Data come from the NYC Low Income Housing, Neighborhoods, and Health Study, a community-based study of neighborhood environments and cardiovascular health among low income housing residents, which has been described elsewhere in detail [25, 26]. Briefly, the overall study included 120 low-income residents, most of whom reported living in public housing. This was a convenience sample, as participants were recruited through community-based approaches, which included distributing flyers outside four selected public housing developments in the Manhattan and Queens boroughs of NYC. In addition, we recruited through flyers posted and circulated by community-based organizations that work with low-income individuals, flyers posted in community locations, and through word of mouth. Inclusion criteria included reporting living in low-income (e.g., public) housing in NYC, being 18 years old or older, being able to speak English, self-reporting not being pregnant, self-reporting no restrictions to usual physical activity, and being willing to wear a global positioning system (GPS) device for 1 week.
Self-administered survey measures
Acceptability of smartphone-based ecological momentary assessment (EMA) methods
The acceptability of two different EMA methods were assessed with two items: “Would you participate in a study that sent you texts via a smartphone asking you questions about your current mood, surroundings, and feelings?” (text message-based EMA) and “Would you participate in a study that called you to ask questions about your current mood, surroundings, and feelings?” (voice-based EMA). Response options for these two items were “Yes” and “No.”
Cell phone ownership and use
Cell phone use was assessed with one item reading, “Have you previously used a cell phone?” with two response options (yes, no). Cell phone ownership was assessed with one item reading, “Do you have a cell phone?” with two response options (yes, no). If an individual reported cell phone ownership, they were asked, “Do you own a smartphone?” with two response options (yes, no). If an individual reported smartphone ownership, they were asked “What is the operating system?” with four response options (Apple, Android, Blackberry, Other).
Blood pressure and body mass index (BMI)
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. These measurements were then used to calculate BMI using standard formulas. BMI under 18.5 were classified as underweight, between 18.5 and 24.9 were classified as normal weight, between 25.0 and 29.9 were classified as overweight, and 30.0 and over were classified as obese. Blood pressure was measured a single time in the seated position with the participants’ legs uncrossed and arms outstretched after the participants had been seated for 15–30 s, using a Welch Allyn Vital Signs 300 monitor. Measured hypertension was classified as a systolic pressure ≥ 140 mmHg or a diastolic pressure ≥ 90 mmHg. Pre-hypertension was classified as a systolic pressure between 120 and 139 mmHg or a diastolic pressure between 80 and 89 mmHg. Normal blood pressure was classified as a systolic pressure below 120 mmHg and a diastolic pressure below 80 mmHg .
Participants reported age (years), gender (male, female), race/ethnicity (White, Black, Hispanic, Asian, Other), household income (less than $25,000; $25,000 to $49,999; $50,000 to $74,999; $75,000 or greater), educational attainment (less than 12th grade, high school or GED, some college, bachelor’s degree, graduate degree), employment status (working full-time, working part-time, not working, retired, in school), and health insurance status (yes, no). This information was collected via survey.
The analytical sample was restricted to participants who answered both EMA acceptability items (n = 112), representing 94.2% of the overall sample. Descriptive statistics (e.g. frequencies) were calculated for all variables. Differences in acceptability of each of the EMA methods by socio-demographic characteristics and health status were assessed using Chi square tests. Statistical significance was set at p < .05.