Associations Between Prenatal Exposure to Air Pollution and Congenital Hypothyroidism

Associations between short-term exposure to air pollution and thyroid function in a representative sample of the Korean population

BACKGROUND

Disruption of thyroid function can profoundly affect various organ systems. However, studies on the association between air pollution and thyroid function are relatively scarce and most studies have focused on the long-term effects of air pollution among pregnant women.

OBJECTIVES

This study aimed to explore the associations between short-term exposure to air pollution and thyroid function in the general population.

METHODS

Data from the Korea National Health and Nutrition Examination Survey (2013-2015) were analyzed (n = 5,626). Air pollution concentrations in residential addresses were estimated using Community Multiscale Air Quality models. The moving averages of air pollution over 7 days were set as exposure variables through exploratory analyses. Linear regression and quantile g-computation models were constructed to assess the effects of individual air pollutants and air pollution mixture, respectively.

RESULTS

A 10-ppb increase in NO2 (18.8-μg/m3 increase) and CO (11.5-μg/m3 increase) was associated with 2.43% [95% confidence interval (CI): 0.42, 4.48] and 0.19% (95% CI: 0.01, 0.36) higher thyroid-stimulating hormone (TSH) levels, respectively. A 10-μg/m3 increase in PM2.5 and a 10-ppb increase in O3 (19.6-μg/m3 increment) were associated with 0.87% (95% CI: 1.47, -0.27) and 0.59% (95% CI: 1.18, -0.001) lower free thyroxine (fT4) levels, respectively. A simultaneous quartile increase in PM2.5, NO2, O3, and CO levels was associated with lower fT4 but not TSH levels.

CONCLUSIONS

As the subtle changes in thyroid function can affect various organ systems, the present results may have substantial public health implications despite the relatively modest effect sizes. Because this was a cross-sectional study, it is necessary to conduct further experimental or repeated-measures studies to consolidate the current results.

Associations between OGTT results during pregnancy and offspring TSH levels: a birth cohort study

BACKGROUND

Limited evidence exists regarding the association between gestational diabetes mellitus (GDM) and elevated levels of thyroid-stimulating hormone (TSH) in newborns. Therefore, this study aimed to investigate the potential risk of elevated TSH levels in infants exposed to maternal GDM, considering the type and number of abnormal values obtained from the 75-gram oral glucose tolerance test (OGTT).

METHODS

A population-based, prospective birth cohort study was conducted in Wuhan, China. The study included women who underwent GDM screening using a 75-g OGTT. Neonatal TSH levels were measured via a time-resolved immunofluorescence assay. We estimated and stratified the overall risk (adjusted Risk Ratio [RR]) of elevated TSH levels (defined as TSH > 10 mIU/L or > 20 mIU/L) in offspring based on the type and number of abnormal OGTT values.

RESULTS

Out of 15,236 eligible mother-offspring pairs, 11.5% (1,753) of mothers were diagnosed with GDM. Offspring born to women diagnosed with GDM demonstrated a statistically significant elevation in TSH levels when compared to offspring of non-GDM mothers, with a mean difference of 0.20 [95% CI: 0.04-0.36]. The incidence of elevated TSH levels (TSH > 10 mIU/L) in offspring of non-GDM women was 6.3 per 1,000 live births. Newborns exposed to mothers with three abnormal OGTT values displayed an almost five-fold increased risk of elevated TSH levels (adjusted RR 4.77 [95% CI 1.64-13.96]). Maternal fasting blood glucose was independently and positively correlated with neonatal TSH levels and elevated TSH status (TSH > 20 mIU/L).

CONCLUSIONS

For newborns of women with GDM, personalized risk assessment for elevated TSH levels can be predicated on the type and number of abnormal OGTT values. Furthermore, fasting blood glucose emerges as a critical predictive marker for elevated neonatal TSH status.

Advances in methodologies of negative controls: a scoping review

OBJECTIVES

Negative controls are considered an important tool to mitigate biases in observational studies. The aim of this scoping review was to summarize current methodologies of negative controls (both negative control exposure [NCE] and negative control outcome [NCO]).

STUDY DESIGN AND SETTING

We searched PubMed, Web of Science, Embase, and Cochrane Library (up to March 9, 2023) for articles on methodologies of negative controls. Two reviewers selected eligible studies and collected relevant data independently and in duplicate. We reported total numbers and percentages, and summarized methodologies narratively.

RESULTS

A total of 37 relevant methodological articles were included in our review. These publications covered NCE (n = 11, 29.8%), NCO (n = 13, 35.1%), or both (n = 13, 35.1%), with most focused on bias detection (n = 14, 37.8%), bias correction (n = 16, 43.3%), and P value or confidence interval (CI) calibration (n = 5, 13.5%). For the two remaining articles (5.4%), one discussed bias detection and P value or CI calibration and the other covered all the three functions. For bias detection, the existence of an association between the NCE (NCO) and outcome (exposure) variables of interest simply indicates that results may suffer from confounding bias, selection bias and/or information bias. For bias correction, however, the algorithms of negative control methods need more stringent assumptions such as rank preservation, monotonicity, and linearity.

CONCLUSION

Negative controls can be leveraged for bias detection, P value or CI calibration, and bias correction, among which bias correction has been the most studied methodologically. The current available methods need some stringent assumptions to detect or remove bias. More methodological research is needed to optimize the use of negative controls.

A comprehensive review on endocrine toxicity of gaseous components and particulate matter in smog

Smog is a form of extreme air pollution which comprises of gases such as ozone, sulfur dioxide, nitrogen and carbon oxides, and solid particles including particulate matter (PM2.5 and PM10). Different types of smog include acidic, photochemical, and Polish. Smog and its constituents are hazardaous to human, animals, and plants. Smog leads to plethora of morbidities such as cancer, endocrine disruption, and respiratory and cardiovascular disorders. Smog components alter the activity of various hormones including thyroid, pituitary, gonads and adrenal hormones by altering regulatory genes, oxidation status and the hypothalamus-pituitary axis. Furthermore, these toxicants are responsible for the development of metabolic disorders, teratogenicity, insulin resistance, infertility, and carcinogenicity of endocrine glands. Avoiding fossil fuel, using renewable sources of energy, and limiting gaseous discharge from industries can be helpful to avoid endocrine disruption and other toxicities of smog. This review focuses on the toxic implications of smog and its constituents on endocrine system, their toxicodynamics and preventive measures to avoid hazardous health effects.

"We adjusted for race": now what? A systematic review of utilization and reporting of race in American Journal of Epidemiology and Epidemiology, 2020-2021

Race is a social construct, commonly used in epidemiologic research to adjust for confounding. However, adjustment of race may mask racial disparities, thereby perpetuating structural racism. We conducted a systematic review of articles published in Epidemiology and American Journal of Epidemiology between 2020 and 2021 to (1) understand how race, ethnicity, and similar social constructs were operationalized, used, and reported; and (2) characterize good and poor practices of utilization and reporting of race data on the basis of the extent to which they reveal or mask systemic racism. Original research articles were considered for full review and data extraction if race data were used in the study analysis. We extracted how race was categorized, used-as a descriptor, confounder, or for effect measure modification (EMM)-and reported if the authors discussed racial disparities and systemic bias-related mechanisms responsible for perpetuating the disparities. Of the 561 articles, 299 had race data available and 192 (34.2%) used race data in analyses. Among the 160 US-based studies, 81 different racial categorizations were used. Race was most often used as a confounder (52%), followed by effect measure modifier (33%), and descriptive variable (12%). Fewer than 1 in 4 articles (22.9%) exhibited good practices (EMM along with discussing disparities and mechanisms), 63.5% of the articles exhibited poor practices (confounding only or not discussing mechanisms), and 13.5% were considered neither poor nor good practices. We discuss implications and provide 13 recommendations for operationalization, utilization, and reporting of race in epidemiologic and public health research.

Association between ambient air pollution and thyroid hormones levels: A systematic review and meta-analysis

BACKGROUND

Growing studies have focused on the effects of ambient air pollution on thyroid hormones (THs), but the results were controversial. Therefore, a systematic review and meta-analysis was conducted by pooling current evidence on this association.

METHODS

Four databases were searched for studies examining the associations of particulate matter [diameter ≤10 μm (PM10) or ≤2.5 μm (PM2.5)] and gaseous [sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO)] pollutants with THs levels. Random effects models were used to pool the changes in THs levels with increasing air pollutant concentrations. Subgroup analyses were constructed by region, design, sample size, pollutant concentrations, evaluated methods, and potential risk exposure windows.

RESULTS

A total of 14 studies covering 357,226 participants were included in this meta-analysis. The pooled results showed significant associations of exposure to PM2.5, PM10, NO2, SO2, and CO with decreases in free thyroxine (FT4) with percent changes (PC) ranging from -0.593 % to -3.925 %. PM2.5, NO2, and CO were negatively associated with levels of FT4/FT3 (PC: from -0.604 % to -2.975 %). In addition, results showed significant associations of PM2.5 with hypothyroxinemia and high thyroid-stimulating hormone (TSH). Subgroup analyses indicated that PM2.5 and NO2 were significantly associated with FT4 in studies of Chinese, and similar significant findings were found in studies of PM2.5 and FT4/FT3 in areas with higher concentrations of air pollutants and larger samples. PM2.5 exposure in the first trimester was found to be associated with lower FT4 levels in pregnant women.

CONCLUSION

Our findings suggest that exposure to air pollution is associated with changes in THs levels. Enhanced management of highly polluted areas, identification of harmful components and sources of PM, and protection from harmful exposures in early pregnancy may be of great public health importance for the population's thyroid function.

Predictive factors for the diagnosis of permanent congenital hypothyroidism and its temporal changes in Sergipe, Brazil - A real-life retrospective study

Objective

Congenital hypothyroidism (CH) can be permanent (PCH) or transient (TCH). While the importance of thyroxine in myelination of the brain is undisputed, the benefits to neurodevelopmental outcomes of TCH treatment are controversial. Our objectives were to determine predictive factors for PCH and verify its prevalence changes over time.

Subjects and methods

A total of 165 children were evaluated at 3 years of age to verify the diagnosis of PCH. 130 were submitted to a two-step cluster analysis, with the aim of grouping them into homogeneous clusters. The mean incidence of PCH and TCH was calculated from 2004 to 2010 and 2011 to 2015.

Results

Sixty-six children were diagnosed with PCH, and 99 were diagnosed with TCH. Eighty-one percent of PCH children and all TCH children with thyroid imaging had glands in situ. Eighty children (61.5%) were in Cluster 1, 8 children (6.2%) were in Cluster 2 and 42 children (32.3%) were in Cluster 3. No children had PCH in Cluster 1, while 87.5% of children in Cluster 2 and all children in Cluster 3 had PCH. The most important predictor for PCH was the initial serum TSH, which was marginally higher in importance than the blood spot TSH, followed by the initial serum free T4. The mean incidence of PCH (odds ratio: 1.95, 95% CI 1.36 to 2.95, p < 0.0001) and TCH (odds ratio 1.33, 95%, CI 1.02 to 1.77, p = 0,038) increased over time.

Conclusion

The most important PCH predictors are the initial serum TSH and the blood spot TSH. The mean incidence of both PCH and TCH in our series increased.

Causal relationship between particulate matter 2.5 and hypothyroidism: A two-sample Mendelian randomization study

Background

Epidemiological surveys have found that particulate matter 2.5 (PM_2.5) plays an important role in hypothyroidism. However, due to the methodological limitations of traditional observational studies, it is difficult to make causal inferences. In the present study, we assessed the causal association between PM_2.5 concentrations and risk of hypothyroidism using two-sample Mendelian randomization (TSMR).

Methods

We performed TSMR by using aggregated data from genome-wide association studies (GWAS) on the IEU Open GWAS database. We identified seven single nucleotide polymorphisms (SNPs) associated with PM_2.5 concentrations as instrumental variables (IVs). We used inverse-variance weighting (IVW) as the main analytical method, and we selected MR-Egger, weighted median, simple model, and weighted model methods for quality control.

Results

MR analysis showed that PM_2.5 has a positive effect on the risk of hypothyroidism: An increase of 1 standard deviation (SD) in PM_2.5 concentrations increases the risk of hypothyroidism by ~10.0% (odds ratio 1.10, 95% confidence interval 1.06-1.13, P = 2.93E-08, by IVW analysis); there was no heterogeneity or pleiotropy in the results.

Conclusion

In conclusion, increased PM_2.5 concentrations are associated with an increased risk of hypothyroidism. This study provides evidence of a causal relationship between PM_2.5 and the risk of hypothyroidism, so air pollution control may have important implications for the prevention of hypothyroidism.

Exposure errors due to inaccurate residential addresses and their impact on epidemiological associations: Evidence from a national neonate dataset

BACKGROUND

Studies assessing the associations between prenatal air pollution exposures and birth outcomes commonly use maternal addresses at the time of delivery as a proxy for residency throughout pregnancy. Yet, in large-scale epidemiology studies, maternal addresses commonly originate from an administrative source.

OBJECTIVE

This study aimed to examine the use of population registry addresses to assign exposure estimations and to evaluate the impact of inaccurate addresses on exposure estimates and association measures of prenatal exposures with congenital hypothyroidism.

METHODS

We used morbidity data for congenital hypothyroidism from the national program for neonatal screening for 2009-2015 and address data from two sources: population registry and hospital records. We selected neonates with geocoded addresses from both sources (N = 685,491) and developed a comparison algorithm for these addresses. Next, we assigned neonates with exposures from ambient air pollution of PM and NO₂/NO_X, evaluated exposure assessment differences, and used multivariable logistic regression models to assess the impact that these differences have on association measures.

RESULTS

We found that most of the exposure differences between neonates with addresses from both sources were around zero and had a leptokurtic distribution density, with most values being zero. Additionally, associations between exposure and congenital hypothyroidism were comparable, regardless of address source and when we limited the model to neonates with identical addresses.

CONCLUSIONS

We found that ignoring residential inaccuracies results in only a small bias of the associations towards the null. These results strengthen the validity of addresses from population registries for exposure assessment, when detailed residential data during pregnancy are not available.

Associations of Fine Particulate Matter Constituents with Metabolic Syndrome and the Mediating Role of Apolipoprotein B: A Multicenter Study in Middle-Aged and Elderly Chinese Adults

Fine particulate matter (PM_2.5) was reported to be associated with metabolic syndrome (MetS), but how PM_2.5 constituents affect MetS and the underlying mediators remains unclear. We aimed to investigate the associations of long-term exposure to 24 kinds of PM_2.5 constituents with MetS (defined by five indicators) in middle-aged and elderly adults and to further explore the potential mediating role of apolipoprotein B (ApoB). A multicenter study was conducted by recruiting subjects (n = 2045) in the Beijing-Tianjin-Hebei region from the cohort of Sub-Clinical Outcomes of Polluted Air in China (SCOPA-China Cohort). Relationships among PM_2.5 constituents, serum ApoB levels, and MetS were estimated by multiple logistic/linear regression models. Mediation analysis quantified the role of ApoB in "PM_2.5 constituents-MetS" associations. Results indicated PM_2.5 was significantly related to elevated MetS prevalence. The MetS odds increased after exposure to sulfate (SO₄^2-), calcium ion (Ca²⁺), magnesium ion (Mg²⁺), Si, Zn, Ca, Mn, Ba, Cu, As, Cr, Ni, or Se (odds ratios ranged from 1.103 to 3.025 per interquartile range increase in each constituent). PM_2.5 and some constituents (SO₄^2-, Ca²⁺, Mg²⁺, Ca, and As) were positively related to serum ApoB levels. ApoB mediated 22.10% of the association between PM_2.5 and MetS. Besides, ApoB mediated 24.59%, 50.17%, 12.70%, and 9.63% of the associations of SO₄^2-, Ca²⁺, Ca, and As with MetS, respectively. Our findings suggest that ApoB partially mediates relationships between PM_2.5 constituents and MetS risk in China.

The Physiological Effects of Air Pollution: Particulate Matter, Physiology and Disease

Nine out of 10 people breathe air that does not meet World Health Organization pollution limits. Air pollutants include gasses and particulate matter and collectively are responsible for ~8 million annual deaths. Particulate matter is the most dangerous form of air pollution, causing inflammatory and oxidative tissue damage. A deeper understanding of the physiological effects of particulate matter is needed for effective disease prevention and treatment. This review will summarize the impact of particulate matter on physiological systems, and where possible will refer to apposite epidemiological and toxicological studies. By discussing a broad cross-section of available data, we hope this review appeals to a wide readership and provides some insight on the impacts of particulate matter on human health.