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      Water Fluoridation and Birth Outcomes in California

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          Abstract

          Background:

          There is a lack of research on the relationship between water fluoridation and pregnancy outcomes.

          Objectives:

          We assessed whether hypothetical interventions to reduce fluoride levels would improve birth outcomes in California.

          Methods:

          We linked California birth records from 2000 to 2018 to annual average fluoride levels by community water system. Fluoride levels were collected from consumer confidence reports using publicly available data and public record requests. We estimated the effects of a hypothetical intervention reducing water fluoride levels to 0.7  ppm (the current level recommended by the US Department of Health and Human Services) and 0.5  ppm (below the current recommendation) on birth weight, birth-weight-for-gestational age z-scores, gestational age, preterm birth, small-for-gestational age, large-for-gestational age, and macrosomia using linear regression with natural cubic splines and G-computation. Inference was calculated using a clustered bootstrap with Wald-type confidence intervals. We evaluated race/ethnicity, health insurance type, fetal sex, and arsenic levels as potential effect modifiers.

          Results:

          Fluoride levels ranged from 0 to 2.5  ppm , with a median of 0.51  ppm . There was a small negative association on birth weight with the hypothetical intervention to reduce fluoride levels to 0.7  ppm [ 2.2 g ; 95% confidence interval (CI): 4.4 , 0.0] and to 0.5  ppm ( 5.8 g ; 95% CI: 10.0 , 1.6 ). There were small negative associations with birth-weight-for-gestational-age z-scores for both hypothetical interventions ( 0.7  ppm : 0.004 ; 95% CI: 0.007 , 0.000 and 0.5  ppm : 0.006 ; 95% CI: 0.013 , 0.000). We also observed small negative associations for risk of large-for-gestational age for both the hypothetical interventions to 0.7  ppm [ risk difference  ( RD ) = 0.001 ; 95% CI: 0.002 , 0.000 and 0.5  ppm ( 0.001 ; 95% CI: 0.003 , 0.000)]. We did not observe any associations with preterm birth or with being small for gestational age for either hypothetical intervention. We did not observe any associations with risk of preterm birth or small-for-gestational age for either hypothetical intervention.

          Conclusion:

          We estimated that a reduction in water fluoride levels would modestly decrease birth weight and birth-weight-for-gestational-age z-scores in California. https://doi.org/10.1289/EHP13732

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          Most cited references72

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          Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

          Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma.
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            A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect

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              Implementation of G-computation on a simulated data set: demonstration of a causal inference technique.

              The growing body of work in the epidemiology literature focused on G-computation includes theoretical explanations of the method but very few simulations or examples of application. The small number of G-computation analyses in the epidemiology literature relative to other causal inference approaches may be partially due to a lack of didactic explanations of the method targeted toward an epidemiology audience. The authors provide a step-by-step demonstration of G-computation that is intended to familiarize the reader with this procedure. The authors simulate a data set and then demonstrate both G-computation and traditional regression to draw connections and illustrate contrasts between their implementation and interpretation relative to the truth of the simulation protocol. A marginal structural model is used for effect estimation in the G-computation example. The authors conclude by answering a series of questions to emphasize the key characteristics of causal inference techniques and the G-computation procedure in particular.
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                Author and article information

                Journal
                Environ Health Perspect
                Environ Health Perspect
                EHP
                Environmental Health Perspectives
                Environmental Health Perspectives
                0091-6765
                1552-9924
                16 May 2024
                May 2024
                : 132
                : 5
                : 057004
                Affiliations
                [ 1 ]Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology, and Reproductive Sciences, School of Medicine, University of California, San Francisco , San Francisco, California, USA
                [ 2 ]Emmett Interdisciplinary Program in Environment and Resources, Stanford University , Palo Alto, California, USA
                [ 3 ]Department of Environmental Science, Policy, and Management, University of California, Berkeley , Berkeley, California, USA
                [ 4 ]School of Public Health, University of California, Berkeley , Berkeley, California, USA
                Author notes
                Address correspondence to Dana E. Goin, 480 16th St., San Francisco, CA 94143 USA. Email: dg3369@ 123456cumc.columbia.edu
                Author information
                https://orcid.org/0000-0002-7557-7977
                Article
                EHP13732
                10.1289/EHP13732
                11098007
                38752991
                fa03f914-3e60-424a-94c0-bc0e3f207aab

                EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.

                History
                : 01 August 2023
                : 21 March 2024
                : 22 March 2024
                Categories
                Research

                Public health
                Public health

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