Table 2.

Unadjusted Baseline Foodborne Illness Rates and Adjusted Difference-in-Differences Models^a

Analysis	Unadjusted baseline rate (SD)	Adjusted difference-in-differences
		Coefficient	SE	p-value	Policy effect (% change from baseline)
Aggregated foodborne illness cases/100,000
All jurisdictions	3.660 (2.628)	−0.787	0.737	0.286
Laws that are more supportive	4.486 (3.098)	−1.002	0.356	0.005	−22.3
Laws that are less supportiveb	2.570 (0.895)	0.984	0.705	0.162
Salmonellosis cases/100,000
All jurisdictions	1.100 (0.529)	0.059	0.084	0.479
Laws that are more supportive	1.083 (0.529)	0.067	0.117	0.564
Laws that are less supportiveb	1.121 (0.529)	0.405	0.416	0.331
Campylobacteriosis cases/100,000
All jurisdictions	1.637 (1.22)	−0.266	0.557	0.633
Laws that are more supportive	1.938 (1.42)	−0.671	0.213	0.002	−34.6
Laws that are less supportiveb	1.142 (0.508)	0.930	0.366	0.011	81.4
Shigellosis cases/100,000
All jurisdictions	0.503 (0.828)	−0.221	0.162	0.172
Laws that are more supportive	0.713 (1.011)	−0.309	0.250	0.217
Laws that are less supportiveb	0.205 (0.240)	−0.515	0.504	0.307

Notes: Boldface indicates statistical significance (p<0.05).

^aAdjusted models use linear regression with random effects (adjusting for correlation of SEs using an AR(1) matrix). A negative difference-in-difference indicates that the PSL is associated with a decrease in foodborne illness rates. Covariates are the difference-in-differences (shown), which is the interaction between being in a jurisdiction with a PSL law and after the law is in effect; the main effects of the difference-in-differences; percent population by age; percent food establishments by number of employees; month; and year. San Francisco and Seattle’s laws are more supportive of employees taking paid sick leave, and Washington, DC and Connecticut’s laws are less supportive (see Methods).

^bThis excludes matched Pair 3, as the comparison jurisdiction for that pair only provided annual foodborne illness cases.

PSL, paid sick leave