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Modeling Respiratory Disease Modeling Respiratory Disease Clusters in Central Appalachia Clusters in Central Appalachia

Timothy S. HareTimothy S. HareIRAPP, MSUIRAPP, MSU414C Bert Combs Building414C Bert Combs BuildingTel. 606-783-9436Tel. 606-783-9436E-mail: E-mail: t.hare@morehead-st.edu

Matt Laurin - Matt Laurin - Morehead State UniversityMorehead State UniversityE-mail: E-mail: mrlaur01@morehead-st.edu Aaron Pierce - Aaron Pierce - Morehead State UniversityE-mail: Morehead State UniversityE-mail: anpierce@moreheadstate.eanpierce@moreheadstate.edu

Study Area

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GeorgiaSouth Carolina

AlabamaMississippi

Missouri

Illinois

Indiana

OhioOhio

Virg

inia

Virg

inia

North C

arolina

North C

arolina

PennsylvaniaPennsylvania

Raleigh

Columbus

Baltimore

Charlotte

Lexington

Nashville

WashingtonCincinnati

Louisville

Virginia Beach

Asheville

Knoxville

CharlestonHuntington

Pittsburgh

Chattanooga

Johnson CityWinston-Salem

³0 10050Miles

Appalachian Cities

!( Over 50,000

Non-Appalachian Cities

!( Over 250,000

Northern Appalachia

Central Appalachia

Southern Appalachia

Mortality Rates - All Causes

LISA Cluster Map – Mortality - All Causes – Moran’s I 0.520***

Age-Adjusted Mortality for All Causes

55

LISA Cluster Map of Mortality for All Causes

66

000

GeorgiaSouth Carolina

AlabamaMississippi

Missouri

Illinois

Indiana

OhioOhio

Virg

inia

Virg

inia

North C

arolina

North C

arolina

PennsylvaniaPennsylvania

³0 10050Miles

Male Mortality LISA Cluster MapNot Significant

High - High

High - Low

Low - High

Low - Low

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Research Questions

Are mortality rates due to major respiratory conditions distributed evenly across central Appalachia?

What factors are associated with elevated mortality rates due to major respiratory conditions?

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Key Tasks

Identify meaningful clusters of high mortality rates.

Use techniques of ESDA to characterize associated factors.

Examine the effects of factors on spatial clusters of high mortality rates.

88

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Data & Methods

Data SeerStat Health Care Services

– AHA Annual Survey

– Additional surveys & questionnaires

– Area Resource File

Socioeconomic Data - Census

Travel – Kentucky State Transportation Model (KYSTM)

Methods Spatial Aggregation County-level (598) Mortality Rates Temporal Aggregation Direct Standardization Age-Adjusted Rates Year 2000 U.S. Standard

Population Travel time calculations

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Analysis Techniques

Map visualization Univariate & Bivariate Moran’s I Local Indicators of Spatial

Autocorrelation Spatial Regression (lag & error

models) Geographically Weighted

Regression

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Research Question 1

A. Are mortality rates due to lung cancer distributed evenly across central Appalachia?

B. Are Mortality rates due to COPD distributed evenly across central Appalachia?

Age-Adjusted Mortality for Lung Cancer

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LISA Cluster Map of Lung Cancer Mortality

1313

Age-Adjusted Mortality for Lung Cancer by Sex

1414

LISA Cluster Map of Lung Cancer Mortality by Sex

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Age-Adjusted Mortality for COPD

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LISA Cluster Map of COPD Mortality

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Age-Adjusted Mortality for COPD by Sex

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LISA Cluster Map of COPD Mortality by Sex

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Female vs. Male Lung Cancer Mortality Multivariate LISA Cluster Map Moran’s I = 0.3700 p < 0.001

2020

Female vs. Male COPD Mortality Multivariate LISA Cluster Map Moran’s I = 0.3368 p < 0.001

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Spatial Autocorrelation: Moran’s I

2222

Univariate Moran's I P-Value

Total Mortality Lung Cancer 0.53673 ***Female Mortality Lung Cancer

0.35862 ***

Male Mortality Lung Cancer 0.50032 ***Total Mortality COPD 0.52669 ***Female Mortality COPD 0.38812 ***Male Mortality COPD 0.45586 ***

Note: *** P < 0.001, ** P < 0.01, * P < 0.05

Multivariate: Female vs. Male

Moran's I P-Value

Lung Cancer 0.3700 ***COPD 0.3368 ***

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Research Question 1

A. Are mortality rates due to lung cancer distributed evenly across central Appalachia? - No

B. Are Mortality rates due to COPD distributed evenly across central Appalachia? - No

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Research Questions 2

A. What factors are associated with elevated mortality rates due to Lung Cancer?

B. What factors are associated with elevated mortality rates due to Lung Cancer?

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Population Density Population Density (people/mile(people/mile22))

Median Household Income

LISA Cluster Map – Median Income – Moran’s I 0.681***

% with High School Education

LISA Cluster Map – High School – Moran’s I 0.582***

LISA Cluster Map – College – Moran’s I 0.532***

Total Household Health Care Expenditures

LISA Cluster Map - Household Health Care – Moran’s I 0.579***

Health Care Spending (% of Total Household Spending)

000

Illinois

³0 10050Miles

Health Care Spending7.06% - 7.37%6.72% - 7.05%6.31% - 6.71%5.83% - 6.3%5.09% - 5.82%

Health Insurance Spending

LISA Cluster Map - Insurance – Moran’s I 0.589***

Health Insurance Spending (% of Total Expenditures)

000

Illinois

³0 10050Miles

% Health Insurance Spending3.6% - 3.8%3.4% - 3.5%3.1% - 3.3%2.9% - 3%2.6% - 2.8%

Total Household Education Spending

LISA Cluster Map – Total Education – Moran’s I 0.680***

Persistent Pattern: Rx Drug Spending

LISA Cluster Map - Rx Drug Spending – Moran’s I 0.419***

Bivariate Moran’s I vs. Total Mortality for Lung Cancer

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Variables Moran's I P-Value

Median Household Income -0.3550***Unemployment Rate 0.3355***Mining as Percent of Total Employment 0.3027***Percent With High School Diploma or Equivalent

-0.3833***

Health Care as Percent of Total Household Spending

0.2529***

Health Insurance as Percent of Total Household Spending

0.2335***

Hospital as Percent of Total Household Spending

0.3242***

Non-Prescription Drugs as Percent of Total Household Spending

0.3124***

Prescription Drugs as Percent of Total Household Spending

0.3110***

Education as Percent of Total Household Spending

-0.3324***

Note: *** P < 0.001, ** P < 0.01, * P < 0.05

Bivariate Moran’s I vs. Total Mortality for COPD

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Variables Moran's I P-Value

Median Household Income -0.3920***Unemployment Rate 0.3217***Mining as Percent of Total Employment 0.3027***Percent With High School Diploma or Equivalent

-0.3432***

Health Care as Percent of Total Household Spending

0.2940***

Health Insurance as Percent of Total Household Spending

0.2739***

Hospital as Percent of Total Household Spending

0.3434***

Non-Prescription Drugs as Percent of Total Household Spending

0.3506***

Prescription Drugs as Percent of Total Household Spending

0.3507***

Education as Percent of Total Household Spending

-0.3506***

Note: *** P < 0.001, ** P < 0.01, * P < 0.05

OLS Regression Model 1

4343

Variable Coefficient Std.Error t-Statistic ProbabilityCONSTANT 75.963630 9.848863 7.712934***Unemployment Rate 1.007752 0.196690 5.123532 ***% Employed in Mining 0.649820 0.143670 4.522988 ***% High School Graduates -0.509364 0.072799 -6.996775 ***% Household Health Spending -6.462413 2.344200 -2.756767 **% Household Hospital Spending 256.6613 71.9874 3.565364 ***

Note: *** P < 0.001, ** P < 0.01, * P < 0.05

Adjusted R-squared:    0.328321Akaike info criterion:     4677.76

Spatial Regression Model 1 (Lag)

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Variable Coefficient Std.Error z-value ProbabilityLag of Total Lung Cancer Mortality

0.5101864 0.04091244 12.4702 ***

CONSTANT 39.61875 8.884213 4.459455 ***Unemployment Rate 0.6780908 0.1712365 3.959966 ***% Employed in Mining 0.332557 0.1255439 2.648929 **

% High School Graduates2.02509 0.0645824 -

4.601721 ***

% Household Health Spending-4.60215 2.02509 -

2.272565 *

% Household Hospital Spending

162.1175 62.41695 2.597331 **Note: *** P < 0.001, ** P < 0.01, * P < 0.05

R-squared:    0.49796    Akaike info criterion:     4575.46

Comparison of OLS & Spatial Lag Regression

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VariableOLS

CoefficientOLS

ProbabilitySpatial Lag Coefficient

Spatial Lag Probability

Lag of Total Lung Cancer Mortality na na

0.51019 ***

CONSTANT 75.963630*** 39.61875***Unemployment Rate 1.007752 *** 0.67809 ***% Employed in Mining 0.649820 *** 0.33256**% High School Graduates -0.509364 ** -0.29719***% Household Health Spending -6.462413*** -4.60215*

% Household Hospital Spending 256.6613 * 162.1175

0 **

Note: *** P < 0.001, ** P < 0.01, * P < 0.05

R-squared:    0.49796    Akaike info criterion:     4575.46

Adjusted R-squared:    0.328321Akaike info criterion:     4677.76

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Results

1. Mortality rates due to major respiratory conditions are not distributed evenly across central Appalachia.

2. All examined factors are associated with elevated mortality rates due to major respiratory conditions.

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Future Investigations

Further explore differences by sex Deal with multicollinearity

– Create composite deprivation index Examine service utilization patterns Examine

– Tobacco use– Air quality

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Questions?!Questions?!

4949

Institute for Regional Analysis and Institute for Regional Analysis and Public PolicyPublic Policy

(IRAPP)(IRAPP)

Center of Excellence, MSUCenter of Excellence, MSUAA Kentucky Program of DistinctionKentucky Program of Distinction

http://irapp.morehead-st.edu

Thank YouThanks to:The National Center for Health Statistics for the mortality data.

This Research is supported in part by:An MSU Faculty Research GrantKBRIN-NIH Research GrantThe Institute for Regional Analysis and Public PolicyBooth Endowment Research Grant