- Open Access
Perceived neighborhood environment walkability and health-related quality of life among predominantly Black and Latino adults in New York City
BMC Public Health volume 23, Article number: 127 (2023)
Measures of the built environment such as neighborhood walkability have been associated with health behaviors such as physical activity, the lack of which in turn may contribute to the development of diseases such as obesity, diabetes, cardiovascular disease, and cancer. However, limited research has examined these measures in association with health-related quality of life (HR-QoL), particularly in minoritized populations. We examined the relationship between perceived neighborhood environment and HR-QoL in a sample of mostly Black and Latino residents in New York City (NYC).
This study utilized the baseline survey data from the Physical Activity and Redesigned Community Spaces (PARCS) Study among 1252 residents [34.6% Black, 54.1% Latino, 80.1% female, mean(±SD) age = 38.8 ± 12.5) in 54 park neighborhoods in NYC. Perceived built environment was measured using Neighborhood Environment and Walkability Survey, and mental and physical HR-QoL was estimated using Short Form (SF)-12. Using factor analysis, we identified two subscales of neighborhood walkability: enablers (e.g., trails, sidewalks, esthetics) vs. barriers (e.g., high crime and traffic). In addition, we included a third subscale on neighborhood satisfaction. Generalized Estimating Equation models adjusted for demographics and BMI and accounted for the clustering effect within neighborhood. Multiple imputation was used to account for missing data.
Mental HR-QoL was associated with barriers of walkability (β ± SE = − 1.63 ± 0.55, p < 0.01) and neighborhood satisfaction (β ± SE = 1.55 ± 0.66, p = 0.02), after adjusting for covariates. Physical HR-QoL was associated with only barriers of walkability (β ± SE = − 1.13 ± 0.57, p < 0.05).
Among NYC residents living in minoritized neighborhoods, mitigating negative aspects of the neighborhood environment may be more crucial than adding positive features in terms of HR-QoL. Our study points to the need to investigate further the role of the built environment in urban, minoritized communities.
The built environment has been increasingly recognized as an important dimension in the framework of social determinants of health [1, 2]. There is a growing body of literature linking the built environment to physical and mental health [3,4,5,6,7,8,9]. For example, the design of urban environments, such as neighborhood walkability, transportation, food density, parks and recreational facilities, and aesthetics, has been associated with health behaviors such as diet  and physical activity . These health behaviors, in turn, contribute to the development of diseases such as obesity, type 2 diabetes, cardiovascular disease, and cancer [12,13,14,15].
While objective physical attributes of the built environment are important (e.g., concrete amount of green space), perceptions of the environment, as proxies of how people experience their environment, may be just as critical. For example, built environment attributes have been found to have an indirect effect through the perception of the built environment on moderate-to-vigorous physical activity . Indeed, perceptions of the built environment, such as the sense of satisfaction with one’s neighborhood, has been shown to mediate the relationship between objective measures of the environment and health [17, 18]. The perceived physical environment has also been found to be positively associated with physical health outcomes such as obesity  and mental health outcomes such as depression [20,21,22].
While the conventional biomedical model emphasizes disease outcomes, quality of life, as measured by various validated survey instruments, is increasingly seen as an important health outcome in its own right . Research on the relationship between the built environment and measures of health-related quality of life (HR-QoL) is limited but emerging [3, 8, 24,25,26,27,28]. In one study, land-use heterogeneity and housing density were found to be associated with HR-QoL . Perceptions of the built environment, such as perceived street noise and traffic safety, have also been related to mental and physical health components of quality of life [3, 27]. Furthermore, research has shown a positive correlation between neighborhood walkability and HR-QoL in Australia and China [26, 27]. Increased perceived diversity, safety and esthetics were found to be associated with higher physical and mental HR-QoL . However, to our knowledge, little is known about these relationships in minoritized populations in the United States.
To bridge this gap, we first tested the psychometric properties of the Neighborhood Environment and Walkability Survey (NEWS) in New York City (NYC), recognizing its unique built environment compared to other major American cities. Subsequently, we examined the association between perceptions of the neighborhood environment and HR-QoL in a sample of mostly Black and Latino residents in NYC. We hypothesized that positive perceptions of the neighborhood environment would be associated with higher physical and mental components of HR-QoL.
This study utilized the baseline adult survey data from the Physical Activity and Redesigned Community Spaces (PARCS) Study, a natural experiment evaluation on the impact of citywide park redesign and renovation on health and wellbeing . The baseline survey data were collected from Summer 2016 – Spring 2018 (except during winter months) in 54 park neighborhoods throughout the five boroughs of NYC. A convenience sample of adult residents was invited to participate in the study survey.
Park neighborhood selection
To be included in the study, NYC Parks and Recreation identified parks in neighborhoods which met two of three selection criteria: high poverty (≥ 20% population below poverty line), high population growth (≥25% growth during 2000–2010) or high population density (≥ 110 people/acre). For the purpose of the PARCS evaluation study, study park buffer zones were defined as the area within a 0.30-mile radius from the perimeter of each park.
To meet the PARCS Study eligibility criteria, participants needed to live within the designated 0.3-mile buffer zone. Eligible participants were adults ≥18 years of age who owned a smart phone, spoke English, Spanish or Chinese (Mandarin or Cantonese), did not have any mobility issues and were intending to stay in the neighborhood for at least 4 years (due to the longitudinal nature of the parent study). This paper included observations from 1252 participants who provided any data on the relevant survey items described below.
Health-related quality of life (HR-QoL)
HR-QoL is a multidimensional concept that includes individuals’ perception of their physical and mental functioning, limitations due to physical or mental health problems, bodily pain, vitality, general health, and social functioning . We used the well-validated Short-Form 12 (SF-12) survey  in this study. Eight domains were covered by the SF-12 survey questions including 1) limitations in physical activities because of health problems 2) limitations in social activities because of physical or emotional problems 3) limitations in usual role activities because of physical health problems 4) bodily pain 5) general mental health 6) limitations in usual role activities because of emotional problems 7) vitality 8) general health perceptions. For the purpose of our analysis, we used the composite scores on mental health and physical health as our two primary outcome variables, using the standard scoring protocol for SF-12 . The higher the score, the better the self-reported HR-QoL in mental health and physical health (range 0–100).
Neighborhood Environment and Walkability Survey (NEWS)
NEWS was developed in 2002 to measure resident perceptions of neighborhood characteristics , including residential density, land use mix, street connectivity, infrastructure for walking/cycling, neighborhood aesthetics, traffic and crime safety, and neighborhood satisfaction . This survey we used included: places for walking and cycling (5 items), neighborhood surroundings (6 items), safety from traffic (8 items), safety from crime (6 items), and neighborhood satisfaction (18 items) . Items for the first four original subscales all had four response options (1 = strongly disagree, 2 = somewhat disagree, 3 = somewhat agree, 4 = strongly agree) while items in the neighborhood satisfaction subscale had five response options (1 = strongly dissatisfied, 2 = somewhat dissatisfied, 3 = neither satisfied nor dissatisfied, 4 = somewhat satisfied, 5 = strongly satisfied). Items were coded such that the higher the subscale score, the more positive the attitude regarding the construct.
Demographic variables included age, gender (female vs. male as reference group), ethnicity (Black, Other vs. Latino as reference group), BMI (overweight 25–29 kg/m2, obese > = 30 kg/m2 vs. under and normal < 25 kg/m2 as reference group,), annual household income (< $20,000 vs. ≥ $20,000 as reference group), education (high school graduate, some college or higher vs. less than high school as reference group), employment (self-employed, homemaker, student, retired, unable to work, unemployed for 1 year or more, unemployed for less than 1 year, don’t know/not sure vs. employed as reference group), and marital status (divorced, widowed, separated, never married, a member of an unmarried couple living together vs. married as reference group).
NEWS was originally developed in Seattle and cross-validated in Baltimore . Factor analysis has been used to adapt to countries other than the United States, such as Australia and Western Europe . Due to the unique neighborhood characteristics of NYC, we first tested the psychometric properties of NEWS using exploratory factor analysis (EFA) with oblimin rotation . Items with factor loading < 0.40 were dropped in subsequent analysis . We used Cronbach’s alpha  was used to assess the internal consistency of the newly constituted subscales based on the factor analysis, considering Cronbach’s alpha > 0.7 as good and acceptable. Spearman correlation tests were performed between NEWS subscales and HR-QoL components.
To deal with missing data, we used sequential regression modelling to impute the missing values in the NEWS scales, QoL scores and covariates . Twenty imputations were generated, taking into account 14% of missing cells in the original dataset. Descriptive statistics were estimated for all the NEWS subscales, HR-QoL components, and covariates with and without imputation. Then, we regressed mental and physical HR-QoL scores (in separate models) on the newly formed NEWS subscales, adjusting for covariates, with multiple imputed dataset. Generalized Estimating Equation (GEE) models  were used to account for the clustering effect of park neighborhoods. Sensitivity analyses were conducted using the complete cases for GEE modeling.
To test the multicollinearity between NEWS subscales, variance inflation factors (VIF) were calculated in the GEE models. The VIF for the NEWS subscales ranged from 1.1 to 1.6, showing no multicollinearity among NEWS subscales .
All analyses were performed using R version 4.0.4 . The package of “psych” in R was utilized for the EFA . We used the “MICE” package in R for multiple imputations . The “geepack” package in R was utilized to test GEE models . Alpha was set at p < 0.05.
Factor analysis of NEWS subscales
Using the raw data, Cronbach’s alpha showed poor internal consistency for three of the original survey subscales: places for walking and cycling (0.57, 95% Confidence Interval (CI) = 0.54–0.61), safety from traffic (0.64, 95% CI = 0.61–0.67), safety from crime (0.66, 95% CI = 0.63–0.69). Neighborhood surroundings had good internal consistency with a Cronbach’s alpha of 0.79 (95% CI = 0.77–0.80) and neighborhood satisfaction had high internal consistency with a Cronbach’s alpha of 0.91 (95% CI = 0.90–0.92).
To adapt NEWS for NYC, EFA was performed for the above scales besides neighborhood satisfaction. EFA yielded two subscales: enablers (e.g., trails, sidewalks, esthetics) vs. barriers (e.g., high crime and traffic) of walkability. EFA results for the first two subscales with items demonstrating a factor loading ≥0.40 are shown in Table 1. Cronbach’s alpha was 0.84, 0.78 and 0.91 for walkability enablers, walkability barriers, and neighborhood satisfaction, indicating good internal consistency. The higher the NEWS subscale value, the stronger agreement on the statements for enablers and barriers.
Participant characteristics and bivariate associations of NEWS and HR-QoL
Table 2 provides the descriptive statistics of the sample with and without imputation. The imputed results closely matched those of the non-imputed data. The sample had a mean (±standard error) age of 38.8 ± 12.5 years and was 80.1% female. The vast majority of the participants were Latino (54.1%) or Black (34.6%). Just over half of the participants were in a household with an annual income lower than $20,000 while almost half had some college or a higher degree. In terms of employment, 37.5% of the sample was employed and 11.4% was self-employed). Just over one-third of the participants were married or living with a partner. Table 3 shows significant crude associations between NEWS scales and HR-QoL. The correlation coefficients of NEWS walkability enablers, NEWS walkability barriers, and NEWS neighborhood satisfaction with physical HR-QoL are 0.086, − 0.151 and 0.098 (p < 0.05). The correlation coefficients of NEWS walkability enablers, NEWS walkability barriers, and NEWS neighborhood satisfaction with mental HR-QoL are 0.180, − 0.143 and 0.218 (p < 0.05).
Using separate GEE models with multiple imputations, mental and physical HR- QoL scores were regressed on NEWS subscales adjusting for covariates (Table 4). Results (with multiple imputations) showed mental HR-QoL was negatively associated with barriers of walkability (β ± SE = − 1.63 ± 0.55, p = 0.003) but positively associated with neighborhood satisfaction (β ± SE = 1.55 ± 0.66, p = 0.02), after adjusting for covariates. Physical HR-QoL was associated with only barriers of walkability (β ± SE = − 1.13 ± 0.57, p < 0.05). Sensitivity analyses showed the regression results were similar in imputed vs. non-imputed data (data not shown).
This is one of the first studies to examine HR-QoL in relation to perceived neighborhood environment. In particular, our study adds to the emerging literature with a specific focus on Latino and Black residents in lower income neighborhoods. We found that high perceived barriers of walkability was associated with both lower physical and mental HR-QoL. In addition, a global scale of neighborhood satisfaction was positively related to mental, but not physical, HR-QoL.
Despite the ubiquity of NEWS and SF-12 (or SF-36) in the literature, there have been surprisingly few studies investigating the relationship between these two sets of measures. In prior research, an Australian study on people aged 75 or greater showed a positive correlation between the original NEWS subscales and physical and mental HR-QoL using SF-36, but the study did not consider covariates . Another study conducted in adults of different ages in 6 urban centers of China used multivariable models to examine each original NEWS subscale in relation to mental and physical HR-QoL (measured by SF-12) and found that higher perceived land use diversity, safety and esthetics were associated with higher physical and mental well-being . Our study is the first to examine the association of the NEWS in relation to HR-QoL in the United States, especially among minority populations.
HR-QoL is an important public health outcome given the growing body of literature showing it to be an independent predictor of diverse clinical outcomes [46,47,48,49,50,51,52,53,54]. Physical HR-QoL as measured by SF-12 or SF-36 has been associated with the mortality of patients with hemodialysis , after coronary artery bypass graft surgery , and within 48 hours of admission to the ICU , as well as the development of obesity , diabetes , cardiovascular disease , and several cancers (e.g., oral  and advanced breast cancer ). In addition, patients with better mental HR-QoL scores were shown to be more likely to improve after lumbar fusion . Mental HR-QoL has also been associated with mental health outcomes, such as anxiety , depression , and relapse of schizophrenia at 24-month follow up . Therefore, HR-QoL can be considered a proxy of global well-being but more research is warranted on how to intervene on HR-QoL, including potentially via environmental strategies such as improving neighborhood walkability.
The items for the barriers for walkability subscale were a function of perceived traffic and crime. Our results are corroborated by prior research linking these environmental factors to health. For example, a previous study on children found that children who were exposed to high traffic volumes had significantly higher odds of asthma . In addition, exposure to traffic congestion has been associated with on-the-job elevations of urinary catecholamines (a marker of stress) among bus drivers . Elsewhere, the safer or less crime individuals feel in their neighborhood, the better mental health outcomes they have such as lower distress [62, 63] and better physical health . Collectively, these and our findings point to the potential importance of transportation and neighborhood design in urban areas where the alleviation of traffic  and improvement in perceived safety [62, 66,67,68] may contribute to population well-being, which in turn may have a downstream impact on reducing health disparities.
It was notable that neighborhood satisfaction was significantly associated with mental but not physical HR-QoL. Neighborhood satisfaction has previously been found to be a predictor of mental health outcomes . Neighborhood satisfaction has also been studied as a significant mediator between the quality of green space in a neighborhood and general health outcomes . It is possible that mental HR-QoL serves as a mediator between neighborhood satisfaction and physical HR-QoL over time; future longitudinal studies are needed to further examine this hypothesis.
This study highlights a caveat for the generalizability of well published psychosocial scales such as NEWS without further psychometric testing. NEWS has been widely used in research globally [35, 70,71,72]. However, items in NEWS may be context-specific and may need to be customized to specific study populations [26, 70]. An important contribution of this paper is the application of EFA to reconstruct the factors, an approach that could be considered for future studies using surveys of perceptions of the environment.
This study and its findings add to the literature on urban livability. Urban livability is a multifaceted concept that incorporates diverse aspects of the neighborhood environment, including physical, biological and socioeconomic characteristics and their interactions [73, 74]. HR-QoL in this literature may be conceptualized, for instance, in terms of the number or density of health-related facilities and services . Our study shows that the lived experience of community residents is an additional important dimension to consider. As such, this study has important research and policy implications that require the convergence of public health, urban planning and design, and other fields in a more holistic approach to urban livability.
Several limitations are inherent in this study. The study was cross-sectional; thus, no causality could be inferred. The target population included mostly residents of low-income, minority neighborhoods, limiting the generalizability of our findings to all of NYC or elsewhere. In addition, we cannot rule out the possibility of selection bias among those who chose to participate in the survey study, thus study findings may not be representative of the entirety of the underlying communities. The population focus, however, was also a strength of the study given the heightened health disparities experienced by Latino and Black communities in the United States.
In conclusion, perceptions of the built environment appear to be important factors in the HR-QoL of low-income residents in NYC. Further research is warranted to investigate the pathways by which such perceptions influence HR-QoL, including potential stress mechanisms. The current paper adds to the literature on urban health and urban planning and shows the potential value of incorporating community members’ experiences of the built environment and robust HR-QoL measures in studies of population well-being and environmental livability.
Availability of data and materials
The datasets generated and/or analyzed during the current study are not publicly available due to the fact that this is an ongoing study but are available from the corresponding author on reasonable request.
Stokols D. Establishing and maintaining healthy environments: toward a social ecology of health promotion. Am Psychol. 1992;47(1):6.
Ward Thompson C, Aspinall PA. Natural environments and their impact on activity, health, and quality of life. Appl Psychol. 2011;3(3):230–60.
Parra DC, Gomez LF, Sarmiento OL, Buchner D, Brownson R, Schimd T, et al. Perceived and objective neighborhood environment attributes and health related quality of life among the elderly in Bogota, Colombia. Soc Sci Med. 2010;70(7):1070–6.
Evans GW. The built environment and mental health. J Urban Health. 2003;80(4):536–55.
Jackson RJ, Dannenberg AL, Frumkin H. Health and the built environment: 10 years after. Am J Public Health. 2013;103(9):1542–4.
Rachele JN, Sugiyama T, Davies S, Loh VH, Turrell G, Carver A, et al. Neighbourhood built environment and physical function among mid-to-older aged adults: a systematic review. Health Place. 2019;58:102137.
Fleming R, Goodenough B, Low L-F, Chenoweth L, Brodaty H. The relationship between the quality of the built environment and the quality of life of people with dementia in residential care. Dementia. 2016;15(4):663–80.
Moore T, Kesten J, López-López JA, Ijaz S, McAleenan A, Richards A, et al. The effects of changes to the built environment on the mental health and well-being of adults: systematic review. Health Place. 2018;53:237–57.
Schulz M, Romppel M, Grande G. Built environment and health: a systematic review of studies in Germany. J Public Health. 2018;40(1):8–15.
Patel O, Shahulhameed S, Shivashankar R, Tayyab M, Rahman A, Prabhakaran D, et al. Association between full service and fast food restaurant density, dietary intake and overweight/obesity among adults in Delhi, India. BMC Public Health. 2018;18(1):1–11.
Nicosia N, Datar A. Neighborhood environments and physical activity: a longitudinal study of adolescents in a natural experiment. Am J Prev Med. 2018;54(5):671–8.
Hruby A, Manson JE, Qi L, Malik VS, Rimm EB, Sun Q, et al. Determinants and consequences of obesity. Am J Public Health. 2016;106(9):1656–62.
Wray AJD, Minaker LM. Is cancer prevention influenced by the built environment? A multidisciplinary scoping review. Cancer. 2019;125(19):3299–311.
Malambo P, Kengne AP, De Villiers A, Lambert EV, Puoane T. Built environment, selected risk factors and major cardiovascular disease outcomes: a systematic review. PLoS One. 2016;11(11):e0166846.
Amuda AT, Berkowitz SA. Diabetes and the built environment: evidence and policies. Curr Diabetes Rep. 2019;19(7):1–8.
Zhao L, Shen Z, Zhang Y, Sheng F. Study on the impact of the objective characteristics and subjective perception of the built environment on residents’ physical activities in Fuzhou, China. Sustainability. 2019;12(1):329.
Xiao Y, Miao S, Sarkar C, Geng H, Lu Y. Exploring the impacts of housing condition on migrants’ mental health in nanxiang, shanghai: a structural equation modelling approach. Int J Environ Res Public Health. 2018;15(2):225.
De Jong K, Albin M, Skärbäck E, Grahn P, Björk J. Perceived green qualities were associated with neighborhood satisfaction, physical activity, and general health: results from a cross-sectional study in suburban and rural Scania, southern Sweden. Health Place. 2012;18(6):1374–80.
Powell-Wiley TM, Ayers CR, De Lemos JA, Lakoski SG, Vega GL, Grundy S, et al. Relationship between perceptions about neighborhood environment and prevalent obesity: data from the Dallas heart study. Obesity. 2013;21(1):E14–21.
Van Dyck D, Teychenne M, McNaughton SA, De Bourdeaudhuij I, Salmon J. Relationship of the perceived social and physical environment with mental health-related quality of life in middle-aged and older adults: mediating effects of physical activity. PLoS One. 2015;10(3):e0120475.
Roh S, Jang Y, Chiriboga DA, Kwag KH, Cho S, Bernstein K. Perceived neighborhood environment affecting physical and mental health: a study with Korean American older adults in New York City. J Immigr Minor Health. 2011;13(6):1005.
Andrews MR, Ceasar J, Tamura K, Langerman SD, Mitchell VM, Collins BS, et al. Neighborhood environment perceptions associate with depression levels and cardiovascular risk among middle-aged and older adults: data from the Washington, DC cardiovascular health and needs assessment. Aging Ment Health. 2021;25(11):2078–89.
Haraldstad K, Wahl A, Andenæs R, Andersen JR, Andersen MH, Beisland E, et al. A systematic review of quality of life research in medicine and health sciences. Qual Life Res. 2019;28(10):2641–50.
Brennan P, McKay J, Moore L, Zaridze D, Mukeria A, Szeszenia-Dabrowska N, et al. Obesity and cancer: Mendelian randomization approach utilizing the FTO genotype. Int J Epidemiol. 2009;38(4):971–5.
Sallis JF, Saelens BE, Frank LD, Conway TL, Slymen DJ, Cain KL, et al. Neighborhood built environment and income: examining multiple health outcomes. Soc Sci Med. 2009;68(7):1285–93.
Byles JE, Mackenzie L, Redman S, Parkinson L, Leigh L, Curryer C. Supporting housing and neighbourhoods for healthy ageing: findings from the H ousing and I ndependent L iving S tudy (HAIL). Australas J Ageing. 2014;33(1):29–35.
Gao M, Ahern J, Koshland CP. Perceived built environment and health-related quality of life in four types of neighborhoods in Xi’an, China. Health Place. 2016;39:110–5.
Sarmiento OL, Schmid TL, Parra DC, Díaz-del-Castillo A, Gómez LF, Pratt M, et al. Quality of life, physical activity, and built environment characteristics among colombian adults. J Phys Act Health. 2010;7(s2):S181–S95.
Huang TT, Wyka KE, Ferris EB, Gardner J, Evenson KR, Tripathi D, et al. The physical activity and redesigned community spaces (PARCS) study: protocol of a natural experiment to investigate the impact of citywide park redesign and renovation. BMC Public Health. 2016;16(1):1–12.
Rissanen R, Berg H-Y, Hasselberg M. Quality of life following road traffic injury: a systematic literature review. Accid Anal Prev. 2017;108:308–20.
Schofield MJ, Mishra G. Validity of the SF-12 compared with the SF-36 health survey in pilot studies of the Australian longitudinal study on Women's health. J Health Psychol. 1998;3(2):259–71.
Ware JE Jr, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34:220–33.
Cerin E, Saelens BE, Sallis JF, Frank LD. Neighborhood environment walkability scale: validity and development of a short form. Med Sci Sports Exerc. 2006;38(9):1682.
Cerin E, Conway TL, Saelens BE, Frank LD, Sallis JF. Cross-validation of the factorial structure of the neighborhood environment walkability scale (NEWS) and its abbreviated form (NEWS-A). Int J Behav Nutr Phys Act. 2009;6(1):1–10.
Cerin E, Conway TL, Cain KL, Kerr J, De Bourdeaudhuij I, Owen N, et al. Sharing good NEWS across the world: developing comparable scores across 12 countries for the neighborhood environment walkability scale (NEWS). BMC Public Health. 2013;13(1):1–14.
Watkins MW. Exploratory factor analysis: a guide to best practice. J Black Psychol. 2018;44(3):219–46.
Stevens JP. Applied multivariate statistics for the social sciences. 5th ed. New York: Routledge; 2012.
Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16(3):297–334.
Van Buuren S, Groothuis-Oudshoorn K. Mice: multivariate imputation by chained equations in R. J Stat Softw. 2011;45(1):1–67.
Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986;73(1):13–22.
Alin A. Multicollinearity. Wiley Interdiscip Rev. 2010;2(3):370–4.
Chambers JM. Software for data analysis: programming with R. New York: Springer; 2008.
Revelle W, Revelle MW. Package ‘psych’. The comprehensive R archive network. 2015;337:338.
Azur MJ, Stuart EA, Frangakis C, Leaf PJ. Multiple imputation by chained equations: what is it and how does it work? Int J Methods Psychiatr Res. 2011;20(1):40–9.
Højsgaard S, Halekoh U, Yan J. The R package geepack for generalized estimating equations. J Stat Softw. 2006;15:1–11.
Fang FM, Liu YT, Tang Y, Wang CJ, Ko SF. Quality of life as a survival predictor for patients with advanced head and neck carcinoma treated with radiotherapy. Cancer. 2004;100(2):425–32.
Boyer L, Millier A, Perthame E, Aballea S, Auquier P, Toumi M. Quality of life is predictive of relapse in schizophrenia. BMC Psychiatry. 2013;13(1):1–8.
Mapes DL, Lopes AA, Satayathum S, Mccullough KP, Goodkin DA, Locatelli F, et al. Health-related quality of life as a predictor of mortality and hospitalization: the Dialysis outcomes and practice patterns study (DOPPS). Kidney Int. 2003;64(1):339–49.
Carreon LY, Glassman SD, Djurasovic M, Dimar JR, Johnson JR, Puno RM, et al. Are preoperative health-related quality of life scores predictive of clinical outcomes after lumbar fusion? Spine. 2009;34(7):725–30.
Seid M, Varni JW, Segall D, Kurtin PS. Health-related quality of life as a predictor of pediatric healthcare costs: a two-year prospective cohort analysis. Health Qual Life Outcomes. 2004;2(1):1–10.
Lee C, Stockler M, Coates A, Gebski V, Lord S, Simes R. Self-reported health-related quality of life is an independent predictor of chemotherapy treatment benefit and toxicity in women with advanced breast cancer. Br J Cancer. 2010;102(9):1341–7.
Hofhuis JG, Spronk PE, Van Stel HF, Schrijvers AJ, Bakker J. Quality of life before intensive care unit admission is a predictor of survival. Crit Care. 2007;11(4):1–7.
Tarsitano A, Pizzigallo A, Ballone E, Marchetti C. Health-related quality of life as a survival predictor for patients with oral cancer: is quality of life associated with long-term overall survival? Oral Surg Oral Med Oral Pathol Oral Radiol. 2012;114(6):756–63.
Rumsfeld JS, MaWhinney S, McCarthy M Jr, Shroyer ALW, VillaNueva CB, O'Brien M, et al. Health-related quality of life as a predictor of mortality following coronary artery bypass graft surgery. JAMA. 1999;281(14):1298–303.
Kolotkin R, Meter K, Williams G. Quality of life and obesity. Obes Rev. 2001;2(4):219–29.
Rubin RR, Peyrot M. Quality of life and diabetes. Diabetes Metab Res Rev. 1999;15(3):205–18.
Li C, Ford ES, Mokdad AH, Balluz LS, Brown DW, Giles WH. Clustering of cardiovascular disease risk factors and health-related quality of life among US adults. Value Health. 2008;11(4):689–99.
Conn WS, Taylor SG, Wiman P. Anxiety, depression, quality of life, and self-care among survivors of myocardial infarction. Issues Ment Health Nurs. 1991;12(4):321–31.
Rothrock NE, Lutgendorf SK, Kreder KJ. Coping strategies in patients with interstitial cystitis: relationships with quality of life and depression. J Urol. 2003;169(1):233–6.
Feng X, Astell-Burt T. Is neighborhood green space protective against associations between child asthma, neighborhood traffic volume and perceived lack of area safety? Multilevel analysis of 4447 Australian children. Int J Environ Res Public Health. 2017;14(5):543.
Evans GW, Carrère S. Traffic congestion, perceived control, and psychophysiological stress among urban bus drivers. J Appl Psychol. 1991;76(5):658.
White M, Kasl SV, Zahner GE, Will JC. Perceived crime in the neighborhood and mental health of women and children. Environ Behav. 1987;19(5):588–613.
Booth J, Ayers SL, Marsiglia FF. Perceived neighborhood safety and psychological distress: exploring protective factors. J Soc Soc Welfare. 2012;39:137.
Lovasi GS, Goh CE, Pearson AL, Breetzke G. The independent associations of recorded crime and perceived safety with physical health in a nationally representative cross-sectional survey of men and women in New Zealand. BMJ Open. 2014;4(3):e004058.
Habib N, Mohammed K. Evaluation of planning options to alleviate traffic congestion and resulting air pollution in Dhaka City; 2002.
Marzbali MH, Abdullah A, Tilaki MJM. The effectiveness of interventions in the built environment for improving health by addressing fear of crime. Int J Law Crime Justice. 2016;45:120–40.
Tamayo A, Karter AJ, Mujahid MS, Warton EM, Moffet HH, Adler N, et al. Associations of perceived neighborhood safety and crime with cardiometabolic risk factors among a population with type 2 diabetes. Health Place. 2016;39:116–21.
Won J, Lee C, Forjuoh SN, Ory MG. Neighborhood safety factors associated with older adults' health-related outcomes: a systematic literature review. Soc Sci Med. 2016;165:177–86.
Adams RE. Is happiness a home in the suburbs?: the influence of urban versus suburban neighborhoods on psychological health. J Community Psychol. 1992;20(4):353–72.
Van Dyck D, Cerin E, Conway TL, De Bourdeaudhuij I, Owen N, Kerr J, et al. Perceived neighborhood environmental attributes associated with adults’ transport-related walking and cycling: findings from the USA, Australia and Belgium. Int J Behav Nutr Phys Act. 2012;9(1):1–14.
Frank LD, Sallis JF, Saelens BE, Leary L, Cain K, Conway TL, et al. The development of a walkability index: application to the neighborhood quality of life study. Br J Sports Med. 2010;44(13):924–33.
Cerin E, Sit CH, Cheung M-c, Ho S-y, L-cJ L, Chan W-m. Reliable and valid NEWS for Chinese seniors: measuring perceived neighborhood attributes related to walking. Int J Behav Nutr Phys Act. 2010;7(1):1–14.
Kashef M. Urban livability across disciplinary and professional boundaries. Front Architect Res. 2016;5(2):239–53.
Pacione M. Urban liveability: a review. Urban Geogr. 1990;11(1):1–30.
This study was supported by the National Cancer Institute (R01CA206877), New York State Health Foundation (#16–04236), Robert Wood Johnson Foundation (E4A Program Grant #76473), and Bryant Park Corporation. Additional funding support for TH, KW, and LT was provided by a grant U48DP006396 from the Centers for Disease Control and Prevention.
Ethics approval and consent to participate
The PARCS Study was approved by the City University of New York IRB (#2016–0248) and participants provided written consent prior to study enrollment. Informed consent was obtained from all subjects and/or their legal guardian(s). All methods were performed in accordance with the relevant guidelines and regulations.
Consent for publication
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Zhu, J., Kodali, H., Wyka, K.E. et al. Perceived neighborhood environment walkability and health-related quality of life among predominantly Black and Latino adults in New York City. BMC Public Health 23, 127 (2023). https://doi.org/10.1186/s12889-022-14973-1
- Built environment
- Neighborhood satisfaction
- Quality of life
- African American
- Community health