Obesity epidemic in us and canada: etiology and policy recommendations

*Bei Eva
Student, University College London, United Kingdom

*Corresponding Author:

Bei Eva
Student, University College London
United Kingdom

Published on: 2017-06-30



Hypertension, Leaver Disease, Heart Disease, Cancer Risk


Obesity epidemic is one of the most important -and critical to be addressed- medical and public health problems. According to the World Health Organization (2016), obesity is defined as ''excessive fat accumulation that presents a risk to health''. Body Mass Index (BMI) is used to determine obesity and is defined as a person's weight divided by his square of height [1]. A person with a BMI of 30 or more is categorized as obese. In 2014, 13% worldwide was found obese [2].

Obesity is a multifactorial disease -mediated by a range of biological, nutritional and socioeconomic factors- that affects both developed and developing countries, posing a major risk for individual's health. As a chronic disease, it increases dramatically the risk of other serious diseases such as type 2 diabetes mellitus, cardiovascular diseases, coronary heart disease (CHD), hypertension etc. [3]. Apart from medical comorbidity, obese present a greater risk of experiencing depressive-anxiety symptoms, something that might be related to increased stress and hypothalamic-pituitary-adrenal (HPA) dysregulation [4]. Along with significant physical and mental health consequences, obesity pandemic imposes a major economic load (In 2008, 15.8% of global health care expenditure) and may also contribute to decreased life expectancy due to deleterious association of a high BMI with morbidity/mortality [1,5,6].

After a brief presentation of why obesity epidemic is a problem of global concern, we are going to focus on the main causes and policies in the adult population of the United States and Canada. US remains one of the countries where levels of obesity are dramatically high (approximately 35%) [4]. On the other hand, Canada reports lower levels of obesity (20.2%), with the rates although to have been increased over time and still present a risk to health for Canadians [7].

Main causes and etiology of obesity epidemic

Etiology of obesity remains one of the most complex and not fully understood issues. Overall, biological, nutritional and socioeconomic factors may interact to each other, contributing eventually to what has been referred as “Globesity” [8].

Food and drink environment have been shifted dramatically over the past few decades. Fast food-low-quality food consumption accompanied by larger portion sizes, inexpensive prices and a huge industry of food advertising has been rapidly developed, both in US and Canada covering a big percentage of daily diet and leading to a poorer dietary lifestyle with nutritional deficiencies, high calorie food-beverages and a greater risk of obesity [9,10]. Highly processed foods and drinks with added sugar, salt, fat, and sodium are available for all ages and every socioeconomic group, increasing the possibility of obesity [10]. According to research, between 2003 and 2010, 11.3% of American’s daily energy was from fast food [11,12] while findings based on Canadian Community Health Survey (CCHS), revealed that 6.3% of total daily intake was from fast food [9]. However, as with many studies, cross-sectional design, doesn’t let us determine whether people with higher BMI overconsume low-quality food or low-quality food is leading to a higher BMI. Future research should explore further this complex association, informing policy makers with well-evidenced data.

Physical activity has also been decreased, with people following a more sedentary-inactive life accompanied by the daily use of technological advances [8]. Literature supports that inactivity may contribute to an increase of BMI, posing individuals at risk of obesity. However, findings remain mixed with some systematic reviews even support that PA’s changes are not directly followed by changes on BMI [13]. According to data from National Health and Nutrition Examination Survey (NHANES) (1988-2010), inactivity in US was significantly associated with increased rates of obesity [14]. An and colleagues (2016) revealed that inactivity is extremely high in US with only 3 states to report a PA more than 35%. Based on cross-sectional data from the CCHS (2000-01), [15] showed that obese Canadians adopt a generally sedentary lifestyle with inactivity rates to be estimated at 59.7% in men and 71.4% in women. Overall, between 1994 and 2005, Canadians reported a decline in leisure, transport and work- related PA something that may have contributed to obesity epidemic [16]. PA remains one of the major factors that have been suggested for obesity epidemic. However, causality hasn't been proven in all findings, making the association even more complex.

Continuing, obesity epidemic is not just a health problem determined by energy intake and PA. Socioeconomic status, gender, ethnicity and education are significantly related to dietary patterns and thus to obesity.

Literature indicates that a lower education is related to a higher risk of obesity. According to theory, education delivers messages of a healthier lifestyle, preventing the development of obesity while well-educated individuals are more likely to have a higher income and a better access to health care system [17]. Recent research in US population found that one more year of schooling predicts a reduction of 0.15 in BMI [17]. According to NCHS, between 2005 and 2008 obesity rates were estimated to 27.4% and 23.4% in graduate’s men and women compared to 32.1% and 42.1% in those with a high school diploma [18-21]. On the other hand, Canadian data showed that lack of education was among the main factors that increased risk of obesity in low-income Canadians [22]. Increasing educational attainment by one year in Canadian population predicts a 4% decrease of obesity [23]. The above data indicate that education could tackle with obesity, something that preventive interventions should take into serious account.

Income-inequality and low SES remain one of the biggest challenges related to general quality of life and public health problems. In US, income inequality has been negatively associated with BMI. In their attempt to save money, many low SES families consume inexpensive-low-quality food, increasing thus the risk of obesity [24]. Results from a decomposition analysis in Canada has shown that obesity and PA were more concentrated among poor [22]. Overall, income inequality may lead to limited opportunities of PA and nutritious food, which in turn may increase the possibility of obesity. However, low SES is a more complex factor that cannot be explained only in terms of PA and low-quality food. As we will see, low SES is one of the major confounder factors that mediates in complex relationships of obesity.

Obesity has been associated to ethnic disparities in both Canada and US. CCHS (2000-03) found that obesity in Canada varies among different races-ethnicities. Overall, Aboriginal people had the highest prevalence of obesity (28%) followed by Whites (17%) and East/Southeast Asians (only 3%) [25]. A systematic review in US, revealed large ethnic differences with minority groups of non-Hispanic Blacks and Mexican Americans to present a 10% higher prevalence of obesity compared to non-Hispanic Whites while on the same time Asian Americans reported the lowest rates [26]. Obese black population is estimated at 44% with black women to present the highest rates of obesity in US (almost 50%) [27]. However, how could we explain ethnic disparities in obesity? Risk of obesity is determined by an interaction between genetic predisposition and environmental factors [25]. According to some theories, higher rates of obesity may indicate a biological predisposition [28], supported that energy-metabolism may differ among different ethnicities and thus ''thrifty genes'' theory may explain why for example Black and not Asian women present a higher risk of obesity. Another wide-accepted explanation is related to SES. Minorities groups with a very low SES like Black population may have limited access to expensive nutritious food, education and PA [27]. Apart from that, ethnicities like Aboriginal people who live in low SES remote locations don’t have access to Health services and thus opportunity to deal with obesity. Cultural norms related to dietary patterns may also play an important role. For instance, in black population, lower weight may be conceptualized as a sign of disease [24]. Further research-in order to clearly understand ethnicity’s effects and confounder factors such as low SES-is critical.

Obesity epidemic has been globally associated with gender disparities with findings supporting a potential dynamic-complex relationship between gender, obesity and other social determinants. However, a systematic review revealed that literature has rarely explained gender disparities [29]. In 2012, non-Hispanic Black women in US presented a higher prevalence of obesity (56.6%) compared to non- Hispanic Black men (37.1%). However, gender gap was insignificant among Whites (32.2% female vs. 36.2% male). In a Canadian survey, findings revealed that gender disparities in BMI were associated with other psychosocial determinants. Women suffering from a mood disorder were more likely to be obese compared to men [30]. Theories about gender disparities suggest that females of a low SES are probably more vulnerable to obesity due to confounder factors such as social construct of gender [30]. Overall, sociocultural factors, gender-based food preferences and low SES have been suggested (but not explained) for gender disparities in obesity. Future research should focus on explaining this complex relationship in order to intervene properly by addressing different needs that genders present.

Policy Recommendations

Obesity is a multidimensional chronic disease and thus intervening successfully means that the response should be proportional to the complexity. A holistic multifaceted approach is critical.

High calorie and low-quality foods-g at crebeverages is a common dietary pattern for both US and Canada. Therefore, weight-management strategies aiming at a healthy food and drink environment are necessary. Government’s leaderships of both countries should promote product reformulation by improving access to healthier choices in a variety of settings such as schools, hospitals, workplace etc. [31]. They should also adopt measures that reduce impact of fast food marketing in US and Canadian population and increase consumer-friendly labelling. Health care settings have to ensure universal health coverage for the prevention and treatment of obesity and implement initiatives for health promotion such as behavioral counselling and nutritional assessment in every socioeconomic group [31]. Food policy councils that inform and advice residents and governments about healthy food, could be also a promising strategy taking into account that they design interventions at regional and local level, targeting low-income populations, schools and community [32,33].

Policy-makers should prioritize the reduction of any social inequality if they want to eliminate obesity as a pandemic phenomenon. Improving access to healthful foods in underserved communities may help low SES-minority groups to engage in a healthier diet. Minority-low-income neighborhoods usually don't have access to supermarkets selling nutritious foods, thus consuming products of high calorie and saturated fats from outlets [34]. Findings from interventions like Pennsylvania Fresh Food Financing Initiative (PFFI) and policies for Aboriginal groups in underserved communities support that improving access to healthy food, results in a better daily diet for low SES, minority groups [32,33,35]. Overall, low SES and ethnic disparities in US and Canada should be approached by innovative interventions emphasizing on creating a new local environment that offers more opportunities for nutritious-inexpensive food, competing cheap-low-quality food. Establishment of anthropometric surveillance systems combined with a good use of research data system is also critical in order to inform effectively diet-related policy-making.

Continuing, nutritional interventions procedures should be accompanied by strategies that increase physical activity. Community-wide campaigns that promote PA, may be a helpful solution as they are designed to operate at multiple levels, including community, media, advertising, schools, etc. [32,33]. Apart from that, increasing physical education may be beneficial for every socioeconomic group in US and Canada. Being aware of the benefits that activity has, might motivate people to engage in programs provided by government or community. However, it is critical that community offers free of charges activities, targeting low SES minority groups that are not able to afford even low-cost services. Moreover, evidence from Canadian NPHS panel indicates that not only leisure but also transport and work-related activity have been decreased [13]. Active transport-related strategies should be promoted through infrastructure changes that create a sense of safety for both adults and children. Case studies in programs such as Walking School Bus targeting children, support that active transportation may increase PA [32,33]. A systematic review showed that interventions like behavioral-informational strategies, modification of worksite environment and counselling in improving worksite PA had a modest effect on BMI. Further research on transport and worksite activity is critical in order to define which exactly are the most promising interventions.

Finally, education has been supported as one of the factors that may contribute to the risk of obesity in later life. Therefore, it is important to refer some school-based policies and guidelines that may be beneficial and have long-term effects on obesity epidemic. Targeting young children that have not fully developed their dietary habits is an excellent entry point that may help eliminate obesogenic environment in both US and Canada [31]. In a systematic review of school-based initiatives aimed at preventing obesity, results showed that combinations of education, PA and healthy food presented some positive effect on weight-status. In contrast, programs in US that focused only on PA or education didn't present significant results, indicating that future policies should provide a combination of interventions [36]. Public Health Ontario Corporation [37] examined previous meta-analyses-reviews of effective interventions. According to results, initiatives were more effective when programs were implemented together with other community facilities, combined PA with a healthy menu, had a long-term duration and aimed at gradually increasing the intensity of activities. CDC guidelines (2011) recommend Physical Education along with Physical Activity, supporting that a PE program accompanied by PA interventions may lead children to a physically active lifestyle. Overall, a combination of PE, PA and a healthy daily diet inside school may help US and Canada's children to engage in a healthier lifestyle, something that in future may function as a protective factor against obesity epidemic.

Future Directions

As a multifactorial disease, obesity could be proved challenging in examining thoroughly every risk factor. Overall, biological, nutritional and socioeconomic factors seem to interact and finally shape what has been called obesity epidemic. However, future research should focus on better examining low SES, ethnic disparities as well as causality of PA and low-quality food. Literature on gender disparities should go even further by providing not only data but also explanations about gender differences in obesity.

To sum up, policy-makers should emphasize on creating a healthy environment at national and local level, promoting health care settings and improving weight-management and PA programs in every cultural background, socioeconomic and age group (38-41).


  1. Shamseddeen H, Getty JZ, Hamdallah IN, et al. Epidemiology and economic impact of obesity and type 2 diabetes. Surg Clin North Am. (2016) 91: 1163-1172.
  2.  World Health Organization (WHO). Obesity and Overweight. http://www.who.int/mediacentre/factsheets/fs311/en/ (2016).
  3.  Packianathan I, Finer N. Medical Consequences of Obesity. Medicine. (2003) 31: 8-12.
  4.  Jantaratnotai N, Mosikanonc K, Lee Y, et al. The interface of depression and obesity. Obesity Research & Clinical Practice. (2016) 593: 1-10.
  5.  Mehta NK. Obesity and Mortality. International Encyclopedia of the Social & Behavioral Sciences. (2015) 75-81.
  6.  Peeters A, Barendregt JJ, Willekens F, et al. Obesity in Adulthood and Its Consequences for Life Expectancy: A Life-Table Analysis. Ann Intern Med. (2003) 138: 24-32.
  7.  Twells LK, Gregory DM, Reddigan J, et al. Current and predicted prevalence of obesity in Canada: a trend analysis. CMAJ Open. (2014) 2: 18-26.
  8.  Wright S, Aronne L. Causes of Obesity. Abdominal Radiology. (2012) 37: 730-732.
  9.  Black J, Billette JM. Food intake in Canada: Differences among Canadians with diverse demographic, socio-economic and lifestyle characteristics. Canadian journal of       public health. (2015) 106: 52-58.
  10.  Rolls JB. The Supersizing of America: Portion Size and the Obesity Epidemic. Nutrition Today. (2003) 38: 42-53
  11.  An R. Fast-food and full-service restaurant consumption and daily energy and nutrient intakes in US adults. European Journal of Clinical Nutrition. (2016) 70: 97-103.
  12.  An R, Xiang X, Yang Y, et al. Mapping the Prevalence of Physical Inactivity in U.S. States, 1984-2015. Plos ONE. (2016) 11: 168-175.
  13.  Sarma S, Zaric GS, Campbell MK, et al. The effect of physical activity on adult obesity: Evidence from the Canadian NPHS panel. Economics & Human Biology. (2014) 14: 1-21.
  14.  Ladabaum U, Mannalithara A, Myer PA, et al. Obesity, Abdominal Obesity, Physical Activity and Caloric Intake in US Adults: 1988 to 2010. The American Journal of Medicine. (2014) 127: 717-727.
  15.  Chen Y, Mao Y. Obesity and leisure time physical activity among Canadians. Preventive Medicine. (2006) 42: 261-265.
  16.  Juneau CE, PotvinL. Trends in leisure-, transport-, and work-related physical activity in Canada 1994 -2005. Preventive Medicine. (2010) 51: 384-386.
  17.  Kim YJ. The long-run effect of education on obesity in the US. Economics & Human Biology. (2016) 21: 100-109.
  18.  Flegal KM, Carroll MD, Kit BK, et al. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA. (2012) 30: 491-497.
  19.  McGuire S, Shields M, Carroll MD, et al. Adult Obesity Prevalence in Canada and the United States. NCHS Data Brief no. 56, Hyattsville, MD: National Center for Health Statistics, 2011. Advances in Nutrition. (2011) 2: 368-369.
  20.  Ogden CL, Carroll MD, Fryar CD, et al. Prevalence of obesity among adults and youth: United States, 2011-2014. Hyattsville, MD: National Center for Health Statistics. (2015) 219: 1-8.
  21.  Ogden CL, Lamb MM, Carroll MD, et al. Obesity and socioeconomic status in adults: United States 1988 -1994 and 2005-2008. NCHS data brief no 50. Hyattsville, MD: National Center for Health Statistics. (2010).
  22.  Hajizadeh M, Karen Campbell M, Sarma S. Socioeconomic inequalities in adult obesity risk in Canada: trends and decomposition analyses. The European Journal of Health Economics. (2014) 15: 203-221.
  23.  Devaux M, Sassi F, Church J, et al. Exploring the Relationship between Education and Obesity. OECD Journal: Economic Studies. (2011) 1: 1-40.
  24.  Broady K, Meeks A. Obesity and social inequality in America. The Review of Black Political Economy. (2015) 42: 201-209.
  25.  Tremblay MS, Katzmarzyk PT, Bryan SN, et al. Obesity, overweight and ethnicity. Health Reports. (2005) 16: 23-34.
  26.  Wang Y, Beydoun MA. The obesity epidemic in the United States-gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis. Epidemiologic Reviews. (2007) 29: 6-28.
  27.  Walker RE, Gordon M. The Use of Lifestyle and Behavioral Modification Approaches in Obesity Interventions for Black Women. Health Education & Behavior. (2014) 41: 242-258.
  28.  Kumanyika SK. Understanding ethnic differences in energy balance: Can we get there from here? American Journal of Clinical Nutrition. (1999) 70: 1-2.
  29. Kanter R, Caballero B. Global Gender Disparities in Obesity: A Review. American Society for Nutrition. (2012) 3: 491-498.
  30.  Pouliou T, Elliot JS. Individual and socio-environmental determinants of overweight and obesity in Urban Canada. Health & Place. (2010) 16: 389-398.
  31.  World Health Organization (WHO). REGIONAL COMMITTEE FOR EUROPE 64th SESSION Copenhagen, Denmark, 15-18 September 2014. European Food and Nutrition Action Plan 2015 -2020. (2015).
  32.  Centers for Disease Control and Prevention. Strategies to Prevent Obesity and Other Chronic Diseases: The CDC Guide to Strategies to Increase Physical Activity in the Community. Atlanta: U.S. Department of Health and Human Services. (2011).
  33. Centers for Disease Control and Prevention. Strategies to Prevent Obesity and Other Chronic Diseases: The CDC Guide to Strategies to Increase the Consumption of Fruits and Vegetables. Atlanta: U.S. Department of Health and Human Services. (2011).
  34. Cobb LK, Appel LJ, Franco M, et al. The relationship of the local food environment with obesity: A systematic review of methods, study quality, and results. Obesity. (2015) 23: 1331-1344.
  35. Ferris M. Preventing Obesity in Canada's Aboriginal Children: Not Just a Matter of Eating Right and Getting Active. International Indigenous Policy Journal. (2011) 2: 1-13.
  36. Shirley K, Rut?eld R, Hall N. Combinations of Obesity Prevention Strategies in US Elementary Schools: A Critical Review. J Primary Prevent. (2015) 36: 1-20.
  37. Ontario Agency for Health Protection and Promotion (Public Health Ontario). Addressing obesity in children and youth: evidence to guide action for Ontario: summary report. Toronto, ON: Queen’s Printer for Ontario. (2013).
  38. Anderson LM, QuinnT A, Glanz K, et. al. The Effectiveness of Worksite Nutrition and Physical Activity Interventions for Controlling Employee Overweight and Obesity: A Systematic Review. American Journal of Preventive Medicine. (2009) 37: 340-357.
  39. Gartner DR, Taber DR, Hirsch JA. The spatial distribution of gender differences in obesity prevalence differs from overall obesity prevalence among US adults. Annals of Epidemiology. (2016) 26: 293-298.
  40. Skinner AC, Perrin EM, Skelton JA. Prevalence of obesity and severe obesity in US children, 1999?2014. Obesity. (2016) 24: 1116-1123.
  41. Mehta T, Pajewski, NM, Keith SW, et al. Role of a plausible nuisance contributor in the declining obesity-mortality risks over time. Experimental Gerontology. (2016) 86: 14-21.            

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