## MICA User Group Newsletter Practice Exercise Solutions

### Issue #15

As a coach at a local high school, you are concerned about the risk of dehydration for your athletes.  You wonder how commonly dehydration occurs in Missouri and decide to use the MICAs and Profiles to research this condition.

1. You start by reviewing the Emergency Room Profile.  What is the most recent Missouri emergency room (ER) visit rate for fluid and electrolyte disorders (dehydration)?  1.9 ER visits per 1,000 population

2. You create a significance map to see which areas of the state are more impacted by dehydration.  You are surprised to learn that many of the counties in the northern part of the state have significantly high rates.  Which county has the highest rate?  Harrison

3. You notice that the Missouri Emergency Profile has a Race tab at the top.  You click on it to view the data by race.  Which race group has the higher dehydration ER visit rate?  African-American Missourians have the higher ER visit rate for dehydration at 2.37 visits per 1,000 population compared to 1.76 visits for White Missourians.

4. You decide to check the Inpatient Hospitalization Profile to see if data would be available on more serious cases of dehydration.  How many Missouri residents were hospitalized for fluid and electrolyte disorders (dehydration) in the most recent year?  8,625

5. You wonder about the financial impact of dehydration on Missouri.  After some searching, you find fluid and electrolyte disorders under the Nutritional – metabolic – immunity grouping in the Hospital Discharges, Charges and Days of Care MICA.  You create a table showing the hospital charges for the most recent year.  What was the initial amount charged for Missouri residents with a primary diagnosis of fluid and electrolyte disorders?  \$148,493,657.00

6. According to the Hospital Discharges, Charges and Days of Care MICA, how many inpatient hospitalizations (i.e., hospital discharges) of Missouri residents were due to fluid and electrolyte disorders?  8,625  Does this figure match the answer to #4 above?  Yes

7. What is the average initial hospitalization charge per patient for Missouri residents with a primary diagnosis of fluid and electrolyte disorders?  (HINT:  Divide the #5 answer by the #4 answer.)  \$17,216.66

### Issue #14

While working on a community health assessment for your agency, the Washington County Health Department, you notice a significant increase in COPD/bronchiectasis hospitalizations between 2011 and 2013.  You discuss your concerns with staff from the Franklin County Department of Health and the Warren County Health Department, which are also located within the St. Louis Metro BRFSS Region.  Together, you decide to use the MICA system to determine whether or not there is an increasing problem with COPD in the area.  If so, you would be interested in applying for grant dollars to allow you to partner with local hospitals to stage an intervention.  You begin researching grant opportunities to find out what sorts of data may be required.

1. Use the Inpatient Hospitalization MICA to determine the 2011 and 2013 age-adjusted COPD/bronchiectasis hospitalization rates for residents of the state, each of the three partner counties, and the three counties combined.  The Franklin County information is provided as a guide.  (HINT:  If County/City is selected as the row variable in Step One and all three counties are selected using the CTRL key in Step Five, the Total for Selection row provides the combined rates for all three counties.)
2.  2011 2013 Did rate increase? Missouri 23.7 20.2 No Franklin County 22.0 20.7 No Warren County 13.0 15.0 Yes Washington County 31.7 56.1 Yes Tri-county area 21.6 25.0 Yes
3. You want to determine if any changes in Washington County and in the tri-county area are meaningful and if there are meaningful differences between your area and the state overall.  Return to the query screen and add 95% confidence intervals to your table.  What are the confidence intervals for the following areas of interest?
4.  2011 2013 Missouri 23.4 to 24.1 19.9 to 20.5 Washington County 25.2 to 39.3 47.8 to 65.5 Tri-county area 19.5 to 23.9 22.8 to 27.4

Is the difference between the 2011 and 2013 Washington county rates statistically significant?  Yes.  If so, how?  The 2013 Washington County COPD/bronchiectasis hospitalization rate is significantly higher than the 2011 rate.
Is the difference between the 2011 and 2013 tri-county rates statistically significant?  No.
If so, how?  The 2013 tri-county COPD/bronchiectasis hospitalization rate is not significantly different from the 2011 rate.
Are the 2013 Washington County and Missouri rates statistically significantly different?  Yes.  If so, how?  The Washington County rate is significantly higher than the Missouri rate.
Are the 2013 tri-county and Missouri rates statistically significantly different?  No.  If so, how?  The tri-county rate is not significantly different from the Missouri rate.

5. Many of the grant opportunities you review ask that grantees target the age groups that are most impacted by high COPD/bronchiectasis rates.  Revise your query so that you can view rates by age for the 2013 data.  Which age group(s) have the highest rates in Washington County and the tri-county area?  (HINT:  Click the All Ages hyperlink to view more detailed age groups.)
Washington County  The highest COPD/bronchiectasis hospitalization rates in Washington County occur among residents ages 75 to 84 (277.8 hospitalizations per 10,000 residents) and 65 to 74 (219.6).
Tri-county area  The highest COPD/bronchiectasis hospitalization rates in the tri-county area occur among residents ages 65 to 74 (105.5 hospitalizations per 10,000 residents) and 75 to 84 (105.2).

6. Based on the data gathered in the questions above, should the partners move forward in applying for grant dollars to fund a COPD intervention?  Why or why not?  Based on the data, Washington County should definitely consider applying.  The Washington County rates are significantly high compared to the state overall and are on the rise.  It is less clear whether the tri-county areas as a whole should apply.  The Franklin and Warren rates did not change much; in fact, additional analysis of their confidence intervals reveals that there was no significant difference between the 2011 and 2013 rates.  Furthermore, the Franklin County rates are only slightly lower than the state rates for these years, while the Warren County rates are considerably lower.  (Additional analysis of the confidence intervals for Warren County would reveal that the Warren County rates are significantly lower than the state rates.)

### Issue #13

A coworker’s recent nasty fall and resulting broken arm inspired you to think about ways your employer, the Shannon County Health Department, can combat injuries due to falls.  You decide to use the Injury MICA and the Unintentional Injury Profile to gather some preliminary data so you can understand the overall severity of the problem and the recent trends in your county, as well as the groups most at risk of falls.

1. Using the Injury MICA, select Unintentional as the Intention on Step 3.  Then compare overall fall injury rates to the rates for all other injury mechanisms during the most recent year.  (HINT:  Select Mechanism as the row variable in Step 1.  In Step 6, highlight all of the categories in the Mechanism box by using the CTRL key.)
What is the fall injury rate? The 2013 unintentional fall injury rate in Shannon County was 2,375.0 per 100,000 residents.  This rate is age adjusted to the 2000 U.S. Standard Population.
How does the fall injury rate compare to the rates for the other injury mechanisms? In Shannon County, the fall rate of 2,375.0 per 100,000 residents is higher than the rate for any other mechanism.
2. Return to the Injury MICA query screen and change the column variable in Step 2 to Age.  Which age group has the highest unintentional fall injury rate?  Shannon County residents ages 65 and over have the highest unintentional fall injury rate (at 5,063.3 per 100,000 residents) among the five age groups included in the table.
Return to the query screen again and add 95% confidence intervals to the table.  Is the rate for this age group significantly high compared to the other age groups?  Yes.  The lower end of the confidence interval for the 65 and over age group, which is 4,014.9, is higher than the upper ends of the confidence intervals for the other age groups.
3. Use the Unintentional Injury Profile to look at fall deaths, hospitalizations, and emergency room visits in a single table.  Are the Shannon County rates significantly different from the state rates in each of these categories?
Deaths:  No.  There is no significant difference between the Shannon County and the Missouri rates.
Hospitalizations:  Yes.  The Shannon County rate is significantly lower than the Missouri rate.
Emergency Room Visits:  Yes.  The Shannon County rate is significantly higher than the Missouri rate.
4. Use the Trend Line feature to determine if the fall hospitalization and emergency room visit rates are changing significantly over time.
Hospitalizations:  The Shannon County rate has not changed significantly over time.
Emergency Room Visits:  The Shannon County rate has significantly increased over time.

### Issue #12

As a staff member at the Phelps County Health Department, you eagerly scan each MICA newsletter to discover better ways to track health status in your county.  After reading about the MAP program in the Spotlight article on Belinda Heimericks, you decide to explore data on the impact of heart disease and stroke in Phelps County.

1. According to the Heart Disease Profile, what is the frequency and rate of hospitalizations due to heart disease in Phelps County?  Which years of data were included in this statistic?  Phelps County had 3,742 hospitalizations due to heart disease for 2007-2011.  The age-adjusted rate for this time period was 159.0 heart disease hospitalizations per 10,000 residents.
2. What were the total charges for hospital utilization due to diseases of the heart?  The total hospital charges for diseases of the heart were \$27,548,649 for 2011.
3. What percentage of adult residents in the Central Region, which contains Phelps County, are estimated to have incorrectly answered survey questions about the signs and symptoms of heart attack?  (The source of this indicator is the Behavioral Risk Factor Surveillance System, which does not provide county-level data.  The regional percentage is provided on county-level Profiles as a proxy.)  Is this statistically significantly different from the state percentage?  86.6% of adult Central Region residents were estimated to have incorrectly answered survey questions about the signs and symptoms of heart attack during 2009.  This percentage is not statistically significantly different from the state estimate of 84.5%.
4. According to the Stroke Profile, what is the Phelps County death rate from strokes and other cerebrovascular diseases?  How does the county rate compare to the state rate?  Phelps County lost 344 residents due to strokes and other cerebrovascular diseases during the 2001-2011 time period.  The age-adjusted death rate for this time period was 66.2 per 100,000 residents.  The state rate for the same time period was 51.7.  Phelps County’s stroke death rate was statistically significantly higher than the state rate.
5. Use the Comparison Bar Graphs feature to compare the stroke/other cerebrovascular disease hospitalization rate in Phelps County to the rates of its neighboring counties – Crawford and Pulaski.  How does Phelps County compare to Crawford and Pulaski?  Do any of the counties have a rate that is statistically significantly different from the state rate?  Phelps County has the highest rate of stroke hospitalizations among these three counties, while Crawford County has the lowest rate.  Pulaski falls in the middle.  Crawford County’s stroke hospitalization rate is statistically significantly lower than the state rate, but the other counties are not significantly different from the state.

### Issue #11

After attending the MICA trainings, you go back to your office in Cedar County and begin to explore the 2011 County-Level Study – Health and Preventive Practices Profile.  During your exploration, you find that your county has a COPD (chronic obstructive pulmonary disease) diagnosis rate that is significantly higher than the state’s rate.  You immediately discuss this issue with your supervisor and request funding to combat this problem.  Unfortunately, no local funding is currently available.  After completing further research, you discover that some neighboring counties also fall within the first quintile, or the top 20 percent of all Missouri counties, for COPD diagnosis rates.  You approach these counties about forming a coalition and decide to write a grant to outside funders in order to address this problem in your area.  Use the 2011 County-Level Study – Health and Preventive Practices Profile to gather the following data needed in your grant application.

What was the age-adjusted rate of Cedar County residents who had ever been told they had COPD, emphysema, or chronic bronchitis?  15.8 percent [Navigate to the 2011 CLS – Health and Preventive Practices Profile for Cedar County.  Then select the age-adjusted link in the upper right corner.]

What neighboring counties also fell within the first quintile for this indicator?  (HINT:  Remember to use the age-adjusted prevalence.)  Dade and St. Clair [Navigate to the 2011 CLS – Health and Preventive Practices Profile for Missouri.  Select the age-adjusted link in the upper right corner.  Then select the COPD map icon under the Download Indicator Data column.]

What were these counties’ age-adjusted rates for this indicator?  14.7 percent (Dade) and 19.9 percent (St. Clair) [Scroll down to the data table below the map.]

Were these rates significantly higher than the Missouri rate? Dade’s prevalence is not significantly different from Missouri’s prevalence, but St. Clair’s prevalence is significantly higher than Missouri’s.  [Navigate to the 2011 CLS – Health and Preventive Practices Profiles for Dade County and St. Clair County and check the State Significance column.]

Create a graphic comparing the COPD rates for these three counties to the state rate.
Which chart type would best compare these rates?  A bar (or column) chart
Which Profile feature will assist you in creating this graphic?  From the Missouri age-adjusted Profile, choose the Microsoft Excel icon under the Download Indicator Data column.  After the data file opens, select the appropriate geographies and use Excel’s chart tools to generate a graphic such as the one shown below.

In your grant application, you note that you plan to evaluate your program when new data become available in order to determine whether there has been a significant change in the age-adjusted prevalence of COPD diagnoses.  Which County-Level Study Profile statistics could you use to determine significance?  The confidence intervals provided on the CLS Profiles can be used to determine significance.  Alternatively, if future County-Level Study Comparison Profiles are provided, these tools report significant change from one version of the CLS to the next.

### Issue #10

You are collecting data on various death rates in Pulaski County and Missouri.  You need to report and cite these rates.  Refer to the Q&A section of this newsletter to see example citations and links to additional resources for citing sources.

1. Use the Unintentional Injury Profile to find the state’s motor vehicle accident death rate for the 2002-2012 time period.  Write a sentence or two about this rate and provide an in-text citation.

For 2002-2012, the Missouri age-adjusted death rate from Motor Vehicle Traffic accidents was 16.7 per 100,000 residents.  This rate was based on 10,869 Missouri resident deaths (MODHSS, Unintentional Injury Profile).

Create a bibliography entry for this source.

MODHSS (Missouri Department of Health and Senior Services).  Community Data Profiles.  In Unintentional Injury Profile.  Retrieved 2014, July 1, from https://webapp01.dhss.mo.gov/MOPHIMS/ProfileHome.

1. Use the MICA datasets to find the 2010 cancer death rate for Pulaski County.

In which MICA did you find this information?
Death MICA or Chronic Disease (Deaths) MICA

Pulaski County’s 2010 age-adjusted cancer death rate was 166.2 per 100,000 residents (MODHSS, Death MICA).

OR

Pulaski County’s 2010 age-adjusted cancer death rate was 166.2 per 100,000 residents (MODHSS, Chronic Disease MICA).

Prepare a bibliography entry for your source.

MODHSS (Missouri Department of Health and Senior Services).  MICA.  In Death MICA.  Retrieved 2014, May 19, from https://webapp01.dhss.mo.gov/MOPHIMS/MICAHome.

OR

MODHSS (Missouri Department of Health and Senior Services).  MICA.  In Chronic Disease MICA.  Retrieved 2014, May 19, from https://webapp01.dhss.mo.gov/MOPHIMS/MICAHome.

### Issue #9

As an employee of the Bates County Health Department, you are interested in changes in preventive health behaviors during recent years.  You decide to use the 2007-2011 County-Level Study (CLS) Comparison Profiles to analyze changes among Bates County residents.

1. What is the 2011 estimated prevalence for no leisure-time physical activity?  26.7%
What was the change in prevalence for no leisure-time physical activity between 2007 and 2011? -5.2% (or a 5.2% decrease)
Was this change in prevalence statistically significant? No, the 2011 prevalence is not significantly different from the 2007 prevalence.

2. What is the 2007 estimated prevalence for consumption of fruits and vegetables less than five times per day?  78.3%
What is the 2011 estimated prevalence?  91.9%
What was the percentage change between these two years?  13.6% (or a 13.6% increase)
You decide to compare the change in Bates County to the change in Missouri.  How did the state prevalence for this indicator change between 2007 and 2011?  The Missouri prevalence statistically significantly increased by 10.5% (from 77.0% in 2007 to 87.5% in 2011).
You decide to compare the change in Bates County to the change in the Kansas City Metro Region (which includes Bates County).  How did the regional prevalence for this indicator change between 2007 and 2011? The Kansas City Metro Region prevalence significantly increased by 12.8% (from 75.0% in 2007 to 87.9% in 2011).

3. What is the Bates County 2011 estimated prevalence for smoking not allowed in the home? 64.5%
What was the change in prevalence for smoking not allowed in the home between 2007 and 2011?  9.5% (or a 9.5% increase)
Was this change in prevalence statistically significant?  No, the 2011 prevalence is not statistically significantly different from the 2007 prevalence.
In which Profile did you find this information?  County-Level Study 2007-2011 Comparison Secondhand Smoke Profile

4. Your supervisor asks you to briefly summarize the 2007-2011 changes in the Bates County prevalence estimates for “Current cigarette smokers who made a quit attempt in past year” and “Current smokers who intend to quit in next 6 months.” The prevalence of current smokers who made a quit attempt in the past year decreased from 70.9% in 2007 to 30.5% in 2011, while the prevalence of current smokers who intend to quit in the next 6 months decreased from 79.1% to 42.9%.  The decreases for these two indicators are statistically significant and reveal meaningful decreases in prevalence between the two CLS surveys.  The Bates County Health Department may need to increase tobacco cessation efforts.

### Issue #8

 Health Indicator Data Source Most Recent Rate Time Period Type of Rate/Constant Stroke Mortality Death MICA 48.5 2011 1-Year/100,000 Leading Causes of Death Profile 48.7 2001-2011 11-Year/100,000 Stroke Profile 48.7 2001-2011 11-Year/100,000 Women’s Health Profile 51.6 (females) 1999-2009 11-Year/100,000 Chronic Disease Comparisons Profile 51.6 1999-2009 11-Year/100,000 Stroke Prevalence (Adults 18 years and older) Stroke Profile 2.9 (Central Region rate) 2011 1-Year/100 Stroke Hospitalizations Inpatient Hospitalization MICA 22.1 2011 1-Year/10,000 Inpatient Hospitalization Profile 23.8 2009 1-Year/10,000 Chronic Disease Comparisons Profile 26.7 2005-2009 5-Year/10,000 Stroke Profile 24.0 2007-2011 5-Year/10,000 Stroke Emergency Room Visits Emergency Room MICA 0.3 2011 1-Year/1,000 Emergency Room Profile 0.3 2011 1-Year/1,000 Chronic Disease Comparisons Profile 0.5 2005-2009 5-Year/1,000 Stroke Profile 0.4 2007-2011 5-Year/1,000 Stroke Hospital Charges (in \$) Hospital Discharges, Charges & Days of Care MICA \$9,356,325 2011 1-Year Stroke Risk Factors: Current Smoking Stroke Profile 18.0 2007 1-Year/100 High Blood      Pressure Stroke Profile 26.2 2007 1-Year/100 High Cholesterol Stroke Profile 33.5 2007 1-Year/100

Halloween Costumes

Front Row:
Becca Mickels – Toddler
Whitney Coffey – The Cat in the Hat
Becky Chitima-Matsiga – Rock Bridge High School Football Player

Back Row:
Evan Mobley – Corporate Lumberjack
Andy Hunter – African Prince

### Issue #7

Motor vehicle accident death rates are higher in rural regions compared to urban areas. Use the Leading Causes of Death Profile to answer the following questions related to Motor Vehicle Accident Deaths in Cass County and Bates County. These two counties are adjacent to each other in west-central Missouri. By some definitions Cass is considered urban while Bates is considered rural.

1. What is the age-adjusted motor vehicle accident death rate for Cass County?
16.6 per 100,000 population

2. Is the Cass County rate significantly different from the state rate?
No

3. What is the age-adjusted motor vehicle accident death rate for Bates County?
28.9 per 100,000 population

4. Is the Bates County rate significantly different from the state rate?
Yes – The Bates County rate is significantly higher than the state rate.

5. What time period was used to calculate these rates?
2001-2011

A long time period was needed in order to generate statistically stable rates.  There are relatively few motor vehicle accident deaths in most counties.  For example, there were only 54 deaths in Bates County during the eleven-year time period from 2001-2011.  In Clay County, which has a larger population and is considered to be more urban, there were only 165 deaths during the eleven-year time period, or roughly 15 deaths per year.

7. What constant was used in calculating these rates?
These rates are per 100,000 population (residents).

8. What DHSS tool could be used to determine if there is a statistically significant difference between Cass County and Bates County?
The confidence intervals feature in the Death MICA can be used to determine statistical significance at either a 95% or a 99% confidence level.  If the intervals overlap, the rates are considered to be statistically similar, or not significantly different.  If the intervals do not overlap, the rates are considered to be statistically significantly different.  (The Bates County rate is significantly higher at the 95% confidence level but not at the 99% confidence level.)

95% CI:  Bates 21.5 to 38.0 versus Cass 14.2 to 19.4
99% CI:  Bates 19.6 to 41.1 versus Cass 13.4 to 20.3

### Issue #6

You work for the Washington County Health Department and are interested in applying for a grant to prevent tobacco use and support tobacco cessation programs in your county.  Use the 2011 County-Level Study Profiles to research tobacco use in Missouri.

The answers to questions 1-3 are found on the Health and Preventative Practices Profile.

1. What is the Washington County prevalence of current cigarette smoking?  36.4%
Is the Washington County prevalence statistically significantly different from the state prevalence?  Yes – significantly higher

2. What is the Central Region (which includes Washington County) prevalence of current cigarette smoking?  22.5%
Is the Central Region prevalence statistically significantly different from the state prevalence?  No

3. Use the Download Indicator Data column (available only on the Missouri Profile) to determine which region has the highest current cigarette smoking prevalence.  Southeastern Region (27.5%)
Which region has the lowest prevalence?  St. Louis Metro Region (20.0%)
Which county/city has the highest prevalence of current cigarette smoking? Pemiscot County (45.5%)
Which has the lowest? Scotland County (8.4%)

The answers to questions 4-6 are found on the Tobacco Use Profile.

1. What is the Washington County prevalence of former cigarette use?  22.1%
Is the Washington County prevalence statistically significantly different from the state prevalence?  No

2. What is the Washington County prevalence of smokeless tobacco use?  7.2%
Is the Washington County prevalence statistically significantly different from the state prevalence?  No

3. What are the Washington County prevalence rates for belief that smoking cigarettes causes the following conditions?
 Condition Prevalence Rate Heart attack 76.5% Colon cancer 36.1% Stroke 67.5% Low-birth weight 78.4% Impotence 41.5%

Visit http://health.mo.gov/data/mica/MICA/solutions.html to check the solution.

### Issue #5

You are researching the use of caesarean sections in Missouri.  You would like to determine which mothers are at highest risk for a caesarean delivery.  Use the Birth MICA to complete the following tables and determine which demographics groups are at significantly higher risk for caesarean deliveries based on 2009 data.

 Number Rate 95% Confidence Interval Whites 20,494 32.3 31.9 to 32.6 African Americans 3,967 32.9 32.1 to 33.8 American Indians/Alaskan Natives 107 30.1 25.5 to 35.0 Asians/Native Hawaiians/Pacific Islanders 677 33.7 31.6 to 35.8 Groups at significantly higher risk: None – The confidence intervals overlap.
 Number Rate 95% Confidence Interval Hispanic 1,184 27.6 26.3 to 29.0 Non-Hispanic 24,310 32.6 32.3 to 33.3 Group at significantly higher risk: Non-Hispanics, when compared to Hispanics
 Number Rate 95% Confidence Interval 10-14 20 27.0 18.2 to 38.1 15-17 509 21.5 19.9 to 23.2 18-19 1,527 24.9 23.9 to 26.0 20-24 6,300 28.7 28.1 to 29.3 25-29 7,612 32.0 31.4 to 32.6 30-34 6,039 36.9 36.2 to 37.7 35-39 2,865 41.9 40.8 to 43.1 40+ 643 46.7 44.1 to 49.4 All Ages 25,517 32.4 32.0 to 32.7 Groups at significantly higher risk: Ages 30+ are at significantly higher risk than the overall state population.
 Number Rate 95% Confidence Interval Married 15,656 33.6 33.2 to 34.0 Not married 9,858 30.6 30.1 to 31.1 Group at significantly higher risk: Married women, when compared to not married women

### Issue #4

1. Highest - Madison -170.9       Lowest – Lewis – 17.4
2. Yes to both
3. No, CI’s overlap
4. Saline (2709)
5. Crawford
6. Open Wounds and Strains and Sprains

### Issue #3

Use the Birth MICA to answer the following questions related to premature births in Jackson County and the Kansas City metropolitan area.

1. Using the 2008 and 2009 data years, what is the premature birth rate for Jackson County?  12.2% of live births (or 12.2 per 100 live births  What is the rate for the State of Missouri? 12.6% of live births (or 12.6 per 100 live births)
2. Use 95% confidence intervals to determine if the difference between your answers to Question 1 represents a statistically significant difference.  Is the Jackson County rate significantly higher than, significantly lower than, or not significantly different from the State of Missouri rate?  The Jackson County and State of Missouri rates are not significantly different.
3. Now calculate the premature birth rate using the same time period for a region that includes Jackson, Cass, Clay and Platte Counties.  What is the rate?  11.8% of live births (or 11.8 per 100 live births)  Is this rate significantly higher than, significantly lower than, or not significantly different from the state rate at a 95% confidence level?  This rate is significantly lower than the state rate.
4. If we change the confidence level to 99%, does that change the answer to Question 3?  If so, how?  No
5. Now use the Kansas City ZIP Code option on the Birth MICA to determine which ZIP Code in the range from 64011 through 64030 had the highest number of premature births for 2008-2009.  64030 (109)  Do you get the same answer if you look for the ZIP Code with the highest rate of premature births?  If the answer is not the same, which ZIP Code has the highest rate?  No – 64024 (15.5%)

### Issue #2

As a health educator in Miller County, you are preparing some materials for American Heart Month.  You would like to include the prevalence of current high blood pressure in your county, because this is one of the most important risk factors for heart disease.  After reviewing the MICA suite of tools, you remember that the County-Level Study is the only source of county-specific prevalence rates for many risk factors and conditions.  Use the 2007 Health and Preventive Practices Profile to answer the following questions about current high blood pressure in Miller County and the state.

1. What is the age-adjusted rate for current high blood pressure in Miller County?  23.6% (Use the Age-adjusted weighted percent link in the upper right corner of the screen to view age-adjusted weighted percents rather than weighted percents.)
2. How does this rate compare to the state rate?  The Miller County rate is significantly higher than the state rate.
3. How does it compare to the rate for the Central Region, which contains Miller County?  The Miller County rate is significantly higher than the Central Region rate.
4. While reviewing the current high blood pressure map from the Missouri 2007 Health and Preventive Practices Profile, you notice that there are a few pockets or clusters of counties with high rates.  In general, where are these clusters located?  Use the Select a different geographical area link at the top of the screen to view the Missouri Profile.  Choose the Missouri icon in the Current high blood pressure row to view the map.  A large cluster exists in the Southeastern part of the state and extends into South Central Missouri and towards the St. Louis Metro area.  There is also a small cluster in the Central part of the state that includes only Miller County and Morgan County.
5. From the Missouri Profile, how could you determine the number of counties that have significantly higher or significantly lower rates than the state overall?  Select either the Microsoft Excel icon or the Adobe PDF icon in the Download Indicator Data column.  Both options provide the number of interviews, the weighted (or age-adjusted weighted) percent, significance compared to the region, and significance compared to the state for every geographic area for which data are available.  In Microsoft Excel, you could sort the list by state significance to more easily determine the number of counties in each category.
6. You want to know if the prevalence of current high blood pressure is increasing or decreasing in Miller County.  Use the 2003-2007 CLS Comparison – Health and Preventive Practices Profile to determine how the Miller County rate changed during that time period.  (NOTE:  The 2007 Miller County rate on the Comparison Profile will differ from your answer to #1.  Fewer interviews were completed in 2003, so Miller County data was combined with Camden County data to produce a more stable and reliable bi-county rate.)  What was the 2003-2007 percentage change for Camden-Miller?  3.42% increase  Was this change statistically significant, and, if so, how?  This change was not statistically significant.

### Issue #1

You have been asked to write an article about methods of cataract prevention.  You decide to use the Procedures MICA to find statistics on the number of older adults who received cataract treatment.  Set up your query to determine which of the following groups of older adults underwent more cataract procedures in Missouri during 2008:  White Males, White Females, African-American Males, or African-American Females.  What settings did you use?

Step One:

Row variable Race (or Sex)

Step Two:

Column variable Sex (or Race)

Step Three (Optional):

Race All Races, Ethnicity All Ethnicities, Sex All,
Age 65 and Over, Pay Source All Pay Sources, Setting All Settings

Step Four:

Year(s) of Interest 2008

Step Five:

Statewide/County/Cities Missouri

Step Six:

Indicator variable Operations on the eye

Step Seven:

Statistics to be displayed Frequencies and Rates,
Standard population 2000 Population,
Confidence intervals No Confidence Intervals