8/9/2012

LOOKING FOR MORE ANSWERS: ADDITIONAL DATA SOURCES FOR COMMUNITY HEALTH ASSESSMENT Local Public Health Assessment and Planning Data Webinar #3

August 1/ August 9, 2012 Please call in: 1-888-742-5095 Conf ID: 427 158 4560

LPHAP Data Webinar Series • Data Webinar #1: County Level Indicators for Community

Health Assessment (June 2012) • Data Webinar #2: What Do the Data Say? (July 2012)

Check the OPI training page: http://www.health.state.mn.us/divs/cfh/ophp/consultation/training/

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Today’s Presenters • Dorothy Bliss, Office of Performance Improvement • Kim Edelman, Minnesota Center for Health Statistics • Chuck Stroebel, MN Environmental PH Tracking • Kelly Muellman, Minnesota Climate and Health Program Facilitator/Recorder:

• Jeannette Raymond, Office of Performance Improvement

Learning Objectives Participants will: 1) Become familiar with an expanded range of

data sources for community health assessment 2) Meet two more MDH staff who can help with

data and analysis

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Agenda I.

Introduction

II. Vital Statistics Interactive Query III. MN Public Health Data Access IV. Climate Change Tools V. Webinar Evaluation Request

Steps in Community Health Assessment Organize Plan Assessment in Partnership Gather and Analyze Data Document and Communicate Findings

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Data Analysis Cycle

Enough information? If not, repeat cycle

Gather data

Add community knowledge and experience

Analyze, interpret, explain

“Round One” Data • County-level indicators for community health

assessment: 114 indicators from MCHS

http://www.health.state.mn.us/divs/chs/ind/index.htm

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“Round One” Data Analysis • Gathered data together • Scanned the data for indicators to start with: local

concern, public health initiative, unusual numbers (Examples: Teen marijuana use, teen birth rates)

• Looked for trends/changes over time • Compared to the state, other counties

Now what?

MINNESOTA VITAL STATISTICS INTERACTIVE QUERIES WEBSITE

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Data Webinar #2: Recap Teen Birth Rates per 1,000 Females 15-19 40.0

34.8 31.9

Rate

30.0 29.5

34.7

34.6

26.9

26.1

30.8

20.0 Minnesota 10.0

Steele Co.

0.0 1991-1995 1996-2000 2001-2005 2006-2010

Data Webinar #2: Recap Conclusions thus far: • Steele County’s TBR is higher than Minnesota’s TBR and • Steele County’s TBR is on an upward trend while

Minnesota is on a downward trend

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Data Webinar #2 Recap Next steps: • What other Round 1 indicators might help assess teen

births? • What are the risk and protective factors related to teen

births included in Round 1?

Data Webinar #2 Recap Other Round 1 Indicators: Risk and Protective Factors for Teen Births • Socioeconomic background • Poverty rates - VS Trend Report • School performance • Graduation rate - VS Trend Report • Drop out rate - VS Trend Report • Sexual activity – MSS Single Year Report • Contraceptives use - MSS Single Year Report

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Data Webinar #2 Recap Teen Birth Rates - Steele County Indicator

Steele Trend

State Trend

Better than State (last time period)

Teen Birth Rate

Negative

Positive

Worse

Poverty Rate – All

Negative

Negative

Better

Poverty Rate - u 18

Negative

Negative

Better

Graduation Rate

Positive

Positive

Better

Drop Out Rate

Positive

Positive

Better

Sexual Activity 9th Graders

Positive

Negative

Better

Condom Use 9th Graders

Positive

Negative

Better

Conclusions Thus Far State Trend

Better than State (last time period)

Negative

Positive

Worse

Negative

Negative

Better

Negative

Negative

Better

Positive

Positive

Better

Positive

Positive

Better

Sexual Activity 9th Graders

Positive

Negative

Better

Condom Use 9th Graders

Positive

Negative

Better

Indicator Teen Birth Rate Poverty Rate – All

Steele Trend

Huh?

Poverty Rate - u 18 Graduation Rate Drop Out Rate

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Possible Next Steps • Gather input from your staff • Add community knowledge and experience

Repeat cycle – add data, add more layers • Look at teen birth rates by age • Is the increase in a certain age group? • Examine poverty rates over a longer time period (e.g. 1991 to 2010) • Add 12th graders to the MSS analysis • Determine what other MSS indicators should be reviewed

Possible Next Steps • Gather input from your staff • Add community knowledge and experience

Repeat cycle – add data, add more layers • Look at teen birth rates by age • Is the increase in a certain age group? • Examine poverty rates over a longer time period (e.g. 1991 to 2010) • Add 12th graders to the MSS analysis • Determine what other MSS indicators should be reviewed

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Teen Birth Rates Using VS IQ • Create teen birth rates for Steele County for 15-17 year

olds and 18-19 year olds using the VS IQ • The Minnesota Vital Statistics Interactive Queries • https://pqc.health.state.mn.us/mhsq/index.jsp

VS IQ Background • The Vital Statistics Interactive Queries website allows you

to query births, deaths and population by state and county for the years 1990 to 2010 (most recent). • To query birth data by county you will need a login ID and

password • To get a login and password, contact Kim Edelman @

[email protected]

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Where is the VS IQ?

Click on Data & Statistics

Under Interactive Data Sources, select MN VS IQ

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Click on Login

Enter login and password

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Click on Birth Queries Looks similar to original screen with this box added.

Step 1

Select counties or state Select one or more years

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Step 2

Select up to four variables

Step 3

Select your type of analysis

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Step 4

Select variables to narrow your query by a certain population (e.g. American Indians) or certain characteristics (e.g. low birth weight)

Steele County Teen Birth Rate Age 15-17, 2006-2010 Query Steps • Step 1: • Select “Steele County” • Select “2006-2010”

• Step 4: Age (single

year) • Select “15” in Min Age • Select “17” in Max Age

• Step 2: • Select “Age of Mother”

• Press “Submit”

• Step 3: • Select “Rate”

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Teen Birth Rate (15-17), Steele County 2006-2010

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Teen Birth Rate (15-17), Minnesota 2006-2010

Steele County Teen Birth Rate Age 18-19, 2006-2010 Query Steps • Step 1: • Select “Steele County” • Select “2006-2010”

• Step 4: Age (single

year) • Select “18” in Min Age • Select “19” in Max Age

• Step 2: • Select “Age of Mother”

• Press “Submit”

• Step 3: • Select “Rate”

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Teen Birth Rate (18-19), Steele County 2006-2010

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Teen Birth Rate (18-19), Minnesota 2006-2010

Teen Birth Rates per 1,000 Females, Steele County and Minnesota 90.0

Age 15-19

90.0

70.0

80.0

60.0

70.0

50.0

60.0

40.0

34.8 31.9

34.7

34.6

30.0 20.0

29.5

30.8

26.9

26.1

Rate

Rate

80.0

50.0

Ages 15-17 and 18-19 77.4 57.7

58.8

57.3

52.7

40.0 30.0

46.5 20.1

20.0

10.0

10.0

0.0

0.0

Minnesota

Steele Co.

61.7

18.2

46.1

18.5 12.4

14.5

16.9

13.5

MN 18-19

Steele 18-19

MN 15-17

Steele 15-17

12.4

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Conclusions Thus Far • Steele County’s teen birth rate (15-19) on an upward

trend while Minnesota’s TBR is on a downward trend. • Further analysis reveals that Steele County’s 15-17 TBR

is trending down, and equal to the Minnesota rate for 2006-2010. • The 18-19 TBR for Steele County is on the rise and higher

than the state rate (77.4 vs. 46.1). • The increase in TBR 15-19 due to the increase in birth

rate for the 18-19 year olds.

Possible Next Steps: Focus on 18-19 year olds • Gather input from your staff • Add community knowledge and experience • Repeat cycle – add data, add more layers • Teen Birth Rates (18-19) by race/ethnicity

• Add 12th graders to the MSS analysis

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Using the VS IQ in Assessment • The VS IQ can be used generate Round 1 indicators • Some counties have enough births and deaths to do single year rates and percentages. You can use the VS IQ to generate these rates and percentages. • The VS IQ can expand on Round 1 indicators related to birth

and death moving into Round 2. For example: • Round 1 Indicator: Teen Birth Rate age 15-19 • Round 2 – Rates broken out by age (15-17 and 18-19) • Round 2 – Rates by race/ethnicity • Round 1 Indicator: Leading causes of death - age adjusted

rates per 100,000 (e.g. cancer, heart disease, stroke) • Round 2 – Rates by age, gender or race/ethnicity

Vital Statistics Interactive Queries • Website: https://pqc.health.state.mn.us/mhsq/index.jsp • For questions, login/passwords, questions, help or to

schedule a VS IQ training contact: Kim Edelman [email protected] 651 201 5944

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MINNESOTA PUBLIC HEALTH DATA ACCESS Chuck Stroebel

Key Features • One-stop shop for health & environment data • Nationally consistent measures (indicators) • Interactive maps & queries

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Audiences Local Health Departments State & Local Agencies Researchers Non-Profit Organizations Policymakers, Public

Demonstration https://apps.health.state.mn.us/mndata/

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Coming Soon (2012-13) • New data & features • Climate change (heat stress) • Behavior Risk Factor Surveillance Survey

(smoking, obesity) • Population characteristics • Biomonitoring (additional chemicals) • E-learning modules

• Custom data access

Potential New Data Sources • Developmental disabilities (autism) • Pesticide poisonings • Private well water (arsenic) • Radon • Others?

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Questions?

Subscribe for updates at: https://apps.health.state.mn.us/mndata

CLIMATE CHANGE TOOLS

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MN Climate & Health Program

http://www.health.state.mn.us/divs/climatechange/

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Extreme Heat Events • Record heat and

humidity! • Minnesotans are equipped to deal with cold not heat • How do you know if your community is at risk or prepared? • Toolkit • Maps and data tools

Toolkit Appendix F: Data Sources

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Heat Vulnerability Assessment • Social and demographic indicators of risk: • Children less than 5 years old • Adults 65 years old and older • Adults 65+ living alone • Poverty • Pre-existing conditions that can be aggravated by heat: • Asthma • Diabetes • Cardiovascular/heart disease • Exposure related risks: • Urban areas • Athletes, outdoor workers, persons exposed to heat for long periods of time

At Risk: Elderly Living Alone • Physiological changes; decreased ability to adapt to

temperature changes • Pre-existing conditions, e.g., diabetes • Use of certain medications • Combinations of factors: poverty, aging, social isolation,

economic constraints, mobility constraints

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Social and demographic data • Details of map components

described on the back (page 2) of each map • Definitions • Data description • Statistics

• Statewide map allows you

to compare communities • Limitation: only shows a range of values • Specific values available in Excel data table

filter arrow

county selection

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Health data • Pre-existing conditions that can be aggravated by heat: • Asthma - Minnesota Public Health Data Access • Diabetes - www.cdc.gov/diabetes/statistics/ • Cardiovascular/heart disease - http://www.cdc.gov/dhdsp/

Exposure related risks • Living in urban areas

http://land.umn.edu/maps/impervious/landbrowse.php • Athletes, outdoor workers, persons exposed to heat for long periods of time http://www.positivelyminnesota.com/assets/lmi/lehd.shtml

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MN Climate & Health Program

http://www.health.state.mn.us/divs/climatechange/ Questions? [email protected]

EVALUATION REQUEST

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Data Webinar Series Evaluation After the August 9 presentation, all participants in the series of data webinars will receive an email invitation to evaluate these trainings. The survey also will ask you to suggest future topics for training on local public health assessment and planning. Please help improve the training opportunities by filling out this evaluation survey. Thank you!

Resources Minnesota Center for Health Statistics http://www.health.state.mn.us/divs/chs/ Kim Edelman, [email protected] Ann Kinney, [email protected] Minnesota Public Health Data Access https://apps.health.state.mn.us/mndata/ Chuck Stroebel, [email protected] Climate Change Tools http://www.health.state.mn.us/divs/climatechange/ Kelly Muellman [email protected]

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THANKS Have a healthy day!

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