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DATA ANALYTICS, HEALTH OUTCOMES EXTERNSHIP WITH ADVANCING RESEARCH FOR CHILDREN'S ENVIRONMENTAL HEALTH – ASTHMA AIR QUALITY

CALIFORNIA COUNTY-YEARS, 2016–2023

ANASWAR (AJ) JAYAKUMAR  ·  ARCEH HEALTH OUTCOMES EXTERNSHIP

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SUMMARY

  • Counties with dirtier air record higher rates of children's asthma emergency visits. Seven counties record far more visits than their air quality alone predicts. One pattern across all counties, plus a small group that breaks it 
  • 363 county-years · 47 of California's 58 counties · 2016–2023

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FINDING

  • How to read the chart: Each grey dot is one county in one year.
    • The line is what the model predicts at that pollution level. Red dots sit far higher than the usual distance above the line. Blue dots sit far lower than the usual distance above the line
  • The counties that stand out: Labelled counties appear more than once — Fresno four times in eight years
    • Air quality is not monitored for 11 counties, so they could never appear here

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FINDINGS AND LIMITATIONS

  • Findings: counties with dirtier air have higher rates of children's asthma emergency visits
    • 17 county-years sat far above prediction — 16 of the 17 worse, from just 7 counties. Recur across years, so this is not one bad wildfire season
  • Limitations: air quality and year together explain only half of why rates differ between counties
    • Comparing each county against its own past, the pattern nearly disappears.
    • What separates counties are factors such as emergency departments are nearby, housing quality, whether families have a regular doctor

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IMPLICATIONS

  • The decision: where to concentrate childhood asthma outreach next year
    • Start with the seven counties — as a place to investigate, not a place to act
  • What this points toward: asking what is driving the excess visits in those counties
    • Adding county data on poverty, insurance coverage and emergency department capacity to show which explanation holds
  • What this points away from: treating this as evidence that air quality is the cause
    • Acting on air quality would rest on an explanation this analysis does not support

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BACKGROUND/METHODS

  • Why county scale: known pollution–asthma link comes from daily data on individual patients.
    • Programs work in counties and budget years
  • Two public sources: CA Department of Public Health (CDPH), U.S. Environmental Protection Agency (EPA)
    • CDPH – asthma emergency visits by county and age, EPA – monitoring stations averaged to county level
  • What the measures do and don't capture: outcome counts emergency visits, not diagnosed asthma cases.
    • Third of county-years rest on readings from single monitor. Model adjusts for year — in 2020 visits fell while wildfire smoke raised pollution
  • One limitation: 11 of 58 counties have no monitoring data at all, most of them rural