Bias in estimates of alcohol use among older people: selection effects due to design, health, and cohort replacement

Table 3 Sex-adjusted odds ratios of being an alcohol consumer rather than a non-consumer depending on survey design, health, and birth cohort

		Bivariate		Within categories		Model 4		Model 5
		OR	p-value	OR	p-value	OR	p-value	OR	p-value
Survey design				Model 1
Interview succession (linear)		0.95	0.011	0.97	0.142	0.97	0.169	0.98	0.330
Proxy		0.45	<0.001	0.49	<0.001	0.94	0.746	0.99	0.977
Telephone		0.59	<0.001	0.89	0.493	0.82	0.209	0.73	0.054
Health				Model 2
Living in an institution (Women)		0.55	0.001	0.98	0.906	1.06	0.801	1.11	0.624
Living in an institution (Men)		0.20	<0.001	0.39	<0.001	0.42	0.002	0.43	0.002
ADL limitation		0.40	<0.001	0.58	<0.001	0.60	<0.001	0.65	0.005
Mobility problem		0.45	<0.001	0.60	<0.001	0.61	<0.001	0.59	<0.001
Birth cohort				Model 3
Period	1992	1.00	ref	1.00	ref			1.00	ref
	2002	1.21	0.152	0.72	0.080			1.06	0.788
	2011	1.61	<0.001	0.59	0.039			1.07	0.795
Birth cohort (linear)		1.44	<0.001	1.78	<0.001			1.31	0.026
Age (linear)		0.58	<0.001	^a

Significant estimates (p<0.05) are in bold ^aAs age, cohort and period cannot be analysed in the same model, and because the period change was not related to changed age distribution over the years, age was excluded in the full model

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