Childhood Elevated Blood Lead Levels in Monroe County, NY
Childhood lead exposure can have serious consequences on lifelong health and continues to be an important public health issue. In the state of New York, health care providers are mandated to test all children for lead at around one year of age and again at around two years; providers are also required to evaluate children ages 6 months to 6 years for potential lead exposure and perform blood lead testing for all children who are found at risk for lead poisoning. In their dataset Childhood Blood Lead Testing and Elevated Incidence by Zip Code: Beginning 2000, the New York State Department of Health provides the number and rate of children in each ZIP code who are tested for lead and identified to have elevated blood lead concentration.
Combining this dataset with US census data, I created an interactive chart visualizing childhood elevated blood lead level trends in Monroe County, NY in connection with social determinants of health such as geography and socioeconomic status.
Childhood lead exposure can have serious consequences on lifelong health and continues to be an important public health issue. In the state of New York, health care providers are mandated to test all children for lead at around one year of age and again at around two years; providers are also required to evaluate children ages 6 months to 6 years for potential lead exposure and perform blood lead testing for all children who are found at risk for lead poisoning. In their dataset Childhood Blood Lead Testing and Elevated Incidence by Zip Code: Beginning 2000, the New York State Department of Health provides the number and rate of children in each ZIP code who are tested for lead and identified to have elevated blood lead concentration.
Combining this dataset with US census data, I created an interactive chart visualizing childhood elevated blood lead level trends in Monroe County, NY in connection with social determinants of health such as geography and socioeconomic status.
An interactive chart visualizing the demographic and temporal trends in childhood elevated blood lead levels across Monroe County ZIP codes.
An interactive chart visualizing the demographic and temporal trends in childhood elevated blood lead levels across Monroe County ZIP codes.
TOOLS
Adobe Illustrator
Open Data NY
Google Sheets
RAWGraphs
Figma
TOOLS
Adobe Illustrator
Open Data NY
Google Sheets
RAWGraphs
Figma
FORMAT
Interactive data visualization
FORMAT
Interactive data visualization
DATA SOURCES
Childhood Blood Lead Testing and Elevated Incidence by Zip Code: Beginning 2000 (from New York State Department of Health via Open Data NY)
US Census Bureau
DATA SOURCES
Childhood Blood Lead Testing and Elevated Incidence by Zip Code: Beginning 2000 (From New York State Department of Health via Open Data NY)
US Census Bureau
DATA COLLECTION
Combining health and census data
DATA COLLECTION
Combining health and census data
DATA VISUALIZATION
Combining health and census data
I exported the NY Department of Health childhood lead testing dataset from Open Data NY as a CSV file and used the spreadsheet to filter and sort the rows by ZIP codes in Monroe County. I was then able to merge the childhood blood lead testing data for each ZIP code with demographic information (collected from the US Census Bureau), including the ZIP code’s median household income, population, number of housing units, employment rate, and health care coverage.
I exported the NY Department of Health childhood lead testing dataset from Open Data NY as a CSV file and used the spreadsheet to filter and sort the rows by ZIP codes in Monroe County. I was then able to merge the childhood blood lead testing data for each ZIP code with demographic information (collected from the US Census Bureau), including the ZIP code’s median household income, population, number of housing units, employment rate, and health care coverage.
I exported the NY Department of Health childhood lead testing dataset from Open Data NY as a CSV file and used the spreadsheet to filter and sort the rows by ZIP codes in Monroe County. I was then able to merge the childhood blood lead testing data for each ZIP code with demographic information (collected from the US Census Bureau), including the ZIP code’s median household income, population, number of housing units, employment rate, and health care coverage.
DATA EXPLORATION
Preliminary visualizations
DATA EXPLORATION
Preliminary visualizations
DATA EXPLORATION
Preliminary visualizations
Using Google Sheets, I created some quick and simple scatterplots to explore relationships between certain demographic variables and rates of elevated blood lead levels. The chart visualizing the relationship between time and incidence rates appeared to show the strongest correlation.
Using Google Sheets, I created some quick and simple scatterplots to explore relationships between certain demographic variables and rates of elevated blood lead levels. The chart visualizing the relationship between time and incidence rates appeared to show the strongest correlation.
Using Google Sheets, I created some quick and simple scatterplots to explore relationships between certain demographic variables and rates of elevated blood lead levels. The chart visualizing the relationship between time and incidence rates appeared to show the strongest correlation.
VISUALIZATION
From raw numbers to colorful dots
VISUALIZATION
From raw numbers to colorful dots
VISUALIZATION
From raw numbers to colorful dots
The final data visualization takes the form of a scatterplot, with each dot representing a ZIP code for a given year. The graph shows the trend in incidence rates over time, with additional variables— median income and population— being visually represented through dot color and size.
The final data visualization takes the form of a scatterplot, with each dot representing a ZIP code for a given year. The graph shows the trend in incidence rates over time, with additional variables— median income and population— being visually represented through dot color and size.
The final data visualization takes the form of a scatterplot, with each dot representing a ZIP code for a given year. The graph shows the trend in incidence rates over time, with additional variables— median income and population— being visually represented through dot color and size.
TOOLS
Adobe Illustrator
Open Data NY
Google Sheets
RAWGraphs
Figma
FORMAT
Interactive Data Visualization