Where is Malaysia in the midst of the Asian epidemic of diabetes mellitus?

Abstract by (Zaini, 2000)

Population studies all over the world have clearly showed that the prevalence of Type 2 diabetes mellitus (DM) is escalating at phenomenal scale and very likely we are heading towards epidemic proportions.

In 1985, the estimated population of diabetic individuals in the world was 30 million but by 1995 this figure soared to 135 million. Based on current trends, epidemiologists predict that the population of diabetic individuals will swell up to a staggering 300 million by the year 2025. Almost half of that will be in the Asia Oceania region alone. Dr Hilary King of WHO pointed out that there will be a projected rise of about 42% in developed countries whereas the developing countries will see an escalation to the magnitude of 170% (H. King, R.E. Aubert, W.H. Herman, Global burden of diabetes, 1995–2025: prevalence, numerical estimates and projections, Diabetes Care 21 (1998) 1414–1431; WHO Health Report 1997, WHO Switzerland). There will be a 3-fold rise of the disease in Asia and much of these will be seen in China (40 million) and India (55 million) by virtue of the massive population of these countries.

Nevertheless, the other rapidly developing Asian nations like Singapore, Malaysia, Thailand and those making up Indochina will experience the surge. At the same time the prevalence and incidence of diabetes complications will also increase. Based on recent WHO prediction (WHO Newsletter, The global burden of diabetes 1995–2025. World Diabetes 3 (1997) 5–6), it is estimated that by the year 2000 the following figures will be seen:

Taiwan                 35% with retinopathy

Japan                    35% with nephropathy

Thailand               20% nephropathy

Sri Lanka              12% cardiovascular disease

Diabetes complications are major causes of premature death all over the world and most of these are avoidable. DCCT and UKPDS are landmark studies showing strong evidence that major complications can be drastically reduced by maintaining to near normoglycaemic control.

ZAINI, A. 2000. Where is Malaysia in the midst of the Asian epidemic of diabetes mellitus? Diabetes Research and Clinical Practice, 50, Supplement 2, S23-S28.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Abstract

Background

Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference.

Objective

The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires.

Methods

The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB.

Results

The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use.

Conclusions

This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Reference

RHYNER, D., LOHER, H., DEHAIS, J., ANTHIMOPOULOS, M., SHEVCHIK, S., BOTWEY, R. H., DUKE, D., STETTLER, C., DIEM, P. & MOUGIAKAKOU, S. 2016. Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study. Journal of Medical Internet Research, 18.

5 Simple Tips to Maintain Healthy and Slim Body

Tip 1  You must exercise to burn calories

To maintain slim body, you not only need to watch the amount of calories intake but you must exercise to burn excess calories. Physical activity is the most effective way to keep your body in the best shape yet healthy. Try to exercise at least 150 minutes weekly. If you are overweight and obese and want to lose weight and achieve your ideal weight you may need to exercise up to 300 minutes a week.

Tip 2  Eat when you're hungry not when you want

Watch your food intake, eat enough and right. You have to manage your eating behaviour if you demand a slim body. Eat slowly and mindful eating to determine your level of fullness, instead of rushing down your meal until your stomach stretch. It takes about 20 minutes to signal your brain that you are full. Concentrate while eating and avoid distraction such as using a smartphone, watching TV or talking to others while having a meal. Beside, drinking a glass of water before meal also helps to reduce the amount of food intake, since it make you feel full and may reduce the chance of overeating. Also, try to avoid any cues of overeating. 

Tip 3  You are what you eat

Being healthy is also about eat right. Never skip your breakfast! Start your day with healthy breakfast speed up your body metabolism, allow your body to burn more calories throughout the day. Choose healthy carbs, leaner protein and eat more fruits and vegetables. They can keep you satisfied longer and keep your body in shape. Avoid processed food and sugary food that have imbalanced nutrition. Do not waste your calories on unhealthy food!! Choose wisely.

Tip 4  Sleep enough!

Sleep is essential in helping you maintain good body health. Inadequate sleep affects the production of your hunger hormone, leptin and ghrelin level, which make you hard to stick to optimal portion sizes and might increase your food intake up to 30%! Recommended sleep duration is 7-9 hours per day. You may try to use tracker to keep tracker sleep duration.

Tip 5  Free from stress

When stress is not managed well, steroid hormone such as cortisol will be released by the body. Disorders of cortisol production will make your body perceive that you might be starving, hence it will hoard the fat into the abdomen, where it has more cortisol receptors. What's more, stress will increase appetite, make you crave for sweet food as sugar can stimulate your brain to release chemicals that make you conform. You may find relaxing exercise help to manage stress. Share problem with others also might help as well.     

Obesity: Causes and Prevalence

Highlights

• Obesity is a global epidemic primarily resulting from unhealthy environments that cause excess caloric intake and insufficient physical activity
• Obesity increases the risk of adverse health conditions, including cardiovascular disease, diabetes, certain cancers, and musculoskeletal disorders

Abstract

Obesity is a global epidemic primarily resulting from unhealthy environments that cause excess caloric intake and insufficient physical activity. An estimated 3.4 million adult deaths annually are attributed to overweight and obesity, making them the leading causes of death worldwide. Prevalence of adult obesity is 11% globally and 35% in the United States.

Obesity increases the risk of adverse health conditions, including cardiovascular disease, diabetes, certain cancers, and musculoskeletal disorders. Furthermore, obese individuals face stigma and discrimination. The economic costs are substantial as well. Although extensive research is dedicated to managing obesity with lifestyle interventions, medications, and surgery, success has been limited. Short-term weight loss has been achieved, but further research is needed to discover how to maintain healthy weight long term.

Several studies support the use of fiscal and regulatory measures such as taxing sugar-sweetened beverages; however, these measures are often not politically feasible.

               

ALEXANDER, E., SELWYN, A., CALITZ, C., YACH, D. & WANG, Y. C. 2016. Obesity: Causes and Prevalence. Encyclopedia of Food and Health. Oxford: Academic Press.

Microbiota and lifestyle interactions through the lifespan

Abstract of the study

Background

The human intestinal microbiota is an adaptive entity, being capable of adjusting its phylogenetic and functional profile in response to changes in diet, lifestyle and environment. Providing the host with functions important to regulate energetic homeostasis and immunological function, the gut microbiota is strategic to keep metabolic and immunological homeostasis during the entire lifespan.

 Scope and approach

(Rampelli et al., 2016) review studies exploring human gut microbiota variations at different age, describing the trajectory of ecosystem changes during the course of our life, from infancy to the old age. Gut microbiota variation mirroring subsistence strategy is also explored, with a particular focus on how the gut microbiota changes in response to modifications in the diet. Finally, the study illustrates how an abnormal dietary intake could force microbiota to an obese-associated configuration, which concurs in compromising the host metabolic homeostasis.  

Key findings and conclusions

(Rampelli et al., 2016) work allows appreciating the importance of the physiological flexibility conferred by the microbiota for modulating our metabolic and immunological phenotype along the course of our life. Further, the key role of the gut microbiota in providing an extra means of adaptive potential during our evolutionary history is highlighted, suggesting the importance of the intestinal microbiota-host interplay for the maintenance of human health and homeostasis in changing environments. On the other hand, different lifestyle and dietary factors, such as sanitization and antibiotic usage or high-fat diet, can force maladaptive changes in the microbiota configuration which could have negative effects on human health. Thus, it is important to modulate diet and lifestyle habits to keep a mutualistic gut microbiota layout along the course of our life.

Rampelli, S., et al. (2016). "Microbiota and lifestyle interactions through the lifespan." Trends in Food Science & Technology 57, Part B: 265-272.

A pro-inflammatory diet is associated with increased risk of developing hypertension among middle-aged women

Highlights

• A pro-inflammatory diet is associated with higher hypertension incidence in women.
• The pro-inflammatory diet was low in fish, vegetables, fruits, nuts, potatoes, pasta/rice and high in high-fat dairy.
• No interaction between inflammatory potential of diet and BMI or diabetes was found.

Abstract study

A pro-inflammatory diet is thought to lead to hypertension through oxidative stress and vessel wall inflammation. We therefore investigated the association between the dietary inflammatory index (DII) and developing hypertension in a population-based cohort of middle-aged women.

The Australian Longitudinal Study on Women's Health included 7169 Australian women, aged 52 years (SD 1 year) at baseline in 2001, who were followed up through 4 surveys until 2013. The DII, a literature-derived dietary index that has been validated against several inflammatory markers, was calculated based on data collected via a validated food-frequency questionnaire administered at baseline. Hypertension was defined as new onset of doctor-diagnosed hypertension, ascertained through self-report between 2001 and 2013. Generalised Estimating Equation analyses were used to investigate the association between the DII and incident hypertension. The analyses were adjusted for demographic and hypertension risk factors. During 12-years follow-up we identified 1680 incident cases of hypertension. A more pro-inflammatory diet was associated with higher risk of hypertension in dichotomised analyses with an ORfully adjusted of 1.24, 95% CI: 1.06–1.45.

A pro-inflammatory diet might lead to a higher risk of developing hypertension. These results need to be replicated in other studies.

Reference: Vissers, L. E. T., et al. (2017). "A pro-inflammatory diet is associated with increased
                  risk of developing hypertension among middle-aged women." Nutrition, Metabolism
                  and Cardiovascular Diseases 27(6): 564-570.

Short and long-term energy intake patterns and their implications for human body weight regulation

Abstract view

Adults consume millions of kilocalories over the course of a few years, but the typical weight gain amounts to only a few thousand kilocalories of stored energy. Furthermore, food intake is highly variable from day to day and yet body weight is remarkably stable. These facts have been used as evidence to support the hypothesis that human body weight is regulated by active control of food intake operating on both short and long time scales.

The study demonstrate that active control of human food intake on short time scales is not required for body weight stability and that the current evidence for long term control of food intake is equivocal. To provide more data on this issue, the study suggest for developing new methods for accurately measuring energy intake changes over long time scales.

They propose that repeated body weight measurements can be used along with mathematical modeling to calculate long-term changes in energy intake and thereby quantify adherence to a diet intervention and provide dynamic feedback to individuals that seek to control their body weight. Thus mathematical modelling of human metabolism and body weight dynamics suggest that the large day to day variations in energy intake are irrelevant for body weight regulation. Rather, persistent changes in energy intake can lead to substantial weight changes over long time scales.


 
Fig.. Schematic of a method for personalized model-based feedback control of body weight. Using individual anthropometric and demographic data, a personalized mathematical model of metabolism is created to plan a lifestyle intervention to achieve a goal body weight in a specified time frame. By monitoring body weight and physical activity repeatedly, adherence to the intervention can be calculated and used iteratively to provide quantitative feedback regarding revised body weight predictions or changes in the prescribed intervention required to achieve the body weight goal.

Reference abstract: Chow, C. C. and K. D. Hall (2014). "Short and long-term energy intake patterns and their implications for human body weight regulation." Physiology & Behavior 134: 60-65.

Metabolically obese, non-obese (MONO): Who are they???

Metabolically obese, non-obese (MONO): Study finding

Metabolically obese, non-obese(MONO) was defined as individuals with Body Mass Index(BMI) range 18.5-29.9 kg.m² and metabolic syndrome. Well known obesity placing individual at high risk for chronic disease. The non-obese individuals could have metabolic disorders that are typically associated with elevated BMI, placing them at elevated risk for chronic disease as well. 

Based on (Lee et al., 2017) study on Metabolic syndrome among non-obese adults in the teaching profession in Melaka, Malaysia, among 1168 teachers included in the study, the prevalence of MONO was 17.7%. It is found that MONO prevalence was higher among males, Indians, and older participants and inversely associated with sleep duration. Besides, metabolic syndrome was also more prevalent among those with central obesity, regardless they were normal or overweight. Those with BMI 27.5-29.9 kg/m² have the highness odds of metabolic syndrome compared with BMI 18.5-22.9 kg/m². It shown that those with BMI ≥23.0 kg/m² had significantly higher odds of metabolic syndrome even the BMI is normal. 

Therefore, the healthcare professionals and physicians should start to screen non-obese individuals for metabolic risk factors. It is recommended individual with central obesity and BMI ≥23.0 kg/m² to screen for metabolic risk factors as early prevention of chronic disease and start to reduce waist circumference and achieve BMI ≤23. 0 kg/m² through healthy diet and physical activity.

LEE, S. C., HAIRI, N. N. & MOY, F. M. 2017. Metabolic syndrome among non-obese adults in the teaching profession in Melaka, Malaysia. Journal of Epidemiology, 27, 130-134.