Mobile Health Technology
For many of our newer studies, we are using custom-made highly secure, smartphone applications to determine where participants spend their time, and how physically active they are. This allows us to examine time-activity patterns, and to develop a more comprehensive picture of exposures than we can get from a home or work address alone.
We currently have two major mobile health studies we are utilizing
Nurses' Health Study 3 Mobile Health Study
Among almost 500 women in NHS3, participants in this substudy provided location data and wore FitBits for seven day periods, four times over a year.
Nurses' Health Study 3 and Growing Up Today Study Beiwe Study
Using the open source Beiwe smartphone app, almost 2400 NHS3 and GUTS participants provided up to a year of data on location, movement, and short questionnaires
Select recent articles
Yi L, Hart JE, Straczkiewicz M, Karas M, Wilt GE, Hu CR, Librett R, Laden F, Chavarro JE, Onnela JP, James P. Measuring environmental and behavioral drivers of chronic diseases using smartphone-based digital phenotyping: Intensive longitudinal observational mHealth substudy embedded in 2 prospective cohorts of adults. JMIR Public Health Surveill. 2024; 10:e55170. PubMed PMID: 39393682.
Hu CR, Delaney C, Chavarro JE, Laden F, Librett R, Katuska L, Kaplan ER, Yi L, Rueschman M, Kossowsky J, Onella JP, Coull BA, Redline S, James P, Hart JE. Quantification of differences in sleep measurement by a wrist-worn consumer wearable compared to research-grade accelerometry and sleep diaries of female adults in free-living conditions. Nat Sci Sleep. 2025; 17:1973. PubMed PMID: 40901279.
Yi L, Hart JE, Wilt G, Hu CR, Jimenez MP, Lin PID, Suel E, Hystad P, Hankey S, Zhang W, Chavarro JE, Laden F, James P. GPS-based street-view greenspace exposure and wearable assessed physical-activity in a prospective cohort of US women. Int J Behav Nutr Phys Act. 2025; 22(1): 92. PubMed PMID: 40619433.
Hu CR, Wilt GE, Roscoe C, Iyer HS, Kessler WH, Laden F, Chavarro JE, Coull BA, Redline S, James P, Hart JE. Associations of seasonally available global positioning systems-derived walkability and objectively measured sleep in the Nurses’ Health Study 3 Mobile Health Study. Environ Epidemiol. 2024; 8(6):e348. PubMed PMID: 39399736.
Current and Recent Funding
NIH/NIEHS R01 ES035736-01A1: Environmental and social determinants of mammographic features
Percent mammographic density (PMD) is one of the strongest risk factors for, and is considered an intermediate marker of, breast cancer. Recent wide spread uptake of digital mammography, and advances in image analyses have identified additional mammographic features including texture variation (gray-scale and spatial variation) in breast density and deep learning-based risk scores that predict breast cancer risk independent of PMD. Because of the strong associations with breast cancer risk there is a need to identify potential modifiable risk factors of mammographic features. Using the resources of the nationwide prospective Nurses’ Health Study 3 (NHS3), we are uniquely positioned to study the complex associations of multiple environmental exposures and SDOH on mammographic features predictive of breast cancer.
NIH/NIEHS R01 ES028712-01: The Effects of Environmental Exposures on Semen Quality and the Sperm Epigenome
The aims of this project are to assess the impact of multiple environmental exposures (air pollution and endocrine disruptors) on measures of semen quality (concentration, total count, and motility) assessed via cell phone, morphology assessed with standard laboratory methods, and novel epigenomic markers (sperm DNA methylation).
NIH/NCI R00 CA201542: High Resolution Measures of Behavioral Cancer Risk Factors from Mobile Technology
This project is exploring the relationships between geographic context, physical activity, sleep, and obesity by deploying smartphone applications and wearable devices within a subsample (n=500) of the Nurses’ Health Study 3 (NHS3).