Patterns of Non-Infectious Disease (HSC SSCE Biology): Revision Notes

Patterns of Non-Infectious Disease

Introduction to epidemiology

When scientists observe that a particular disease appears to be increasing in a population, they need to answer important questions: Are there patterns to this disease? What causes it? How can we prevent it? To answer these questions, researchers conduct epidemiological studies.

What is epidemiology?

The term 'epidemiology' comes from two Greek words: epi (meaning 'upon') and demos (meaning 'people' or 'populace'). Literally, it means the study of 'that which is upon people'. While doctors focus on disease in individual patients, epidemiologists study disease across entire populations.

The World Health Organisation (WHO) defines epidemiology as:

The study of the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems.

What do epidemiologists study?

Epidemiologists can investigate both infectious and non-infectious diseases, as well as other health events such as:

• Suicides
• Car accidents
• Work-related injuries
• Chronic diseases like cancer and diabetes

Key purposes of epidemiological studies

Epidemiological research helps public health authorities to:

1. Identify causes - Determine what factors contribute to disease development
2. Target populations - Identify which groups are most affected
3. Develop interventions - Create strategies to prevent disease occurrence
4. Allocate resources - Direct limited public health funding to where it's needed most
5. Evaluate strategies - Assess whether current control measures are working effectively

Analysing patterns of non-infectious disease

The role of epidemiological studies

Epidemiological studies play a crucial role in identifying patterns in disease through analysis of:

• Incidence - The number of new cases diagnosed in a specific time period
• Distribution - How disease is spread across different populations and locations
• Prevalence - The total number of people living with the disease at a given time
• Mortality rates - The number of deaths from the disease

These studies also investigate which population groups face higher risks and determine the most effective strategies for disease control.

Methods of data analysis

Researchers use accepted scientific and mathematical models to statistically analyse collected data. This analysis provides information about:

• Trends for the overall population
• Patterns in specific population subsets (males vs females, different age groups, different ethnic backgrounds, different geographic locations)

Presenting epidemiological data

Data is typically presented in multiple formats to help identify trends and patterns:

• Tables - Allow precise comparison of numerical values
• Graphs - Reveal visual trends over time or between groups
• Age-specific rates - Show how disease affects different age groups
• Age-standardised rates - Allow fair comparison between populations with different age structures

Case study: Colorectal cancer patterns in Australia

Understanding colorectal cancer

Colorectal cancer (also called bowel cancer) includes all cancers affecting the colon and rectum. Understanding its epidemiological patterns helps identify risk factors and improve prevention strategies.

Risk factors

Hereditary factors:

• 25% of cases have some hereditary influence
• 75% of cases have no family history

Age:

• Sharp increase in incidence after age 50

Lifestyle and environmental factors:

• Smoking and alcohol consumption
• Eating red meat, especially when charred
• Consuming processed meats (preserved, salted, cured, or smoked)
• Being overweight or obese
• Lack of physical activity

Age-specific incidence and mortality patterns

Analysis of age-specific data for Australia in 2017 reveals several important patterns:

Age patterns:

• Incidence and mortality rates are very low in young age groups
• Both measures increase dramatically with age
• The highest rates occur in people aged 85 and above
• The sharp rise begins around age 50, confirming age as a major risk factor

Gender differences:

• Males consistently show higher incidence rates than females across all age groups
• Males also have higher mortality rates than females
• The gap between males and females widens in older age groups

Trends over time (1968-2014)

Examining long-term trends reveals important changes in colorectal cancer patterns:

Incidence trends (1982-2013):

• Incidence rates increased from the 1980s through the mid-1990s
• Rates have plateaued or slightly decreased since around 2000
• Males continue to show higher rates than females
• The gap between male and female incidence has narrowed slightly in recent years

Mortality trends (1968-2014):

• Mortality rates have shown a consistent downward trend over the entire period
• Death rates have approximately halved since the late 1960s
• This decline is observed for both males and females
• Males still have higher mortality than females, but the difference is decreasing

Reasons for declining mortality despite stable incidence:

• Earlier detection through screening programmes
• Improved surgical techniques
• More effective treatment options
• Better post-operative care
• Increased public awareness leading to earlier presentation

Survival rates

The 5-year relative survival rate indicates the percentage chance that someone diagnosed with colorectal cancer will still be alive five years later.

Key trends (1984-2013):

• Survival rates have improved dramatically over three decades
• In 1984-1988, approximately 48-50% of patients survived 5 years
• By 2009-2013, this had increased to approximately 68-70%
• Males and females show very similar survival rates
• The improvement has been steady and consistent

Factors contributing to improved survival:

• Better treatment protocols
• More effective chemotherapy drugs
• Advances in surgical techniques
• Earlier stage diagnosis through screening
• Improved supportive care

Global patterns of colorectal cancer

Worldwide data from 2012 shows significant variation in colorectal cancer burden:

Global overview:

• 1.36 million new cases worldwide
• 694,000 deaths
• 3.54 million people living with the disease (5-year prevalence)

Regional disparities:

• More developed regions show much higher incidence rates
• Less developed regions have lower incidence but higher mortality relative to incidence
• This suggests differences in both risk factors and access to treatment

Gender patterns globally:

• Males have higher incidence than females worldwide (746,000 vs 614,000 cases)
• Males also have higher mortality (374,000 vs 320,000 deaths)
• This pattern is consistent across most world regions

Geographic analysis reveals:

Highest incidence regions:

• Australia/New Zealand
• Western Europe
• Northern Europe
• Northern America

Lowest incidence regions:

• Western Africa
• Middle Africa
• South-Central Asia

These patterns correlate strongly with:

• Economic development
• Dietary patterns (high meat consumption in developed nations)
• Lifestyle factors (physical inactivity, obesity)
• Age structure of populations

Indigenous vs non-Indigenous Australians

Comparing colorectal cancer patterns between Indigenous and non-Indigenous Australians reveals important health disparities:

Incidence rates (2008-2012):

• Indigenous and non-Indigenous Australians show similar age-standardised incidence rates
• Both groups experience approximately 50-55 cases per 100,000 population

Mortality rates (2010-2014):

• Indigenous Australians have a lower age-standardised mortality rate
• Non-Indigenous: approximately 15.5 deaths per 100,000
• Indigenous: approximately 12 deaths per 100,000

Possible explanations for mortality difference:

• Younger age structure of Indigenous population
• Different distribution of cancer stages at diagnosis
• Access to treatment services
• Other competing causes of mortality in Indigenous populations

Key epidemiological concepts

Understanding rates

Incidence rate:

• Measures new cases diagnosed during a specific time period
• Usually expressed per 100,000 population
• Helps identify if a disease is becoming more or less common

Prevalence:

• Total number of people living with the disease at a specific time
• Can be measured over different time periods (e.g., 1-year prevalence, 5-year prevalence)
• Affected by both incidence and survival rates

Mortality rate:

• Number of deaths from the disease in a specific time period
• Usually expressed per 100,000 population
• Indicates the lethality of the disease

Age-specific vs age-standardised rates

Age-specific rates:

• Show disease rates within specific age groups (e.g., 45-49 years, 50-54 years)
• Useful for identifying which age groups are most affected
• Help target screening and prevention programmes

Age-standardised rates:

• Adjust for differences in age structure between populations
• Allow fair comparison between populations with different age distributions
• Essential when comparing trends over time or between countries

Practical applications of epidemiological data

Informing public health strategies

Analysis of colorectal cancer patterns has led to:

Screening programmes:

• National Bowel Cancer Screening Programme in Australia
• Targets people over 50 (when risk sharply increases)
• Free screening kits sent to eligible age groups

Prevention campaigns:

• Public health messages about diet and lifestyle
• Emphasis on physical activity and healthy weight
• Warnings about processed meat consumption
• Anti-smoking campaigns

Resource allocation:

• Directing research funding to improve treatment
• Planning healthcare services based on projected disease burden
• Training specialists in areas with growing need

Predicting future trends

Based on current patterns, epidemiologists can predict:

• Which population groups will need more services
• How many treatment facilities will be required
• The likely impact of aging populations on disease burden
• The potential benefits of prevention programmes

Remember!