A generation ago, people used to see their doctor only when they were sick or dying. Today, preventative health care is becoming commonplace as people become more educated and empowered about their own health. Regular, routine medical check

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Scenario:

A generation ago, people used to see their doctor only when they were sick or dying. Today, preventative health care is becoming commonplace as people become more educated and empowered about their own health. Regular, routine medical check-ups can help find potential health issues before they become a problem. Early detection of problems gives the best chance for getting the right treatment quickly, avoiding any complications.

You have been employed as part of an active public health campaign that is aiming to increase routine 12-monthly check-ups. Your job is to identify groups of people with lower rates of check-ups in the last 12 months where a targeted campaign would be of most benefit.

The Behavioral Risk Factor Surveillance System (BRFSS) is a collaborative project between all of the states in the United States (US) and participating US territories and the Centers for Disease Control and Prevention (CDC). The BRFSS is a system of ongoing health-related telephone surveys designed to collect data on health-related risk behaviours, chronic health conditions and use of preventive services from the non-institutionalised adult population (≥18 years) residing in the United States. Using the prepared BRFSS data, identify demographic, social and behavioural factors that are associated with routine check- up attendance.

Dataset:

BRFSS 2024 data

Format:

Your written briefing document must consist of a 250-word executive summary and a detailed structured results section. This template will assist you with the format and information required.

Executive Summary (Marks: 25)

The 250-word summary should identify demographic, social and behavioural factors that are associated with routine check-up attendance in a statistically valid, clear and concise manner that can be understood by someone with minimal knowledge of epidemiology and biostatistics. You must identify a group or groups of people where a targeted campaign would be of most benefit.

Results:

The BRFSS:

  • A short summary of the study design of the BRFSS and a brief discussion of its limitations (no more than 250 words (Marks: 6)
  • Find a peer-reviewed primary quantitative research study in the literature that investigates the determinants of routine check-up attendance. Compare the designs between the study described in that paper and BRFSS (not more than 150 words). (Marks: 4)

Description of the population and analysis:

1) By analysing the BRFSS dataset, answer the following questions:

  • In your dataset, what percentage of participants reported routine check-up attendance? (Marks: 5)
  • Create a table of routine check-up attendance and 3 demographic factors, one of which must be binary, one numerical and one multi-category categorical (either nominal or ordinal). (Marks: 15)
    2) Examine the association between 4 social and/or behavioural factors and routine check-up attendance:
    • Each cell should contain the appropriate summary measure and 95% confidence interval
    • The final column in the table should contain the p-value for statistical tests of difference or independence (i.e., tests that we covered in week 6). Footnotes should be used to indicate which statistical tests were used.
  • In an appropriate manner, present the results of analysis into the effect of four social and/or behavioural factors on routine check-up attendance. You must analyse a binary, numeric, nominal and ordinal factor. (Marks: 20)
      • Variable name and data type
      • Name of measure  calculated
      • Results of statistical analysis performed
      • Statistical interpretation
      • The Stata output (including visible code) e.g.
    • For one of the identified factors, you should explore the possibility of confounding or effect modification by sex. (Marks: 10)
      • Perform appropriate analysis
      • Present STATA output (including visible code)
      • Report the results in a table
      • Interpret your result
    • Conduct a multivariable regression and present the results of the adjusted regression model by including the four factors you examined in your analysis of social and behavioural factors. (Marks: 10)
      • Present STATA output (including visible code)
      • Report the results in a table.
      • Interpret your result

For each factor you should report:

t test sample