Monday, May 30, 2022

Prediabetes and Retinopathy

 Retinopathy is a disease of the retina. There are various forms of the disease. For example, there is hypertensive retinopathy and there is diabetic retinopathy. Treatment and prevention of these diseases involves controlling  high blood pressure and blood glucose levels. And of course, a yearly eye exam is critically important for those persons with retinopathy. Diabetic retinopathy is the most common form of the disease. And this type of retinopathy is one of the principal causes of vision loss worldwide. At least two studies have linked prediabetes to a high level of retinopathy.

Prediabetes is where there is a higher than normal level of glucose in the blood, but the elevated level is not high enough to be deemed diabetes. For some time, it was known that prediabetes was often followed by diabetes. So, a study was designed to look into the progression from prediabetes to diabetes. The Diabetes Prevention Program trial was done between 1996 and 2001. The researchers looked at how prediabetes could lead to diabetes. It was found that prediabetes raises the risk of type 2 diabetes, and treating prediabetes could delay or prevent type 2 diabetes is many cases.

Further investigation into the incidence of retinopatyh among persons with prediabetes was done after the original Diabetes Prevention Program study. The researchers looked at a subset of the participants in the original study. There were 3224 participants in the original Diabetes Prevention Program study. The subset consisted of 302 participants. The researchers "found detectable retinopathy in 7.6% of patients," who had prediabetes. So, retinopathy can be associated with prediabetes.

In another study, to determine a relationship between retinopathy and prediabetes, researchers examined articles in MEDLINE, EMBASE, PubMed, Web of Science, CINAHL, Google Scholar and the Cochrane databases. After examining 5994 abstracts and 98 full-text articles, the researchers chose twenty-four studies for their analysis. The twenty-four studies consisted of 8759 participants with prediabetes. The researchers concluded that there was a 6.6% rate of retinopathy among persons with prediabetes compared with 3.2% for populations with normal levels of blood glucose.

The above studies indicate that healthcare providers may want to examine the eyes of patients with prediabetes. The providers may detect early signs of retinopathy. And this would be beneficial to the patient and the provider.


Tags: environmental scanning, balanced scorecard, business planning, strategic management, bariatric medicine,obesity medicine,medical practice start up,bariatric industry analysis, weight loss industry analysis, weight management industry analysis, diabetes prevention, prediabetes

Saturday, May 28, 2022

Using Simulation to Investigate Obesity and Type 2 Diabetes

According to Wikipedia, “A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation.”

Simulation is beneficial for assessing public health concerns.
Indeed, simulation, using modeling, has been employed to forecast future levels of obesity and the relationship between obesity and type 2 diabetes as we age.

In one study, 41,567 children and adults' life paths were examined using simulation. And the researchers concluded that, "Given the current level of childhood obesity, the models predicted that a majority of today’s children, [approximately 57%] will be obese at the age of 35 years, and roughly half of the projected prevalence will occur during childhood.”

Additionally, another study employed simulation to analyze the incidence and trends of obesity, as well as the influence of obesity on the risk of type 2 diabetes in a computer model of Los Angeles-born children.

The researchers created the Virtual Los Angeles cohort-ViLA. This was a model calibrated to the Los Angeles County population. The model incorporated trends, causes, and effects of obesity, with a particular emphasis on diabetes as a significant obesity consequence over the duration of the participants represented in the simulation.

Each person depicted in the model engaged in both beneficial and not so beneficial behaviors that are known to be associated with obesity and diabetes. These behaviors included the intake of sugar-sweetened beverages, engagement or non-engagement in physical activity, fast-food consumption, and consumption of diets rich in fresh fruits and vegetables.

Additionally, the model used probability estimates to predict which modeled person might acquire or lose weight and develop type 2 diabetes, based on the person’s sociodemographic characteristics, historical activities, and previous weight or type 2 diabetes status. The researchers utilized the model to create a simulation of 98,230 residents ranging in age from birth to 65 years and residing in 235 Los Angeles County areas.

The simulation results indicated that obesity prevalence frequently increased from 10% to 30% across the life-course of the modeled individuals. And the prevalence of type 2 diabetes  typically increased from less than 2% in the 18-to-24 age group to 25% in the 40-to-49 age group.

As demonstrated, simulation can be beneficial for examining public health concerns. And obesity is a significant public health problem. Another significant public health problem is type 2 diabetes. The modeling experiments cited above indicate the magnitude of the health issues created by the combination of obesity and type 2 diabetes. Additionally, the research underscores the need for the healthcare sector to step up efforts to address obesity and diabetes.


Tags: environmental scanning, balanced scorecard, business planning, strategic management, bariatric medicine,obesity medicine,medical practice start up,bariatric industry analysis, weight loss industry analysis, weight management industry analysis, diabetes prevention, prediabetes

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