The digital lifestyle program reduces the risk of diabetes by 46% in prediabetics, the study of 130,000 adults reveals

Could a 45-minute weekly digital coach be the key to reverse diabetes? A new 130K + adult study presents spectacular risk reduction rates and remission, without pills or extreme diets.

Study: Modification of the lifestyle in prediabetes and diabetes: a great analysis of the population. Image credit: RSPLANETA / Shutterstock

In a recent article published in the journal NutrientsResearchers in the United States have evaluated a large population of predica, diabetics and healthy individuals to test the effectiveness of a digital lifestyle modification program to reduce cardiovascular and diabetes risk and improve metabolic markers.

Their results indicate that the intervention of the lifestyle has considerably reduced the risk of diabetes to 10 years in prediabetics by almost 46% and increased the rate of diabetes, stressing the importance of lifestyle changes.

However, the study was not a randomized trial, and participation in lifestyle intervention was voluntary, which can introduce a selection bias.

Background

Diabetes mellitus is diagnosed on the basis of high levels of fasting glucose or HBA1C and is a significant risk factor in neuropathy, retinopathy, kidney disease and atherosclerotic cardiovascular diseases (ASCVD).

Prediabetics affect approximately a third of adults of average and older in the United States, and various factors such as inactivity, family history and obesity increase the risk of progressing to diabetes.

Behavioral lifestyle interventions that target weight loss of 7% and increased physical activity can half the risk of diabetes, but traditional programs require frequent sessions in person and are not widely adopted. Risk prediction models have been developed to identify high-risk individuals, using factors such as glucose, body mass index (BMI), high density lipoprotein cholesterol (HDL-C) and triglycerides.

The authors previously developed a diabetes risk model at 10 years old based on glycated serum albumin (ungladed serum non -protein), fasting glucose, adiponectin and triglycerides, which have reached high predictive precision using prospective data from the Framingham Offspring study. Given the importance of lifestyle changes in diabetes and the prevention of ASCVD, easily implementable interventions targeting high -risk individuals must be tested.

About the study

The study evaluated 133,764 adults, categorizing as diabetics (7.5%), prediabetic (36.2%) and healthy (56.3%), based on levels of fasting and HBA1C glucose.

Participants suffered bloody blood tests measuring adiponectin, insulin, glucose, HBA1C, glycated serum protein, fibrinogen, high sensitivity myeloperoxidase, phospholipase A2 (LPPLA2), highloperoxidase with high-c and standard lipids, Automated and standardized tests.

After 6 to 12 months, a blood -monitoring sampling was carried out for just over 20% of prediabetics and 22% of diabetics. Among those who have follow -up data, 12.2% of prediabetics and 9.7% of diabetic participants agreed to participate in a digital, voluntary and dietary lifestyle focused on food and behavioral changes.

The impact of the program was evaluated using a 10 -year biochemical diabetes risk model previously developed by the authors using data from the Framingham offspring. The model has incorporated glucose into an empty stomach, levels of glycated serum albumin, adiponectin and triglycerides.

Changes in the risk of diabetes, metabolic markers, weight loss and remission rates were analyzed to determine the efficiency of the program compared to participants who have not engaged in the intervention.

Results

The diabetic and prediabetic groups had fewer women than the group of healthy subjects and were significantly older and heavier, with a higher BMI and body weight.

The control of blood sugar has worsened between the groups: HBA1C, fasting glucose, glycated serum protein, fasting insulin and peptide C were all significantly higher in men and prediabetic and diabetic women than in the population of healthy individuals.

Insulin resistance has shown the most striking increase, greater than 75% and 260% in predica and diabetic men, and 112% and 306% in women, respectively. Insulin production was particularly low than in diabetic subjects. Many diabetics have shown both insulin resistance and a reduction in insulin production.

Insulin production and insulin sensitivity in healthy, prediabetic and diabetic subjects. In this figure, we have drawn data for the entire population of 133,764 subjects (56.3% healthy, 36.2% of prediabetics and 7.5% of diabetics). Assessment of the assessment model of homeostasis of insulin production, or Homa_βwas calculated as equal to (360 × empty insulin (µu / ml)) / (plasma glucose on an empty stomach (MG / DL) – 63) as described previously and traced on the horizontal axis (22). The homeostasis model of insulin resistance, or Homa_Irwas calculated as equal to (empty insulin (µu / ml)) × (plasma glucose on an empty stomach (mg / dl)) / 405 as described previously. We then traced the reciprocal of this value multiplied by 100, or like (1 / Homa_Ir) × 100), for the same subjects as an insulin sensitivity measure (Homa_S). What can be clearly seen on the graph is that diabetic subjects rarely have Homa_β of <60 (the value of the 25th centile in healthy subjects), as well as a decrease in insulin sensitivity compared to healthy and prediabetic subjects, with clear lines of demarcation between diabetic, prediabetic and healthy subjects.

Inflammation The markers were high, especially the HS-CRP (90% for men and 200% for women in diabetic). Smaller changes have been observed for adiponectin, fibrinogen, myeloperoxidase and LPPLA2. The risk of diabetes at 10 years was considerably higher in prediabetics (7% for men, 4.2% for women) compared to healthy subjects (0.6% for men, 0.3% for women).

Regarding lipids, only modest changes have been observed for LDL-C and apolipoproteins. However, prediabetic and diabetic subjects had significantly higher fasting triglycerides and a small dense LDL-C, and higher HDL-C levels, highlighting a distinctly more atherogenic atherogenic lipid profile. For example, the small LDL-Cse increased up to 35% in diabetic women, while HDL-C decreased by 23% and triglycerides increased by 70%.

The modification of the lifestyle in prediabetic individuals has considerably reduced the risk of diabetes, triglycerides, LDL-C and resistance to insulin while increasing adiponectin levels compared to witnesses. The analysis revealed that prediabetic subjects experienced a relative reduction of 45.6% of the risk of diabetes provided, compared to a 1.6% reduction in the control group.

Among the diabetics, the lifestyle group reached a 2.4 -time increase in the rate of remission (8.2% against 3.4%), as well as a greater weight loss and improvements in glycemic and inflammatory markers.

Conclusions

The study has shown that prediabetic and diabetic individuals already have significant metabolic and inflammatory changes compared to healthy people. Insulin resistance, more than altered insulin production, seems to cause early anomalies.

However, in established diabetes, insulin resistance and reduced insulin secretion are obvious. Increased levels of HS-CRP suggest an important role in inflammation, while changes in other markers were more modest.

Although lipid anomalies are relatively light for LDL-C and Apolipoproteins, greater differences in triglycerides, HDL-C and small, dense LDL-C suggest increased cardiovascular risk even before the development of manifest diabetes.

The results underline that metabolic deterioration begins well before the diagnosis of clinical diabetes, stressing the importance of early identification and intervention in high -risk individuals.

Although this digital lifestyle program has been effective in improving risk markers, the authors note that wider evidence suggest that entirely digital interventions can have more modest impacts than mixed or face -to -face approaches. The meta-analyzes cited by the authors show that the interventions combined in person and digital lead to greater conversion into normoglycemia than digital programs only.

Future studies should explore more how inflammation and lipid abnormalities contribute to the progression of diabetes and to the risk of cardiovascular disease.