Dataset Information

Predicted lean body mass in relation to cognitive function in the older adults.

ABSTRACT:

Background

Previous findings about lean body mass (LBM) and cognitive function remain unclear. We aimed to examine this association by using data from the National Health and Nutrition Examination Survey (NHANES).

Methods

Using data from the NHANES 2011-2014, we conducted logistic regression models to investigate the relation between the predicted LBM and domain-specific cognitive function assessed by Digit Symbol Substitution Test (DSST), Consortium to Establish a Registry for Alzheimer's Disease Word Learning test (CERAD-WL) and Delayed Recall test (CERAD-DR), and Animal Fluency (AF) for information processing speed, memory, and executive function, respectively. Cognitive impairment was defined as the lowest quartile of each cognitive test in the total population. Sex-stratified analysis was further made.

Results

A total of 2955 participants aged 60 and above (mean [SD] age, 69.17[0.20] years; 1511 female [51.13%]) were included in the study. After being adjusted for social economic factors, anthropometric parameters, and diseases, we found a positive association between predicted LBM and information processing speed (Odds ratio of DSST impairment= 0.95, 95%CI= 0.91 to 0.99) regardless of body mass index and sex. Compared with patients in the first quartile of predicted LBM, those in the fourth quartile had an odds ratio of 0.355 (95% confidence interval 0.153-0.822) for DSST impairment. No significant relation in other cognitive tests and predicted LBM was found whether stratified by sex or not.

Conclusion

Our findings point to the association between predicted lean body mass and cognitive dysfunction in information processing speed, which could be used for early detection and prevention of deterioration of cognitive function among older adults.

SUBMITTER: Gong HJ

PROVIDER: S-EPMC10358760 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Predicted lean body mass in relation to cognitive function in the older adults.

Gong Hong-Jian HJ Tang Xingyao X Chai Yin-He YH Qiao Yu-Shun YS Xu Hui H Patel Ikramulhaq I Zhang Jin-Yan JY Zhou Jian-Bo JB

Frontiers in endocrinology 20230706

<h4>Background</h4>Previous findings about lean body mass (LBM) and cognitive function remain unclear. We aimed to examine this association by using data from the National Health and Nutrition Examination Survey (NHANES).<h4>Methods</h4>Using data from the NHANES 2011-2014, we conducted logistic regression models to investigate the relation between the predicted LBM and domain-specific cognitive function assessed by Digit Symbol Substitution Test (DSST), Consortium to Establish a Registry for Al ...[more]

PMID: 37484948

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Project description:BackgroundLittle is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.MethodsThis nationwide, population-based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20-39 years without a previous history of CVD who underwent two health screening examinations during 2009-2010 and 2011-2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.ResultsThe mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person-years of follow-up. Each 1 kg/m2 increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82-0.91; aHR: 0.76, 95% CI 0.69-0.82, respectively] and women (aHR: 0.77, 95% CI 0.63-0.95; aHR: 0.75, 95% CI 0.59-0.96). Each 1 kg/m2 increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10-1.22) and women (aHR: 1.32, 95% CI 1.06-1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between -1 and +1 kg/m2 also had a decreased risk of CVD per 1 kg/m2 increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80-0.92; aHR: 0.85, 95% CI 0.76-0.95) and women (aHR: 0.62, 95% CI 0.47-0.83; aHR: 0.59, 95% CI 0.44-0.80) and had a greater risk of CVD per 1 kg/m2 increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10-1.25) and women (aHR: 1.64, 95% CI 1.20-2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.ConclusionsAmong young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.

Project description:BackgroundStudies on the prospective association of body composition with mortality in US general populations are limited. We aimed to examine this association by utilizing data from the National Health and Nutrition Examination Survey (NHANES), a representative sample of US adults, linked with data from the National Death Index.MethodsWe analysed data of NHANES 1988-1994 and 1999-2014, with 55 818 participants [50.6% female, baseline mean age: 45.0 years (SE, 0.2)]. Predicted fat mass and lean mass were calculated using the validated sex-specific anthropometric prediction equations developed by the NHANES based on individual age, race, height, weight, and waist circumference. Body composition and other covariates were measured at only one time point. Multivariable Cox regression was used to investigate the associations of predicted fat mass and lean mass with overall and cause-specific mortality, adjusting for potential confounders. Interactions between age and body composition on mortality were examined with likelihood ratio testing.ResultsMean predicted fat mass was 24.1 kg [95% confidence interval (CI): 23.9-24.3) for male participants and 29.9 kg (95% CI: 29.6-30.1) for female participants, while mean predicted lean mass was 59.3 kg (95% CI: 59.1-59.5) for male participants and 41.7 kg (95% CI: 41.5-41.8) for female participants. During a median period of 9.7 years from the survey, 10 408 deaths occurred. When predicted fat and lean mass were both included in the model, predicted fat mass showed a U-shaped association with all-cause mortality, with significantly higher risk at two ends: Quintile 1 (HR, 1.17; 95% CI: 1.05-1.31), Quintile 2 (HR, 1.14; 95% CI: 1.04-1.26) and Quintile 5 (HR, 1.37; 95% CI: 1.12-1.68) compared with Quintile 3. In contrast, predicted lean mass showed a L-shaped association with all-cause mortality, with higher mortality in those with lower lean mass: Quintile 1 (HR, 1.64; 95% CI: 1.46-1.83) and Quintile 2 (HR, 1.29; 95% CI: 1.18-1.42) compared with Quintile 3. Similar results were found for cardiovascular, cancer, and respiratory cause-specific mortality. Age was a significant modifier: There was a monotonic positive association of predicted fat mass with mortality in younger participants (<60 years), but an approximate J-shaped association in older participants (≥60 years) (P interaction <0.001); there was a stronger inverse association between predicted lean mass and mortality in older participants (≥60) compared with those <60 years (P interaction <0.001).ConclusionsIn this US general population, predicted fat mass and lean mass were independent predictors for overall and cause-specific mortality. Age was a significant modifier on the associations.

Project description:BackgroundAn inadequate protein intake may offset the muscle protein synthetic response after physical activity, reducing the possible benefits of an active lifestyle for muscle mass. We examined the effects of 12 weeks of daily protein supplementation on lean body mass, muscle strength, and physical performance in physically active older adults with a low habitual protein intake (<1.0 g/kg/day).MethodsA randomized double-blinded controlled trial was performed among 116 physically active older adults [age 69 (interquartile range: 67-73) years, 82% male] who were training for a 4 day walking event of 30, 40, or 50 km/day. Participants were randomly allocated to either 31 g of milk protein or iso-caloric placebo supplementation for 12 weeks. Body composition (dual-energy X-ray absorptiometry), strength (isometric leg extension and grip strength), quadriceps contractile function, and physical performance [Short Physical Performance Battery, Timed Up-and-Go test, and cardiorespiratory fitness (Åstrand-Rhyming submaximal exercise test)] were measured at baseline and after 12 weeks. We assessed vitamin D status and markers of muscle damage and renal function in blood and urine samples before and after intervention.ResultsA larger increase in relative lean body mass was observed in the protein vs. placebo group (∆0.93 ± 1.22% vs. ∆0.44 ± 1.40%, PInteraction = 0.046). Absolute and relative fat mass decreased more in the protein group than in the placebo group (∆-0.90 ± 1.22 kg vs. ∆-0.31 ± 1.28 kg, PInteraction = 0.013 and ∆-0.92 ± 1.19% vs. ∆-0.39 ± 1.36%, PInteraction = 0.029, respectively). Strength and contractile function did not change in both groups. Gait speed, chair-rise ability, Timed Up-and-Go, and cardiorespiratory fitness improved in both groups (P < 0.001), but no between-group differences were observed. Serum urea increased in the protein group, whereas no changes were observed in the placebo group (PInteraction < 0.001). No between-group differences were observed for vitamin D status, muscle damage, and renal function markers.ConclusionsIn physically active older adults with relatively low habitual dietary protein consumption, an improvement in physical performance, an increase in lean body mass, and a decrease in fat mass were observed after walking exercise training. A larger increase in relative lean body mass and larger reduction in fat mass were observed in participants receiving 12 weeks of daily protein supplementation compared with controls, whereas this was not accompanied by differences in improvements between groups in muscle strength and physical performance.

Project description:BackgroundThe association between body mass index (BMI) and the risk of cognitive impairment remains uncertain. Relatively few studies have analyzed the dose-response relationship between BMI and cognitive impairment. This article utilized nationally representative longitudinal data to assess the association between BMI and cognitive impairment in Chinese older adults.ObjectiveThe present study aimed to analyze the association between BMI and cognitive impairment in Chinese older people, including an investigation of gender differences and the dose-response relationship.MethodsData were obtained from the China Health and Retirement Longitudinal Study database in 2015 and 2018. The present study used logistic regression to analyze the relationship between baseline BMI and cognitive impairment, and adopted a restricted cubic spline model to plot dose-response curves for baseline BMI and prevalence of risk of cognitive impairment.ResultsThe mean BMI of the survey population was 23.48 ± 3.66 kg/m2, and the detection rate of cognitive impairment was 34.2%. Compared to the normal weight group (18.5 ≤ BMI < 23.9 kg/m2), the odds ratio (OR) for cognitive impairment was 1.473 (95% CI: 1.189-1.823) in the underweight group (BMI < 18.5 kg/m2), whereas the corresponding OR was 0.874 (95% CI: 0.776-0.985) for the overweight or obese group (BMI ≥ 24.0 kg/m2) after adjusting for confounders. Gender subgroup analysis showed that overweight or obese older women were less likely to develop cognitive impairment (OR = 0.843; 95% CI: 0.720-0.987). The results of the restricted cubic spline analysis revealed a curvilinear L-shaped relationship between BMI and the risk of cognitive impairment (P non-linearity <0.05). In particular, the risk of cognitive impairment was higher at a lower baseline BMI. In contrast, BMI in the range of 23.2-27.8 kg/m2 was associated with a decreased risk of cognitive impairment.ConclusionBMI is a dose-dependent related factor for cognitive impairment in Chinese older adults. Being underweight is a risk factor for the development of cognitive impairment, while being overweight or obese is less likely to have cognitive impairment, particularly in female older people. Keeping BMI ranging from 23.2-27.8 kg/m2 in older adults can help maintain cognitive function.

Project description:IntroductionFew studies have deciphered whether lean body mass (LBM) or fat mass (FM) is predominantly responsible for the body mass index (BMI)-hypertension association. This study aimed to assess the associations of predicted LBM and FM with hypertension risk among Chinese male adults.MethodsA prospective cohort study was conducted among 2,812 male participants free of hypertension in the Fangchenggang Area Males Health and Examination Survey in 2009. We performed multivariable Cox models and restricted cubic spline to examine the associations of predicted LBM and FM and BMI with hypertension, and to further explore the mediating roles of lipid and glycemic traits in the relationship between predicted FM and blood pressure.ResultsOf 1,238 participants included in the cohort study, 306 (24.8%) hypertension cases were identified during a median follow-up of 3.8 years, with an incidence rate of 7.0 per 100 person-years. A positive linear-shaped association was consistently observed between BMI and hypertension (p for trend <0.001). Multivariable-adjusted Cox models including predicted LBM and FM observed a positive association between predicted FM and hypertension. Compared with those in the lowest quartile of predicted FM, men in the highest quartile had a hazard ratio (HR) of 1.83 (95% confidence interval (CI): 1.13-2.97) for hypertension. The HR per standard deviation increase of BMI and predicted FM was 1.11 (95% CI: 1.04-1.19) above 23.1 kg/m2 and 1.05 (95% CI: 1.02-1.15) above 14.6 kg, respectively. However, predicted LBM was not associated with hypertension. In addition, high-density lipoprotein cholesterol (HDL-c) and fasting blood glucose (FBG) mediated the relationship of predicted FM with systolic blood pressure, with a mediation ratio of 37.1% and 8.2%, respectively. Furthermore, total cholesterol (TC) and triglyceride (TG) positively mediated the association of predicted FM with diastolic blood pressure, with a mediation ratio of 9.5% and 9.9%, respectively.ConclusionHigher predicted FM might play a central role in the positive linear relationship of the BMI-hypertension association in Chinese male adults, and the link from predicted FM to blood pressure was partially mediated by TC, TG, HDL-c, and FBG.

Dataset Information

Predicted lean body mass in relation to cognitive function in the older adults.

Background

Methods

Results

Conclusion

Publications

Predicted lean body mass in relation to cognitive function in the older adults.

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