Risk factors and multifactorial disease

A risk factor is something associated with an increased chance or rate of a disease. Risk factors can include aspects of lifestyle, such as diet or smoking, or substances present in the body or the environment.

A risk factor changes probability, not certainty. An exposed person may never develop the disease, while someone without that exposure may still develop it.

Association and cause

If a disease occurs more often in people exposed to a factor, the factor is associated with that disease. This association alone does not prove that the factor causes the disease: other differences between the groups may help explain the pattern.

For some risk factors, evidence also shows a causal mechanism: a way in which the factor produces changes that can lead to disease. For example, substances in tobacco smoke can damage cells in the lungs, contributing to the development of lung cancer. Other factors are associated with disease even though a cause-and-effect mechanism has not been proven.

Several factors and disease incidence

Many diseases are multifactorial: they result from the interaction of several factors rather than one single cause. For example, more than one lifestyle or environmental risk may contribute to a person’s chance of developing a disease. This helps explain why the same exposure does not have the same outcome for everyone.

Disease incidence describes the rate of new cases in a population over a period of time. Incidence can differ between local, national and global populations partly because their exposure to lifestyle and environmental risks differs. Such differences do not, by themselves, prove which factor caused the difference in incidence.

Costs of non-communicable disease

Non-communicable diseases are diseases that cannot be passed from one person to another. Their costs include both human costs, such as pain and loss of quality of life, and financial costs, such as paying for treatment and care.

Costs to individuals and families

A person with a non-communicable disease may experience pain, disability or a reduced quality of life. Some diseases can also cause premature death. Treatment and care may create costs for the individual or their family. If the person cannot work, or a family member reduces their working hours to provide care, the family may also lose income.

Providing support can place demands on family members’ time and wellbeing, especially when care is needed over a long period.

Costs to communities and wider society

A local community may need to provide more care and support for people living with non-communicable diseases. Illness or premature death can also mean that people are less able to contribute to work and community life.

At national and global levels, treatment and long-term care place demands on health services and their funding. Illness can reduce economic productivity when people are unable to work as much, while premature death can cut short their working lives.

The size of these human and financial costs depends on the disease, how frequently it occurs and the resources available to prevent and treat it. For example, a disease that requires long-term care can create continuing demands on families and health services.

Sampling in risk-factor studies

A risk-factor study often cannot investigate every person in the population of interest. Instead, researchers study a sample: a subset of that population. They use the results to look for patterns that may also apply to the wider population.

Sample size and chance variation

A sample needs to be large enough that results are not dominated by chance differences between the people selected. For example, a small sample might contain an unusually high proportion of people with a particular exposure or disease simply by chance. A larger sample reduces the effect of this chance variation, although it does not eliminate it.

Selection and representation

The people selected should represent the population being studied. If they differ from it systematically, estimates of how common an exposure or disease is may be misleading. For example, a sample drawn only from one age group may give a misleading estimate for a population containing several age groups.

Random selection gives people in the population a chance of being selected and can reduce selection bias: systematic differences caused by how the sample is chosen. However, even a randomly selected sample may, by chance, differ from the wider population. A large sample is not necessarily representative if the way it was selected favours certain people.

When interpreting a risk-factor study, consider both the sample size and how participants were selected. These affect how confidently its findings can be applied to the wider population.

Presenting and interpreting risk-factor data

Risk-factor data show how a measure of health, such as the percentage of people developing a disease, varies between groups or over time. The data may be given as numbers in a table or displayed in a chart or graph.

Reading and comparing risk-factor data

First identify what each variable measures. For example, one variable might describe a risk factor, while another gives the percentage of people who developed a disease. Read the headings, units and scales before extracting the values needed for a comparison.

Check that the values use compatible measures, populations and time periods. A percentage developing a disease over one year, for example, should not be directly compared with a percentage developing it over ten years.

Suppose a fictional data set records the percentage of initially disease-free adults who develop a disease over ten years:

• Group with lower exposure to a risk factor: $$10%$$
• Group with higher exposure to the risk factor: $$20%$$

The recorded percentage is higher in the higher-exposure group by 10 percentage points. This describes an association in the data; the comparison alone does not establish that the risk factor caused the disease.

Converting between numerical data and graphs

Choose a display that suits the variables. A bar chart can compare separate groups, while a line graph can show how a measure changes across a continuous variable such as time. Label the axes, include units where needed, and choose a scale that covers the data with equal, readable intervals. Plot each value accurately.

For the fictional data above, a bar chart could have the two exposure groups on the horizontal axis and the percentage developing the disease on the vertical axis. A vertical scale from $$0%$$ to $$20%$$ in intervals of $$5$$ percentage points would allow the bars to be plotted at $$10%$$ and $$20%$$.

To convert a graph back into numerical data, locate each group or point and read its value against the labelled scale. Record the value with its unit or percentage. If a point falls between scale markings, estimate its value rather than treating the reading as exact.

Reducing coronary heart disease risk

The coronary arteries supply the heart muscle with blood. In coronary heart disease, fatty deposits build up in these arteries, narrowing them and reducing blood flow to the heart muscle. Diet and physical activity can lower the risk of this narrowing developing.

Diet and coronary heart disease risk

A healthy diet helps maintain a healthy body mass and reduces conditions that put extra strain on the heart and blood vessels. In particular, limiting excessive intake of saturated fat can help reduce the build-up of fatty deposits in coronary arteries.

Exercise and coronary heart disease risk

Regular exercise improves fitness and helps the heart and circulatory system work efficiently. It can also help maintain a healthy body mass and reduce problems associated with inactivity. Together, these effects can lower the risk of coronary heart disease.

These lifestyle choices reduce risk rather than eliminate it: they make coronary heart disease less likely, but they do not guarantee that it will be prevented.

Lifestyle and genetic cancer risk

A risk factor is something that increases the likelihood of developing a disease. It does not mean that the disease is certain to occur. Both lifestyle and inherited genetic variants can affect a person’s risk of developing some cancers.

Lifestyle and cancer risk

Lifestyle factors are patterns of behaviour that can change a person’s exposure to carcinogens: agents that can cause cancer. Carcinogens can damage DNA, increasing the chance of changes that disrupt the control of cell growth and division.

Different cancers are associated with different risk factors. For example, smoking increases the risk of lung cancer because tobacco smoke contains carcinogens. Frequent exposure to ultraviolet radiation from the Sun increases the risk of skin cancer.

Inherited genetic susceptibility

A person can inherit a genetic variant that increases their susceptibility to certain cancers. Some inherited variants affect processes that normally control cell growth and division, making it more likely that cells will grow and divide uncontrollably.

Inheriting susceptibility is not the same as inheriting cancer. The variant increases risk, but cancer is not certain to develop. Lifestyle and inherited genetic factors can both contribute to a person’s risk.

Smoking and cardiovascular disease

Smoking increases the risk of cardiovascular disease by damaging blood vessels and placing extra strain on the heart and circulation.

Smoking and narrowed arteries

Chemicals in tobacco smoke damage the walls of blood vessels. This encourages fatty deposits to build up in artery walls, narrowing the arteries and restricting blood flow.

If arteries supplying the heart muscle become narrowed, less oxygen reaches the heart muscle. This can lead to coronary heart disease. If blood flow to part of the brain is interrupted, a stroke can occur.

Nicotine and carbon monoxide

Nicotine increases heart rate and blood pressure. The heart must work harder, and the increased pressure places strain on blood vessels.

Carbon monoxide binds to haemoglobin in red blood cells, reducing the amount of oxygen the blood can carry. This reduces the oxygen available to body tissues, including the heart muscle.

Obesity and Type 2 diabetes

Insulin is a hormone that helps regulate blood glucose concentration by causing body cells to take up glucose from the blood. In Type 2 diabetes, body cells become less responsive to insulin. This is called insulin resistance.

When cells respond less effectively to insulin, glucose uptake is less effectively regulated. As a result, blood glucose concentration can remain too high.

Obesity is a risk factor for Type 2 diabetes because excess body fat increases the risk of insulin resistance. A risk factor increases the chance of a condition developing; it does not make the condition inevitable. Not everyone with obesity develops Type 2 diabetes, and other factors also contribute to its development.

Alcohol and liver disease

The liver breaks down alcohol, but drinking excessive amounts over a long period can damage its cells. As damage develops, fat can accumulate in the liver. If damage continues, scar tissue can form.

Extensive scarring of the liver is called cirrhosis. Scar tissue reduces the liver’s ability to function, and severe damage can lead to liver failure, when the liver can no longer function adequately.

The longer heavy drinking continues, the greater the risk of liver damage and the more severe that damage can become.

Alcohol and brain function

Alcohol affects how the brain works. While it is acting on the brain, it can make it harder to make decisions, control movements, respond quickly and remember information.

These effects include:

• Impaired judgement: a person may assess risks poorly or make decisions they would not otherwise make.
• Reduced coordination: movements become harder to control accurately, affecting balance and tasks that require precise movements.
• Slower reaction time: a person takes longer to respond to a situation.
• Impaired memory: a person may have difficulty forming or recalling memories of events.

The extent of impairment depends partly on the amount of alcohol consumed: drinking more generally produces greater impairment.

The effects above can occur while alcohol is acting on the brain. Prolonged heavy drinking can also damage the brain, causing problems with brain function that last longer than the immediate effects of alcohol.

Smoking and chronic lung disease

Tobacco smoke damages both the airways that carry air through the lungs and the tiny air sacs where gas exchange takes place. Over time, this damage can make breathing difficult.

Mucus and airway inflammation

The airways produce mucus, which traps particles and microorganisms. Tiny hair-like structures called cilia normally move the mucus out of the airways. Tobacco smoke damages the cilia, so less mucus is cleared. Mucus can then accumulate, and infections become more likely.

Smoke also causes inflammation of the airways. Inflamed airways become narrower, making it harder for air to move through them.

Alveolar damage and restricted airflow

Alveoli are tiny air sacs in the lungs where oxygen enters the blood and carbon dioxide leaves it. Smoke can damage the walls of the alveoli, reducing the surface area available for gas exchange. This makes gas exchange less effective.

These changes contribute to chronic obstructive pulmonary disease (COPD). In COPD, airflow is persistently restricted, so air cannot move easily into and out of the lungs and breathing becomes difficult.

Carcinogens and cancer

A carcinogen is an agent that increases the risk of cancer. Carcinogens can damage DNA, causing changes called mutations. If a mutation affects a gene that controls cell division, that control may be disrupted. Cells may then divide uncontrollably and form a tumour.

Carcinogens: radiation and tobacco smoke

Ionising radiation is a carcinogen because it can damage DNA. Tobacco smoke also contains carcinogenic chemicals, and smoking increases the risk of lung cancer.

Exposure to a carcinogen increases the risk of cancer; it does not guarantee that cancer will develop.

Smoking during pregnancy

Smoking during pregnancy exposes the developing baby to substances in tobacco smoke. The baby receives oxygen and nutrients from the mother’s blood through the placenta, so changes to the mother’s blood and blood flow can affect the baby’s supply.

Carbon monoxide reduces the amount of oxygen carried in the blood. Nicotine can narrow blood vessels, reducing blood flow to the placenta. This can reduce the supply of oxygen and nutrients reaching the baby and restrict fetal growth.

Smoking during pregnancy increases the risk of low birth weight, premature birth and stillbirth. These are increased risks, not certain outcomes: smoking makes them more likely, but they do not happen in every pregnancy.

Alcohol during pregnancy

Alcohol consumed during pregnancy can pass from the mother's blood across the placenta and reach the developing baby. The placenta allows substances to pass between the mother's blood and the baby's blood; it does not prevent alcohol from crossing.

Alcohol can interfere with normal development, including development of the brain. This increases the risk of fetal alcohol spectrum disorders (FASD), a range of effects caused by exposure to alcohol before birth.

Effects can include impaired growth and lasting difficulties with learning, behaviour or coordination. Drinking alcohol during pregnancy increases the risk of these effects, but the effects and their severity vary.

Scatter diagrams and correlation

A scatter diagram shows the relationship between two numerical variables. One variable is plotted on each axis. Each point represents a pair of measurements taken together: its position shows the value of each variable for that pair.

The overall pattern of points can reveal a correlation: a tendency for the variables to change together.

• Positive correlation: as one variable increases, the other tends to increase.
• Negative correlation: as one variable increases, the other tends to decrease.
• No clear correlation: the points show no clear increasing or decreasing pattern.

A correlation describes the overall tendency; individual points do not all have to follow the pattern exactly.

Correlation and disease

A scatter diagram may show a correlation between a risk factor and the frequency of a disease. This is an association: the two variables tend to change together. It does not, by itself, prove that the risk factor causes the disease, because other factors may also contribute.