Journal of Nutritional Disorders & Therapy

Calculation of Obesity in Older Adults

Caroline Jack^* Department of Nutritional Sciences, University of Surrey, Guildford, United Kingdom
^*Correspondence: Caroline Jack, Department of Nutritional Sciences, University of Surrey, Guildford, United Kingdom, Email:

Received: 04-Jul-2022, Manuscript No. JNDT-22-17653; Editor assigned: 07-Jul-2022, Pre QC No. JNDT-22-17653 (PQ); Reviewed: 21-Jul-2022, QC No. JNDT-22-17653; Revised: 28-Jul-2022, Manuscript No. JNDT-22-17653 (R); Published: 04-Aug-2022, DOI: 10.35248/2161-0509.22.12.193

Description

Over the past century, the United States life expectancy has improved significantly. The average life expectancy was 47 years in 1900 as opposed to 78.8 years today. The number of adults 65 and older is predicted to rise from 43.1 million in 2012 to 83.7 million in 2050 as a result of this phenomenon, which also contributes to population growth. The number and makeup of this population will primarily depend on the factors that influence mortality such as obesity. The global pandemic of obesity is becoming more and more common. The prevalence of obesity among adults in the United States over the age of 60 grew by 4.4% between 2004 and 2012, rising from 31% to 35.4%. Due to the recognized link between obesity, disability and an increase in absolute mortality risk up to age 75, this rising frequency in older persons is especially worrisome. Osteoarthritis, cancer and cognitive dysfunction are all linked to obesity in addition to hypertension, hyperlipidemia, diabetes and sleep apnea.

Obesity also raises mortality, morbidity and disability rates, which raises the expense of medication. Up to 2.8% of healthcare costs are attributable to obesity and as the prevalence of obesity rises, this percentage is expected to rise. Older men and women who were overweight or obese at the age of 65 spent 6% to 13% and 11% to 17% more overall on healthcare. Up to age 70 years fat mass increases and fat-free mass decreases (mainly in skeletal muscle) are linked to ageing. Physical signs of ageing not only encourage sarcopenia, the loss of skeletal muscular mass and reduced muscle function, but also a continuous increase in body fat. The dangers linked to obesity vary by age group. For instance, older persons with higher BMIs had fewer odds of having hypertension than younger adults do and between the ages of 30 years and 74 years, being overweight or obese increases the risk of dying from any cause and developing cardiovascular disease.

BMI measurement for older people

The standard method of measuring adiposity is called Body Mass Index (BMI), which is calculated by dividing weight (in kg) by height (in m²). This evaluation is simple and quick to complete. BMI however, is a poor indicator of obesity in older persons in a number of ways. First, BMI measures exaggerate fatness due to age-typical height decrease brought on by vertebral body compression and spine angulation. Second, visceral fat has been linked to metabolic syndrome type 2 diabetes decreased glucose tolerance, aortic stiffness and myocardial infarction in women. BMI does not take this into consideration. As a result, the use of BMI in populations of older adults has been heavily challenged because it does not take into account changes in adipose tissue caused by ageing notably the ratio of fat mass to fat-free mass. BMI understates fatness because fat mass replaces fat-free mass as people age. Normal weight obesity is described as having a normal BMI (18.5 kg/m² to 25 kg/m²) but a high body fat percentage and is frequently brought on by this change. Obesity of normal weight puts older persons at higher risk for endothelial dysfunction, metabolic syndrome, cardiovascular risk factors, mortality and disability. Measures of adipose distribution rather than overall fatness should be used to determine risk because overall obesity is only marginally predictive of metabolic syndrome type 2 diabetes and impaired glucose tolerance but not predictive of aortic stiffness and myocardial infarction.

There are numerous methods for determining fatness ranging from simple to expensive. Waist circumference was the best predictor of mobility difficulty in men and women in an observation that compared weight, BMI, hip circumference and waist-hip ratio. Men's impairment results are similarly accurately predicted by waist-hip ratio. These anthropometric measurements can be used realistically to provide further risk stratification among overweight and obese people because they are affordable and simple to execute.