Air pollution
CalEnviroScreen tracks urban pollution and social vulnerability
Open access · cc by · source: Europe PMC
California’s cumulative-impact screen captures urban/industrial pollution plus socioeconomic vulnerability, which together track environmentally related disease burden.
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CalEnviroScreen tracks urban pollution and social vulnerability
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First three principal components explain 50% of data variability
For the entire data set, the first three PCs explain 50% of data variability in combination.
First PC explains 23% of variation
The first principal component (PC) (Fig. , horizontal axis), explaining 23% of variation, is positively associated with all variables except for a weak negative association with pesticide use and impaired water bodies.
Key findings
The first three PCs explained 50% of indicator variance. CalEnviroScreen scores correlated strongly with the leading all-variable PC (ρ=0.95) and socioeconomic PC (ρ=0.82), moderately with the urban-pollution PC (ρ=0.59). Socioeconomic indicators explained more disease burden than environmental hazards; diesel PM correlated with PM2.5 (r=0.41) and traffic (r=0.56).
Methodology
Authors ran principal component analyses on CalEnviroScreen 3.0 indicators, mapped environmental versus socioeconomic axes, and compared those components with zip-code hospital disease-burden rates.
Limitations
The design is ecological, not causal, and cannot be read as individual risk. Environmental PCs were only weakly related to hospital rates, partly because health data were zip-code discharges aligned to census tracts.
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