Which Cities in America Have the Highest Obesity Rates

What Defines Obesity at the City Level

Obesity is typically defined using body mass index (BMI), which relates weight to height. Public health surveillance often relies on self-reported height and weight from household surveys, which can underreport obesity. At the city level, estimates come from annual measures such as the CDC’s Behavioral Risk Factor Surveillance System (BRFSS) and, in some years, the National Health and Nutrition Examination Survey (NHANES). Because methodologies and sample sizes vary, comparisons across places and years should account for measurement uncertainty and reporting differences rather than treating any single ranking as definitive.

How We Identify the Most Obese Cities

City-level obesity estimates commonly derive from large household surveys or administrative health data. Key sources include BRFSS, which samples adults and calculates age-adjusted prevalence; NHANES, which includes clinical measurements but limited geographic coverage for small areas; and, in some analyses, school health surveys or Medicaid claims. Rankings that label a city as the "most obese" can shift depending on which dataset, year, and adjustment method is used. Readers should prioritize trends within a city over granular rank differences, and consider contextual factors such as data collection mode and response bias.

Data Sources and Limitations

• BRFSS: Large sample size, consistent over time, subject to self-report bias and varying response rates.
• NHANES: Objective measurements, high quality, limited geographic coverage and smaller sample sizes for subnational areas.
• Local surveys: May allow tailored questions but complicate comparisons with national estimates.

Contextual Patterns Across U.S. Cities

Evidence suggests obesity prevalence is higher in certain regions and among demographic groups with lower incomes and less access to care. At the city scale, variation reflects a combination of diet, physical activity environments, transportation systems, neighborhood safety, access to parks and grocery stores, and structural inequities. In many analyses, cities with larger low-income populations and neighborhoods with limited walkability or food access show higher measured obesity prevalence. These relationships are correlational and do not imply individual blame; they highlight the importance of policy and infrastructure in shaping opportunities for healthy living.

Notable Cities Frequently Cited in Analyses

Over the past decade, analyses from CDC and other organizations have repeatedly found higher obesity prevalence in certain metropolitan areas, often in the South and Midwest. Many of these cities share characteristics such as higher poverty rates, lower educational attainment on average, and environments that can limit routine physical activity. The following table summarizes illustrative examples based on prior years of BRFSS and comparable city- or state-level reports, not a single definitive ranking. Readers should use these examples as reference points rather than fixed standings.

Drivers of Higher Obesity Prevalence in Certain Cities

Neighborhood and Built Environment

Features such as street connectivity, presence of sidewalks, availability of safe parks, and proximity to destinations influence daily movement. Cities with more walkable neighborhoods and robust recreational infrastructure often show stronger engagement in routine physical activity. Conversely, sprawling layouts and perceived safety concerns can reduce active travel and recreational opportunities, contributing to more sedentary lifestyles.

Food Environment and Access

Access to affordable, nutritious food varies by neighborhood. Areas with limited supermarket access and more fast food or convenience options can pose challenges to balanced eating. Local food policies, urban agriculture initiatives, and incentives for healthy retail can shift availability over time, but historical patterns of access continue to shape dietary behaviors and related health outcomes.

Economic and Structural Factors

Poverty, employment conditions, education, and housing stability affect the time, resources, and choices available for health-promoting behaviors. Structural inequities, including discrimination and limited access to quality health care, can compound these challenges. Public investments in transportation, housing, education, and community programs can create conditions that support healthier weights across populations.

Evidence-Based Strategies for Healthier Cities

Improving population weight outcomes requires multi-sector approaches that address social determinants and everyday environments. Proven strategies include policies that increase access to affordable healthy food, such as incentives for supermarkets and support for local producers; investments in safe walking and cycling infrastructure; and workplace programs that encourage movement. Community-level programs that engage residents and respect local priorities tend to be more sustainable and equitable.

Policy and System Changes

• Complete streets and safe routes to schools to support active travel.
• Zoning that encourages mixed-use development and proximity to services.
• Incentives for grocery stores and healthy retailers in underserved areas.

Community and Clinical Approaches

• Culturally relevant nutrition and physical activity programs.
• Improved coordination between health care and community resources.
• Workplace wellness initiatives that make healthier choices easier.

Moving Toward Healthier Urban Environments

Addressing obesity at the city level is most effective when framed as building healthier environments rather than targeting individuals. Sustainable change involves coordinated efforts across housing, transportation, economic development, and public health. By focusing on equity, data, and community engagement, cities can create conditions in which active living and good nutrition become accessible, realistic choices for more residents.