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Little is known about the health and health behaviors of non-English Speaking late-life Asian immigrants, which is attributable to language and cultural barriers to participate research. In our Healthy Aging and Neighborhood Study, we collected objective measures of space and time use, location- and time-specific physical activities using accelerometer and Global Positioning System devices, and self-reported sleep quality and health. We obtained 3,915 person-days of accelerometer readings from 511 participants including 43 Asians. Compared to non-Hispanic Whites, Asians had worse self-rated health and poorer vision, more medical conditions and physical limitations as measured by ADL and IADL. Asians had higher daily step counts overall and at home; high proportions of steps on sidewalk or street and senior centers, lower in fee-based outdoor recreational areas, less in restaurant and vehicle. Sleep quality did not differ significantly between Asians and Whites. Risk profiles differed between Asians and Whites, which warrants further investigation.

Adequate minority participation is critical to health disparity research. Conventional direct mails are less effective in minority recruitment. The Healthy Aging and Neighborhood Study developed a multifaceted, community-engaged, culturally and linguistically appropriate method to recruit community-living older adults (≥65y) in Worcester County, Massachusetts. The research team is bilingual, racially and culturally diverse. A direct mail campaign was conducted in a geographically diverse random sample of residents from neighborhoods with high concentrations of minorities, stratified by rurality. To increase minority participation, the mailings included an invitational letter or a flyer with a graphic that portrays diverse racial/ethnic background. We engaged communities by presenting the study at senior and community centers, and faith-based organizations that are frequented by minorities and by posting study information in minority social media groups (e.g., Chinese resident associations). Participants promoted the study to friends while staff promoted through professional or social networks. To recruit non-English speaking minorities, all materials were printed in age-friendly large fonts in Spanish or Chinese, and interviews were conducted using their preferred language. Within 9 months, we enrolled 326 participants, including 216 Whites, 57 Hispanics, 21 Blacks, 31 Asians, and 1 Native American. An additional 38 Asians are on the waiting list. Blacks were more likely to respond to community presentations. Hispanics were most likely to respond to the colorful flyer. Older minorities (>76y) were more likely to respond to presentations (57%) while the younger (

Little is known about the health and health care needs of non-English Speaking late-life Asian immigrants. Due to language barriers and memory issues, self-report data are unreliable for investigating activity patterns in this population. In the ongoing NIA-funded Healthy Aging and Neighborhood Study, we developed a novel method to objectively measure space and time use, location- and time-specific physical and social activities using accelerometer (ACC) and Global Positioning System (GPS) devices. The study has recruited over 150 Caucasians and 150 minorities including 50 non-English speaking late-life Asian immigrants. The participants answered surveys in their preferred language (English, Spanish, traditional or simplified Chinese) and wore ACC/GPS devices for 7 to 10 full days. Activity levels and geographic locations are recorded every 30 seconds. Using the combined ACC/GPS data, time- and location-specific activity amounts, time use and mobility patterns are objectively measured. Baseline findings will be reported at the GSA conference.

A better understanding of how older adults use neighborhood built environment for physical activity (PA) can inform effective promotion of PA for them. From 2012 to 2014, 208 community-living adults aged ≥65 years were recruited from car-dependent urban and rural neighborhoods in Worcester County, Massachusetts. Participants wore a Global Positioning System device and an accelerometer for 7 consecutive days. Total PA amount was measured as average daily number of steps, and stepping rate as number of steps per minute. PA amount and stepping rate were evaluated according to 17 categories of geographic location, overall and by gender and age group. Participants included 108 men and 100 women, 88% White, and averaged 74 years of age. Men and women on average took 3962 and 3773 steps/day, respectively. Over 50%, 70% and 90% of total PA occurred within 0.2, 2 and 10 miles from home, respectively. In-home PA accounted for 64% of total PA. Shopping was the second-highest place of PA. Walking on sidewalks/streets averaged

A better understanding of how older adults spend time in neighborhoods may inform promotion of social and physical activities. Between 2012 and 2014, we measured time use of 208 community-living adults aged ≥65 years who were recruited from car-dependent urban and rural neighborhoods in Central Massachusetts. Participants included 108 men and 100 women, 88% White, and averaged 74 years of age. Participants wore a Global Positioning System (GPS) device for 7 consecutive days. Location-specific time use was measured as average daily number of minutes spent in each of the 18 categories of geographic location during each hour from 5 am to midnight based on GPS records, overall and by gender. For men and women, most time was spent in the home (81%), followed by driving (5.1%), shopping (3.2%), civic center (2.6%), other residence (2.5%), medical facility (2.3%), restaurant (1.5%), sidewalk/street (1.1%), and indoor fitness (0.9%). While women spent more time on streets/sidewalks and at medical facilities, men spent more time driving and at other residences, restaurants and civic places. Hourly patterns of time use were similar between genders, with activity outside the home peaking between 9 am and 4 pm. In summary, older adults spent about 20% of their waking time outside their homes. Men and women had similar patterns of time and space use. Location preferences for spending time away from home may be considered in community-based promotion of social activities for older adults.

Accurate measurement of dietary intake is an important component in the assessment of racial disparities in healthy eating among older adults. We examined the agreement in alternative healthy eating indices (AHEI) based upon Women’s Health Initiative food frequency questionnaire (FFQ) and 24-hour dietary recalls (24HR) by race among urban older women. In 2014 and 2015, 49 White and 44 Black women 65 years and older living in Washington, DC, were queried about diet using both FFQ and 24HR. The correlation coefficients (rho) of 56 nutrient intake measures and agreements in AHEI based on FFQ and 24HR were compared by race. The median rho was 0.50 for Whites and 0.21 for Blacks. For 48 measures, rho was lower for Blacks. Whites had a strong correlation of >0.5 for 25 items, while Blacks had strong correlations for only 3 items. Based on FFQ, the mean (SD) of AHEI was 54.0 (10.3) for Whites and 45.9 (8.8) for Blacks (p

A better understanding of sex differences in physical activity (PA) may inform sex-specific promotion programs. Between 2013 and 2015, we queried 111 men and 102 women 65 years and older living in urban and rural neighborhoods in Central Massachusetts about their PA and use of neighborhood resources. The participants wore an accelerometer and a Global Positioning System (GPS) device for 7 consecutive days. Level and location of self-report PA were validated against accelerometer/GPS measures. We evaluated level, type and location of PA by sex. Compared to men, women reported more frequent PA inside the home (mean (SD) 59.1 (25.2) vs. 47.8 (30.0) times per month, p=0.004), and similar frequencies of PA outside home and utilitarian and recreational walking. Daily step counts were highly correlated with reported frequency of recreational walking and PA away from home but not with PA in home. Men had substantially higher average daily step count (4339 (2131) vs. 3661 (1725), p=0.01), self-report weekly frequencies of all exercise (21.4 (13.8) vs. 16.9 (9.4), p=0.007) and moderate-high-intensity exercise activities (11.8 (9.4) vs. 6.8 (6.4), p