Barber County

Barber County, Kansas — key demographics (latest available U.S. Census Bureau estimates; ACS 2019–2023 5-year unless noted; rounded)

• Population: ~4,300 (2023 estimate)
• Age:
  • Median age: ~44 years
  • Under 18: ~22%
  • 18–64: ~54%
  • 65 and over: ~24%
• Gender: ~50% female, ~50% male
• Race and ethnicity:
  • White (non-Hispanic): ~87–90%
  • Hispanic or Latino (any race): ~5–7%
  • Two or more races: ~3%
  • American Indian/Alaska Native: ~1%
  • Black or African American: ~0.5–1%
  • Asian: ~0.3%
• Households and housing:
  • Households: ~1,900–2,000
  • Average household size: ~2.3
  • Family households: ~60–65% of households (majority married-couple)
  • Owner-occupied housing rate: ~75–80%

Source: U.S. Census Bureau, American Community Survey 2019–2023 5-year estimates; Population Estimates Program (2023). Figures are estimates and rounded.

Barber County, KS snapshot (estimates; triangulated from ACS internet-subscription data, Pew email adoption, and rural Kansas trends):

• Estimated email users: ≈3,000 residents (about 65–72% of total population ~4.2–4.4k).
• Age distribution of email users:
  • 13–24: ~15%
  • 25–44: ~28%
  • 45–64: ~30%
  • 65+: ~27%
• Gender split among users: roughly even (≈49% female, 51% male).

Digital access and trends:

• Home internet subscription likely mid-70% of households; a growing share are smartphone‑only connections (~10–15%).
• Fixed wireless is common outside towns; limited fiber in town centers; DSL is declining. Satellite is countywide fallback.
• Usage is steady among working‑age adults and rising among seniors, though affordability and device gaps persist (ACP wind‑down may affect low‑income households).

Local density/connectivity context:

• Sparse population (~4 people per square mile across ~1,100+ sq mi) raises last‑mile costs and affects service consistency.
• Better speeds/availability in Medicine Lodge and Kiowa; coverage becomes patchier on farms and in the Gypsum Hills terrain, where line‑of‑sight wireless can be challenging.

Summary: Mobile phone usage in Barber County, Kansas (focus on how it differs from statewide patterns)

Context snapshot

• Population and households: Approximately 4.2–4.5k residents and ~1.8–2.0k households. Adults (18+) ≈ 78–82% of residents.
• Demographics: Older than Kansas overall (larger 55+ and 65+ shares), lower population density, and modestly lower median household income than state average.

User estimates (adults)

• Any mobile phone ownership: ~90–96% of adults (≈3.0k–3.4k users). Slightly below Kansas, where near-universal mobile ownership is typical.
• Smartphone users: ~78–85% of adults (≈2.6k–3.0k users). Below the Kansas average (roughly high-80s to ~90%), largely due to older age structure and coverage constraints.
• Wireless-only households (no landline): ~62–68% of households (≈1.1k–1.3k). Slightly lower than the statewide share, reflecting the county’s older population that retains landlines.
• Prepaid share: Higher than the state average (estimated 30–40% of lines vs ~20–25% in Kansas overall), tied to income mix, rural work patterns, and carrier retail footprints.
• Upgrade cycle: Longer than state average; many users hold devices 3–4 years (vs ~2–3 years statewide).

Demographic breakdown and usage patterns

• Age:
  • 18–34: Smaller share than Kansas; heavy smartphone use, social/video apps similar to state peers but more off‑loading to Wi‑Fi due to variable mobile speeds.
  • 35–54: Similar app and tethering habits to statewide norms; frequent use of banking, ag/commodity, and navigation apps.
  • 55–64 and 65+: Larger local share; lower smartphone adoption and more basic/flip‑phone usage than state average; heavier reliance on voice/SMS, fewer data‑intensive apps.
• Income and plans:
  • More price‑sensitive plan selection; higher incidence of multi‑line family plans, MVNOs, and prepaid.
  • Greater use of Wi‑Fi calling at home because of spotty indoor signal in some areas.
• Language/ethnicity:
  • Predominantly non‑Hispanic White with a small but meaningful Hispanic population; bilingual outreach via SMS performs well but overall app‑based government/health engagement trails state averages.

Digital infrastructure points (where Barber differs from state-level)

• Coverage and technology mix:
  • LTE is common along primary corridors (US‑160, US‑281, K‑2), but there are gaps in the Gypsum Hills and river/valley areas; in‑building coverage is less consistent than in Kansas overall due to sparse tower placement.
  • Low‑band 5G is present mainly along highways and in/near towns; mid‑band 5G (for higher speeds) is limited or absent in much of the county. This is well behind coverage in metro and many micropolitan Kansas areas.
  • mmWave 5G is effectively absent (typical for rural Kansas), so peak urban‑style speeds are not a realistic baseline.
• Carrier dynamics:
  • Verizon and AT&T tend to have the most reliable rural coverage; T‑Mobile’s footprint is improving along corridors but remains patchier off‑road compared with statewide patterns.
  • FirstNet (AT&T) presence supports public safety; that network often provides some of the most reliable indoor coverage in and near public facilities.
• Backhaul and tower grid:
  • Fewer fiber‑fed macro sites and heavier reliance on microwave backhaul compared with urban Kansas, constraining capacity during peak times.
  • Tower density is low for the county’s land area, which drives the need for boosters/repeaters in metal‑roof homes and larger ranch properties.
• Home and community connectivity interplay:
  • Fiber is available in pockets of towns and near some exchanges; outside of town, fixed wireless and legacy DSL are more common. This mix pushes residents to prefer Wi‑Fi for data‑heavy use and rely on mobile mainly for communications and light apps.
  • Public Wi‑Fi (libraries, schools, some businesses) plays an outsized role relative to urban Kansas, especially for software updates and video calls.
• Performance:
  • Median mobile speeds are generally below the Kansas statewide median, with greater variability by location and carrier.
  • Reliability (call completion, SMS delivery) is good on corridors but degrades faster with distance from towers than in denser parts of the state.

Trends that stand out vs. the Kansas average

• Lower smartphone penetration and a higher share of voice/SMS‑centric users due to age mix and patchier 5G, especially mid‑band.
• Heavier reliance on Wi‑Fi and Wi‑Fi calling at home; more conservative data use on cellular.
• Higher prepaid/MVNO usage and longer device replacement cycles.
• Carrier choice is driven by coverage first, price second—contrast with urban Kansas where plan features and 5G speeds weigh more.
• More frequent use of signal boosters/repeaters and external antennas in homes and farm/ranch operations.

Planning implications

• Outreach that assumes text/voice delivery will reach more residents than app‑only strategies.
• Services that function well on low‑band 5G/LTE and tolerate offline periods will perform better than bandwidth‑intensive, always‑connected tools.
• Public Wi‑Fi and device training for older adults can materially increase effective smartphone use.
• Targeted tower infill, fiber backhaul to existing sites, and fixed‑wireless upgrades will close the largest experience gaps relative to the state.

Method and notes

• Figures are estimates derived from county population/household counts and applying national/state adoption rates adjusted for Barber County’s older age profile, rural density, and known rural network constraints.

Note: Barber County–specific social metrics aren’t directly published. The figures below are best-available estimates based on Pew Research Center’s 2024 U.S. social media data, rural-urban differences, and Kansas small-county demographics. Treat them as directional.

Overall reach and user counts

• Population: roughly 4,300–4,600; adults (18+): ~3,200–3,700.
• Adults using at least one social platform: ~70–75% of adults ≈ 2,300–2,700 people.
• Daily users: ~55–60% of adults ≈ 1,800–2,200.

Most-used platforms among adults (share of adults; county-level estimate)

• YouTube: 75–80%
• Facebook: 65–70%
• Instagram: 25–35%
• TikTok: 20–30%
• Snapchat: 20–30% (skews under 30)
• Pinterest: 25–35% (skews female)
• X/Twitter: 10–15%
• LinkedIn: 10–15%
• Reddit: 8–12%
• WhatsApp: 8–12%
• Nextdoor: <5% (local Facebook Groups fill this role)

Age-group patterns

• Teens/18–29: Heavy on Snapchat, TikTok, Instagram; YouTube universal. Facebook is used, mostly for events and family.
• 30–49: Facebook is the hub (school, youth sports, buy/sell, events), YouTube strong; Instagram moderate; TikTok growing.
• 50–64: Facebook and YouTube dominate; some Pinterest; limited Instagram/TikTok.
• 65+: Facebook first (community news, church, clubs), YouTube for how‑tos and local content.

Gender tendencies (tendencies, not absolutes)

• Women: Over-index on Facebook and Pinterest; Instagram usage higher than men in 25–44.
• Men: Over-index on YouTube and Reddit; Facebook usage still high but slightly lower engagement in posting.

Behavioral trends in Barber County–type communities

• Community info flows through Facebook Groups and Pages: school districts, high school sports, county fair/rodeo, 4‑H/FFA, churches, first responders, buy/sell/trade.
• Weather and emergencies drive spikes: severe storms, wildfire risk, road closures, power outages. Local pages and sheriff/emergency pages see rapid sharing.
• Local commerce: Marketplace and group posts outperform brand pages for immediate sales; service businesses use Messenger for appointments.
• Content formats:
  • Facebook: photos + concise text; event flyers; short native video.
  • Short-form video (Reels/TikTok/Shorts) performs with under‑35s, especially sports recaps, hunting/fishing, farm/ranch life, local highlights.
  • YouTube: how‑to, equipment repair, outdoors, local history.
• Timing: Peaks before work (6–8 am) and evenings (7–10 pm); weekends for events/sports results.
• Trust: High for locally known admins and organizations; posts with names/faces and clear local ties get more engagement.
• Connectivity: Mobile-first; variable rural broadband—optimize for low data (captions, short clips, compressed images).

Data caveat

• Small-county variability can be high. Use these ranges to plan, then validate by checking actual engagement on local Pages/Groups and platform audience tools filtered to ZIPs in Medicine Lodge, Kiowa, and surrounding areas.