The relationship between headache-attributed disability and lost productivity: 3 Attack frequency is the dominating variable

Table 3 Multiple linear regressions predicting lost productivity (work days and household days) from frequency, duration and intensity of migraine attacks

Sample	N	Regression model	Equation (unstandardized coefficients)	Standardized coefficients			VIF	p
				F	D	I		F	D	I
	HALT questions 1+ 2 (lost work days per 3 months)
Population-based
male	1,615	F (3, 1611) = 94.3 p < 0.001, R² = 0.15	Y = 0.85xF + 0.01xD + 1.30xI – 0.93	0.37	0.03	0.11	<1.04	<0.001	0.17	<0.001
female	2,383	F (3, 2379) = 38.2 p < 0.001, R² = 0.05	Y = 0.34xF + 0.01xD + 0.91xI – 1.05	0.18	0.06	0.10	<1.03	<0.001	0.007	<0.001
Eurolight
male	816	F (3, 812) = 27.8 p < 0.001, R² = 0.09	Y = 0.75xF + 0.02xD +1.32xI – 2.46	0.26	0.06	0.10	<1.05	<0.001	0.06	0.003
female	1,667	F (3, 1663) = 63.0, p < 0.001 R² = 0.10	Y = 0.53xF + 0.01xD + 1.31xI – 2.14	0.26	0.04	0.13	<1.07	<0.001	0.14	<0.001
	HALT questions 3 + 4 (lost household days per 3 months)
Population-based
male	1,197	F (3, 1193) =34.9 p < 0.001, R² = 0.08	Y = 0.67xF + 0.01xD + 1.15xI – 1.77	0.25	0.07	0.10	<1.05	<0.001	0.01	0.001
female	2,732	F (3, 2728) =122.2 p < 0.001, R² = 0.12	Y = 0.89xF + 0.01xD + 1.43xI – 0.98	0.33	0.03	0.10	<1.03	<0.001	0.14	<0.001
Eurolight
male	812	F (3, 808) =52.5 p < 0.001, R² = 0.16	Y = 0.87xF + 0.04xD + 1.31xI – 2.91	0.31	0.16	0.11	<1.05	<0.001	<0.001	0.001
female	1,720	F (3, 1716) =112.2 p < 0.001, R² = 0.16	Y = 0.83xF + 0.02xD + 2.07xI – 3.53	0.32	0.10	0.16	<1.08	<0.001	<0.001	<0.001

F frequency of migraine attacks (continuous, measured in days/month), D duration of migraine attacks (continuous, measured in hours), I intensity of migraine attacks (ordinal: 1=“not bad”; 2=“quite bad”; 3=“very bad], VIF variance inflation factor

ISSN: 1129-2377