Explinations and health problems

Obesity

abnormal or excessive fat accumulation that presents a risk to health. A body mass index (BMI) over 25 is considered overweight, and over 30 is obese.

Biology
cognative

Obesity can be explained through genetic inheritance affecting BMI

Sorensen et al (1998)

To investigate the heritability of obesity by comparing the BMI (Body Mass Index) of adopted children with their biological and adoptive parents/siblings.

correlational adoption study
840 Danish adoptees.
Researchers calculated the BMI of the adoptees and compared them to their biological families and adoptive families. They also utilized school records for weight/height from ages 7–13 and questionnaires to document environmental factors.

Adoptees' BMI correlated highly with their biological family, not the adoptive family with whom they lived.
Environmental factors (e.g., family income, family lifestyle) did not play a significant role in determining the BMI of the adoptees.
Adoptee BMI was positively correlated with full siblings, and to a lesser extent, half-siblings, even when separated.

this supports biological explination for obesity as the study shows how an indivual may have a genetic predisoptiion to Obesity.

T: The study is highly testable because it uses an adoption design comparing BMI between biological and adoptive parents, allowing researchers to isolate genetic influences from environmental ones, strengthening internal validity. However, genetic influence on BMI is complex and influenced by many interacting genes, meaning it is difficult to fully isolate and test specific genetic factors responsible for obesity.

A: A key strength is its real-world application in understanding risk factors for obesity. It suggests that individuals with a family history of obesity may have a higher genetic predisposition, which can inform early prevention strategies giving the study a high external validity. However, focusing on genetic explanations may reduce perceived personal control, potentially discouraging individuals from engaging in healthy behaviours if they believe weight is purely inherited.

U: The use of adoption data reduces environmental bias, as adoptees are raised in different environments from their biological parents, helping to separate genetic and environmental influences. However, environmental factors are not fully controlled, as adoptees may still share similarities with their biological parents due to selective placement or broader social influences. This introduces potential confounding variables, making it difficult to completely isolate genetic effects and reducing internal validity. Additionally, adoption samples may be biased because adoptive families are often not representative of the general population, for example having higher socioeconomic status, which limits the generalisability of the findings.

Overall biological explination explains how genetics can play a role in the explination for obesity. However, it does not fully account for environmental and behavioural factors such as diet and physical activity, which also strongly influence obesity.

A psychological explanation of obesity focuses on how cognition influences eating behaviour and physiological responses

Crum et al 2011

To investigate whether one’s perception of the number of calories in a milkshake would impact the participants’ physiological response and subjective feeling of satiety.

Repeated measures design
46 participants recruited via a volunteer sampling method. 18 - 35 years of age and had a normal range of body mass
Meassued grehlin - a hormone that signals hunger.
Ghrelin normally:
rises when people are hungry
drops when they feel full.

two tasting sessions that were 1 week apart, which was counterbalanced.
first session: "indulgent shake,” - told it was 620 calories
2nd session: "sensible shake" - told it was 140 calories.
In reality, they both had 380 calories.
The researchers used intravenous blood samples to conduct 3 tests to measure the participants' ghrelin levels: baseline levels, before consuming the shake, and after consuming the shake. The participants were also asked about their perception of the shake, in order to make sure they had the appropriate mindset.

When participants believed the shake was indulgent and high-calorie:
ghrelin levels dropped significantly
participants felt more full

When participants believed the shake was low-calorie and sensible:
ghrelin levels did not drop as much
participants felt less full

Even though the milkshakes were identical.

The study concluded that beliefs and expectations about food can influence physiological responses to eating.
This suggests that mindset plays an important role in hunger, satiety, and eating behaviour.

This suggests that cognitive beliefs about food can directly influence biological processes related to hunger and satiety. Thus supporting the cognative explination for obesity

A: A key strength is strong real-world application, particularly in public health interventions that aim to change beliefs in order to improve behaviours such as exercise, diet, or screening. However, changing beliefs does not always lead to behaviour change, as habits, environment, and social factors may override cognitive intentions.

U: The use of pedometers reduces bias in measuring exercise behaviour, as it provides objective behavioural data rather than relying on self-report or memory. However, the self-report questionnaires used to measure TPB constructs are vulnerable to social desirability bias, where participants may overstate positive attitudes and intentions toward exercise in order to present themselves in a healthier light. This reduces the validity of the psychological measures and may mean that the questionnaire did not accurately capture participants’ true beliefs or intentions. As a result, this may help explain the discrepancy between reported intentions and actual walking behaviour, highlighting a gap between behaviour and intention.

P: The study has partial predictive validity because TPB successfully predicts exercise intentions, showing that cognitive attitudes are related to planned behaviour. However, predictive validity is weak when it comes to actual behaviour, as intentions did not reliably translate into real walking behaviour measured by the pedometer. This highlights a gap between cognition and action, limiting TPB’s ability to predict real-world health behaviour.

A strength of cognative explination is that it implies that individuals’ beliefs about food and eating may influence how much they consume, potentially affecting long-term weight regulation. However, a limitation is that the study was conducted in a controlled laboratory setting, meaning it may not fully reflect real-world eating behaviour.

In conclusion, obesity can be explained through both biological and psychological approaches. Adoption studies such as Sorensen et al. demonstrate the influence of genetic factors on BMI, while Crum et al. shows that cognitive perceptions can influence physiological satiety responses. Together, these findings suggest that obesity is a complex condition resulting from multiple interacting factors rather than a single cause. However, a full explanation requires consideration of biological, psychological, and social influences.