Table 1.

Generalised linear model (Poisson distribution) for any risk-reduction behaviour before events, N=556, Optimise participants, Victoria, Australia, February 2022.

Variable	Total N=556 n (%)	Any risk reduction n=339 (61%)	No risk reduction n=217 (39%)	Unadjusted relative risk N=556	Unadjusted p-value	Adjusted relative risk N=556	Adjusted p-value
Age (years)
18–34	167 (30)	116 (69)	51 (31)	1.19 (1.02, 1.39)	0.0263	1.20 (1.01, 1.41)	0.0348
35–54	190 (34)	107 (56)	83 (44)	0.97 (0.81, 1.15)	0.6939	0.97 (0.81, 1.15)	0.7109
55+	199 (36)	116 (58)	83 (42)	ref	-	ref	-
Gender
Women	419 (75)	265 (63)	154 (37)	1.17 (0.99, 1.39)	0.0703	1.16 (0.97, 1.38)	0.1006
Men	137 (25)	74 (54)	63 (46)	ref	-	ref	-
Region in Victoria
Regional Victoria	101 (18)	49 (49)	52 (51)	0.76 (0.62, 0.94)	0.0117	0.78 (0.62, 0.97)	0.0233
Metropolitan Melbourne	450 (82)	287 (64)	163 (36)	ref	-	ref	-
Country of birth
Overseas	188 (34)	113 (60)	75 (40)	0.98 (0.85, 1.13)	0.7663	0.99 (0.85, 1.14)	0.8531
Australia	368 (66)	226 (61)	142 (39)	ref	-	ref	-
Healthcare worker
Yes	128 (23)	79 (62)	49 (38)	1.02 (0.87, 1.19)	0.8423	1.00 (0.85, 1.17)	0.9843
No	428 (77)	260 (61)	168 (39)	ref	-	ref	-
Chronic health condition
Yes	210 (38)	136 (65)	74 (35)	1.10 (0.97, 1.26)	0.1465	1.15 (1.00, 1.33)	0.0482
No	346 (62)	203 (59)	143 (41)	ref	-	ref	-
Recruitment method
Seed	305 (55)	186 (61)	119 (39)	1.00 (0.88, 1.14)	0.9947	0.98 (0.85, 1.12)	0.7437
Other	251 (45)	153 (61)	98 (39)	ref		ref
Months in Optimise study (median, (IQR))	11 (6, 14)	10 (6, 14)	11 (6, 14)	1.00 (0.99, 1.01)	0.9623	1.00 (0.98, 1.01)	0.8138

Covariates: Gender, country of birth, time in study, recruitment method.

Months in Optimise study: Number of months since recruitment into the Optimise Study.

Recruitment method: Whether participants were recruit via responding to advertising (“seed”) or referral from their social networks (“other”).

∗Bolded p-values represent <0.05.

Ref—reference category.