Author
Andrea Ranzi
Other affiliations: University of Modena and Reggio Emilia
Bio: Andrea Ranzi is an academic researcher from ARPA-E. The author has contributed to research in topics: Population & Environmental exposure. The author has an hindex of 42, co-authored 101 publications receiving 8090 citations. Previous affiliations of Andrea Ranzi include University of Modena and Reggio Emilia.
Papers published on a yearly basis
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University of Copenhagen1, Utrecht University2, National and Kapodistrian University of Athens3, University of Ulm4, University of Düsseldorf5, Imperial College London6, Umeå University7, Norwegian Institute of Public Health8, University of Oslo9, Karolinska Institutet10, Aarhus University11, Cancer Epidemiology Unit12, Institut Gustave Roussy13, French Institute of Health and Medical Research14, Swiss Tropical and Public Health Institute15, University of Washington16, University of Turin17
TL;DR: The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 and PM2·5, and no association between lungcancer and nitrogen oxides concentration or traffic intensity on the nearest street.
Abstract: Summary Background Ambient air pollution is suspected to cause lung cancer. We aimed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European populations. Methods This prospective analysis of data obtained by the European Study of Cohorts for Air Pollution Eff ects used data from 17 cohort studies based in nine European countries. Baseline addresses were geocoded and we assessed air pollution by land-use regression models for particulate matter (PM) with diameter of less than 10 μm (PM10), less than 2·5 μm (PM2·5), and between 2·5 and 10 μm (PMcoarse), soot (PM2·5absorbance), nitrogen oxides, and two traffi c indicators. We used Cox regression models with adjustment for potential confounders for cohort-specifi c analyses and random eff ects models for meta-analyses. Findings The 312 944 cohort members contributed 4 013 131 person-years at risk. During follow-up (mean 12·8 years), 2095 incident lung cancer cases were diagnosed. The meta-analyses showed a statistically signifi cant association between risk for lung cancer and PM10 (hazard ratio [HR] 1·22 [95% CI 1·03–1·45] per 10 μg/m³). For PM2·5 the HR was 1·18 (0·96–1·46) per 5 μg/m³. The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 (1·10–2·08) and 1·55 (1·05–2·29), respectively. An increase in road traffi c of 4000 vehicle-km per day within 100 m of the residence was associated with an HR for lung cancer of 1·09 (0·99–1·21). The results showed no association between lung cancer and nitrogen oxides concentration (HR 1·01 [0·95–1·07] per 20 μg/m³) or traffi c intensity on the nearest street (HR 1·00 [0·97–1·04] per 5000 vehicles per day).
1,257 citations
Utrecht University1, University of Copenhagen2, University of Düsseldorf3, University of Ulm4, National and Kapodistrian University of Athens5, Imperial College London6, University College London7, Umeå University8, National Institutes of Health9, Norwegian Institute of Public Health10, University of Oslo11, Karolinska Institutet12, Aarhus University13, University Medical Center Utrecht14, Cancer Epidemiology Unit15, University of Basel16, Swiss Tropical and Public Health Institute17, French Institute of Health and Medical Research18, Institut Gustave Roussy19, University of Washington20, University of Turin21, Basque Government22
TL;DR: In this article, the authors investigated the association between natural-cause mortality and long-term exposure to several air pollutants, such as PM2.5, nitrogen oxides, and NOx.
1,056 citations
Utrecht University1, Imperial College London2, Karolinska Institutet3, Vytautas Magnus University4, Flemish Institute for Technological Research5, University of Hasselt6, National and Kapodistrian University of Athens7, University of California, Berkeley8, Swiss Tropical and Public Health Institute9, University of Basel10, National Institutes of Health11, University of Manchester12, Norwegian Institute of Public Health13, University of Duisburg-Essen14, ARPA-E15, University of Washington16
TL;DR: Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models, which are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.
Abstract: Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.
861 citations
Utrecht University1, Imperial College London2, National and Kapodistrian University of Athens3, Swiss Tropical and Public Health Institute4, University of Washington5, University of Basel6, University of Verona7, University of Crete8, National Institutes of Health9, University of Augsburg10, Vytautas Magnus University11, University of Manchester12, Norwegian Institute of Public Health13, ARPA-E14, University of Düsseldorf15, University of Duisburg-Essen16, Karolinska Institutet17, Umeå University18, University of Hasselt19, Flemish Institute for Technological Research20, University of California, Berkeley21
TL;DR: In this article, the authors estimate within-city variability in air pollution concentrations using Land Use Regression (LUR) models and show that LUR models are able to explain small-scale within city variations.
758 citations
University of Copenhagen1, Utrecht University2, Karolinska Institutet3, Stockholm University4, Karolinska University Hospital5, University of Turin6, Augsburg College7, University of Düsseldorf8, National Institutes of Health9, Aalborg University10, Aarhus University11, Imperial College London12, University of Ulm13
TL;DR: Long term exposure to particulate matter is associated with incidence of coronary events, and this association persists at levels of exposure below the current European limit values.
Abstract: OBJECTIVES: To study the effect of long term exposure to airborne pollutants on the incidence of acute coronary events in 11 cohorts participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). DESIGN: Prospective cohort studies and meta-analysis of the results. SETTING: Cohorts in Finland, Sweden, Denmark, Germany, and Italy. PARTICIPANTS: 100 166 people were enrolled from 1997 to 2007 and followed for an average of 11.5 years. Participants were free from previous coronary events at baseline. MAIN OUTCOME MEASURES: Modelled concentrations of particulate matter <2.5 μm (PM2.5), 2.5-10 μm (PMcoarse), and <10 μm (PM10) in aerodynamic diameter, soot (PM2.5 absorbance), nitrogen oxides, and traffic exposure at the home address based on measurements of air pollution conducted in 2008-12. Cohort specific hazard ratios for incidence of acute coronary events (myocardial infarction and unstable angina) per fixed increments of the pollutants with adjustment for sociodemographic and lifestyle risk factors, and pooled random effects meta-analytic hazard ratios. RESULTS: 5157 participants experienced incident events. A 5 μg/m(3) increase in estimated annual mean PM2.5 was associated with a 13% increased risk of coronary events (hazard ratio 1.13, 95% confidence interval 0.98 to 1.30), and a 10 μg/m(3) increase in estimated annual mean PM10 was associated with a 12% increased risk of coronary events (1.12, 1.01 to 1.25) with no evidence of heterogeneity between cohorts. Positive associations were detected below the current annual European limit value of 25 μg/m(3) for PM2.5 (1.18, 1.01 to 1.39, for 5 μg/m(3) increase in PM2.5) and below 40 μg/m(3) for PM10 (1.12, 1.00 to 1.27, for 10 μg/m(3) increase in PM10). Positive but non-significant associations were found with other pollutants. CONCLUSIONS: Long term exposure to particulate matter is associated with incidence of coronary events, and this association persists at levels of exposure below the current European limit values.
525 citations
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TL;DR: The 11th edition of Harrison's Principles of Internal Medicine welcomes Anthony Fauci to its editorial staff, in addition to more than 85 new contributors.
Abstract: The 11th edition of Harrison's Principles of Internal Medicine welcomes Anthony Fauci to its editorial staff, in addition to more than 85 new contributors. While the organization of the book is similar to previous editions, major emphasis has been placed on disorders that affect multiple organ systems. Important advances in genetics, immunology, and oncology are emphasized. Many chapters of the book have been rewritten and describe major advances in internal medicine. Subjects that received only a paragraph or two of attention in previous editions are now covered in entire chapters. Among the chapters that have been extensively revised are the chapters on infections in the compromised host, on skin rashes in infections, on many of the viral infections, including cytomegalovirus and Epstein-Barr virus, on sexually transmitted diseases, on diabetes mellitus, on disorders of bone and mineral metabolism, and on lymphadenopathy and splenomegaly. The major revisions in these chapters and many
6,968 citations
TL;DR: It is found that emissions from residential energy use such as heating and cooking, prevalent in India and China, have the largest impact on premature mortality globally, being even more dominant if carbonaceous particles are assumed to be most toxic.
Abstract: Assessment of the global burden of disease is based on epidemiological cohort studies that connect premature mortality to a wide range of causes, including the long-term health impacts of ozone and fine particulate matter with a diameter smaller than 2.5 micrometres (PM2.5). It has proved difficult to quantify premature mortality related to air pollution, notably in regions where air quality is not monitored, and also because the toxicity of particles from various sources may vary. Here we use a global atmospheric chemistry model to investigate the link between premature mortality and seven emission source categories in urban and rural environments. In accord with the global burden of disease for 2010 (ref. 5), we calculate that outdoor air pollution, mostly by PM2.5, leads to 3.3 (95 per cent confidence interval 1.61-4.81) million premature deaths per year worldwide, predominantly in Asia. We primarily assume that all particles are equally toxic, but also include a sensitivity study that accounts for differential toxicity. We find that emissions from residential energy use such as heating and cooking, prevalent in India and China, have the largest impact on premature mortality globally, being even more dominant if carbonaceous particles are assumed to be most toxic. Whereas in much of the USA and in a few other countries emissions from traffic and power generation are important, in eastern USA, Europe, Russia and East Asia agricultural emissions make the largest relative contribution to PM2.5, with the estimate of overall health impact depending on assumptions regarding particle toxicity. Model projections based on a business-as-usual emission scenario indicate that the contribution of outdoor air pollution to premature mortality could double by 2050.
3,848 citations
Icahn School of Medicine at Mount Sinai1, Pure Earth2, World Bank3, University of Arizona4, McGill University5, Indian Ministry of Environment and Forests6, Qatar Airways7, University of Health Sciences Antigua8, Ludwig Maximilian University of Munich9, Johns Hopkins University10, Boston College11, Chulabhorn Research Institute12, University of Maryland, College Park13, University of Ghana14, Centro Nacional de Investigaciones Cardiovasculares15, University of Chicago16, University of London17, University of Oxford18, Indian Institute of Technology Delhi19, Simon Fraser University20, Consortium of Universities for Global Health21, University of Ottawa22, Columbia University23, Stockholm Resilience Centre24, Massachusetts Institute of Technology25, University of Queensland26, University of California, Berkeley27, New York University28, National Institutes of Health29, Public Health Research Institute30, United Nations Industrial Development Organization31, Renmin University of China32
TL;DR: This book is dedicated to the memory of those who have served in the armed forces and their families during the conflicts of the twentieth century.
2,628 citations
Health Canada1, United States Environmental Protection Agency2, Brigham Young University3, University of Texas at Austin4, University of British Columbia5, Health Effects Institute6, McGill University7, University of Minnesota8, Harvard University9, Utrecht University10, University of Washington11, Fudan University12, New York University13, University of California, Los Angeles14, University of Ottawa15, American Cancer Society16, University of California, Davis17, Cancer Prevention Institute of California18, University of New Brunswick19, Dalhousie University20, Carleton University21, Statistics Canada22, University of Toronto23, Chinese Center for Disease Control and Prevention24, St George's, University of London25, University of Hong Kong26, University of Ulm27, SERC Reliability Corporation28
TL;DR: PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
Abstract: Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
1,283 citations
University of Copenhagen1, Utrecht University2, National and Kapodistrian University of Athens3, University of Ulm4, University of Düsseldorf5, Imperial College London6, Umeå University7, Norwegian Institute of Public Health8, University of Oslo9, Karolinska Institutet10, Aarhus University11, Cancer Epidemiology Unit12, French Institute of Health and Medical Research13, Institut Gustave Roussy14, Swiss Tropical and Public Health Institute15, University of Washington16, University of Turin17
TL;DR: The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 and PM2·5, and no association between lungcancer and nitrogen oxides concentration or traffic intensity on the nearest street.
Abstract: Summary Background Ambient air pollution is suspected to cause lung cancer. We aimed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European populations. Methods This prospective analysis of data obtained by the European Study of Cohorts for Air Pollution Eff ects used data from 17 cohort studies based in nine European countries. Baseline addresses were geocoded and we assessed air pollution by land-use regression models for particulate matter (PM) with diameter of less than 10 μm (PM10), less than 2·5 μm (PM2·5), and between 2·5 and 10 μm (PMcoarse), soot (PM2·5absorbance), nitrogen oxides, and two traffi c indicators. We used Cox regression models with adjustment for potential confounders for cohort-specifi c analyses and random eff ects models for meta-analyses. Findings The 312 944 cohort members contributed 4 013 131 person-years at risk. During follow-up (mean 12·8 years), 2095 incident lung cancer cases were diagnosed. The meta-analyses showed a statistically signifi cant association between risk for lung cancer and PM10 (hazard ratio [HR] 1·22 [95% CI 1·03–1·45] per 10 μg/m³). For PM2·5 the HR was 1·18 (0·96–1·46) per 5 μg/m³. The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 (1·10–2·08) and 1·55 (1·05–2·29), respectively. An increase in road traffi c of 4000 vehicle-km per day within 100 m of the residence was associated with an HR for lung cancer of 1·09 (0·99–1·21). The results showed no association between lung cancer and nitrogen oxides concentration (HR 1·01 [0·95–1·07] per 20 μg/m³) or traffi c intensity on the nearest street (HR 1·00 [0·97–1·04] per 5000 vehicles per day).
1,257 citations