Pregnancy outcome of women in the vicinity of nuclear power plants in Taiwan

Study Protocol for Radiation Exposure and Cancer Risk Assessment: The Taiwan Nuclear Power Plants and Epidemiology Cohort Study (TNPECS)

BACKGROUND

This cohort was established to evaluate whether 38-year radiation exposure (since the start of nuclear reactor operations) is related to cancer risk in residents near three nuclear power plants (NPPs).

METHODS

This cohort study enrolled all residents who lived within 8 km of any of the three NPPs in Taiwan from 1978 to 2016 (n = 214,502; person-years = 4,660,189). The control population (n = 257,475; person-years = 6,282,390) from three towns comprised all residents having lived more than 15 km from all three NPPs. Radiation exposure will be assessed via computer programs GASPAR-II and LADTAP-II by following methodologies provided in the United States Nuclear Regulatory Commission regulatory guides. We calculated the cumulative individual tissue organ equivalent dose and cumulative effective dose for each resident. This study presents the number of new cancer cases and prevalence in the residence-nearest NPP group and control group in the 38-year research observation period.

CONCLUSION

TNPECS provides a valuable platform for research and opens unique possibilities for testing whether radiation exposure since the start of operations of nuclear reactors will affect health across the life course. The release of radioactive nuclear species caused by the operation of NPPs caused residents to have an effective dose between 10^-7 and 10^-3 mSv/year. The mean cumulative medical radiation exposure dose between the residence-nearest NPP group and the control group was not different (7.69; standard deviation, 18.39 mSv and 7.61; standard deviation, 19.17 mSv; P = 0.114).

Energy, Data, and Decision-Making: a Scoping Review-the 3D Commission

Access to energy is an important social determinant of health, and expanding the availability of affordable, clean energy is one of the Sustainable Development Goals. It has been argued that climate mitigation policies can, if well-designed in response to contextual factors, also achieve environmental, economic, and social progress, but otherwise pose risks to economic inequity generally and health inequity specifically. Decisions around such policies are hampered by data gaps, particularly in low- and middle-income countries (LMICs) and among vulnerable populations in high-income countries (HICs). The rise of "big data" offers the potential to address some of these gaps. This scoping review sought to explore the literature linking energy, big data, health, and decision-making.Literature searches in PubMed, Embase, and Web of Science were conducted. English language articles up to April 1, 2020, were included. Pre-agreed study characteristics including geographic location, data collected, and study design were extracted and presented descriptively, and a qualitative thematic analysis was performed on the articles using NVivo.Thirty-nine articles fulfilled eligibility criteria. These included a combination of review articles and research articles using primary or secondary data sources. The articles described health and economic effects of a wide range of energy types and uses, and attempted to model effects of a range of technological and policy innovations, in a variety of geographic contexts. Key themes identified in our analysis included the link between energy consumption and economic development, the role of inequality in understanding and predicting harms and benefits associated with energy production and use, the lack of available data on LMICs in general, and on the local contexts within them in particular. Examples of using "big data," and areas in which the articles themselves described challenges with data limitations, were identified.The findings of this scoping review demonstrate the challenges decision-makers face in achieving energy efficiency gains and reducing emissions, while avoiding the exacerbation of existing inequities. Understanding how to maximize gains in energy efficiency and uptake of new technologies requires a deeper understanding of how work and life is shaped by socioeconomic inequalities between and within countries. This is particularly the case for LMICs and in local contexts where few data are currently available, and for whom existing evidence may not be directly applicable. Big data approaches may offer some value in tracking the uptake of new approaches, provide greater data granularity, and help compensate for evidence gaps in low resource settings.

Residential mobility of pregnant women and implications for assessment of spatially-varying environmental exposures

Health studies on spatially-varying exposures (e.g., air pollution) during pregnancy often estimate exposure using residence at birth, disregarding residential mobility. We investigated moving patterns in pregnant women (n = 10,116) in linked cohorts focused on Connecticut and Massachusetts, U.S., 1988-2008. Moving patterns were assessed by race/ethnicity, age, marital status, education, working status, population density, parity, income, and season of birth. In this population, 11.6% of women moved during pregnancy. Movers were more likely to be younger, unmarried, and living in urban areas with no previous children. Among movers, multiple moves were more likely for racial/ethnic minority, younger, less educated, unmarried, and lower income women. Most moves occurred later in pregnancy, with 87.4% of first moves in the second or third trimester, although not all cohort subjects enrolled in the first few weeks of pregnancy. Distance between first and second residence had a median value of 5.2 km (interquartile range 11.3 km, average 57.8 km, range 0.0-4277 km). Women moving larger distances were more likely to be white, older, married, and work during pregnancy. Findings indicate that residential mobility may impact studies of spatially-varying exposure during pregnancy and health and that subpopulations vary in probability of moving, and timing and distance of moves.

Maternal residential proximity to nuclear facilities and low birth weight in offspring in Texas

Health effects of close residential proximity to nuclear facilities have been a concern for both the general public and health professionals. Here, a study is reported examining the association between maternal residential proximity to nuclear facilities and low birth weight (LBW) in offspring using data from 1996 through 2008 in Texas, USA. A case-control study design was used together with a proximity-based model for exposure assessment. First, the LBW case/control births were categorized into multiple proximity groups based on distances between their maternal residences and nuclear facilities. Then, a binary logistic regression model was used to examine the association between maternal residential proximity to nuclear facilities and low birth weight in offspring. The odds ratios were adjusted for birth year, public health region of maternal residence, child's sex, gestational weeks, maternal age, education, and race/ethnicity. In addition, sensitivity analyses were conducted for the model. Compared with the reference group (more than 50 km from a nuclear facility), the exposed groups did not show a statistically significant increase in LBW risk [adjusted odds ratio (aOR) 0.91 (95% confidence interval (CI): 0.81, 1.03) for group 40-50 km; aOR 0.98 (CI 0.84, 1.13) for group 30-40 km; aOR 0.95 (CI 0.79, 1.15) for group 20-30 km; aOR 0.86 (CI 0.70, 1.04) for group 10-20 km; and aOR 0.98 (CI 0.59, 1.61) for group 0-10 km]. These results were also confirmed by results of the sensitivity analyses. The results suggest that maternal residential proximity to nuclear facilities is not a significant factor for LBW in offspring.

The influence of the built environment on adverse birth outcomes

Adverse birth outcomes are associated with neonatal morbidity and mortality, and higher risk for coronary heart disease, non-insulin-dependent diabetes and hypertension in adulthood. Although there has been considerable research investigating the association between maternal and environmental factors on adverse birth outcomes, one risk factor, not fully understood, is the influence of the built environment. A search of MEDLINE, Scopus, and Cochrane was conducted to find articles assessing the influence of the built environment on preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA). In total, 41 studies met our inclusion criteria, and were organized into nine categories: Roadways, Greenness, Power Plants, Gas Stations/Wells, Waste Management, Power Lines, Neighborhood Conditions, Food Environment, and Industry. The most common built environmental variable was roads/traffic, encompassing 17/41 (41%) of the articles reviewed, of which 12/17 (71%) found a significant small to moderate association between high traffic exposure and adverse birth outcomes.

Cancer incidence in the vicinity of nuclear power plants in Taiwan: a population-based study

Numerous antinuclear demonstrations reveal that the public is anxious about the potential health effects caused by nuclear power plants. The purpose of this study is to address the question "Is there a higher cancer incidence rate in the vicinity of nuclear power plants in Taiwan?" The Taiwan Cancer Registry database from 1979 to 2003 was used to compare the standardized incidence rate of the top four cancers with strong evidence for radiation risks between the "plant-vicinity" with those "non-plant-vicinity" groups. All cancer sites, five-leading cancers in Taiwan, and gender-specific cancers were also studied. We also adopted different observation time to compare the incidence rate of cancers between two groups to explore the impact of the observation period. The incidences of leukemia, thyroid, lung, and breast cancer were not significantly different between two groups, but cervix uteri cancer showed higher incidence rates in the plant-vicinity group. The incidence of cervical cancer was not consistently associated with the duration of plant operation, according to a multiyear period comparison. Although there was higher incidence in cervix cancer in the plant-vicinity group, our findings did not provide the crucial evidence that nuclear power plants were the causal factor for some cancers with strong evidence for radiation risks.

Associations Between Residential Proximity to Power Plants and Adverse Birth Outcomes

Few studies have assessed the associations between residential proximity to power plants and adverse birth outcomes including preterm delivery (PTD), very preterm delivery (VPTD), and term low birth weight (LBW). We geocoded 423,719 singleton Florida births born from 2004 to 2005 and all active power plants and determined residential proximity to the nearest power plant for each birth. Prenatal exposure to particulate matter less than 2.5 µm in diameter for women living near different types of power plants was also determined by using National Environmental Public Health Tracking Network data. Logistic regression models were used to test the hypothesized associations. Women who lived closer to coal and solid waste power plants were exposed to higher levels of particulate matter less than 2.5 µm in diameter compared with other types. We observed a 1.8% (95% confidence interval (CI): 1.3, 2.3) increased odds for PTD, 2.2% (95% CI: 1.0, 3.4) for VPTD, and 1.1% (95% CI: 0.2, 2.0) for term LBW for each 5 km closer to any power plant. When stratifying by different fuel type, we found that only solid waste had an association with term LBW, whereas oil, gas, and solid waste all had an association with PTD and VPTD. Results were consistent when exposure was categorized by number of power plants. Our study found evidence of increasing odds of adverse birth outcomes among infants born to pregnant women living closer to power plants. More research is warranted to better understand the causal relationship.

Review of research on residential mobility during pregnancy: consequences for assessment of prenatal environmental exposures

Studies on environmental exposures during pregnancy often have limited residential history (e.g., at delivery), potentially introducing exposure misclassification. We reviewed studies reporting residential mobility during pregnancy to summarize current evidence and discuss research implications. A meaningful quantitative combination of results (e.g., meta-analysis), was infeasible owing to variation in study designs. Fourteen studies were identified, of which half were from the US. Most were case-control studies examining birth defects. Residential history was typically assessed after delivery. Overall mobility rates were 9-32% and highest in the second trimester. Mobility generally declined with age, parity, and socioeconomic status, although not consistently. Married mothers moved less frequently. Findings were dissimilar by race, smoking, or alcohol use. On the basis of the few studies reporting distance moved, most distances were short (median often <10 km). Results indicate potential misclassification for environmental exposures estimated with incomplete residential information. This misclassification could be associated with potential confounders, such as socioeconomics, thereby affecting risk estimates. As most moves were short distances, exposures that are homogenous within a community may be well estimated with limited residential data. Future research should consider the implications of residential mobility during pregnancy in relation to the exposure's spatial heterogeneity and factors associated with the likelihood of moving and distance moved.