Complete Demographic & Statistical Summary for Texas 24-County Obesity
1. Dataset Structure & Coverage
| Dimension | Detail |
|---|---|
| Geography | 24 Texas counties (DFW metro + surrounding rural counties) |
| Time span | 2000–2019 (20 years, annual) |
| Ethnicity | 6 categories: Total, Latino (Any ethnicity), Non-Latino White, Non-Latino Black, Non-Latino American Indian/Alaska Native, Non-Latino Asian/Pacific Islander |
| Male or Female | “Both” only (no male/female split in this extract) |
| Age groups | 14 five-year bands (20–24 through 80–84, plus 85+), plus 2 aggregates: “20 plus” and “20 plus, age standardized” |
| Metric | Prevalence rate of obesity (proportion of population, e.g. 0.30 = 30%) |
| Total rows | 46,080 |
| Data completeness | 67% populated (15,040 cells suppressed — typical for small-population ethnicity/age cross-tabs, e.g. Asian/Pacific Islander in rural counties) |
Counties included: Bosque, Brown, Collin, Comanche, Dallas, Denton, Eastland, Ellis, Erath, Hamilton, Hill, Hood, Hunt, Jack, Johnson, Kaufman, Navarro, Palo Pinto, Parker, Rockwall, Somervell, Stephens, Tarrant, Wise
2. Statewide Trend (24-county average, age-standardized, all races)
| Year | Obesity Prevalence |
|---|---|
| 2000 | 29.96% |
| 2005 | 35.50% |
| 2010 | 39.65% |
| 2015 | 42.50% |
| 2019 | 45.39% |
- Absolute increase: +15.43 percentage points (2000→2019)
- Relative growth: +51.5%
- CAGR: 2.21%/year over the full period
3. Breakdown by Ethnicity (2000 vs 2019, age-standardized)
| ETHNICITY | 2000 | 2019 | Δ pts | % growth |
|---|---|---|---|---|
| Non-Latino, White | 28.54% | 43.97% | +15.43 | +54.1% |
| Total | 29.96% | 45.39% | +15.44 | +51.5% |
| Latino, Any ethnicity | 36.93% | 50.86% | +13.93 | +37.7% |
| Non-Latino, American Indian/AK Native | 31.35% | 44.01% | +12.65 | +40.4% |
| Non-Latino, Black | 39.73% | 50.92% | +11.19 | +28.2% |
| Non-Latino, Asian/Pacific Islander | 12.59% | 22.54% | +9.95 | +79.1% |
Key insight: Black and Latino populations have the highest absolute obesity rates throughout the period, but Asian/Pacific Islander populations show the fastest relative growth rate — nearly doubling, albeit from a low base.
4. Breakdown by Age Group (Total ethnicity, statewide avg)
| Age Band | 2000 | 2019 | Δ pts |
|---|---|---|---|
| 20–24 | 21.60% | 32.21% | +10.61 |
| 35–39 | 32.22% | 48.75% | +16.52 |
| 45–49 (peak) | 33.48% | 50.93% | +17.45 |
| 65–69 | 32.67% | 47.37% | +14.70 |
| 85+ | 13.21% | 25.42% | +12.21 |
Obesity prevalence peaks in middle age (45–54) across both years and declines after 65, consistent with national CDC patterns.
5. County-Level Highlights (2019, age-standardized)
Highest obesity prevalence:
- Navarro County — 49.66%
- Hill County — 49.29%
- Ellis County — 47.63%
Lowest obesity prevalence:
- Collin County — 35.02%
- Denton County — 39.60%
- Rockwall County — 39.68%
Fastest-growing counties (2000→2019):
- Johnson County — +16.50 pts
- Stephens County — +16.41 pts
- Wise County — +16.25 pts
Pattern: affluent, more urbanized counties near Dallas (Collin, Denton, Rockwall) consistently post the lowest rates; rural/exurban counties (Navarro, Hill, Stephens) post the highest.
6. Growth Projections (Linear Trend Extrapolation)
| Year | Full-period trend (2000–19) | Recent-momentum trend (2015–19) |
|---|---|---|
| 2020 | 46.7% | 46.1% |
| 2022 | 48.2% | 47.5% |
| 2025 | 50.5% | 49.7% |
| 2030 | 54.4% | 53.3% |
Linear extrapolation only — does not account for COVID-era disruptions, policy interventions, or demographic shifts. Treat as a directional estimate, not a forecast.
7. Practical Uses of This Data
- Public health resource allocation — target counties (Navarro, Hill, Ellis) for intervention funding
- Grant writing / research justification — supports Tarleton State research with quantified disparity trends by ethnicity and county
- Healthcare facility planning — bariatric/metabolic service demand forecasting by region
- Policy support — demonstrates disparate impact across ethnicity groups for equality-focused programs
- Academic publication — 20-year longitudinal dataset suitable for trend/disparity analysis in peer-reviewed work
- Insurance/employer wellness programs — regional risk stratification
8. Note on Dashboard Metric
Your two dashboards plot SUM(Obesity) (summed across multiple age-group rows per county/ethnicity/year) — values in the 5–7.5 range. This is a different scale than the age-standardized prevalence rate (%) used in this summary. Both are valid for comparison purposes (year-over-year, county-over-county), but the dashboard values aren’t directly interpretable as “% of population obese” the way the age-standardized figures above are.