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This is the first study to show that individuals with higher levels of antibody to CMV experience a more-rapid rate of cognitive decline than those with lower levels. Understanding the mechanisms by which CMV influences cognition may aid development of intervention strategies targeting infection, viral reactivation, and immune response over the life course.

Studies examining urban health and the environment must ensure comparability of measures across cities and countries. We describe a data platform and process that integrates health outcomes together with physical and social environment data to examine multilevel aspects of health across cities in 11 Latin American countries. We used two complementary sources to identify cities with ≥ 100,000 inhabitants as of 2010 in Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico, Nicaragua, Panama, and Peru. We defined cities in three ways: administratively, quantitatively from satellite imagery, and based on country-defined metropolitan areas. In addition to “cities,” we identified sub-city units and smaller neighborhoods within them using census hierarchies. Selected physical environment (e.g., urban form, air pollution and transport) and social environment (e.g., income, education, safety) data were compiled for cities, sub-city units, and neighborhoods whenever possible using a range of sources. Harmonized mortality and health survey data were linked to city and sub-city units. Finer georeferencing is underway. We identified 371 cities and 1436 sub-city units in the 11 countries. The median city population was 234,553 inhabitants (IQR 141,942; 500,398). The systematic organization of cities, the initial task of this platform, was accomplished and further ongoing developments include the harmonization of mortality and survey measures using available sources for between country comparisons. A range of physical and social environment indicators can be created using available data. The flexible multilevel data structure accommodates heterogeneity in the data available and allows for varied multilevel research questions related to the associations of physical and social environment variables with variability in health outcomes within and across cities. The creation of such data platforms holds great promise to support researching with greater granularity the field of urban health in Latin America as well as serving as a resource for the evaluation of policies oriented to improve the health and environmental sustainability of cities.

Background Walk Score® and Transit Score® are open-source measures of the neighborhood built environment to support walking (“walkability”) and access to transportation. Purpose To investigate associations of Street Smart Walk Score and Transit Score with self-reported transport and leisure walking using data from a large multi-city and diverse population-based sample of adults. Methods Data from a sample of 4552 residents of Baltimore MD; Chicago IL; Forsyth County NC; Los Angeles CA; New York NY; and St. Paul MN from the Multi-Ethnic Study of Atherosclerosis (2010–2012) were linked to Walk Score and Transit Score (collected in 2012). Logistic and linear regression models estimated ORs of not walking and mean differences in minutes walked, respectively, associated with continuous and categoric Walk Score and Transit Score. All analyses were conducted in 2012. Results After adjustment for site, key sociodemographic, and health variables, a higher Walk Score was associated with lower odds of not walking for transport and more minutes/week of transport walking. Compared to those in a “walker’s paradise,” lower categories of Walk Score were associated with a linear increase in odds of not transport walking and a decline in minutes of leisure walking. An increase in Transit Score was associated with lower odds of not transport walking or leisure walking, and additional minutes/week of leisure walking. Conclusions Walk Score and Transit Score appear to be useful as measures of walkability in analyses of neighborhood effects.

Objective To investigate whether moving to neighborhoods with closer proximity of destinations and greater street connectivity is associated with more walking, a greater probability of meeting the “Every Body Walk!” campaign goals (≥150 min/week of walking), and reductions in body mass index (BMI). Methods Longitudinal data from 701 participants who moved between two waves of the Multi-Ethnic Study of Atherosclerosis (2004–2012) were linked to a neighborhood walkability measure (Street Smart Walk Score®) for each residential location. Fixed effects models were used to estimate if changes in walkability resulting from relocation are associated with simultaneous changes in walking behaviors and BMI. Results Moving to a location with a 10 point higher Walk Score® was associated with a 16.04 minutes/week (Confidence Intervals (CI) 5.13, 29.96) increase in transport walking, 11% higher odds of meeting “Every Body Walk!” goals through transport walking (Adjusted Odds Ratio 1.11; CI 1.02, 1.21), and a 0.06 kg/m2 (CI −0.12, −0.01) reduction in BMI. Change in walkability was not associated with change in leisure walking. Conclusions These findings illustrate the potential for neighborhood infrastructure to support health-enhancing behaviors and overall health of Americans.