Factors that Influence – ‘Life Expectancy’:
Multivariate Regression Analysis of US counties
Joo young Park
Contents
Introduction
Literature Review
Data & Methods
Results
Public Policy
Life expectancy is the expected number of years of life
remaining at a given age, in the statistical sense.
(Sheffrin, 2003)
1.0 Introduction
Steven M. Sheffrin (2003). Economics: Principles in action. Upper Saddle River,
New Jersey: Pearson Prentice Hall. p. 473.
Potential factors that drive Life Expectancy
Demographic factors :race, gender, income
Direct mortality causes: cancer, stroke, heart disease
Environmental heath: air quality, toxic chemical
Risk factors for premature death : smoking, obesity
Access to care service
1.0 Introduction
Research Question:
In terms of individual behavioral risk factors &
availability of public health supports,
what are the influential factors
of ‘Average Life expectancy’ of US citizens?
1.0 Introduction
2.0 Literature Review
Jean Marie Robine, Karen Ritchie, 1991, “Health life expectancy :
evaluation of global indicator of change in population health”
‘Healthy life expectancy’ is a valuable index for the appreciation of changes in both the physical and the mental health states of the general population, for allocating resources, and for measuring the success of political programs
Gabriel Gulis, 2000, “Life expectancy as an indicator of environmental health” European Journal of Epidemiology
Life expectancy at birth is related to the quality of life as expressed by global economic, environmental and nutritional measures.
2.0 Literature Review
Anna Peeters, 2003, “Obesity in Adulthood and its consequences for life
expectancy : Life table analysis” Annals of Internal Medicine
Obesity and overweight in adulthood are associated with large decreases in life expectancy and increases in early mortality
Henrik Bronnum-Hansen, Knud Juel, 2001 “Abstention from smoking
extends life and compresses morbidity: a population based study of health expectancy among smokers and never smokers in Denmark” Tobacco Control
Smoking reduces the expected lifetime in good health and increase the expected lifetime in poor health
2.0 Literature Review
Mira M.Hidajat, Mark D.Hayward, Yasuhiko Saito, 2007 “Indonesia’s social
capacity for population health: the educational gap in active life expectancy” Population Research and Policy Review
Education increases life expectancy but it also expands the expected years with a major functional problem.
Eileen M. Crimmins, Yasuhiko Saito, 2001 “Trends in healthy life expectancy in the United States, 1970-1990: gender, racial, and educational differences” Social Science & Medicine 52
Large racial and educational differences in healthy life expectancy
2.0 Literature Review
R G Wilkinson, 1992 “Income distribution and life expectancy” BMJ vol. 304 :165-168
Health and income distribution is a result of factors to do with relative rather than absolute income. Increasingly social scientists have emphasized the importance of relative poverty.
Robert A. Hahn, Steven Eberhardt, 1995 “Life Expectancy in Four U.S. Racial/Ethnic Populations:1990” Epidemiology
Race/ethnicity on death certificates to calculate life expectancy for Black, White, American Indian, Hispanic and Asian men and women in the United States in 1990. Asian men had life expectancies of 82 years and Asian women 85.8 years-the highest life expectancies
3.1 Data
Dependent
Variable Definition Data source Year
Life Expectancy
The average number of years that a baby born in a particular
year is expected to live if current age-specific mortality trends
continue to apply
The Community Health Status Indicators Report by Department of Health
and Human Service
2008
Data set : CHSI 2009 (Community Health Status Indicators) 205 health indicators for 3,141 current counties in 50 states and District of Columbia
3.1 Data (Continued)
Independent
Variable
Expected
sign Definition Data source Year
Population Size unclear Annual estimates of the resident population US Census Bureau 2008
Population
Density negative Population density (people per square mile) US Census Bureau 2008
Poverty negative individuals living below poverty level % US Census Bureau 2008
Population
Race/Ethnicity unclear
Race and ethnicity-specific population size %
; White/Black/
American Indian/Asian/Hispanic
US Census Bureau 2008
Unemployed negative Unemployed % US Bureau of Labor Statistics 2008
No Exercise negative
% of adults reporting of no participation
in any leisure-time physical activity or exercises in
the past month
Centers for Disease Control
and Prevention 2006
Few fruits/
vegetables negative
% of adults reporting an average
fruits/vegetables
consumption of less than 5 servings per day
Centers for Disease Control
and Prevention 2006
Obesity negative Calculated % of adults of overweight,
based on body mass index (BMI)
Centers for Disease Control
and Prevention 2006
Smoker negative % of adult smoker Centers for Disease Control
and Prevention 2006
Uninsured negative Estimated % of uninsured individuals
under age 65 US Census Bureau 2006
Medicaid
Beneficiaries positive Medicaid beneficiaries
Centers for Medicare and Medicaid
Services 2008
Primary care
physicians positive Primary care physicians per 100,000 pop % HRSA 2008
Elderly
Medicare positive
% of Medicare beneficiaries
for elderly (age 65+)
Centers for Medicare
and Medicaid Services 2008
Dentist Rate positive dentists % per 100,000 pop HRSA 2008
Community
Health Center positive
Indicator for any Community/Migrant Health
Centers located in the county HRSA 2009
HPSA positive Indicator for single county designated
Health Professional Shortage Area HRSA 2009
Data Cleaning
Data Recoding : % conversion
Unemployment, Insurance, Elderly Medicare and Medicaid Beneficiaries
Test for Normality: histogram
Identification of Outliers
Screening and Tests for Multicollinearity
3.2 Methods
4.2 Results: Regression Models
Multivariate Regression Analysis
• Exclusions of Population size and Population density
• VIF and Pearson correlation test :
1) Unemployment vs.Uninsurance
2) Medicaid Beneficiaries, Elderly Medicare, Primary care
physicians
• Races, Black & Asian : clear direction, But Hispanic -unsecured,
White & American Indian no direction
• Exclusion of Dentist rate : limited coefficient level
4.2 Results: Regression Models
Table 7: Coefficients* and Collinearity Statistics of Final Model
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Collinearity
Statistics
B Std. Error Beta Tolerance VIF
(Constant) 83.640 .534 156.654 .000
Poverty -.081 .006 -.229 -13.530 .000 .512 1.952
Black -.052 .002 -.345 -23.612 .000 .687 1.455
Asian .050 .009 .076 5.418 .000 .744 1.344
No_Exercise -.057 .006 -.183 -9.658 .000 .407 2.459
Few_Fruit_Veg -.008 .006 -.019 -1.337 .181 .730 1.369
Obesity -.048 .008 -.107 -6.363 .000 .518 1.931
Smoker -.109 .006 -.290 -18.763 .000 .613 1.632
Uninsurance% -.019 .006 -.041 -2.947 .003 .767 1.304
Elderly_Medicare% .030 .007 .057 4.113 .000 .766 1.306
Community_Health_Center_I
nd
.138 .054 .034 2.542 .011 .843 1.186
HPSA_Ind -.059 .074 -.010 -.787 .431 .866 1.155
4.2 Results: Regression Models
Table 5: Summary of Final Model
Model R R2 Adjusted R2 Std. Error of
the Estimate
Regression 2 0.860* 0.739 0.737 1.0451
* a. Predictors: (Constant), Poverty, Uninsurance%, Black, Asian, Few_Fruit_Veg, Obesity, No_Exercise, Smoker, Elderly_Medicare%, Community_Health_Center_Ind, HPSA_Ind, b. Dependent Variable: ALE
Average life expectancy
= 83.640 +0.138(Community HC) +0.050(Asian)
+0.030(Elderly Medicare) -0.109(Smoker)
-0.081(Poverty) -0.059(HPSA)-0.057(no exercise)
-0.052(Black) -0.048(Obesity)-0.019(Uninsurance)
-0.008(Few Fruit and vegetable)
4.2 Results: Regression Models
• Mobilize and enhance Community Health Centers which are
for low income and uninsurance care
• Develop policies and plans that support HPSA
• Assures the quality and accessibility of health services,
especially in HPSA
• Inform and educate people about healthy behaviors
• Intensify anti-smoking policies
5.0 Public Policy
Any Questions?
The End
4.1 Results: Descriptive Statistics Table 4: Descriptive Statistics for Independent Variables
Variable Mean Median Std.Deviation Minimum Maximum Percentile
25 50 75
Poverty 15.24 14.30 6.06 3.10 54.40 10.90 14.30 18.30
Black 9.12 2.30 14.39 0.00 86.00 0.60 2.30 10.60
Asian 1.18 0.50 2.77 0.00 55.60 0.30 0.50 1.00
No Exercise 26.51 26.00 6.70 8.30 52.40 21.90 26.00 30.80
Few fruits/
vegetables 78.92 79.00 5.16 63.10 96.40 75.50 79.00 82.40
Obesity 24.15 24.30 4.90 4.20 42.60 21.10 24.30 27.20
Smoker 23.11 23.00 5.73 3.60 46.20 19.40 23.00 26.70
Uninsured 15.10 14.41 5.08 0.00 41.91 11.33 14.41 18.02
Elderly
Medicare 14.76 14.30 4.26 0.00 38.10 11.98 14.30 17.16
Community
Health
Center
0.51 1.00 0.50 0.00 1.00 0.00 1.00 1.00
HPSA 0.75 1.00 0.43 0.00 1.00 1.00 1.00 1.00