Students Eating Breakfast in the Past Day, by Race/Ethnicity

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California	Percent
Race/Ethnicity	Yes	No
African American/Black	59.2%	40.8%
American Indian/Alaska Native	60.6%	39.4%
Asian	71.6%	28.4%
Hispanic/Latino	57.4%	42.6%
Native Hawaiian/Pacific Islander	61.8%	38.2%
White	66.9%	33.1%
Multiracial	61.7%	38.3%
Another Group	67.7%	32.3%

Alameda County	Percent
Race/Ethnicity	Yes	No
African American/Black	56.1%	43.9%
American Indian/Alaska Native	75.8%	24.2%
Asian	75.8%	24.2%
Hispanic/Latino	58.3%	41.7%
Native Hawaiian/Pacific Islander	54.5%	45.5%
White	70.4%	29.6%
Multiracial	64.9%	35.1%
Another Group	66.5%	33.5%

Alpine County	Percent
Race/Ethnicity	Yes	No
African American/Black	N/A	N/A
American Indian/Alaska Native	S	S
Asian	N/A	N/A
Hispanic/Latino	S	S
Native Hawaiian/Pacific Islander	N/A	N/A
White	S	S
Multiracial	S	S
Another Group	S	S

Amador County	Percent
Race/Ethnicity	Yes	No
African American/Black	87.3%	12.7%
American Indian/Alaska Native	54.6%	45.4%
Asian	81.8%	18.2%
Hispanic/Latino	64.9%	35.1%
Native Hawaiian/Pacific Islander	S	S
White	66.1%	33.9%
Multiracial	65.3%	34.7%
Another Group	89.2%	10.8%

Butte County	Percent
Race/Ethnicity	Yes	No
African American/Black	29.5%	70.5%
American Indian/Alaska Native	58.4%	41.6%
Asian	58.9%	41.1%
Hispanic/Latino	50.0%	50.0%
Native Hawaiian/Pacific Islander	41.9%	58.1%
White	66.6%	33.4%
Multiracial	59.5%	40.5%
Another Group	70.6%	29.4%

Calaveras County	Percent
Race/Ethnicity	Yes	No
African American/Black	48.4%	51.6%
American Indian/Alaska Native	64.0%	36.0%
Asian	61.7%	38.3%
Hispanic/Latino	59.5%	40.5%
Native Hawaiian/Pacific Islander	40.3%	59.7%
White	64.9%	35.1%
Multiracial	68.5%	31.5%
Another Group	67.4%	32.6%

Colusa County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	S	S
Asian	S	S
Hispanic/Latino	64.9%	35.1%
Native Hawaiian/Pacific Islander	N/A	N/A
White	78.8%	21.2%
Multiracial	52.6%	47.4%
Another Group	S	S

Contra Costa County	Percent
Race/Ethnicity	Yes	No
African American/Black	56.3%	43.7%
American Indian/Alaska Native	72.8%	27.2%
Asian	75.3%	24.7%
Hispanic/Latino	60.1%	39.9%
Native Hawaiian/Pacific Islander	61.8%	38.2%
White	70.9%	29.1%
Multiracial	64.1%	35.9%
Another Group	68.1%	31.9%

Del Norte County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	57.0%	43.0%
Asian	47.1%	52.9%
Hispanic/Latino	48.1%	51.9%
Native Hawaiian/Pacific Islander	S	S
White	54.1%	45.9%
Multiracial	59.1%	40.9%
Another Group	S	S

El Dorado County	Percent
Race/Ethnicity	Yes	No
African American/Black	53.9%	46.1%
American Indian/Alaska Native	59.4%	40.6%
Asian	72.4%	27.6%
Hispanic/Latino	61.1%	38.9%
Native Hawaiian/Pacific Islander	69.6%	30.4%
White	68.6%	31.4%
Multiracial	66.3%	33.7%
Another Group	67.5%	32.5%

Fresno County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	S	S
Asian	S	S
Hispanic/Latino	S	S
Native Hawaiian/Pacific Islander	S	S
White	S	S
Multiracial	S	S
Another Group	S	S

Glenn County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	56.5%	43.5%
Asian	64.3%	35.7%
Hispanic/Latino	64.2%	35.8%
Native Hawaiian/Pacific Islander	S	S
White	62.8%	37.2%
Multiracial	53.2%	46.8%
Another Group	53.7%	46.3%

Humboldt County	Percent
Race/Ethnicity	Yes	No
African American/Black	61.1%	38.9%
American Indian/Alaska Native	57.7%	42.3%
Asian	60.6%	39.4%
Hispanic/Latino	54.7%	45.3%
Native Hawaiian/Pacific Islander	58.1%	41.9%
White	64.8%	35.2%
Multiracial	60.5%	39.5%
Another Group	68.7%	31.3%

Imperial County	Percent
Race/Ethnicity	Yes	No
African American/Black	72.2%	27.8%
American Indian/Alaska Native	46.4%	53.6%
Asian	71.0%	29.0%
Hispanic/Latino	63.8%	36.2%
Native Hawaiian/Pacific Islander	37.5%	62.5%
White	62.3%	37.7%
Multiracial	62.9%	37.1%
Another Group	82.3%	17.7%

Inyo County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	51.7%	48.3%
Asian	S	S
Hispanic/Latino	58.0%	42.0%
Native Hawaiian/Pacific Islander	S	S
White	64.4%	35.6%
Multiracial	52.2%	47.8%
Another Group	S	S

Kern County	Percent
Race/Ethnicity	Yes	No
African American/Black	59.2%	40.8%
American Indian/Alaska Native	57.6%	42.4%
Asian	71.6%	28.4%
Hispanic/Latino	56.4%	43.6%
Native Hawaiian/Pacific Islander	62.4%	37.6%
White	64.2%	35.8%
Multiracial	55.0%	45.0%
Another Group	64.1%	35.9%

Kings County	Percent
Race/Ethnicity	Yes	No
African American/Black	55.3%	44.7%
American Indian/Alaska Native	58.4%	41.6%
Asian	18.6%	81.4%
Hispanic/Latino	52.7%	47.3%
Native Hawaiian/Pacific Islander	S	S
White	60.7%	39.3%
Multiracial	58.9%	41.1%
Another Group	21.8%	78.2%

Lake County	Percent
Race/Ethnicity	Yes	No
African American/Black	52.9%	47.1%
American Indian/Alaska Native	45.0%	55.0%
Asian	83.6%	16.4%
Hispanic/Latino	61.3%	38.7%
Native Hawaiian/Pacific Islander	70.7%	29.3%
White	64.0%	36.0%
Multiracial	59.5%	40.5%
Another Group	68.0%	32.0%

Lassen County	Percent
Race/Ethnicity	Yes	No
African American/Black	18.6%	81.4%
American Indian/Alaska Native	43.5%	56.5%
Asian	60.8%	39.2%
Hispanic/Latino	47.2%	52.8%
Native Hawaiian/Pacific Islander	20.1%	79.9%
White	57.5%	42.5%
Multiracial	50.9%	49.1%
Another Group	72.5%	27.5%

Los Angeles County	Percent
Race/Ethnicity	Yes	No
African American/Black	58.0%	42.0%
American Indian/Alaska Native	63.1%	36.9%
Asian	72.5%	27.5%
Hispanic/Latino	57.2%	42.8%
Native Hawaiian/Pacific Islander	63.9%	36.1%
White	69.1%	30.9%
Multiracial	62.3%	37.7%
Another Group	62.2%	37.8%

Madera County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	S	S
Asian	S	S
Hispanic/Latino	S	S
Native Hawaiian/Pacific Islander	S	S
White	S	S
Multiracial	S	S
Another Group	S	S

Marin County	Percent
Race/Ethnicity	Yes	No
African American/Black	53.1%	46.9%
American Indian/Alaska Native	55.5%	44.5%
Asian	71.9%	28.1%
Hispanic/Latino	68.5%	31.5%
Native Hawaiian/Pacific Islander	75.5%	24.5%
White	77.5%	22.5%
Multiracial	74.0%	26.0%
Another Group	80.9%	19.1%

Mariposa County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	59.8%	40.2%
Asian	N/A	N/A
Hispanic/Latino	50.5%	49.5%
Native Hawaiian/Pacific Islander	N/A	N/A
White	66.2%	33.8%
Multiracial	64.1%	35.9%
Another Group	S	S

Mendocino County	Percent
Race/Ethnicity	Yes	No
African American/Black	74.2%	25.8%
American Indian/Alaska Native	48.5%	51.5%
Asian	52.6%	47.4%
Hispanic/Latino	50.0%	50.0%
Native Hawaiian/Pacific Islander	69.6%	30.4%
White	54.8%	45.2%
Multiracial	50.9%	49.1%
Another Group	46.2%	53.8%

Merced County	Percent
Race/Ethnicity	Yes	No
African American/Black	69.4%	30.6%
American Indian/Alaska Native	56.7%	43.3%
Asian	66.1%	33.9%
Hispanic/Latino	59.6%	40.4%
Native Hawaiian/Pacific Islander	53.1%	46.9%
White	67.3%	32.7%
Multiracial	61.3%	38.7%
Another Group	65.7%	34.3%

Modoc County	Percent
Race/Ethnicity	Yes	No
African American/Black	N/A	N/A
American Indian/Alaska Native	74.1%	25.9%
Asian	S	S
Hispanic/Latino	59.3%	40.7%
Native Hawaiian/Pacific Islander	N/A	N/A
White	62.6%	37.4%
Multiracial	46.3%	53.7%
Another Group	S	S

Mono County	Percent
Race/Ethnicity	Yes	No
African American/Black	N/A	N/A
American Indian/Alaska Native	S	S
Asian	S	S
Hispanic/Latino	53.7%	46.3%
Native Hawaiian/Pacific Islander	S	S
White	73.0%	27.0%
Multiracial	73.1%	26.9%
Another Group	S	S

Monterey County	Percent
Race/Ethnicity	Yes	No
African American/Black	49.4%	50.6%
American Indian/Alaska Native	37.3%	62.7%
Asian	84.3%	15.7%
Hispanic/Latino	63.4%	36.6%
Native Hawaiian/Pacific Islander	70.8%	29.2%
White	67.0%	33.0%
Multiracial	64.3%	35.7%
Another Group	44.7%	55.3%

Napa County	Percent
Race/Ethnicity	Yes	No
African American/Black	64.5%	35.5%
American Indian/Alaska Native	60.7%	39.3%
Asian	68.4%	31.6%
Hispanic/Latino	58.9%	41.1%
Native Hawaiian/Pacific Islander	70.4%	29.6%
White	67.0%	33.0%
Multiracial	61.4%	38.6%
Another Group	63.2%	36.8%

Nevada County	Percent
Race/Ethnicity	Yes	No
African American/Black	35.9%	64.1%
American Indian/Alaska Native	53.5%	46.5%
Asian	53.3%	46.7%
Hispanic/Latino	58.8%	41.2%
Native Hawaiian/Pacific Islander	47.7%	52.3%
White	63.9%	36.1%
Multiracial	58.7%	41.3%
Another Group	80.5%	19.5%

Orange County	Percent
Race/Ethnicity	Yes	No
African American/Black	58.9%	41.1%
American Indian/Alaska Native	65.8%	34.2%
Asian	70.1%	29.9%
Hispanic/Latino	58.2%	41.8%
Native Hawaiian/Pacific Islander	66.1%	33.9%
White	69.1%	30.9%
Multiracial	64.0%	36.0%
Another Group	72.4%	27.6%

Placer County	Percent
Race/Ethnicity	Yes	No
African American/Black	52.5%	47.5%
American Indian/Alaska Native	69.8%	30.2%
Asian	75.9%	24.1%
Hispanic/Latino	60.7%	39.3%
Native Hawaiian/Pacific Islander	57.0%	43.0%
White	70.5%	29.5%
Multiracial	64.9%	35.1%
Another Group	73.4%	26.6%

Plumas County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	78.2%	21.8%
Asian	S	S
Hispanic/Latino	48.4%	51.6%
Native Hawaiian/Pacific Islander	S	S
White	58.1%	41.9%
Multiracial	40.0%	60.0%
Another Group	63.3%	36.7%

Riverside County	Percent
Race/Ethnicity	Yes	No
African American/Black	60.7%	39.3%
American Indian/Alaska Native	59.7%	40.3%
Asian	69.8%	30.2%
Hispanic/Latino	59.1%	40.9%
Native Hawaiian/Pacific Islander	60.8%	39.2%
White	65.1%	34.9%
Multiracial	60.1%	39.9%
Another Group	62.6%	37.4%

Sacramento County	Percent
Race/Ethnicity	Yes	No
African American/Black	57.9%	42.1%
American Indian/Alaska Native	62.7%	37.3%
Asian	67.1%	32.9%
Hispanic/Latino	58.8%	41.2%
Native Hawaiian/Pacific Islander	61.4%	38.6%
White	67.6%	32.4%
Multiracial	59.3%	40.7%
Another Group	66.3%	33.7%

San Benito County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	93.2%	6.8%
Asian	59.9%	40.1%
Hispanic/Latino	61.3%	38.7%
Native Hawaiian/Pacific Islander	40.8%	59.2%
White	63.1%	36.9%
Multiracial	62.7%	37.3%
Another Group	66.7%	33.3%

San Bernardino County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	S	S
Asian	S	S
Hispanic/Latino	S	S
Native Hawaiian/Pacific Islander	S	S
White	S	S
Multiracial	S	S
Another Group	S	S

San Diego County	Percent
Race/Ethnicity	Yes	No
African American/Black	58.1%	41.9%
American Indian/Alaska Native	65.6%	34.4%
Asian	72.0%	28.0%
Hispanic/Latino	60.4%	39.6%
Native Hawaiian/Pacific Islander	65.3%	34.7%
White	70.4%	29.6%
Multiracial	63.5%	36.5%
Another Group	66.4%	33.6%

San Francisco County	Percent
Race/Ethnicity	Yes	No
African American/Black	61.9%	38.1%
American Indian/Alaska Native	S	S
Asian	75.9%	24.1%
Hispanic/Latino	55.0%	45.0%
Native Hawaiian/Pacific Islander	47.8%	52.2%
White	82.8%	17.2%
Multiracial	66.0%	34.0%
Another Group	55.0%	45.0%

San Joaquin County	Percent
Race/Ethnicity	Yes	No
African American/Black	53.1%	46.9%
American Indian/Alaska Native	48.9%	51.1%
Asian	55.4%	44.6%
Hispanic/Latino	51.4%	48.6%
Native Hawaiian/Pacific Islander	46.2%	53.8%
White	62.0%	38.0%
Multiracial	50.9%	49.1%
Another Group	62.0%	38.0%

San Luis Obispo County	Percent
Race/Ethnicity	Yes	No
African American/Black	59.3%	40.7%
American Indian/Alaska Native	72.0%	28.0%
Asian	81.1%	18.9%
Hispanic/Latino	55.1%	44.9%
Native Hawaiian/Pacific Islander	44.2%	55.8%
White	66.4%	33.6%
Multiracial	60.4%	39.6%
Another Group	78.9%	21.1%

San Mateo County	Percent
Race/Ethnicity	Yes	No
African American/Black	62.3%	37.7%
American Indian/Alaska Native	75.3%	24.7%
Asian	75.1%	24.9%
Hispanic/Latino	64.6%	35.4%
Native Hawaiian/Pacific Islander	61.2%	38.8%
White	75.7%	24.3%
Multiracial	69.8%	30.2%
Another Group	74.4%	25.6%

Santa Barbara County	Percent
Race/Ethnicity	Yes	No
African American/Black	61.0%	39.0%
American Indian/Alaska Native	62.7%	37.3%
Asian	73.8%	26.2%
Hispanic/Latino	62.6%	37.4%
Native Hawaiian/Pacific Islander	65.8%	34.2%
White	72.6%	27.4%
Multiracial	66.2%	33.8%
Another Group	69.4%	30.6%

Santa Clara County	Percent
Race/Ethnicity	Yes	No
African American/Black	61.6%	38.4%
American Indian/Alaska Native	0.6%	99.4%
Asian	83.9%	16.1%
Hispanic/Latino	58.5%	41.5%
Native Hawaiian/Pacific Islander	89.7%	10.3%
White	47.8%	52.2%
Multiracial	4.7%	95.3%
Another Group	6.2%	93.8%

Santa Cruz County	Percent
Race/Ethnicity	Yes	No
African American/Black	57.3%	42.7%
American Indian/Alaska Native	60.3%	39.7%
Asian	71.9%	28.1%
Hispanic/Latino	56.7%	43.3%
Native Hawaiian/Pacific Islander	75.5%	24.5%
White	71.8%	28.2%
Multiracial	63.7%	36.3%
Another Group	65.3%	34.7%

Shasta County	Percent
Race/Ethnicity	Yes	No
African American/Black	43.4%	56.6%
American Indian/Alaska Native	44.4%	55.6%
Asian	51.1%	48.9%
Hispanic/Latino	49.3%	50.7%
Native Hawaiian/Pacific Islander	59.2%	40.8%
White	59.4%	40.6%
Multiracial	55.1%	44.9%
Another Group	78.0%	22.0%

Sierra County	Percent
Race/Ethnicity	Yes	No
African American/Black	N/A	N/A
American Indian/Alaska Native	N/A	N/A
Asian	N/A	N/A
Hispanic/Latino	N/A	N/A
Native Hawaiian/Pacific Islander	N/A	N/A
White	N/A	N/A
Multiracial	N/A	N/A
Another Group	N/A	N/A

Siskiyou County	Percent
Race/Ethnicity	Yes	No
African American/Black	64.7%	35.3%
American Indian/Alaska Native	56.4%	43.6%
Asian	77.7%	22.3%
Hispanic/Latino	60.3%	39.7%
Native Hawaiian/Pacific Islander	S	S
White	66.0%	34.0%
Multiracial	56.5%	43.5%
Another Group	S	S

Solano County	Percent
Race/Ethnicity	Yes	No
African American/Black	54.4%	45.6%
American Indian/Alaska Native	58.2%	41.8%
Asian	66.3%	33.7%
Hispanic/Latino	55.5%	44.5%
Native Hawaiian/Pacific Islander	62.1%	37.9%
White	64.4%	35.6%
Multiracial	56.0%	44.0%
Another Group	58.1%	41.9%

Sonoma County	Percent
Race/Ethnicity	Yes	No
African American/Black	62.7%	37.3%
American Indian/Alaska Native	67.9%	32.1%
Asian	71.4%	28.6%
Hispanic/Latino	59.6%	40.4%
Native Hawaiian/Pacific Islander	51.9%	48.1%
White	67.3%	32.7%
Multiracial	60.8%	39.2%
Another Group	68.0%	32.0%

Stanislaus County	Percent
Race/Ethnicity	Yes	No
African American/Black	56.7%	43.3%
American Indian/Alaska Native	72.7%	27.3%
Asian	72.6%	27.4%
Hispanic/Latino	59.3%	40.7%
Native Hawaiian/Pacific Islander	57.9%	42.1%
White	63.0%	37.0%
Multiracial	57.3%	42.7%
Another Group	76.1%	23.9%

Sutter County	Percent
Race/Ethnicity	Yes	No
African American/Black	52.9%	47.1%
American Indian/Alaska Native	62.0%	38.0%
Asian	73.7%	26.3%
Hispanic/Latino	56.3%	43.7%
Native Hawaiian/Pacific Islander	52.2%	47.8%
White	70.5%	29.5%
Multiracial	64.7%	35.3%
Another Group	63.6%	36.4%

Tehama County	Percent
Race/Ethnicity	Yes	No
African American/Black	51.9%	48.1%
American Indian/Alaska Native	66.4%	33.6%
Asian	83.2%	16.8%
Hispanic/Latino	58.6%	41.4%
Native Hawaiian/Pacific Islander	S	S
White	69.8%	30.2%
Multiracial	65.6%	34.4%
Another Group	67.8%	32.2%

Trinity County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	65.4%	34.6%
Asian	69.7%	30.3%
Hispanic/Latino	29.1%	70.9%
Native Hawaiian/Pacific Islander	N/A	N/A
White	54.0%	46.0%
Multiracial	70.8%	29.2%
Another Group	S	S

Tulare County	Percent
Race/Ethnicity	Yes	No
African American/Black	S	S
American Indian/Alaska Native	S	S
Asian	S	S
Hispanic/Latino	S	S
Native Hawaiian/Pacific Islander	S	S
White	S	S
Multiracial	S	S
Another Group	S	S

Tuolumne County	Percent
Race/Ethnicity	Yes	No
African American/Black	56.8%	43.2%
American Indian/Alaska Native	71.2%	28.8%
Asian	66.0%	34.0%
Hispanic/Latino	44.7%	55.3%
Native Hawaiian/Pacific Islander	61.4%	38.6%
White	62.7%	37.3%
Multiracial	54.3%	45.7%
Another Group	71.6%	28.4%

Ventura County	Percent
Race/Ethnicity	Yes	No
African American/Black	58.9%	41.1%
American Indian/Alaska Native	63.8%	36.2%
Asian	77.9%	22.1%
Hispanic/Latino	58.4%	41.6%
Native Hawaiian/Pacific Islander	64.0%	36.0%
White	70.7%	29.3%
Multiracial	63.8%	36.2%
Another Group	61.5%	38.5%

Yolo County	Percent
Race/Ethnicity	Yes	No
African American/Black	53.4%	46.6%
American Indian/Alaska Native	53.7%	46.3%
Asian	71.7%	28.3%
Hispanic/Latino	57.5%	42.5%
Native Hawaiian/Pacific Islander	58.9%	41.1%
White	68.5%	31.5%
Multiracial	61.9%	38.1%
Another Group	63.3%	36.7%

Yuba County	Percent
Race/Ethnicity	Yes	No
African American/Black	69.2%	30.8%
American Indian/Alaska Native	72.1%	27.9%
Asian	64.2%	35.8%
Hispanic/Latino	61.5%	38.5%
Native Hawaiian/Pacific Islander	85.2%	14.8%
White	62.1%	37.9%
Multiracial	64.5%	35.5%
Another Group	67.5%	32.5%

Definition, Source & Notes (Return to top)

Definition: Estimated percentage of public school students in grades 7, 9, 11, and non-traditional programs who ate breakfast on the day of survey, by race/ethnicity (e.g., in 2017-2019, 57.4% of Hispanic/Latino students in grades 7, 9, 11, and non-traditional programs in California had eaten breakfast in the past day).
Data Source: WestEd, California Healthy Kids Survey (CHKS) and Biennial State CHKS. California Dept. of Education (Aug. 2020).
Footnote: Years presented comprise two school years (e.g., 2017-18 and 2018-19 school years are shown as 2017-2019). County- and state-level data are weighted estimates; school district-level data are unweighted. Students in non-traditional programs are those enrolled in community day schools or continuation education. The notation S refers to (a) data for school districts that have been suppressed because there were fewer than 10 respondents in that group, and (b) data for counties that have been suppressed because the sample was too small to be representative. N/A means that data are not available.

Learn More About Nutrition

Measures of Nutrition on Kidsdata.org

Kidsdata.org offers the following nutrition-related indicators:

Children ages 2-17 who drank one or more sodas or other sugar-sweetened beverages in the previous day, who ate five or more servings of fruits or vegetables in the previous day, and who ate fast food two or more times in the previous week*
Students in grades 7, 9, 11, and non-traditional programs who ate breakfast in the previous day†
School staff reports on the extent to which their school provides students with healthy food choices‡

* These estimates come from the California Health Interview Survey and are available, depending on the indicator, by county, age group, and/or race/ethnicity.

† These estimates come from the California Healthy Kids Survey (CHKS) and are available by grade level, gender, level of school connectedness, parent education level, and sexual orientation. State-level CHKS estimates, although derived from the Biennial State CHKS, may differ from data published in Biennial State CHKS reports due to differences in grade-level classification of students in continuation high schools.

‡ These data come from the California School Staff Survey and are available for elementary, middle, high, and non-traditional school staff.

Related Data

Nutrition

Student Demographics

Students Eligible for Free or Reduced Price School Meals
- by Eligibility Status

Food Security

Physical Fitness

Weight

Students Who Are Overweight or Obese, by Grade Level
- by Gender and Grade Level
- by Race/Ethnicity and Grade Level

Why This Topic Is Important

Children and youth need a nutritious diet for healthy growth and development (1). Proper nutrition over the life course can help reduce the risk of developing dental cavities, high blood pressure, diabetes, obesity, heart disease, osteoporosis, cancer, and other conditions (1, 2). Unfortunately, estimates show that about half (49%) of U.S. children have poor-quality diets (2).

Eating a healthy breakfast is an important way to promote proper nutrition (3). Children who eat breakfast have higher daily intakes of key vitamins and minerals and tend to make better food choices throughout the day (3). Eating a nutritious breakfast also is associated with improved mood, cognitive functioning, and school attendance (1).

Children in low-income households and children of color are at increased risk for inadequate nutrition, which can have long-term negative consequences (4, 5). For example, economically disadvantaged children tend to consume more sugar-sweetened beverages, which contribute to obesity and increase the risk for chronic diseases later in life (5). In addition, food insecurity (limited or uncertain access to adequate food) can adversely affect children's cognitive development and academic performance (6). More than 1 million children in California—and nearly 11 million nationwide—live in households experiencing food insecurity (6).

For more information, see kidsdata.org’s Research & Links section.

Sources for this narrative:

1. Centers for Disease Control and Prevention. (2021). Childhood nutrition facts. Retrieved from: https://www.cdc.gov/healthyschools/nutrition/facts.htm

2. Liu, J., et al. (2021). Trends in food sources and diet quality among U.S. children and adults, 2003-2018. JAMA Network Open, 4(4), e215262. Retrieved from: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2778453.

3. Giménez-Legarre, N., et al. (2020). Breakfast characteristics and its association with daily micronutrients intake in children and adolescents: A systematic review and meta-analysis. Nutrients, 12(10), 3201. Retrieved from: https://www.mdpi.com/2072-6643/12/10/3201

4. Peltz, A., & Garg, A. (2019). Food insecurity and health care use. Pediatrics, 144(4), e20190347. Retrieved from: https://publications.aap.org/pediatrics/article/144/4/e20190347/76973/Food-Insecurity-and-Health-Care-Use

5. Muth, N. D., et al. (2019). Public policies to reduce sugary drink consumption in children and adolescents. Pediatrics, 143(4), e20190282. Retrieved from: https://publications.aap.org/pediatrics/article/143/4/e20190282/37217/Public-Policies-to-Reduce-Sugary-Drink-Consumption

6. Feeding America. (n.d.). Map the meal gap: Child food insecurity in the United States. Retrieved from: https://map.feedingamerica.org/county/2019/child

How Children Are Faring

In 2017-2019, an estimated 66% of California 7th graders, 60% of 9th graders, 58% of 11th graders, and 50% of students in non-traditional programs had eaten breakfast in the past day. Across grade levels statewide, boys were more likely to have had breakfast than girls. In general, estimates of eating breakfast are lowest for students with low levels of school connectedness and those whose parents did not finish high school (46% and 54%, respectively, in 2017-2019), and increase as levels of school connectedness and parent education improve. In 2017-2019, fewer than 50% of gay, lesbian, and bisexual students in California had eaten breakfast in the past day, compared with more than 60% of students in other groups.

According to estimates from a 2017-2018 survey of parents and teens, around one in four California children ages 2-17 had eaten at least five servings of fruits and vegetables in the past day. Estimates from the same survey in 2015-2016 showed 40% of children drinking at least one sugar-sweetened beverage in the past day and 43% eating fast food at least twice in the past week, with wide variation at the county level—from fewer than 12% to more than 60% across regions with data. Sugary drink consumption also varied by age and race/ethnicity. Statewide, among youth ages 12-17, an estimated 58% had drunk sugar-sweetened beverages in the previous day, whereas estimates for younger children were lower, at 35% for ages 6-11 and 22% for ages 2-5. Among groups with data, an estimated 66% of multiracial and 64% of Hispanic/Latino youth ages 12-17 had consumed sugary beverages in the past day, compared with African American/black youth at 55%, white youth at 53%, and Asian youth at 43%.

Policy Implications

Nutrition during childhood, beginning in the prenatal stage, influences lifelong health (1). The childhood years also are a critical time for establishing long-term dietary habits. Children and youth need a balanced diet rich in fruits and vegetables, as well as adequate water (2). Health experts also recommend minimizing consumption of solid fats, sodium, and added sugars, which are linked to negative health outcomes (2). Ensuring that children have access to nutritious food and learn to make healthy choices requires effort from multiple sectors, including local, state, and federal government, schools, health care, communities, businesses, and others (1, 2, 3, 4).

Schools are well-positioned to educate children about nutrition and promote healthy habits (2). Poor diets and food insecurity have been shown to substantially affect student achievement, making nutrition a priority for school performance (2). Children in poverty and children of color are particularly vulnerable to poor nutrition (4, 5). Federal nutrition programs such as the Supplemental Nutrition Assistance Program (SNAP, or CalFresh in California) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program offer vital support for low-income children and families, although many of these programs continue to be underutilized in California (3, 6). Policymakers can work to reduce poverty and economic inequities, preserve and strengthen food assistance programs, and expand access to nutritious, affordable foods in low-income communities (4, 7).

Policy and practice options to improve nutrition for children include:

Promoting strategies to ensure adequate nutrition for infants, toddlers, and pregnant and breastfeeding women; for example, assuring that health care providers are trained on nutrition issues and are able to refer families to appropriate support services (1)
Continuing to increase participation in food assistance programs—such as WIC and CalFresh—by improving integration and linkages across nutrition, health care, and other safety net programs in order to streamline enrollment and service delivery (3, 6)
Maintaining and strengthening recent state and federal legislation to provide healthy meals for low-income children in child care; as part of this, reducing administrative burden and providing adequate training and support to increase child care provider participation in the Child and Adult Care Food Program (CACFP), especially in underserved areas (8, 9)
Increasing awareness among school stakeholders—leaders, teachers, students, families, community members, and others—about the connections between nutrition, weight, cognitive functioning, academic performance, and school funding; this includes incorporating nutrition education into health curricula for students (2, 10)
Ensuring that California's Free School Meals for All Act of 2021 is implemented effectively at the local level so that all K-12 students receive healthy school meals (2, 11)
Continuing to promote robust nutrition programs for low-income children when school is out or when schools are closed due to emergencies; as part of this, ensuring that families are aware of such programs and that meals are provided in safe and welcoming environments, especially for immigrant families (11)
Promoting cross-sector, comprehensive strategies to reduce consumption of sugary beverages and increase the availability of healthy, affordable food options for children and families, particularly in low-income areas and communities of color; for example, attracting retailers of nutritious food (e.g., grocery stores) to locate in under-resourced areas, and advocating for restaurants to remove sugary drinks from children's menus (4, 5)
Continuing efforts to reduce marketing of unhealthy foods and beverages to children and adolescents, particularly advertising that disproportionately targets youth of color (5, 12)
Supporting action at the federal level to reduce child food insecurity, including strengthening and expanding nutrition assistance programs and improving coordination across federal agencies (7)

For more information, see the Research & Links section on kidsdata.org or visit Nourish California and Food Research and Action Center. Also see Policy Implications on kidsdata.org under Food Security and Family Income and Poverty.

Sources for this narrative:

1. Schwarzenberg, S. J., et al. (2018). Advocacy for improving nutrition in the first 1000 days to support childhood development and adult health. Pediatrics, 141(2), e20173716. Retrieved from: https://publications.aap.org/pediatrics/article/141/2/e20173716/38085/Advocacy-for-Improving-Nutrition-in-the-First-1000

2. Centers for Disease Control and Prevention. (2021). CDC healthy schools: Childhood nutrition facts; Dietary behaviors and academic grades; Nutrition education in U.S. schools. Retrieved from: https://www.cdc.gov/healthyschools

3. Danielson, C., et al. (2020). The importance of CalFresh and CalWORKs in children's early years. Public Policy Institute of California. Retrieved from: https://www.ppic.org/publication/the-importance-of-calfresh-and-calworks-in-childrens-early-years

4. PolicyLink. (n.d.). Equitable food systems resource guide. Retrieved from: https://www.policylink.org/food-systems/equitable-food-systems-resource-guide

5. Muth, N. D., et al. (2019). Public policies to reduce sugary drink consumption in children and adolescents. Pediatrics, 143(4), e20190282. Retrieved from: https://publications.aap.org/pediatrics/article/143/4/e20190282/37217/Public-Policies-to-Reduce-Sugary-Drink-Consumption

6. California WIC Association. (2021). Linking WIC for health equity: Expanding access to WIC through horizontal integration. Retrieved from: https://www.calwic.org/wp-content/uploads/2021/07/Expanding-Access-to-WIC-Through-Horizontal-Integration_07_21.pdf

7. Food Research and Action Center. (n.d.). Action center. Retrieved from: https://frac.org/action

8. Cannon, M. (2021). State funding for child care meals finally realized. Nourish California. Retrieved from: https://nourishca.org/impact-stories/statefundingforchildcaremeals

9. Marshall, S. (2020). CACFP is moving from CDE to CDSS: Let's make sure we don't get lost in transition. CACFP Roundtable. Retrieved from: https://www.ccfproundtable.org/post/cacfp-is-moving-from-cde-to-cdss-let-s-make-sure-we-don-t-get-lost-in-transition

10. California Department of Education. (2021). Nutrition education in California schools. Retrieved from: https://www.cde.ca.gov/ls/nu/he/nutritionedcaschools.asp

11. Free School Meals for All Act of 2021, Cal. S. B. 364 (2021-2022). Retrieved from: https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202120220SB364

12. Harris, J. L., et al. (2020). Sugary drink f.a.c.t.s. 2020. Rudd Center for Food Policy and Obesity. Retrieved from: https://www.sugarydrinkfacts.org/resources/Sugary%20Drink%20FACTS%202020/Sugary_Drink_FACTS_Full%20Report_final.pdf

Research & Links

Websites with Related Information

Action for Healthy Kids
California School Boards Association: Governance and Policy Resources
CDC Healthy Schools. Centers for Disease Control and Prevention.
Center for Science in the Public Interest
Child and Adolescent Nutrition: Professional Resource Guide. Maternal and Child Health Digital Library.
Child Nutrition Sharing Site. Institute of Child Nutrition.
Children: Food and Nutrition. Nutrition.gov.
Dietary Guidelines for Americans. U.S. Dept. of Agriculture & U.S. Dept. of Health and Human Services.
Food Research and Action Center
Healthy Eating and Nutrition Education. California Dept. of Education.
Healthy Eating Research. Robert Wood Johnson Foundation.
Healthy Food Access Portal. PolicyLink, et al.
Nourish California
Nutrition and Physical Activity Branch. California Dept. of Public Health.
Nutrition and Physical Activity Initiative. California Dept. of Public Health, Maternal, Child and Adolescent Health Division.
Nutrition Policy Institute. University of California, Agriculture and Natural Resources.
Public Health Advocates
Roots of Change. Public Health Institute.
Rudd Center for Food Policy and Health. University of Connecticut.

Key Reports and Research

Access to Food in Early Care Continues to Decline. (2019). Nourish California. Homel Vitale, E.
Advocacy for Improving Nutrition in the First 1000 Days to Support Childhood Development and Adult Health. (2018). Pediatrics. Schwarzenberg, S. J., et al.
Early Care and Education Policies and Programs to Support Healthy Eating and Physical Activity: Best Practices and Changes Over Time. (2017). Healthy Eating Research. Fox, T., et al.
Effective Access to Drinking Water in Schools. (2021). Nutrition Policy Institute.
Equitable Food Systems Resource Guide. PolicyLink.
Free School Meals for All Here to Stay in California. (2021). EdSource. Tadayon, A.
Marketing of Foods and Beverages: Impact and Potential Solutions for Children and Young People’s Health. International Journal of Environmental Research and Public Health. Harris, J. L., & Tatlow-Golden, M. (Eds.).
Public Policies to Reduce Sugary Drink Consumption in Children and Adolescents. (2019). Pediatrics. Muth, N. D., et al.
School Breakfast Program. Food Research and Action Center.
Snacks, Sweetened Beverages, Added Sugars, and Schools. (2015). Pediatrics. American Academy of Pediatrics, Council on School Health & Committee on Nutrition.
Soda on the Menu: Improvements Seen But More Change Needed for Beverages on Restaurant Children's Menus. (2017). Center for Science in the Public Interest. Ribakove, S., et al.
Sugary Drink F.A.C.T.S. 2020. (2020). Rudd Center for Food Policy and Obesity. Harris, J. L., et al.
The Associations Between Sugar-Sweetened Beverage Consumption and Children’s Health: An Updated Review of the Literature. (2018). Healthy Eating Research. Bleich, S. N., & Vercammen, K. A.
The Healthy Communities Study: Examining Community Programs, Policies and Other Characteristics in Relation to Child Weight, Diet, and Physical Activity. (2018). Pediatric Obesity. Kumanyika, S. K. (Ed.).
The Role of the Federal Child Nutrition Programs in Improving Health and Well-Being. (2017). Food Research and Action Center. Hartline-Grafton, H.
Trends in Food Sources and Diet Quality Among U.S. Children and Adults, 2003-2018. (2021). JAMA Network Open. Liu, J., et al.
Trends in Sugar-Sweetened Beverage Consumption Among California Children. (2020). Public Health Nutrition. Beck, A. L., et al.

County/Regional Reports

Annual Report on the Conditions of Children in Orange County. Orange County Children's Partnership.
Community Health Equity Improvement Plan for Los Angeles County. Los Angeles County Dept. of Public Health.
Community Health Profiles. Los Angeles County Dept. of Public Health.
San Mateo County All Together Better. San Mateo County Health.
Santa Clara County Children's Data Book. Santa Clara County Office of Education, et al.
Santa Clara County Public Health Department: Open Data Portal

More Data Sources For Nutrition

California Health and Human Services Open Data Portal. California Health and Human Services Agency.
California Health Interview Survey. UCLA Center for Health Policy Research.
California School Climate, Health, and Learning Surveys Public Dashboards. WestEd & California Dept. of Education.
Health, United States – Data Finder. National Center for Health Statistics.
Map the Meal Gap. Feeding America.
National Health and Nutrition Examination Survey (NHANES). Centers for Disease Control and Prevention.
Nutrition, Physical Activity, and Obesity: Data, Trends, and Maps. Centers for Disease Control and Prevention.
State and County Nutrition Profiles. Nourish California.
State of the States: Profiles of Hunger, Poverty, and Federal Nutrition Programs. Food Research and Action Center.
U.S. Dept. of Agriculture: Data Products
Youth Risk Behavior Surveillance System (YRBSS). Centers for Disease Control and Prevention.

Students Eating Breakfast in the Past Day, by Race/Ethnicity

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