Invited Perspective: Oil and Gas Development and Adverse Birth Outcomes: What More Do We Need to Know?

This issue of Environmental Health Perspectives presents a new epidemiological study supporting a link between oil and gas extraction and lower term birth weight. The analysis by Willis et al. (2021) is a large ( births), retrospective, registry-based study in Texas that uses a difference-in-difference quasi-experimental design. Based on their primary model, the authors estimated that living within of an oil or gas drilling site (based on maternal residence at birth) was associated with a small reduction of (95% confidence interval: , ) in term birth weight. Associations were more pronounced among Hispanic women (vs. non-Hispanic White women), women with lower educational attainment, and women who lived in metropolitan areas.

A distinguishing aspect of the study by Willis et al. (2021) is the application of a difference-in-differences research design, an approach used to explore causal relationships where randomized controlled trials are not possible (Wing et al. 2018). With this study design, the reported associations were based on both the difference during vs. prior to drilling activity and living near vs. further from an oil or gas well site. The difference-in-differences approach accounts for temporal trends that may coincide with but are not directly related to the oil and gas drilling exposures of interest, thereby providing some control for unmeasured confounders, including potentially positive socioeconomic changes. Oil and gas drilling activities can produce numerous environmental hazards that could influence maternal and fetal health, such as toxic air emissions, water contamination, and noise (Adgate et al. 2014; Hays and Shonkoff 2016). Potential local and societal benefits also with relevance to health include increases in employment (e.g., oil and gas industry, food service industry, truck driving), increases in wages, increases in income for residents leasing their land or mineral rights, increases in revenues for local governments, and reductions in emissions of toxic chemicals and greenhouse gases from the replacement of coal with natural gas as an energy source (Marchand and Weber 2018; Sovacool 2014). However, there is ongoing debate about the magnitude, scale, and duration of these societal benefits and evidence that they are not distributed or perceived equally (Clarke et al. 2016; Kroepsch et al. 2019; Krupnick and Echarte 2017; Ravikumar and Brandt 2017).

The registry-based aspect of the study by Willis et al. enabled evaluation of a large and racially/ethnically diverse study population with a low probability of the selection bias that may occur with approaches requiring participant enrollment. One limitation is the reliance on data available in birth records, prompting use of single address at the time of birth to assign exposure, which could introduce exposure misclassification due to unaccounted residential mobility (Lupo et al. 2010; Warren et al. 2018), and limited information on individual-level confounders and paternal characteristics.

The study by Willis et al. adds to a mounting body of evidence, with studies in California, Colorado, Oklahoma, Pennsylvania, Texas, and British Columbia documenting increased risk of adverse birth outcomes (e.g., low birth weight, preterm birth, congenital anomalies) in relation to residential proximity to oil and natural gas drilling, although studies have not been entirely consistent across end points (reviewed in Deziel et al. 2020). Associations have also been reported for other adverse health outcomes in both children and adults, such as increased asthma exacerbations and childhood cancers, with the majority of approximately 50 publications to date pointing to increased health problems with increasing exposure to oil and gas drilling sites and activities.

Given the findings from these numerous studies, what research questions require further investigation?

. Willis et al. point to one important knowledge gap with their statement that “Additional work is needed to investigate specific drilling-related exposures that might explain these associations.” Epidemiological studies to date have generally relied on models and metrics that capture proximity and density of oil and gas wells. These spatial surrogates have several strengths. First, they are feasible to construct for large populations because they can be calculated largely with available data and do not require participant contact. Second, they are particularly useful for retrospective studies because they also allow assessment of exposures during specific temporal windows, such as the different phases of oil and gas development (e.g., drilling, production) or different windows of vulnerability (e.g., trimesters). Third, these surrogates serve as an aggregate measure of the myriad of physical, chemical, and social stressors potentially associated with oil and gas development, a useful feature for this complex industrial process where exposures to multiple hazards are likely and the dominant stressor is not known. Finally, the relatively simple proximity metrics are directly relevant for certain policy measures, such as the establishment of setbacks or the minimum allowable distance between an oil or gas well and sensitive human receptors (e.g., residences, schools, hospitals).

Although these metrics have great utility, spatial surrogates do not allow for identification of etiologic agents underlying an observed association, as Willis et al. acknowledge. Additionally, the metrics assume exposures decrease in a predictable way around an oil and gas well pad and do not account for the complexities of the fate and transport of environmental chemicals, such as breakdown products and directional dispersion. Moreover, only a few studies have compared these metrics and models to environmental measurements (e.g., Allshouse et al. 2017; Elliott et al. 2018), and therefore we understand very little about their ability to capture exposure-specific agents. These limitations likely introduce exposure misclassification into epidemiological analyses, which would be expected to attenuate observed associations and potentially contribute to inconsistencies across studies.

Increasing the accuracy and specificity of current commonly used exposure models and metrics could have the power to illuminate causal mechanisms, reduce exposure misclassification, direct new monitoring efforts, and inform exposure mitigation strategies. Advancements have been made toward developing more specific metrics, including models to capture the practice of flaring (Franklin et al. 2019), radioactivity (Li et al. 2020), drinking water vulnerability (Soriano et al. 2020), and oil and gas infrastructure other than well pads (Koehler et al. 2018); more such research is needed.

. Studies in different populations, states, countries, and regions provide information about the consistency of associations with respect to differences in industry practices, regulations, formation characteristics, and time. In addition to replication being a critical component of causal inference in epidemiology, policy makers rely on results from their own state or municipality to inform local policies. Additionally, we need more studies of the potential disproportionate environmental health impacts on different populations with regard to race, ethnicity, socioeconomic vulnerability, and urbanity/rurality, because certain subgroups may experience more pronounced responses due to greater cumulative burdens of multiple socioenvironmental stressors (Kroepsch et al. 2019; Payne-Sturges et al. 2021). The need for additional environmental justice-focused analyses is supported by findings from Willis et al. and by a study of birth outcomes and flaring from oil and gas wells in the Eagle Ford Shale of Texas that reported that adverse effects appeared to be disproportionately borne by Hispanic women (Cushing et al. 2020).

The new study by Willis et al. provides additional evidence supporting adverse effects of oil and gas extraction on neonatal health. Although more specific exposure assessments would add rigor to epidemiological studies, these methodological uncertainties need not be used as a barrier to implementing public health protections. The current evidence supports the urgent need for policies to mitigate oil- and gas-related impacts.