Adolescent Birth Rate Decline in California
Regional Contributions (2010-2020)
From 2010 – 2020, California's Adolescent Birth Rate (ABR) continued to decline, resulting in an all-time low and mirroring the national trend.1-,2,3,4 ABR decreases occurred across age and racial/ethnic groups and the state's geographical regions. This data brief presents 2010–12 and 2018–20 rate estimates by subgroup and examines regional contributions5,6 to the overall decline statewide.
Key Findings - Statewide
Statewide ABR
- The ABR for those ages 15–19 years declined from 31.6 live births per 1,000 population (2010) to 10.1 per 1,000 (2020), an absolute difference of 21.5 live births per 1,000, which is a 68% decline.
Statewide By Age Group
- ABR for ages 15-17 dropped from 14.7 (2010–12) to 4.9 (2018–20) live births per 1,000 (absolute difference of 9.8 live births per 1,000, or 67% decline).
- Birth rate among adolescents ages 18-19 dropped from 46.5 (2010–12) to 20.3 (2018–20) live births per 1,000 population (absolute difference of 26.2 per 1,000, or 56% decline).
Statewide by Race/Ethnicity
The ABR (ages 15–19) varied substantially by race/ethnicity, and the differences have become more pronounced over time, even as the racial/ethnic-specific ABRs have declined.
- In 2010–12, the ABR ranged from 5.2 among Asian adolescents to 44.1 among Hispanic adolescents; this is more than an eight-fold difference.
- In 2018–20, the ABR ranged from 1.5 among Asian adolescents to 17.4 among Hispanic adolescents; this is more than an 11-fold difference.
- These changes in ABR among Asian and Hispanic adolescents reflect declines of 71.7% and 60.6%, respectively.
Notes: Multi-race=Multiple races; AIAN=American Indian and Alaska Native; PI=Pacific Islander
Key Findings - Region and County
Region
Across California's nine regionsi:
- San Joaquin Valley region had the highest ABR in both 2010–12 (44.8 live births per 1,000) and 2018–20 (19.7 live births per 1,000).
- San Francisco Bay Area region had the lowest ABR in both 2010–12 (18.2 live births per 1,000) and 2018–20 (6.6 live births per 1,000).
- San Diego County, a region on its own, had the largest decline at 65.1%.
- North/Mountain region had the smallest ABR decline at 50.9%.
- The ABR absolute decline between 2010–12 and 2018–20 ranged from 11.5 live births per 1,000 in the San Francisco Bay Area region to 25.1 live births per 1,000 in the San Joaquin Valley region.
-
The nine regions are groups of counties as defined by the
California’s Maternal and Infant Health Assessment survey
County
The ABR varied widely across California's 58 counties with at least 10 live births in 2018–20:
- Marin County had the lowest ABR in both 2010–12 (10.7 live births per 1,000) and 2018–20 (4.3 live births per 1,000).
- Tulare County had the highest ABR in 2010–12 (55.6 live births per 1,000).
- Kern County had the highest ABR in 2018–20 at 23.3 live births per 1,000, more than five times that of Marin County.
- Santa Clara County had the largest decline in ABR between 2010–12 and 2018–20 at 70.0% .
- Mariposa County had the smallest decline in ABR between 2010–12 and 2018–20 at 20.7%.
- The ABR absolute decline between 2010–12 and 2018–20 ranged from 3.7 live births per 1,000 in Tuolumne County to 32.6 live births per 1,000 in Tulare County.
County and Regional Contributions to The Statewide ABR Decline
County and regional contributions to the decline in California's ABR between 2010–12 and 2018–20 are as follows:
- Los Angeles County, 29.2%
- San Joaquin Valley Region, 17.5%
- Southeastern CA Region, 15.2%
- San Francisco Bay Area Region, 10.5%
- The remaining 28% of the decline can be attributed to the following counties and regions:
- San Diego County, 7.7%
- Orange County, 6.1%
- Central Coast Region, 5.9%
- Greater Sacramento Region, 5.2%
- North/Mountain Region, 2.6%
Public Health Implications
Unprecedented reductions in the birth rates nationally and in California occurred in the last decade. Preventing unintended pregnancy among adolescents is critical to achieving positive health outcomes across the life course and has been included in the Centers for Disease Control and Prevention's list of “Winnable Battles."7,8
Broad economic and social factors influence adolescents' behaviors, such as whether they abstain from sex or use contraceptives. Providing access to, and promoting the use of, contraception among sexually active adolescents should reduce unintended pregnancies and births.
The Maternal, Child, and Adolescent Health's
Adolescent Sexual Health Education Program provides California youth with knowledge and skills to help them make informed decisions, develop life skills and healthy relationships, protect themselves from sexually transmitted infections, and avoid unintended pregnancies. The
California Home Visiting Program and the
Adolescent Family Life Program help pregnant and parenting adolescents by offering services such as counseling on postpartum contraception to enhance pregnancy planning and spacing and to boost educational attainment. Targeted prevention initiatives within high birth rate areas could improve health and social outcomes for all adolescents.
Methods
Data Sources
The following data sources were used in the development of this data brief:
- 2010–12, California Birth Statistical Master File. California Department of Public Health, Center for Health Statistics and Informatics.
- 2018–20, California Comprehensive Master Birth File. California Department of Public Health, Center for Health Statistics and Informatics.
- 2010-20, Population data, State of California, Department of Finance. Demographic Research Unit. County Population Projections 2010–2060. Sacramento, California. January 2020. Updated July 14, 2021.
To obtain stable statewide demographic characteristics of births by demographic and geographic characteristics, three-year aggregated (2010–12 and 2018–20) data were used.
Definition of Adolescent Birth Rate (ABR)
The ABR is defined as the number of live births to adolescents aged 15–19 years divided by the total number of female adolescent population ages 15–19 years, then multiplied by 1,000.
Definition of Regions
Regions are groups of counties as defined by California's Maternal and Infant Health Assessment (MIHA). Three regions are standalone counties: Los Angeles, Orange, and San Diego. See map below.
- Cental Coast Region - Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz, Ventura
- Greater Sacramento Region - El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba
- Los Angeles County
- North/Mountain Region - Alpine, Amador, Butte, Calaveras, Colusa, Del Norte, Glenn, Humboldt, Inyo, Lake, Lassen, Mariposa, Mendocino, Modoc, Mono, Nevada, Plumas, Shasta, Sierra, Siskiyou, Tehama, Trinity, Tuolumne
- Orange County
- San Diego County
- San Francisco Bay Area - Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solando, Sonoma
- San Joaquin Valley - Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, Sonoma
- Southeastern California - Imperial, Riverside, San Bernadino
Kitagawa Rate Decomposition
To estimate the regional contributions to the ABR decline, the Kitagawa rate decomposition method was used. This method identifies the relative contributions of changes to ABR's two factors: (1) distribution of birthing people ages 15–19 by time and geography; (2) each ABR-specific to time and geography (see equation below). The Kitagawa rate decomposition method compared the ABR between two periods, 2010–12 and 2018–20, by region. This method breaks down the total change in the birthing population over time, partitioning changes in the given region and region-specific ABR, to determine the contribution attributable to a region.
The difference in the overall rates (R1 – R2) is attributable to these factors:
- Distribution of factor (percent by category i, Pi)
∑i (P1i – P2i) x ((R1i + R2i) ÷ 2)
- Factor-specific rates of an outcome (rates by category i, Ri)
∑i (R1i – R2i) x ((P1i + P2i) ÷ 2)
Where:
Factor 1, P = distribution of birthing population
Factor 2, R = ABR factor-specific rates
1i = time 1, 2010–12
2i = time 2, 2018–20
Limitation
The Kitagawa rate decomposition method evaluates a single covariate or risk factor assessment at a time and, thus, is not a multivariable approach.
|
Monterey |
45.2 |
22.4 |
-50.4% |
|
San Benito |
21.7 |
11.3 |
-47.9% |
|
San Luis Obispo |
16.2 |
6.8 |
-58.0% |
|
Santa Barbara |
29.5 |
16.7 |
-43.4% |
|
Santa Cruz |
21.7 |
7.1 |
-67.3% |
|
Ventura |
26.9 |
11.3 |
-58.0% |
|
El Dorado |
13.0 |
4.5 |
-65.4% |
|
Placer |
12.6 |
5.0 |
-60.3% |
|
Sacramento |
27.3 |
10.9 |
-60.1% |
|
Sutter |
29.3 |
14.9 |
-49.1% |
|
Yolo |
15.7 |
5.8 |
-63.1% |
|
Yuba |
43.1 |
18.8 |
-56.4% |
|
Los Angeles |
27.9 |
10.6 |
-62.0% |
|
Alpine |
* |
* |
* |
|
Amador |
19.4 |
11.6 |
-40.2% |
|
Butte |
23.2 |
10.2 |
-56.0% |
|
Calaveras |
19.1 |
10.6 |
-44.5% |
|
Colusa |
34.7 |
16.5 |
-52.4% |
|
Del Norte |
53.4 |
20.9 |
-60.9% |
|
Glenn |
39.5 |
15.6 |
-60.5% |
|
Humboldt |
22.8 |
10.4 |
-54.4% |
|
Inyo |
34.9 |
21.4 |
-38.7% |
|
Lake |
38.2 |
22.8 |
-40.3% |
|
Lassen |
36.3 |
23.1 |
-36.4% |
|
Mariposa |
23.7 |
18.8 |
-20.7% |
|
Mendocino |
37.3 |
17 |
-54.4% |
|
Modoc |
28.6 |
16.5 |
-42.3% |
|
Mono |
21.5 |
10.8 |
-49.8% |
|
Nevada |
14.7 |
6.1 |
-58.5% |
|
Plumas |
23.9 |
13.6 |
-43.1% |
|
Shasta |
29.8 |
14.5 |
-51.3% |
|
Sierra |
* |
* |
* |
|
Siskiyou |
35.9 |
15.4 |
-57.1% |
|
Tehama |
36.6 |
19.8 |
-45.9% |
|
Trinity |
38.5 |
19.2 |
-50.1% |
|
Tuolumne |
16.0 |
12.3 |
-23.1% |
|
Orange |
20.1 |
7.5 |
-62.7% |
|
San Diego |
26.0 |
9.1 |
-65.0% |
|
Alameda |
18.6 |
6.3 |
-66.1% |
|
Contra Costa |
18.3 |
7.6 |
-58.5% |
|
Marin |
10.7 |
4.3 |
-59.8% |
|
Napa |
21.7 |
7.5 |
-65.4% |
|
San Francisco |
12.3 |
5.1 |
-58.5% |
|
San Mateo |
16.1 |
6.6 |
-59.0% |
|
Santa Clara |
19.0 |
5.7 |
-70.0% |
|
Solano |
24.0 |
11.2 |
-53.3% |
|
Sonoma |
19.1 |
7.8 |
-59.2% |
|
Fresno |
45.6 |
19.4 |
-57.5% |
|
Kern |
52.4 |
23.3 |
-55.5% |
|
Kings |
48.8 |
20.3 |
-58.4% |
|
Madera |
50.2 |
20.4 |
-59.4% |
|
Merced |
41.9 |
18.9 |
-54.9% |
|
San Joaquin |
33.9 |
15.9 |
-53.1% |
|
Stanislaus |
34.7 |
16.7 |
-51.9% |
|
Tulare |
55.6 |
23.0 |
-58.6% |
|
Imperial |
50.8 |
22.4 |
-55.9% |
|
Riverside |
29.1 |
13.0 |
-55.3% |
|
San Bernardino |
35.9 |
15.6 |
-56.5% |
* Data are suppressed due to small numbers (i.e., between 1 and 9).
References
-
Osterman, M, Hamilton, B, Martin, J, Driscoll, A. Births: Final Data for 2020 National Vital Statistics Reports Vol 70, Number 17. February, 2022. https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-17.pdf
-
Power to Decide U.S. Teen Birth Rates Down 73% Since 1991 May, 2021. https://powertodecide.org/about-usnewsroom/us-teen-birth-rates-down-73-1991
-
Cal Matters In California, the teen birth rate has hit a record low. How? https://calmatters.org/health/2019/10/behind-californias-record-low-teen-birth-rate
- Brindis CD, Decker MJ, Gutmann-Gonzalez A, Berglas NF. Perspectives on Adolescent Pregnancy Prevention Strategies in the United States: Looking Back, Looking Forward. Adolesc Health Med Ther. 2020 Oct 12;11:135-145
- Kitagawa EM. Components of a difference between two rates. J Am Stat Assoc 1955;50(272):1168-94
- Chabot MJ, Campa M, Damesyn M.
Decomposing adolescent birth rates in the U.S.: Contributions of individual states and population subgroups to the nationwide decline. Paper presented at American Public Health Association Conference; November 1, 2015; Chicago, IL
https://apha.confex.com/apha/143am/webprogram/Paper328542.html
-
Centers for Disease Control and Prevention. CDC Reports Winnable Battles Results, 2016.
https://www.cdc.gov/media/releases/2016/p1205-winnable-battles.html
-
Centers for Disease Control and Prevention. Preventing pregnancies in younger teens. April 2014.
https://www.cdc.gov/vitalsigns/pdf/2014-04-vitalsigns.pdf