Embed Size (px)
Citation preview
Place Matters for Health:Geographic Health Patterns in Genesee County
Daniel J. Kruger, PhDUniversity of Michigan School of Public Health
Genesee County Public Health Week ConferenceMay 7, 2013
John Snow
England, 1813 - 1858
Voted “the greatest doctor of all time”Hospital Doctor magazine-March 2003 survey
John Snow’s map of water pumps John Snow’s map of water pumps and cholera casesand cholera cases
Cholera case
Water pump
John Snow’s map of water pumps John Snow’s map of water pumps and cholera casesand cholera cases
Cholera case
Water pump
Broad StreetPump
John Snow MemorialJohn Snow Memorial
John Snow MemorialJohn Snow Memorial
Genesee County, Michigan
SPEAK TO YOUR HEALTH!Community Survey
Comparing health indicators across geographical areas
Survey MethodologySurvey Methodology2003-20092003-2009
• Random sample Random sample of households in Genesee Countyof households in Genesee County
• 20 residents per Census Tract in Flint20 residents per Census Tract in Flint
• 10 residents per Census Tract outside of Flint10 residents per Census Tract outside of Flint
• Telephone interviewsTelephone interviews conducted by the Michigan conducted by the Michigan Public Health Institute Public Health Institute
• Adults ages Adults ages 18 years and older18 years and older
• Final sample size = Final sample size = 1700 residents 1700 residents
• 900 in Flint and 800 Out-County900 in Flint and 800 Out-County
• Data analyses can be weighted Data analyses can be weighted to take into account to take into account sampling strategy and demographic distribution sampling strategy and demographic distribution
Survey MethodologySurvey Methodology20112011
• Random sample Random sample of households in Genesee of households in Genesee CountyCounty
• Adults ages Adults ages 18 years and older18 years and older
• Telephone interviewsTelephone interviews conducted by the conducted by the Michigan Public Health InstituteMichigan Public Health Institute
• Mailed hard copy surveys Mailed hard copy surveys compiled by MPHIcompiled by MPHI
• On-line survey On-line survey linked to GCHD homepagelinked to GCHD homepage
• Results weighted Results weighted to take into account sampling to take into account sampling strategy and demographic distribution strategy and demographic distribution
Survey TopicsPhysical Health and chronic health conditionsPhysical Health and chronic health conditions
Mental Health Mental Health
Health Care Access, Coverage, Satisfaction, Trust Health Care Access, Coverage, Satisfaction, Trust
Physical and Mental Health ScreeningPhysical and Mental Health Screening
Health Promoting Behaviors (nutrition, exercise, etc.)Health Promoting Behaviors (nutrition, exercise, etc.)
Health Adverse Behaviors (tobacco use, etc.) Health Adverse Behaviors (tobacco use, etc.)
Sleep QualitySleep Quality
Spirituality, Religion, and Health Spirituality, Religion, and Health
Experiences of discriminationExperiences of discrimination
Financial health Financial health
Violence, crime, relations with police, and incarcerationViolence, crime, relations with police, and incarceration
Neighborhood ConditionsNeighborhood Conditions
Disease Burden• Heart disease• Stroke• Cancer • Depression• Anxiety• Diabetes• Asthma• Sleep disorder• Sarcoidosis• Sickle cell anemia• Lupus
Proportion who eat at least5 fruits and vegetables per day
Proportion of respondents who eat at least5 fruits and vegetables per day
Kruger, D.J., Greenberg, E., Murphy, J.B, DiFazio, D.A., & Youra, K.R. (in press). Local concentration of fast food outlets is associated with poor nutrition and obesity. American Journal of Health Promotion.
Those who lived near more fast food outlets: •Were more likely to be overweight and obese•Ate fewer fruits and vegetables
Minutes of exercise per week
Proportion who have a park in their neighborhood that they feel safe using for physical activity
Fear of crime
Proportion who sleep less than 7 hours a night
48504
48505 48506
48532
48507
48509
48503
Diabetes Risk by EXPORT ZIP Code in 2003 Percent of Respondents Classified as High Risk
In Targeted Diabetes Intervention Areas
48458
24.1 – 29.9%
30.0 – 34.9%
35.0 – 36.8%
48504
48505 48506
48532
48507
48509
48503
Diabetes Screening by EXPORT ZIP by EXPORT ZIP CodePercent of Respondents Who Say They Were
Screened for Diabetes in the Past Year
76 – 82%
71 – 72%
60 – 70%
48458
48504
48505 48506
48532
48507
48509
48503
Project EXPORT Activities by ZIP CodeMap Indicates Percent of Respondents
Classified as High Risk in 2003
48458
24.1 – 29.9%
30.0 – 34.9%
35.0 – 36.8%
4
21
1
1
2005 Community Survey Results2005 Community Survey Results
Diabetes RiskDiabetes RiskPercent of Respondents 45+ Percent of Respondents 45+ Classified as High Risk for Classified as High Risk for
Diabetes by ZIP Code Diabetes by ZIP Code Genesee County, 2005Genesee County, 2005
61 – 80%
51 – 60%
30 – 50%
Insufficient Data
2005 Data
Kruger, D.J., Brady, J.S., & Shirey, L.A. (2008). Using GIS to facilitate community-based public health planning of diabetes intervention efforts. Health Promotion Practice, 9, 76-81.
Diabetes DiagnosesDiabetes DiagnosesPercent of respondents Percent of respondents
45+ who have been 45+ who have been diagnosed with diabetes diagnosed with diabetes Genesee County, 2005Genesee County, 2005
26 – 35%
16 – 25%
1 – 15%
Insufficient Data
2005 Data
Kruger, D.J., Brady, J.S., & Shirey, L.A. (2008). Using GIS to facilitate community-based public health planning of diabetes intervention efforts. Health Promotion Practice, 9, 76-81.
Diabetes ScreeningDiabetes ScreeningPercent of respondents Percent of respondents
45+ high risk for diabetes and 45+ high risk for diabetes and have not been screened, have not been screened, Genesee County, 2005Genesee County, 2005
31 – 50%
21 – 30%
1 – 20%
Insufficient Data
2005 Data
Kruger, D.J., Brady, J.S., & Shirey, L.A. (2008). Using GIS to facilitate community-based public health planning of diabetes intervention efforts. Health Promotion Practice, 9, 76-81.
Diabetes ScreeningDiabetes ScreeningPercent of respondents Percent of respondents
45+ high risk for diabetes and 45+ high risk for diabetes and have not been screened, have not been screened, Genesee County, 2005Genesee County, 2005
31 – 50%
21 – 30%
1 – 20%
Insufficient Data
2005 Data
1
4
12 11
2 Indicates EXPORT Activities
Kruger, D.J., Brady, J.S., & Shirey, L.A. (2008). Using GIS to facilitate community-based public health planning of diabetes intervention efforts. Health Promotion Practice, 9, 76-81.
Importance of the built environment
Elevated blood lead levels in older housing stockElevated blood lead levels in older housing stock
Percentage of Housing Units Percentage of Housing Units Constructed Pre-1940Constructed Pre-1940
31 - 47%31 - 47%21 - 30%21 - 30%
11 - 20%11 - 20% 0 - 10%0 - 10%
No ExposureNo ExposureSome ExposureSome Exposure
Lead Poisoned (10-19)Lead Poisoned (10-19)Lead Poisoned (20+)Lead Poisoned (20+)
Elevated Blood Lead Levels
Kruger, D.J., Shirey, L.A., Taylor, S. Kruger, D.J., Shirey, L.A., Taylor, S. (in press). GIS facilitates community-(in press). GIS facilitates community-based child lead screening efforts. based child lead screening efforts. Michigan Journal of Public HealthMichigan Journal of Public Health..
Flint Environmental Block Assessment
VacantResidential structures
Residential structures in disrepair or not salvageable
Flint Environmental Block Assessment
VacantCommercial structures
Flint Environmental Block Assessment
Commercial structures in disrepair or not salvageable
Flint Environmental Block Assessment
The built environment affects social conditions The built environment affects social conditions and mental healthand mental health
EBA Data Community Survey Data
Kruger, D.J., Reischl, T.M., & Gee, G.C. (2007). Neighborhood social conditions mediate the Kruger, D.J., Reischl, T.M., & Gee, G.C. (2007). Neighborhood social conditions mediate the association between physical deterioration and mental health. association between physical deterioration and mental health. American Journal of Community American Journal of Community Psychology, 40, Psychology, 40, 261-271.261-271.
Density of deteriorated structuresDensity of deteriorated structures
Density of pre-mature birthsDensity of pre-mature births
Density of low birth weight birthsDensity of low birth weight births
The built environment and birth outcomes
Correlations with density of structural deterioration
Race Pre-maturity Low birth weight
All .441*** .500***
Black .354*** .336***
White .228** .026
N = 169; ** indicates p < .01, *** indicates p < .001. Controlling for maternal education, paternal education, and private insurance status.
Kruger, D.J., Munsell, M.A., & French-Turner, T. M. (2011). Using a life history framework to understand the relationship between neighborhood structural deterioration and adverse birth outcomes. Journal of Social, Evolutionary, and Cultural Psychology, 5, 260-274.
The built environment and birth outcomesBlack births were overrepresented in areas with high structural deterioration
Race Top 25% Top 5%
Black 49% 20%
White 22% 6%
Proportion of births by area level of deterioration
Kruger, D.J., Munsell, M.A., & French-Turner, T. M. (2011). Using a life history framework to understand the relationship between neighborhood structural deterioration and adverse birth outcomes. Journal of Social, Evolutionary, and Cultural Psychology, 5, 260-274.
