Marta M. Jankowska

Validity of Palms Gps Scoring of Active and Passive Travel Compared with Sensecam

PURPOSE The objective of this study is to assess validity of the personal activity location measurement system (PALMS) for deriving time spent walking/running, bicycling, and in vehicle, using SenseCam (Microsoft, Redmond, WA) as the comparison. METHODS Forty adult cyclists wore a Qstarz BT-Q1000XT GPS data logger (Qstarz International Co., Taipei, Taiwan) and SenseCam (camera worn around the neck capturing multiple images every minute) for a mean time of 4 d. PALMS used distance and speed between global positioning system (GPS) points to classify whether each minute was part of a trip (yes/no), and if so, the trip mode (walking/running, bicycling, or in vehicle). SenseCam images were annotated to create the same classifications (i.e., trip yes/no and mode). Contingency tables (2 × 2) and confusion matrices were calculated at the minute level for PALMS versus SenseCam classifications. Mixed-effects linear regression models estimated agreement (mean differences and intraclass correlation coefficients) between PALMS and SenseCam with regard 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. Seventy-two percent to 80% of outdoor walking/running minutes, 73% of bicycling minutes, and 74%-76% of in-vehicle minutes were correctly classified by PALMS. For minutes per day, PALMS had a mean bias (i.e., amount of over or under estimation) of 2.4-3.1 min (11%-15%) for walking/running, 2.3-2.9 min (7%-9%) for bicycling, and 4.3-5 min (15%-17%) for vehicle time. Intraclass correlation coefficients were ≥0.80 for all modes. CONCLUSIONS PALMS has validity for processing GPS data to objectively measure time spent 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 effect on physical activity.

Connecting the Dots Between Health, Poverty and Place in Accra, Ghana

West Africa has a rapidly growing population, an increasing fraction of which lives in urban informal settlements characterized by inadequate infrastructure and relatively high health risks. Little is known, however, about the spatial or health characteristics of cities in this region or about the spatial inequalities in health within them. In this article we show how we have been creating a data-rich field laboratory in Accra, Ghana, to connect the dots between health, poverty, and place in a large city in West Africa. Our overarching goal is to test the hypothesis that satellite imagery, in combination with census and limited survey data, such as that found in demographic and health surveys (DHSs), can provide clues to the spatial distribution of health inequalities in cities where fewer data exist than those we have collected for Accra. To this end, we have created the first digital boundary file of the city, obtained high spatial resolution satellite imagery for two dates, collected data from a longitudinal panel of 3,200 women spatially distributed throughout Accra, and obtained microlevel data from the census. We have also acquired water, sewerage, and elevation layers and then coupled all of these data with extensive field research on the neighborhood structure of Accra. We show that the proportional abundance of vegetation in a neighborhood serves as a key indicator of local levels of health and well-being and that local perceptions of health risk are not always consistent with objective measures.

Do the Most Vulnerable People Live in the Worst Slums? A Spatial Analysis of Accra, Ghana

Slums are examples of localized communities within third-world urban systems representing a range of vulnerabilities and adaptive capacities. This study examines vulnerability in relation to flooding, environmental degradation, social status, demographics, and health in the slums of Accra, Ghana, by utilizing a place-based approach informed by fieldwork, remote sensing, census data, and geographically weighted regression (GWR). The study objectives are threefold: (1) to move slums from a dichotomous into a continuous classification and examine the spatial patterns of the gradient, (2) to develop measures of vulnerability for a developing world city and model the relationship between slums and vulnerability, and (3) to assess if the most vulnerable individuals live in the worst slums. A previously developed slum index is utilized, and four new measures of vulnerability are developed through principal components analysis (PCA), including a novel component of health vulnerability based on child mortality. Visualizations of the vulnerability measures assess spatial patterns of vulnerability in Accra. Ordinary least squares (OLS), spatial, and GWR model the ability of the slum index to predict the four vulnerability measures. The slum index performs well for three of the four vulnerability measures, but is least able to predict health vulnerability, underscoring the complex relationship between slums and child mortality in Accra. Finally, quintile analysis demonstrates the elevated prevalence of high vulnerability in places with high slum index scores.

Spatial Energetics: Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity.

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward.

Geospatial and Contextual Approaches to Energy Balance and Health.

In the past 15 years, a major research enterprise has emerged that is aimed at understanding associations between geographic and contextual features of the environment (especially the built environment) and elements of human energy balance, including diet, weight and physical activity. Here we highlight aspects of this research area with a particular focus on research and opportunities in the United States as an example. We address four main areas: (1) the importance of valid and comparable data concerning behaviour across geographies; (2) the ongoing need to identify and explore new environmental variables; (3) the challenge of identifying the causally relevant context; and (4) the pressing need for stronger study designs and analytical methods. Additionally, we discuss existing sources of geo-referenced health data which might be exploited by interdisciplinary research teams, personnel challenges and some aspects of funding for geospatial research by the US National Institutes of Health in the past decade, including funding for international collaboration and training opportunities.

Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies

A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development. Cancer Epidemiol Biomarkers Prev; 26(9); 1370–80. ©2017 AACR.

A spatial analysis of climate-related child malnutrition in the Lake Victoria Basin

Despite growing research into the socio-economic aspects of vulnerability [1-3], relatively little work has linked population dynamics with climate change. Understanding the role of population dynamics remains critical. How a given number of people, in a given location and with varying population characteristics may exacerbate or mitigate the impacts of climate change or how, conversely, they may be vulnerable to climate change impacts are basic questions that remain largely unresolved [4]. This paper explores where and to what extent population dynamics intersect with high exposure to climate change. Specifically, in Eastern Africas Lake Victoria Basin (LVB), a climate change/health vulnerability hotspot we have identified in prior research [5], we model child malnutrition vulnerability indices based on climate variables at a 5km spatial resolution.

Agency, access, and Anopheles : neighborhood health perceptions and the implications for community health interventions in Accra, Ghana

Background Social and environmental factors are increasingly recognized for their ability to influence health outcomes at both individual and neighborhood scales in the developing urban world. Yet issues of spatial heterogeneity in these complex environments may obscure unique elements of neighborhood life that may be protective or harmful to human health. Resident perceptions of neighborhood effects on health may help to fill gaps in our interpretation of household survey results and better inform how to plan and execute neighborhood-level health interventions. Objective We evaluate differences in housing and socioeconomic indicators and health, environment, and neighborhood perceptions derived from the analysis of a household survey and a series of focus groups in Accra, Ghana. We then explore how neighborhood perceptions can inform survey results and ultimately neighborhood-level health interventions. Design Eleven focus groups were conducted across a socioeconomically stratified sample of neighborhoods in Accra, Ghana. General inductive themes from the focus groups were analyzed in tandem with data collected in a 2009 household survey of 2,814 women. In-depth vignettes expand upon the three most salient emergent themes. Results Household and socioeconomic characteristics derived from the focus groups corroborated findings from the survey data. Focus group and survey results diverged for three complex health issues: malaria, health-care access, and sense of personal agency in promoting good health. Conclusion Three vignettes reflecting community views about malaria, health-care access, and sense of personal agency in promoting good health highlight the challenges facing community health interventions in Accra and exemplify how qualitatively derived neighborhood-level health effects can help shape health interventions.

Climate-Related Child Undernutrition in the Lake Victoria Basin: An Integrated Spatial Analysis of Health Surveys, NDVI, and Precipitation Data

Despite growing research into the socio-economic aspects of vulnerability [1]-[4], relatively little work has linked population dynamics with climate change beyond the complex relationship between migration and climate change [5]. It is likely, however, that most people experience climate change in situ, so understanding the role of population dynamics remains critical. How a given number of people, in a given location and with varying population characteristics may exacerbate or mitigate the impacts of climate change or how, conversely, they may be vulnerable to climate change impacts are basic questions that remain largely unresolved [6]. This paper explores where and to what extent population dynamics intersect with high exposure to climate change. Specifically, in Eastern Africas Lake Victoria Basin (LVB), a climate change/health vulnerability hotspot we have identified in prior research [7], we model child undernutrition vulnerability indices based on climate variables, including proxy measures (NDVI) derived from satellite imagery, at a 5-km spatial resolution. Results suggest that vegetation changes associated with precipitation decline in rural areas of sub-Saharan Africa can help predict deteriorating child health.

Neighborhoods of Health: Comparing Boundaries for Measuring Contextual Effects on Health in Accra, Ghana

The concept of neighborhood is at the forefront of place and health research as an appropriate scale of study (Sampson 2003; Riva et al. 2007). What actually constitutes a neighborhood is subjective at best, but an underlying idea of a geographic unit of limited size with some degree of social interaction is generally acknowledged (Weiss et al. 2007). The last two decades have seen significant evidence that the neighborhood influences health beyond individual characteristics in the developed and developing world (Pickett and Pearl 2001; Sampson et al. 2002; Stafford and Marmot 2003; Montgomery and Hewett 2005; Perera et al. 2009; Diez-Roux 1998; Robert 1999). While there are a number of issues for health and place research, establishing geographical boundaries that define ‘place’ has been the subject of significant debate in the field (Diez Roux 2001; Entwisle 2007; Gauvin et al. 2007).