Impact of BMI on Health Status, Hospitalizations, Day Procedures, and Physician Costs

While in individuals BMI may not be the best measure of obesity (or health), in population studies, it does serve as a reliable indicator of the ‘burden’ of overweight and underweight.

In a paper by Jean-Eric Tarride (McMaster University) that we just published in ClinicoEconomic and Outcomes Research, we examine data from all Ontarians who participated in the Canadian Community Health Survey (CCHS), cycle 1.1 and provided consent to data linkage were linked to three administrative databases.

Obese adults, and to a lesser extent overweight adults (together about 50% of the population), were more likely to report physician-diagnosed comorbid conditions, to use medications, and to have a lower health-related quality of life.

After adjustment for for personal income, smoking status, physical activity status, age and gender, the hospitalization and physician costs were respectively 40% and 22% higher among obese and overweight adults than among normal-weight adults.

No statistical cost differences were observed between normal and underweight individuals or between normal and overweight individuals.

On the other hand, health-related quality of life was significantly lower in both the underweight and obese adults when compared to normal-weight individuals.

With regard to the excess costs associated with obesity, these were not equally distributed between the genders – surprisingly enough, overall obese men did not appear to incur higher medical costs in this analysis.

In contrast,

“women had significantly higher physician, day procedure and hospitalization costs than men once a cost has been incurred. In addition, women had a higher probability of being hospitalized or undergoing a day procedure than men.”

Thus, we suggest that obesity programs targeted towards women may have greater potential for reducing costs associated with hospitalization, day procedures, and physicians.

Similarly, increased costs were not equally distributed across age groups – the greatest cost difference were seen in the 40–59 year old age group.

This finding suggests that obesity programs should perhaps focus their interventions on middle-aged obese individuals, which also suggests that the workplace may be the most practical environment for the implementation of such programs.

In this paper, we also point out that,

“…BMI does not truly reflect the burden of obesity-related health risks. Thus, as recently demonstrated in several large US population samples,26,27 the Edmonton Obesity Staging System (EOSS), which classified overweight and obese individuals on a 5-point ordinal scale based on the presence of medical, mental and/or functional comorbidities, strongly predicted mortality, whereas BMI did not. Importantly, in this analysis, a considerable proportion (about 50%) of individuals in the overweight range presented with obesity-related health problems (EOSS >1), while a substantial number (about 30%) of individuals with BMI >30 had no obesity-related health risks.”

It is also important to note that this paper did not look at all of the health care costs related to obesity – there were no data for medication cost or other health care costs that may have been incurred by participants – it is very likely that these costs will also be higher in obese people with associated health problems.

Reason enough to hope that with better obesity prevention and/or treatment efforts, some of these excess costs could be reduced – however, that of course, remains to be seen, as neither obesity prevention nor treatment are likely to be cheap. So far, cost savings with obesity treatment have only been shown for bariatric surgery in patients with significant health problems like diabetes (EOSS 2+).

Edmonton, Alberta

ResearchBlogging.orgTarride JE, Haq M, Taylor VH, Sharma AM, Nakhai-Pour HR, O’Reilly D, Xie F, Dolovich L, & Goeree R (2012). Health status, hospitalizations, day procedures, and physician costs associated with body mass index (BMI) levels in Ontario, Canada. ClinicoEconomics and outcomes research : CEOR, 4, 21-30 PMID: 22347802