Numerous studies have indicated an obesity paradox in observational research on aging health, where being normal weight or underweight adversely affects cognitive function, while moderate obesity may offer protective benefits. This study aims to investigate the association between body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), abdominal volume index (AVI), and the joint effect of BMI and HC on cognitive impairment in older Chinese people. A total of 10,579 participants aged 65 years and older from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) were included in this cross-sectional study. BMI, WC, HC, WHtR, WHR, and AVI were calculated from height, weight, WC, and HC measurements, where weight, WC, and HC were obtained by direct measurement. Mini-Mental State Examination was used to assess cognitive impairment. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using binary logistic regression. Non-linear correlations were investigated using restricted cubic spline curves. In multivariate logistic regression models fully adjusted for confounding variables, our analyses showed significant negative associations of WC [OR 0.93 (95%CI 0.88–0.98), P = .012], HC [OR 0.92 (95%CI 0.87–0.97), P = .004], lower WHR (Q2) [OR 0.85 (95%CI 0.72-1.00), P = .044], and AVI [OR 0.93 (95%CI 0.88–0.98), P = .011] with cognitive impairment. Nonlinear curve analysis showed that the risk of cognitive impairment was lowest when the BMI was about 25.5 kg/m², suggesting that the optimal BMI for older Chinese people to maintain good cognitive ability may be in the overweight range. In addition, there was a non-linear “N” shaped relationship between HC and cognitive impairment, with HC having the highest risk of cognitive impairment at about 82 cm and the lowest risk at about 101 cm. The joint effects analysis indicated that the lowest risk was observed among those with normal or higher BMI but higher HC compared with participants with normal BMI levels and lower HC levels. In older Chinese people, a low-waisted and high-hip circumference body figure is favorable for cognitive function in older people. It also found a significant association between AVI and cognitive impairment. The joint analysis of BMI and HC suggests that maintaining a normal or higher BMI with a higher HC may be more conducive to maintaining good cognitive function.

Aim: To investigate the associations of body mass index (BMI), waist circumference (WC) and the weight‐adjusted waist index (WWI) with the impairment of activities of daily living (ADL) in older Chinese people. Methods: A total of 13 260 participants aged 65 years and older from the 2018 Chinese Longitudinal Healthy Longevity Survey were included in this cross‐sectional study. BMI, WC and the WWI were calculated from measurements of height, weight and WC. Binary logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs). Non‐linear correlations were investigated using restricted cubic spline curves. Results: In multivariate logistic regression fully adjusted for confounding variables, our analyses revealed significant associations between WC and WWI and ADL impairment, with adjusted ORs (95% CI) of 1.01 (1.00, 1.01) and 1.08 (1.03, 1.12), respectively. Meanwhile, participants with a high WWI had a higher risk of ADL impairment compared with those with a low WWI, with an adjusted OR (95% CI) of 1.12 (1.02, 1.23). Subgroup analyses showed that only the association between WWI and ADL impairment did not differ in any of the different populations. In addition, we found that BMI, WC and WWI were non‐linearly associated with ADL impairment. Conclusions: There are significant associations between WC and WWI and ADL impairment in older Chinese people. The findings show the ability of the WWI to serve as a comprehensive and effective indicator of obesity in older Chinese people and emphasize the importance of assessing WWI in screening and preventing ADL impairment in older people.

Background: Systemic juvenile idiopathic arthritis (SJIA) is a form of childhood arthritis with clinical features such as fever, lymphadenopathy, arthritis, rash, and serositis. It seriously affects the growth and development of children and has a high rate of disability and mortality. SJIA may result from genetic, infectious, or autoimmune factors since the precise source of the disease is unknown. Our study aims to develop a genetic-based diagnostic model to explore the identification of SJIA at the genetic level. Methods: The gene expression dataset of peripheral blood mononuclear cell (PBMC) samples from SJIA was collected from the Gene Expression Omnibus (GEO) database. Then, three GEO datasets (GSE11907-GPL96, GSE8650-GPL96 and GSE13501) were merged and used as a training dataset, which included 125 SJIA samples and 92 health samples. GSE7753 was used as a validation dataset. The limma method was used to screen differentially expressed genes (DEGs). Feature selection was performed using Lasso, random forest (RF)-recursive feature elimination (RFE) and RF classifier. Results: We finally identified 4 key genes (ALDH1A1, CEACAM1, YBX3 and SLC6A8) that were essential to distinguish SJIA from healthy samples. And we combined the 4 key genes and performed a grid search as well as 10-fold cross-validation with 5 repetitions to finally identify the RF model with optimal mtry. The mean area under the curve (AUC) value for 5-fold cross-validation was greater than 0.95. The model’s performance was then assessed once more using the validation dataset, and an AUC value of 0.990 was obtained. All of the above AUC values demonstrated the strong robustness of the SJIA diagnostic model. Conclusions: We successfully developed a new SJIA diagnostic model that can be used for a novel aid in the identification of SJIA. In addition, the identification of 4 key genes that may serve as potential biomarkers for SJIA provides new insights to further understand the mechanisms of SJIA.

Background: The association between obesity indicators and sleep quality remains unclear among elderly Chinese people. Therefore, we aimed to assess this association by utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).Methods: A total of 10,505 participants aged 65 and above from the 2018 CLHLS were included. Calculate body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and weight-adjusted-waist index (WWI) based on measured weight, height, and waist circumference. Based on BMI values, individuals were classified as underweight (<18.5 kg/m²), normal weight (18.5–23.9 kg/m²) and overweight or obesity (BMI ≥24 kg/m²). In the survey, sleep quality was rated in a 5-point format (“1 = very good,” “2 = good,” “3 = fair,” “4 = poor,” or “5 = very poor”), and we categorized “1” and “2” as good sleep quality and “3,” “4,” and “5” as poor sleep quality. Logistic regression models were used to evaluate odds ratios (ORs) and 95% confidence intervals (CIs), with subgroup analysis and restricted-cubic-spline (RCS) conducted.Results: The prevalence of poor sleep quality was 47.06%. There are significant differences in obesity indicators and other factors between the two groups of people with good sleep and poor sleep. After adjusting for potential confounding factors (including demographics, socioeconomic status, lifestyle behaviors, health-related issues and activities of daily living), our analyses revealed significant negative associations of BMI [OR 0.96 (95% CI 0.95–0.98)], WC [OR 0.99 (95% CI 0.98–0.99)] and WHtR [OR 0.18 (95% CI 0.09–0.35)] with poor sleep quality. RCS regression also showed that BMI, WC, WHtR and WWI were all strongly negatively correlated with poor sleep quality.Conclusions: In elderly Chinese people, overweight/obese elderly people may have a better sleep quality compared to elderly people with normal weight, while underweight elderly people are unfavorable for sleep quality.

Background: Obesity, through mechanisms such as insulin resistance and systemic low-grade inflammation, can damage the central nervous system and impair cognitive function. Weight-adjusted waist index (WWI) is a novel measure of obesity that may offer more precise assessments of muscle and fat mass. This study aims to investigate the association between WWI and cognitive function in older Chinese men.Methods: Data from the 2011–2018 China Longitudinal Health and Longevity Survey (CLHLS) were used in this study. WWI and cognitive function were examined in both linear and non-linear situations using Kaplan–Meier survival curves, multivariate Cox regression models, and restricted cubic spline (RCS) regression.Results: This study included 1,392 older Chinese men aged 65 years and over for whom complete data were available. After controlling for all potential confounding variables, our analysis showed a statistically significant positive association between WWI and cognitive decline. Specifically, for every 1 cm/√kg increase in WWI, the risk of cognitive impairment increased by 17% (HR = 1.17, 95% CI: 1.02–1.35). Using 11.52 cm/√kg as the cutoff point for WWI, we found that High WWI was associated with a 44% increased risk of cognitive impairment compared with Low WWI (HR = 1.44, 95% CI: 1.07–1.96). RCS regression analysis confirmed a linear positive correlation between WWI and cognitive impairment.Conclusion: Higher WWI is linked to worse cognitive performance in older Chinese men.

Despite the wide application of radiotherapy in HCC, radiotherapy efficacy is sometimes limited due to radioresistance. Although radioresistance is reported with high glycolysis, the underlying mechanism between radioresistance and cancer metabolism, as well as the role of cathepsin H (CTSH) within it, remain unclear. In this study, tumor-bearing models and HCC cell lines were used to observe the effect of CTSH on radioresistance. Proteome mass spectrometry, followed by enrichment analysis, were used to investigate the cascades and targets regulated by CTSH. Technologies such as immunofluorescence co-localization flow cytometry and Western blot were used for further detection and verification. Through these methods, we originally found CTSH knockdown (KD) perturbed aerobic glycolysis and enhanced aerobic respiration, and thus promoted apoptosis through up-regulation and the release of proapoptotic factors such as AIFM1, HTRA2, and DIABLO, consequently reducing radioresistance. We also found that CTSH, together with its regulatory targets (such as PFKL, HK2, LDH, and AIFM1), was correlated with tumorigenesis and poor prognosis. In summary, our study found that the cancer metabolic switch and apoptosis were regulated by CTSH signaling, leading to the occurrence of radioresistance in HCC cells and suggesting the potential value of HCC diagnosis and therapy.