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Assessment – Macronutrient Needs and Oral Intake
Published in Jennifer Doley, Mary J. Marian, Adult Malnutrition, 2023
A variety of factors affect metabolic rate, including disease state, body composition, age, and sex. Accurately assessing metabolic rate enables the clinician to determine energy, protein, and fluid needs in all stages of disease. There are multiple methods to estimate needs, including indirect measurement and predictive equations, as discussed below. Research is ongoing to determine the most precise methods for different disease states and care settings.1
Weight Concerns
Published in Carolyn Torkelson, Catherine Marienau, Beyond Menopause, 2023
Carolyn Torkelson, Catherine Marienau
However, there is more to the story. The saying “Let food be thy medicine and medicine be thy food” hearkens back to Hippocrates, the father of medicine. This quote, though thousands of years old, acknowledges the importance of healthy foods and how the nutrients in various foods help with satiety and energy levels and even provide healing properties. Even if we were to concede that “calories in versus calories out” is the key to weight loss, it is the macronutrient composition that carries vital metabolic benefits for overall health and can’t be ignored. Also, remember that the problem is not solved with a singular focus on what and how much to eat but rather why, where, and with whom you eat.
Metabolic Syndrome
Published in Jahangir Moini, Matthew Adams, Anthony LoGalbo, Complications of Diabetes Mellitus, 2022
Jahangir Moini, Matthew Adams, Anthony LoGalbo
Metabolic syndrome is actually a group of risk factors that increases risks for diabetes mellitus, heart disease, stroke, and other health problems. There must be at least three of the following metabolic risk factors in order for metabolic syndrome to be diagnosed: A larger than normal waist circumference, high triglyceride level, low HDL cholesterol level, hypertension, and high fasting blood sugar. The risk of having metabolic syndrome is closely linked to obesity and lack of physical activity, as well as insulin resistance. Metabolic syndrome is becoming more common because of increased obesity rates. Conditions that play a role in the development of metabolic syndrome include fatty liver disease, polycystic ovarian syndrome, and respiratory conditions such as obstructive sleep apnea. Metabolic syndrome is treated with a combination of lifestyle improvements and medications.
Relationship between rotating shift work and white blood cell count, white blood cell differential count, obesity, and metabolic syndrome of nurses
Published in Chronobiology International, 2022
In our study, age and the WBC count are the main risk factors influencing an overly large waist circumference and overly high BMI. These findings are consistent with those in existing literature, which reports that metabolism slows down as age increases. Increases in waist circumference and body weight are also attributed to insufficient exercise due to an accumulation of body fat (Cho et al. 2018; Stevens et al. 2010). The chronic low-grade inflammation caused by excess WBCs is indeed associated with body fat content; however, the mechanisms of this association are still under debate (Kim and Park 2008). In a study by Yu et al. (2019) health checkup results from 600 adults were collected and abdominal computed tomography was used to examine intra-abdominal visceral adipose tissue content, and a significant correlation was identified between WBC count and visceral obesity. Visceral adipose tissue is located in the abdomen and thus influences waist circumference.
Hypothesis of using albumin to improve drug efficacy in cancers accompanied by hypoalbuminemia
Published in Xenobiotica, 2021
Soghra Bagheri, Ali A. Saboury
Drug resistance is the main cause of more than 90% of cancer patients' deaths, which its mechanism includes increasing drug metabolism, altering drug transport (increasing drug efflux/decreasing drug influx), enhancing DNA repair capacity, growth factors, and genetic factors (Bukowski et al. 2020; Zahreddine and Borden 2013). Drug metabolism does not refer to the usual metabolic pathways that include anabolism and catabolism, but rather changes that facilitate the excretion of the drug from the body (Benet and Zia-Amirhosseini 1995). There are two main phases in drug metabolism. The first phase involves processes such as oxidation, reduction, and hydrolysis that alter the pharmacological activity of the drug, usually resulting in loss of activity, and the second phase increases its solubility in water by adding endogenous molecules to the drug (Caira and Ionescu 2005). Most drugs lose their medicinal properties in this way and produce highly soluble metabolites that are easily excreted (Li et al. 2019). The main organ that metabolizes drugs is the liver. However, other organs, such as the kidneys, lungs, intestine, and skin, also have metabolizing enzymes (Alfarouk et al. 2015). Understanding drug resistance mechanisms is critical to overcoming them in order to develop new effective treatment strategies.
Comorbidity patterns among people living with HIV: a hierarchical clustering approach through integrated electronic health records data in South Carolina
Published in AIDS Care, 2021
Xueying Yang, Jiajia Zhang, Shujie Chen, Sharon Weissman, Bankole Olatosi, Xiaoming Li
The hierarchical cluster analysis identified four comorbidity clusters from the 24 diagnosis groups. As shown in Figure 2, the four comorbidity clusters were: (1) “substance use and mental disorders” (6 diagnosis groups: alcohol use, tobacco use, anxiety, depression, psychiatric disorders, illicit drug use); (2) “metabolic disorders” (10 diagnosis groups: hypothyroidism, anemia, diabetes, dyslipidemia, cardiac disorders, hypertension, ulcer disease, chronic obstructive pulmonary disease [COPD], osteoporosis/osteoarthritis, chronic kidney disease); (3) “liver disease and cancer” (4 diagnosis groups: hepatitis B, chronic liver disease, hepatitis C, non-AIDS defining cancers); and (4) “cerebrovascular disease” (4 diagnosis groups: stroke, cerebral infarction, peripheral vascular disease, dementia). The concurrence (in %) of comorbidity clusters among all the PLWH were shown in Figure 3, with 11.50% of the patients being diagnosed only with substance use and mental disorders (cluster 1), 12.94% only with metabolic disorders (cluster 2), 0.52% only with liver diseases and cancer (cluster 3) and 0.09% only with cerebrovascular disease (cluster 4). In the meantime, the 2 most frequent concurrent dyads were: clusters 1 and 2 (22.56%) and clusters 2 and 3 (1.30%). The 2 most frequent concurrent triads were clusters 1, 2, and 3 (6.22%) and clusters 1, 2, and 4 (2.41%). The proportion of patients who were diagnosed with all four clusters was low (1.32%).