IB Docs (2) Team
Sociocultural explanations of obesity
Sociocultural factors may play a key role in obesity. Social factors may include access to healthy food. Many people today blame the obesity epidemic on the availability of fast food. Many governments are trying to combat the obesity epidemic by taxing transfats, soda or other unhealthy foods.
Another sociocultural factor is the effect of technology on our daily lives. Many psychologists argue that we have become more sedentary - that is, we are less physically active on a daily basis than we should be. We spend way too many hours sitting in front of our computers rather than going for a walk in the forest.
Finally, there may be cultural factors that encourage weight loss or gain. As you read through this chapter, remember the research on genetics. As you know, it is not really possible to separate out environmental and genetic factors in the study of obesity.
Can we just blame McDonald's?
Culture plays a significant role in how we eat. Food choices are learned very early in life. Social events and family rituals are often centered around large meals. Today's culture promotes eating habits that contribute to obesity. Restaurants often serve large portions. When looking for a quick lunch, we often choose foods that are most readily available instead of choosing foods that are the most nutritious. Food is also often used as a reward. Children are treated to sweets for cleaning their room, and the team is taken for pizza or ice cream after the game. Seldom is eating only when hunger is present.
In one of the largest correlational studies of its type, Currie et al (2010) collected data from four US states (California, Michigan, Texas and New Jersey) comprising roughly 3 million children. Her research found that among ninth-graders, a fast food restaurant within 0.1 miles of a school results in a 5.2 percent increase in obesity rates. Non-fast food restaurants showed no significant correlation with weight outcomes. Although this does not provide evidence of a cause-and-effect relationship, there is a large amount of data which increases the reliability of the findings.
When we think of fast food, many of us have an ethnocentric bias - thinking of McDonald's, KFC or Taco Bell, rather than thinking of kebab stands, Singaporean street food or Indian samosas. Joseph (2015) investigated the role of local fast food on Indian teenage boys. The sample was made up of 300 high school boys from three private schools in Mangalore city. The mean age was 13.5 years old.
Data was collected using a semi-structured self-administered questionnaire. The questionnaire asked about the frequency of fast food meals, years of fast food consumption, awareness of health hazards, time spent in fast-food restaurants and parental food consumption patterns. In addition, the boys were asked about the type and frequency of physical activity. Finally, their height and weight were measured, and their height and weight from two years previous were obtained from the school register.
The researchers found that an increased frequency of fast food consumption in a week was associated with overweight or obesity status after matching for physical activity. They also found that peer influence played a key role in fast food consumption. Fast food restaurants are important centers for socializing with one’s peer group among adolescents.
Sedentary lifestyle
Overweight people are usually less physically active than normal-weight adults. Lakdawalla & Philipson (2002) argue that obesity has more to do with a lack of physical activity than with food intake. The change to a more sedentary lifestyle is an important variable in the "obesity epidemic."
The body uses energy during physical activity, and if one eats more than is burned, fat will be stored. In the past, people used much more energy in their daily lives than they do today. Television viewing, Internet surfing and gaming have all increased over the years, as has obesity. But the research that follows is all correlational. How does one manipulate the level of sedentary behaviour in either a practical or an ethical manner?
Martinez-Gonzalez et al (1999) carried out a large-scale study of 15,239 people in the European Union to determine the relationship between sedentary behaviour and obesity. 15 different countries were studied to avoid cultural bias in the sample. The sample was a stratified cluster sample - that is, the sample taken from each country was stratified to represent its population. The sample was made up of males and females ages 15 and older.
The study was a structured interview carried out by professional interviewers in the homes of the participants. Sedentary lifestyle was assessed by self-reported hours spent sitting down during leisure time. In addition, BMI measurements were calculated.
The researchers found a direct correlation between those who had high amounts of sedentary time (35 hours per week) and obesity and an inverse correlation between those with high amounts of physical activity and obesity.
A more recent study by Vandelanotte et al (2009) investigated the potential negative impact of increased computer use on body weight and health. The sample was made up of 2650 adults living in Adelaide, Australia. The participants were asked to complete a mail-back questionnaire including items on their height and weight, recall of physical activity over the past seven days, the amount of time spent on the Internet and computer use, and other leisure-time sedentary behaviours. Leisure-time Internet and computer use were categorized into no use, low use (less than three hours per week), or high use (three hours or more per week).
Participants with a high leisure-time Internet and computer use were 1.46 times more likely to be overweight and 2.52 times more likely to be obese, compared to those who reported no Internet and computer use in their leisure time. Adults with high leisure-time Internet and computer use were more likely to be overweight or obese even if they were highly active in their leisure time.
She, King and Jacobson (2017) may have found part of the solution to our sedentary lifestyle. Ironically, it may be that public transportation lowers obesity. The researchers analysed data from the United States regarding public transit accessibility, vehicle ownership and obesity levels at the county level. The results suggest that a one percent increase in county population usage of public transit is associated with a 0.22 percent decrease in county population obesity prevalence. Walking to the tram or bus stop on a daily basis may be enough exercise help people to control their weight.
These findings suggest that, apart from nutritional and physical activity interventions, it may also be necessary to decrease time spent in sedentary behaviours, such as leisure-time Internet use and driving in our cars, in order to reduce the prevalence of overweight and obesity.
Research in psychology: Forslund et al (2005)
Forslund et al. (2005) undertook a cross-sectional study in 22 medical centers in Sweden, to investigate how snacking may influence weight. They used self-reports (questionnaires) to compare the energy intake (estimated in kilocalories) of 4259 obese men and women with 1095 controls. They were interested in how much of the energy came from meals and how much came from snacking. Snacking was defined as eating between the main meals. The participants had a physical exam and blood tests were taken.
The obese people ate on average six times a day, compared to five times in the non-obese group. The obese were also more likely to eat later in the day than the non-obese. The researchers noticed that, overall, obese participants reported a significantly higher energy intake than the control group.
Snacking was more frequent in the obese group, and women were more frequent snackers than men. The proportion of energy from fat was more pronounced in the obese group. Generally, energy intake was more likely to come from sweet, fatty food choices in obese frequent snackers. The non-obese ate more healthy snacks. The researchers found that obese participants exercised less than non-obese participants. The obese participants also had lower education levels than non-obese participants.
Obese men n = 1891 | Non-obese men n = 505 | Obese women n = 2368 | Non-obese women n = 587 | |
| Average BMI | 37.1 | 25.8 | 38.7 | 24.7 |
| Total energy (kcal) | 3234 | 2766 | 2683 | 2223 |
| % of time with no physical activity | 31.5 | 9.5 | 32.3 | 11.0 |
The role of culture
Watch the following video on countries that value obesity in women. Listen carefully to the theories as to why these cultures see being overweight as something positive. To what extent do you think that these arguments are valid?
Teacher only boxThis activity gets students to think about why culture's may have norms that promote obesity.
1. South Africa: The link between HIV infection and weight loss. In addition, there is a correlation between being overweight and personal wealth.
2. Afghanistan: Fertility is seen as linked to obesity.
3. Tahiti: A diet rich in carbohydrates and coconut milk.
4. Nauru: Linked to fertility in women and strength in men.
5. Mauritania: Seen as linked to health and beauty
- Many studies are naturalistic, meaning that they have high ecological validity.
- The approach is more holistic, recognizing how factors may interact to lead to obesity.
- Sociocultural theories have addressed the stigma of obesity, promoting environmental changes that may help people to maintain a healthy weight.
- Sample sizes of many of the studies are very large, making the data more reliable.
- Most research is correlational and extraneous variables are not controlled, meaning that a cause and effect relationship cannot be established.
- Many of the studies are difficult to replicate the findings to establish reliability.
- Findings from studies in a specific culture or group may be difficult to transfer to other groups.
- Researchers are in danger of committing the ecological fallacy - that is, they choose people to be in the study because they are obese. They assume that all people who are obese share certain characteristics (high blood pressure, sedentary lifestyle, poor eating habits). This is why it is important that studies are matched for these traits to eliminate them as confounding variables.
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