Global Positioning Systems (GPS) are increasingly applied in activity studies, yet significant theoretical and methodological challenges remain. This paper presents a framework for integrating GPS data with other technologies to create dynamic representations of behaviors in context. Utilizing more accurate and sensitive measures to link behavior and environmental exposures allows for new research questions and methods to be developed.

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Purpose To assess validity of the Personal Activity Location Measurement System (PALMS) for deriving time spent walking/running, bicycling, and in vehicle, using SenseCam as the comparison. Methods 40 adult cyclists wore a Qstarz BT-Q1000XT GPS data logger and SenseCam (camera worn around neck capturing multiple images every minute) for a mean of 4 days. PALMS used distance and speed between GPS points to classify whether each minute was part of a trip (yes/no), and if so, the trip mode (walking/running, bicycling, in vehicle). SenseCam images were annotated to create the same classifications (i.e., trip yes/no and mode). 2×2 contingency tables and confusion matrices were calculated at the minute-level for PALMS vs. SenseCam classifications. Mixed-effects linear regression models estimated agreement (mean differences and intraclass correlations [ICCs]) between PALMS and SenseCam with regards to minutes/day in each mode. Results Minute-level sensitivity, specificity, and negative predictive value were ≥88%, and positive predictive value was ≥75% for non mode-specific trip detection. 72–80% of outdoor walking/running minutes, 73% of bicycling minutes, and 74–76% of in-vehicle minutes were correctly classified by PALMS. For minutes/day, PALMS had a mean bias (i.e., amount of over or under estimation) of 2.4–3.1 minutes (11–15%) for walking/running, 2.3–2.9 minutes (7–9%) for bicycling, and 4.3–5 minutes (15–17%) for vehicle time. ICCs were ≥.80 for all modes. Conclusions PALMS has validity for processing GPS data to objectively measure time walking/running, bicycling, and in vehicle in population studies. Assessing travel patterns is one of many valuable applications of GPS in physical activity research that can improve our understanding of the determinants and health outcomes of active transportation as well as its impact on physical activity.

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Objectives The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sociocultural Ancillary Study aims to examine associations between sociocultural and psychosocial factors and cardiovascular disease (CVD) and metabolic syndrome prevalence in Hispanics/Latinos. The conceptual framework is based on the Reserve Capacity and Lifespan Biopsychosocial Models, which emphasize multiple risk and protective pathways underlying socioeconomic and ethnic influences in health. This study describes the rationale, participants, and procedures for the HCHS/SOL Sociocultural Ancillary Study. Design and Setting The Sociocultural Ancillary Study to the HCHS/SOL is a cross-sectional cohort study with future opportunities for prospective investigation. Participants Participants were 5,313 adults, aged 18-74 years, of self-identified Hispanic/Latino descent and representing multiple Hispanic/Latino background groups, recruited from the Bronx, NY, Chicago, IL, Miami, FL, and San Diego, CA. Intervention Participants completed an interview-administered sociocultural assessment battery within 9 months of their HCHS/SOL clinical baseline exam. Outcome Measures The primary outcomes are CVD and the metabolic syndrome and its component risk factors. Results The Sociocultural Ancillary Study sample is broadly representative of the HCHS/SOL cohort. Weighted demographics are: 55% male, 56% 18-44 years, 44% 45 years and older, and 37% Mexican, 20% Cuban, 16% Puerto Rican, 12% Dominican, 8% Central American, and 5% South American descent. Conclusions By testing theoretically driven hypotheses concerning sociocultural and psychosocial factors in CVD, the Sociocultural Ancillary Study seeks to inform future prevention and intervention efforts for U.S. Hispanic/Latinos.