The digital lifestyle program reduces the risk of diabetes by 46% in prediabetics, 130k+ adults reveal

In the last article published in the journal Scientists in the United States evaluated a large population of pre -diabetes, diabetic and healthy people to test the effectiveness of a digital lifestyle modification program in reducing cardiovascular risk and diabetes and improving metabolic markers.

Their findings indicate that lifestyle intervention significantly reduced the 10-year risk of diabetes among the prediabetics by almost 46% and increased the diabetes remission rate, emphasizing the importance of changes in lifestyle.

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

Background

Diagnosis is diagnosed based on elevated glucose or fasting HBA1C and is a significant risk factor for neuropathy, retinopathy, kidney disease and atherosclerotic cardiovascular disease (ASCVD).

Prediabetes affects about a third of middle -aged adults in the United States, and various factors, such as inaction, family history and obesity, increase the risk of going to diabetes.

Behavioral interventions, which is focused on 7% loss of body weight and increased physical activity, can swallow the risk of diabetes, but traditional programs require frequent sessions in person and are not widely accepted. Risk forecasting models have been developed to identify high-risk people, using factors such as glucose, body mass index (BMI), high-density lipoprotein cholesterol (HDL-C) and triglycerides.

The authors previously developed a 10-year risk model of diabetes based on glycated serum albumin (not glycated serum protein), fasting glucose, adiponektyn and triglycerides, which have achieved high predictive accuracy using prospective data from the offspring Framingham study. Given the importance of lifestyle changes in diabetes and ASCVD prevention, easy implementation of interventions addressed to high -risk people should be tested.

About the study

The study evaluated 133,764 adults, categorizing them as diabetes (7.5%), pre -clipping (36.2%) and healthy (56.3%), based on fasting glucose and HBA1C.

Participants underwent blood tests on an empty stomach measuring adiponektyn, insulin, glucose, HBA1C, rag of serum protein, C-reactive protein (LPPLA2 HS-CRP), choloproteolsmoloprotoidase choloproteol, LPOPROTEIN (LDODROTEOL LD-C), independent A2 (LPPLA2). LDL-C and standard lipids, using automated and normalized tests.

After 6 to 12 months, blood samples were taken for just over 20% pre -diabetes and 22% diabetics. Among people with control, 12.2% pre -diabetes and 9.7% of diabetic participants agreed to participate in digital, voluntary, under the control of a dietitian, focused on dietary and behavioral changes.

The impact of the program was assessed using the biochemical 10-year risk model of diabetes previously developed by authors using data from the Framingham offspring. The model included fasting glucose, serum albumin levels, adiponektyn and triglyceride.

Changes in the risk of diabetes, metabolic markers, weight loss and remission indicators have been analyzed to determine the effectiveness of the program compared to participants who were not involved in intervention.

Arrangements

Diabetic and pre -diabetes groups had fewer women than a group of healthy people and were much older and heavier, with higher BMI and body weight.

Blood glucose control has deteriorated in the following groups: HBA1C, fasting glucose, plugged serum protein, fasting insulin and peptides C were much higher in men and women with diabetes than in the population of healthy people.

Insulin resistance showed the most striking growth, larger by 75% and 260% in pre -poore and diabetic men, and 112% and 306% respectively in women. Insulin production was much lower only in people with diabetes. Many diabetics showed both insulin resistance and reduced insulin production.

Inflammation Markers were elevated, especially HS-CRP (by 90% for men and 200% for women in diabetics). Smaller changes were observed for adiponectin, fibrinogen, myeloperoxidase and LPPLA2. The 10-year risk of diabetes was much higher in prediabetics (7% for men, 4.2% for women) compared to healthy people (0.6% for men, 0.3% for women).

As for lipids, only small changes were observed for LDL-C and Apolipoprotein. However, pre-diabetes and diabetic people had much higher fasting triglycerides and small dense LDL-C and lower HDL-C levels, which is clearly emphasized by the more atherosclerotic lipid profile. For example, a small dense LDL-C increased by up to 35%in women with diabetes, while HDL-C decreased by 23%and triglycerides increased by 70%.

Modification of lifestyle in pre-diabetes significantly reduced the risk of diabetes, triglycerides, LDL-C and insulin resistance while increasing the level of adiponectin compared to control. The analysis showed that pre -diabetes experienced 45.6% of the relative reduction of the expected risk of diabetes, compared to only a 1.6% reduction in the control group.

Among the diabetics, the lifestyle group achieved a 2.4-fold increase in remission rate (8.2% vs. 3.4%), along with greater weight loss and improvement of glucose and inflammatory markers.

Conclusions

The study showed that pre -diabetes and diabetic people already show significant metabolic and inflammatory changes compared to healthy people. It seems that insulin resistance, more than impaired insulin production, drives early irregularities.

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

Although lipid abnormalities were relatively mild for LDL-C and apolipoprotein, greater differences in triglycerides, HDL-C and a small dense LDL-C suggest an increased cardiovascular risk even before the development of open diabetes.

The results emphasize that metabolic deterioration begins long before diagnosing clinical diabetes, emphasizing the importance of early identification and intervention in high -risk people.

Although this digital lifestyle program was effective in improving risk markers, the authors notice that wider evidence suggests that fully digital interventions can have a more modest impact than mixed methods or face to face. The meta -analyzes cited by the authors show that combined personal and digital interventions cause greater conversion to normoglycaemia than digital programs.

Future research should further examine how inflammation and lipid abnormalities contribute to the progress of diabetes and the risk of cardiovascular diseases.