The Healthiest Weight: Present and Future

Successful weight loss and maintenance programs should consider the optimal timing for the brain's control of body weight. The bases for successful Weight Management Programs have been recently proposed utilizing a new BMI sub-categorization and current state-of-the-art technologies. An inverse relationship between meal frequency and body weight has also been observed and is directly related to achieving a healthy weight.
Practising regular exercise has also been shown to cause a significant reduction in Heart Rate while achieving and maintaining the Healthiest Weight as well as increasing life expectancy. Thus, the implementation of healthy habits and regular aerobic exercise programs by public authorities may contribute to the reduction in all-cause mortality worldwide. Adapting WHO-defined BMI thresholds to novel calibrated thresholds has been further revalidated by incorporating recently published multi-dimensional data from large- scale worldwide studies, resulting in a new likelihood model of the health risks associated with adiposity. This latest study has great potential in personalized and preventive medicine. In addition to ongoing vaccination programs, the results of this novel approach could be used as an “alternative method of prevention” to naturally tackle the current COVID-19 pandemic, and other anticipated in the future to come. Other current and future weight management developments are also discussed.

Obesity continues to be a very interesting topic of study given its involvement in human disease [1-3], requiring urgent public health solutions [4-6]. The Ideal Weight and the Healthiest Weight (HW), a unique measurement of general health status for everyone, has been an interesting topic for years [7]. For decades, health specialists have been classifying people into different weight categories based on Body Mass Index (BMI) thresholds [8]. This popular measurement, adopted by the World Health Organization (WHO), has been questioned due to various deficiencies in estimating obesity/over weight for both healthy and diseased populations [9]. The main purpose of this article is to review the current obesity concerns, by introducing the HW measurement and recent approaches to assess BMI thresholds using the latest discoveries on: a) Health risks, including COVID- 19, and mortality data; b) The average of adiposity levels with the same BMI across different ages and genders; and c) The optimal timing for the brain control of weight- presetting (the bases of the “Lipostat theory”).

A volunteer individual was subjected to a case study. The participant showed to have a strong commitment to improving both physical and mental health. The values of BMI (Normal category: 18.5–25) were transformed into ideal weights, based on height and weight, and further sub-categorized into three categories [7]. A comprehensive bibliographic review of the best psychological approaches used for motivation and weight management programs was conducted, and the most effective parameters were incorporated into a user-friendly mobile app.

The Present and Future of The Healthiest Weight

Studies have shown that successful weight loss and maintenance programs should consider the optimal timing for the brain control of weight-presetting [7]. The bases for successful Weight Management Programs have been recently proposed employing BMI sub-categorization and current state-of-the-art technologies, the first reported human experiment involving successful long-term weight loss, metabolic adaptation and weight-presetting, which is consistent with the Lipostat theory [7], raising new concepts, ideas and setting up the bases for further investigations. Furthermore, during the same study, an inverse relationship between meal frequency and HW was consistently observed, suggesting that “snack-eating” may help to avoid obesity/weight gain, further supporting other previously published meal frequency studies [10]. On the other hand, this study concluded that aerobic exercise positively contributes to decreasing HR, achieving and maintaining HW, and increasing life expectancy [11,12]. Thus, the implementation of regular aerobic exercise programs by public authorities may contribute to the reduction in all-cause mortality in the population.

This novel approach consisting of adapting WHO-defined BMI thresholds to novel calibrated thresholds has been further revalidated more recently by incorporating published multi-dimensional data from large-scale worldwide studies [13]. 

This novel WHO-readapted probabilistic BMI-based approach is providing a more realistic body weight categorization resulting in a new likelihood  model of the health risks associated with adiposity. This new calibrated version of WHO-defined BMI thresholds set up the bases for further  experimental investigations aiming  at the application of personalized  and preventive medicine, as well as successful long-term Weight and Health Management Programs. In addition to ongoing vaccination initiatives, this novel approach could be used as an “alternative method of prevention” to naturally tackle the current COVID-19 pandemic, and other  anticipated to  come in the future.

While studies show that most people are not able to keep weight loss for the long term, probably due to a lack of motivation, recent studies have shown that the effective application of motivational initiatives is fundamental to creating a positive mindset and habits. The HW studies provide  additional qualitative research on the effect of motivation as a factor in behavioural interventions to reduce obesity/overweight levels in the population, highlighting the importance of self-determination for succeeding in long-term weight loss and maintenance programs [14].

Current modern methodologies

Weight loss and maintenance programs can be delivered through various methods including the latest technologies such as mobile apps. The number of downloadable health-related apps for mobiles has been rising exponentially [15]. Interestingly, out of the thousands of downloadable health-related apps that use effective weight management and scientifically-proven interventions, only one app has been associated with long-term weight loss and HW maintenance, the “One Click to Health” app [7]. This app has also been shown to be fundamental to reducing the chance of disease severity due to COVID-19 as well as other severe diseases [13].

Given the importance of motivation to effectively implement any weight management program, an effective evaluation of the level of motivation before implementing any weight management strategy, as well as monitoring further progress, is fundamental [14]. Based on 14 habits and psychological questions, the “Weight loss motivator” app: First, calculate the level of Weight loss/Maintenance Motivation; Then, gives the advice to boost motivation; and finally, provides useful information and tips for future actions. In summary, the app, which evaluates an individual level of motivation, provides a list of recommendations to help boost motivation, warranting long-term weight loss and HW success and maintenance.

Other modern developments that help to achieve and maintain the HW include the following user-friendly apps: 1) Healthy eating quiz [16]; Calorie breaker [17]; Weight checker [18]; Smart vibes [19]; Future weight [20]; Belly calculator [21]; Smart weight [22]; and Calorie distance[23].  Altogether, these apps are tackling the most important aspects of weight loss and HW success and maintenance, including healthy eating, physical  activity and mindset, all seen from different perspectives.

The future

Many areas of improvement regarding weight management and HW success has been identified [15], setting up the bases for further experimental studies and future eHealth developments. Effective interventions urge the implementation of collaborative efforts for the future development and  testing of high-quality scientifically-driven modern technologies such as mobile apps applied to mHealth weight management before they are distributed into commercial markets.

Weight management mobile apps are currently widely available and very popular but they lack professional content expertise. Only ~0.05% of apps have been developed with an identifiable professional input [24]. Encouraging app development based on mHealth evidence-based approaches would assure content quality, allowing healthcare professionals to recommend their use, and greatly facilitating their professional interventions. Personal contact and frequent interactions in interventions have also been associated with weight loss [25]. By conducting comprehensive literature and clinical trial searches, a recent study found very few active, completed, or published studies testing the efficacy of mobile apps using randomized controlled trials [26]. Ideally, research efforts should focus on demonstrating the efficacy of behavioural interventions and remote self- monitoring for mHealth weight management treatments using effective, randomized controlled trials. Furthermore, an article has shown that most currently available apps collecting dietary intake use the same nutrition assessment methods and technologies for data input [27]. However, emerging technologies, such as image recognition, natural language processing, and artificial intelligence (AI), have not yet been widely identified.

Furthermore, most of the available apps have no decision-making engine capable of providing personalized expert advice. Collaborative efforts between developers, researchers, clinicians, and patients will be highly recommended to develop and test high-quality science-based mobile apps for the effective implementation of mHealth weight management programs before they can be widely distributed into online markets [28,29].

As for the current indiscriminate use of machine learning and AI applied to most fields, the use of AI in weight loss programs is still in the early stages. Recently, some authors have proposed a framework for the applicability of AI for weight loss but cautioned about its contingency upon  engagement  and context ualisation [30]. Further research into AI and its application in telemedicine, with clinical trials investigating effects on weight, health  behaviours, user engagement and acceptability, appears to be a rising area of investigation [31].