Ethnic- and gender-specific differences in the prevalence of HIV among patients in opioid maintenance treatment—a case register analysis

Table 3 Risk ratio (RR) of predictors of HIV-positive status according to GEE analysis

Independent variables	Complete dataset			Imputed dataset
Independent variables	RR	CI 95%-	CI 95%+	RR	CI 95%-	CI 95%+
Calendar year	0.76	0.70	0.82	0.78	0.72	0.83
Year of birth	0.96	0.94	0.98	0.96	0.94	0.97
Year of birth^a	0.95	0.93	0.97	0.96	0.94	0.98
Year of birth^b	1.02	1.01	1.03	1.01	1.00	1.02
Age	1.04	1.03	1.06	1.04	1.02	1.05
Age^c	0.95	0.94	0.96	0.96	0.95	0.97
Age^d	1.01	1.01	1.02	1.01	1.01	1.02
Female, non-Swiss, non-injector	0.17	0.07	0.45	0.24	0.08	0.69
Female, non-Swiss, ever injector	1.64	1.21	2.24	1.58	1.18	2.12
Female, Swiss, non-injector	0.26	0.18	0.38	0.25	0.17	0.38
Female, Swiss, ever injector	1.20	1.05	1.38	1.18	1.04	1.34
Male, non-Swiss, non-injector	0.22	0.12	0.39	0.24	0.14	0.40
Male, non-Swiss, ever injector	0.93	0.75	1.15	0.92	0.74	1.13
Male, Swiss, non-injector	0.21	0.16	0.28	0.21	0.16	0.28

The time variables were rescaled to fit the GEE model as follows: calendar year = logarithm of year - 1990, year of birth = year - 1960, age = age - 30. ^aYear of birth = Year of birth × Year of birth / 10. ^bYear of birth = Year of birth × Year of birth × Year of birth / 100. ^cAge = Age × Age / 10, ^dAge = Age × Age × Age / 100. The group ‘Male, Swiss, ever injector’ was reference category and is therefore omitted from the independent variable list.

ISSN: 1477-7517