Analysis of Demographic Major written Assessment 4

Assessment 4

SILOs

• Comprehend the fundamental principles of epidemiology and biostatistics (SILO 1).
• Explain how the principles of epidemiology and biostatistics can be applied in public health (SILO 2).
• Explain, differentiate, and apply fundamental concepts of epidemiology and biostatistics (SILO 3).
• Recognise, generate, interpret and communicate descriptive and basic inferential statistics (SILO 5).

Task Details

Prepare a written briefing document. Using the dataset provided, identify demographic, social and behavioural factors that are associated with routine check-up attendance.

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 analyse a subset of variables (as indicated below) and describe the association between these variables and routine checkup attendance and highlight the 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 healthrelated 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.

Assessment Requirements Brief Summary

Assessment 4 requires students to prepare a written public health briefing document using a provided dataset derived from the Behavioral Risk Factor Surveillance System (BRFSS). The core aim is to identify and explain demographic, social, and behavioural factors associated with routine 12-monthly medical check-up attendance.

Students are expected to analyse selected variables and describe their association with preventive health behaviour, particularly focusing on groups with lower rates of routine check-ups. These findings are then used to inform targeted public health campaign recommendations.

Key Pointers to Be Covered in the Assessment

• Understanding core principles of epidemiology and biostatistics
• Application of epidemiological concepts to a real-world public health scenario
• Identification and interpretation of demographic, social, and behavioural variables
• Use of descriptive statistics and basic inferential statistics
• Clear communication of findings in a written briefing format
• Interpretation of data to support public health decision-making

Aligned Subject Intended Learning Outcomes (SILOs)

• SILO 1: Comprehend fundamental principles of epidemiology and biostatistics
• SILO 2: Apply epidemiological and biostatistical principles in public health contexts
• SILO 3: Explain, differentiate, and apply key epidemiological and statistical concepts
• SILO 5: Recognise, generate, interpret, and communicate descriptive and basic inferential statistics

Academic Mentor’s Step-by-Step Approach

The academic mentor guided the student through a structured and progressive process to ensure both conceptual understanding and correct application of analytical skills.

Step 1: Understanding the Public Health Scenario

The mentor began by clarifying the purpose of the assessment linking preventive healthcare behaviours to public health outcomes. The scenario was discussed to help the student understand why routine check-ups matter and how epidemiological data informs health campaigns.

Step 2: Familiarisation with the BRFSS Dataset

The student was guided through the BRFSS dataset structure, including variable types and population characteristics. Emphasis was placed on identifying relevant demographic, social, and behavioural variables aligned with routine check-up attendance.

Step 3: Applying Epidemiological Concepts

The mentor explained key epidemiological principles such as:

• Exposure and outcome variables
• Associations and patterns in population health
• Risk and protective factors

These concepts were applied directly to the dataset to ensure theoretical understanding translated into practical analysis.

Step 4: Statistical Analysis and Interpretation

The mentor supported the student in:

• Generating descriptive statistics to summarise routine check-up attendance
• Interpreting patterns across demographic and behavioural groups
• Using basic inferential reasoning to explain observed associations

The focus remained on interpretation, not just calculation, ensuring statistical findings were meaningful in a public health context.

Step 5: Identifying Priority Groups

Using the analysed data, the mentor guided the student to identify populations with lower routine check-up rates, reinforcing how data-driven insights inform targeted health interventions.

Step 6: Structuring the Written Briefing Document

The mentor assisted in structuring the briefing document clearly and professionally, ensuring:

• Logical flow of findings
• Clear communication of statistical results
• Evidence-based recommendations aligned with the campaign objective

Outcome Achieved and Learning Objectives Covered

Final Outcome

• A well-structured public health briefing document
• Clear identification of demographic, social, and behavioural factors influencing routine check-up attendance
• Data-driven identification of target populations for preventive health campaigns
• Accurate interpretation and communication of statistical findings

Learning Objectives Successfully Addressed

• Application of epidemiology and biostatistics to real-world public health issues
• Interpretation of population health data
• Use of descriptive and basic inferential statistics
• Development of analytical and written communication skills
• Translation of data insights into public health strategy recommendations

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