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. Author manuscript; available in PMC: 2023 Apr 15.
Published in final edited form as: Environ Res. 2021 Oct 22;206:112254. doi: 10.1016/j.envres.2021.112254

Noise complaint patterns in New York City from January 2010 through February 2021: Socioeconomic disparities and COVID-19 exacerbations

Bruce Ramphal a, Jordan D Dworkin a, David Pagliaccio a, Amy E Margolis a
PMCID: PMC8838876  NIHMSID: NIHMS1751725  PMID: 34695430

Abstract

Background:

Excessive environmental noise exposure and noise annoyance have been linked to adverse physical and mental health outcomes. Although socioeconomic disparities in acoustically measured and geospatially estimated noise have been established, less is known about disparities in noise complaints, one of the most common sources of distress reported to local municipalities. Furthermore, although some studies have posited urban quieting during the COVID-19 pandemic, little empirical work has probed this and probed noise complaints during the pandemic.

Objectives:

Using over 4 million noise complaints from the New York City (NYC) 311 database, we quantified census tract-level socioeconomic disparities in noise complaints since 2010 and examined how such disparities changed during the COVID-19 pandemic.

Methods:

Using data from January 2010 through February 2020, we fit linear mixed-effects models, estimating monthly tract-level noise complaints by the proportion of residents who were low-income, time in months since January 2010, categorical month, their interactions, and potential confounds, such as total population and population density. To estimate COVID-19 pandemic effects, we included additional data from March 2020 through February 2021 and additional interactions between proportion low-income, month of year, and an indicator variable for COVID-19 pandemic onset in March 2020.

Results:

Census tracts with a higher proportion of low-income residents reported more monthly noise complaints and this increased over time (time×month×proportion low-income interaction p-values < .0001 for all months), particularly in warmer months. Socioeconomic disparities in noise complaints were exacerbated during the COVID-19 pandemic (month×proportion low-income×pandemic era interaction p-values < .0001 for March through November), also in a seasonal manner.

Discussion:

Since 2010, noise complaints have increased the most in the most economically distressed communities, particularly in warmer seasons. This disparity was particularly exacerbated during the COVID-19 pandemic, contrary to some theories of urban quieting. Community-based interventions to ameliorate noise and noise annoyance, both public health hazards, are needed in underserved communities.

Keywords: noise, noise annoyance, noise complaints, COVID-19 pandemic, socioeconomic status

Introduction

Excessive environmental noise (e.g., from traffic, airplanes, construction, etc.) and noise annoyance (irritation resultant from unwanted noise) are associated with poor auditory, cardiovascular, metabolic, cognitive, sleep, and mental health outcomes across the lifespan (Basner et al., 2014; Bronzaft & McCarthy, 1975; Lan, Roberts, Kwan, & Helbich, 2020; Stansfeld, Haines, & Brown, 2000). Neighborhood-level noise exposure has previously been examined using acoustic recordings (Collins, Nadybal, & Grineski, 2020) and geospatial models that incorporate recordings, land use, environmental acoustics, and other parameters (Casey et al., 2017; Mennitt & Fristrup, 2016). Using these methods, it has been shown that stay-at-home orders during the COVID-19 pandemic resulted in reductions in public noise in cities (Aletta, Brinchi, et al., 2020; Aletta, Oberman, Mitchell, Tong, & Kang, 2020; Asensio, Pavón, & De Arcas, 2020; Basu et al., 2021; Rumpler, Venkataraman, & Göransson, 2020).

Municipal noise complaint repositories represent a relatively untapped source of noise data that may potentially probe neighborhood-level noise annoyance, an important (though not the only) mediator linking excessive noise exposure to poor health outcomes (Basner et al., 2014; Stansfeld et al., 2000). In Vancouver, noise complaints are elevated near construction sites, particularly during the evening and early morning (Hong, Kim, & Widener, 2019). In New York city, noise complaint rates are generally higher in areas nearer to street intersections, during the weekends, and in the late evening, and noise complaints about outdoor noise sources increase during warmer months (Tong & Kang, 2021a). These lines of evidence suggest that neighborhood-level noise complaints likely track neighborhood-level noise conditions and associated annoyance.

Studies that analyze acoustic street recordings have demonstrated that lower-income communities and communities of color experience greater noise exposure (Casey et al., 2017; Collins et al., 2020), however less is known about disparities in noise complaints. One study examining almost 400,000 noise complaints in London showed that more socioeconomically distressed communities also reported more noise complaints in 2011 (Tong & Kang, 2021b). Furthermore, although acoustically measured street noise decreased following stay-at-home orders during the COVID-19 pandemic in multiple cities (Aletta, Brinchi, et al., 2020; Aletta, Oberman, et al., 2020; Asensio et al., 2020; Basu et al., 2021; Rumpler et al., 2020), few studies have examined noise complaints using municipal data during the pandemic. One analysis of 43,186 noise complaints in London demonstrated that the COVID-19 pandemic coincided with an increase in noise complaints during spring 2020 relative to spring 2019, particularly in socioeconomically distressed communities (Tong, Aletta, Mitchell, Oberman, & Kang, 2021). Another study of about 4,000 noise complaints in Dallas, Texas, however, demonstrated pandemic-related reductions in noise complaints (Yildirim & Arefi, 2021). Other studies using survey data have examined transformations of the in-home soundscape during the COVID-19 pandemic (Andargie, Touchie, & O’Brien, 2021; Dzhambov et al., 2021; Torresin et al., 2021).

Herein, we analyze data on over 4 million municipal noise complaints in New York City (NYC) from January 2010 through February 2021. New York City was examined because it was particularly affected by the first wave of COVID-19 in the United States, has substantial inequality, has high population density, and has not been examined in previous studies of pandemic-related noise. Specifically, we examine whether socioeconomic disparities in noise complaints existed in NYC before the COVID-19 pandemic, how the pandemic has affected noise complaints, and whether this effect has been socioeconomically disparate. Given the multifarious health consequences of noise and noise annoyance, understanding how they are distributed may help inform the placement of noise-related public health interventions.

Methods

Data sources

The New York City Noise Code circumscribes construction timing (7AM to 6PM), sets decibel limits for nightlife, dissuades loud residential activities, and establishes fines for violations (Protection, 2018). New York City noise complaint data from January 1, 2010 through February 28, 2021 were downloaded from NYC Open Data (https://data.cityofnewyork.us/Social-Services/311-Noise-Complaints/p5f6-bkga/data). Of the 4,332,857 noise complaints downloaded, 4,275,768 (98.7%) included latitude and longitude coordinates and were geocoded to census tracts using the tigris package (version 0.9.4 (Walker, 2016)) in R (version 4.0.0). Tract-level demographic data from the American Community Survey (ACS) 5-Year Estimates (total population and proportion low-income residents (Table C17002; Figure 1A) were acquired using the acs package (version 2.1.4) for 2010 through 2018 (Glenn, 2019). Low-income residents reside in a household with an income-to-poverty ratio below 2 (e.g., $53,000 for a family of four in 2021). Census Bureau tract shapefiles were downloaded using the tigris package (version 0.9.4), and visualization was performed using the leaflet (version 2.0.3 (Cheng, Karambelkar, & Xie, 2021)) and ggplot2 (version 3.3.2 (Wickham, 2011)) packages.

Figure 1.

Figure 1.

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The distribution of A) noise complaints in 2019 and B) the proportion of residents who were low-income (mean of American Community Survey estimates from 2010 through 2018) across New York City. Note that areas of the map in gray do not yield noise complaint data (i.e, bodies of water, airports, parks). For visualization, values above 401 complaints per 1000 residents per year (99th percentile) were Winsorized.

Statistical analyses

Our first analysis sought to examine socioeconomic disparities in census tract-level noise complaints before the COVID-19 pandemic (January 1, 2010 through February 28, 2020). A linear mixed effects model was estimated using the nlme (version 3.1–147) package to examine the monthly number of noise complaints at the tract-level as the dependent variable with the following fixed effect predictors of interest: time (month numbered from 0 for January 2010 to 133 for February 2021 and then divided by 12 to improve coefficient interpretability), month (categorical variable), proportion of residents in a tract who were in low-income households (from ACS, average of values from 2010 through 2018), and their interactions (Supplementary Equation 1). Although the growth of noise complaints over time was best fit using a linear approach, results using a negative binomial model are detailed in the Supplementary Materials (Table S1). We report month-specific time-by-income interaction effects; these coefficients are interpreted as the expected difference in the year-over-year noise complaint increase between a 0% low-income tract and a 100% low-income tract within a given month. This model also included the following fixed effect covariates: population (ACS, average of values from 2010 through 2018) and population density (ACS, population divided by census tract land area; Supplementary Equation 2). Random intercepts for census tract and random slopes for time were included. An autocorrelation covariance structure was used. A post-hoc analysis used January as the reference month to examine seasonal differences in noise complaint disparity growth. Due to the presence of some extreme tract-level noise complaint counts, 29 (out of 282,874 total) values above the 99.99th percentile (corresponding to 710 noise complaints) were Winsorized.

Our second analysis built on our first analysis and sought to examine the effects of COVID-19 on noise complaint growth. To model pandemic-related effects, we included additional data from March 2020 through February 2021 and added a binary variable indicating months during the pandemic (0 before March 2020 and 1 between March 2020 and February 2021). Interactions were added between the pandemic era indicator variable, categorical month, and proportion of residents low-income. We report month-specific pandemic-by-income interaction effects; these coefficients are interpreted as the pandemic-related noise complaint increase disparity between a 0% low-income tract and a 100% low-income tract within a given month. A post-hoc analysis used January as the reference month to examine seasonal differences in pandemic-related noise complaint disparity growth. All statistical tests were two-sided and alpha was set at .002 (.05/24 [12 terms per analysis examined]).

Results

The quantity of noise complaints and the percentage of low-income residents varied widely across census tracts in NYC (Figure 1A and 1B). Tract-level population density was strongly associated with noise complaints such that for every increase in 1 person per 100 square meter, monthly noise complaints increased by 1.7 (p<.0001). Since 2010, noise complaints have increased in a socioeconomically disparate manner (pre-pandemic data is left of black line in Figure 2) with disproportionate increases over time in lower income communities for all months (month × proportion low-income × time interaction, monthly βs=[1.2, 1.0, 1.3, 1.8, 3.6, 4.8, 4.8, 3.9, 3.3, 1.9, 1.1, 1.6], p-values < .0002). Relative to January, economically disparate increases in noise complaints were larger from April through October (monthly p-values <.002). Figure 3A further displays noise complaint increases over time and elevated socioeconomic disparities during warmer months. For example, in July 2010, the mean quantity of noise complaints among tracts in the lowest income quartile (51–98% low-income) was 10, and this value was 5 in the highest income quartile (5–24% low-income). In July 2019, these values were 36 and 10, respectively, corresponding to a yearly increase of 29% in the lowest income quartile and 11% in the highest income quartile.

Figure 2.

Figure 2.

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The evolution of mean monthly noise complaints in New York City from January 2010 through February 2021, stratified by census tract income levels. Census tracts were binned into quartiles based on the proportion of residents who were low-income for visualization only; all statistical analyses were implemented using a continuous variable. The black line corresponds to March 2020, which was when the first case of COVID-19 was detected in New York City.

Figure 3.

Figure 3.

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The growth of socioeconomic disparities in noise complaints from January 2010 through February 2021. A) Model fit lines from our first analysis are shown representing noise complaints over time stratified by month and socioeconomic groups. From January 2010 through February 2020, noise complaint increases were highest in lower income communities and during warmer months (gray intervals: 95% confidence intervals). B) Differences between noise complaint values observed during the COVID-19 pandemic (March 2020 through February 2021) and the values expected based on pre-pandemic noise complaint growth trends. Pandemic-related noise complaint growth exceeded typical trends to the greatest degree in the lowest income tracts during warmer months (bars: ± the standard error of the mean).

Socioeconomic disparities in noise complaint increases were magnified during the COVID-19 pandemic (month × proportion low-income × pandemic era interaction, monthly βs=[2.0, 5.3, 10.8, 15.0, 46.5, 86.7, 58.0, 66.8, 45.0, 24.8, 21.8, 5.0], p-values < .0001 for March through November; Figure 3B). Relative to January, pandemic-related, socioeconomically disparate noise complaint increases were larger from March through November, demonstrating seasonal differences in noise complaint disparity growth (monthly p-values <.002). For example, whereas low- and high-income quartiles had yearly noise complaint increases of 29% and 11% for July between 2010 and 2019, their July increases from 2019 to 2020 were 103% and 50%, respectively.

Discussion

Summary of findings

In an analysis of over 4 million noise complaints in New York City since 2010, we have demonstrated that noise complaints have disproportionately increased over time in lower income communities, particularly in warmer months. We have further shown that economic and seasonal disparities in noise complaint increases have been magnified during the COVID-19 pandemic.

Noise complaints vs. street recordings

Studies across the world have demonstrated pandemic-related decreases in noise (Aletta, Brinchi, et al., 2020; Aletta, Oberman, et al., 2020; Asensio et al., 2020; Basu et al., 2021; Rumpler et al., 2020), and it has been proposed that this alleged global quieting could produce population-level cardiovascular benefits (Dutheil, Baker, & Navel, 2020). The current results, as well as recent results in London (Tong et al., 2021), demonstrate that acoustic street recordings at specific locations in a city may not capture the full spectrum of noise sources, resultant annoyance, and associated disparities and may ultimately obfuscate potential public health ramifications. This contrast between scales and sources of environmental data may extend to the examination of other deleterious exposures in the COVID-19 pandemic. For example, on the one hand, global air pollution emissions decreased during the COVID-19 pandemic (Venter, Aunan, Chowdhury, & Lelieveld, 2020), and studies have estimated potential beneficial consequences for pediatric asthma and premature death (Liu, Wang, & Zheng, 2021; Venter, Aunan, Chowdhury, & Lelieveld, 2021); on the other hand, it is possible that staying at home during the pandemic may have exacerbated already disparate exposure to household indoor air pollutants, such as tobacco smoke (Carreras et al., 2021; Gonzalez, Epperson, Halpern-Felsher, Halliday, & Song, 2021; Grechyna, 2020; Koopmann et al., 2021; Suarez-Lopez et al., 2021). Thus, scale of measurement, modality of measurement, and population studied appear to be important factors in determining the effects of the COVID-19 pandemic on environmental exposure.

Limitations of 311 noise complaint data and the current analysis

Importantly, the disparities demonstrated in the current study may be underestimates given previous studies showing that socioeconomically disadvantaged communities are less likely to make complaints to their local municipalities about quality-of-life issues. One study in Kansas City demonstrated that low-income communities and communities of color underreport street infrastructure issues relative to their need, instead prioritizing complaints about property code violations and safety concerns (Kontokosta & Hong, 2021); meanwhile, communities with higher income and larger proportions of white residents overreport infrastructure complaints despite lower need. Another study in New York City showed that neighborhoods that experience invasive policing (police stops, frisks, and use of force) participate less in 311 in general (Lerman & Weaver, 2014). Given the economically and racially discriminatory nature of policing (Fagan & Davies, 2000) and the attenuating effects of invasive policing on noise complaints, our calculated noise complaint disparities are likely conservative. Our analysis was also potentially limited by using low-income proportion as our primary predictor rather than other measures of economic distress such as income or poverty rate. Furthermore, census tract demographics are not static; for example, gentrification may influence the growth of noise complaints (Cheshire, Fitzgerald, & Liu, 2018; Ramírez, 2019). Finally, the current analysis did not account for spatial autocorrelation.

Implications for the amelioration of noise and noise annoyance

Given the effects of noise on chronic illness incidence (Basner et al., 2014; Stansfeld et al., 2000) and already extant economic disparities in chronic illness prevalence, the economically disparate distribution of noise and noise annoyance shown here suggest that efforts to attenuate noise and noise annoyance may have public health benefits. According to a recent report by the New York State Comptroller, current strategies of addressing noise complaints have failed (Comptroller, 2018). Because enforcing the noise ordinance in New York City is largely under the auspices of the New York Police Department (86% in our data, with the other major agency being the Department of Environmental Protection), the expansion of local police forces may appear a plausible solution to rising noise levels. However, given discriminatory policing practices and documented inverse associations between policing and physical health, mental health, and cognitive development, such a solution is likely specious (Bailey, Feldman, & Bassett, 2020; Bor, Venkataramani, Williams, & Tsai, 2018; Geller, Fagan, Tyler, & Link, 2014; Sewell, 2017; Sewell et al., 2020; Sewell & Jefferson, 2016; Sewell, Jefferson, & Lee, 2016).

Noise interventions that do not recapitulate health disparities are needed. Just as mental health professionals can supplant the police in psychiatric emergency response protocols (e.g., “Crisis Assistance Helping Out On The Streets (CAHOOTS)” in Eugene, Oregon), trained community mediators may be effective at addressing residential noise complaints (Ufkes, Giebels, Otten, & van der Zee, 2012). Concrete changes such as soundproofing or other acoustic improvements would also provide noise reduction and may be required by law in some cases (“New York State Real Property Law: Warranty of Habitability,” 2014; Siegler & Talel, 2006).

Increasing greenspace may be another modality of intervention because it serves as a physical barrier to excessive noise and buffers the psychological impact of noise (Dzhambov & Dimitrova, 2015; Kondo, Fluehr, McKeon, & Branas, 2018; Koopmann et al., 2021; Markevych et al., 2017); greenspace also has a variety of other potential community benefits including improved mental health and reduced violence (Branas et al., 2018; South, Hohl, Kondo, MacDonald, & Branas, 2018). Greening interventions designed with community input and accompanied by policies that maintain neighborhood affordability may be effective at reducing noise and noise annoyance while also eschewing the gentrification that can accompany new greenspace (Cole, Garcia Lamarca, Connolly, & Anguelovski, 2017; Kim & Wu, 2021; Wolch, Byrne, & Newell, 2014). Noise complaint increases were largest during warmer months, consistent with a previous analysis (Tong & Kang, 2021a), possibly due to outdoor activity in close proximity to residences; greenspace may additionally serve as a place where outdoor noise is less likely to penetrate into residences. Education about the deleterious effects of noise (e.g., in school curricula (Bronzaft, 2021) or through seasonal, geographically targeted public health campaigns) may be another way to reduce noise. Finally, emerging community-based organizations seeking to address noise may have additional and neighborhood-specific recommendations for interventions. In the context of alarmingly widening disparities in neighborhood noise and annoyance, community-based interventions are urgently needed to halt their disproportionate prevalence in economically disadvantaged communities.

Supplementary Material

1

Acknowledgments

This work was funded by NIEHS grants R01ES030950 and K23ES026239.

Footnotes

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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