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Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental analysis among Swedish siblings Juan Merlo In collaboration.

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Presentation on theme: "Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental analysis among Swedish siblings Juan Merlo In collaboration."— Presentation transcript:

1 Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental analysis among Swedish siblings Juan Merlo In collaboration with: SV Subramanian, Henrik Ohlsson, Basile Chaix, Paul Lichtenstein, Ichiro Kawachi, Social Epidemiology, Department of Clinical Sciences, Faculty of Medicine, Lund University, Sweden (Juan Merlo, Henrik Ohlsson). Department of Society, Human Development and Health, Harvard School of Public Health, Boston, USA (Ichiro Kawachi, Subramanian SV). Unit for Primary Health Care Research, Region Skåne, Sweden (Juan Merlo, Henrik Ohlsson) Centrum for Economic Demography, Lund University, Sweden (Juan Merlo) Inserm, U707, Paris, France (Basile Chaix) Université Pierre et Marie Curie-Paris6, UMR-S 707, Paris, France (Basile Chaix) Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Paul Lichtenstein)

2 Counterfactual approach to causation Exchangeable?

3 Exchangeable?

4 UNEXPOSEDEXPOSED N=1 TEMPORAL CONFOUNDING Exchangeable?

5 x 1 = x 2 UNEXPOSED EXPOSED TWINS Exchangeable ?

6 EXPOSED UNEXPOSED Identical twins Exchangeable? TEMPORAL CONFOUNDING

7 EXPOSED UNEXPOSED “AVERAGE” causal effects

8 SAMPLING StatisticaL inference X sample x Knowing the distribution  information on the population (confidence interval) +/- random error

9 RANDOMISATION (Instrumental variable) (RCT) X Urval x 2 Random samples +/- random error Urval x 1 X≈ x 1 ≈ x 2 x 1 = x 2 UNEXPOSED EXPOSED Intervention “AVERAGE” causal effects +/- random error Exchangeable?

10 EXPOSED UNEXPOSED OBSERVATION

11 X x 2 +/- random error x 1 X≠ x1≠ x2X≠ x1≠ x2 OBSERVATIONAL EPIDEMIOLOGY TRIES TO SIMULATE “COUNTERFACTUAL” SITUATIONS X≈ x 1 ≈ x 2 Multiple/risk score regression Stratification Restriction Propensity of exposition score matching UNEXPOSED EXPOSED EXPOSED UNEXPOSED Intervention Exchangeable?

12 ISCHEMIC HEART DISEASE INDIVIDUAL FACTORS (common cause) Pathway / independent / confounding effect in the actual world ISCHEMIC HEART DISEASE INDIVIDUAL FACTORS AREA EXPOSED/UNEXPOSED AREA EXPOSED/UNEXPOSED Exchangeable?

13 UNEXPOSED EXPOSED x 1 ≈ x 2 Exchangeable? SIBLINGS 50% genetic Shared early environment better controlling for unknown confounding

14 Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental analysis among Swedish siblings

15 BACKGROUND Previous studies: neighborhood socioeconomic disadvantage  individual risk of ischemic heart disease (IHD) The value of those observations for causal inference is uncertain

16 AIMS To apply a quasi-experimental family- based design to investigated whether a discrepant exposure to neighborhood socioeconomic circumstances among full brothers is associated with the IHD risk. AREA

17 –Swedish Multi-Generational Register –Register of Total Population –Longitudinal Integration Database for Health Insurance and Labor Market Studies The study was approved by the Ethics Committee of the Karolinska Institute (Dnr 2009-939). REGISTERS

18 Swedish population residing in the country by December 31th, 2004 –971,519 men aged 45 to 64 years –403,135 men aged 65 to 80 years INCLUSION AND EXCLUSION CRITERIA:INCLUSION AND EXCLUSION CRITERIA: –Only men (higher incidence of IHD, more definite measures of socioeconomic position than women) –Only Swedish born individuals (identification of familial relations by the Multi-generation register) –Without previous hospitalization for IHD between January 1st 2001 and December 31st 2004. –Only residing in neighborhoods with more than 50 people –Who had continuously resided in the country between December 31th 1992 and December 31th 2004 –Only families with two or more full brothers. POPULATION-1

19 POPULATION-2

20 INDIVIDUAL LEVEL VARIABLES

21 NEIGBOURHOOD LEVEL VARIABLES -1

22 NEIGBOURHOOD LEVEL VARIABLES - 2

23 FAMILY LEVEL VARIABLES - 2

24 STATISTICAL ANALYSES

25 RESULTS - 1

26 RESULTS -2 Low familial mean neighborhood income This observation was in line with previous findings obtained by traditional multilevel analyses and investigating different socioeconomic characteristics of the neighborhood. – 45 to 64 year-old males Age-adjusted OR = 1.05, (95%CI: 1.04 – 1.06) + Individual variables OR = 1.04, (95%CI: 1.03 – 1.04) –65 to 80 year-old males Age-adjusted OR = 1.05, (95%CI: 1.03 – 1.07) + Individual variables OR = 1.04, (95%CI: 1.02 – 1.05) The low familial mean neighborhood income deliberately forced a confounded comparison of unrelated individuals from families that differ in unknown – and thereby difficult to control – shared genetic and environmental factors.

27 RESULTS-3 Intrafamilial-centered neighborhood income (i.e., comparing full brothers with a different contextual exposures), –45 to 64 year-old males Age-adjusted OR = 1.04 (1.03 – 1.05) + Individual variables OR = 1.02 (1.02 – 1.04). –65 to 80 year-old males Age-adjusted OR = 1.01 (0.99 – 1.03) + Individual variables OR = 1.00 (0.98 – 1.02).

28 DISCUSSION-1 We need to consider that in addition to discrepancies in the contextual exposure of interest, –Full brothers still have a 50% difference in genetic background. –They also differ in non-shared environmental circumstances acquired across their life course and these circumstances may be a common cause of both increased IHD risk, and the selection of a neighborhood of residence.

29 DISCUSSION-2 Selection bias, especially in the elderly –Siblings were younger –They had a lower IHD mortality that the overall population –Otherwise, the characteristics of the sibling subpopulation were very similar.

30 DISCUSSION-3 Results very similar using a family stratified conditional Cox regression. Cox regression, however, cannot estimate the association between low familial mean neighborhood income and individual IHD since there is not variation within families in mean neighborhood income.

31 We replicated the association between impaired socioeconomic characteristics in a neighborhood and increased individual IHD risk previously described(Chaix B, 2009)Chaix B, 2009 However, we observed this association only in adult men, not in the elderly, and residual confounding by genetic and non-shared environmental factors may still be present DISCUSSION-4

32 Anders Zorn (1860 – 1920) Joaquin Sorolla y Bastida (1863-1923) Exchangeable?


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