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Abstract	48-51	Individuals who lived in redlined areas had an interaction odds ratio for mortality of 1.0093 1.0104 (95% confidence interval [CI]: 1.0084 1.0095, 1.0101 1.0114) for each 10 µg m-3 increase in same-day ambient PM2.5 compared to individuals who did not live in redlined areas. For extreme heat, the interaction odds ratio was 1.0218 1.0146 (95% CI 1.0031 1.0039, 1.0408 1.0457).
Methods	159-161	To derive measures of extreme heat, we first calculated various percentiles of minimum temperature in each block group in each year. For our main analysis, we considered the 95 th 90 th percentile.
Methods	163-165	In other words, if the minimum temperature on a certain day met or exceeded the 95 th 90 th percentile of minimum temperature in that block group in that year, then that day was marked as an extreme heat day.
Results	229-237	We obtained 11,115,380 11,076,020 mortality records from the twelve thirteen state departments of public health. From these records, we sequentially excluded 466,874 453,754 deaths involving external causes; 139,908 133,348 deaths involving individuals younger than 18 years old; 196,558 deaths with geocodes that were missing or coarser than block group-level; 331 deaths involving individuals whose home locations were outside of the state that reported their death; 1,392,423 1,372,743 deaths before January 5th, 2001 or after December 31st, 2016 and 537 deaths whose home block groups had a population of zero according to the preceding Decennial Census (for which 4-day moving averages of population-weighted PM2.5 could not be calculated); and 34,016 deaths with lag days from 0 to 4 that included December 31st on leap years (for which Daymet predictions are not available; Figure 3)
Results	272-278	We found a significant interaction with exposure to any extreme heat (interaction odds ratio 1.0218 1.0246; 95% CI 1.0031 1.0039, 1.0408 1.0457) while we did not observe significant interactions for singleton heat events or when looking at length-specific exposures. In absolute terms, this amounts to a 2.157% 2.434% (95% CI 0.307% 0.386%, 4.036% 4.521%) increase in the daily risk of death death from non-external causes by exposure to any extreme heat in historically-redlined neighborhoods compared to other neighborhoods. The highest overall effects were observed for exposure to any extreme heat, followed by 3, 1 2, and 2 1 consecutive days of extreme heat, respectively.
Results	283-287	We found a significant interaction with same-day ambient PM2.5 (interaction odds ratio for each 10 µg/m-3 increase: 1.0093 1.0104; 95% CI 1.0084 1.0095, 1.0101 1.0114) while we did not observe interactions for different moving averages of ambient PM2.5. In absolute terms, this amounts to a 0.930% 1.029% (95% CI 0.831% 0.940%, 1.000% 1.128%) increase in the daily risk of death from non-external causes for each 10 µg/m-3 increase in ambient PM2.5 in historically-redlined neighborhoods compared to other neighborhoods.
Results	295-296	However, for PM2.5, we did observe that the interaction with same-day ambient PM2.5 was not significant for a population cutoffs of 50% and 99%.
Results	302-305	We also observed that the 85th and 95th percentile cutoffs of minimum temperature had higher interactions than the 90th percentile cutoff on earlier days, with the 85th percentile being the highest for any exposure or the 1 st day of extreme heat and the 99th percentile being the highest for any exposure or the 1st or 2 nd days of extreme heat.