Prevalence of Obesity (DP IB Psychology): Revision Note

Prevalence of obesity

• Prevalence rates show how common a disorder is within a defined population over a set time period

• Prevalence rates are calculated as follows:

  • Number of obesity cases divided by the total population

  • E.g., if 4,500 in a population of 50,000 are obese, this means that the prevalence rate is 9%

• Prevalence tells us the likelihood of any person in a population being obese, making it a useful predictive tool

• Obesity is is defined as having a Body Mass Index (BMI) over 30

• Obesity figures in the UK (2023/24) showed that:

  • 26.5% of adults were obese

  • 64.5% were overweight or obese combined

Research support for prevalence of obesity

Kyle et al. (2016)

Aim:

• To investigate obesity prevalence among nurses in Scotland compared with other professions

Participants:

• 13,483 adults (aged 17–65):

  • 411 nurses

  • 320 healthcare professionals

  • 685 care assistants

  • 12,067 non-healthcare professionals

Procedure:

• Participants’ BMI was measured

Results:

• 69.1% of nurses were obese

• This was compared with 51.3% healthcare professionals, 68.5% care assistants, and 68.9% non-healthcare professionals

Conclusions:

• Obesity prevalence among Scottish nurses is significantly higher than in other healthcare and non-healthcare groups

Evaluation of prevalence of obesity

Strengths

• Prevalence data is extremely useful for public health planning, as obesity is linked to serious health risks

• Kyle et al. used a large sample size, producing robust quantitative data, which means that the findings are more reliable and generalisable

Limitations

• Knowing prevalence is not the same as addressing the issue; governments may struggle to implement effective interventions

• Prevalence data lacks depth – it does not explain why people are obese

  • More qualitative research is needed to understand the complex causes of obesity (e.g., lifestyle, socioeconomic status, culture)

Link to concepts

Responsibility

• Research into obesity is socially sensitive, as it can lead to a ‘blame’ culture surrounding the health problem

  • Reporting the results of studies into obesity is riven with potential opportunities for the media to attribute negative behaviours (e.g., laziness, greed) to people who are obese without reflecting on the factors that may have contributed to the obesity

• There are many different and complex variables which contribute to obesity (socioeconomic status, stress, availability of junk food, education level), which means that it must be considered in the context of the person’s life rather than as a ‘lifestyle choice’

Measurement

• BMI is not necessarily the best – or the only – way to measure obesity, as it is based on the height and weight of a person and does not consider their muscle mass, bone density or racial/gender differences

  • This means that it cannot identify body fat with 100% accuracy and is not a ‘one size fits all’ measure