Month: June 2018

Preventive Care


Practical thoughts for responsible people and their governments. – By Dr. Mehdi Khaled

There are striking similarities between global warming and modern-age chronic medical conditions. Both come with enough scientific evidence predicting their paths, their effects on our planet, and on our wellbeing and economies respectively. While a lot has been undertaken globally in defining the framework of actions to be engaged at individual and government levels in tackling the global warming plague, initiatives anticipating the onset of preventable causes of premature deaths and poor life quality are fragmented and poorly coordinated.

While there is more than one underlying cause to life-threatening chronic diseases, I will focus on obesity which, because of its pandemic nature, remains the main underlying factor of human health mischief and high mortality rates today. The causality link between obesity, metabolic (diabetes, high cholesterol, etc) and cardiovascular illnesses is supported by a wide array of scientific evidence1.

Globally, the prevalence of chronic, non-communicable diseases is increasing at an alarming rate. About 18 million people die every year from cardiovascular disease, for which diabetes and hypertension are major predisposing factors. Propelling the upsurge in cases of diabetes and hypertension is the growing prevalence of overweight and obesity – which have, during the past decade, joined underweight, malnutrition, and infectious diseases as major health problems threatening the developing world.

In 2014, there were around 600 million obese adults, with over twice that number overweight – that means around 1.9 billion adults are too fat. Over 200 million school-age children are overweight, making this generation the first predicted to have a shorter lifespan than their parents, according to the International Obesity Task Force2.

Obesity is a medical condition described as excess body weight in the form of fat. When accumulated, this fat can lead to severe health impairments. The prevalence of obesity is continuing to increase at an alarming rate in both the developed world and the developing world. This is of major concern not only because of the well-established detrimental health consequences for the obese person but also because obese parents are likely to have obese children, thus perpetuating a cycle of obesity3.

Obesity is measured by the Body Mass Index (BMI) value. That is the body weight in kilograms divided by the square of the body height in meters. According to the WHO, a BMI equal or higher than 30 for adults defines obesity. In clinical settings though, the interpretation of the BMI value depends on the gender, age and race. Henceforth, an 8-year-old Caucasian boy whose BMI is 30 is considered a healthy individual, whereas a 42-year-old with the same characteristics and BMI value would be considered obese. Nevertheless, a clinical study published in 2011 suggests that an elevated BMI in adolescence – one that is well within the range currently considered to be normal – constitutes a substantial risk factor for obesity-related disorders in midlife.

Although the risk of diabetes is mainly associated with increased BMI close to the time of diagnosis, the risk of coronary heart disease is associated with an elevated BMI both in adolescence and in adulthood, supporting the hypothesis that the processes causing incident coronary heart disease, particularly atherosclerosis, are more gradual than those resulting in incident diabetes4.

In the past 20 years, the rates of obesity have tripled in developing countries that have been adopting a Western lifestyle involving decreased physical activity and overconsumption of cheap, energy-dense food. Such lifestyle changes are also affecting children in these countries; the prevalence of overweight among them ranges from 10 to 25 per cent, and the prevalence of obesity ranges from 2 to 10 per cent. The Middle East, Pacific Islands, Southeast Asia and China face the greatest threat. Interestingly enough though, none of the developing nations in these geographies is represented on the World Obesity Federation Steering Committee.

The relationship between obesity and poverty is complex: Being poor in one of the world’s poorest countries (i.e., in countries with a per capita gross national product [GNP] of less than USD$800 per year) is associated with underweight and malnutrition, whereas being poor in a middle-income country (with a per capita GNP of about USD$3,000 per year) is associated with an increased risk of obesity5.

Simply put, obesity is a behavioural disorder and diet studies are nothing else but behavioural studies. Obesity is frequently an acquired condition through the perpetual iteration of poor lifestyle choices, especially in adults. Children’s obesity is a more complex problem where their parents largely make these choices for them. There are two types of choices: Those made deliberately by the individual and those under the influence of their immediate social circles – choice by proxy.

Social network models in the Framingham Heart Study6 (No, not Facebook! This was a real social life network back in 2000) show a clear social connection between individuals of similar BMI. This strongly suggests that individuals with a certain body weight tend to flock with their peers in the same BMI range.

There are two types of actions underpinning poor choices: Emotionally active actions and emotionally passive ones.

Making a deliberate decision to not do something science has proven is good for your health is a passive action. While active actions trigger the classic feeling of ‘guilt’ and the related (mostly missed opportunities of) New Year’s resolutions (“I will quit smoking by Jan 1st!”), the passive actions are mostly sub-conscious and don’t surface as often as the active ones, e.g. every smoker I know thinks about quitting every day, but they remember they missed an opportunity to go for a 30-minute run only once a week – at the very best. The prevalence of choice types and their sub-categories in society is not clear as there’s a high level of individual and contextual variance. While the psychological mechanisms of making poor lifestyle choices is well understood, changing the course of actions to make better ones remains a true individual challenge.

Following the universal consensus that every individual is responsible for his own health, it really remains up to every one to seek ways to bring their high BMI back to normal and maintain it over time. Ultimately, the BMI is nothing else but the clinical representation of the delta between the calories ingested into a body and those burned by the same. Because we’re humans and we live in an increasingly complex world, mathematical variations in that formula always occur. In summary, most of us know the best way to keep a sane BMI is to maintain a balanced food and exercise ratio over time.

Today, the modern world offers a myriad of wearable sensors to monitor our energy outputs from the simple step-count to the number of sports activities with all the covered distances in kilometres over time. While the scientific correlation between using wearable health trackers and achieving significant and long-term health benefits have been very controversial, these devices carried the promise to change their users’ physical activity profiles by kicking them out of a sedentary lifestyle.

This can be achieved by triggering more awareness on the user’s perceived activity levels. However, while the awareness expectation was widely met, the initial high adoption rate of these sensors contrasts sharply with the high dropout rates. Indeed, in a 2015 study of the Pennsylvania State University, results show a 50 per cent drop rate at 15 days and a surprising 75 per cent drop rate at just 30 days from the beginning of using wearable activity trackers7. These results clearly show that like classic food diets, these “digital diets” are not changing their user’s behaviours in short and long terms. Like with food diets and if these ever helped them lose weight, users gain it back again as soon as they stop using their wearable health trackers.

The lifestyle choices we make remain very much framed by local government healthcare strategies, food and drug policies, as well as by the existence of infrastructure to practice physical activities.

The emergence of Pay-for-Performance models (P4P) in the UK Healthcare System in the early 90s, was more recently followed by a tuned-up version under the so-called Accountable Care Act in the USA are encouraging initiatives to tackle the obesity issue at the population level. Both are national programmes that reward caregivers who improve their patients’ BMI and/or help them quit smoking (among other health outcome KPIs). Still, these programmes fall short from implementing long-term lifestyle changes that would reverse the course of obesity in the related societies.

Classic health models suggest there are three population segments among the citizens: Healthy people, those at risk of developing certain diseases and those who are already sick. Predictive statistical models show alarming projected prevalence rates of obesity globally. A sound and logical healthcare strategy would therefore anchor its priorities in designing and driving programmes aiming at keeping the healthy people healthy and those at risk of running overweight at bay – as long as possible. With the exception of the US, the GDP percentage of public healthcare expenditure is a single digit number (five to eight per cent) in most affected economies.

Knowing that 80 per cent of those healthcare budgets flow into managing chronically ill patients (most of which are obese), it is innocuous to argue that spending some two per cent of that budget to proactively prevent obesity from eating up the society would not only flatten the growth rate of healthcare expenditure, but also directly contribute to more positive economic balance sheets. Yes, taking down fat from your population grants you a leaner economy as well. Scientific evidence is however needed to support these presumptions but we can safely consider disease prevention as an economic growth accelerator.

In the US, government healthy-eating initiatives are dwarfed by the USD$1.6 billion spent by the food industry influencing kids to consume unhealthy food. The Centers for Disease Control’s budget for nutrition, physical activity, and obesity is about USD$41 million for Americans of all ages. The U.S. Department of Agriculture’s Team Nutrition, whose goal is to improve children’s eating and physical-activity habits, has an annual budget of about USD$10 million8.

Today, many governments still make a deliberate choice to sustain the unhealthy spending drivers instead of drafting and enforcing successful practices on food policies. By not doing so, these governments directly contribute to incurring physical long-term prejudice to the wellbeing of the very citizens they have vowed to protect.

I remain a strong advocate of enforcing detailed food labeling and agriculture policies as well as imposing high-level taxes on junk food if not banning certain items from entering the food chain at all. Education and awareness remain however the biggest challenge, especially in scattered Asian geographies. Professional and sound recommendations to governments on strategies to tackle the obesity pandemic in their respective societies are very well documented. Approaches to action those are largely lagging behind in most countries mainly because of political short-sightedness and other mysterious economic drivers.

Realistically though, short-term positive outcomes and quick wins remain very much within reach: If active lifestyle programmes are already working at individual levels, scaling them up to run healthy population campaigns would very much benefit from the social accelerator effect and other incentives to achieve the desired outcomes within one year only. Other complementary initiatives will then have to kick in to maintain the social BMI at the newly achieved levels (long-term benefits). Cascading social models to design and drive these programmes to success are documented.

The other reality about healthcare today is the word itself infers a negative state of wellbeing and sickness. However true, the aptitude of modern healthcare systems to successfully promote wellbeing, foresee and prevent diseases should be added to the metrics measuring their ability in curing them. In most Asian countries, the ageing tsunami is right around the corner and if these governments keep ignoring the rampant obesity issue, the already shorter life-spanned “active” population won’t be lean enough to keep their economies going.

It would be very practical to think that Earth Day is every day, not once a year. The very same line of thoughts should apply for our lifestyle choices. Nobody’s perfect but every day we have an opportunity to make the right choices. Hence, whether you represent your government body or your own, carpe diem!






Dr. Mehdi Khaled is the Founder and Managing Director of Fit Populations LLC and can be reached at


  1. Franks P.W., Hanson R.L., Knowler W.C., et al. Childhood Obesity, Other Cardiovascular Risk Factors, and Premature Death. N Eng J Med 2010; 362:485-493
  2. Haslam DW, James WP. Obesity. Lancet 2005;366:1197-1209
  3. Susan E. Ozanne, Ph.D. Epigenetic Signatures of Obesity. N Eng J Med 2015; 372:973-974
  4. Amir Tirosh & Al. Adolescent BMI Trajectory and Risk of Diabetes versus Coronary Disease. N Eng J Med 2011; 364:1315-1325
  5. Parvez Hossain & Al. Obesity and Diabetes in the Developing World — A Growing Challenge. N Engl J Med 2007; 356:213-215
  6. Christakis NA, Fowler JH. The Spread of Obesity in a Social Network. N Engl J Med 2007; 357:370-379
  7. Shih, P.C., Han, K., Poole, E.S., Rosson, M.B., Carroll, J.M. Use and Adoption Challenges of Wearable Activity Trackers — iConference 2015 Proceedings.
  8. US Federal Trade Commission report on food marketing to children (2006)

Credits : InfoMed (Malaysia)