Department of Biostatistics
Environmental Statistics Seminar

2014 - 2015

Coordinator: Dr. Ander Wilson

Schedule: Fridays, 12:30-2:00 p.m.
HSPH2, Room 426 (unless otherwise notified)

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Seminar Description
This seminar focuses on statistical issues related to assessing environmental effects on human health and analyzing environmental data in general. Specific areas of interest include air pollution epidemiology, exposure assessment, teratology, fertility and reproduction, respiratory studies, and community-based research as well as general topics such as errors-in-variables models, missing data methods, hierarchical modeling, smoothing, and methods for correlated data such as longitudinal and spatial data analysis. The seminars are generally pitched at a level that encourages student participation. Students interested in receiving credit for attending the seminars may sign up with individual faculty members for some guided readings on a special topic. Please see Brent Coull for details.

October 24 (Kresge 212) Canceled

Evan Peet, Ph.D.
Research Fellow, Department of Global Health and Population, Harvard School of Public Health

"Environment and Human Capital: The Effects of Early-Life Pollution Exposure in the Philippines"
ABSTRACT: Human capital, a determining factor in individual labor market and macroeconomic outcomes, is malleable to early-life investments and insults. This study examines the long-term human capital impacts of early-life exposure to criteria air pollutants in the developing economy context of Metropolitan Cebu, Philippines. A three-decade, longitudinal survey containing frequent measures of human capital is combined with macro- and micro-environmental databases characterizing exposure to carbon monoxide and ozone. An instrumental variable strategy corrects the bias from unobserved heterogeneity and measurement error. Findings indicate that height and cognition - correlates and measures of human capital - are negatively affected by increased early-life exposures. Impacts to labor market outcomes, including hours worked and earnings, vary by gender and labor sector. Carbon monoxide exposure is consistently detrimental to both height and cognition while the effects of ozone exposure grow over time and are highly detrimental to cognition and earnings. In present value terms, a nationwide 10% policy reduction in carbon monoxide and ozone levels would annually generate approximately $5.15 billion in discounted lifetime earnings per annual birth cohort.

November 7 (Kresge G2)

Elizabeth Smoot
Doctoral Student, Department of Biostatistics, Harvard University

"Hospital Admission Causes Related to Acute Fine Particulate Air Pollution Exposure in Older Adults"
ABSTRACT: Exposure to air pollutants adversely affects human health, but the full scope of this impact is unknown. Studies to date have largely examined the magnitude of air pollution's effect on a set of pre-specified health conditions, rather than investigating a wide spectrum of conditions making no a priory assumptions. We aim to identify the full range of reasons for hospitalization in the older US population associated with short-term exposure to fine-particulate matter (PM2.5) air pollution, while accounting for temporal trends in hospital admission rates and PM2.5 levels.

November 14

Mariel Finucane, Ph.D.
Biostatistician, Mathematica Policy Research

"Bayesian Estimation of Trends in Population-Level Health Metrics Using Disparate Data Sources"
ABSTRACT: Rational priority setting in global health requires rigorous quantification of worldwide, population-level trends in health status. Because global-level surveys are not available, researchers are forced to rely on country-level and local data that are often sparse, fragmentary, or unreliable. We present a Bayesian model that addresses this problem by systematically combining data from disparate sources to make country-level estimates of trends in important health metrics for all nations. The model uses Markov random field methods to allow for nonlinear trends and a hierarchical structure to borrow strength within and across regional country clusters. MCMC sampling facilitates inference in a high-dimensional, constrained parameter space, while providing posterior draws that enable straightforward inference on the wide variety of functionals of interest. Throughout, the Bayesian approach accounts for uncertainty resulting from data missingness, as well as sampling and parameter uncertainty.

In this talk, I will present results for two example health metrics. First, I will discuss trends in hypertension, a primary risk factor for cardiovascular disease the leading cause of death worldwide. I will then turn to malnutrition, an important contributor to childhood morbidity and mortality in low-income regions. As all levels of mild, moderate, and severe malnutrition are of clinical and public health importance, I will present an extension of the model that uses a finite normal mixture to estimate the shape of the distributions for markers of malnutrition. The model incorporates both individual-level data when available, as well as aggregated summary statistics from studies for which individual-level data could not be obtained.

This work addresses three important problems that often arise in the fields of public health surveillance and global health monitoring. First, data are always incomplete. Second, data from different sources are often incomparable. Third, standard techniques fail to provide estimates of the full distributions of health metrics, the tails of which are often of substantive interest.

February 6

Jonathan Levy, SD
Professor of Public Health, Boston University School

"Talk Title TBD"
ABSTRACT: None Given

February 20

Joseph Antonelli
Doctoral Student, Department of Biostatistics, Harvard University

"Two Dimensional Wavelet Decomposition on Irregular Grids With Application to Satellite PM2.5 Data "
ABSTRACT: None Given

March 6

Shelley Liu
Doctoral Student, Department of Biostatistics, Harvard University

"Statistical Methods for Complex Mixtures and Time-varying Exposures"
ABSTRACT: None Given

April 3

Tristan Hayeck
Doctoral Student, Department of Biostatistics, Harvard University

"2-Step Bayesian Model Averaging for Improved Causal Effect Estimation"
ABSTRACT: None Given

April 17

To Be Announced

"Talk Title TBD"
ABSTRACT: None Given

May 1

Michelle L. Bell, Ph.D.
Professor of Environmental Health, Yale University School of Forestry and Environmental Studies

"Talk Title TBD"
ABSTRACT: None Given

May 15

Joshua Warren, Ph.D.
Assistant Professor, Department of Biostatistics, Yale School of Public Health

"Talk Title TBD"
ABSTRACT: None Given

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Last Update: December 10, 2014