OFFICE BLUES

BURNOUT INDEX — CA — #15th OF 50

Sacramento-Roseville-Folsom
CA

33
/100
Moderate pressure
+1 vs. last update

Median household income sits +17% vs. the national median against a BEA Regional Price Parity of 100.3. Unemployment at 5.2% and a 27.4-minute average commute put Sacramento-Roseville-Folsom in the middle of the pack — the numbers don't make it a disaster, but they don't make it a bargain either.

Scored 2026-10-05. Data: Census ACS 5-year 2023, BEA RPP 2024. Unemployment: BLS LAUS (preliminary BLS estimate).

The receipts

Three components, three public sources. Each term is clamped to [0, 1] before weighting. The formula is published on the methodology page; any change to the weights requires a public ADR (ADR-0013+).

Component Raw value vs. national Weight Contribution Source
Pay-to-cost gap
Median HH income vs. cost of living.
Purchasing power index: 1.16 (wages above cost-adjusted national) 		$93,986
RPP 100.3 		+17% national
median income 		40% 0 Census ACS 2023 BEA RPP 2024
Mean commute
Minutes/day, ACS 5-year. Capped at 60 min. 		27.4 min 0.9 min longer than
26.5 min national 		30% 13.7 Census ACS 2023
Unemployment rate
BLS LAUS (monthly, MSA-level). Capped at 8%. Preliminary. 		5.2% 1.3pp above
3.9% national (ACS period) 		30% 19.5 BLS LAUS LAUMT064090000000003
Total score 33

Sacramento-Roseville-Folsom in context

Sacramento-Roseville-Folsom ranks 15th out of 50 major US metro areas on the Office Blues Burnout Index. The index measures three labor-market signals that directly affect worker quality of life: the gap between wages and cost of living, commute time, and unemployment pressure. It does not measure culture, management quality, or RTO mandates — those signals are not yet available at MSA level from primary sources without scraping.

The metro area population is approximately 2,399,935, making it one of the top-50 US metros by size. The data covers the Sacramento-Roseville-Folsom, CA Metropolitan Statistical Area (CBSA 40900), which typically extends well beyond the core city limits.

On wages vs. cost of living: median household income here is $93,986 per year (+17% the national median of $80,610). Against a BEA Regional Price Parity of 100.3 (national average = 100, higher = more expensive), that works out to a purchasing-power index of 1.16 relative to a national baseline of 1.0. Wages here stretch further than the national average on a cost-adjusted basis — that's why the pay-to-cost gap contributes 0 points, not more.

On commute: the average one-way trip takes 27.4 minutes — 0.9 min longer than the national mean of 26.5 minutes. The commute component contributes 13.7 points out of a possible 30 (capped when commute ≥ 60 minutes). Commute time is the most consistent predictor of reported job dissatisfaction in the academic literature; it compounds every other signal.

On unemployment: the rate is 5.2%, which is 1.3pp above the national reference figure of 3.9% for the ACS measurement period. The unemployment component contributes 19.5 points out of a possible 30 (capped at 8%). High unemployment signals a weak labor market where workers have fewer outside options — the classic condition for wage suppression and lower bargaining power. This figure is from BLS LAUS (2026-08-31), a preliminary BLS estimate, subject to revision.

The score formula is editorial — 40/30/30 weights are a deliberate choice, not derived from regression. If you think the weights are wrong, the methodology page explains the rationale. Weight changes require a public ADR (ADR-0013+). The sources are federal, license-free for reuse with attribution.

HOW THIS IS CALCULATED

Formula (ADR-0012, binding):

burnout_score = round(
  40 × clamp₀₁(1 − normalized_wage / cost_norm)   // pay-to-cost gap
+ 30 × clamp₀₁(commute_min / 60)                  // commute
+ 30 × clamp₀₁(unemployment_pct / 8)              // unemployment
)

Where:

  • normalized_wage = $93,986 ÷ $80,610 (national median) = 1.1659
  • cost_norm = 100.268 ÷ 100 = 1.0027
  • pay_term = clamp₀₁(1 − 1.1659 ÷ 1.0027) = 0.0000
  • commute_term = clamp₀₁(27.4 ÷ 60) = 0.4567
  • unemp_term = clamp₀₁(5.2 ÷ 8) = 0.6500

Score = round(40 × 0.0000 + 30 × 0.4567 + 30 × 0.6500) = round(33.20) = 33

Full methodology, weight rationale, and source citations: /methodology#burnout-index. Weight changes are a brand contract — any modification requires ADR-0013+.

What changed since last update

Score moved from 32 to 33 (+1 points). Data sources refresh weekly via CI cron. Score changes reflect BLS LAUS monthly releases (unemployment) and are recomputed every Monday at 14:30 UTC.

Metros that feel like Sacramento

Same index, same three inputs. These metros land nearest Sacramento's 33/100 — which makes them the fair comparison when someone tells you the grass is greener.

Elsewhere in the Pacific

Both ends of the scale, for scale: Riverside carries the most pressure of the 50 metros ranked (39/100), and Cleveland the least (23/100). See the full ranking →

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Raw JSON: /burnout-index/sacramento-ca.json · License: CC BY 4.0 · Cite as: Office Blues Burnout Index, Sacramento-Roseville-Folsom, CA, officeblues.net/burnout-index/sacramento-ca, 2026-10-05