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      Associations between Residential Proximity to Oil and Gas Drilling and Term Birth Weight and Small-for-Gestational-Age Infants in Texas: A Difference-in-Differences Analysis

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          Abstract

          <div class="section"> <a class="named-anchor" id="d111170e197"> <!-- named anchor --> </a> <h5 class="section-title" id="d111170e198">Background:</h5> <p id="d111170e200">Oil and natural gas extraction may produce environmental pollution at levels that affect reproductive health of nearby populations. Available studies have primarily focused on unconventional gas drilling and have not accounted for local population changes that can coincide with drilling activity. </p> </div><div class="section"> <a class="named-anchor" id="d111170e202"> <!-- named anchor --> </a> <h5 class="section-title" id="d111170e203">Objective:</h5> <p id="d111170e205">Our study sought to examine associations between residential proximity to oil and gas drilling and adverse term birth outcomes using a difference-in-differences study design. </p> </div><div class="section"> <a class="named-anchor" id="d111170e207"> <!-- named anchor --> </a> <h5 class="section-title" id="d111170e208">Methods:</h5> <p id="d111170e210">We created a retrospective population-based term birth cohort in Texas between 1996 and 2009 composed of mother–infant dyads ( <span class="inline-formula"> <math id="i1" overflow="scroll"> <mrow> <mi>n</mi> <mo>=</mo> <mn>2,598,025</mn> </mrow> </math> </span>) living <span class="inline-formula"> <math id="i2" overflow="scroll"> <mrow> <mo>&lt;</mo> <mn>10</mn> <mspace width="0.3em"/> <mi mathvariant="normal">km</mi> </mrow> </math> </span> from an oil or gas site. We implemented a difference-in-differences approach to estimate associations between drilling activities and infant health: term birth weight and term small for gestational age (SGA). Using linear and logistic regression, we modeled interactions between births before (unexposed) or during (exposed) drilling activity and residential proximity near (0–1, 1–2, or <span class="inline-formula"> <math id="i3" overflow="scroll"> <mrow> <mn>2</mn> <mo>–</mo> <mn>3</mn> <mspace width="0.3em"/> <mi mathvariant="normal">km</mi> </mrow> </math> </span>) or far ( <span class="inline-formula"> <math id="i4" overflow="scroll"> <mrow> <mn>3</mn> <mo>–</mo> <mn>10</mn> <mspace width="0.3em"/> <mi mathvariant="normal">km</mi> </mrow> </math> </span>) from an active or future drilling site, adjusting for individual- and neighborhood-level characteristics. </p> </div><div class="section"> <a class="named-anchor" id="d111170e259"> <!-- named anchor --> </a> <h5 class="section-title" id="d111170e260">Results:</h5> <p id="d111170e262">The adjusted mean difference in term birth weight for mothers living 0–1 vs. <span class="inline-formula"> <math id="i5" overflow="scroll"> <mrow> <mn>3</mn> <mo>–</mo> <mn>10</mn> <mspace width="0.3em"/> <mi mathvariant="normal">km</mi> </mrow> </math> </span> from a current or future drilling site was <span class="inline-formula"> <math id="i6" overflow="scroll"> <mrow> <mo>–</mo> <mn>7.3</mn> <mspace width="0.3em"/> <mi mathvariant="normal">g</mi> </mrow> </math> </span> [95% confidence interval (CI): <span class="inline-formula"> <math id="i7" overflow="scroll"> <mrow> <mo>–</mo> <mn>11.6</mn> </mrow> </math> </span>, <span class="inline-formula"> <math id="i8" overflow="scroll"> <mrow> <mo>–</mo> <mn>3.0</mn> </mrow> </math> </span>] for births during active vs. future drilling. The corresponding adjusted odds ratio for SGA was 1.02 (95% CI: 0.98, 1.06). Negative associations with term birth weight were observed for the 1–2 and <span class="inline-formula"> <math id="i9" overflow="scroll"> <mrow> <mn>2</mn> <mo>–</mo> <mn>3</mn> <mspace width="0.3em"/> <mi mathvariant="normal">km</mi> </mrow> </math> </span> near groups, and no consistent differences were identified by type of drilling activity. Larger, though imprecise, adverse associations were found for infants born to Hispanic women, women with the lowest educational attainment, and women living in cities. </p> </div><div class="section"> <a class="named-anchor" id="d111170e317"> <!-- named anchor --> </a> <h5 class="section-title" id="d111170e318">Conclusions:</h5> <p id="d111170e320">Residing near oil and gas drilling sites during pregnancy was associated with a small reduction in term birth weight but not SGA, with some evidence of environmental injustices. Additional work is needed to investigate specific drilling-related exposures that might explain these associations. <a data-untrusted="" href="https://doi.org/10.1289/EHP7678" id="d111170e322" target="xrefwindow">https://doi.org/10.1289/EHP7678</a> </p> </div>

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          Most cited references58

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          Designing Difference in Difference Studies: Best Practices for Public Health Policy Research

          The difference in difference (DID) design is a quasi-experimental research design that researchers often use to study causal relationships in public health settings where randomized controlled trials (RCTs) are infeasible or unethical. However, causal inference poses many challenges in DID designs. In this article, we review key features of DID designs with an emphasis on public health policy research. Contemporary researchers should take an active approach to the design of DID studies, seeking to construct comparison groups, sensitivity analyses, and robustness checks that help validate the method's assumptions. We explain the key assumptions of the design and discuss analytic tactics, supplementary analysis, and approaches to statistical inference that are often important in applied research. The DID design is not a perfect substitute for randomized experiments, but it often represents a feasible way to learn about casual relationships. We conclude by noting that combining elements from multiple quasi-experimental techniques may be important in the next wave of innovations to the DID approach.
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            Semiparametric Difference-in-Differences Estimators

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              Ambient air pollution, birth weight and preterm birth: a systematic review and meta-analysis.

              Low birth weight and preterm birth have a substantial public health impact. Studies examining their association with outdoor air pollution were identified using searches of bibliographic databases and reference lists of relevant papers. Pooled estimates of effect were calculated, heterogeneity was quantified, meta-regression was conducted and publication bias was examined. Sixty-two studies met the inclusion criteria. The majority of studies reported reduced birth weight and increased odds of low birth weight in relation to exposure to carbon monoxide (CO), nitrogen dioxide (NO(2)) and particulate matter less than 10 and 2.5 microns (PM(10) and PM(2.5)). Effect estimates based on entire pregnancy exposure were generally largest. Pooled estimates of decrease in birth weight ranged from 11.4 g (95% confidence interval -6.9-29.7) per 1 ppm CO to 28.1g (11.5-44.8) per 20 ppb NO(2), and pooled odds ratios for low birth weight ranged from 1.05 (0.99-1.12) per 10 μg/m(3) PM(2.5) to 1.10 (1.05-1.15) per 20 μg/m(3) PM(10) based on entire pregnancy exposure. Fewer effect estimates were available for preterm birth and results were mixed. Pooled odds ratios based on 3rd trimester exposures were generally most precise, ranging from 1.04 (1.02-1.06) per 1 ppm CO to 1.06 (1.03-1.11) per 20 μg/m(3) PM(10). Results were less consistent for ozone and sulfur dioxide for all outcomes. Heterogeneity between studies varied widely between pollutants and outcomes, and meta-regression suggested that heterogeneity could be partially explained by methodological differences between studies. While there is a large evidence base which is indicative of associations between CO, NO(2), PM and pregnancy outcome, variation in effects by exposure period and sources of heterogeneity between studies should be further explored. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Environmental Health Perspectives
                Environ Health Perspect
                Environmental Health Perspectives
                0091-6765
                1552-9924
                July 2021
                July 2021
                : 129
                : 7
                : 077002
                Affiliations
                [1 ]School of Biological and Population Health Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA
                [2 ]Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts, USA
                [3 ]Department of Public Health Sciences, School of Medicine and Dentistry, University of Rochester, Rochester, New York, USA
                [4 ]Rochester Data Science Consortium, Rochester, New York, USA
                Article
                10.1289/EHP7678
                3c73f344-46db-4f0f-9487-53c84c3be8fe
                © 2021
                History

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