The system for maintaining a healthy body weight, human or animal, is weight management. While it monitors subjects in real time, it also relies on both established and new scientific data as guidelines for activity and nutrition.
Proper weight maintenance improves physical and mental well-being as well as prevents future illness or injury.
To build a proper weight maintenance system, begin with individual age, sex, activity level, and current and desired weight. Additional vital data includes medical conditions, allergies, and religious or other convictions that restrict diet.
External data necessary for weight maintenance are nutrition data and, if relevant, data on medications taken—especially their interactions with food or side effects. Some medications, for example, cause sleep disturbances which make weight management very difficult.
Organizational psychology data may also help a weight management system, especially if this system is part of a workplace health and wellness plan; such psychological data can help provide motivation for employees participating in these programs.
Budget or other financial data may also be included in a this type of system.
There are several challenges of this use case. Some environments, for example, lack enough food or simply enough nutritious food; social obligations pressure individuals to overeat or under-eat; underlying health issues may interfere with the ability to follow a diet or exercise program at all.
There are also enormous amounts of nutrition data that is seemingly inconsistent or contradictory. Additionally, social trends often outpace the science. For example, the benefits of fasting or eating multiple meals, eating a low-carb, high-fat diet vs a low-fat, high-carb diet, or whether eggs are healthy at all. Sport or exercise data, especially as it relates to age or sex, suffers from similar inconsistent data or incorrect information.
Used by many major corporations, from Samsung to Aetna, Noom’s health coaching—with weight management services—show results.
[They have] published research in internationally recognized journals such as Nature and British Medical Journal (BMJ) 1, which has shown that 64% of Noom users lost 5% or more of body weight, greatly reducing their risk of diabetes and other conditions.
In 2017, Noom’s program received full recognition by the Centers for Disease Control and Prevention (CDC)
IBM MarketScan Research Databases provides one of the oldest continually-updated collection of health claims data in the USA. Organizations use this data to prove their value to healthcare professionals, insurers, and private individuals.
The data includes drug claims, dental claims, lab results, hospital discharges, and EMR data for millions of people in the country. It also contains workplace productivity data, telling institutions how many workplaces absences they suffer and how many of their healthcare workers suffer disability due to their work.
FooDB’s dataset provides information about food for users to better understand their composition, macronutrients and micronutrients. Their database contains almost 800 foods and is a free resource to the public.
Definitive Healthcare’s Hospital & IDNs Database provides benchmark data for hospitals and IDNs to compare against competitors and identify growth opportunities.
Zeta-Tools Health Research conducts research among physicians, general population, and patients for marketing needs.
EMIS Health EMIS Web allows healthcare providers, community care services and hospitals to share expertise and information between their varying areas improving customer care and safety.