Abstract
Common mental disorders such as depression and anxiety are prevalent globally, and rates are especially high in New York City (NYC) since the COVID-19 pandemic. Neighborhood social and physical environments have been found to influence mental health. We investigated the impact of neighborhood social cohesion and neighborhood rodent sightings (as an indicator of neighborhood cleanliness) on nonspecific serious psychological distress (NSPD) status using 2020 NYC Community Health Survey data from 8781 NYC residents. Multivariable logistic regression was used to evaluate the relationships among social cohesion, rodent sightings, and NSPD adjusted for confounders and complex sampling and weighted to the NYC population. Effect measure modification of rodent sightings on the effect of social cohesion on NSPD was evaluated on the multiplicative scale by adding the interaction term to the multivariable model and, if significant, stratifying on the effect modifier, and on the additive scale using the relative excess risk due to interaction (RERI). Social cohesion was found to decrease the odds of NSPD, and rodent sightings were found to increase the odds of NSPD. We found significant evidence of effect measure modification on the multiplicative scale. In the stratified models, there was a protective effect of social cohesion against NSPD among those not reporting rodent sightings, but no effect among those reporting rodent sightings. Our findings suggest that both neighborhood social cohesion and rodent sightings impact the mental health of New Yorkers and that rodent infestations may diminish the benefit of neighborhood social cohesion.
Keywords: Mental Health, Neighborhood Social Cohesion, Rodents, Neighborhood Cleanliness, Neighborhood Disorder, New York City, Community Health Survey (CHS)
Introduction
The World Health Organization reports that globally one in eight people live with a mental disorder, including 301 million people who are living with anxiety and 280 million with depression [1]. Rates are even higher in New York City (NYC). According to the NYC Mayor’s Office of Community Mental Health, one in five residents of NYC experience mental illness every year [2]. Poor mental well-being not only affects emotional, behavioral, and social health, but also increases risk for various physical health issues including diabetes, heart disease, and stroke [3].
Mental health needs and access to mental health care vary by race and by neighborhood in NYC. According to the NYC Department of Health and Mental Hygiene (DOHMH), only 33% of Black NYC residents have access to mental health care compared to 58% of White residents. In addition, their data show that the neighborhoods in NYC with the highest rates of poverty have more than double the number of psychiatric hospitalizations per capita compared to the lowest poverty neighborhoods (1001 and 399 per 100,000, respectively) [2]. Data from the 2017 NYC Social Determinants of Health survey show that adults with income < 200% of the federal poverty line had nearly four times the prevalence of serious psychological distress (11%) compared to those with income ≥ 200% of the federal poverty line (3%), indicating that income level also plays a significant role in mental illness in NYC [4]. Further, education and employment status are considered core social determinants of mental health [5]. Researchers suggest that those with poor education are more likely to have reduced employment options and participate in high-risk behaviors leading to overall greater risk of both physical and mental illness [5]. Additionally, researchers report that those experiencing unemployment, underemployment, and job insecurity are more likely to experience financial and other related stress, putting them at higher risk for mental illness [5].
Neighborhood social cohesion is defined as a sense of community belonging, “attraction” to one’s neighborhood, and level of interaction with neighbors in the community [6]. Social cohesion and community engagement have been found to positively impact long-term mental well-being and to reduce depression and anxiety symptoms and psychological distress [7–9]. The 2017 NYC Social Determinants of Health Survey data found that adults who agreed with or were neutral towards the statement that their neighbors were willing to help each other had less than one-third the prevalence of serious psychological distress (5%) compared to adults who disagreed (16%), indicating that social cohesion may play a role in New Yorkers’ mental health [4].
Additionally, research shows that poor housing quality negatively affects mental health outcomes [4, 10, 11]. Subjective perceptions of housing quality and neighborhood poverty have been found to be associated with both mental health and health behaviors [12, 13]. One aspect of housing quality that has been shown to impact mental health is in-home and neighborhood cleanliness. High neighborhood physical disorder (e.g., vandalism or dirtiness) and “dirty-looking,” “squalid,” or “unclean” neighborhood environments have been shown to increase insomnia and depression symptoms among older adults and adolescents in the US and Japan [14, 15]. Additionally, in-home pest infestation has been linked to increased odds of worse mental health outcomes [11]. Neighborhood order, of which cleanliness is a component, is also associated with higher community pride and trust in neighbors [16], indicating the potential for an interactive effect of neighborhood cleanliness and social cohesion on mental health. In a study investigating neighborhood physical disorder as an effect modifier of social cohesion on self-rated health in Los Angeles, Bjornstrom et al. note that physical and social neighborhood disorder can lead to residents distrusting and withdrawing from their communities which can prevent the development of neighborhood social cohesion [17]. They found the positive impact of social cohesion on self-rated health to be diminished by neighborhood disorder [17]. The combined effect of social cohesion and neighborhood cleanliness on mental health in New York has been largely unstudied, and how these two factors impacted the mental health of New Yorkers during the early years of the COVID-19 pandemic, when mental health was challenged on numerous fronts, is unknown.
Our study used 2020 NYC Community Health Survey (CHS) data to investigate the association of social cohesion and neighborhood rodent sightings (a proxy for neighborhood cleanliness) with nonspecific serious psychological distress (NSPD) status and examined potential effect measure modification (EMM) among residents of NYC.
Methods
Study Design
For this study, we used data from the 2020 NYC Community Health Survey (CHS) [18] which is a cross-sectional survey conducted annually by the NYC DOHMH. The CHS collected data from adults over the age of 18 living in non-group settings in NYC and who have a cell phone or live in a household with a landline telephone. A stratified random sampling method was used to produce neighborhood and citywide estimates. Neighborhoods were determined by ZIP codes using United Hospital Fund (UHF)–defined neighborhoods. To avoid small sample sizes, the 42 UHF neighborhoods were collapsed into 34 neighborhoods. Phone numbers were selected from a sampling frame provided by a commercial vendor, and one adult per selected household was randomly chosen to participate [19]. Participants were consented prior to answering survey questions, and the NYC Department of Health IRB reviews all research prior to initiation. Data were collected using a computer-assisted telephone interviewing system from March to December of 2020. Surveys were conducted in Bengali, Chinese, English, Haitian Creole, Russian, and Spanish. Data were collected from 8781 New Yorkers, and the survey had a response rate, defined as the number who completed the survey divided by all individuals who are known to be or likely to be eligible, of 7.4%, and a cooperation rate, defined as the number who participated in the survey divided by the number of individuals in the sample who were contacted and identified as eligible, of 74.4% [19].
Measures
The outcome of interest was nonspecific serious psychological distress (NSPD), which was measured using the six-item Kessler Psychological Distress Scale (K6) [20]. The K6 is a validated psychometric instrument that asks respondents to rate the frequency of feeling sad, nervous, restless/fidgety, hopeless, that everything was an effort, and worthless over the past 30 days, with answers collected on a Likert scale with five response options: (1) none of the time, (2) a little of the time, (3) some of the time, (4) most of the time, and (5) all of the time [20]. The total score was calculated by NYC DOHMH by summing the numerical scores of each of the six questions and collapsing the score into a dichotomous indicator for NSPD (total score > 12 as defined by the scale developers [20]) for analysis [21, 22].
The main exposure of interest was neighborhood social cohesion (missing = 446) which was determined based on agreement with five statements: (1) “People in your neighborhood are willing to help their neighbors,” (2) “I can trust at least one of my neighbors with a key to my home in case of an emergency, such as being locked out,” (3) “I get together with people in my neighborhood to discuss common political and social issues happening in my community,” (4) “I contribute to community projects or events such as organizing block parties, helping at a community center, garden, or school fundraisers,” and (5) “I’m proud to live in my neighborhood.” The first statement was only asked to a randomly selected set of participants who completed the long version of the survey (n = 4336). Response options were on a five-point Likert scale ranging from strongly agree to strongly disagree for the first item and a four-point Likert scale ranging from strongly agree to strongly disagree for items 2–5. Each of the five factors was reverse-coded such that a higher score corresponds to an increase in social cohesion. For any participants for whom only one of the five factors was missing, the mean of the four responses was used to impute the missing response. Using the methodology previously described [23], a single binary social cohesion variable was created by first summing the responses for all five factors and then splitting the resulting continuous variable at the midpoint to create an indicator for high social cohesion (score range: [12.5–21]) versus low social cohesion (score range [5–12.5]). The internal consistency of the scale was assessed as acceptable (Cronbach’s alpha = 0.7), especially given the small number of items (n = 5) [24]. The CHS included a sixth question related to social cohesion: “If I saw someone walking their dog in my neighborhood and they didn’t clean up after their dog, I’d say something to them about it.” We did not include this question in the measure because it did not coincide with the questions used in other social cohesion measures described in the literature [6, 8, 15]. However, as a sensitivity analysis, we added this sixth question to our social cohesion measure and reran the models. The Cronbach’s alpha for the six-item measure did not change (0.7). As a second sensitivity analysis, all models were rerun only including those who completed the long version of the survey.
Neighborhood rodent sightings were investigated as both a secondary exposure of interest and an effect modifier of social cohesion on NSPD. Rodent sightings were determined by responses of “yes” to the question: “At any time in the last 90 days have you seen any mice or rats or signs of mice or rats on the street where you live?” Rodents are a consequence resulting from poor sanitation [25] and reporting rodent sightings is used in our analysis as a proxy for lack of neighborhood cleanliness.
We included several confounders in our analysis. Combined household income as percent below the federal poverty level was provided in five categories ranging from < 100 to ≥ 600%; for analyses, categories were combined into a dichotomous indicator (< 200% versus ≥ 200%). Age, sex assigned at birth, education level, and employment status were also included. Race/ethnicity was determined based on response to two questions: (1) “Are you Hispanic or Latino/a?” and (2) “Which one or more of the following would you use to describe yourself? Would you describe yourself as…” with answer choices: White; Black or Black American; Asian; Middle Eastern or North African; Native Hawaiian or Other Pacific Islander; American Indian, Native, First Nations, Indigenous Peoples of the Americas, or Alaska Native; or Something else. For this analysis, we used the five-category race/ethnicity indicator provided in the public data, with categories of (1) non-Hispanic White/North African/Middle Eastern (White), (2) non-Hispanic Black (Black), (3) Hispanic, (4) non-Hispanic Asian/Pacific Islander (Asian), and (5) non-Hispanic Other (Other). Other included American Indian, Native, First Nations, Indigenous Peoples of the Americas, and Alaska Native.
Analyses
We describe the population overall and stratified by social cohesion, reporting unweighted sample size and weighted percentages. The Rao-Scott chi-squared test was used to examine differences in characteristics by social cohesion. We used univariate logistic regression models to estimate the crude association of each variable with NSPD. We then developed a multivariable logistic regression model including both exposures and all confounders described above. Multiplicative EMM was assessed by adding an interaction term for social cohesion*rodent sightings to the multivariable model; if we found significant statistical interaction, we reran the multivariable model stratified on the effect modifier. Additive EMM was assessed by calculating the relative excess risk due to interaction (RERI) and its 90% confidence interval (CI). Using people who reported low social cohesion and no rodent sightings as the common reference group, we calculated the odds of NSPD for those reporting high social cohesion and no rodent sightings, the odds of NSPD for those reporting low social cohesion and rodent sightings, and the odds of NSPD for those reporting high social cohesion and rodent sightings. Statistical significance was set at α = 0.05 for main effects, and α = 0.1 was used for the assessment of statistical interaction due to the decreased statistical power for assessing interaction [26]. All analyses were conducted in SAS Studio version 3.81 (Cary, NC), adjusted for the complex sampling, and weighted to the New York City population.
Results
The total analytic sample included 8781 NYC residents. Overall, 6.2% of adults in NYC screened positive for NSPD, high neighborhood social cohesion was reported by 61.4% of participants, and neighborhood rodent sightings were reported by 34.2% of participants (Table 1). Among all participants, 54.9% had household income ≥ 200% of the federal poverty line, about half (53.6%) were female at birth, and 53.2% were aged 18–44 years. The largest racial/ethnic group was White (35.6%), followed by Hispanic (26.9%), Black (22.0%), Asian (13.2%), and Other (2.4%). More than half (58.6%) of the population had completed at least some college or technical school. The majority were employed (55.7%), while 30.7% reported not being in the labor force and 13.6% were unemployed (Table 1).
Table 1.
Description of 2020 NYC Community Health Survey population overall and stratified by level of social cohesion
| Variable | Total sample, n (wt%) | Low social cohesion, n (wt%) | High social cohesion, n (wt%) | Rao-Scott X2 p-value |
|---|---|---|---|---|
| Total | 8781* | 3168 (38.6%) | 5167 (61.4%) | N/A |
| Nonspecific serious psychological distress (NSPD) (N missing = 0) | 8781 | 0.012 | ||
| Has NSPD | 516 (6.2%) | 232 (7.6%) | 252 (5.4%) | |
| Does not have NSPD | 8265 (93.8%) | 2936 (92.4%) | 4915 (94.6%) | |
| Rodents sighted in neighborhood (N missing = 46) | 8735 | 0.010 | ||
| No | 5433 (65.8%) | 2005 (63.0%) | 3428 (67.1%) | |
| Yes | 2868 (34.2%) | 1152 (37.0%) | 1716 (32.9%) | |
| Combined household income (N missing = 0) | 8781 | 0.0002 | ||
| ≥ 200% federal poverty line | 4998 (54.9%) | 1478 (51.7%) | 2073 (58.0%) | |
| < 200% federal poverty line | 3783 (45.1%) | 1690 (48.3%) | 3094 (41.9%) | |
| Age (N missing = 14) | 8767 | < 0.0001 | ||
| 18–44 | 3895 (53.2%) | 1371 (62.8%) | 2299 (48.2%) | |
| 45 + | 4872 (46.8%) | 1791 (37.2%) | 2852 (51.8%) | |
| Sex assigned at birth (N missing = 29) | 8752 | 0.198 | ||
| Male | 3850 (46.4%) | 1355 (45.1%) | 2474 (47.3%) | |
| Female | 4902 (53.6%) | 1627 (54.9%) | 3251 (52.7%) | |
| Race/ethnicity (N missing = 0) | 8781 | < 0.0001 | ||
| White | 2859 (35.6%) | 779 (26.6%) | 1942 (41.5%) | |
| Black | 1837 (22.0%) | 748 (26.0%) | 1004 (19.6%) | |
| Hispanic | 2457 (26.9%) | 1051 (31.8%) | 1301 (24.0%) | |
| Asian | 1340 (13.2%) | 495 (13.8%) | 741 (12.2%) | |
| Other | 288 (2.4%) | 95 (1.9%) | 179 (2.6%) | |
| Education level (N missing = 49) | 8732 | 0.0004 | ||
| College graduate | 4009 (36.2%) | 1331 (32.6%) | 2514 (39.4%) | |
| Some college/technical school | 1691 (22.4%) | 648 (23.6%) | 968 (21.9%) | |
| High school graduate | 1809 (23.9%) | 681 (25.0%) | 1038 (23.2%) | |
| Less than high school | 1223 (17.5%) | 487 (18.8%) | 625 (15.4%) | |
| Employment status (N missing = 60) | 8721 | 0.125 | ||
| Employed | 4720 (55.7%) | 1705 (56.0%) | 2835 (57.0%) | |
| Unemployed | 1172 (13.6%) | 491 (15.1%) | 627 (12.8%) | |
| Not in labor force | 2829 (30.7%) | 949 (28.9%) | 1678 (30.3%) |
All sample sizes (n) are unweighted, and all percentages (wt%) are weighted. *446 were missing social cohesion data
Compared to people living in neighborhoods with low social cohesion, people living in neighborhoods with high social cohesion were more likely to not report seeing rodents in their neighborhood (67.1% vs. 63.0%, p = 0.010), to have a combined household income of ≥ 200% of the federal poverty line (58.0%, vs. 51.7%, p < 0.001), to be White (41.5% vs. 26.6%, p < 0.0001), and to be college graduates (39.4% vs. 32.6%, p < 0.001) (Table 1).
The unadjusted odds of NSPD were 0.70 (95%CI 0.53, 0.92) times lower among those with high social cohesion compared to those with low social cohesion. The unadjusted odds of NSPD were 1.73 (95%CI 1.32, 2.28) times higher among individuals who reported seeing rodents in their neighborhood compared to those who had not seen rodents (Table 2). The associations were similar in the adjusted model; the adjusted odds of NSPD were 0.73 (95%CI 0.55, 0.97) times lower among those with high social cohesion and 1.66 (95%CI 1.25, 2.20) times higher among residents of neighborhoods with rodents (Table 2).
Table 2.
Univariate and multivariable logistic regression models evaluating the odds of nonspecific serious psychological distress by social cohesion and neighborhood rodent sightings
| Univariate model | Multivariable model (n = 8183) | ||||
|---|---|---|---|---|---|
| Variable | n | Odds ratio [95% CI] | P-value | Odds ratio [95% CI] | P-value |
| Social cohesion (ref = low) | |||||
| High social cohesion | 0.70 [0.53, 0.92] | 0.012 | 0.73 [0.55, 0.97] | 0.032 | |
| Rodents sighted in neighborhood (ref = no) | 8735 | ||||
| Yes | 1.73 [1.32, 2.28] | < 0.0001 | 1.66 [1.25, 2.20] | 0.0004 | |
| Combined household income (ref = ≥ 200% federal poverty line) | 8781 | ||||
| < 200% federal poverty line | 2.27 [1.71, 3.00] | < 0.0001 | 1.98 [1.42, 2.76] | < 0.0001 | |
| Age (ref = 18–44 years) | 8767 | ||||
| 45 + years | 0.96 [0.73, 1.25] | 0.7408 | 0.85 [0.64, 1.12] | 0.252 | |
| Sex assigned at birth (ref = male) | 8752 | ||||
| Female | 1.59 [1.21, 2.09] | 0.001 | 1.47 [1.11, 1.95] | 0.007 | |
| Race/Ethnicity (ref = White) | 8781 | ||||
| Black | 1.05 [0.70, 1.55] | 0.829 | 0.76 [0.49, 1.19] | 0.227 | |
| Hispanic | 1.50 [1.07, 2.09] | 0.019 | 0.91 [0.59, 1.39] | 0.646 | |
| Asian | 0.94 [0.59, 1.50] | 0.802 | 0.74 [0.44, 1.23] | 0.238 | |
| Other | 1.92 [0.80, 4.59] | 0.142 | 1.60 [0.63, 4.05] | 0.323 | |
| Education level (ref = college graduate) | 8732 | ||||
| Some college/technical school | 1.38 [0.94, 2.03] | 0.100 | 1.13 [0.75, 1.70] | 0.550 | |
| High school graduate | 1.40 [0.97, 2.04] | 0.077 | 0.97 [0.63, 1.49] | 0.884 | |
| Less than high school | 1.85 [1.29, 2.65] | 0.001 | 1.11 [0.69, 1.79] | 0.678 | |
| Employment status (ref = employed) | 8721 | ||||
| Unemployed | 2.07 [1.45, 2.97] | < 0.0001 | 1.80 [1.22, 2.67] | 0.003 | |
| Not in labor force | 2.26 [1.67, 3.05] | < 0.0001 | 1.95 [1.40, 2.71] | < 0.0001 | |
The interaction term for social cohesion*rodent sightings was significant at the a priori α = 0.1 in the multivariable model (p = 0.059) indicating EMM on the multiplicative scale. After stratifying on rodent sightings, we found that the protective effect of high social cohesion on NSPD existed only among those who had not seen rodents in their neighborhood (OR = 0.57, 95%CI [0.39, 0.82]); among those who had seen rodents in their neighborhood, there was no effect (OR = 0.99, 95%CI [0.65, 1.51]) (Table 3). The estimated RERI was 0.41 (90%CI − 0.07, 0.88). These findings suggest there may be EMM between high social cohesion and rodent sightings on the additive scale; however, the confidence interval contained the null value of 0. Associations for both sensitivity analyses were consistent with multivariable models and EMM findings.
Table 3.
Multivariable logistic regression models evaluating the association of social cohesion on nonspecific serious psychological distress stratified by neighborhood rodent sightings
| Has seen a rodent (n = 3105) | Has not seen a rodent (n = 5078) | |||
|---|---|---|---|---|
| Variable | Odds ratio [95% CI] | P-value | Odds ratio [95% CI] | P-value |
| Social cohesion (ref = low) | ||||
| High | 0.99 [0.65, 1.51] | 0.973 | 0.57 [0.39, 0.82] | 0.003 |
| Combined household income (ref = ≥ 200% federal poverty line) | ||||
| < 200% federal poverty line | 1.76 [1.08, 2.87] | 0.023 | 2.21 [1.42, 3.46] | 0.001 |
| Age (ref = 18–44 years) | ||||
| 45 + years | 0.64 [0.43, 0.94] | 0.022 | 1.08 [0.762, 1.62] | 0.713 |
| Sex assigned at birth (ref = male) | ||||
| Female | 1.33 [0.88, 2.00] | 0.177 | 1.67 [1.41, 2.44] | 0.008 |
| Race/Ethnicity (ref = White) | ||||
| Black | 0.64 [0.35, 1.19] | 0.160 | 0.86 [0.46, 1.60] | 0.632 |
| Hispanic | 0.75 [0.41, 1.39] | 0.358 | 0.96 [0.56, 1.65] | 0.755 |
| Asian | 0.57 [0.25, 1.28] | 0.173 | 0.91 [0.47, 1.76] | 0.780 |
| Other | 1.13 [0.27, 4.77] | 0.863 | 2.04 [0.64, 6.57] | 0.228 |
| Education level (ref = college graduate) | ||||
| Some college/technical school | 1.29 [0.68, 2.44] | 0.435 | 1.06 [0.62, 1.81] | 0.838 |
| High school graduate | 1.24 [0.63, 2.43] | 0.529 | 0.81 [0.46, 1.42] | 0.455 |
| Less than high school | 1.36 [0.64, 2.89] | 0.423 | 0.91 [0.49, 1.67] | 0.750 |
| Employment status (ref = employed) | ||||
| Unemployed | 1.47 [0.80, 2.71] | 0.212 | 2.23 [1.34, 3.69] | 0.002 |
| Not in labor force | 1.76 [1.11, 2.80] | 0.017 | 2.18 [1.37, 3.47] | 0.001 |
Discussion
In this study, we investigated the effect of social cohesion, neighborhood rodent sightings (as a proxy for neighborhood cleanliness), and the combination of the two on nonspecific serious psychological distress (NSPD) status. We found that high neighborhood social cohesion was associated with decreased NSPD while neighborhood rodent sightings were associated with increased NSPD. When examining the joint effect of these exposures, we found social cohesion to be protective against NSPD only among those who had not reported seeing rodents on their street; among those who reported seeing rodents on their street, we found no effect.
Our findings that high social cohesion was protective against serious mental health disorders while neighborhood rodent sightings increased the odds of NSPD are consistent with previous studies. Social cohesion is an indicator of community belonging and engagement, and can facilitate the development of social structures that promote health such as social support and informal social control [17]. Further, socially cohesive communities may provide both a powerful sense of belonging and identification with a social group which may be beneficial for both physical and mental wellbeing [7]. Meanwhile, physical neighborhood disorder, of which neighborhood cleanliness is a component, is understood as an indication of the collapse of informal social control and has been linked to fear and isolation, both of which have been found to be associated with poor mental health [17]. Further, pest infestation is thought to be perceived as an “uncontrollable stressor,” leading to feelings of loss of control which has been found to increase risk for poor mental health outcomes [11].
Our analysis was unique in examining the joint effect of social cohesion and neighborhood rodent sightings, and our findings were somewhat unexpected. We observed that seeing rodents may be an effect modifier of the association between social cohesion and NSPD. Our observation that lack of cleanliness may erode the protective effect of social cohesion on NSPD aligns with Bjornstrom et al.’s [17] finding that the positive impact of social cohesion on self-rated health was hindered by neighborhood disorder [17]. The additive EMM phenomenon could be partially explained by findings from a previous study which investigated informal social control—which often arises from or alongside high social cohesion—as a mediator of the impact of neighborhood disorder on mental health. This study found that while decreased neighborhood disorder was associated with increased informal social control, increased informal social control was associated with increased anxiety symptoms [27]. The author notes that since informal social control involves willingness to take action to address neighborhood problems (e.g., violence or vandalism), this could be associated with “increased vigilance, frustration, or anxiety” [27]. Applying this concept to our findings, since high/increased social cohesion involves being actively engaged with and deriving a sense of identity from one’s community, when one is faced with neighborhood disorder—such as rodent sightings—they may be more likely to be negatively affected.
During the COVID-19 pandemic, when these data were collected, neighborhood social cohesion may have been lower than prior to the epidemic as a result of the lockdown and recommendations for social distancing [28]. Additionally, NYC’s sanitation budget was cut resulting in less frequent trash pickups and street cleanings [29], which likely contributed to an increase in complaints about both trash and rats on NYC streets [25]. It is possible that the pandemic contributed both to lower social cohesion and increased rodent presence on NYC streets which could have contributed to the increase in poor mental health across NYC during the COVID-19 pandemic [30]. Given our findings showing the harmful effects of these exposures, we may expect to see an increase in NSPD cases particularly among neighborhoods with high reports of rodent sightings and high social cohesion.
Our findings suggest that increasing social cohesion and improving the cleanliness of neighborhoods could be means to improve mental health outcomes in NYC. Targeted, community- and evidence-based interventions should be considered to improve social cohesion in NYC. One model that could be used is Neighbor Day, an Australian campaign which builds social cohesion by empowering individuals to organize activities in their local communities such as barbeques/picnics, home visits to elderly neighbors, or setting up neighborhood WhatsApp groups. Neighbor Day’s community-led nature allows for cultural and contextual tailoring based on community preferences, which would be beneficial for NYC’s diverse cultural landscape, and has been found to increase neighborhood social cohesion and decrease psychological distress [31]. Additional interventions to improve social cohesion could include community volunteering opportunities, arts and cultural activities, sports groups, online spaces, access to green spaces, and neighborhood regeneration programs [32]. However, given our findings, interventions to improve mental health through facilitating social cohesion may only be effective in communities that are also clean. Therefore, existing efforts to improve cleanliness and reduce pest infestation should continue. If neighborhood sanitation program changes are considered during future disease outbreaks to decrease workforce risk and modify street parking rules so people do not need to move their cars for street cleaning, the potential impact of deteriorating neighborhood cleanliness on mental health should be taken into consideration and programs to try to minimize the impact on neighborhood cleanliness should be put into effect (e.g., public messaging about the importance of minimizing garbage and not dropping trash on streets as well as policies to minimize packaging of home deliveries to decrease waste).
This study has a number of limitations that should be considered when interpreting the results. This was a cross-sectional study, which prevents the assessment of temporality between neighborhood social cohesion/rodent sightings and NSPD. It is possible that people with NSPD are more likely to live in dirtier and less cohesive neighborhoods, perhaps due to challenges with employment that have economic consequences, affecting where they can afford to live. It is also possible that, given the cultural diversity of NYC, some of the mental health questions may have been poorly understood by some respondents, since mental health symptoms tend to be culturally specific [33]. We think this misclassification of the outcome would be non-differential, biasing our results towards the null. In addition, there may have been residual confounding due to the lack of data on other causes of mental health distress that we could not adjust for, such as housing type and condition, which may be associated with both rodent infestations and social cohesion [34, 35]. Further, while the questions used to measure social cohesion were similar to those used in previous studies, a validated scale was not used to measure social cohesion in this study. Lastly, our findings cannot be generalized to New Yorkers who do not have telephones or who are living in group-living environments, such as incarcerated individuals, students, and those living in shelters or elderly care facilities, as they were excluded from this survey. In addition, the NYC population is extremely diverse and therefore our findings may not be generalizable to other populations; and due to the unique impact of the COVID-19 pandemic, our findings may not be generalizable to other time periods.
Our study is one of the first to explore the impact of neighborhood social cohesion and neighborhood cleanliness on mental health in NYC. Our findings suggest that neighborhood social cohesion and rodent sightings impact the mental health of New Yorkers individually and jointly, and that the positive effect of social cohesion is only present among those not reporting rodent sightings. Additional research into the combined effects of social and physical neighborhood environment would be beneficial for better understanding these effects and for designing and evaluating ways to improve mental health in NYC.
Data Availability
Data supporting all results and tables are publicly available at the following link: https://www.nyc.gov/site/doh/data/data-sets/community-health-survey-public-use-data.page [18].
Footnotes
Publisher's Note
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References
- 1.Mental disorders. World health organization.https://www.who.int/news-room/fact-sheets/detail/mental-disorders. Accessed May 5 2023.
- 2.Mental Health Data Dashboard. NYC Mayor’s office of community mental health.https://mentalhealth.cityofnewyork.us/dashboard/. Accessed March 11 2023.
- 3.National Center for Chronic Disease Prevention and Health Promotion DoPH. About Mental Health. Centers for disease control and prevention. Updated June 28, 2021. https://www.cdc.gov/mentalhealth/learn/index.htm. Accessed March 11 2023.
- 4.Epi data brief: health equity in New York City: social determinants of mental health among New York City Adults. 2019. https://www.nyc.gov/assets/doh/downloads/pdf/epi/databrief115.pdf. Accessed 11 Mar 2023.
- 5.Compton MT, Shim RS. The social determinants of mental health. FOCUS. 2015;13(4):419–425. doi: 10.1176/appi.focus.20150017. [DOI] [Google Scholar]
- 6.Buckner JC. The development of an instrument to measure neighborhood cohesion. Am J Community Psychol. 1988;16(6):771–791. doi: 10.1007/BF00930892. [DOI] [Google Scholar]
- 7.Bowe M, Wakefield JRH, Kellezi B, et al. The mental health benefits of community helping during crisis: coordinated helping, community identification and sense of unity during the COVID-19 pandemic. J Community Appl Soc Psychol. 2022;32(3):521–535. doi: 10.1002/casp.2520. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Williams AJ, Maguire K, Morrissey K, Taylor T, Wyatt K. Social cohesion, mental wellbeing and health-related quality of life among a cohort of social housing residents in Cornwall: a cross sectional study. BMC Public Health. 2020;20(1):985. doi: 10.1186/s12889-020-09078-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Yeo LHW, Mah FCY, Chong EY, Lim AH, Ng ST, Yi H. Does gender matter to promote mental health through community engagement among older adults? Aging Ment Health. 2022;26(1):186–195. doi: 10.1080/13607863.2020.1855106. [DOI] [PubMed] [Google Scholar]
- 10.Seo BK, Park GR. Housing, living arrangements and mental health of young adults in independent living. Int J Environ Res Public Health. 2021;18(10). 10.3390/ijerph18105250. [DOI] [PMC free article] [PubMed]
- 11.Shah SN, Fossa A, Steiner AS, et al. Housing quality and mental health: the association between pest infestation and depressive symptoms among public housing residents. J Urban Health. 2018;95(5):691–702. doi: 10.1007/s11524-018-0298-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Leventhal T, Brooks-Gunn J. Moving to opportunity: an experimental study of neighborhood effects on mental health. Am J Public Health. 2003;93(9):1576–1582. doi: 10.2105/ajph.93.9.1576. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Wee LE, Tsang YYT, Tay SM, et al. Perceived neighborhood environment and its association with health screening and exercise participation amongst low-income public rental flat residents in Singapore. Int J Environ Res Public Health. Apr 17 2019;16(8). 10.3390/ijerph16081384. [DOI] [PMC free article] [PubMed]
- 14.Asakura T. Neighborhood environment quality, individual-level social capital, and depressive symptoms among adolescents. Nihon Koshu Eisei Zasshi. 2011;58(9):754–767. [PubMed] [Google Scholar]
- 15.Chen-Edinboro LP, Kaufmann CN, Augustinavicius JL, et al. Neighborhood physical disorder, social cohesion, and insomnia: results from participants over age 50 in the Health and Retirement Study. Int Psychogeriatr. 2014;1–8. 10.1017/s1041610214001823. [DOI] [PMC free article] [PubMed]
- 16.Nienaber S. Foundations of Civic Health: Neighborhood Order (and Disorder). 2017. https://www.nlc.org/article/2017/07/27/foundations-of-civic-health-neighborhood-order-and-disorder/. Accessed 15 Sept 2023.
- 17.Bjornstrom EE, Ralston ML, Kuhl DC. Social cohesion and self-rated health: the moderating effect of neighborhood physical disorder. Am J Community Psychol. 2013;52(3–4):302–312. doi: 10.1007/s10464-013-9595-1. [DOI] [PubMed] [Google Scholar]
- 18.Data from: Community Health Survey Public Use Data. New York City: Department of Health and Mental Hygiene; 2020. https://www.nyc.gov/site/doh/data/data-sets/community-health-survey-public-use-data.page. Accessed 13 Feb 2023.
- 19.Community Health Survey Methodology. New York City Department of Health and Mental Hygiene. https://www.nyc.gov/site/doh/data/data-sets/community-health-survey-methodology.page. Accessed March 11 2023.
- 20.Kessler RC, Barker PR, Colpe LJ, et al. Screening for serious mental illness in the general population. Arch Gen Psychiatry. 2003;60(2):184–189. doi: 10.1001/archpsyc.60.2.184. [DOI] [PubMed] [Google Scholar]
- 21.2020 NYC Community Health Survey Analytic Codebook. New York City Department of Health and Mental Hygiene. https://www.nyc.gov/assets/doh/downloads/pdf/episrv/chs2020-codebook.pdf. Accessed February 13 2023.
- 22.2020 New York City Community Health Survey. New York City Department of Health and Mental Hygiene. https://www.nyc.gov/assets/doh/downloads/pdf/episrv/chs2020survey.pdf. Accessed February 13 2023.
- 23.Xie B, Ma C, Wang J. Independent and combined relationships of perceived neighborhood social cohesion and physical frailty on functional disability in community-dwelling older adults. Int J Environ Res Public Health. 2020;17(16):5912. doi: 10.3390/ijerph17165912. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Morera OF, Stokes SM. Coefficient α as a measure of test score reliability: review of 3 popular misconceptions. Am J Public Health. 2016;106(3):458–461. doi: 10.2105/ajph.2015.302993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Mays JC. In battle against trash and rats, N.Y.C. Officials try a schedule shift. The New York Times. 2022. https://www.nytimes.com/2022/10/17/nyregion/garbage-nyc-sidewalk-timing.html. Accessed September 15 2023.
- 26.Marshall SW. Power for tests of interaction: effect of raising the Type I error rate. Epidemiol Perspect Innov. 2007;4:4. 10.1186/1742-5573-4-4. [DOI] [PMC free article] [PubMed]
- 27.Mattocks N. Neighborhood disorder and mental health outcomes among a sample of Baltimore City residents: the influence of urban parks, social cohesion, and social control. University of Maryland Baltimore; 2019. https://archive.hshsl.umaryland.edu/handle/10713/11606. Accessed 15 Sept 2023.
- 28.Jewett RL, Mah SM, Howell N, Larsen MM. Social cohesion and community resilience during COVID-19 and pandemics: a rapid scoping review to inform the United Nations research roadmap for COVID-19 recovery. Int J Health Serv. 2021;51(3):325–336. doi: 10.1177/0020731421997092. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.McGowan C. How the city’s budget cuts will impact sanitation operations. Spectrum News NY1. 2020. https://ny1.com/nyc/all-boroughs/news/2020/07/07/dsny-sanitation-budget-cuts-what-to-expect. Accessed September 15 2023.
- 30.Still recovering: mental health impact of the COVID-19 pandemic in New York State. 2021. https://nyhealthfoundation.org/resource/still-recovering-mental-health-impact-of-the-covid-19-pandemic-in-new-york-state/#key-findings. Accessed September 23, 2023.
- 31.Cruwys T, Fong P, Evans O, Rathbone JA. A community-led intervention to build neighbourhood identification predicts better wellbeing following prolonged COVID-19 lockdowns. Front Psychol. 2022;13:1030637. doi: 10.3389/fpsyg.2022.1030637. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Breedvelt JJF, Tiemeier H, Sharples E, et al. The effects of neighbourhood social cohesion on preventing depression and anxiety among adolescents and young adults: rapid review. BJPsych Open. 2022;8(4):e97. doi: 10.1192/bjo.2022.57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Chapter 2 Culture counts: the influence of culture and society on mental health. 2001. Mental health: culture, race, and ethnicity: a supplement to mental health: a report of the Surgeon General. https://www.ncbi.nlm.nih.gov/books/NBK44243/pdf/Bookshelf_NBK44243.pdf. Accessed 23 Sept 2023.
- 34.Brisson D, Peña SL, Plassmeyer M. Prioritizing choice: perceptions of neighborhood social cohesion for residents in subsidized housing. J Soc Serv Res. 2018;44(3):267–278. doi: 10.1080/01488376.2018.1457592. [DOI] [Google Scholar]
- 35.Garg R, McQueen A, Wolff JM, Skinner KE, Kegler MC, Kreuter MW. Low housing quality, unmet social needs, stress and depression among low-income smokers. Prev Med Rep. 2022;27:101767. doi: 10.1016/j.pmedr.2022.101767. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data supporting all results and tables are publicly available at the following link: https://www.nyc.gov/site/doh/data/data-sets/community-health-survey-public-use-data.page [18].