Minnesota Lao community dashboard
Live federal indicators from the U.S. Census Bureau ACS 5-year estimates (2022). Community-partnered indicators below combine ACS with local research collected with Minnesota Lao community partners.
Population
Economic
Education
Housing & language
Community-partnered indicators
Sources: MN Department of Health BRFSS 2024, Community Health Survey 2025.
Key Insights
The most important findings from disaggregated analysis, curated by Dr. Phouthakannha Nantharath. Each insight pairs a data visualization with context to explain why the finding matters for policy and practice.
The "Asian" category conceals a 4.8x disparity in gambling addiction
When Lao data is separated from the aggregate "Asian" category, the gambling addiction rate is 24.0% — nearly five times the 5.0% state average. The aggregated "Asian" rate of 8.0% makes it appear Southeast Asian communities have only modestly elevated risk.
Source: MDH BRFSS 2024, Community Health Survey 2025
Linguistic isolation affects 1 in 3 Lao households — 8x the state rate
34.8% of Lao households are linguistically isolated, meaning no one over 14 speaks English "very well." This creates cascading barriers to healthcare access, employment, and civic participation that compound across domains.
Source: Census ACS 5-year estimates 2020-2024
45% of Lao elders received no formal schooling — a 22x disparity
Nearly half of Lao elders (65+) report zero years of formal education, reflecting the disruption of the Secret War and refugee experience. This is 22 times the state rate of 2.0% and is invisible in aggregated data.
Source: Census ACS 2020-2024, Community Survey 2025
ML models predict rising elder isolation risk in 3 Minneapolis neighborhoods
The Elder Isolation Index (86.2% accuracy, AUC-ROC 0.89) shows Minneapolis North, Brooklyn Center, and St. Paul East at risk scores exceeding the 65-point community threshold. Early warning triggered for proactive temple-based intervention.
Source: Lao People Data & Research ML Pipeline, 2025
Interactive Data Explorer
Select a metric to explore trends, compare populations, and examine statistical significance. Switch between chart and table views to interact with the data.
Gambling Addiction Rate
Time series: Lao community vs. Minnesota state average (2019–2025)
24%
[21.2, 26.8]
d = 1.42 (large)
p = 0.001 ***
Source: Census ACS 2020-2024, MDH BRFSS, Community Survey 2025
Lao People Data & Research
Community Disparity Profile
Composite scores across six dimensions (0–100 scale, higher = better)
Source: Composite index from Census ACS, BRFSS, Community Survey 2025
Lao People Data & Research
Disaggregation Reveals Hidden Disparities
The same data, disaggregated: rates when Lao data is separated from 'Asian'
Source: Census ACS 2020-2024, MDH BRFSS, Community Survey 2025
Lao People Data & Research
Methodology
Data sources. This dashboard integrates data from 6 primary sources: U.S. Census American Community Survey (ACS) 5-year estimates (2020–2024), Minnesota Department of Health BRFSS, Bureau of Labor Statistics (BLS), Federal Reserve Economic Data (FRED), Bureau of Economic Analysis (BEA), and the Lao Community Health Survey (n=412, 2025).
Statistical methods. All confidence intervals are computed at the 95% level using Wilson score intervals for proportions. Effect sizes are reported as Cohen's d for continuous measures and odds ratios for binary outcomes. Significance is assessed using two-tailed tests with Bonferroni correction for multiple comparisons across domains.
Machine learning. Four predictive models (gambling risk, dropout prediction, mental health screening, elder isolation) use gradient-boosted trees (XGBoost) with 5-fold stratified cross-validation. All models include SHAP feature importance, fairness auditing (four-fifths rule, disparate impact ratio), and standardized model cards per Mitchell et al. (2019).
Limitations. Community survey data is convenience-sampled through temple networks and community organizations, which may under-represent highly isolated individuals. Census ACS estimates for small populations carry larger margins of error. ML predictions are intended to support — not replace — community judgment and culturally-informed decision-making.
Dr. Phouthakannha Nantharath · Professor of Economics and a Research & Data Scientist · Lao People Data & Research
Explore by Domain
Health Disparities
Gambling addiction, healthcare access, mental health, chronic disease, substance use
Economic Security
Income, employment, poverty, entrepreneurship, financial security
Education
Attainment, ELL, dropout risk, elder educational exclusion, literacy
Housing & Social
Housing stability, elder isolation, civic engagement, social networks