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Black JL, Macinko J. Neighborhoods and obesity. Nutr Rev. 2008 Jan;66(1):2-20.

PubMed ID: 18254880
Study Design:
Systemic Review
M - Click here for explanation of classification scheme.
POSITIVE: See Research Design and Implementation Criteria Checklist below.
Research Purpose:

This review summarizes the literature on neighborhood determinants of obesity.

Inclusion Criteria:
  • Outcome variables including a measure of body weight, physical activity or diet
  • Independent variables including a neighborhood-level measure or assessment of a social, behavioral, or demographic predictor of obesity
  • The study was conducted in a human population in an industrialized country.
  • Only English-language articles were reviewed.
Exclusion Criteria:

all others not meeting inclusion criteria.

Description of Study Protocol:

Search procedure

The literature review was conducted from August 2005 through March 2007 by systemically searching the PubMed and PsychInfo databases.

 Both databases were searched with the following keywords in their title or abstract: "neighborhood AND obesity."

The following combinations of keywords were searched in abstracts and titles: "obesity" AND "multilevel"; "SES"; "income"; "income inequality"; "race"; "supermarket"; "grocery store"; "fast food"; "farmers market"; "food policy"; "food price"; "restaurant"; "built environment"; "physical activity"; "crime"; and "transportation". The keyword "neighborhood" was also combined with "physical activity", "diet", "race", and "socioeconomic status".


Type of intervention and outcomes investigated

  • measure of body weight
  • physical activity
  • or diet



Data Collection Summary:


Type of information abstracted from articles

Results were grouped according to the major neighborhood characteristics analyzed in the literature.


How was data combined:

  • Macro-level social, historical, and economic factors that shape overall neighborhood context
  • neighborhood or meso-level living conditions, such as infrastructure and services
  • local availability and quality of food
  • neighborhood characteristics that promote or inhibit physical activity


Description of Actual Data Sample:


# of articles included: 36 included a specific measure of body weight status or obesity

# of articles identified: 2000 potential articles were identified; 90 of which assessed at least one neighborhood determinant of obesity

Studies of neighborhood- and area-level socioeconomic resources and obesity

Reference Country, location (population sampled) Sample size Study design Neighborhood metric Height and weight data Body weight outcome(s)
Chang (2006) USA (MSAs with >10% black) 46,881 (130 MSAs) M MSAs Self-reported Overweight=BMI≥25; obese=BMI≥30
Chen & Paterson (2006) USA, St Louis, MO (adolescents) 315 I Census block group Measured BMI
Inagami et al (2006) USA, Los Angeles County, CA 2620 (65 NHs) M Census tract Self-reported BMI
Janssen et al (2006) Canada (students in grades 6-10) 6684 (169 schools) M 5 km Radius around school Self-reported Obese=BMI≥30
King et al (2006) Australia, Melbourne 4913 (50 NHs) M Census collector district Self-reported BMI
Mobley et al (2006) US States: CT, MA, NE, NC, SD (low-income women) 2692 (222 NHs) M Zip code Measured BMI
Monden et al (2006) Netherlands, Eindhoven 8802 (86 NHs) M Administrative unit Self-reported Overweight=BMI≥25
Nelson et al (2006) USA (students in grades 7-12) 20,745 I Constructed via cluster analysis Self-reported Overweight=BMI≥95th percentile
Spillsbury et al (2006) USA, Cleveland (African American children) 843 I Census tract Measured BMI percentile for age
Boardman et al (2005) USA 402,154 M "Very small areas" from NHIS Self-reported Obese=BMI≥30
Vandergrift & Yoked (2004) USA 47 E State Self-reported Obesity=% per state with BMI≥30
Robert and Reither (2004) USA 3617 M Census tract Self-reported BMI
Van Lenthe et al (2002) Netherlands, Eindhoven 8897 (86 NHs) M Census tract Self-reported Overweight=BMI≥25
Sundquist et al (1999) Sweden 9240 I Small area market Self-reported Overweight and obesity
Davey Smith et al (1998) Scotland, Renfew and Paisley 6961 men (7991 women) I Postcode sector and enumeration district Measured BMI
Ellaway et al (1997) Scotland, Glasgow 691 (4NHs) I Socially contrasting neighborhoods Measured Obese=BMI≥30

Abbreviations: E, ecologic; I, individual; M, multilevel; MSAs metropolitan statistical area; NHs neighborhoods; NHIS, 1990-1994 National Health Interview Survey

 Studies of income equality and obesity

Reference Country,location (population sampled) Sample size Study design Main measure(s) Association with BMI/weight status Metric of income inequality measure Height and weight data Body weight outcome(s)
Mobley et al (2006) USA: CT, MA, NE, NC, SD (low income women) 2692; 88 NHs M Income sipersion Ø County Self-reported BMI
Picket et al (2005) Large, high income countries 21 E Gini coeeficients, UNDPHP indicators + Country Pooled data from the International Obesity Taskforce Proportion obese (BMI≥30) per country
Robert & Reither (2004) USA 3617 M Gini coefficients + Census tract Self-reported BMI
Diez-Roux et al (2000) USA


44 states

M Robin Hood Index + for women only State Self-reported BMI
Kahn et al (1998) USA

34,158 male; 42,741 female

21 states

I Household Inequality Index + for men only State Self-reported Self-reported weight gain in waist

Abbreviations: E, ecologic; I, Individual; M, multilevel; MSAs, metropolitan statistical areas; NHs, neighborhoods

Studies of neighborhood and racial composition and obesity

Reference Country, location (population sampled) Sample size Study type Measure(s) of racial composition Association with BMI/weight status Neighborhood metric of SES measure Height and weight data Body weight outcome(s)
Chang (2006) USA (MSAs with >10% black) 46,881; 130 MSAs M Index of racial isolation +for blacks; Ø for whites MSA Self-reported BMI; overweight=BMI≥25
Mobley et al (2006) USA States: CT, MA, NE, NC, SD (low-income women) 2692; 88 NHs M Index or racial segregation Ø Zip code Measured BMI
Boardman et al (2005) USA 402,154 M Proportion black + "Very small areas" from NHIS Self-reported Obese=BMI≥30
Robert & Reither (2004) USA 3617 M Percent black Ø Census tract Self-reported BMI

Abbreviations: E, ecologic; I, Individual; M, multilevel; MSAs, metropolitan statistical areas; NHs, neighborhoods

Studies of neighborhood food availability and obesity

Reference Country, location (population sampled) Sample size Study type Main measure Method of measuring food access Association with BMI/weight status Height and weight data Body weight outcomes
Inagami et al (2006) USA, Los Angeles County, CA 2620; 65 NHs M Access to primary grocery store Distance between residence and census tract centroid


For father distances

Self-reported BMI
Morland et al (2006) USA, states: MS, NC, MD,MN 10,763; 207 NHs M Availability of food stores Number of food stores per census tract


For supermarkets;


for convenience stores

Measured Overweight=BMI≥25; obese=BMI≥30
Jeffery et al (2006) USA, state: MN 1033 I Access to restaurants Restaurant outlet density within 2 mile radius of work and home


for fats food;

-for men with more restaurants near work

Self-reported BMI
Mobley et al (2006) USA, states: CT, MA, NE, NC, SD (low-income women) 2692; 222 NHs M Availability of food stores Density of grocery stores, fast food, restaurants and mini-marts per zip code Ø Measured BMI
Sturm and Data (2005) USA, (children >4 years old followed until 3rd grade) 6918; 724 schools; 59 MSAs; 37 states M Access to food stores Distance from home and school zip codes to grocery stores, convenience stores and restaurants and food prices



for fruit and vegetable price index

Measured BMI
Maddock (2004) USA 50 states E Availability of fast food State-level availability (square miles and populationper outlet) of McDonalds and Burger King + State-level aggregates based on self-reported data Percent obese (BMI≥30) per state
Burdette and Whitaker (2003) USA, Cincinnati, OH (3-4-year old children in WIC) 7020 I Availability of fast food Distance from home to fast-food outlet Ø Measured Overweight=BMI≥95th percentile

Ø, no significant association; +, positive association; -, negative association

Abbreviations: E, ecologic; I, Individual; M, multilevel; MSAs, metropolitan statistical areas; NHs, neighborhoods

Studies of neighborhood physical activity environment and obesity

Reference Country, location (subpopulation studied) Sample size Study type Type of measure Main neighborhood variable(s) Metric of neighborhood measure Association with BMI/weight status Height and weight data Body weight outcome
Boehmer et al (2007) USA, Savannah, GA and St. Louis, MO 1032 I Perceived and objective Recreation facilities, land use, transportation, aesthetics Perceived objective 400 m buffers from residence

+For perceived lack of destinations, sidewalks and objective poor sidewalk quality, physical disorder, garbage;

Øfor recreation facilities, traffic safety

Self-reported Obese=BMI≥30
Berke et al (2007) USA, King County, WA (older adults 65-97 years) 936 I Objective Walkability score 1-3 km buffers from residence Ø for walkability Measured BMI
Poortinga (2006) England 14,836; 720 postcodes M Perceived Self-rated local environment features (e.g. access to amenities, physical features, reputation, aesthetics, social support and capital) Perceived neighborhood

+for social nuisances;

- for perceptions of the social environment

Measured Obese=BMI≥30
Mobley et al (2006) USA; CT, MA, NE,  NC, SD (low-income women) 2692; 222 NHs M Objective Land use, fitness facilities per 1000 residents, robbery arrest per 100,000 Zip code

- for mised land use, fitness facilities;

+ for crime

Measured BMI
Gordon-Larsen et al (2006) USA (adolescents) 20,745 I Objective

Access to physical activity facilities

Block group - for increased facilities Self-reported Overweight=BMI≥95th percentile
Nelson et al (2006) USA (students grade 7-12) 20,745 I Objective Access to physical activity facilities, walkability, crime used to define neighborhood clusters 3-km distance from residence + for rural working class and exurban and mixed-race urban areas Self-reported Overweight=BMI≥95th percentile
Lumeng et al (2006) USA children (7019 years) 768; 10 NHs I Perceived Parental perceptions of neighborhood safety Perceived neighborhood - for perceived safety Self-reported Overweight=BMI≥95th percentile
Glass et al (2006) USA, Baltimore, MD (age50-70 years) 1140; 65 NHs M Perceived Neighborhood psychosocial hazard scale Baltimore "city neighborhoods" + for perceived psychosocial hazards Self-reported Obese=BMI≥30
Timperio et al (2005) Australia, Melbourne (families with children ages 5-6 and 10-12 years) 291 families of 5-6 and 919 families of 10-12 year olds I Perceived (by parents and children) Neighborhood access to physical activity facilities, traffic and safety Perceived neighborhood + for parental perception of traffic, concern for road safety with children aged 10-12 years Measured (for children) Obese=BMI≥30
Ellaway et al (2005) Europe 6919; 8 countries I Perceived (by surveyors) Graffiti, litter, dog mess, and greenery Immediate residential environment - for green space; + for graffiti, garbage Self-reported Overweight/obese =BMI≥25
Rutt and Coleman (2005) USA, El Paso, TX (mainly Hispanic) 996 I Perceived Physical environment characteristics, barriers to exercise 2.5 mile radius + for land use mix Self-reported BMI
Lopez-Zetina (2005) USA, CA 33 counties E Objective Aggregate VNT per county County (with >100,000 residents) + for county VMT Self-reported County-level % obese (BMI≥30)
Vanderfrift and Yoked (2004) USA 50 states E Objective Urban sprawl State level + for amount of developed land Self-reported from secondary data State-level percent obese (BMI≥30)
Frank et al (2004) USA, Atlanta, GA 10,878 I Objective Land use mix 1-kb distance from residence - for mixed land use Self-reported Obese=BMI≥30
Saelens et al (2003) USA, San Francisco, CA 107 I Perceived Neighborhood environment walkability scale Perceived neighborhood - for walkability Self-reported Overweight=BMI≥25

Abbreviations: E, ecologic; I, Individual; M, multilevel; MSAs, metropolitan statistical areas; NHs, neighborhoods; VMT, vehicle miles traveled

Summary of Results:


Key Findings

  • From 37 studies, the influence of neighborhood factors on obesity are mixed.
  • Neighborhood-level measures of economic resources were associated with obesity in 15 studies
  • The associations between neighborhood income inequality and racial composition with obesity were mixed.
  • The availability of healthy versus unhealthy food was inconsistently related to obesity.
  • Neighborhood features that discourage physical activity were consistently asociated with increased body mass index.


Other Findings

  • This review suggests that, at minimum, individual-level approaches such as diet and exercise guidelines need to recognize potential barriers to good health imparted by the neighborhood context.


Author Conclusion:

Characterisitcs of the built environment and neighborhood opportunities for physical activity are consistently associated with reduced body weight status, while the influence of food avialability on obesity is mixed. The efficacy of targeted neighborhood interventions to reduce obesity remains unknown.

Reviewer Comments:

Research Design and Implementation Criteria Checklist: Review Articles
Relevance Questions
  1. Will the answer if true, have a direct bearing on the health of patients?
  2. Is the outcome or topic something that patients/clients/population groups would care about?
  3. Is the problem addressed in the review one that is relevant to nutrition or dietetics practice?
  4. Will the information, if true, require a change in practice?
Validity Questions
  1. Was the question for the review clearly focused and appropriate?
  2. Was the search strategy used to locate relevant studies comprehensive? Were the databases searched and the search termsused described?
  3. Were explicit methods used to select studies to include in the review? Were inclusion/exclusion criteria specified and appropriate? Were selection methods unbiased?
  4. Was there an appraisal of the quality and validity of studies included in the review? Were appraisal methods specified, appropriate, and reproducible?
  5. Were specific treatments/interventions/exposures described? Were treatments similar enough to be combined?
  6. Was the outcome of interest clearly indicated? Were other potential harms and benefits considered?
  7. Were processes for data abstraction, synthesis, and analysis described? Were they applied consistently across studies and groups? Was there appropriate use of qualitative and/or quantitative synthesis? Was variation in findings among studies analyzed? Were heterogeneity issued considered? If data from studies were aggregated for meta-analysis, was the procedure described?
  8. Are the results clearly presented in narrative and/or quantitative terms? If summary statistics are used, are levels of significance and/or confidence intervals included?
  9. Are conclusions supported by results with biases and limitations taken into consideration? Are limitations of the review identified and discussed?
  10. Was bias due to the review’s funding or sponsorship unlikely?

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