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Remember that this is only increased risk. The bottom line is that everyone should work to maintain or improve their health, rather than indulge in excessive worry. It also suggests that the focus of society should be on helping those with pre-existing conditions improve their health, and those in good health to maintain their health, rather than mass experimental vaccinations.

A new study (July 2021) appearing in a CDC journal entitled “Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021” found that the strongest risk factors for death were obesity, anxiety and fear-related disorders, and diabetes with complications, as well as the total number of conditions. However, a subset of the study suggests that anxiety leads to a higher likelihood of ICU (intensive care) admission and not IMV or death. It is possible that more anxious patients may be more insistent upon being put into ICU. Nonetheless, excessive fear and anxiety can weaken the immune system. Furthermore, another study suggested that uncontrolled diabetes without complications may increase risk, as well.

Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021. By Kompaniyets L, Pennington AF, Goodman AB, Rosenblum HG, Belay B, Ko JY, et al., Prev Chronic Disease, Volume 18, E66, July 2021. https://www.cdc.gov/pcd/issues/2021/pdf/21_0123.pdf

This study says almost word-for-word what US Congresswoman Marjorie Taylor Greene recently stated. It says: “High baseline prevalence of obesity and diabetes, combined with their association with severe COVID-19 illness, suggest that these 2 conditions could have an outsized impact on the population with COVID-19. Prevention and treatment of these conditions may be an important strategy that could improve national resilience against chronic threats and acute crises.”

Remember when reading the study that a positive correlation is negative in this context. In the context of this paper, a positive correlation means increased likelihood of bad Covid-19 outcomes and a negative correlation means decreased likelihood of bad outcomes. A negative correlation is also known as an inverse relationship, such as increasing pressure decreases volume, if temperature is constant. For a positive correlation if one increases, the other increases, and for a negative correlation if one increases, the other decreases and vice versa.

If you, or your loved ones, have pre-existing conditions, please read the full study (screen shots are at the post bottom) carefully, because there are age differences and differences in the overall population of the study, and the subset groups.

The study appears to suggest that excessively anxious fear of Covid-19 may worsen outcomes. This makes sense, since enough fear can weaken the immune system and the mainstream media, and some politicians, have worked overtime to increase fear, especially in their attempts to force experimental vaccines upon the public. This is anxious helpless fear and should not be confused with taking appropriate precautions, which some call fear: “In a subset of patients with pre-COVID encounters in our study, anxiety diagnosed before COVID-19 was not independently associated with death or IMV during COVID-19 hospitalization and, therefore, it is also plausible that anxiety was diagnosed during COVID-19 illness and may be a resulting sequela of COVID-19 (21). Future studies could explore the temporal and causal associations between anxiety disorders and severe COVID-19 illness”. Later the paper states that “Anxiety and fear-related disorders were associated with a 2% (95% CI, 0.4%–4%) higher risk of ICU admission but not with a higher risk of death or IMV, on the basis of the full model.

The overall study results were: “Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27–1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25–1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24–1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41–1.67) for patients with 1 condition to 3.82 (95% CI, 3.45–4.23) for patients with more than 10 conditions (compared with patients with no conditions).

Relative risk of death in the full model was 30% higher with obesity (95% CI, 27%–33%), 28% higher with anxiety and fear-related disorders (95% CI, 25%–31%), 26% higher with diabetes with complication (95% CI, 24%–28%), 21% higher with CKD (95% CI, 19%–24%), 18% higher with neurocognitive disorders including dementia and Alzheimer’s disease (95% CI, 15%–21%), 18% higher with chronic obstructive pulmonary disease and bronchiectasis (95% CI, 16%–20%), 17% higher with aplastic anemia including anemia in CKD (95% CI, 14%–19%), 14% higher with coronary atherosclerosis and other heart disease (95% CI, 12%–16%), and 4% higher with thyroid disorders including hypothyroidism (95% CI, 2%–6%) (Table 2). These conditions were also associated with a higher risk of IMV and ICU admission.”

There are differences according to age:
The most frequent conditions were obesity, diabetes, and essential hypertension among patients younger than 65, and disorders of lipid metabolism, essential hypertension, diabetes, and coronary atherosclerosis among patients aged 65 or older.

Among patients aged 18 to 39, essential hypertension was associated with a 26% higher risk of death (95% CI, 10%–44%), 25% higher risk of IMV (95% CI, 17%–35%), and an 11% higher risk of ICU admission (95% CI, 7%–15%). In the same age group, asthma was frequent and was associated with a 9% (95% CI, 5%–13%) higher risk of ICU admission but was not significantly associated with higher risk of IMV or death.

Other specified status (CCSR category indicating a need for specific medical support, such as a wheelchair or renal dialysis) was a frequent category among patients aged 40 to 64 and 65 or older and was associated with a 7% (1%–13%) and 4% (1%–6%) higher risk of death, respectively.

We found a dose–response association between the total number of underlying medical conditions and risk of severe COVID-19 illness (Figure 2). Compared with patients with no documented underlying medical conditions, patients’ risk of death was 1.53 times (95% CI, 1.41–1.67) as high if they had 1 condition, 2.55 times (95% CI, 2.32–2.80) as high if they had 2 to 5 conditions, 3.29 times (95% CI, 2.98–3.63) as high if they had 6 to 10 conditions, and 3.82 times (95% CI, 3.45–4.23) as high if they had more than 10 conditions.

Later in the paper they write: “In the first sensitivity analysis, performed by using all CCSR categories, we identified 6 additional frequent “indeterminate” CCSR categories: cardiac dysrhythmias (n = 124,367 [23.0%]), heart failure (n = 104,858 [19.4%]), other specified nervous system disorders (n = 89,929 [16.6%]; top ICD-10-CM code, metabolic encephalopathy), other specified and unspecified nutritional and metabolic disorders (n = 89,337 [16.5%]; top code, hypomagnesemia), coagulation and hemorrhagic disorders (n = 75,766 [14.0%]), and diseases of white blood cells (n = 57,765 [10.7%]). The risk ratio estimates of most previously found underlying conditions were lower with the inclusion of these 6 conditions in the full models.

In the second sensitivity analysis, which used a subset of 278,215 patients with at least 1 encounter in the PHD-SR before their first COVID-19 hospitalization, diabetes without complication was associated with an 8% (95% CI, 5%–12%) higher risk of death, a 13% (95% CI, 10%–17%) higher risk of IMV, and a 5% (95% CI, 4%–7%) higher risk of ICU admission; sleep–wake disorders were associated with an 8% (95% CI, 5%–11%) higher risk of IMV. Anxiety and fear-related disorders were associated with a 2% (95% CI, 0.4%–4%) higher risk of ICU admission but not with a higher risk of death or IMV, on the basis of the full model.

They also state that: “A sensitivity analysis revealed 6 “indeterminate” conditions (such as coagulation and hemorrhagic disorders, cardiac dysrhythmias, and heart failure) that were both frequent and associated with at least 1 severe COVID-19 illness outcome. Without better information on the temporality of these 6 conditions relative to the COVID-19 illness, we were unable to determine whether these were truly underlying conditions (27,28). Our second sensitivity analysis, restricted to 278,215 patients with encounters that preceded the first COVID-19 encounter, found a positive association of sleep–wake disorders and uncomplicated diabetes with severe COVID-19 illness.

Essential hypertension, for which evidence is mixed on its association with severe COVID-19 illness (1), was shown in our analysis to be the most prevalent condition. It was found to be associated with a higher risk of severe COVID-19 illness only among patients aged 18 to 39 but with a lower risk of severe COVID-19 illness among older patients and in the full sample. This finding supports a possible link with severe COVID-19 illness and identifies essential hypertension as a risk factor, especially among younger patients.

Uncomplicated diabetes was found to be negatively associated with the risk of death and IMV. A positive association with risk of ICU admission was found only among patients aged 18 to 39. A previous study showed that although type 2 diabetes was a risk factor for mortality from severe COVID-19 illness, patients with diabetes and well-controlled blood glucose had lower mortality than those with diabetes and poorly controlled blood glucose (13). Our sensitivity analysis of a subset of patients with pre-COVID encounters identified a higher relative risk of death associated with uncomplicated diabetes present before the first COVID hospitalization. Coding bias (uncomplicated diabetes may be less frequently coded in hospitalizations with severe outcomes) (17) or reverse causality (diabetes complications arising from COVID-19 illness or treatment) (18) could explain this finding.

It’s unclear if the paragraph, below, means in comparison to diabetes without complications or to non-diabetic, etc. This was earlier in the paper and the diabetes without complication statement seems to be modified by later sensitivity analyses found in the paragraphs, which we cut and pasted above:
Diabetes without complication was associated with a 6% lower risk of death (aRR = 0.94; 95% CI, 0.91–0.97), 9% lower risk of IMV (aRR = 0.91; 95% CI, 0.88–0.94), and 2% lower risk of ICU admission (aRR = 0.98; 95% CI, 0.97–0.998). Essential Hypertension was associated with an 8% lower risk of death (aRR = 0.92; 95% CI, 0.90–0.93), 6% lower risk of IMV (aRR = 0.94; 95% CI, 0.92–0.95), and a 1% lower risk of ICU admission (aRR = 0.99; 95% CI, 0.97–0.999). Asthma was associated with a 9% lower risk of death (aRR = 0.91; 95% CI, 0.89–0.94) and a 4% lower risk of IMV (aRR = 0.96; 95% CI, 0.94–0.99)

It says that they excluded “indeterminate” and “likely acute” categories. So, it seems that the pre-existing conditions, then could be even higher than 95%. It seems that undiagnosed and/or untreated high blood pressure (hypertension), along with undiagnosed diabetes or other undiagnosed conditions could also increase the percentage with pre-existing conditions. Indeed, at the end of the paper they state that “relying on ICD-10-CM codes to identify underlying medical conditions may have underestimated their prevalence. For example, obesity was diagnosed in 33.0% of the patients, which is possibly an underestimate of this condition, given the national prevalence of 42.4% in 2017–2018 and the prevalence of 50.8% among patients with available height and weight data in PHD-SR. Fifth, prior literature shows evidence of both increased documentation and underdiagnosis of certain chronic conditions among patients with more severe illness.”

Toward the beginning of the paper they explain:
To further differentiate underlying conditions from acute complications of COVID-19, a panel of physicians (K.K.W., W.M.K., H.G.R., B.B., N.T.A., J.M.N.) classified the 314 CCSR categories into “likely underlying” (274 categories; eg, asthma); “indeterminate,” which could include underlying or acute complications or both (29 categories; eg, cardiac dysrhythmias); or “likely acute” (11 categories; eg, acute pulmonary embolism). We used the “likely underlying” CCSR categories for our analysis of underlying medical conditions and excluded the “indeterminate” or “likely acute” CCSR categories.
People diagnosed with both CCSR categories of “diabetes with complication” and “diabetes without complication” (n = 55,141) were classified as having diabetes with complication. The number of underlying medical conditions was defined as the number of unique CCSR categories associated with each patient (0, 1, 2–5, 6–10, >10)…. We described the sample by patient and hospital characteristics. Then we selected the most frequent underlying CCSR categories with a prevalence of 10% or more in the sample. We used multivariable generalized linear models with Poisson distribution and log link function to estimate adjusted risk ratios (aRRs) for 3 outcomes of interest among hospitalized patients: ICU admission, IMV, and death (reference was surviving hospitalized patients without that outcome). We performed these estimations by 1) including all frequent CCSR categories in the same model (“full model”) and 2) including 1 CCSR category per statistical model (“restricted model”). We focused our interpretations on the CCSR categories whose direction of association (positive or negative)… was consistent between the restricted and the full model. We also conducted a stratified analysis of frequent conditions by age group (frequency ≥10.0% in each age group). Finally, we estimated the association between the number of CCSR categories and the 3 severity outcomes…

At the end they state that: “Our study found that 9 of 18 frequent underlying medical conditions among adults hospitalized with COVID-19 were associated with severe illness. Combined with the high prevalence of these conditions (affecting 81.9% of hospitalized patients with COVID-19 in PHD-SR), this finding suggests a potentially high impact at the population level. The highest risk of severe COVID-19 illness was associated with obesity, anxiety and fear-related disorders, diabetes with complication, CKD, and neurocognitive disorders. Among patients younger than 40, essential hypertension was also a risk factor for death. The total number of underlying medical conditions was a strong risk factor of severe COVID-19 illness. Preventing COVID-19 in populations with these conditions and multiple conditions should remain a public health priority, along with targeted mitigation efforts and ensuring high uptake of vaccine, when available, in these people and their close contacts”.
See: “Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021. Kompaniyets L, Pennington AF, Goodman AB, Rosenblum HG, Belay B, Ko JY, et al., Prev Chronic Disease, Volume 18, E66, July 2021. https://www.cdc.gov/pcd/issues/2021/pdf/21_0123.pdf
[See link or screen shots, with highlight, below]

Related:
Hyperlipidemia, mentioned in the article, includes what is commonly called high cholesterol. However, it’s high levels of bad cholesterol (LDL) and low levels of good cholesterol (HDL). While for some people it’s genetic, for others it’s related to diet and lack of exercise. Exercise can increase good cholesterol (HDL). Some research has indicated that one serving of alcohol per day improves HDL levels, whereas more than one has the opposite effect. Weight and gender should be considered. It is advised that you not start to drink alcohol, however, if you haven’t. See: https://www.mayoclinic.org/diseases-conditions/high-blood-cholesterol/in-depth/hdl-cholesterol/art-20046388

Hyperlipidemia is a condition that incorporates various genetic and acquired disorders that describe elevated lipid levels within the human body. Hyperlipidemia is extremely common, especially in the Western hemisphere, but also throughout the world. Alternatively, a more objective definition describes hyperlipidemia as low-density lipoprotein (LDL), total cholesterol, triglyceride levels, or lipoprotein levels greater than the 90th percentile in comparison to the general population, or an HDL level less than the 10th percentile when compared to the general population. Lipids typically include cholesterol levels, lipoproteins, chylomicrons, VLDL, LDL, apolipoproteins, and HDL.” Excerpt from: Hill MF, Bordoni B. Hyperlipidemia. 2021 Feb 7. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan–. PMID: 32644608. https://pubmed.ncbi.nlm.nih.gov/32644608/

Metabolic Syndrome What Is – Metabolic Syndrome

Metabolic syndrome is the name for a group of risk factors that raises your risk for heart disease and other health problems, such as diabetes and stroke.

The term “metabolic” refers to the biochemical processes involved in the body’s normal functioning. Risk factors are traits, conditions, or habits that increase your chance of developing a disease.

In this article, “heart disease” refers to ischemic heart disease, a condition in which a waxy substance called plaque builds up inside the arteries that supply blood to the heart.

Plaque hardens and narrows the arteries, reducing blood flow to your heart muscle. This can lead to chest pain, a heart attack, heart damage, or even death.

Metabolic Risk Factors

The five conditions described below are metabolic risk factors. You can have any one of these risk factors by itself, but they tend to occur together. You must have at least three metabolic risk factors to be diagnosed with metabolic syndrome.
* A large waistline. This also is called abdominal obesity or “having an apple shape.” Excess fat in the stomach area is a greater risk factor for heart disease than excess fat in other parts of the body, such as on the hips.
* A high triglyceride level (or you’re on medicine to treat high triglycerides). Triglycerides are a type of fat found in the blood.
* A low HDL cholesterol level (or you’re on medicine to treat low HDL cholesterol). HDL sometimes is called “good” cholesterol. This is because it helps remove cholesterol from your arteries. A low HDL cholesterol level raises your risk for heart disease.
* High blood pressure (or you’re on medicine to treat high blood pressure). Blood pressure is the force of blood pushing against the walls of your arteries as your heart pumps blood. If this pressure rises and stays high over time, it can damage your heart and lead to plaque buildup.
* High fasting blood sugar (or you’re on medicine to treat high blood sugar). Mildly high blood sugar may be an early sign of diabetes.
*
* Overview
Your risk for heart disease, diabetes, and stroke increases with the number of metabolic risk factors you have. The risk of having metabolic syndrome is closely linked to overweight and obesity and a lack of physical activity.

Insulin resistance also may increase your risk for metabolic syndrome. Insulin resistance is a condition in which the body can’t use its insulin properly. Insulin is a hormone that helps move blood sugar into cells where it’s used for energy. Insulin resistance can lead to high blood sugar levels, and it’s closely linked to overweight and obesity. Genetics (ethnicity and family history) and older age are other factors that may play a role in causing metabolic syndrome.

Outlook

Metabolic syndrome is becoming more common due to a rise in obesity rates among adults. In the future, metabolic syndrome may overtake smoking as the leading risk factor for heart disease.

It is possible to prevent or delay metabolic syndrome, mainly with lifestyle changes. A healthy lifestyle is a lifelong commitment. Successfully controlling metabolic syndrome requires long-term effort and teamwork with your health care providers.https://www.nhlbi.nih.gov/health-topics/metabolic-syndrome

Lipid Storage Diseases Fact Sheet”: https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/Fact-Sheets/Lipid-Storage-Fact-Sheet

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See: “Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021. Kompaniyets L, Pennington AF, Goodman AB, Rosenblum HG, Belay B, Ko JY, et al., Prev Chronic Disease, Volume 18, E66, July 2021. https://www.cdc.gov/pcd/issues/2021/pdf/21_0123.pdf