Epidemiology

Obesity Epidemiology in California (Prevalence Map)

Explore and compare county-level estimates of obesity prevalence across California

Crude prevalence reflects the estimated prevalence in the local population with its actual age structure. Age-adjusted prevalence standardizes for differences in age distribution, making geographic comparisons more appropriate. Both values are CDC PLACES model-based estimates.
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How to read this map: Each polygon represents a U.S. county. Hover over a county for a quick prevalence estimate, or click on it for detailed data. Use the control panel above to filter by state, health measure, and estimate type.

Data source:

CDC PLACES

Geographic level:

U.S. counties

Measure:

Obesity among adults

Estimates:

Crude and age-adjusted prevalence

Obesity Prevalence Data

In the current dataset, crude obesity prevalence ranges from 17.2% in San Francisco County to 37.7% in Fresno County, with Riverside, Madera, Stanislaus, and Kern counties also showing comparatively high estimates. The table provides a structured view of county-level obesity prevalence across California, allowing users to search, sort, filter, and compare counties. Each record includes crude and age-adjusted prevalence estimates together with their corresponding 95% confidence intervals.

Available data include:

  • County and state
  • County FIPS code
  • Crude obesity prevalence
  • Crude 95% confidence interval
  • Age-adjusted obesity prevalence
  • Age-adjusted 95% confidence interval
State Name County FIPS Crude Prevalence (%) Crude 95% CI Adj Prevalence (%) Adj 95% CI
California Alameda 06001 22.8 (18.8, 26.6) 22.5 (18.5, 26.3)
California Alpine 06003 28.4 (21.4, 36.4) 28.7 (21.6, 37.0)
California Amador 06005 29.6 (22.6, 37.5) 29.5 (22.5, 37.2)
California Butte 06007 29.3 (23.2, 35.9) 30.6 (24.3, 37.4)
California Calaveras 06009 29.8 (23.3, 37.1) 29.8 (23.2, 37.1)
California Colusa 06011 35 (26.7, 43.7) 35.3 (26.9, 43.9)
California Contra Costa 06013 28 (23.8, 32.5) 27.8 (23.5, 32.2)
California Del Norte 06015 31 (23.2, 39.3) 30.9 (23.2, 39.1)
California El Dorado 06017 27.7 (21.5, 34.6) 27.4 (21.4, 34.3)
California Fresno 06019 37.7 (32.2, 43.4) 37.9 (32.4, 43.6)
California Glenn 06021 32.1 (24.5, 41.3) 32.4 (24.8, 41.6)
California Humboldt 06023 31.3 (24.9, 38.2) 32.1 (25.6, 39.0)
California Imperial 06025 34.7 (28.0, 41.8) 35.2 (28.4, 42.3)
California Inyo 06027 28.2 (21.2, 36.0) 28.5 (21.5, 36.2)
California Kern 06029 36 (30.6, 41.6) 36.2 (30.8, 41.8)
California Kings 06031 34.7 (27.2, 42.6) 34.9 (27.5, 42.9)
California Lake 06033 32.7 (25.0, 40.9) 32.8 (25.2, 40.9)
California Lassen 06035 34.2 (26.7, 42.5) 34.3 (26.8, 42.6)
California Los Angeles 06037 26.5 (23.8, 29.5) 26.4 (23.7, 29.4)
California Madera 06039 36.5 (29.3, 44.1) 36.7 (29.5, 44.3)
California Marin 06041 21.3 (16.2, 27.3) 21.3 (16.3, 27.2)
California Mariposa 06043 30.5 (23.2, 38.4) 30.9 (23.7, 38.8)
California Mendocino 06045 29.3 (22.7, 36.6) 29.5 (23.0, 36.9)
California Merced 06047 33.8 (26.6, 40.9) 34.3 (27.2, 41.4)
California Modoc 06049 31.9 (24.3, 40.5) 32.3 (24.6, 41.0)
California Mono 06051 31.2 (23.3, 39.5) 30.9 (23.2, 39.1)
California Monterey 06053 31.1 (25.3, 37.6) 31.4 (25.7, 38.0)
California Napa 06055 27.9 (21.6, 35.3) 28.2 (21.7, 35.6)
California Nevada 06057 27.5 (21.1, 34.9) 27.6 (21.1, 34.7)
California Orange 06059 23.9 (20.4, 27.5) 23.9 (20.4, 27.4)
California Placer 06061 27.3 (21.7, 33.6) 27.2 (21.8, 33.5)
California Plumas 06063 29.9 (22.6, 38.4) 30.1 (22.7, 38.3)
California Riverside 06065 36.8 (32.8, 41.0) 37 (33.0, 41.2)
California Sacramento 06067 29.6 (25.2, 34.5) 29.5 (25.1, 34.3)
California San Benito 06069 31.5 (24.4, 39.6) 31.3 (24.3, 39.3)
California San Bernardino 06071 33.3 (29.0, 37.8) 33.3 (29.0, 37.8)
California San Diego 06073 25.3 (22.2, 28.5) 25.4 (22.4, 28.7)
California San Francisco 06075 17.2 (13.7, 21.3) 17.1 (13.7, 21.2)
California San Joaquin 06077 30.7 (25.7, 36.2) 30.6 (25.6, 36.2)
California San Luis Obispo 06079 26.1 (20.9, 31.9) 27.6 (22.4, 33.5)
California San Mateo 06081 22.3 (17.9, 27.1) 22 (17.7, 26.8)
California Santa Barbara 06083 26.1 (20.6, 31.7) 27.6 (21.8, 33.3)
California Santa Clara 06085 21.9 (18.5, 25.7) 21.9 (18.5, 25.7)
California Santa Cruz 06087 25.8 (20.4, 31.8) 26.8 (21.2, 33.0)
California Shasta 06089 29.3 (23.0, 35.9) 29.3 (23.1, 36.1)
California Sierra 06091 32.5 (24.5, 40.7) 32.4 (24.5, 40.5)
California Siskiyou 06093 31.8 (24.5, 39.8) 32 (24.7, 39.8)
California Solano 06095 31.3 (25.2, 37.6) 31.2 (25.2, 37.4)
California Sonoma 06097 26.1 (20.8, 31.9) 26.1 (20.8, 31.9)
California Stanislaus 06099 36.4 (30.2, 42.9) 36.6 (30.3, 43.1)
California Sutter 06101 29.5 (22.5, 37.5) 29.7 (22.7, 37.8)
California Tehama 06103 31.6 (24.3, 40.3) 31.8 (24.4, 40.4)
California Trinity 06105 33.3 (25.5, 41.9) 33.2 (25.3, 41.5)
California Tulare 06107 35 (28.2, 42.1) 35.3 (28.5, 42.4)
California Tuolumne 06109 29 (22.0, 36.5) 29.2 (22.5, 36.8)
California Ventura 06111 25.7 (21.1, 30.8) 25.7 (21.1, 30.8)
California Yolo 06113 25.7 (20.1, 32.0) 27.9 (22.0, 34.6)
California Yuba 06115 30.8 (23.9, 38.9) 30.9 (23.9, 39.0)

Map_OBESITY_California

References & Data Sources

  • Centers for Disease Control and Prevention (CDC). PLACES: Local Data for Better Health.
  • Centers for Disease Control and Prevention (CDC). PLACES Measure Definitions: Health Outcomes — Obesity Among Adults.
  • Centers for Disease Control and Prevention (CDC). PLACES Methodology.
  • Centers for Disease Control and Prevention (CDC). PLACES Current Release Notes.

This article was reviewed for accuracy by Dr. Bahman Akbari. The content is based on current scientific evidence and is intended for educational purposes only. It does not constitute medical advice and should not be used as a substitute for consultation with a qualified health professional.

Mahdi Morshedi Yekta

I'm a medical biotechnologist, researcher, scientific tool developer, and scientific visual designer with interests in bioinformatics, computational biology, data visualization, and scientific communication. I founded Science Codons in 2022 to make practical scientific resources more accessible to researchers and students. Alongside research and tool development, I also create scientific visualizations and graphical abstracts, turning complex biological concepts, workflows, and research findings into clear and engaging graphics.

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