Faculty Bibliography

RATIONALE/BACKGROUND:Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. OBJECTIVES/OBJECTIVE:In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. METHODS:Regionally-resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. RESULTS:Effect estimates, and associated uncertainties, varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1-1.1% per 1 degree C) was estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel, and include: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socio-economic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. CONCLUSIONS:This work provides an example for how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Importance/UNASSIGNED:There is limited evaluation of the performance of Medicaid managed care (MMC) private plans in covering substance use disorder (SUD) treatment. Objective/UNASSIGNED:To compare the performance of MMC plans across 19 indicators of access, quality, and outcomes of SUD treatment. Design Setting and Participants/UNASSIGNED:This cross-sectional study used administrative claims and mandatory assignment to plans of up to 159 016 adult Medicaid recipients residing in 1 of the 5 counties (boroughs) of New York, New York, from January 2009 to December 2017 to identify differences in SUD treatment access, patterns, and outcomes among different types of MMC plans. Data from the latest years were received from the New York State Department of Health in October 2019, and analysis began soon thereafter. Approximately 17% did not make an active choice of plan, and a subset of these (approximately 4%) can be regarded as randomly assigned. Exposures/UNASSIGNED:Plan assignment. Main Outcomes and Measures/UNASSIGNED:Percentage of the enrollees achieving performance measures across 19 indicators of access, process, and outcomes of SUD treatment. Results/UNASSIGNED:Medicaid claims data from 159 016 adults (mean [SD] age, 35.9 [12.7] years; 74 261 women [46.7%]; 8746 [5.5%] Asian, 73 783 [46.4%] Black, and 40 549 [25.5%] White individuals) who were auto assigned to an MMC plan were analyzed. Consistent with national patterns, all plans achieved less than 50% (range, 0%-62.1%) on most performance measures. Across all plans, there were low levels of treatment engagement for alcohol (range, 0%-0.4%) and tobacco treatment (range, 0.8%-7.2%), except for engagement for opioid disorder treatment (range, 41.5%-61.4%). For access measures, 4 of the 9 plans performed significantly higher than the mean on recognition of an SUD diagnosis, any service use for the first time, and tobacco use screening. Of the process measures, total monthly expenditures on SUD treatment was the only measure for which plans differed significantly from the mean. Outcome measures differed little across plans. Conclusions and Relevance/UNASSIGNED:The results of this cross-sectional study suggest the need for progress in engaging patients in SUD treatment and improvement in the low performance of SUD care and limited variation in MMC plans in New York, New York. Improvement in the overall performance of SUD treatment in Medicaid potentially depends on general program improvements, not moving recipients among plans.

In October 2021 the Food and Drug Administration released draft rules creating a new class of hearing aids to be sold over the counter. Since Medicare does not cover hearing aids, the ready availability of low-cost aids is potentially good news for the millions of older Americans with hearing loss, a disorder that is associated with isolation, depression and poor health. However, better financial access to hearing aids will not necessarily translate into better hearing: many older people will need assistance in fitting, using and maintaining their aids. Policymakers, managers, and clinicians need to consider how to structure, fund and deliver these vital adjunctive services.

Increased study and methodological innovation have led to growth in the field of fetal brain fMRI. An important gap yet to be addressed is optimization of fetal fMRI preprocessing. Rapid developmental changes, imaged within the maternal compartment using an abdominal coil, introduce novel constraints that challenge established methods used in adult fMRI. This study evaluates the impact of (1) normalization to a group mean-age template versus normalization to an age-matched template; (2) independent components analysis (ICA) denoising at two criterion thresholds; and (3) smoothing using three kernel sizes. Data were collected from 121 fetuses (25-39 weeks, 43.8% female). Results indicate that the mean age template is superior in older fetuses, but less optimal in younger fetuses. ICA denoising at a more stringent threshold is superior to less stringent denoising. A larger smoothing kernel can enhance cross-hemisphere functional connectivity. Overall, this study provides improved understanding of the impact of specific steps on fetal image quality. Findings can be used to inform a common set of best practices for fetal fMRI preprocessing.

INTRODUCTION/UNASSIGNED:Coffee is one of the most frequently consumed beverages worldwide and has been found to have a wide assortment of health benefits. Although habitual coffee consumption is associated with a lower incidence of chronic kidney disease, an association between coffee and acute kidney injury (AKI) has not yet been revealed. METHODS/UNASSIGNED:In the Atherosclerosis Risk in Communities (ARIC) Study, a prospective cohort study of 14,207 adults aged 45 to 64 years, coffee consumption (cups/d) was assessed at a single visit via food frequency questionnaires and compared with incident AKI defined by hospitalization with an AKI-related International Classification of Diseases code. RESULTS/UNASSIGNED: = 0.02). CONCLUSION/UNASSIGNED:Higher coffee intake was associated with a lower risk of incident AKI and could present an opportunity for cardiorenal protection through diet. Further evaluation of the physiological mechanisms underlying the cardiorenal protective effects of coffee consumption is necessary.

Despite recent advances in algorithmic fairness, methodologies for achieving fairness with generalized linear models (GLMs) have yet to be explored in general, despite GLMs being widely used in practice. In this paper we introduce two fairness criteria for GLMs based on equalizing expected outcomes or log-likelihoods. We prove that for GLMs both criteria can be achieved via a convex penalty term based solely on the linear components of the GLM, thus permitting efficient optimization. We also derive theoretical properties for the resulting fair GLM estimator. To empirically demonstrate the efficacy of the proposed fair GLM, we compare it with other wellknown fair prediction methods on an extensive set of benchmark datasets for binary classification and regression. In addition, we demonstrate that the fair GLM can generate fair predictions for a range of response variables, other than binary and continuous outcomes.

BACKGROUND/OBJECTIVES/OBJECTIVE:Excessive gestational weight gain (GWG) and pre-pregnancy obesity affect a significant portion of the US pregnant population and are linked with negative maternal and child health outcomes. The objective of this study was to explore associations of pre-pregnancy body mass index (pBMI) and GWG with longitudinally measured maternal urinary metabolites throughout pregnancy. SUBJECTS/METHODS/METHODS:Among 652 participants in the New York University Children's Health and Environment Study, a longitudinal pregnancy cohort, targeted metabolomics were measured in serially collected urine samples throughout pregnancy. Metabolites were measured at median 10 (T1), 21 (T2), and 29 (T3) weeks gestation using the Biocrates AbsoluteIDQ® p180 Urine Extension kit. Acylcarnitine, amino acid, biogenic amine, phosphatidylcholine, lysophosphatidylcholine, sphingolipid, and sugar levels were quantified. Pregnant people 18 years or older, without type 1 or 2 diabetes and with singleton live births and valid pBMI and metabolomics data were included. GWG and pBMI were calculated using weight and height data obtained from electronic health records. Linear mixed effects models with interactions with time were fit to determine the gestational age-specific associations of categorical pBMI and continuous interval-specific GWG with urinary metabolites. All analyses were corrected for false discovery rate. RESULTS:Participants with obesity had lower long-chain acylcarnitine levels throughout pregnancy and lower phosphatidylcholine and glucogenic amino acids and higher phenylethylamine concentrations in T2 and T3 compared with participants with normal/underweight pBMI. GWG was associated with taurine in T2 and T3 and C5 acylcarnitine species, C5:1, C5-DC, and C5-M-DC, in T2. CONCLUSIONS:pBMI and GWG were associated with the metabolic environment of pregnant individuals, particularly in relation to mid-pregnancy. These results highlight the importance of both preconception and prenatal maternal health.