Using Dietary Macronutrient Patterns to Predict Sarcopenic Obesity in Older Adults: A Representative Korean Nationwide Population-Based Study

Abstract

Older adults with sarcopenic obesity (SO) are at increased risk of adverse health outcomes. It has not been identified which pattern of macronutrient intake is appropriate in relation to SO. We aimed to compare the patterns of macronutrient intake for predicting SO in older adults. Data from a total of 3828 older adults who participated in the 2008–2011 Korea National Health and Nutrition Examination Survey were analyzed. The one-day 24 h dietary recall method was used to assess macronutrient intake. SO was defined by a combination of body mass index (BMI) ≥ 25 kg/m2 and BMI adjusted-appendicular skeletal muscle mass <0.789 for men and <0.512 for women. Weighted logistic regression analysis revealed the odds ratio (95% confidence interval) for SO of total calorie intake per 100 increments and carbohydrate (CHO) intake (g/kg/day) per 1 increment to be 0.95 (0.91–0.99) and 0.83 (0.74–0.94), respectively, after adjusting for confounding variables in women. The predictive power for SO of CHO intake (g/kg/day) was higher compared with the other patterns of macronutrient intake both in men and women. In conclusion, total calorie intake and CHO intake (g/kg/day) are inversely related to SO in women. CHO intake (g/kg/day) could be the best index for determining SO.

Predictive Roles of Basal Metabolic Rate and Body Water Distribution in Sarcopenia and Sarcopenic Obesity: The link to Carbohydrates

“…Sarcopenic obesity is also related to cognitive impairment [ 29 ], low bone mineral density [ 26 ], frailty [ 7 ], and metabolic diseases [ 34 ]. A study found that carbohydrate intake could be the best indicator for determining sarcopenic obesity in older adults [ 35 ], and body composition plays an important role in sarcopenia. In this case, we explored the associations of nutrition and body composition with sarcopenia or sarcopenic obesity, evaluated the ability of BMR and body water distribution to identify sarcopenia or sarcopenic obesity, and found a significant mediating effect of BMR in the relationship between carbohydrates and SMI, as well as the moderating role of body water distribution in the indirect relationship between carbohydrates and SMI through BMR.…”

“…A study in older Korean adults showed an inverse relationship between carbohydrate intake and sarcopenic obesity [ 35 ]. Our study also found that the obese population took in more carbohydrates, but people with sarcopenic obesity had lower carbohydrate intake.…”

Sex-Specific Effects of Dietary Factors on Sarcopenic Obesity in Korean Elderly: A Nationwide Cross-Sectional Study

“…Overall, diet quality has been associated with a reduction in the risk of sarcopenic obesity in the elderly [ 14 , 15 , 16 ]. Additionally, there is an association between sarcopenic obesity and appropriateness of energy intake [ 17 , 18 ], energy ratio of macronutrients [ 18 , 19 ], and protein intake [ 20 , 21 , 22 , 23 ].…”

“…Thus, age-related sarcopenic obesity is an emerging concern in South Korea. Although there is an association between sarcopenic obesity and dietary factors in Korean older adults, the majority of these studies were based on analyses of the 2008–2011 KNHANES [ 18 , 19 , 23 , 24 , 25 ]. Moreover, subsequent research on sarcopenic obesity in the elderly and its association with dietary factors, based on an analysis of the 2016–2018 KNHANES, has been limited to studies investigating regional differences in the association between dietary quality and sarcopenic obesity [ 14 ] and examining the nutritional intake of elderly men and women with sarcopenic obesity [ 20 ].…”

Publication trends in nutrition research for sarcopenic obesity: A 20-year bibliometric analysis

“…Specifically, timely diagnosis, assessment of nutritional status, and reasonable intake of nutrients are essential for the prevention and treatment of sarcopenic obesity. [20,21] Bibliometrics is a method used in library science to systematically evaluate documents; as such, it has been applied to measure the influence of academic journals and identify hotspots and frontiers in specific fields. [22] It comprehensively summarizes and points out future research orientations in a field according to the contribution of individuals, countries, and institutions, and identifies the influence of publications and the frequency of keywords, among other indicators.…”