Extracellular flux analyses reveal differences in mitochondrial PBMC metabolism between high-fit and low-fit females

Analyzing metabolism of peripheral blood mononuclear cells (PBMCs) can possibly serve as a cellular metabolic read-out for lifestyle factors and lifestyle interventions. However, the impact of PBMC composition on PBMC metabolism is not yet clear, neither is the differential impact of a longer-term lifestyle factor versus a short-term lifestyle intervention. We investigated the effect of aerobic fitness level and a recent exercise bout on PBMC metabolism in females. PBMCs from 31 young female adults divided into a high-fit (V̇O2peak ≥ 47 mL/kg/min, N = 15) and low-fit (V̇O2peak ≤ 37 mL/kg/min, N = 16) group were isolated at baseline and overnight after a single bout of exercise (60 minutes, 70% V̇O2peak). Oxygen consumption rate (OCR) and glycolytic rate (GR) were measured using extracellular flux (XF) assays and PBMC subsets were characterized using fluorescence-activated cell sorting (FACS). Basal OCR, FCCP-induced OCR, spare respiratory capacity, ATP-linked OCR, and proton leak were significantly higher in high-fit compared to low-fit females (all P < 0.01), while no significant differences in glycolytic rate (GR) were found (all P > 0.05). A recent exercise bout did not significantly affect GR or OCR parameters (all P > 0.05). The overall PBMC composition was similar between high-fit and low-fit females. Mitochondrial PBMC function was significantly higher in PBMCs from high-fit compared to low-fit females, which was unrelated to PBMC composition and not impacted by a recent bout of exercise. Our study reveals a link between PBMC metabolism and levels of aerobic fitness, increasing the relevance of PBMC metabolism as a marker to study the impact of lifestyle factors on human health.

Association of age-related cataract risk high polygenetic risk scores involved in galactose-related metabolism and dietary interactions

Introduction: Cataracts are associated with the accumulation of galactose and galactitol in the lens. We determined the polygenetic risk scores for the best model(PRSBM) associated with age-related cataract(ARC) risk and their interaction with diets and lifestyles in 40,262 Korean adults aged over 50 years belonged to a hospital-based city cohort. Methods: The genetic variants for ARC risk were selected in lactose and galactose metabolism-related genes with multivariate logistic regression using the PLINK 1.9 version. PRSBM from the selected genetic variants was estimated by generalized multifactor dimensionality reduction (GMDR) after adjusting covariates. The interactions between the PRSBM and each lifestyle factor were determined to modulate ARC risk. Results: The genetic variants for ARC risk related to lactose- and galactose metabolism were SLC2A1_rs3729548, ST3GAL3_rs3791047, LCT_rs2304371, GALNT5_rs6728956, ST6GAL1_rs2268536, GALNT17_rs17058752, CSGALNACT1_rs1994788, GALNTL4_rs10831608, B4GALT6_rs1667288, and A4GALT_ rs9623659. In GMDR, the best model included all ten genetic variants. The highest odds ratio (OR) for a single SNP in the PRSBM was 1.26. However, subjects with a high-PRSBM had a higher ARC risk by 2.1-fold than a low-PRSBM after adjusting for covariates. Carbohydrate, dairy products, kimchi, and alcohol intake interacted with PRSBM for ARC risk: the participants with high-PRSBM had a much higher ARC risk than those with low-PRSBM when consuming diets with high carbohydrate and low dairy product and kimchi intake. However, only with low alcohol intake, the participants with high-PRSBM had a higher ARC risk than those with low-PRSBM. Conclusion: Adults aged >50 years having high-PRSBM may modulate dietary habits to reduce ARC risk.

Concept of Fatty liver and its management in Ayurveda

Fatty liver disease is a most common liver disease affecting a wide range of population worldwide. It is caused due to excessive fat accumulation in liver cells resulting in inflammation in liver. There are various symptoms such as confusion, fatigue, weakness etc. Over-eating is the major lifestyle factor causing fatty liver disease. Alcoholic intake results in alcoholic fatty liver disease Ajirna (indigestion), Sthaulya (obesity) and Prameha (diabetes mellitus) which occurs due to the vitiation of Annavaha, Rasavaha and Medovaha Srotas acts as Nidanarthakara Rogas (diseases which cause another diseases) which may result in the manifestation of non-alcoholic fatty liver. According to Ayurvedic texts, Panchkarma (Virechana) and herbs like Bhumiamalaki and Guduchi etc. acts a hepatoprotective and improves the functioning of liver.

Consequential Impacts of Tobacco Use on Cognitive Performance

Tobacco use represents a pernicious lifestyle factor that may influence processes of aging, including cognitive functioning. As individuals tend to start smoking before adulthood, it may serve as an important factor in cognitive development and maintenance. We explored smoking history-cognition associations in a sample approaching midlife. Study data was derived from the Colorado Adoption/Twin Study of Lifespan behavioral development and cognitive aging (CATSLife 1; N = 1195 [53% F]; x̄age = 33.2 years, SD = 5.0). All cognitive measures were t-scored covering working memory, spatial reasoning, processing speed (WAIS-III Digit Span, Block Design, and Digit Symbol, and Colorado Perceptual Speed) and episodic memory domains (Picture Memory, immediate and delayed). Tobacco use measures included ever-smokers, current-smokers, and log-transformed packyears. Mixed-effects regression models were applied, accounting for sex, age, race, ethnicity, and clustering among siblings. Tobacco use was associated with worse episodic memory, spatial and speed performance, but not working memory. When educational attainment was included, patterns remained consistent though attenuated. Results suggested current-smokers scored 0.27 to 0.36 SD lower than non-smokers on speed and spatial reasoning tasks. Episodic memory performance was reduced by approximately 0.07 to 0.1 SD per log packyear. In a sample approaching midlife, the harmful impacts of tobacco use on cognitive performance may be already apparent with cumulative impacts of packyears on episodic memory and current smoking associated with spatial and speed performance. This work helps to elucidate the temporal associations of an important lifestyle factor that may influence cognitive functioning prior to midlife.

Cluster Analysis for Identifying Obesity Subrouops in Health and Nutritional Status Survey Data

This study presents the discovery of meaningful patterns (groups) from the obese samples of health and nutritional survey data by applying various clustering techniques. Due to the mixed nature of the data (qualitative and quantitative variables) in the data set, the best-suited clustering techniques with appropriate dissimilarity metrics were chosen to interpret the meaningful results. The relationships between obesity and the lifestyle affecting factors like demography, socio-economic status, physical activity, and dietary behavior were assessed using four cluster techniques namely Two-Step clustering, Partition Around Medoids (PAM), Agglomerative Hierarchical clustering and, Kohonen Self Organizing Maps (SOMs). The solutions generated by these techniques were analyzed and validated by the help of cluster validity (CV) indices and later on their associations were determined with the obesity classes to discover the pattern from the obese sample. Two-Step clustering and hierarchical clustering outperformed the other applied techniques in identifying the subgroups based on the underlying hidden patterns in the data. Based on the CV indices values and the association analysis (obesity factor with the cluster solutions), two subgroups were generated and profiles of these groups have been reported. The first group belonged to the middle-aged individuals who seem to take care of their lifestyle while the other group belonged to young-aged individuals who in contrast to the first group presented a careless lifestyle factor (i.e., physical activity and dietary behavior). The salient features of these subgroups have been reported and can be proposed for the betterment in the health care industry. The research helped in identifying the interesting subsets/groups within survey data demonstrating similar characteristics and health status (i.e., prevalence of obesity with respect to lifestyle factors like physical activity, dietary behavior etc.) which will help to suggest appropriate measures/steps to be taken by the concerned departments to counter them and prevent in the population.

Food Away From Home and Self-Perceived Gastrointestinal Health

Dietary behavior is a critical lifestyle factor affecting health. This study aimed to investigate food away from home (FAFH) and its effect on gastrointestinal (GI) health. A questionnaire-based survey was conducted with 300 participants at a hospital in Liouying, Taiwan. The survey collected demographic information and data on FAFH and GI health. The association of GI health with FAFH consumption behavior was significant (t-test, p &lt; 0.05). Bodyweight status was associated with age (F = 5.01, p = 0.01), dietary situation (F = 1.96, p = 0.04), number of meals (F = 1.85, p = 0.03), dietary preferences (F = 2.84, p = 0), reasons for FAFH (F = 1.86, p = 0.02), FAFH types (F = 2.01, p = 0), and outcomes associated with FAFH (F = 2.51, p = 0). Gastrointestinal condition was associated with the number of meals (F = 2.55, p = 0), the level of activity after meals (F = 2.16, p = 0.02), and FAFH type (F = 1.48, p = 0.04). The results indicated that the participants aged 20–40 years had more problems related to their self-perceived body weight status than those aged 41–50 years. The results of this study clarify the FAFH among people in Taiwan and the effects on GI health and may serve as a reference for relevant behavioral research in food and health studies.

Comparison of four healthy lifestyle scores for predicting cardiovascular events in a national cohort study

The protective effect of different healthy lifestyle scores for the risk of cardiovascular disease (CVD) was reported, although the comparisons of performance were lacking. We compared the performance measures of CVDs from different healthy lifestyle scores among Taiwanese adults. We conducted a nationwide prospective cohort study of 6042 participants (median age 43 years, 50.2% women) in Taiwan’s Hypertensive, Hyperglycemia and Hyperlipidemia Survey, of whom 2002 were free of CVD at baseline. The simple and weighted the Mediterranean diet related healthy lifestyle (MHL) scores were defined as a combination of normal body mass index, Mediterranean diet, adequate physical activity, non-smokers, regular healthy drinking, and each dichotomous lifestyle factor. The World Cancer Research Fund and American Institute for Cancer Research cancer prevention recommended lifestyle and Life's Simple 7 following the guideline definition. The incidence of CVD among the four healthy lifestyle scores, each divided into four subgroups, was estimated. During a median 14.3 years follow-up period, 520 cases developed CVD. In the multivariate-adjusted Cox proportional hazard models, adherence to the highest category compared with the lowest one was associated with a lower incidence of CVD events, based on the simple (hazard ratio [HR] 0.43, 95% confidence interval [CI] 0.2–0.94) and weighted MHL scores (HR 0.44, 95% CI 0.28–0.68). Additionally, age played a role as a significant effect modifier for the protective effect of the healthy lifestyle scores for CVD risk. Specifically, the performance measures by integrated discriminative improvement showed a significant increase after adding the simple MHL score (integrated discriminative improvement: 0.51, 95% CI 0.16–0.86, P = 0.002) and weighted MHL score (integrated discriminative improvement: 0.38, 95% CI 0.01–0.74, P = 0.021). We demonstrated that the healthy lifestyle scores with an inverse association with CVD and reduced CVD risk were more likely for young adults than for old adults. Further studies to study the mechanism of the role of lifestyle on CVD prevention are warranted.

Criterion Referenced Factor Analysis (CRFA): Method and Illustration

CRFA is a valid method for evaluating relationships between criteria and “factors'' initially identified from both the predictor and the criterion variables. Among others, it may be applied to classical problems involving: 1) Changes in complex task ability requirements as a function of practice, 2) Impacts of environmental stressors on personality or performance factors overtime, or 3) Residential Lifestyle Factor Impacts on Energy-Use (as herein). CRFA differs from traditional battery developments in its: (a) Initial inclusion of both criterion and predictor variables for factor identifications, but (b) Exclusion of criterion in the ultimate calculation of factor-scores. This avoids the vexing confounding of criterion variance in factor score estimates, and ultimately provides for unconfounded analyses of criterion and factor relationships. A “Big-Data'' illustration of CRFA is presented that highlights the stability of model results for independent samples across years. The primary model of interest built upon a USA-representative survey (N = 2,165) sample of 17 variables adapted from RECS-2005 (USEIA, 2019). These included16 lifestyle-related and an annual energy use criterion (i.e., LNKWH, Ln-transformed annual KiloWatt Hours). Unweighted least squares (ULS) factor analysis revealed a 5- Lifestyle factor solution that accounted for 45.5% of the total variation in the 17-variable set and 45.3% of the 16 less LNKWH. “Lifestyle” factor predictions – subsequently derived by CRFA less LNKWH– are found to be remarkably stable when compared to a similar sample taken 4-years earlier (RECS-2001). Specifically, (1) the proportions of LNKWH variance explained with lifestyle factor scores alone are nearly identical across the 4-year gap (2005 R2 = 0.42- and 2001 R2 = 0.38; ps <10-10), (2) these increased after external additions of household characteristics (R2 = 0.55 both fore- and back-casting; ps <10-15), and model B-weights were near identical. CRFA is strongly recommended for valid evaluations of relationships between criteria and predictor-based factor-scores, where factor characterizations are initially derived from both predictor and criterion variables.

Hypothetical Interventions for Falls Among Older Adults: An Application of the Parametric G-Formula

Introduction: Falls, which have a higher incidence and mortality due to accidental injuries, are a major global health challenge. The effects of lifestyle factor, health indicator, psychological condition, and functional status interventions on the risk of falls are unknown and the conventional regression model would not adjust for the confounders. This study aimed to evaluate the 4-year risk of falls on the basis of these hypothetical interventions among Chinese older adults.Methods: Data were obtained from 9,692 aged 65 years and over older adults in the China Health and Retirement Longitudinal Study wave, from 2011 to 2015. We used the parametric g-formula to evaluate the risk of falls on the basis of independent hypothetical interventions of sleep duration, social activities, smoking status, drinking status, body mass index (BMI), systolic blood pressure (SBP), vision, depression, activities of daily living (ADL), and their different joint intervention combinations.Results: During the follow-up of 4 years, we documented 1,569 falls. The observed risk of falls was 23.58%. The risk ratios (95% confidence intervals [CIs]) of falls under the intensive hypothetical interventions on increasing sleep duration, participating in more social activities, quit smoking and drinking, reducing BMI and SBP, better vision, alleviating depressive symptoms, and improving ADL capability were 0.93 (0.87–0.96), 0.88 (0.79–0.92), 0.98 (0.95–1.03), 0.97 (0.95–1.02), 0.92 (0.86–1.03), 0.93 (0.87–1.04), 0.86 (0.74–0.91), 0.91 (0.85–0.96), and 0.79 (0.74–0.85), respectively. The feasible and intensive joint hypothetical intervention reduced the 4-year fall risk by 22% (95% CI: 0.52–0.91) and 33% (95% CI: 0.56–0.72), respectively.Conclusions: Hypothetical interventions for increasing sleep duration, participating in more social activities, better vision, alleviating depressive symptoms, and improving ADL capability help protect older adults from falls. Our findings suggest that a combination of lifestyle factors, health indicators, psychological conditions, and functional status may prove to be an effective strategy for preventing falls among older adults.

1270The Contribution of Lifestyle Patterns to Clustering of Elevated Depressive Symptoms within Birth Cohorts

Background Some birth cohorts experience a larger burden of depression than others. We hypothesize that lifestyle, i.e. BMI, alcohol consumption, smoking and physical activity, are potential drivers of these generational differences. Methods We analyzed data from US adults aged 50-80 years enrolled in the Health and Retirement Study (N = 163,760 person-years). Birth cohort effects were estimated with the age-period-cohort model approach according to Carstensen. Consequently, we assessed the contribution of lifestyle factors by comparing the predicted probability of elevated depressive symptoms to a counterfactual scenario in which all birth cohorts are assigned the lifestyle factor distribution of the 1945 cohort (counterfactual decomposition analysis). We stratified all analyses by sex and ethnicity. Results BMI contributes to an increased probability of elevated depressive symptoms of up to 32.7% (95%CI: 190.9-11.23%, 1923 cohort) for cohorts born before 1927 and a decrease of up to 16.7% (95%CI: 0.5-26.8, 1964 cohort) for cohorts born after 1959. Contributions are most pronounced in females and white/Caucasians. Alcohol consumption contributes up to 20% (95%CI: 0.8%;45.3%, 1925 cohort) to cohort effects of elevated depressive symptoms, whereas the magnitude differs by ethnicity. We found no evidence for contributions of smoking or physical activity. Conclusions Birth cohort effects of elevated depressive symptoms can be partly explained by lifestyle. In particular, mental health of females and the white/Caucasian population may have suffered from the increase in obesity levels in the US. Key messages BMI and alcohol consumption, but not smoking or physical activity, contribute to birth cohort differences in depression risk.