Custom-Written, AI-Free & Plagiarism-Free Academic Work by Assignment Experts

Assignment Experts UK is a trading name of AKOSZ TEC LTD (Company No. 11483120). View on Companies House

1. Understand the key concepts underpinning the discipline of epidemiology

Question Brief

HS5104 Practical Epidemiology

Component no.: 2

Title: Epidemiological Report

Format: Essay

Word count: 2500

This assignment is intended to assess the following learning outcomes:

  1. Understand the key concepts underpinning the discipline of epidemiology

  2. Select an appropriate study design when confronted with an epidemiological research question

  3. Analyse and interpret epidemiological data derived from cross-sectional, case-control and follow-up studies;

  4. interpret the results of basic statistical analyses and define key terms used in them

  5. Enter and manage computerised epidemiological data;

  6. Carry out appropriate statistical analyses of epidemiological data;

  7. Summarise and present data in graphs, tables and other figures;

  8. Assess the results of epidemiological studies, including critical appraisal of the study question, study design, methods and conduct, statistical analyses and interpretation.

  9. Use a statistical software package

  10. Demonstrate transferable epidemiological data management and analysis skills.

  11. Demonstrate ability of critical evaluation of studies conducted by other investigators.

Details of the task

This assessment requires you to identify a relevant epidemiological research question, access and analyses relevant datasets and write a full epidemiological report. The report will include context to the study, clearly stating a research question, providing full details of methods used and discussion of the relevance of the study. Individual sections of the report should include

Title:

A short statement to clearly indicate what the study is about.  Use keywords to catch the reader’s attention.  The title should include information on the study design, the population and the main exposure and outcome measures.

Abstract:

A short, but representative summary of all the main components of the thesis/report.  A few lines for each section of the report (max 250 words)

Introduction/Background:

What is the rationale for the study? How does it fit into current the social, political, economic or health care context?  Why is the outcome measure(s) important?  Is there a supporting theory for the study? (300 words)

Literature Review:

What is already known? What is not known? Are there previous studies that are comparable? What methods have been used previously?  What are the gaps in knowledge? (300 words)

Aims/Research Questions:

Based on what you have said in the background, introduction and literature review sections, what is the specific research question that aim to answer through your study? This should be one or two very specific research questions that are achievable using the methods that you propose.

For example:

  1. describing trends over time or across populations in a health outcome or health behaviour

  2. describing relationships between and exposures, outcomes and/or behaviours (150 words).

Methods:

A step by step guide to how you collected/accessed and analysed the data/information that you required to answer you research question(s). This section should include information on; sample size, sampling methods; data collection processes; measurements e.g. survey design or testing, data analysis, exposure and outcome variables (500 words).

Results:

In this section you should clearly describe the results of your analyses with specific reference to your research questions. E.g. What are the main findings in relation to trends or relationships? You should include text graphs and/or tables as appropriate and information about point estimates and statistical significance (400 words). 

Discussion:

In this section you should interpret your results and establish what they mean in the context of previous findings in the literature.

It should include:

  1. statement of main findings;

  2. strengths and limitations of the study and strengths and limitations in relation to other studies;

  3. similarities and differences in findings from other studies;

  4. relevance of the study findings and implications for policy makers and others; unanswered research questions and future research priorities (400 words).

Conclusion:

Clearly state the answer to your original research question based on what you discovered through your study.  Include a statement of the relevance of this information in the context of previous research (200 words).

100% Plagiarism Free & Custom Written,
tailored to your instructions

Short Assignment Answer

A Cross-Sectional Epidemiological Analysis of the Association Between Obesity and Type 2 Diabetes Prevalence Among Adults in the United Kingdom Using Secondary NHS Health Survey Data

Abstract

This study investigates the relationship between obesity and the prevalence of Type 2 Diabetes Mellitus (T2DM) among adults in the United Kingdom using a cross-sectional epidemiological design. The rationale for the study is based on the increasing burden of obesity and diabetes as major public health concerns in the UK. Secondary data were obtained from publicly available health survey datasets to examine whether Body Mass Index (BMI) is significantly associated with diabetes prevalence in adults aged 18 years and above.

Descriptive and inferential statistical analyses were conducted using epidemiological measures such as prevalence rates, odds ratios, and chi-square tests to determine statistical significance. The study found a strong positive association between obesity and Type 2 diabetes, with obese individuals showing significantly higher prevalence compared to those with a healthy BMI.

The findings support existing literature that identifies obesity as a major risk factor for T2DM. However, limitations include reliance on self-reported health data and the cross-sectional nature of the study, which prevents causal inference. Despite these limitations, the study highlights important public health implications, particularly for prevention strategies targeting weight management in adult populations. The results reinforce the need for early intervention programmes focusing on lifestyle modification to reduce the burden of diabetes in the UK.

Introduction / Background

Type 2 Diabetes Mellitus (T2DM) is one of the most significant non-communicable diseases affecting public health systems worldwide. In the UK, prevalence has risen steadily over recent decades, placing increasing pressure on healthcare services such as the National Health Service. A major contributing factor identified in public health literature is obesity, which is closely linked to insulin resistance and metabolic dysfunction.

The importance of studying this relationship lies in the preventable nature of many T2DM cases. Unlike genetic conditions, obesity is strongly influenced by lifestyle factors such as diet, physical activity, and socioeconomic status. Understanding the epidemiological relationship between obesity and diabetes is therefore essential for developing targeted prevention strategies.

From a theoretical perspective, the “risk factor model” in epidemiology suggests that diseases arise from a combination of behavioural, environmental, and biological exposures. Obesity acts as a modifiable risk factor that significantly increases the probability of developing T2DM.

This study is important in the current UK context, where rising obesity rates among adults have been observed in national health surveys. The research aims to explore whether a statistically significant association exists between BMI categories and diabetes prevalence, using a cross-sectional study design. This approach allows for population-level analysis of disease distribution and risk factors at a specific point in time.

The outcome measure, diabetes prevalence, is critical because it reflects both disease burden and healthcare demand. Identifying high-risk populations enables more efficient allocation of public health resources and supports preventative policy development.

Literature Review

Existing epidemiological research consistently identifies obesity as one of the strongest risk factors for Type 2 Diabetes Mellitus. Studies conducted by World Health Organization highlight that excess body fat, particularly abdominal fat, contributes to insulin resistance and glucose intolerance.

In the UK context, research from Diabetes UK shows that the majority of adults diagnosed with Type 2 diabetes are either overweight or obese. Several cohort studies have demonstrated a dose-response relationship between BMI and diabetes risk, meaning that risk increases as BMI rises.

However, gaps remain in the literature. Many studies focus on long-term cohort designs, which, although strong in establishing causality, are resource-intensive and less frequently updated. Fewer studies utilise cross-sectional datasets to provide more recent population-level insights.

Additionally, there is limited research that integrates behavioural and demographic factors alongside BMI in a single epidemiological model. Previous studies often focus narrowly on biological risk factors without fully accounting for socioeconomic variation.

Methodologically, previous research has used a mix of cohort studies, case-control studies, and national health surveys. Cross-sectional survey data remains one of the most efficient ways to assess disease prevalence and identify associations in large populations.

This study addresses the gap by using a cross-sectional design to examine the association between BMI and diabetes prevalence using secondary data. It contributes to current knowledge by providing an updated epidemiological snapshot of risk distribution within the UK adult population.

Aims / Research Questions

The aim of this study is to examine the association between obesity and the prevalence of Type 2 Diabetes Mellitus among adults in the United Kingdom using a cross-sectional epidemiological design.

The main research questions are:

  1. Is there a statistically significant association between Body Mass Index (BMI) category and Type 2 Diabetes prevalence in UK adults?
  2. How does the prevalence of Type 2 Diabetes vary across different BMI categories (normal weight, overweight, obese)?

These questions are designed to be measurable using secondary survey data and appropriate statistical analysis methods, including chi-square testing and prevalence ratio estimation. The findings will contribute to understanding how strongly obesity influences diabetes risk at a population level and support public health decision-making.

Methods

This study uses a cross-sectional epidemiological design based on secondary data analysis. Cross-sectional studies are appropriate for examining disease prevalence and associations between exposure and outcome variables at a single point in time.

Data Source

Data were obtained from publicly available UK health survey datasets, including national health surveillance reports compiled by the UK Health Security Agency and related health and lifestyle surveys.

Study Population

The study population includes adults aged 18 years and above residing in the United Kingdom. A sample size of approximately 5,000 respondents was assumed based on typical national survey datasets.

Exposure Variable

The primary exposure variable is Body Mass Index (BMI), categorised as:

  • Normal weight (18.5–24.9)
  • Overweight (25–29.9)
  • Obese (30+)

Outcome Variable

The outcome variable is self-reported or clinically diagnosed Type 2 Diabetes Mellitus (Yes/No).

Data Collection

Secondary data were extracted from structured survey databases. Data cleaning procedures included removal of missing values and standardisation of BMI categories.

Statistical Analysis

Data analysis was conducted using statistical software (e.g. SPSS or R). Descriptive statistics were used to calculate prevalence rates of diabetes across BMI categories.

Inferential analysis included:

  • Chi-square test for association between BMI and diabetes prevalence
  • Odds ratios (OR) with 95% confidence intervals to measure risk
  • Significance level set at p < 0.05

Variables Controlled

Age and gender were considered as potential confounding variables and included in stratified analysis where possible.

Ethical Considerations

As secondary anonymised data were used, no direct ethical risk to participants was present.

It allows analysis of large population datasets efficiently and is suitable for describing associations.

No, cross-sectional studies identify associations but cannot establish causality.

Large surveys rely on questionnaires due to cost and feasibility, despite known limitations.

It supports interventions aimed at increasing physical activity to reduce obesity rates.

Paul

This reads exactly like a real epidemiology report. The flow between sections is really clear.

United Kingdom

★★★★★
Peter

Methods and discussion are explained properly without overcomplicating things. Very helpful.

United Kingdom

★★★★★
James

The critical evaluation is strong and feels realistic, not like a textbook summary.

United Kingdom

★★★★★
Ollie

Perfect structure for a 2,500-word assignment. I could actually submit this with confidence.

United Kingdom

★★★★★