Katherine Bartley

Using GPS data to study neighborhood walkability and physical activity

INTRODUCTION Urban form characteristics intended to support pedestrian activity, collectively referred to as neighborhood walkability, are thought to increase total physical activity. However, little is known about how neighborhood walkability influences utilization of neighborhood space by residents and their overall physical activity. METHODS Sociodemographic information and data on mobility and physical activity over 1-week periods measured by GPS loggers and accelerometers were collected from 803 residents of New York City between November 2010 and November 2011. Potentially accessible neighborhood areas were defined as land area within a 1-kilometer distance of the subjects home (radial buffer) and within a 1-kilometer journey on the street network from the home (network buffer). To define actual areas utilized by subjects, a minimum convex polygon was plotted around GPS waypoints falling within 1 kilometer of the home. A neighborhood walkability scale was calculated for each neighborhood area. Data were analyzed in 2014. RESULTS Total residential neighborhood space utilized by subjects was significantly associated with street intersection density and was significantly negatively associated with residential density and subway stop density within 1 kilometer of the home. Walkability scale scores were significantly higher within utilized as compared with non-utilized neighborhood areas. Neighborhood walkability in the utilized neighborhood area was positively associated with total weekly physical activity (32% [95% CI=17%, 49%] more minutes of moderate-equivalent physical activity across the interquartile range of walkability). CONCLUSION Neighborhood walkability is associated with neighborhood spaces utilized by residents and total weekly physical activity.

Measurement Error of Self-Reported Physical Activity Levels in New York City: Assessment and Correction

Because it is difficult to objectively measure population-level physical activity levels, self-reported measures have been used as a surveillance tool. However, little is known about their validity in populations living in dense urban areas. We aimed to assess the validity of self-reported physical activity data against accelerometer-based measurements among adults living in New York City and to apply a practical tool to adjust for measurement error in complex sample data using a regression calibration method. We used 2 components of data: 1) dual-frame random digit dialing telephone survey data from 3,806 adults in 2010-2011 and 2) accelerometer data from a subsample of 679 survey participants. Self-reported physical activity levels were measured using a version of the Global Physical Activity Questionnaire, whereas data on weekly moderate-equivalent minutes of activity were collected using accelerometers. Two self-reported health measures (obesity and diabetes) were included as outcomes. Participants with higher accelerometer values were more likely to underreport the actual levels. (Accelerometer values were considered to be the reference values.) After correcting for measurement errors, we found that associations between outcomes and physical activity levels were substantially deattenuated. Despite difficulties in accurately monitoring physical activity levels in dense urban areas using self-reported data, our findings show the importance of performing a well-designed validation study because it allows for understanding and correcting measurement errors.

Sodium Intake in a Cross-Sectional, Representative Sample of New York City Adults

OBJECTIVES We estimated sodium intake, which is associated with elevated blood pressure, a major risk factor for cardiovascular disease, and assessed its association with related variables among New York City adults. METHODS In 2010 we conducted a cross-sectional, population-based survey of 1656 adults, the Heart Follow-Up Study, that collected self-reported health information, measured blood pressure, and obtained sodium, potassium, and creatinine values from 24-hour urine collections. RESULTS Mean daily sodium intake was 3239 milligrams per day; 81% of participants exceeded their recommended limit. Sodium intake was higher in non-Hispanic Blacks (3477 mg/d) and Hispanics (3395 mg/d) than in non-Hispanic Whites (3066 mg/d; both P < .05). Higher sodium intake was associated with higher blood pressure in adjusted models, and this association varied by race/ethnicity. CONCLUSIONS Higher sodium intake among non-Hispanic Blacks and Hispanics than among Whites was not previously documented in population surveys relying on self-report. These results demonstrate the feasibility of 24-hour urine collection for the purposes of research, surveillance, and program evaluation.

Potassium and fruit and vegetable intakes in relation to social determinants and access to produce in New York City

BACKGROUND Potassium-rich diets are inversely associated with blood pressure. Potassium intake before this study had not been objectively measured by using potassium excretion in a population-based sample in the United States. OBJECTIVES The objectives of the analysis were to 1) report mean potassium excretion in a diverse urban population by using 24-h urine collections, 2) corroborate potassium excretion by using self-reported fruit and vegetable consumption, and 3) characterize associations between potassium excretion and socioeconomic indicators and access to produce. DESIGN Participants were from the 2010 Community Health Survey Heart Follow-Up Study-a population-based study including data from 24-h urine collections. The final sample of 1656 adults was weighted to be representative of New York City (NYC) adults as a whole. RESULTS Mean urinary potassium excretion was 2180 mg/d, and mean self-reported fruit and vegetable intake was 2.5 servings/d. Adjusted urinary potassium excretion was 21% lower in blacks than in whites (P < 0.001), 13% lower in non-college graduates than in college graduates (P < 0.001), and 9% lower in the lowest-income than in the highest-income group (P = 0.03). Potassium excretion was correlated with fruit and vegetable intake. Most NYC residents reported a <10-min walk to fresh fruit and vegetables; this indicator of access was not associated with potassium excretion or fruit and vegetable intake. CONCLUSIONS Potassium intake is low in NYC adults, especially in lower socioeconomic groups. Innovative programs that increase fruit and vegetable intake may help increase dietary potassium and reduce hypertension-related disease. This trial is registered at clinicaltrials.gov as NCT01889589.

Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study

Introduction: Electronic health records (EHRs) can potentially extend chronic disease surveillance, but few EHR-based initiatives tracking population-based metrics have been validated for accuracy. We designed a new EHR-based population health surveillance system for New York City (NYC) known as NYC Macroscope. This report is the third in a 3-part series describing the development and validation of that system. The first report describes governance and technical infrastructure underlying the NYC Macroscope. The second report describes validation methods and presents validation results for estimates of obesity, smoking, depression and influenza vaccination. In this third paper we present validation findings for metabolic indicators (hypertension, hyperlipidemia, diabetes). Methods: We compared EHR-based estimates to those from a gold standard surveillance source - the 2013–2014 NYC Health and Nutrition Examination Survey (NYC HANES) - overall and stratified by sex and age group, using the two one-sided test of equivalence and other validation criteria. Results: EHR-based hypertension prevalence estimates were highly concordant with NYC HANES estimates. Diabetes prevalence estimates were highly concordant when measuring diagnosed diabetes but less so when incorporating laboratory results. Hypercholesterolemia prevalence estimates were less concordant overall. Measures to assess treatment and control of the 3 metabolic conditions performed poorly. Discussion: While indicator performance was variable, findings here confirm that a carefully constructed EHR-based surveillance system can generate prevalence estimates comparable to those from gold-standard examination surveys for certain metabolic conditions such as hypertension and diabetes. Conclusions: Standardized EHR metrics have potential utility for surveillance at lower annual costs than surveys, especially as representativeness of contributing clinical practices to EHR-based surveillance systems increases.

Self-Reported Sitting Time in New York City Adults, The Physical Activity and Transit Survey, 2010–2011

Introduction Recent studies have demonstrated the negative health consequences associated with extended sitting time, including metabolic disturbances and decreased life expectancy. The objectives of this study were to characterize sitting time in an urban adult population and assess the validity of a 2-question method of self-reported sitting time. Methods The New York City Health Department conducted the 2010–2011 Physical Activity and Transit Survey (N = 3,597); a subset of participants wore accelerometers for 1 week (n = 667). Self-reported sitting time was assessed from 2 questions on time spent sitting (daytime and evening hours). Sedentary time was defined as accelerometer minutes with less than 100 counts on valid days. Descriptive statistics were used to estimate the prevalence of sitting time by demographic characteristics. Validity of sitting time with accelerometer-measured sedentary time was assessed using Spearman’s correlation and Bland-Altman techniques. All data were weighted to be representative of the New York City adult population based on the 2006–2008 American Community Survey. Results Mean daily self-reported sitting time was 423 minutes; mean accelerometer-measured sedentary time was 490 minutes per day (r = 0.32, P < .001). The mean difference was 49 minutes per day (limits of agreement: −441 to 343). Sitting time was higher in respondents at lower poverty and higher education levels and lower in Hispanics and people who were foreign-born. Conclusion Participants of higher socioeconomic status, who are not typically the focus of health disparities–related research, had the highest sitting times; Hispanics had the lowest levels. Sitting time may be accurately assessed by self-report with the 2-question method for population surveillance but may be limited in accurately characterizing individual-level behavior.