Multilevel survival analysis of health inequalities in life expectancy.
BACKGROUND
The health status of individuals is determined by multiple factors operating at both micro and macro levels and the interactive effects of them. Measures of health inequalities should reflect such determinants explicitly through sources of levels and combining mean differences at group levels and the variation of individuals, for the benefits of decision making and intervention planning. Measures derived recently from marginal models such as beta-binomial and frailty survival, address this issue to some extent, but are limited in handling data with complex structures. Beta-binomial models were also limited in relation to measuring inequalities of life expectancy (LE) directly.


METHODS
We propose a multilevel survival model analysis that estimates life expectancy based on survival time with censored data. The model explicitly disentangles total health inequalities in terms of variance components of life expectancy compared to the source of variation at the level of individuals in households and parishes and so on, and estimates group differences of inequalities at the same time. Adjusted distributions of life expectancy by gender and by household socioeconomic level are calculated. Relative and absolute health inequality indices are derived based on model estimates. The model based analysis is illustrated on a large Swedish cohort of 22,680 men and 26,474 women aged 6569 in 1970 and followed up for 30 years. Model based inequality measures are compared to the conventional calculations.


RESULTS
Much variation of life expectancy is observed at individual and household levels. Contextual effects at Parish and Municipality level are negligible. Women have longer life expectancy than men and lower inequality. There is marked inequality by the level of household socioeconomic status measured by the median life expectancy in each socio-economic group and the variation in life expectancy within each group.


CONCLUSIONS
Multilevel survival models are flexible and efficient tools in studying health inequalities of life expectancy or survival time data with a geographic structure of more than 2 levels. They are complementary to conventional methods and override some limitations of marginal models. Future research on determinants of health inequalities in the LE of the specific cohort on the household and individual factors could reveal some important causes over the marked household level inequalities.
Yang
Min
M
Centre for Psychiatry, Barts and The London, Queen Mary's School of Medicine and Dentistry, William Harvey House, 61 Bartholomew Close, London EC1A 7BE, UK. m.yang@qmul.ac.uk.
Eldridge
Sandra
S
Merlo
Juan
J
J Epidemiol Community Health. 2006 Jan;60(1):31-6
16361452
BMC Public Health. 2006 Mar 28;6:79
16569222
Am J Epidemiol. 1994 Apr 15;139(8):747-60
8178788
Eur J Epidemiol. 2005;20(8):737; author reply 738
16151890
Med Care. 2005 Nov;43(11):1092-100
16224302
Bull World Health Organ. 1999;77(7):537-43
10444876
Bull World Health Organ. 2000;78(1):30-41
10686731
Health Policy Educ. 1982 Mar;2(3-4):251-67
10256648
Int J Equity Health. 2006 Jul 11;5:9
16831231
Bull World Health Organ. 2000;78(1):42-54
10686732
Demography. 2002 Feb;39(1):43-63
11852839
Epidemiol Rev. 2004;26:78-91
15234949
J Epidemiol Community Health. 2003 Aug;57(8):550-2
12883048
Stat Med. 2000 Dec 30;19(24):3417-32
11122505
Int J Equity Health. 2002 May 27;1(1):2
12234389
Soc Sci Med. 1997 Mar;44(6):757-71
9080560
Int J Equity Health. 2002 Aug 12;1(1):3
12379153