New research published in the British Medical Journal on May 4, 2016, has concluded that obesity is associated with high mortality rates when observing the data for nearly 30 million people. The trends show that lowest mortality rates are observed in people with the BMI of 23 to 24 among non smokers, 22 to 23 in healthy non smokers, and showed that people with the BMI of 20 to 22 live the longest.
The study is significant as standard policy of World Health Organization (WHO) currently dictates that the healthy BMI should be within the normal range of 18.5 to 24.9. Recommendations also suggest staying within the lower limit of this range, as evidence suggests, increased risk of diabetes, cancer, cardiovascular disease, while there was risk of some other diseases if it went to the upper normal range. This study however shows that after the analysis of data of more than 30 million people, lowest mortality rates exit within the range of 22 to 24 on a BMI scale.
The study was conducted under the leadership of Dagfinn Aune of Department of Epidemiology and Biostatistics, Imperial College, London, UK, and Department of Public Health and General Practice at Norwegian University of Science and Technology, Norway, who has previously been a critic of two Centers of Disease Control and Prevention (CDC) studies, published in 2005 and 2013 in the Journal of American Medical Association.
The results of those studies suggested that there was a 6% lower risk of death in people who were overweight.
Aune, at the time, told NBC News through an email that, “Unfortunately, sometimes bad science is published and gets a lot of media attention — misleading the public.”
Latest data suggests that 30% of world population (2.1 billion) people are either overweight or obese. The data also shows that no country has reduced their obesity rates in more than three decades.
In the new study researchers accumulated data from PubMed and Embase up to September 23, 2015. Studies included in the research were the ones which reported adjusted risk estimates for at least three categories of BMI and the data was analyzed through random effect models and fractional polynomial models.
Nearly 230 studies were included in the research with more than 3.74 million deaths. Particularly for non smokers the data was included form 53 studies with more than 738,144 deaths. 96 were from Europe, 71 from North America, 3 from South or Latin America, 49 from Asia, 10 from New Zealand and Australia, and 1 form Pacific region. This helps the research to be more inclusive and provides representativeness.
The study provides further evidence of association of premature mortality with BMI as a measure of adiposity.
The results observed showed a relative risk of 1.18 with every five unit increment in BMI among non smokers, 1.21 among healthy non smokers, 1.27 among healthy never smokers with exclusion of early follow-up and 1.05 among all participants.
The lowest risk was observed in never smokers with a BMI of 23 to 24, 22 to 23 among healthy never smokers, and 20 to 22 among never smokers with more than 20 years of follow-up. The dose response curve showed a U shape for all participants and a J shape among non smoker categories.
In analysis the dose response curves also exhibited results consistent with those of the National Cancer Institute (NCI) Cohort Consortium and also partially consistent with the results of analysis of Prospective Studies Collaboration, which shows that the increase in risk of mortality was more pronounced in current smokers than non smokers for people with a BMI of more than 20.
Even when the researchers adjusted their data for age, education, dietary pattern, location, alcohol, height, physical activity, intake of fat, vegetables and fruit, the results were the same.
The team took special care to minimize the confounding effects of smoking and pre-diagnostic weight loss associated with some form of disease. Smoking is itself an important risk factor for premature mortality and is often associated with low body weight, which leads to a low BMI.
BMI, Body Mass Index or Quetelet Index, is usually used to roughly estimate the adiposity of a person’s body and can be calculated by dividing weight in kilograms by the square of the person’s height in meters.
National Institute of Health (NHS), UK, also provides an online BMI calculator on its website.
Body Mass Index is often limited due to issues of scaling. It can also often ignore variation in physical characteristics and cannot differentiate between fat mass and muscle mass. BMI is often not clear on limits of its categories and can also show variations in relation to health. However, some experts believe that despite being inaccurate and needing a revision, BMI is convenient when making day to day estimates.
Alternatives to BMI index for measuring appropriate weights at different heights can be BMI Prime, Surface-based Body Shape Index, and Modified Body Mass Index.