Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

Abstract

Previous research has highlighted the salience of spatial stigma on the lives of low-income residents, but has been theoretical in nature and/or has predominantly utilised qualitative methods with limited generalisability and ability to draw associations between spatial stigma and measured cardiovascular health outcomes. The primary objective of this study was to evaluate relationships between perceived spatial stigma, body mass index (BMI), and blood pressure among a sample of low-income housing residents in New York City (NYC). Data come from the community-based NYC Low-income Housing, Neighborhoods and Health Study. We completed a crosssectional analysis with survey data, which included the four items on spatial stigma, as well objectively measured BMI and blood pressure data (analytic n=116; 96.7% of the total sample). Global positioning systems (GPS) tracking of the sample was conducted for a week. In multivariable models (controlling for individual-level age, gender, race/ethnicity, education level, employment status, total household income, neighborhood percent non-Hispanic Black and neighborhood median household income) we found that participants who reported living in an area with a bad neighborhood reputation had higher BMI (B=4.2, 95%CI: -0.01, 8.3, P=0.051), as well as higher systolic blood pressure (B=13.2, 95%CI: 3.2, 23.1, P=0.01) and diastolic blood pressure (B=8.5, 95%CI: 2.8, 14.3, P=0.004). In addition, participants who reported living in an area with a bad neighborhood reputation had increased risk of obesity/overweight [relative risk (RR)=1.32, 95%CI: 1.1, 1.4, P=0.02) and hypertension/pre-hypertension (RR=1.66, 95%CI: 1.2, 2.4, P=0.007). However, we found no differences in spatial mobility (based GPS data) among participants who reported living in neighborhoods with and without spatial stigma (P>0.05). Further research is needed to investigate how placebased stigma may be associated with impaired cardiovascular health among individuals in stigmatised neighborhoods to inform effective cardiovascular risk reduction interventions.

Acceptability of smartphone text- and voice-based ecological momentary assessment (EMA) methods among low income housing residents in New York City

“…The blood pressure and BMI protocols have been described in detail elsewhere and were collected at our research office the day the survey was administered [ 27 , 28 ]. In brief, participant height and weight were measured to the nearest tenth of a centimeter and to the nearest tenth of a kilogram.…”

“…Consequently, our findings might not be generalizable to all low-income populations, including those in other geographic regions especially those in rural geographies. However, our sample included a diverse sample of low-income adults across different NYC neighborhoods [ 27 ]. Also, given that 20% of Americans now live in the 100 largest cities, and more than 70% of Americans living in urban areas with urbanization still on the rise, the relevance is large and growing [ 33 ].…”

Residential and GPS-Defined Activity Space Neighborhood Noise Complaints, Body Mass Index and Blood Pressure Among Low-Income Housing Residents in New York City

“…We computed BMI for each participant: weight in kilograms/(height in meter) 2 . In addition, participants were instructed to sit in a back supported chair during the measurement of BP while they were outstretching their arms and were not crossing their legs [36-38]. Approximately 15-30 seconds after participants seated, research assistants measured participant's systolic and diastolic BP (millimeter of mercury [mmHg]) using a Welch Allyn Vital Signs 300 monitor.…”

Neighborhood reputations as symbolic and stratifying mechanisms in the urban hierarchy

“…The Japanese study finds this relationship to be stronger for men and the highly educated, possibly because they respond differently to discrimination. Neighborhood reputations are also linked to sleep quality (Ruff et al, 2018) and body mass index (BMI) and blood pressure (Duncan et al, 2016).…”