Contextual Analysis: Applying the Statistical Concepts to Real Data

Seminar IIIMODE-PTD ProjectJuly 2007

Patricia O’Campo Ph.D.St. Michael’s Hospital &Univeristy of Toronto

Project Areas Four University – Government health

departments partnerships; 8 study sites total (5 suburban, 3 urban)

Baltimore City, MD Baltimore County, MD Prince Georges County, MD Montgomery County, MD 16 pooled cities, MI Durham County, NC Wake County, NC Philadelphia, PA

Overview How was an index of neighborhood

deprivation developed?

Is the Neighborhood Deprivation Index associated with Preterm Birth in a single site?

Is the Neighborhood Deprivation Index associated with Preterm Birth across multiple sites?

What are some resources available for those wanting to learn more about multilevel modeling?

Neighborhood characteristics

Existing domains in the literature

Poverty/income Racial/ethnic

composition Education Employment Occupation Housing/crowding Residential stability

Limitations:

Use of theory rare in selecting area factors

Inconsistent operationalization of neighborhood domains

Poverty alone is not a good proxy for other neighborhood factors

Data source & Specification of “neighborhood”

Neighborhood=Census tract

Data come from 2000 Census

Census tracts are small (~4000 residents), relatively permanent statistical subdivisions of counties, designed to be fairly homogeneous united with respect to socio-demographic characteristics and living conditions

Construction of neighborhood deprivation index (NDI)

Identified 20 census variables in 7 domains used consistently to approximate neighborhood-level environments for inclusion in deprivation index

One education variable Two employment variables Five housing variables Four occupation variables Five poverty variables One racial composition variable Two residential stability variables

Neighborhood index: Data reduction

Census tract data from the eight study sites were used in principal components analyses (PCA) to create the index

PCA is a data reduction technique that transforms several correlated variables into a smaller set of uncorrelated variables or components

The first component explains as much of the overall variance as possible

Neighborhood index: Data reduction

Across study areas, loadings on first principal component ranged from -0.041 to 0.295, with a mean loading of 0.211

Item loadings (>.25) were used to retain 8 items in the index

Final item loadings were used to weight each variable’s contribution to the summary score for each census tract

The index was standardized to have a mean of 0 and a standard deviation of 1.

Neighborhood deprivation index

The neighborhood deprivation index accounted for 67% of the total variance

Consistency of loading for each item across sites suggests that variables function similarly across geography, despite heterogeneity in demographics and economic status

Principal Components Analysis

8 variables were retained for the neighborhood deprivation

% males in managerial or professional occup % crowded housing % HH in poverty % female headed HH % HH on public assistance % HH earnings <$30k % < HS educ % unemployed

Socio-demographic variability across geographic areas

0

20

40

60

80

% < 30K % NH White

Baltimore City, MD Baltimore County, MD

Montgomery County, MD Prince Georges County, MD

16 Cities, MI Durham County, NC

Wake County, NC Philadelphia, PA

Distribution of deprivation scores across eight study sites

Individual-level Data from Vital Records (1999-2001)

Individual-level variables Categories

Preterm birth <=37 weeks (preterm)*>=38 weeks

Maternal Age < 2020-24 25-29 30-3435+ years of age

Maternal Race Non-Hispanic BlackNon-Hispanic White

Maternal Education < 20 years & < High school > 20 years & < High school High school or equiv > High school

*preterm infants had to weigh less than 3888 grams

Baltimore City: Preterm Birth %

9.13

15.97

0

2

4

6

8

10

12

14

16

18

NH White (n=5707)

NH Black (n=18038)

Baltimore City Demographics: Age

0

5

10

15

20

25

30

35

<20 20-24 25-29 30-34 35+

NH White (n=5707)NH Black (n=18038)

Baltimore City Demographics: Education

0

10

20

30

40

50

60

<20 years & < HS

>= 20 & < HS

HS or equiv

> HS

NH White (n=5707)

NH Black (n=18038)

Neighborhood Deprivation Index (NDI)

NH White (174 Census tracts)

Median -0.267 25% -0.629 75% 0.202

Min -1.34 Max 2.59

NH Black (191 Census tracts)

Median 0.742 25% 0.082 75% 1.191

Min -1.27 Max 2.59

Methods: Data Analysis

Race-stratified models

1. Multi-level (random intercept) logistic regression models with NDI as only predictor

2. Multi-level (random intercept) logistic regression models with NDI plus the potential confounders maternal age and education

Statistical methods were presented in detail in the previous DataSpeak session on “Methods for Understanding and Interpreting Multilevel Analysis” (June 07)

Neighborhood deprivation odds ratios comparing the 1st to the 5th quintile

Odds ratiosX Data

1 1.5 2 2.5 3 3.51 1.5 2 2.5 3 3.5

Unadjusted modelsAdjusted models

Non-Hispanic Black women

Non-Hispanic White women 2.79

1.87

1.37

1.23

Percent preterm among non-Hispanic White and non-Hispanic Black women by site

02468

1012141618

White Black

Baltimore City, MD Baltimore County, MDMontgomery County, MD Prince Georges County, MD16 Cities, MI Durham County, NCWake County, NC Philadelphia, PA

%

Percent age 30-34 by race and site

0

10

20

30

40

50

White Black

Baltimore City, MD Baltimore County, MD Montgomery County, MD

Prince Georges County, MD 16 Cities, MI Durham County, NC

Wake County, NC Philadelphia, PA

%

Percent with more than high school or equivalent education by race and site

0

20

40

60

80

100

White Black Baltimore City, MD Baltimore County, MDMontgomery County, MD Prince Georges County, MD16 Cities, MI Durham County, NCWake County, NC Philadelphia, PA

%

Neighborhood Deprivation Index Values by Site

Neighborhood deprivation odds ratios for the outcome preterm birth

White-unadj White-adj Black-unadj Black-adj

Philadelphia 1.68*

(1.45, 1.92)

1.52*

(1.28, 1.75)

1.40* (1.27, 1.53)

1.26* (1.13, 1.39)

Wake 1.82*

(1.48, 2.16)

1.52*

(1.15, 1.88)

1.33*

(1.02, 1.64)

1.20 (0.89, 1.51)

Durham 2.18* (1.69, 2.68)

1.68*(1.14, 2.23)

1.48* (1.24, 1.71)

1.20 (0.97, 1.43)

16 Cities 1.64* (1.51, 1.77)

1.48* (1.32, 1.63)

1.14*(1.06, 1.22)

1.05

(0.95, 1.16)

PG Cnty 2.07* (1.29, 2.85)

1.68 (0.90, 2.46)

1.20 (0.97, 1.43)

1.14

(0.90, 1.37)

Montgomery Cnty

1.82*

(1.38, 2.26)

1.56*

(1.09, 2.02)

0.86

(0.36, 1.35)

0.88 (0.38, 1.37)

Baltimore County,

3.14* (2.72, 3.56)

2.24* (1.77, 2.71)

1.37

(0.74, 1.99)

1.40 (0.78, 2.03)

Baltimore City, MD

2.79*

(2.30, 3.08)

1.87* (1.42, 2.31)

1.37*

(1.24, 1.50)

1.23* (1.08, 1.39)

Adjusted models include maternal age and maternal education

Neighborhood-level deprivation and preterm birth: similarity across sites

The Cochran’s Q statistic for homogeneity was calculated across sites to test the null hypothesis that the neighborhood deprivation betas are similar across sites

Cochran’s Q was not significant for both non-Hispanic White women (p=0.83) and non-Hispanic Black women (p=0.50).

Neighborhood-level deprivation and preterm birth: similarity across sites

Because the hypothesis of homogeneity was not rejected, we calculated a summary statistic representing the effect of neighborhood deprivation and preterm birth across sites.

The summary effect for non-Hispanic White women was 1.57 (95% CI: 1.41 to 1.74) and for non-Hispanic Black women it was 1.15 (95% CI: 1.08 to 1.23).

Are the associations similar across geographic area?

White Non-Hispanic Women Ages 20+

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-10.0 -5.0 0.0 5.0 10.0 15.0

Deprivation Score

Est

imat

ed L

og

-Od

ds

Black Non-Hispanic Women Ages 20+

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-10.0 -5.0 0.0 5.0 10.0 15.0

Deprivation Score

Estimated Log-Odds of Preterm Delivery by Deprivation Score and By Site

Baltimore County Baltimore City Montgomery Co

PG County Wake Co Michigan Cities

Philadelphia Durham Co Combined

(adjusted for maternal age and education)

White Non-Hispanic Women Ages 20+

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-10.0 -5.0 0.0 5.0 10.0 15.0

Deprivation Score

Est

imat

ed L

og

-Od

ds

Black Non-Hispanic Women Ages 20+

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-10.0 -5.0 0.0 5.0 10.0 15.0

Deprivation Score

Estimated Log-Odds of Preterm Delivery by Deprivation Score and By Site

Baltimore County Baltimore City Montgomery Co

PG County Wake Co Michigan Cities

Philadelphia Durham Co Combined

(adjusted for maternal age and education)

Summary of deprivation and preterm birth in multiple sites

Despite the diversity of geographic settings, there was homogeneity in the effect of neighborhood deprivation on preterm birth across sites for both non-Hispanic Blacks and non-Hispanic Whites.

The weaker effect for non-Hispanic Blacks versus Whites was explored but could not be explained with the data we had.

Additional project analyses

Examine separate components of the deprivation index

Examine other exposures such as smoking and maternal age

Examine other outcomes such as small for gestational age

Selected examples

Extensive resource listing on the Dataspeak website

Books Luke DA. Multilevel Modeling: Quantitative

Applications in the Social Sciences. July 2004 Sage Publications Inc.

Raudenbush, S. W., and A. S. Bryk.. Heirarchical linear models: Applications and data analysis methods. 2002 Thousand Oaks, CA: Sage.

Selected examples

Websites for General Information & software

Centre for Multilevel Modeling, University of Bristol: http://www.mlwin.com/

For SAS users: http://gseweb.harvard.edu/~faculty/singer/

Selected examples

Websites for General Information & software (cont’d)

Muthen and Muthen, MPLUS http://www.statmodel.com/

For SPSS users: http://www.unc.edu/~painter/SPSSMixed/SPSSMixedModels.PDF

Contact Information

Patricia O’Campo, PhDSt. Michael’s Hospital & University of Toronto

E-mail: pat.ocampo@utoronto.ca