The association of state percent uninsured and the likelihood of low birth weight: evidence from the 2016-2019 Pregnancy Risk Assessment Monitoring System.

OBJECTIVE: To evaluate the association of state-level lack of health insurance among women of reproductive age with variation in state low birth weight (LBW) rates. STUDY DESIGN: This cross-section study analyzes data from the 2016-2019 Pregnancy Risk Assessment Monitoring Survey for respondents with singleton, live births. METHODS: Respondents were divided into groups by state-level percent of uninsured women aged 19-44 years. Poisson regression was used to model the association between state percent uninsured and likelihood of LBW, controlling for individual sociodemographic and clinical risk factors. Sensitivity analyses were done for Medicaid and non-Hispanic Black subpopulations and alternative state characteristics, including Gini coefficients, total and public welfare expenditures, and state reproductive rights rankings. RESULTS: In adjusted multiple regression analyses, compared to respondents from states with <7% uninsured, respondents from states with 7% or more uninsured had an increased risk of LBW status (7-8.99% uninsured: adjusted incidence rate ratio [aIRR] 1.11, 95% confidence interval [CI] 1.04-1.18; 9-11.99% uninsured: aIRR 1.09, 95% CI 1.02-1.17; >11.99% uninsured: aIRR 1.15, 95% CI 1.08-1.22). However, there was no evident dose-response gradient. Sensitivity analyses produced virtually identical findings for subpopulations, and no other state characteristics were significant. CONCLUSION: States with the highest level of insurance coverage had a significantly lower LBW rate than other states. However, there was little evidence for greater odds of LBW with the highest levels of uninsured. Individual risk factors dominated LBW models, while state differences in income inequality, reproductive health policy, and per capita spending explained little of the variance in LBW.

Magma Degassing as a Source of Long-Term Seismicity at Volcanoes: The Ischia Island (Italy) Case.

Transient seismicity at active volcanoes poses a significant risk in addition to eruptive activity. This risk is powered by the common belief that volcanic seismicity cannot be forecast, even on a long term. Here we investigate the nature of volcanic seismicity to try to improve our forecasting capacity. To this aim, we consider Ischia volcano (Italy), which suffered similar earthquakes along its uplifted resurgent block. We show that this seismicity marks an acceleration of decades-long subsidence of the resurgent block, driven by degassing of magma that previously produced the uplift, a process not observed at other volcanoes. Degassing will continue for hundreds to thousands of years, causing protracted seismicity and will likely be accompanied by moderate and damaging earthquakes. The possibility to constrain the future duration of seismicity at Ischia indicates that our capacity to forecast earthquakes might be enhanced when seismic activity results from long-term magmatic processes, such as degassing.

Shallow slip amplification and enhanced tsunami hazard unravelled by dynamic simulations of mega-thrust earthquakes.

The 2011 Tohoku earthquake produced an unexpected large amount of shallow slip greatly contributing to the ensuing tsunami. How frequent are such events? How can they be efficiently modelled for tsunami hazard? Stochastic slip models, which can be computed rapidly, are used to explore the natural slip variability; however, they generally do not deal specifically with shallow slip features. We study the systematic depth-dependence of slip along a thrust fault with a number of 2D dynamic simulations using stochastic shear stress distributions and a geometry based on the cross section of the Tohoku fault. We obtain a probability density for the slip distribution, which varies both with depth, earthquake size and whether the rupture breaks the surface. We propose a method to modify stochastic slip distributions according to this dynamically-derived probability distribution. This method may be efficiently applied to produce large numbers of heterogeneous slip distributions for probabilistic tsunami hazard analysis. Using numerous M9 earthquake scenarios, we demonstrate that incorporating the dynamically-derived probability distribution does enhance the conditional probability of exceedance of maximum estimated tsunami wave heights along the Japanese coast. This technique for integrating dynamic features in stochastic models can be extended to any subduction zone and faulting style.

Structural control on the Tohoku earthquake rupture process investigated by 3D FEM, tsunami and geodetic data.

The 2011 Tohoku earthquake (Mw = 9.1) highlighted previously unobserved features for megathrust events, such as the large slip in a relatively limited area and the shallow rupture propagation. We use a Finite Element Model (FEM), taking into account the 3D geometrical and structural complexities up to the trench zone, and perform a joint inversion of tsunami and geodetic data to retrieve the earthquake slip distribution. We obtain a close spatial correlation between the main deep slip patch and the local seismic velocity anomalies, and large shallow slip extending also to the North coherently with a seismically observed low-frequency radiation. These observations suggest that the friction controlled the rupture, initially confining the deeper rupture and then driving its propagation up to the trench, where it spreads laterally. These findings are relevant to earthquake and tsunami hazard assessment because they may help to detect regions likely prone to rupture along the megathrust, and to constrain the probability of high slip near the trench. Our estimate of ~40 m slip value around the JFAST (Japan Trench Fast Drilling Project) drilling zone contributes to constrain the dynamic shear stress and friction coefficient of the fault obtained by temperature measurements to ~0.68 MPa and ~0.10, respectively.