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Measuring Neighborhood Order and Disorder: a Rapid Literature Review

  • Steeve Ndjila
  • Gina S. LovasiEmail author
  • Dustin Fry
  • Amélia A. Friche
Open Access
Built Environment and Health (M Nieuwenhuijsen and A de Nazelle, Section Editors)
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Part of the following topical collections:
  1. Topical Collection on Built Environment and Health

Abstract

Purpose of Review

Neighborhood disorder has received attention as a determinant of health in urban contexts, through pathways that include psychosocial stress, perceived safety, and physical activity. This review provides a summary of data collection methods, descriptive terms, and specific items employed to assess neighborhood disorder/order.

Recent Findings

The proliferation of methods and terminology employed in measuring neighborhood disorder (or neighborhood order) noted over the past two decades has made related studies increasingly difficult to compare. Following a search of peer-reviewed articles published from January 1998 to May 2018, this rapid literature review identified 18 studies that described neighborhood environments, yielding 23 broad terms related to neighborhood disorder/order, and a total of 74 distinct measurable items.

Summary

A majority of neighborhood disorder/order measurements were assessed using primary data collection, often relying on resident self-report or investigatory observations conducted in person or using stored images for virtual audits. Items were balanced across signs of order or disorder, and further classification was proposed based on whether items were physically observable and relatively stable over time.

Keywords

Neighborhood disorder Neighborhood environments Street observations Virtual audits Physical disorder 

Introduction

Neighborhood conditions are increasingly recognized as having an important impact on the health of neighborhood residents beyond what can be explained by individual-level characteristics alone [1]. Neighborhood characteristics have therefore gained attention in health-related research for several psychosocial and behavioral pathways over the past two decades [2, 3, 4, 5]. Adding to this momentum, Exposure Science in the 21stCentury: A Vision and a Strategy report released in 2012 by the National Research Council (NRC) pointed out a need for more comprehensive exposure data collection procedures that include environmental and community characteristics in addition to individual-level exposures [6].

As the body of literature on neighborhood characteristics has grown, so has the list of terms used to describe these characteristics, and several distinct classification schemes have been proposed [2, 3, 4, 5, 7, 8, 9•, 10, 11, 12]. Given this proliferation and diversification of neighborhood-assessment tools and terminology, distinctions and relationships between concepts can be complex to navigate, making related research challenging to identify and interpret. Consolidation and clear delineation of concepts are made even more important by the emergence of multinational collaborations such as the Salud Urbana en América Latina (Urban Health in Latin America, SALURBAL) project [13••] which includes spatial and temporal comparisons relevant to understanding how urban environments affect population health [14•, 15•]. Quistberg, Roux [16••] further emphasizes the necessity for ensuring comparability of measures across various secondary data from distinct urban settings (cities and sub-cities). However, secondary data are not uniformly available for all aspects of health-relevant urban environmental variation, particularly for indirectly measured concepts such as neighborhood disorder.

Neighborhood disorder/order has emerged as a particularly prominent term that is cited in a large collection of health-related research [3, 7, 9•, 10, 17]. For example, Latkin, Curry [3] report direct associations between neighborhood disorder indicators such as vandalism, littering and/or loitering, and high-risk substance use and sexual behavior patterns. Although the concept of neighborhood disorder is used extensively, it is not always defined explicitly. Available literature shows a gradual evolution of the framing of physical disorder as a potential signal of social context and determinant of health. One of the earliest views of the term neighborhood disorder defines it as a pattern of divergence away from conventionally accepted norms or standards within a community [18]. This may be manifested as the perceptible decay of the urban scenery or the proliferation of uncivil social behavior and resultant physical signs such as broken windows or an accumulation of litter [19, 20, 21]. Ross and Jang [22] built on this early view and introduced a second perspective that highlights the presence of measurable neighborhood processes or items such as vandalized or abandoned property (including both vacant lots, buildings, and vehicles) as indicators of neighborhood disorder. This work brought to prominence the idea that neighborhood disorder is not always criminal in nature but is inclusive of a range of criminalized and non-criminal factors that indicate substandard neighborhood maintenance or affinity such as graffiti, buildings in states of disrepair, and loitering. Today, a third and more prominent view of neighborhood disorder focuses more on perception of the neighborhood by residents as a stressor, incorporating a more subjective lens. Under this definition, neighborhood disorder is described as a generally perceived lack of order and social control within a community [23]. Neighborhood residents and/or investigators see visible cues and decide whether to interpret them as indicators of neighborhood disorder based on their preconceptions. This allows for awareness of how subjectivity can influence ratings, as the same neighborhood feature could be viewed as indicating disorder by one viewer but not by another. Even when residents or researchers would agree that an item indicates disorder, there may be disagreement about the degree to which disorder is perceived (slight to severe). For pathways involving resident stress-related or behavioral responses to the environment, attention to how residents (vs researchers) perceive the environment may be particularly crucial.

In this review, we aim to provide an orientation to some common terms used in describing neighborhoods, including broader terms related to the disorder/order spectrum and the specific items measured to characterize these terms. This will help contextualize current findings and guide the description and consolidation of measurement strategies which to date have been highly variable.

Study Design

A rapid review of the literature on neighborhood disorder and health was conducted to identify common terminology and to provide guidance on measurement options relevant to future data collection for neighborhood-scale investigations globally.

Identification and Inclusion of Papers

To begin the search, the terms “neighborhood disorder” and “physical disorder” were in turn entered in a search box that was restricted to article titles only on the National Center for Biotechnology Information (NCBI) web database, PubMed. Peer-reviewed English language articles published from the year 1998 through May 2018 (20 years span) were then selected through a snowball approach [24] starting with a recently published original research article by Robinette, Charles [25••] published in Social Science and Medicine in 2018. Informed by this search, cited articles with similar and related terms were also identified.

Inclusion criteria were (1) assessment of neighborhood disorder/order and related terms using measurable items (or descriptions) via primary data (in-person, virtual, and/or self-report) and/or secondary data sources and (2) complete information about assessed neighborhood characteristics (reporting all street level items used to assess each neighborhood characteristic) (Fig. 1).
Fig. 1

Identification and inclusion of papers in this rapid review

Characterization of Data Collection Methods and Included Items

Information abstracted from included articles allowed categorization of data collection methods and identification of unique terms and items (Table 1). We distinguished methods to characterize the neighborhood environment as primary (collected by the investigators for research purposes) or secondary data (available from prior research or surveillance efforts, commonly including publicly available data). Studies that used primary data were further categorized with attention to the groupings relevant to whether residents or investigators were engaged in measurement and whether any systematic observation was in-person or virtual. In-person data collection included only studies that trained people to conduct data collection via systematic in-person observations in the neighborhoods of interest. Examples include Kelly, Schootman [11], Wei, Hipwell [26], and Douglas, Briones [9•]. Another such study beyond the scope of our search (screened out prior to full inclusion criteria assessment due to our restriction to English language publications) is Costa, Mingoti [27]. Virtual audit data collection included studies that made use of stored imagery such as Google Street View images. Examples include Marco, Gracia [12], Mooney, Bader [28], and Sampson and Raudenbush [21]. Self-report included surveys or interviews with residents reflecting on the characteristics of their neighborhood, an area for which the boundaries were often not explicitly specified. An example of a study that used this data collection procedure is Oropesa [29]. Other similar studies beyond the scope of our search (due to our restriction to English language publications) include de Almeida Célio, de Lima Friche [30] and Andrade, Peixoto [31].

For each article included in this review, all reported items used in measuring neighborhood characteristics were extracted and initially categorized using terms drawn from the articles themselves. The same specific item could be grouped under multiple broader terms by different articles. Some very similar items were different only based on measuring presence vs absence, and thus could be considered as the inverse (or reverse coding) of each other. For example, Zandieh, Martinez [32] measured litter, placing emphasis on the absence of litter to signal neighborhood order, while Kelly, Schootman [11] also measured litter but focused on presence of litter to indicate neighborhood disorder. To simplify our representation of the items, descriptive terms such as good, bad, high level of, or presence/absence were omitted to distill a shorter list of measurable items. Hence, for both studies named above, the item extracted was “litter/trash/rubbish.” Articles from which the items were drawn were also noted such that each item was associated with an original source reference.

Following this initial extraction of items, the team of authors developed through consensus a stratification system based on three ways to divide the items: (1) order/disorder, whereby each item was determined as indicating either order or disorder; (2) physical/social, whereby each item was assessed for whether it would be apparent through observing the physical environment or through social dynamics; and (3) temporary/stable, whereby each item was assessed for likely short-term variation (hours, days, or weeks) or relative stability (though still subject to longer-term transitions, stable items were thought to be less sensitive to the exact timing of observation). This scheme to stratify items was devised with attention to both capturing a range of positive and negative aspects of urban areas, as well as to show how the nature of items might restrict our options for measurement. For example, physical factors such as litter and graffiti may be more suitable to systematic observation, whereas social dynamics such as trust in neighbors and community unity may not be as readily observable by investigators using virtual or even in-person audits. Although all aspects of neighborhood disorder in general have social causes and psychosocial consequences, not all are detectible from the visible features of the environment. Finally, our classification of items as relatively temporary versus stable is relevant to reliability in capturing a state of the environment such as noise or litter which can vary throughout the day or week. Further refinement to our assessment of which items are stable may be particularly well captured through carefully timed, repeated in-person audits. Where short-term fluctuations are relatively large, the timing of virtual audits that rely on available imagery may be an important limitation. Likewise, self-reported neighborhood characteristics that generally rely on observations over an unspecified period may mask important variation over time. Stable items such as deteriorated buildings may be more reliably observable across a range of data collection techniques, while still being amenable to deliberate community investment efforts such as urban redevelopment (Table 1).
Table 1

Characteristics of articles reviewed

Study

Type of data collected

Primary data collection protocol

Party assessing disorder/order

Bowling, Barber, Morris, and Ebrahim (2006)

Primary data

Self-report (interviews)

Participants

Cunradi (2009)

Primary data

Self-report (interviews)

Participants

Latkin, Curry, Hua, and Davey (2007)

Primary data

Self-report (interviews)

Participants

Latkin et al. (2017)

Primary data

Self-report (interviews)

Participants

Litt et al. (2011)

Primary data

Self-report (interviews)

Participants

Miles (2008)

Primary data

Self-report (interviews) and in-person

Participants and investigators

Oropesa (2012)

Primary data

Self-report (interviews)

Participants

Robinette, Charles, and Gruenewald (2018)

Primary data

Self-report (interviews)

Participants

Ross and Mirowsky (2001)

Both primary and secondary data

Self-report (interviews)

Participants

Zandieh, Martinez, Flacke, Jones, and Van Maarseveen (2016)

Primary data

Self-report (interviews)

Participants

Douglas et al. (2018)

Primary data

In-person

Investigators

Kelly, Schootman, Baker, Barnidge, and Lemes (2007)

Primary data

In-person

Investigators

Wei, Hipwell, Pardini, Beyers, and Loeber (2005)

Both primary and secondary data

In-person

Investigators

Marco, Gracia, Martín-Fernández, and López-Quílez (2017)

Primary data

Virtual

Investigators

Mooney et al. (2014)

Primary data:

Virtual

Investigators

Sampson and Raudenbush (1999)

Primary data

Virtual

Investigators

Cerdá et al. (2009)

Secondary data

N/A

N/A

Mason et al. (2017)

Secondary data

N/A

N/A

Primary data refers to data collected by the investigators for research purposes

Secondary data refers to data available from prior research or surveillance efforts, commonly including publicly available data

Current Findings

The initial title search yielded 73 results in total: 55 for the term “neighborhood disorder” and 18 for the term “physical disorder.” After screening titles to determine which papers assessed neighborhood disorder/order and using a snowball sampling methodology, 25 papers were selected for review. After full text review of these selected papers, 18 met our inclusion criteria.

The review yielded 23 distinct terms (including neighborhood disorder/order themselves) used to describe neighborhood environments with a total of 74 specific items measured to assess them (Table 2).
Table 2

List of street-level items categorized by terms

Term

Number of studies using this term

Street-level item measured

Physical disorder/order [8, 11, 12, 21, 25••, 26, 28, 33, 34]

9

Abandoned vehicles

Auditory annoyance (noise)

Bar-windowed buildings

Broken glass/windows

Cigarette butts

Cleanliness

Deteriorated buildings

Empty bottles (beer or liquor)

Graffiti (with or without political message or protest) and graffiti painted over

House maintenance

Litter/ trash/ rubbish

Needles/ syringes

Sex Paraphernalia

Vacant/abandoned buildings (homes and others)

Vacant/abandoned buildings (homes and others)

Vacant/abandoned or undeveloped land

Vandalism

Vandalized or run-down buildings

Vegetation (artificial and man-made)

Cleanliness

Social disorder/order [21, 25••, 29, 33]

4

Crime (assaults, robbery, muggings…)

Drug use and/or trafficking

Gangs

Respect for rules, laws, and authority

Perceived nighttime street safety

Loitering

Alcohol use

Street fights (and disputes)

Prostitution

interpersonal relationships

Willingness to help neighbors

Perceived neighborhood safety

Neighborhood disorder/order [5, 9, 17, 35]

4

Alcohol use

Auditory annoyance (noise)

Broken glass/windows

Crime (assaults, robbery, muggings…)

Dog refuse

Drug use and/or trafficking

Graffiti (with or without political message or protest) and graffiti painted over

Litter/ trash/ rubbish

Loitering

Owner-occupied housing

Poverty (household and individual)

Sex Paraphernalia

Single-parent households

Street fights (and disputes)

Vacant/abandoned buildings (homes and others)

Vandalism

Vegetation (artificial and man-made)

Neighborhood aesthetics [4, 32]

2

Attractive sites (natural and man-made)

Litter/ trash/ rubbish

Shade

Vegetation (artificial and man-made)

Well-maintained front gardens

Neighborhood safety [29, 32]

2

Crime (assaults, robbery, muggings…)

Pedestrian interaction

Pedestrian visibility

Perceived daytime street safety

Perceived nighttime street safety

Street lighting

Neighborhood air quality [32]

1

Exhaust fumes

Neighborhood amenities [32]

1

Public benches

Public toilets

Shelters

Neighborhood attachment [4]

1

Emotional attachment to neighborhood facilities

Sense of belonging to neighborhood

Neighborhood characteristics [26]

1

Minority concentration

Poverty (household and individual)

Vacant/abandoned buildings (homes and others)

Neighborhood cohesion [25••]

1

Interpersonal solidarity

Sense of belonging to neighborhood

Neighborhood disadvantage [33]

1

Adults 25+ with college degrees

Mother-only households

Owner-occupied housing

Poverty (household and individual)

Neighborhood Interaction (social cohesiveness or neighborhood cohesiveness) [29]

1

Community unity

Interpersonal professional discussions

interpersonal relationships

Interpersonal social visits

Trust in neighbors

Willingness to help neighbors

Neighborhood political engagement [2]

1

Participation in elections

Neighborhood problems [2]

1

Air quality

Auditory annoyance (noise)

Crime (assaults, robbery, muggings…)

Graffiti (with or without political message or protest) and graffiti painted over

Litter/ trash/ rubbish

Speed/volume of traffic (including nearby streets)

Neighborhood quietness [32]

1

Auditory annoyance (noise)

Neighborhood sidewalks [11]

1

Sidewalk walkability

Sidewalks

Neighborhood social involvement [4]

1

Advocacy for neighborhood issues

Participation in local activities

Participation in neighborhood meetings

Neighborhood traffic condition [32]

1

Crosswalks and pedestrian signaling

Perceived safety of crosswalks

Respect of driving rules

Speed/volume of traffic (including nearby streets)

Neighborliness [2]

1

interpersonal relationships

Perceived nighttime street safety

Trust in neighbors

Perceived neighborhood disorder/order [3]

1

Crime (assaults, robbery, muggings…)

Drug use and/or trafficking

Litter/ trash/ rubbish

Loitering

Vacant/abandoned buildings (homes and others)

Vandalism

Perceived neighborhood environment [2]

1

Attractive sites (natural and man-made)

Commercial facilities (shops)

Facilities for people aged 65+

Leisure/social facilities

Local health services

Rubbish collection

Transport

Perceived neighborhood safety [34]

1

Perceived nighttime street safety

Physical decay [12]

1

Deteriorated recreation places

Deteriorated residential units

Vacant/abandoned buildings (homes and others)

Vandalized or run-down buildings

Stratifying the 74 items (disorder/order, physical/social, or temporary/stable) yielded the following results: 43 items described order and related concepts, while the remaining 31 items described disorder and related concepts; 36 items fell under the category physical, while the remaining 38 items fell under the category social; 31 items fell under the category temporary, while the remaining 43 items fell under the category stable (Table 3). We note that there may be efforts needed to avoid conflation of neighborhood social disorder with commonly measured social determinants of health based on population characteristics.
Table 3

List of street-level items categorized by descriptive category

  

Physical

Social

Order (absence of these items indicates disorders)

Temporary

• Cleanliness

• Shade

• Shelters

• Sidewalk walkability

• Vegetation (artificial and man-made)

• Well-maintained front gardens

• Community unity

• Interpersonal professional discussions

• Interpersonal social visits

• Participation in neighborhood meetings

• Pedestrian interaction

• Pedestrian visibility

• Perceived daytime street safety

• Perceived nighttime street safety

• Respect of driving rules

• Willingness to help neighbors

Stable

• Air quality

• Attractive sites (natural and Man-made)

• Commercial facilities (shops)

• Crosswalks and pedestrian signaling

• House maintenance

• Leisure/social facilities

• Local health services

• Owner-occupied housing

• Public benches

• Public toilets

• Sidewalks

• Street lighting

• Transport

• Adults 25+ with college degrees

• Advocacy for neighborhood issues

• Emotional attachment to neighborhood facilities

• Facilities for people aged 65+

• interpersonal relationships

• Interpersonal solidarity

• Participation in elections

• Participation in local activities

• Perceived neighborhood safety

• Perceived safety of crosswalks

• Respect for rules, laws, and authority

• Rubbish collection

• Sense of belonging to neighborhood

• Trust in neighbors

Disorder (presence of these items indicates disorder)

Temporary

• Abandoned vehicles

• Broken glass/windows

• Cigarette butts

• Dog refuse

• Empty bottles (beer or liquor)

• Litter/ trash/ rubbish

• Needles/ syringes

• Sex Paraphernalia

• Alcohol use

• Auditory annoyance (noise)

• Drug use and/or trafficking

• Gangs

• Loitering

• Speed/volume of traffic (including nearby streets)

• Street fights (and disputes)

Stable

• Deteriorated buildings

• Deteriorated recreation places

• Deteriorated residential units

• Exhaust fumes

• Graffiti (with or without political message or protest) and graffiti painted over

• Vacant/abandoned buildings (homes and others)

• Vacant/abandoned or undeveloped land

• Vandalism

• Vandalized or run-down buildings

• Bar-windowed buildings

• Crime (assaults, robbery, muggings…)

• Minority concentration

• Mother-only households

• Poverty (household and individual)

• Prostitution

• Single-parent households

Note: Designation as temporary or stable is provisionally assigned but empirically testable and should be reevaluated in future work

Discussion

During the categorization of the 23 neighborhood disorder/order related terms identified (such as neighborhood aesthetics, physical decay, and neighborhood cohesion), we noted that different data collection methods were varyingly suited to certain groups of street-level items. For example, relatively stable items and those capturing aspects of the physical environment are amenable to data collection using virtual audits, whereas social disorder and related social environment characteristics are more amenable to data collection using self-report or ecometric (a combination of socio-economic and environmental) measures. Across data collection approaches, we note the potential to characterize a spectrum from items signaling order/care to those signaling disorder/deterioration.

Implications

The broad range of terminology obtained from this brief review is important to understand given the rapid growth of interest in measuring and describing neighborhood characteristics. A majority of neighborhood disorder/order measurements were assessed using primary data collection, often relying on resident self-report or investigatory observations conducted in person or using stored images for virtual audits. Items were balanced across signs of order or disorder, and further classification was proposed based on whether items were physically observable and relatively stable over time.

Research focused more on items posited to be stable rather than temporary. Empirical observation can be used to refine our classification of which items are observed to exhibit stability across months, years, and even decades.

Neighborhood disorder, often broken down into two distinct constructs (physical disorder and social disorder) [18, 36], is closely related to other terms (some of which have been identified in this review) that have emerged in recent literature, including neighborhood aesthetics, physical decay, and social cohesion [4, 10, 12, 25••]. Therefore, distinctions and relationships between these concepts can be ambiguous, making related research challenging to assemble and interpret. A more standard application of terminology is needed to reduce the ambiguity often associated with the use of these concepts in research.

Even though our snowball sampling was initiated with the terms physical and neighborhood disorder, we did not include only studies using these specific two terms. The methodology employed entailed actively searching for and reviewing papers that used synonymous or related terms to describe neighborhood environments. We are, however, aware that this strategy made it more likely than not to capture articles that employed these two specific terms, so the proportions of studies under each term in Table 2 should not be taken as representative of the broader literature.

Planned neighborhood observations may benefit from considering whether aspects such as the temporal permanence (temporary/stable) and the physical observability (physical/social) of the specific items is well matched to the measurement strategy, and considering strategies to improve the accuracy and precision of these measurements. As physical disorder/order assessment is extended to new settings, individual items may need to be assessed for differential item functioning and for alignment with what residents understand as representing physical disorder/order. For example, vegetation may be an indicator of disorder in rural settings but an indicator of order in urban settings. Also, graffiti could in some instances be part of urban renovation in informal settlements and may be considered as art potentially indicating order. Hence, certain items may need to be adapted prior to measurement depending on the setting. In addition, many items relevant to physical disorder/order incorporate subjective evaluation such as distinguishing between graffiti and a mural based on aesthetic value and inferred purpose, further rendering the systematization of protocols more challenging.

Strengths and Limitations

The current rapid review provides an orientation to the data collection methods, terms, and items commonly used in health-relevant research on neighborhood disorder/order. However, our focus on title searching followed by a snowball approach to expanding the pool of included articles was not comprehensive, and there may be additional available terminology and measurable items that warrant consideration for future work describing neighborhoods. Although the included articles suggest a wide range of terms and items have been used, this review may have omitted literature with relevance to the subject matter and thus underestimated the heterogeneity of terms and items used.

Conclusions

Understanding the influence of neighborhood disorder/order on population health is challenging due to the diversity of terms and items used. Clear definitions and consolidation of terminology in the neighborhood disorder/order literature would facilitate comparisons and synthesis across related studies. Efforts toward standardization of research and terminology on the neighborhood disorder/order concept may benefit from consolidating measurement items within our proposed strata, as well as refinement of how items are classified and empirical investigation of how items are most reliably measured. Where specific settings require the inclusion of more novel or tailored items, these could be used alongside a common set of items to ease comparisons across settings and clarify the added value of setting-specific additions.

Notes

Acknowledgments

The authors thank Jody Bayer, Rich Remegio, Vaishnavi Vaidya, and the entire Informal Communities Project team at the Urban Health Collaborative, Drexel University for their suggestions, feedback, and support throughout this piece.

Funding Information

Dana and David Dornsife provided the Drexel University Dornsife School of Public Health the funding support to make this study possible. Gina Lovasi’s contributions to this work were supported by the Salud Urbana en América Latina (SALURBAL)/Urban Health in Latin America project which is funded by the Wellcome Trust [205177/Z/16/Z]. More information about the project can be found at www.lacurbanhealth.org.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Human and Animal Rights

All reported studies/experiments with human or animal subjects performed by the authors have been previously published and complied with all applicable ethical standards including the Helsinki declaration and its amendments, institutional/national research committee standards, and international/national/institutional guidelines.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Kawachi I. Subramanian S. Neighbourhood influences on health: BMJ Publishing Group Ltd; 2007.Google Scholar
  2. 2.
    Bowling A, Barber J, Morris R, Ebrahim S. Do perceptions of neighbourhood environment influence health? Baseline findings from a British survey of aging. J Epidemiol Community Health. 2006;60(6):476–83.PubMedPubMedCentralCrossRefGoogle Scholar
  3. 3.
    Latkin CA, Curry AD, Hua W, Davey MA. Direct and indirect associations of neighborhood disorder with drug use and high-risk sexual partners. Am J Prev Med. 2007;32(6):S234–S41.PubMedPubMedCentralCrossRefGoogle Scholar
  4. 4.
    Litt JS, Soobader M-J, Turbin MS, Hale JW, Buchenau M, Marshall JA. The influence of social involvement, neighborhood aesthetics, and community garden participation on fruit and vegetable consumption. Am J Public Health. 2011;101(8):1466–73.PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Mason MJ, Light JM, Mennis J, Rusby JC, Westling E, Crewe S, et al. Neighborhood disorder, peer network health, and substance use among young urban adolescents. Drug Alcohol Depend. 2017;178:208–14.PubMedCrossRefGoogle Scholar
  6. 6.
    NRC. Exposure Science in the 21st Century: a Vision and a Strategy: National Academies Press; 2012.Google Scholar
  7. 7.
    Calvert WJ. Neighborhood disorder, individual protective factors, and the risk of adolescent delinquency. ABNF J. 2002;13(6):127.PubMedGoogle Scholar
  8. 8.
    Cerdá M, Tracy M, Messner SF, Vlahov D, Tardiff K, Galea S. Misdemeanor policing, physical disorder, and gun-related homicide: a spatial analytic test of" broken-windows" theory. Epidemiology. 2009:533–41.PubMedCrossRefGoogle Scholar
  9. 9.
    • Douglas JA, Briones MD, Bauer EZ, Trujillo M, Lopez M, Subica AM. Social and environmental determinants of physical activity in urban parks: Testing a neighborhood disorder model. Prev Med. 2018;109:119–24. This paper is important as it is one of the first recent papers to point out that physical disorder may lead to decreased physical activity in urban environments (urban parks). PubMedCrossRefGoogle Scholar
  10. 10.
    Henderson H, Child S, Moore S, Moore JB, Kaczynski AT. The influence of neighborhood aesthetics, safety, and social cohesion on perceived stress in disadvantaged communities. Am J Community Psychol. 2016;58(1-2):80–8.PubMedCrossRefGoogle Scholar
  11. 11.
    Kelly CM, Schootman M, Baker EA, Barnidge EK, Lemes A. The association of sidewalk walkability and physical disorder with area-level race and poverty. J Epidemiol Community Health. 2007;61(11):978–83.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Marco M, Gracia E, Martín-Fernández M, López-Quílez A. Validation of a Google Street View-based neighborhood disorder observational scale. J Urban Health. 2017;94(2):190–8.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    •• Diez Roux AV, Slesinski SC, Alazraqui M, Caiaffa WT, Frenz P, Jordán Fuchs R, et al. A Novel International Partnership for Actionable Evidence on Urban Health in Latin America: LAC-Urban Health and SALURBAL. Global Chall 2018;1800013. This paper calls for international collaborations and partnerships in studying and describing neighborhood environments. This is very relevant to the context of our review as our review itself is aimed at promoting such partnerships in order to achieve internationally accepted standards for neighborhood order/disorder measurements. Google Scholar
  14. 14.
    • Reid CE, Kubzansky LD, Li J, Shmool JL, Clougherty JE. It's not easy assessing greenness: A comparison of NDVI datasets and neighborhood types and their associations with self-rated health in New York City. Health Place. 2018;54:92–101. This paper is important as it uses a very large data set with varying neighborhood types to assess the relationship between health and neighborhood order/disorder. CrossRefGoogle Scholar
  15. 15.
    • Poulsen MN, Knapp EA, Hirsch AG, Bailey-Davis L, Pollak J, Schwartz BS. Comparing objective measures of the built environment in their associations with youth physical activity and sedentary behavior across heterogeneous geographies. Health Place. 2018;49:30–8. This paper is important because it is one of the only recent papers that specifically emphasizes on measurable aspects of neighborhood environments in assessing neighborhood order/disorder. The authors propose simple objective measures to measure neighborhood disorder/order. CrossRefGoogle Scholar
  16. 16.
    •• Quistberg DA, Roux AVD, Bilal U, Moore K, Ortigoza A, Rodriguez DA, et al. Building a Data Platform for Cross-Country Urban Health Studies: the SALURBAL Study. J Urban Health. 2018:1–27. This paper is very important because it proposes a data platform for understanding neighborhood disorders across different countries and settings, hence encouraging collaboration among researchers in coming up with practical ways of studying and understanding various neighborhood environments. Google Scholar
  17. 17.
    Cunradi CB. Intimate partner violence among Hispanic men and women: The role of drinking, neighborhood disorder, and acculturation-related factors. Violence Vict. 2009;24(1):83.PubMedCrossRefGoogle Scholar
  18. 18.
    LaGrange RL, Ferraro KF, Supancic M. Perceived risk and fear of crime: Role of social and physical incivilities. J Res Crime Delinq. 1992;29(3):311–34.CrossRefGoogle Scholar
  19. 19.
    Erving G. Behavior in public places: notes on the social organization of gatherings. N Y. 1963.Google Scholar
  20. 20.
    Hunter A. Private, parochial and public social orders: The problem of crime and incivility. The challenge of social control: Citizenship and institution building in modern society. 1985.Google Scholar
  21. 21.
    Sampson RJ, Raudenbush SW. Systematic social observation of public spaces: A new look at disorder in urban neighborhoods. Am J Sociol. 1999;105(3):603–51.CrossRefGoogle Scholar
  22. 22.
    Ross CE, Jang SJ. Neighborhood disorder, fear, and mistrust: The buffering role of social ties with neighbors. Am J Community Psychol. 2000;28(4):401–20.PubMedCrossRefGoogle Scholar
  23. 23.
    Skogan WG. Disorder and decline: Crime and the spiral of decay in American cities. 1990.Google Scholar
  24. 24.
    Goodman LA. Snowball sampling. Ann Math Stat. 1961:148–70.CrossRefGoogle Scholar
  25. 25.
    •• Robinette JW, Charles ST, Gruenewald TL. Neighborhood cohesion, neighborhood disorder, and cardiometabolic risk. Soc Sci Med. 2018;198:70–6. This paper is very important as they report measures for some social aspects indicative of the state of order/disorder of neighborhood environments. They introduce concepts such as neighborhood cohesion and neighborhood aesthetics; aspects which are very crucial to our current understanding of perceived neighborhood disorders by both neighborhood residents and external observers. CrossRefGoogle Scholar
  26. 26.
    Wei E, Hipwell A, Pardini D, Beyers JM, Loeber R. Block observations of neighbourhood physical disorder are associated with neighbourhood crime, firearm injuries and deaths, and teen births. J Epidemiol Community Health. 2005;59(10):904–8.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Costa DAS, Mingoti SA, ACdS A, Xavier CC, Proietti FA, Caiaffa WT. Indicadores dos atributos físicos e sociais da vizinhança obtidos pelo método de Observação Social Sistemática. Cad Saude Publica. 2017;33:e00026316.PubMedGoogle Scholar
  28. 28.
    Mooney SJ, Bader MD, Lovasi GS, Neckerman KM, Teitler JO, Rundle AG. Validity of an ecometric neighborhood physical disorder measure constructed by virtual street audit. Am J Epidemiol. 2014;180(6):626–35.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Oropesa RS. Neighbourhood disorder and social cohesiveness among immigrants in a new destination: Dominicans in Reading, PA. Urban Stud. 2012;49(1):115–32.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    de Almeida CF, de Lima Friche AA, Jennings MZ, de Souza Andrade AC, Xavier CC, Proietti F, et al. Contextual characteristics associated with the perceived neighbourhood scale in a cross-sectional study in a large urban centre in Brazil. BMJ Open. 2018;8(8):e021445.CrossRefGoogle Scholar
  31. 31.
    Andrade ACS, Peixoto SV, AAdL F, Goston JL, César CC, Xavier CC, et al. Social context of neighborhood and socioeconomic status on leisure-time physical activity in a Brazilian urban center: The BH Health Study. Cad Saude Publica. 2015;31:136–47.PubMedCrossRefGoogle Scholar
  32. 32.
    Zandieh R, Martinez J, Flacke J, Jones P, Van Maarseveen M. Older adults’ outdoor walking: Inequalities in neighbourhood safety, pedestrian infrastructure and aesthetics. Int J Environ Res Public Health. 2016;13(12):1179.PubMedCentralCrossRefGoogle Scholar
  33. 33.
    Ross CE, Mirowsky J. Neighborhood disadvantage, disorder, and health. J Health Soc Behav. 2001:258–76.PubMedCrossRefGoogle Scholar
  34. 34.
    Miles R. Neighborhood disorder, perceived safety, and readiness to encourage use of local playgrounds. Am J Prev Med. 2008;34(4):275–81.PubMedCrossRefGoogle Scholar
  35. 35.
    Latkin CA, Tseng T-Y, Davey-Rothwell M, Kennedy RD, Moran MB, Czaplicki L, et al. The Relationship between Neighborhood Disorder, Social Networks, and Indoor Cigarette Smoking among Impoverished Inner-City Residents. J Urban Health. 2017;94(4):534–41.PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Baran PK, Smith WR, Moore RC, Floyd MF, Bocarro JN, Cosco NG, et al. Park use among youth and adults: examination of individual, social, and urban form factors. Environ Behav. 2014;46(6):768–800.CrossRefGoogle Scholar

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© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Steeve Ndjila
    • 1
  • Gina S. Lovasi
    • 1
    Email author
  • Dustin Fry
    • 1
  • Amélia A. Friche
    • 2
  1. 1.Urban Health Collaborative, Dornsife School of Public HealthDrexel UniversityPhiladelphiaUSA
  2. 2.Belo Horizonte Observatory for Urban Health, School of MedicineFederal University of Minas GeraisBelo HorizonteBrazil

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