A global perspective on coal-fired power plants and burden of lung cancer

Estimates of the global burden of cancer-related deaths attributable to residential exposure to petrochemical industrial complexes from 2020 to 2040

The petrochemical industry is a major industrial emitter of greenhouse gas (CO2) and environmental pollution, posing health risks to nearby communities. Although previous studies have indicated that residents living near petrochemical industrial complexes are at a higher risk of cancer, they have focused on local or regional burdens. This study aimed to estimate the global cancer burden attributable to residential exposure to petrochemical industrial complexes. The geographical coordinates of petrochemical plants and oil refineries were retrieved and verified from published sources. The ArcGIS software and global population data were used to estimate the number of people living within specific distances (exposed population). The exposure time window was framed as ranging from 1992 to 2035, extending to the latest period of the exposure time window for all cancer types to estimate the attributable deaths between 2020 and 2040. The relative risk of cancer was estimated from 15 published studies. Population attributable fraction (PAF) method was used to estimate the risk of cancer attributable to residential exposure and calculate the number of cancer-related deaths. Our findings indicate that >300 million people worldwide will be estimated to live near petrochemical industrial complexes by 2040. The overall global burden of cancer-related deaths was 19,083 in 2020, and it is estimated to increase to 27,366 deaths by 2040. The region with the highest attributable cancer deaths due to exposure is the high-income region, which had 10,584 deaths in 2020 and is expected to reach 13,414 deaths by 2040. Residential exposure to petrochemical industrial complexes could contribute to global cancer deaths, even if the proportion is relatively small, and proactive measures are required to mitigate the cancer burdens among these residents. Enforcing emissions regulations, improving monitoring, educating communities, and fostering collaboration are vital to protecting residents' health.

Health risks of exposure to air pollution in areas where coal-fired power plants are located: protocol for a scoping review

INTRODUCTION

Coal-fired power plants are major sources of air pollution which impact human health. Coal combustion byproducts released into the air include particulate matter, nitrogen oxides and sulphur dioxide. Exposure to fine particulate matter is associated with increased risk of mortality. This scoping review will examine and summarise the current literature on the health risks of exposure to air pollution in areas in which coal-fired power plants exist.

METHODS AND ANALYSIS

This scoping review will be conducted according to the Joanna Briggs Institute methodological framework and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Five electronic databases (PubMed, ScienceDirect, Scopus, Web of Science and Google Scholar) will be searched for relevant articles. Studies will be included up until 31 January 2024. There will be no restriction on geographical area. The searches will be limited to studies published in English. Title, abstract, full-text screening and data extraction of relevant articles will be done by two independent reviewers. Discrepancies will be resolved by group discussion. The findings will be presented in tables with a narrative summary. This review will consider epidemiological studies and grey literature that report on the health risks of exposure to air pollution in areas where coal-fired power plants exist.

ETHICS AND DISSEMINATION

All data will be collected from published and grey literature. Ethics approval is therefore not required. We will submit our findings for publication in a peer-reviewed journal.

Community-driven research and capacity building to address environmental justice concerns with industrial air pollution in Curtis Bay, South Baltimore

Introduction

Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ.

Methods

Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns.

Results and Discussion

Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues.

Analysis of the cytotoxic and genotoxic effects in a population chronically exposed to coal mining residues

During coal mining activities, many compounds are released into the environment that can negatively impact human health. Particulate matter, polycyclic aromatic hydrocarbons (PAHs), metals, and oxides are part of the complex mixture that can affect nearby populations. Therefore, we designed this study to evaluate the potential cytotoxic and genotoxic effects in individuals chronically exposed to coal residues from peripheral blood lymphocytes and buccal cells. We recruited 150 individuals who lived more than 20 years in La Loma-Colombia and 120 control individuals from the city of Barranquilla without a history of exposure to coal mining. In the cytokinesis-block micronucleus cytome (CBMN-Cyt) assay, significant differences in the frequency of micronucleus (MN), nucleoplasmic bridge (NPB), nuclear bud (NBUD), and apoptotic cells (APOP) were observed between the two groups. In the buccal micronucleus cytome (BM-Cyt) assay, a significant formation of NBUD, karyorrhexis (KRX), karyolysis (KRL), condensed chromatin (CC), and binucleated (BN) cells was observed in the exposed group. Considering the characteristics of the study group, a significant correlation for CBMN-Cyt was found between NBUD and vitamin consumption, between MN or APOP and meat consumption, and between MN and age. Moreover, a significant correlation for BM-Cyt was found between KRL and vitamin consumption or age, and BN versus alcohol consumption. Using Raman spectroscopy, a significant increase in the concentration of DNA/RNA bases, creatinine, polysaccharides, and fatty acids was detected in the urine of individuals exposed to coal mining compared to the control group. These results contribute to the discussion on the effects of coal mining on nearby populations and the development of diseases due to chronic exposure to these residues.

Traffic-related Air Pollution and Lung Cancer Incidence: The California Multiethnic Cohort Study

Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99-1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95-1.32), fine particulate matter with aerodynamic diameter <2.5 μm (HR, 1.20 per 10 μg/m3; 95% CI, 1.01-1.43), carbon monoxide (HR, 1.29 per 1,000 ppb; 95% CI, 0.99-1.67), and regional benzene (HR, 1.17 per 1 ppb; 95% CI, 1.02-1.34) exposures. These patterns of associations were driven by associations among African American and Latino American groups. There was no formal evidence for heterogeneity of effects by nSES (P heterogeneity > 0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.

Development of a neighborhood drivability index and its association with transportation behavior in Toronto

BACKGROUND

Car driving is a form of passive transport that is associated with an increase in physical inactivity, obesity, air pollution and noise. Built environment characteristics may influence transport mode choice, but comprehensive indices for built environment characteristics that drive car use are still lacking, while such an index could provide tangible policy entry points.

OBJECTIVE

We developed and validated a neighbourhood drivability index, capturing combined dimensions of the neighbourhood environment in the City of Toronto, and investigated its association with transportation choices (car, public transit or active transport), overall, by trip length, and combined for residential neighbourhood and workplace drivability.

METHODS

We used exploratory factor analysis to derive distinct factors (clusters of one or more environmental characteristics) that reflect the degree of car dependency in each neighbourhood, drawing from candidate variables that capture density, diversity, design, destination accessibility, distance to transit, and demand management. Area-level factor scores were then combined into a single composite score, reflecting neighbourhood drivability. Negative binomial generalized estimating equations were used to test the association between driveability quintiles (Q) and primary travel mode (>50% of trips by car, public transit, or walking/cycling) in a population-based sample of 63,766 Toronto residents enrolled in the Transportation Tomorrow Survey (TTS) wave 2016, adjusting for individual and household characteristics, and accounting for clustering of respondents within households.

RESULTS

The drivability index consisted of three factors: Urban sprawl, pedestrian facilities and parking availability. Relative to those living in the least drivable neighbourhoods (Q1), those in high drivability areas (Q5) had a significantly higher rate of car travel (adjusted Risk Ratio (RR): 1.80, 95%CI: 1.77-1.88), and lower rate of public transit use (RR: 0.90, 95%CI: 0.85-0.94) and walking/cycling (RR: 0.22, 95%CI: 0.19-0.25). Associations were strongest for short trips (<3 km) (RR: 2.72, 95%CI: 2.48-2.92), and in analyses where both residential and workplace drivability was considered (RR for car use in high/high vs. low/low residential/workplace drivability: 2.18, 95%CI: 2.08-2.29).

CONCLUSION

This novel neighbourhood drivability index predicted whether local residents drive or use active modes of transportation and can be used to investigate the association between drivability, physical activity, and chronic disease risk.

County-Wide Mortality Assessments Attributable to PM2.5 Emissions from Coal Consumption in Taiwan

Over one-third of energy is generated from coal consumption in Taiwan. In order to estimate the health impact assessment attributable to PM_2.5 concentrations emitted from coal consumption in Taiwan. We applied a Gaussian trajectory transfer-coefficient model to obtain county-wide PM_2.5 exposures from coal consumption, which includes coal-fired power plants and combined heat and power plants. Next, we calculated the mortality burden attributable to PM_2.5 emitted by coal consumption using the comparative risk assessment framework developed by the Global Burden of Disease study. Based on county-level data, the average PM_2.5 emissions from coal-fired plants in Taiwan was estimated at 2.03 ± 1.29 (range: 0.32–5.64) μg/m³. With PM_2.5 increments greater than 0.1 μg/m³, there were as many as 16 counties and 66 air quality monitoring stations affected by coal-fired plants and 6 counties and 18 monitoring stations affected by combined heat and power plants. The maximum distances affected by coal-fired and combined heat and power plants were 272 km and 157 km, respectively. Our findings show that more counties were affected by coal-fired plants than by combined heat and power plants with significant increments of PM_2.5 emissions. We estimated that 359.6 (95% CI: 334.8–384.9) annual adult deaths and 124.4 (95% CI: 116.4–132.3) annual premature deaths were attributable to PM_2.5 emitted by coal-fired plants in Taiwan. Even in six counties without power plants, there were 75.8 (95% CI: 60.1–91.5) deaths and 25.8 (95%CI: 20.7–30.9) premature deaths annually attributable to PM_2.5 emitted from neighboring coal-fired plants. This study presents a precise and effective integrated approach for assessing air pollution and the health impacts of coal-fired and combined heat and power plants.

Proximity to coal-fired power plants and neurobehavioral symptoms in children

BACKGROUND

Coal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants contributes to children's neurobehavioral disorders.

OBJECTIVE

This community-based study collected primary data to investigate the relationships of residential proximity to power plants and neurobehavioral problems in children.

METHODS

235 participants aged 6-14 years who lived within 10 miles of two power plants were recruited. Exposure to particulate matter ≤10 μm (PM₁₀) was measured in children's homes using personal modular impactors. Neurobehavioral symptoms were assessed using the Child Behavior Checklist (CBCL). Multiple regression models were performed to test the hypothesized associations between proximity/exposure and neurobehavioral symptoms. Geospatial statistical methods were used to map the spatial patterns of exposure and neurobehavioral symptoms.

RESULTS

A small proportion of the variations of neurobehavioral problems (social problems, affective problems, and anxiety problems) were explained by the regression models in which distance to power plants, traffic proximity, and neighborhood poverty was statistically associated with the neurobehavioral health outcomes. Statistically significant hot spots of participants who had elevated levels of attention deficit hyperactivity disorder, anxiety, and social problems were observed in the vicinity of the two power plants.

SIGNIFICANCE

Results of this study suggest an adverse impact of proximity to power plants on children's neurobehavioral health. Although coal-fired power plants are being phased out in the US, health concern about exposure from coal ash storage facilities remains. Furthermore, other countries in the world are increasing coal use and generating millions of tons of pollutants and coal ash. Findings from this study can inform public health policies to reduce children's risk of neurobehavioral symptoms in relation to proximity to power plants.

Exposure to combustion derived particulate matter exacerbates influenza infection in neonatal mice by inhibiting IL22 production

Background

Particulate matter (PM) containing environmentally persistent free radicals (EPFRs) are formed during various combustion processes, including the thermal remediation of hazardous wastes. Exposure to PM adversely affects respiratory health in infants and is associated with increased morbidity and mortality due to acute lower respiratory tract infections. We previously reported that early-life exposure to PM damages the lung epithelium and suppresses immune responses to influenza virus (Flu) infection, thereby enhancing Flu severity. Interleukin 22 (IL22) is important in resolving lung injury following Flu infection. In the current study, we determined the effects of PM exposure on pulmonary IL22 responses using our neonatal mouse model of Flu infection.

Results

Exposure to PM resulted in an immediate (0.5–1-day post-exposure; dpe) increase in IL22 expression in the lungs of C57BL/6 neonatal mice; however, this IL22 expression was not maintained and failed to increase with either continued exposure to PM or subsequent Flu infection of PM-exposed mice. This contrasts with increased IL22 expression in age-matched mice exposed to vehicle and Flu infected. Activation of the aryl hydrocarbon receptor (AhR), which mediates the induction and release of IL22 from immune cells, was also transiently increased with PM exposure. The microbiome plays a major role in maintaining epithelial integrity and immune responses by producing various metabolites that act as ligands for AhR. Exposure to PM induced lung microbiota dysbiosis and altered the levels of indole, a microbial metabolite. Treatment with recombinant IL22 or indole-3-carboxaldehyde (I3A) prevented PM associated lung injury. In addition, I3A treatment also protected against increased mortality in Flu-infected mice exposed to PMs.

Conclusions

Together, these data suggest that exposure to PMs results in failure to sustain IL22 levels and an inability to induce IL22 upon Flu infection. Insufficient levels of IL22 may be responsible for aberrant epithelial repair and immune responses, leading to increased Flu severity in areas of high PM.

Using an Integrated Social Cognition Model to Explain Green Purchasing Behavior among Adolescents

Strengthening pro-environmental behaviors such as green purchasing behavior is important for environmental sustainability. An integrated social cognition model which incorporates constructs from habit theory, health action process approach (HAPA), and theory of planned behavior (TPB) is adopted to understand Iranian adolescents’ green purchasing behavior. Using a correlational-prospective design, the study recruited Iranian adolescents aged between 14 and 19 years (N = 2374, n = 1362 (57.4%) females, n = 1012 (42.6%) males; Mean (SD) age = 15.56 (1.22)). At baseline (T1), participants self-reported on the following constructs: past behavior; habit strength (from habit theory); action planning and coping planning (from HAPA); and intention, perceived behavioral control, subjective norm, and attitude (from TPB) with respect to green purchasing behavior. Six months later (T2), participants self-reported on their actions in terms of purchasing green goods. Our findings reported direct effects of perceived behavioral control, subjective norms, attitude, and past behavior on intention; intention and perceived behavioral control on green purchase behavior; intention on two types of planning (i.e., action and coping planning); both types of planning on green purchase behavior; and past green purchase behavior and habits on prospectively measured green purchase behavior. These results indicate that adolescent green purchasing behavior is underpinned by constructs representing motivational, volitional, and automatic processes. This knowledge can help inform the development of theory-based behavior change interventions to improve green purchasing in adolescents, a key developmental period where climate change issues are salient and increased independence and demands in making self-guided decisions are needed.

Occupational Dust Hazards and Risk Assessment of Coal-Fired Thermal Power Plants of Different Capacities - China, 2017-2019

What is already known about this topic?

Silica dust and coal dust are the main occupational hazards in coal-fired thermal power plants, which mainly exist in coal transportation workplaces, combustion milling workplaces, and ash removal workplaces.

What is added by this report?

The overall environmental and personal dust exposure levels decrease with an increase in the capacity of coal-fired thermal power plants, the overall dust hazard risk level of the workforce in coal-fired is Medium.

What are the implications for public health practice?

Dust management should be conducted in the coal-fired thermal power plant in 300 million watt units because it has the highest dust exposure level, and ash removal workplaces and combustion milling workplaces are key control points for dust hazards.

Resilience and Equity in a Time of Crises: Investing in Public Urban Greenspace Is Now More Essential Than Ever in the US and Beyond

The intersecting negative effects of structural racism, COVID-19, climate change, and chronic diseases disproportionately affect racial and ethnic minorities in the US and around the world. Urban populations of color are concentrated in historically redlined, segregated, disinvested, and marginalized neighborhoods with inadequate quality housing and limited access to resources, including quality greenspaces designed to support natural ecosystems and healthy outdoor activities while mitigating urban environmental challenges such as air pollution, heat island effects, combined sewer overflows and poor water quality. Disinvested urban environments thus contribute to health inequity via physical and social environmental exposures, resulting in disparities across numerous health outcomes, including COVID-19 and chronic diseases such as cancer and cardiovascular diseases (CVD). In this paper, we build off an existing conceptual framework and propose another conceptual framework for the role of greenspace in contributing to resilience and health equity in the US and beyond. We argue that strategic investments in public greenspaces in urban neighborhoods impacted by long term economic disinvestment are critically needed to adapt and build resilience in communities of color, with urgency due to immediate health threats of climate change, COVID-19, and endemic disparities in chronic diseases. We suggest that equity-focused investments in public urban greenspaces are needed to reduce social inequalities, expand economic opportunities with diversity in workforce initiatives, build resilient urban ecosystems, and improve health equity. We recommend key strategies and considerations to guide this investment, drawing upon a robust compilation of scientific literature along with decades of community-based work, using strategic partnerships from multiple efforts in Milwaukee Wisconsin as examples of success.

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.

Nail Samples of Children Living near Coal Ash Storage Facilities Suggest Fly Ash Exposure and Elevated Concentrations of Metal(loid)s

Children who live near coal-fired power plants are exposed to coal fly ash, which is stored in landfills and surface impoundments near residential communities. Fly ash has the potential to be released as fugitive dust. Using data collected from 263 children living within 10 miles of coal ash storage facilities in Jefferson and Bullitt Counties, Kentucky, USA, we quantified the elements found in nail samples. Furthermore, using principal component analysis (PCA), we investigated whether metal(loid)s that are predominately found in fly ash loaded together to indicate potential exposure to fly ash. Concentrations of several neurotoxic metal(loid)s, such as chromium, manganese, and zinc, were higher than concentrations reported in other studies of both healthy and environmentally exposed children. From PCA, it was determined that iron, aluminum, and silicon in fly ash were found to load together in the nails of children living near coal ash storage facilities. These metal(loid)s were also highly correlated with each other. Last, results of geospatial analyses partially validated our hypothesis that children's proximity to power plants was associated with elevated levels of concentrations of fly ash metal(loid)s in nails. Taken together, nail samples may be a powerful tool in detecting exposure to fly ash.

Air pollution exposure-the (in)visible risk factor for respiratory diseases

There is increasing interest in understanding the role of air pollution as one of the greatest threats to human health worldwide. Nine of 10 individuals breathe air with polluted compounds that have a great impact on lung tissue. The nature of the relationship is complex, and new or updated data are constantly being reported in the literature. The goal of our review was to summarize the most important air pollutants and their impact on the main respiratory diseases (chronic obstructive pulmonary disease, asthma, lung cancer, idiopathic pulmonary fibrosis, respiratory infections, bronchiectasis, tuberculosis) to reduce both short- and the long-term exposure consequences. We considered the most important air pollutants, including sulfur dioxide, nitrogen dioxide, carbon monoxide, volatile organic compounds, ozone, particulate matter and biomass smoke, and observed their impact on pulmonary pathologies. We focused on respiratory pathologies, because air pollution potentiates the increase in respiratory diseases, and the evidence that air pollutants have a detrimental effect is growing. It is imperative to constantly improve policy initiatives on air quality in both high- and low-income countries.

A review on fly ash from coal-fired power plants: chemical composition, regulations, and health evidence

Throughout the world, coal is responsible for generating approximately 38% of power. Coal ash, a waste product, generated from the combustion of coal, consists of fly ash, bottom ash, boiler slag, and flue gas desulfurization material. Fly ash, which is the main component of coal ash, is composed of spherical particulate matter with diameters that range from 0.1 μm to >100 μm. Fly ash is predominately composed of silica, aluminum, iron, calcium, and oxygen, but the particles may also contain heavy metals such as arsenic and lead at trace levels. Most nations throughout the world do not consider fly ash a hazardous waste and therefore regulations on its disposal and storage are lacking. Fly ash that is not beneficially reused in products such as concrete is stored in landfills and surface impoundments. Fugitive dust emissions and leaching of metals into groundwater from landfills and surface impoundments may put people at risk for exposure. There are limited epidemiological studies regarding the health effects of fly ash exposure. In this article, the authors provide an overview of fly ash, its chemical composition, the regulations from nations generating the greatest amount of fly ash, and epidemiological evidence regarding the health impacts associated with exposure to fly ash.

Estimation of Generalized Impact Fraction and Population Attributable Fraction of Hypertension Based on JNC-IV and 2017 ACC/AHA Guidelines for Cardiovascular Diseases Using Parametric G-Formula: Tehran Lipid and Glucose Study (TLGS)

Purpose

An area of interest to health policymakers is the effect of interventions aimed at risk factors on decreasing the number of new cardiovascular disease (CVD) cases. The aim of this study was to estimate the generalized impact fraction (GIF) and population attributable fraction (PAF) of hypertension (HTN) for CVD in Tehran.

Patients and Methods

In this population-based cohort study, 8071 participants aged ≥30 years were followed for a median of 16 years. A survival model was used to estimate the 10- and 18-year risk of CVD. JNC-IV and 2017 ACC/AHA guidelines were used to categorize blood pressure (BP). PAF and GIF were estimated in different scenarios using the parametric G-formula.

Results

Of 7378 participants included in analyses, 22.7% and 52.3% were classified as hypertensive according to the JNC-IV and 2017 ACC/AHA guidelines, respectively. According to the 2017 ACC/AHA, the 10-year risk of CVD was 5.1% (4.3–6.0%), 8.9% (6.7–12.0%), and 7.1% (6.1–8.4%) for normal BP, elevated BP, and stage 1 HTN, respectively, and 20.8% (18.8–23.0%) for stage 2 of the 2017 ACC/AHA and JNC-IV. The PAF of stage 2 vs stage 1 and vs normal BP for CVD was 17.4% (11.5–21.8%) and 20.4% (14.6–26.4%), respectively. The GIF of 30% reduction in the prevalence of stage 2 HTN to stage 1 and to normal BP for CVD was 5.1% (3.4–6.6%) and 6.1% (4.4–8.0%), respectively. Based on JNC-IV, the PAF and GIF of 30% for CVD were 17.8% (12.7–22.9%) and 5.4% (4.0–6.9%), respectively.

Conclusion

By reducing the prevalence of HTN by 30%, a remarkable number of new CVD cases would be prevented. In an Iranian population, the comparison of HTN cases with normal BP showed no association between stage 1 HTN and CVD, whereas elevated BP was a significant risk factor for the incidence of CVD.

Estimation and application of population attributable fraction in ecological studies

Estimation of population attributable fraction (PAF) requires unbiased relative risk (RR) by using either Levin's or Miettinen's formula, on which decision depends on the available exposure information in reference group, not the types of studies. For ecological studies and studies with aggregated outcomes, once having unbiased RRs, Levin's and Miettinen's formulae would provide identical PAF estimates. PAF could also be applied to compare relative burdens of disease between countries across time, which is an additional information in consideration of country-level policies.

Issues with incorrect computing of population attributable fraction (PAF) in a global perspective on coal-fired power plants and burden of lung cancer

All observational studies are liable to confounding and Levin's formula becomes useless in practice for unbiasedly estimating PAF. With respect to causal interpretation of PAF in public health setting, unbiased estimation of PAF requires several assumptions which are ignored in practice. We recommend using Miettinen PAF formula with careful consideration about possibility of bias in study design and analysis.