DFSA Awardee Abstracts

Activation Awardees, 2021

DuanRui Duan, Assistant Professor, Biostatistics
TransPRS: a Federated Transfer Learning Framework for Improving Polygenic Risk Prediction in Underrepresented Populations

Polygenic risk scores (PRS) have shown promising potentials for early disease detection, prevention and intervention. However, as existing genome-wide studies were predominantly conducted in European-ancestry (EA) populations, the performance of PRS is much poor in non-EA populations compared with EA populations, which may exacerbate existing health disparities. The goal of our proposed work is to develop novel transfer and federated learning methods to improve the performance of PRS in underrepresented populations, leveraging multiple datasets and existing evidence across diverse ancestries. We will (1) develop a transfer learning framework based on penalized high-dimensional regressions, which transfer the shared genetic architectures learned from individual-level datasets and available GWAS summary statistics to a target underrepresented population while accounting for the heterogeneity across populations; (2) develop communication efficient federated learning algorithms to increase the training sample size of an underrepresented population by incorporating data from multiple biobanks with communication efficiency and individual level privacy protection. Completion of this project will lead to novel tools that produce high quality PRS with better predictive performance, which can ultimately help advance precision medicine and reduce the disparity in PRS-based research.

SanaikAnna Sinaiko, Assistant Professor, Health Policy and Management
Utilization and Impact of a Novel Form of Out-of-Pocket Cost Information for Prescription Drugs on Prescribing Decisions

Patients’ top concern with the health care system is the affordability of health care, especially prescription drugs. While some increased patient expenditure on medications reflects the development and high prices of new specialty drugs, there is ample evidence that physicians often use more expensive agents when there are less costly, equally effective medications available. Price transparency tools that help clinicians and patients identify and prescribe lower-cost drugs thus have the potential to improve medication adherence and lower patient spending. “Real-Time Benefit Check” for medication (mRTBC) is a novel medication price transparency tool that provides patient-personalized, real-time, out-of-pocket price estimates for medications in the electronic medical record; the price estimates are available to clinician prescribers when they are most salient. In this project we will link clinical medication order data to detailed price transparency tool data from a large, diverse health system to examine use of mRTBC, whether clinicians switch their medication choices after viewing patients’ medication prices, and how this varies with condition, patient, and clinician characteristics, and across diverse ambulatory settings. These findings will inform future support of price transparency policy and future research on how mRTBC tools affect access to and spending on prescription drugs.

Mingyang Song, Assistant Professor, Epidemiology
Microbiome-based Approach for Improved Colorectal Cancer Prevention with Dietary Fiber and Beyond

It remains unknown how diet and the gut microbiome may interact to influence long-term risk of colorectal cancer. Short-chain fatty acids, a family of gut bacterial fermentation products of fiber, have been suggested to protect against colorectal cancer by epigenetic regulation and immune modulation. The project aims to characterize the interplay between dietary pattern, gut microbial features, and risk of colorectal cancer. Our overarching hypothesis is that a dietary pattern that enhances the potential of microbial production of short-chain fatty acids reduces risk of colorectal cancer by counteracting the pro-colorectal cancer effects of F. nucleatum and pks+ E. coli. We will test this hypothesis by developing a dietary pattern that enhances the microbial production of short-chain fatty acids and assessing the dietary pattern in relation to risk of colorectal cancer, overall and according to tumoral levels of F. nucleatum and pks+ E. coli. Leveraging the unique integrated dietary and gut metagenomics data collected in 3 cohorts with over 20-30 years, our project will provide critical preliminary data for further interventional studies on the interplay between diet and the gut microbiome in cancer and shed light on microbiome-based strategies to complement or optimize the current diet-based approaches for cancer prevention.

Activation Awardees, 2020

Jessica Cohen, Associate Professor, Global Health and Population
Evidence-based Policy for Maternal and Child Health: A Quasi-experimental Evaluation of the Impact of Innovative Medicaid Policies on Women’s Use of Effective Postpartum Contraception and Birth Spacing

The early postpartum period is a critical window for addressing women’s health. Effective postpartum contraception is crucial for preventing unintended and short-interval pregnancies, which are associated with adverse infant outcomes. Long-acting reversible contraceptive (LARC) methods are highly effective and safe, but are used by very few postpartum women. In an effort to increase access to LARCs, many state Medicaid programs have begun offering providers payment for immediate postpartum LARCs (IPP-LARCs)—i.e. LARCs placed while women are still in the hospital following childbirth—separately from the fixed delivery payment. In recent work, we found that this policy significantly increased IPP-LARC coverage and reduced short-interval births for adolescent women in South Carolina, the first state to implement the policy. While this suggests important benefits of the policy, it is only one state and the broader impacts of the policy on postpartum contraception and safe birth spacing are unknown. This project will use two quasi-experimental approaches to evaluating the impact of this policy in a broader range of states using inpatient and national birth certificate data. Results from this study will provide pilot evidence for a larger proposal to rigorously analyze the impact of this policy on maternal and infant health outcomes.

Carmen Messerlian, Assistant Professor, Environmental Health
The Preconception Intervention Program for Healthy Reproduction Program (PIPER) Project

Infertility and pregnancy loss are common, costly, and emotional outcomes that affect both fertile and subfertile couples. Evidence shows that the preconception period is a window of susceptibility, and exposure to environmental chemicals such phthalates and phenols in both men and women before conception adversely impacts fertility and pregnancy. Phthalates and phenols are found in food and everyday consumer products, and are among the environmental pollutants whose exposures individuals have some agency to modify and control. The potential for modulation means that the preconception period offers an opportunity to intervene and support reproductive health across the lifecourse. Couples trying to conceive desire information on how to improve their preconception health; yet, clinicians have little to offer in terms of evidence-based prevention to support their fertility potential. The aim of the Preconception Intervention Program for Healthy Reproduction (PIPER) Project is to develop, implement, and evaluate a preconception intervention program to reduce male and female phthalate and phenol exposures from diet and personal care products in couples attempting conception at the Beth Israel Deaconess Medical Center. The PIPER Project seeks to address major gaps in the translation of existing observational evidence into prevention focused on promoting environmental-reproductive health in couples during preconception.

Shoba Ramanadhan, Assistant Professor, Social and Behavioral Sciences
New Measures and Professional Development Opportunities to Promote Evidence-based Cancer Prevention and Control in Underserved Communities

Insufficient and uneven delivery of evidence-based preventive services leads to continuing cervical cancer disparities in the US. The US Preventive Services Task Force highlights the importance of community-based organizations (CBOs) to leverage trust-based relationships with members of underserved communities and deliver evidence-based interventions (EBIs) that increase screening and vaccination rates. However, limited staff capacity constrains the use of EBIs in CBOs and attempts to address this mismatch are hindered by 1) a lack of consensus on the core set of skills needed to deliver EBIs and 2) a dearth of validated, context-appropriate measures. Addressing these gaps will support the development of high-impact programs to build capacity for evidence-based cervical cancer prevention in CBOs working with underserved populations. Aim 1 convenes 56 CBO practitioners and researchers to explore capacity for EBI delivery and agree on core skills for CBO staff to deliver EBIs, using a Delphi process. Aim 2 creates and refines new skills measures through cognitive testing (n=16 practitioners) and gathers preliminary psychometric data (e.g., reliability) from 100 practitioners. These efforts will generate rigorous preliminary data and establish collaborations for an R01 to design and evaluate capacity-building interventions that maximize CBOs’ ability to address cervical cancer disparities.

Activation Awards, 2019

Kevin Croke, Assistant Professor, Global Health and Population
The Political Origins of Ethiopia’s Primary Health Care Expansion

Ethiopia’s expansion of primary health care over the past 15 years has been hailed as a model in sub-Saharan Africa. Propelled by this model, the program’s architect, Dr. Tedros Gebreyesus, is now Director-General of the World Health Organization. There is also a global movement to support the expansion of primary health care, which often cites Ethiopia as a model. Starting in 2004, over 30,000 Health Extension Workers were trained and deployed in Ethiopia, and over 15,000 village-level health posts were constructed. As a result, Ethiopia has been described as a present-day successor to earlier primary health care success stories such as Sri Lanka, Kerala (India), Costa Rica, and China. The global health community wants to learn from Ethiopia’s success, but learning from the Ethiopia case means first understanding it. Why did Ethiopia, unlike many nations facing similar health challenges, lead the way on expansion of primary care? Ethiopia’s reforms are widely attributed to strong leadership by the Prime Minister and Minister of Health, but the underlying political factors which incentivized delivery of care to rural populations are rarely analyzed. This project will use a political economy lens to identify the political conditions which enabled Ethiopia’s expansion of primary health.

Lindsay Jaacks, Assistant Professor, Global Health and Population
Empowering Communities to Reduce their Exposures to Environmental Chemicals

The average American is exposed to hundreds of synthetic chemicals every day, many of them through the food system, and the vast majority of them have not been adequately tested for adverse health effects because of the current approach to regulating chemicals in the US. As a result there is a critical need for efficacious interventions that enable consumers to make informed decisions about their exposures and health. We propose to implement a 3-month randomized controlled trial of a widely-accessible mobile app (Detox Me) aimed at changing consumer dietary behaviors (primary outcome), and reducing environmental chemical exposures (bisphenols) and improving metabolic health (secondary outcomes). Ultimately, we hope to scale up this approach in the US and translate it to other settings, specifically developing countries where these exposures are likely to be higher than other regions of the world. The results of this innovative project will be used in an R01 application to the National Institute of Environmental Health Sciences (NIEHS). In addition, this proposal will fill an important collaboration gap at the Harvard TH Chan School of Public Health where few collaborations exist between environmental health and global health faculty.

Zac Nagel, Assistant Professor, Environmental Health
Genomic Integrity Mechanisms Underlying Disparities in Age-related Disease Risk

Substantial disparities exist in the incidence and mortality of age-related diseases, but the biological mechanisms underpinning these disparities remain unclear. Many age related diseases are associated with deficiencies in genome maintenance, and in the case of cancer, there are clear associations between inefficient DNA repair and cancer. However, limitations of the available assays have hampered efforts to measure DNA repair capacity in large populations, and previous studies not been sufficiently diverse for statistical power needed to investigate the role of DNA repair in health disparities. We hypothesize that DNA repair capacity declines with age, and that this decline is accelerated by environmental stresses that disproportionately affect groups with higher cancer risk. We will test our hypothesis and overcome the limitations of previous studies using emerging technologies for measuring DNA repair (FM-HCR, developed by us) and mutagenesis in human blood cells from groups of individuals distinguished by age, sex, race, and poverty status. To do this, we will leverage the extraordinary datasets and prospectively collected blood samples associated with the Health Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study. We expect our results to enable larger studies that will provide insights into a variety of age-related diseases.

Incubation Awardees, 2020

Curtis Huttenhower, Professor, Biostatistics
Machine Learning for Population-scale Viral Discovery and Monitoring in the Human Microbiome

As has been starkly highlighted by the ongoing COVID-19 pandemic, public health tools for viral data science at scale are surprisingly lacking. Even prior to this outbreak, rapidly-evolving viruses are responsible for conditions from the common cold to influenza and gastroenteritis, and while recent work has highlighted their contributions to the human microbiome, few machine learning methods exist to detect and characterize them. This proposal will thus provide first-in-kind discovery of DNA and RNA viruses throughout the human microbiome. Leveraging the resources of the Harvard Chan Center for the Microbiome in Public Health, we will: Computationally screen an existing meta-analysis of shotgun metagenomes and metatranscriptomes (~12,000 total samples) to establish a “parts list” of DNA and RNA viruses, and Specifically target RNA metatranscriptomes for coronavirus discovery, including testing for SARS-CoV-2 homolog carriage and determining the basic epidemiology of circulating human coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1). The project brings together a cross-departmental collaboration in clinical and basic microbiology, epidemiology, and machine learning methods. It provides the main steps necessary for generalizable human microbiome viral data science, as well as the field’s first assessment of resident viruses, such as SARS-CoV-2, across the body and around the globe.

William Hanage, Professor, Epidemiology
Lineage Calling for Outbreak Detection and Molecular Epidemiology of Klebsiella Pneumoniae Using Rapid Nanopore Sequencing

Determining how isolates of drug resistant bacterial pathogens are related is essential to detecting outbreaks, and potential cases of transmission. While genomic methods have brought unbeatable resolution, standard methods to robustly compare genome sequences typically take days at least to generate the genomes, and require bioinformatic support, limiting their utility in the field and the clinic. We plan to develop a method called lineage calling, for use with the major nosocomial and community acquired drug resistant pathogen Klebsiella pneumoniae. Lineage calling searches a database for the closest match to a read generated in real time on an Oxford Nanopore device, sidestepping problems arising from the high error rate that is characteristic of nanopore technology by searching for short k-mers. The method has already been shown to be capable of detecting resistant strains in other pathogens, and this incubator award will fund its extension to a new pathogen, and a novel application, in rapidly identifying outbreaks and transmission to inform infection control.

Incubation Awardees, 2019

Barbara Burleigh, Professor, Immunology and Infectious Diseases
New Tricks with Old Drugs: Improving Chagas Disease Therapeutics

Persistent infection with the protozoan parasite, Trypanosoma cruzi, underlies the development of human Chagas disease, for which treatment options are limited and new therapeutic strategies are urgently needed. In the proposed study, we examine existing trypanocidal drugs with a view to improving efficacy, indirectly, via metabolic modulation. Benznidazole, is considered the first-line therapy for Chagas disease but delivers limited efficacy due to the difficulty of achieving consistently high serum/tissue concentrations, needed to kill tissue-resident parasites, without introducing toxicity. Our preliminary studies demonstrate the ability to lower the LD50 of benznidazole by inhibiting parasite mitochondrial electron transport using the small molecule inhibitor, GNF7686. To identify additional compounds that can potentiate the lethal action of benznidazole, we will screen a collection of potent T. cruzi growth inhibitors made available by GSK. In addition, we will characterize the role that glutamine metabolism plays in sensitizing intracellular T. cruzi amastigotes to a class of anti-fungal azole derivatives, ergosterol biosynthesis inhibitors, with a view to increasing the efficacy of these trypanocidal compounds. This line of investigation may offer novel opportunities to ‘tune’ parasite metabolism toward a state that is more susceptible to the currently available trypanocidal drugs and to improve in vivo efficacy.

David Hemenway, Professor, Health Policy and Management
Improving Firearm Injury Surveillance Systems: A Road Map

The U.S. has a serious firearm injury problem. The first step in the public health approach to preventing injury and violence is to create ongoing data systems (“surveillance systems”) to understand and track the problem and evaluate what works to prevent it. The overarching aim of the current project is to improve surveillance systems for firearm injury. There have been deliberate and successful attempts both not to collect firearm data and to withhold from researchers the data that are collected. While national expert panels have outlined research priorities for understanding how to bring down gun deaths, no group has delineated the necessary data infrastructure to get us there. The proposed project for the first time will create a detailed list of ongoing firearms data that our nation needs and a cost-effective, efficient strategy for building simple systems to deliver these data. We will also describe the data that are collected but made unavailable to researchers, and explain the potential benefits that can be derived from making these available. This project will help people with a variety of perspectives on firearms recognize the importance of data and effectively advocate for this vital information.

Karestan Koenen, Professor, Epidemiology
The Gut Microbiome and PTSD in Women

Posttraumatic stress disorder (PTSD) is a debilitating mental disorder that occurs in some people after exposure to trauma such as physical or sexual violence. Emerging evidence has suggested a potential role of the gut microbiota in mental health. Moreover, gut microbiota are implicated in amygdala development and response; amygdala dysregulation is a key component of PTSD neurocircuitry. Yet, well-powered, systematic studies are needed to answer foundational questions about the role of gut microbiota in PTSD. Our overall objective is to initiate a unique project to evaluate the microbiota-PTSD relationship leveraging available PTSD and whole-genome shotgun sequencing data on the gut microbiota in women from the Nurses Health Study II. This project represents a new collaboration among a multidisciplinary team with expertise in trauma and PTSD epidemiology and microbiome analysis. Our specific aim is to evaluate differences in the gut microbiota in women with and without PTSD by performing both community-level structural/functional analysis and differential species/gene abundance analysis. The proposed research will provide valuable preliminary data to support future research that holds the potential to fundamentally alter our understanding of a biologic basis or sequelae of PTSD and inform the development of microbiota-targeted interventions for preventing or mitigating effects of PTSD.

Michael Mina, Assistant Professor, Epidemiology
High-throughput Surveillance of Immune Histories for the Simultaneous Construction of Longitudinal Cohorts and Comprehensive Epidemic Detection

Infectious diseases are among the greatest threats to human health. Efficient detection, quantitation and surveillance, especially of those causing novel epidemics remains a major problem for public health agencies. Serological surveillance is a bedrock of infectious disease surveillance efforts, but resources often limit the scope of surveillance efforts to small numbers of pathogens and to cross-sectional samples. The objectives of this McLennan Family Fund Incubation Award are to develop two novel public health sero-surveillance tools that can fundamentally improve the landscape of infectious disease surveillance. In Aim I we will develop PADERNS (Phage display for Antibody repertoire Detection and profiling via pathogen Epitope RecognitioN for public health Surveillance) a novel technology that builds on a previously described extremely high throughput phage-display based technology to provide affordable, accessible and comprehensive detection of exposures to all pathogens known to infect humans, using readily accessible sample types and technologies. In Aim 2 we will develop Epi-TRACER (Epitope-based TRacking of (Anonymous) samples using Comprehensive Epitope Recognition) a novel first-in-kind technology that will leverage PADERNS Ab repertoire data to simultaneously detect and construct ‘virtual’ longitudinal cohorts hidden among cross-sectional data to reconstruct exposure histories and epidemic curves for all known human pathogens.

General Acceleration Awardees, 2020


Marcia Castro, Professor, Global Health and Population

Fires, Smoke Exposure, and Public Health in Brazil: Assessment of the Health Impacts of Amazonian Fires

The smoke from fires is a major contributor to the health burden of air pollution, and climate change will likely enhance fire activity as temperatures rise. In the tropical forest of Amazonia, decades of human intervention have led to large numbers of fires being deliberately set to clear land or manage crops. In 2019, Amazonia experienced a significant uptick in fire activity, reversing a ~15-year trend toward fewer fires in the region and releasing massive amounts of smoke. While much attention has been paid to the potential effects of tropical deforestation on climate, less is known about the magnitude of the impacts of the fires on air quality. Here we propose to examine the links between fire activity, smoke emissions, and health in Brazil over the 2015-2020 timeframe. In particular, we will assess the smoke exposure experienced by populations in Brazil living downwind of the Amazon fires. By quantifying smoke exposure and the associated health impacts, we will draw greater attention to the deleterious consequences of continued biomass burning in the region.  The proposed project takes advantage of an ensemble of environmental and health data and applies statistical and atmospheric modeling.


Karestan Koenen, Professor, Epidemiology
COVID-19, Social Unrest, and Health in the Harvard Cohorts

In response to the COVID-19 pandemic, the leading investigators of the Nurses’ Health Study (NHS) II, NHS3 and the Growing Up Today Study (GUTS) recognized the need to response rapidly to this public health crisis and developed online assessments within these cohorts that would be responsive to the rapidly changing social context on health. The broad goal of this proposal is to obtain support to analyze, in real time, data currently being collected via web questionnaire on COVID-19 infection, related stressors (occupational, financial, caregiving), protective factors, mental health and resilience. These cohorts include large numbers of two groups at high risk of adverse physical and mental health outcomes during the COVID-19 crisis: health care workers (HCW) and older adults. Immediate funding would enable us to quickly analyze these data to inform interventions to benefit these two high-risk groups. Data would also be integrated with the rich cohort data for longer-term investigations on the impact of the COVID-19 pandemic. Of note, the platform developed for COVID-19 has also enabled us to be responsive to other rapidly evolving public health issues such as the rise in intimate partner violence during the pandemic and national protests over police brutality.

COVID-19 Acceleration Awardees, 2020

In 2020, a portion of the Acceleration Award funds were targeted to projects submitted in response to a Special COVID-19 RFA.

Michael Barnett, Assistant Professor, Health Policy and Management
Measuring the Resilience of Nursing Homes Facing COVID-19

COVID-19 presents the greatest challenge in recent memory for the frailest, most vulnerable individuals in the US. Already we have seen over 3,600 deaths in skilled nursing facilities (SNFs) alone nationwide as of early April. The fundamentals of SNF care make them especially susceptible to outbreaks, so they are likely to bear the brunt of current and future COVID-19 waves. In the long-run, COVID-19 poses a devastating risk to SNF economic infrastructure, and thus to an essential stream of care provision in the US. Despite the threat posed, we have little knowledge about the capacity for SNFs to implement COVID-19 prevention measures now or their ability to be resilient under the threat of future waves. SNFs have many potential vulnerabilities in the COVID-19 pandemic that are poorly understood, including lack of PPE, staffing shortages, and diminished financial resources. We propose to perform a nationally representative survey of SNF executive directors to address this evidence gap. We will measure how SNFs have responded to COVID-19 and the capacity for continued response. These results will inform policy to allocate funds and provide other resources to support implementation and address the critical weaknesses in SNFs’ capacity now and in future waves.

Jin Ah Park, Assistant Professor, Environmental Health; Phyllis Kanki, Professor, Immunology and Infectious Diseases
Pathogenesis of SARS-CoV-2 Infection in Primary Human Airway Epithelial Cells: Role of Age

To develop effective and safe therapeutic treatments for SARS-CoV-2 infection, understanding the pathogenesis of SARS-CoV-2 at a cellular level is urgently needed. Age is one of the key risk factors associated with disease severity and the higher mortality rate. Thus, we will focus on the role of age in the pathogenesis of SARS-CoV-2 infection. Primary bronchial epithelial (HBE) cells isolated from young and old human donors will be cultured in air-liquid interface (ALI), where ciliated cells express angiotensin converting enzyme 2, the receptor for SARS-CoV-2. We will examine host cell responses, including viral replication, apoptosis, and pyroptosis to determine mechanisms of host cell death, a process linked to the severity of COVID-19. We will also identify preferentially increased cytokines/chemokines in the SARSCoV- 2 infected cells from old donors. These cytokines could potentially be pathogenic mediators that lead to the disease severity and higher mortality and could serve as therapeutic targets. In the EH department, the Park laboratory routinely uses primary HBE cells in ALI. In the IID department, the Kanki lab is an experienced virology BSL-3 laboratory capable of SARS-CoV-2 in vitro studies. Our cross-disciplinary approach will address an urgent and unmet need in research on this novel viral pathogen.

Acceleration Awardees, 2019


Melvin J. and Geraldine L. Glimcher Associate Professor of Immunology and Infectious Diseases, Immunology and Infectious Diseases
Defining the Factors Driving Spatiotemporal Variation in Antibiotic Prescribing

As antibiotic use drives resistance, addressing the challenge of antimicrobial resistance requires first understanding antibiotic use. Outpatient antibiotic prescribing declined around 10% nationwide from 2011-15, but the factors driving this decline are unclear: is this a reflection of better antibiotic stewardship, a decrease in diseases that prompt antibiotic prescribing, or a shift in how people access healthcare? The conventional expectation is that the decline is driven by stewardship. However, in our preliminary results studying the 17% decline in outpatient prescribing in Massachusetts, the decline is primarily due to a reduction in outpatient visits for several categories of infectious diseases, suggesting that a decrease in disease is the main driver. In the project described in this proposal, we will use a nationally representative insurance claims database from 2008-2017 to decompose the spatiotemporal variation in rates of outpatient prescribing into changes in inappropriate prescribing, in infectious diseases incidence, and in access to care as measured by visit volume. By defining the drivers of shifts in antibiotic prescribing levels, the results from this project will challenge status quo assumptions around efforts to reduce resistance and establish a rigorous evidence base to shape efforts to reduce antibiotic prescribing.


Laura Kubzansky
Lee Kum Kee Professor of Social and Behavioral Sciences, Social and Behavioral Sciences
Using Smartphone Measurement Bursts in an Established Epidemiologic Cohort to Capture Psychological Well-being and Health Behaviors

Various dimensions of psychological well-being—both stable traits (e.g., optimism) and time-varying states (e.g., happiness)—are linked to favorable health outcomes including reduced chronic disease risk and greater longevity. Health behaviors (e.g., nutrition) are risk factors for many chronic diseases and could link psychological well-being to health outcomes. However, most research on psychological well-being and behaviors is cross-sectional, impeding assessment of directionality, or draws on brief measurements taken years apart, limiting understanding of a dynamic system. A more granular evaluation of these relationships is critical to determine underlying mechanisms linking psychological well-being to health, and eventually to facilitate designing effective interventions to improve health behaviors. We will evaluate the feasibility of collecting intensive measures of psychological well-being (optimism, happiness) and health behaviors (nutrition, physical activity, sleep) in 200 women from the Nurses’ Health Study 2. Using the validated smartphone Beiwe application, we will implement 1-week sampling periods (“measurement bursts”) twice over a 4-month interval. Psychological and behavioral data will be obtained actively via smartphone surveys, and passively via smartphone accelerometry and phone usage data. This interdisciplinary project will yield preliminary data for a larger grant proposal and generate information regarding implementation of novel data collection techniques for large epidemiological cohorts.


Florence Sprague Norman and Laura Smart Norman Professor of Public Health, Social and Behavioral Sciences
Reducing Stress and Overweight and Obesity-related Chronic Diseases through Big Data and Digital Phenotyping

Obesity is a persistent public health issue in the US. Over the past decade, prevalence of obesity has increased, placing more than one third of the population at an obesity related increased risk for a number of chronic conditions. Mounting evidence suggests that stress increases the risk of overweight and obesity and this may occur via psychological and/or behavioral pathways. The proposed research addresses several gaps in our current understanding of overweight and obesity and the related behaviors. We will examine the relation of a comprehensive assessment of stressors in a well-defined population through the use of an innovative smartphone application and measure daily stressors and the precursors for obesity. This approach will markedly reduce recall bias and inaccurate reporting of stressors, resilience factors, and weight-gaining behaviors – a problem that plagues the literature. This gives us an opportunity to examine how stressors, the responses to them, and their consequences for weight-gaining behaviors vary by social context, since our smartphone app will capture a person’s mobility patterns in real time and provide new insights into how they are linked to the stress process and its health consequences in the daily lives of individuals.