was agreed that research in the future should be focused on really established combinations (high correlations) and interactions (known effect) with main perspective on the traffic bundle of exposure. It was also discussed and agreed upon that the best knowledge exists on the health effects due to combined exposure to noise and solvents or heavy metals in occupational environments, especially on most of the auditory and non-auditory effects. Possible factors that may have confounding or aggravating effects on the results of noise studies were identified. Such factors are: age, gender, smoking, obesity, alcohol, socio-economic status, occupation, education, family status, active military, experience, hereditary disease, medication, medical status, race and ethnicity, physical activity, noisy leisure activities, stress reducing activities, diet & nutrition, housing condition (crowding), and residential status. Research priorities and recommendations for the future. The highest priority was given to issues related to research on noise and outdoor air pollutants. This is due to the fact that it may concern the largest population compared to the other stressors in this analysis and there is some evidence of serious health outcomes such as cardiovascular effects. The next priority was given to the research on the effects of noise and solvents in occupational settings and to research on noise and organophosphates. In the future research, priority should be given to: 1. evaluation of existing data collections whether re-analyses are possible with respect to combined exposure from traffic sources (road, rail and air), 2. analyses of existing data concerning noise and other stressors interactions in both occupational and environmental settings, 3. detailed assessment of combined exposures to noise, vibrations and PM, CO, NOx, and VOCs with specific studies in urban areas and, especially, cardiovascular health endpoints should be studied as priority health endpoints, 4. identification of causal mechanisms through careful review of toxicological experimental studies.JRC.I.5-Physical and chemical exposure

Causal Inference from Statistical Data

The so-called kernel-based tests of independence are developed for automatic causal discovery between random variables from purely observational statistical data, i.e., without intervention. Beyond the independence relations, the complexity of conditional distriubtions is used as an additional inference principle of determining the causal ordering between variables. Experiments with simulated and real-world data show that the proposed methods surpass the state-of-the-art approaches