A Company Is Only as Healthy as Its Workers: A 6-Month Metabolic Health Management Pilot Program Improves Employee Health and Contributes to Cost Savings.
Nicholas G NorwitzAdrian Soto-MotaTro KalayjianPublished in: Metabolites (2022)
Chronic diet-related metabolic diseases, including diabetes and obesity, impose enormous burdens on patient wellness, healthcare costs, and worker productivity. Given the interdependent nature of the human and economic costs of metabolic disease, companies should be incentivized to invest in the health of their workforce. We report data from an ongoing pilot program in which employees of a manufacturing company with obesity, prediabetes, or diabetes are being treated by a metabolic health clinic using a carbohydrate restriction, community-orientated telemedicine approach. 10 patients completed the first 6 months of the program, and all lost weight, with a mean weight reduction of 38.4 lbs (17.4 kg). Improvements in HbA1c, fasting glucose, HOMA-IR, triglycerides, C-reactive protein, and systolic blood pressure were also observed across the group. Furthermore, the 10-year risk of having a major cardiovascular event, as calculated by the American Heart Association risk calculator, decreased from a mean of 9.22 to 5.18%, representing a 44% relative risk reduction. As a result of improvements in their metabolic health, patients were able to discontinue medications, leading to an estimated annualized cost savings of USD 45,171.70. These preliminary data provide proof-of-principle that when companies invest in the metabolic health of their workers, both parties stand to gain.
Keyphrases
- healthcare
- public health
- mental health
- blood pressure
- type diabetes
- health information
- weight loss
- end stage renal disease
- newly diagnosed
- insulin resistance
- ejection fraction
- heart failure
- physical activity
- weight gain
- chronic kidney disease
- endothelial cells
- quality improvement
- primary care
- health promotion
- randomized controlled trial
- cardiovascular disease
- big data
- left ventricular
- adipose tissue
- blood glucose
- climate change
- machine learning
- glycemic control
- atrial fibrillation
- social media
- risk assessment
- artificial intelligence