Hartford: A GIS Analysis

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Transcription:

Lead Poisoning Risk in the City of Hartford: A GIS Analysis Katie E. Perham, MPH GIS Consultant ESRI Health GIS Conference September 21, 2009

Overview Background on health effects of lead in children Hartford Health & Human Services (HHS) Lead Program High Tech Lead Tracking Project Approach for lead poisoning risk analysis Results

Children and Lead Lead found in and around homes built prior to 1978 Paint chips, dust, soil Can result in: Brain damage Nervous system damage Behavior and learning problems Slowed growth Hearing damage

HHS Lead Program Blood Lead Level μg/dl Action Child has lead in blood. 10 1919 Case management begins. Child is lead poisoned. Epidemiological 20 investigation, inspections, tracking CDC Stellar Database where data is tracked

High Tech Lead Tracking project EPA 2-year grant (Oct 07-Sept 09) specific to use of GIS for prevention of lead poisoning Collect and analyze information on lead hazard inspections Identify properties with lead hazards and properties which have been remediated Guide remediation efforts and allow for real-time analysis of neighborhood hot spots Direct outreach and education efforts to parents and property owners, referring them to funding sources for property abatement.

Research Question Where are the highest risk areas for lead Where are the highest risk areas for lead poisoning in Hartford?

Data Sources Risk Factor Age of Housing (Year Built) Locations of children with elevated blood lead levels (1993-2007) Household Income Percentage of children under age 5 Source Tax Assessor HHS Stellar Database US Census US Census Building type: residential 2 or 3 BR apts or houses Tax Assessor Buildings with soil samples with lead levels 400 ppm HHS Stellar Database

Project Approach Weighted Overlay Analysis Combine all GIS layers to calculate a risk score per building Image source: UN Food and Agriculture Organization www.fao.org/docrep/006/y4816e/y4816e0g.htm

Project Approach Weighted Overlay Analysis Steps: 1. Assign weight to each data source 2. Assign risk values based on our understanding of risk 3. Run layers through weighted overlay tool 4. Map the results

Weighting Previous understanding of risk Experience and insight into area of study Relative influence of each layer on risk Alternative (weighted sum analysis) assumes all six layers are equally influential l on risk

Step 1: Assign weight to each data source Risk Factor Weight Age of Housing (Year Built) 35% Locations of children with elevated blood lead levels 20% Household Income 15% Percentage of children under age 5 15% Building type: residential 2 or 3 BR apts or houses 10% Buildings with soil samples with lead levels 400 ppm 5%

Step 2: Assign rank values to data based on our understanding of risk Layer Age of Housing Children with EBLL (Stellar Results) Values Assigned Risk Value Risk Pre-1950 3 Highest 1950-1977 2 1978-2007 1 20 μg/dl 6 Highest 15-19 5 10-1414 4 5-9 3 >0-4 2 zero 1

Step 2: Assign rank values to data based on our understanding of risk Layer Household Income Percentage of Children < age 5 Values Assigned Risk Value Risk < 10K 8 Highest 10-15K 7 15-19K 6 20-25K 25K 5 25-29K 4 30-40 3 40-50 2 50+ 1 > 10% 3 Highest 1-10% 2 <1% 1

Step 2: Assign rank values to data based on our understanding of risk Layer Soil samples Number of Bedrooms Values Assigned Risk Value Risk 400 ppm 3 Highest 300-400 ppm 2 < 300 1 2+ bedrooms 2 Highest <2 bedrooms 1

Age of Housing

Stellar Lab Samples

Median Household Income

Percentage of Children Under Age 5

Number of Bedrooms

Soil Samples

Remove out non-residential properties

Step 3: Run weighted overlay tool Age of Housing Percent Children <5 Output layer 2 3 2 + = 75% influence 25% influence (2 x 0.75) + (3 x 0.25) 1.5 + 0.75 = 2.25 Rounded to closest integer = 20 2.0

Step 4: Map the results

Results Buildings: 28% of residential buildings in Hartford have a very high-risk for lead poisoning Census blocks: 61 (out of 997) in Hartford have 90% or greater very high-risk building area N i hb h d Hi h t i k B S Neighborhoods: Highest risk are Barry Square, Frog Hollow and the Northeast

Conclusions Based on results, outreach strategies have been designed to educate residents and property owners to improve housing conditions Grant applications submitted GIS layers developed will be used going forward in the future stages of the High Tech Lead Tracking Project, e.g. mobile field applications

Questions and Comments Contact Info: Katie E. Perham, MPH PerhamGIS@me.com