Contra Costa County

Key demographics for Contra Costa County, California (U.S. Census Bureau, American Community Survey 2022 1-year estimates unless noted)

Population

• Total population: ~1.16 million

Age

• Median age: ~39 years
• Under 18: ~23%
• 18 to 64: ~62%
• 65 and over: ~15%

Sex

• Female: ~50.7%
• Male: ~49.3%

Race and ethnicity (mutually exclusive; Hispanic can be any race)

• Hispanic or Latino: ~26–27%
• Non-Hispanic White: ~39–40%
• Non-Hispanic Asian: ~18–19%
• Non-Hispanic Black or African American: ~9–10%
• Non-Hispanic Two or more races: ~5%
• Non-Hispanic Native Hawaiian/Other Pacific Islander: ~0.8%
• Non-Hispanic American Indian/Alaska Native: ~0.5%

Households and housing

• Households: ~400–405k
• Average household size: ~2.75–2.80
• Family households: ~69–71% of households
• Households with children under 18: ~33%
• Owner-occupied housing rate: ~65–67% (renters ~33–35%)

Source: U.S. Census Bureau, American Community Survey (ACS) 2022 1-year; 2020 Census provides a baseline count. If you need a specific year (e.g., 2023 ACS or 2019–2023 ACS 5-year), say the word and I’ll tailor the figures.

Contra Costa County, CA (pop. ~1.17M) has near‑universal adult email use.

Estimated email users

• Roughly 0.9–1.0 million residents use email, assuming ~92–95% adult adoption (Pew-like U.S. rates applied to local population).

Age distribution (usage rates)

• 18–29: very high (≈95–99%)
• 30–49: very high (≈93–97%)
• 50–64: high (≈88–94%)
• 65+: slightly lower but widespread (≈80–90%) Most email users are ages 30–64, reflecting the county’s middle‑aged skew.

Gender split

• Essentially even; email adoption is similar by gender, so users mirror county demographics (~51% female, ~49% male).

Digital access trends and local connectivity

• About 93% of households have a broadband subscription and ~96–97% have a computer (ACS 2018–2022), supporting high email penetration.
• Cable and fiber are widely available in west/central cities; parts of far‑east/rural areas show lower fixed‑broadband adoption.
• Extensive public Wi‑Fi via libraries, schools, and municipal sites helps bridge gaps; smartphone access is widespread, enabling email on mobile.
• Major transit/built‑up corridors (e.g., along I‑80/680 and BART) have strong connectivity.
• Overall population density is high for a suburban county, supporting robust network investment and access.

Mobile phone usage in Contra Costa County, CA (2025 snapshot)

Headline takeaways that differ from California overall

• Very high smartphone adoption driven by income and education, but with sharper intra-county gaps than the state average (wealthy suburbs vs. lower-income bayfront and Delta communities).
• Suburban topography (hills/valleys around the Diablo Range and Briones) creates more terrain-driven dead zones than most urban California counties, so coverage quality is less uniform despite strong overall availability.
• Network demand is concentrated along commuter corridors (I‑80, I‑680, SR‑24, Hwy‑4) and BART rather than dense all-day urban cores; carriers have densified along these routes and in downtown nodes more than in residential hills.
• Small-cell rollout is widespread but faces stricter siting/permit frictions in several affluent suburbs compared with big-city California, so 5G mid‑band is common but ultra-dense mmWave is limited to a few downtowns/venues.

User estimates

• Population baseline: ≈1.17 million residents; ≈900,000 adults (18+).
• Smartphone users: 870,000–910,000 countywide (combining adults and teens). Method: apply high-80s to low-90s adult smartphone adoption typical for Bay Area suburbs, plus ~95% among teens.
• Active mobile lines: roughly on par with population (≈1.0–1.2 million), reflecting 1.1–1.3 lines per adult household in higher‑income suburbs and near‑universal lines among teens.
• 5G-capable handsets: majority; estimated 65–75% of active smartphones, a few points above the state average due to faster device refresh in higher‑income areas.
• Mobile-only home internet: estimated 7–10% of households countywide, below the statewide average but with tracts in Richmond, San Pablo, Bay Point, and parts of East County likely 15–25%. The Affordable Connectivity Program wind‑down in 2024 has likely nudged some fixed-broadband households toward mobile-only plans in these areas.

Demographic patterns

• Age
  • 18–49: near-universal smartphone ownership; heavy video/social use and mobile banking.
  • 50–64: high adoption; growing use as primary device for many services.
  • 65+: adoption materially lower than younger cohorts but rising; still higher than the state average due to education/income. Coverage reliability and larger-screen devices matter more in this group.
• Income and education
  • Lamorinda, Danville/Alamo, Walnut Creek, San Ramon: multi-line family plans, higher 5G device share, strong mobile payments/streaming usage; in-home Wi‑Fi offload common.
  • Richmond, San Pablo, Bay Point, pockets of Antioch/Pittsburg: higher reliance on prepaid, hotspotting, and mobile-only home internet; device turnover slower; multilingual OTT messaging (WhatsApp, WeChat, Messenger) prevalent.
• Geography
  • West/Central County (Richmond–El Cerrito–Orinda–Walnut Creek–Concord): dense macro plus small cells; strong 5G mid‑band. Hills cause shadowed pockets in canyon neighborhoods.
  • East County (Pittsburg–Antioch–Oakley–Brentwood, Byron/Discovery Bay/Bethel Island): rapid housing growth has outpaced capacity in some sectors at peaks; rural edges and Delta islands have coverage gaps and more frequent power-related service degradation than urban CA locales.

Digital infrastructure and performance notes

• Coverage and capacity
  • All national carriers operate robust macro networks along I‑80, I‑680, SR‑24, and Hwy‑4, with small-cell clusters in downtown Walnut Creek, Concord, Richmond, Antioch, Brentwood, and San Ramon.
  • 5G mid‑band is common in urban/suburban cores and along commute corridors; low‑band 5G/LTE persists in rural and hilly pockets. mmWave is limited to select downtown blocks and venues.
  • Terrain-driven shadowing around Lafayette/Orinda/Moraga, the Briones and Diablo foothills, and canyons produces localized dead zones uncommon in flatter California metros.
• Transit
  • Trackside coverage is solid along BART and eBART rights-of-way; in-train performance varies by car load, handoff density, and whether small-cell/DAS is present at stations. Peak-hour congestion is a known stressor.
• Resilience
  • PSPS (public safety power shutoffs) and wildfire weather increase risk of site outages in foothill and Delta areas; backup power provisioning has improved since 2020 but remains uneven compared to flat, fully urban counties.
• Permitting and siting
  • Several cities enforce strict aesthetics and spacing for small cells. Compared with large California cities, this can slow densification in leafy residential zones, leaving more reliance on macro fills and resulting in indoor coverage variability.

How Contra Costa differs from statewide norms

• Adoption: overall smartphone and 5G device adoption are slightly above the state average due to income/education, but the county shows wider neighborhood-to-neighborhood disparities than the statewide pattern.
• Access: fewer truly unserved areas than rural California overall, yet more terrain-caused pockets than typical metro counties; thus user experience is more variable within short distances.
• Usage: heavier concentration of mobile traffic along commuter corridors and suburban shopping/job centers, versus the all-day urban core demand seen in SF/LA. Work-from-home patterns keep residential sector demand high in hills and cul-de-sacs, where small-cell density lags.
• Substitution: countywide mobile-only internet share is lower than California’s average, but in specific lower-income tracts it is markedly higher than both the county and state averages.

Notes on method and uncertainty

• Figures are reasoned estimates based on 2020–2024 county population trends, Bay Area smartphone adoption patterns (e.g., Pew and ACS internet subscription profiles), and publicly available carrier deployment practices (mid‑band 5G along major corridors). Localized conditions can differ by neighborhood and carrier.

Below is a short, directional snapshot for Contra Costa County. There’s no public, county-specific measurement for every platform, so figures are modeled from 2024 U.S. usage (Pew and industry benchmarks) mapped to Contra Costa’s suburban/Bay Area profile and age mix. Use as estimates, not audited counts.

Baseline

• Population ≈1.18M; adults (18+) ≈920K.
• Internet access is high; most adults use at least one social platform (est. 80–85% → ~740K–780K adults).

Most-used platforms (adults; estimated adoption and user counts)

• YouTube: 82–86% → ~755K–790K
• Facebook: 62–70% → ~570K–645K
• Instagram: 45–50% → ~415K–460K
• TikTok: 30–35% → ~275K–320K
• WhatsApp: 28–38% → ~260K–350K (elevated by multilingual/immigrant communities)
• LinkedIn: 30–35% → ~275K–320K (strong professional base)
• Pinterest: 32–38% → ~295K–350K
• Snapchat: 23–28% → ~210K–260K
• X (Twitter): 18–24% → ~165K–220K
• Reddit: 18–22% → ~165K–200K
• Nextdoor: 25–35% of adults; 35–45% of households engage monthly (hyperlocal skew higher than U.S. average)

Age patterns (who uses what, most)

• Teens (13–17): YouTube 90%+; TikTok ~60–65%; Instagram ~60–65%; Snapchat ~55–60%; Facebook <35%.
• 18–29: YouTube 95%+; Instagram ~75–80%; TikTok ~60–65%; Snapchat ~55–60%; Facebook ~60–65%; Reddit/X ~30–35%.
• 30–49: Facebook ~75–80%; YouTube 90%+; Instagram ~55–60%; LinkedIn/Pinterest ~40–45%; WhatsApp/TikTok ~35–40%.
• 50–64: Facebook ~70–75%; YouTube ~85–90%; Pinterest/Instagram ~30–35%; Nextdoor ~30–35% of households; WhatsApp ~25–30%; TikTok ~20–25%.
• 65+: Facebook ~50–55%; YouTube ~55–60%; Nextdoor ~25–30% of households; Instagram ~15–20%; WhatsApp ~20–25%.

Gender breakdown (tendencies)

• Overall social audience ≈ county population split (about 50/50).
• Skews female: Pinterest (~70% women), Facebook (slight), Instagram (slight), Snapchat (moderate), TikTok (slight).
• Skews male: Reddit (strong), X/Twitter (moderate), YouTube (slight), LinkedIn (slight).
• WhatsApp and Nextdoor: near-balanced to slight female lean.

Behavioral trends to note

• Hyperlocal information: Nextdoor and Facebook Groups dominate for neighborhoods, schools, lost/found pets, crime/safety.
• Civic and transit: X/Twitter and Facebook for real-time updates from BART, Caltrans, CHP, cities, and during wildfire/PSPS events.
• Family/education: Strong Facebook/Group chat ecosystems around PTAs, youth sports, camps, and local services.
• Local discovery: Short-form video (Reels/TikTok) for restaurants, breweries/wineries (east county), hikes (Mt. Diablo/Briones), and events; YouTube for how-to, home/garden, and longer reviews.
• Messaging/communities: WhatsApp widely used in Spanish- and Asian-language groups; neighborhood buy/sell via Facebook Marketplace and Nextdoor’s “For Sale & Free.”
• Content/format: Video-first; carousels for events/promotions; Nextdoor text posts with utility get high engagement.
• Timing: Engagement bumps before work (7–9am), lunch (12–1pm), and evenings (7–10pm); weekends favor Instagram/TikTok; weekdays favor LinkedIn/Nextdoor.

Method note

• Estimates apply national adoption rates to Contra Costa’s adult population and adjust for Bay Area suburban patterns (higher LinkedIn, Nextdoor, WhatsApp). For planning, allow ±5–10 percentage points by platform. Sources: Pew Research Center (2024) and ACS demographics.