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Prepared for EvidenceNetwork.ca by Banaz Al-khalidi

Obesity by the numbers

The prevalence of obesity in Canada has substantially increased over the past 30 years. More than one in four Canadian adults have obesity and childhood obesity has tripled during the same time period. The obesity epidemic is one of the biggest health challenges facing Canadians today.

Historically, the prevalence of obesity increased from 9.7 % in 1970-1972 to 14.9 % in 1998. Just recently, Carolyn Gotay, a researcher at the University of British Columbia, reported that obesity rates in Canada have hit record levels. Between 2003 and 2011, obesity rates in Canada have increased from 22.3% to 25.3%. The Atlantic Provinces and the two territories, Nunavut and the Northwest Territories, have the highest obesity rates in the country, with more than 30% of the population in these regions estimated to have obesity.

The health and economic costs of obesity

While the obesity epidemic has long been a public health issue in the United States, it has only recently emerged as a public health epidemic in Canada. Obesity is the leading contributor to chronic disease and reversing the obesity trend is the focus of many major public health campaigns and organizations today.

Obesity is a costly epidemic. Rising obesity rates have been significantly associated with increased rates of cardiovascular disease, stroke, diabetes and cancer. Obesity is linked to both increased health care costs and diminished worker productivity; the economic costs associated with obesity have increased from 3.9 billion in 2000 to 4.6 billion in 2008, a 20% increase in spending based on costs associated with eight chronic diseases linked to obesity.

How is obesity measured in adults and children?

Body mass index (BMI) is the most commonly used measure for classifying weight and evaluating health risks associated with increased weight. BMI is calculated by dividing weight (in kilograms) by height (in meters) squared. Both Health Canada and World Health Organization (WHO) use a weight classification system based on the BMI for evaluating overweight and obesity among adults age 18 and older.

31% of Canadian kids are reported to have overweight or obesity. Defining healthy weights for children and adolescents has been challenging. There are a number of research gaps and methodological challenges in studying obesity in this population, including different systems for defining overweight and obesity at different ages and the study of prevalence among very young children.

There are two different methods used to classify weights in children and youths: the international standard (extrapolating a child’s BMI to match adult categories for being overweight and obese) and BMI-for-age growth charts released by the US Centers for Disease Control and Prevention. These methods yield different population prevalence estimates for overweight and obesity in children. The collaborative statement in 2004 among Canadian health practitioners endorsed the use of the US BMI-for-age charts for clinical and community use.

However, BMI does not take into account body composition or fat distribution on the body. BMI is an inaccurate predictor of health risk for certain subpopulations, including: children and adolescents who have not reached their full growth, adults who are naturally lean or muscular, pregnant women, seniors and members of certain ethnic and racial groups.

Research has shown that waist circumference (WC) is a useful measure of the health risk associated with excess abdominal fat. In general, men with a WC of 102cm (40 inches) or more and women with a WC of 88 (35 inches) or more are at a higher risk of developing obesity related health problems.

One of the biggest challenges of using BMI and waist circumference measures to classify obesity is that both measures do not provide information on the presence or extent of health risks or quality of life. Recently, Sharma and Kushner proposed the Edmonton Obesity Staging System (EOSS) as a practical clinical guide to measure obesity related health risks and as a predictor of mortality.

Should those with obesity lose weight?

People with obesity who have no concurrent medical problems (e.g. type-2 diabetes, hypertension, reduced quality of life) may not necessarily benefit from weight loss. The use of BMI alone may overestimate health problems in some patients but also miss out some patient subgroups who are below the BMI 30 kg/m2 obesity range but do have weight related health issues.

The newly emerging evidence challenges the notion that everyone with obesity needs to lose weight. Applying EOSS would help to identify high risk individuals who urgently require weight-management interventions. In a publicly-funded health care system, identifying and prioritizing care for patients with obesity with greater health risks would allow for improved utilization of limited resources to those in greatest need.

What is driving the obesity epidemic? 

The scientific evidence clearly indicates that the causes of obesity are many. Fundamentally, obesity results from a sustained positive energy balance whereby energy consumption exceeds energy expenditure. Basically, calories matter. The roles played by changes in dietary habits and sedentary lifestyle on the current obesity epidemic remain somewhat uncertain. Obesity results from a complex interaction between individual factors and societal factors.

Individual factors include genetics, psychosocial attributes (e.g. depression, anxiety, disordered eating habits), lifestyle and behaviour. However, individual factors alone cannot explain the rapid increase in the prevalence of obesity we see today. Obesity, like smoking and alcohol abuse, is not simply the result of individuals making bad decisions, but strongly influenced by the social and commercial environment that puts some individuals at a higher risk for certain behaviors. Thus, the obesity epidemic cannot be fixed primarily by telling individuals to modify their behavior.

Genes and other biological factors may predispose some individuals to obesity, but obesity results from a complex interaction between diet, physical (in)activity, and the environment. Intake and expenditure patterns of a population are rooted within the larger environmental risk factors. These risks factors include the promotion and availability of cheap high-calorie foods, limited access to affordable healthy foods, promotion of convenience foods which fill the lack of time for meal preparation, limited cooking skills, promotion of sedentary living (driving, screen time),  and barriers to physical activity.

Our current environment encourages over production and over consumption of cheap energy dense food. The environment has a direct impact on what we eat, our food preferences, and how much we eat. Essentially, there is a biology-environment mismatch whereby increases in food supply and caloric intake combined with a fall in physical activity have created a perfect storm for the obesity epidemic.

Eating habits and food consumption patterns

Eating patterns have an impact on body weight. According to a national study of the food habits of Canadians, 22% of the total calories consumed by adults and 25% of total calories consumed by adolescents ages 14 to 18 were in the “other foods” category, which includes foods that are mainly fat and oils, sugar, high fat/high salt snack foods, sugary beverages and condiments.

Most Canadians are not meeting the minimum servings of vegetables and fruits.

A number of studies have linked the evidence between low consumption of fruits and vegetables to obesity. An Edmonton study showed that easy access to unhealthy food appears to be an important risk factor for obesity. The odds of having obesity increased with the concentration of convenience stores and fast food outlets in the neighborhoods, regardless of neighborhood and individual level economic status, age, sex and education.

Canadians are also eating more foods away from home than they did in the past. This has important implications for the obesity epidemic because an average person consumes more calories when he/she eats large restaurant portions.

Sweetened beverage intake is a common pattern among children and adolescents aged 2-18 years. Consumption of sugar-sweetened soft drinks cause an increase in total energy intake, leading to an energy imbalance and weight gain in the long term. According to results from the 2004 Canada Community Health Survey, children and teens get one-fifth of their daily calories from beverages.

Childhood obesity is also associated with children’s exposure to food/beverage marketing. Commercial food advertising aimed at children directly affects their food preferences, consumption patterns, and food purchase requests. A 2005 IOM review of the literature found strong evidence of advertising’s impact on childhood obesity, less evidence for its impact on adolescents.

Activity levels

Weight is also affected by how active people are. Major changes in modern life such as technological advancements and economic growth have shifted the demands for physical activity associated with work, home and transportation. Although half of Canadian adults (52.5%) report that they are physically active, only 15% are meeting national guidelines when activity is measured with an accelerometer.

The Canadian physical activity levels among youth study estimated that only 7% of children and youth ages 5 to 17 attained moderate physical activity levels. Changes in the environment brought about by industrialization have been associated with reduced work and daily living related physical activities and an increase in physical inactivity or sedentariness — watching television, playing video games, and using the computer.  Canadian youths are accumulating more than six hours of screen time on weekdays and many studies show that TV viewing is associated with greater calorie intake or poorer diets.

The amount of daily physical activity needed to maintain a healthy weight or to help with weight loss is still debatable among researchers. Data on physical activity levels are insufficient and contradicting due to the challenging nature of accurately measuring physical activity, since most studies have relied on self-reported activity in a survey or daily log. This method is not reliable as it tends to overestimate activity levels.

Researchers are still trying to identify convincing evidence on physical activity as a causal factor in the pathway leading to obesity. The exact role that physical activity plays in obesity remains unclear. In fact most of the evidence from school-based physical activity interventions showed no improvement in BMI, despite other beneficial health effects. However, these studies did not measure adherence to the intervention and use of BMI is a poor measure of body composition.

The Canadian Journal of Public Health recently reviewed the evidence on how the built environment influences behavior. While the evidence linking the built environment to obesity is weak, there is more evidence linking the built environment to behaviors (physical activity and diet) especially for adults.

A new emerging area of research has been redirected at studying what constitutes modern life sedentariness and changes in “24-hour” lifestyle habits. It’s not physical inactivity per se but it’s the type of sedentary activity such as reduction in sleep time and long working hours that have been shown to affect energy balance, although the mechanism is not understood clearly.

Is there a link between poverty and obesity?

Certain social and economic factors are linked to body weight. Low income can compromise people’s food choices, weight and health. Canadians who do not have a regular or secure supply of food are likely to be in low income households or dependent on social assistance. A relationship between food insecurity and obesity has not been proven among adult men and the findings for adult women have been inconsistent.

A survey examining factors that predict BMI found that neighborhood socio-economic status was correlated with BMI, where obesity was more prevalent in the most socioeconomically deprived areas than in the least deprived. There is also an association between neighborhood socio-economic status and a child’s weight. Children who live in low income  neighborhoods have a greater likelihood of having overweight or obesity. Evidence on the relationship between economic status and obesity has been inconsistent mainly because many factors tend to confound the relationship and there are methodological flaws in most studies.

Does depression cause obesity?

There is some evidence suggesting a relationship between depression and obesity. Drugs used to treat depression have been cited to cause weight gain as a side effect. Antidepressive drugs including SSRI (selective serotonin reuptake inhibitor) can cause a weight gain of 10 pounds or more. However, evidence linking the use of antidepressant drugs and obesity is still emerging.

There is newly emerging evidence supporting a significant relationship between children diagnosed with attention deficit/hyperactivity disorder (ADHD) and obesity. The first long term study by researchers at NYU Langone Medical Center found that patients diagnosed with ADHD in childhood were twice as likely to be obese compared to patients not diagnosed with the condition. It is speculated that lack of impulse control and poor planning skills in patients with ADHD can lead to poor food choices and disordered eating habits, putting them at a higher risk for obesity.

Healthy weight strategies

In efforts to reverse the obesity trends in Canada, successful prevention efforts are needed. Given the limited success of individual-based interventions in the long term, a multifaceted long term approach is recommended.

Some of the promising regulatory approaches include:

The government can also reform nutrition fact panels. Nutrition information on packaging is not expressed in ways that are meaningful to the average consumer. There is a need for a robust national food scoring and labeling system to help consumers determine how a typical serving of the food fits into a healthful daily diet.

Note on language: In order to prevent the stigmatization of people with obesity, it is preferable to use language that highlights “to have is not to be.” Thus, we use terms such as an individual “having obesity” versus speaking of “being obese” or labelling “the obese.”  For more, read: http://www.drsharma.ca/to-have-is-not-to-be.html

Experts available for interview

Denis Daneman
University of Toronto
Chronic Disease and Social Determinants of Child Health
416-813-6122 | denis.daneman@sickkids.ca

Yoni Freedhoff, MD
University of Ottawa
Nutrition, Obesity, Weight Management
613-730-0264 | drfreedhoff@bmimedical.ca | @YoniFreedhoff

Michael Hayes, PhD
University of Victoria
Health inequities, disability and child obesity
250-853-3108 or (c) 250-818-2410 | mhayes@uvic.ca

Jennifer Kuk, PhD
School of Kinesiology and Health Science
Weight Management, Health Promotion, Lifestyle Interventions
416-736-2100 ext 20080 | jennkuk@gmail.com

John Millar, MD, FRCP(C), MHSc
University of British Columbia
Public Health, Health Policy, International Health
604-922-0995 or (c) 604-785-9058 | john.millar10@gmail.com | @JohnMillar10

Kim Raine
University of Alberta
Social Factors and Interventions in Obesity and Food
780-492-9415 | kim.raine@ualberta.ca

Our commentaries on obesity

Listen to our podcast on the subject:

Fixing a Broken Environment to Curb the Obesity Crisis

Other backgrounders on obesity

Further reading


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