Developmental disabilities prevalence seem to be high in countries around the world. It’s worth understanding the most recent prevalence and trends of developmental disabilities. The objective of this study is to examine the prevalence and trends of developmental disabilities of US children and adolescents. A total of 26,422 individuals aged 3–17 years were included. Annual data were examined from the National Health Interview Survey (2018–2021). Weighted prevalence for each of the selected developmental disabilities were calculated. The prevalence of any developmental disabilities in individuals was 16.65% (95% CI 16.03–17.26%), prevalence of attention deficit/hyperactivity disorder (ADHD), learning disability (LD), autism spectrum disorder (ASD), intellectual disability (ID), and other developmental delay were 9.57% (95% CI 9.09–10.06%), 7.45% (95% CI 7.00–7.89%), 2.94% (95% CI 2.67–3.21%), 1.72% (95% CI 1.51–1.93%), and 5.24% (95% CI 4.89–5.59%), respectively. Significant increases were observed for other developmental delay (4.02–6.05%) and co-occurring LD & ID (1.03–1.82%). Findings form this study highlight a high prevalence of any developmental disabilities, although no significant increase was observed. The prevalence of other developmental delay and co-occurring LD & ID were significantly increased. Further investigation is warranted to assess potentially modifiable risk factors and causes of developmental disabilities.

Background: Sarcopenia and frailty are both age‐related declines in functional reserve that are linked to adverse health outcomes. It is critical to know about the outcomes of a combination of these conditions. The study aimed to investigate the effects of sarcopenia and frailty on postoperative recovery in elderly patients and to explore risk factors.Methods: This prospective cohort study was conducted among 608 patients aged ≥60 years, American Society of Anesthesiologists I‐III, who were scheduled to undergo thoracic (non‐cardiac) and abdominal surgery from 1 March 2022 to 31 October 2022 at the Affiliated Hospital of Xuzhou Medical University. Frailty was measured by the 28‐item frailty index, and sarcopenia was assessed sarcopenia was assessed by skeletal muscle index in computed tomographic scan, handgrip strength and 6‐m walk. Participants were classified as follows: Group A: both sarcopenia and frailty; Group B: sarcopenia only; Group C: frailty only; and Group D: neither frailty nor sarcopenia. The primary outcome was 90‐day morbidity. Multivariable logistic regression model was used to estimate the association between sarcopenia, frailty and 90‐day morbidity.Results: The median (interquartile range) age of participants was 68 (64–72) years, and 62.7% were men. The prevalence rates of sarcopenia and frailty were 32.8% and 47.6%, respectively. The 90‐day morbidity in Group A was 58.5%, in Group B was 46.2%, in Group C was 42.0% and in Group D was 28.8%, and the difference was significant (P < 0.001). In the multivariable analysis, both sarcopenia and frailty [odds ratio (OR), 2.21; 95% confidence interval (CI), 1.26–3.89], sarcopenia only (OR, 1.84; 95% CI, 1.01–3.36), frailty only (OR, 1.77; 95% CI, 1.03–3.03), women (OR, 0.67; 95% CI, 0.45–0.99), body mass index (OR, 0.94; 95% CI, 0.88–0.99), pre‐operative albumin (OR, 0.96; 95% CI, 0.91–1.00) and operative stress score (OSS) [OSS 3 (OR, 2.09; 95% CI, 1.21–3.67); OSS 4–5 (OR, 3.81; 95% CI, 2.31–6.42)] were independently associated with 90‐day morbidity. In the multivariable analysis with inverse probability weighting adjusted cohort, sarcopenia and frailty were also significantly associated with 90‐day morbidity.Conclusions: Sarcopenia and frailty were associated with higher risks of postoperative 90‐day morbidity in elderly patients alone and in combination. Sex, body mass index, pre‐operative albumin and operative stress were also independent factors for postoperative morbidity within 90 days.

Background: Hypertension is a worldwide public health problem. We sought to explore the interaction of oral health and smoking on hypertension, and periodontal disease and smoking on hypertension. Methods: We included 21,800 participants aged ≧ 30 years from the National Health and Nutrition Examination Survey (NHANES) 2009–2018. Information of oral health and periodontal disease were self-reported. Blood pressure was taken by trained personnel and/or physicians at mobile testing center. Multiple logistic regression was used to estimate the association between oral health, periodontal disease and the prevalence of hypertension. The effects of oral health and periodontal disease on hypertension under smoking status and age were analyzed by stratified and interaction analysis. Results: A total of 21,800 participants were investigated, including 11,017 (50.54%) in hypertensive group and 10,783 (49.46%) in non-hypertensive group. Compared with the excellent/very good of oral health, the multivariable-adjusted OR of good, fair, and poor were 1.13 (95% CI, 1.02–1.27), 1.30 (95% CI, 1.15–1.47), and 1.48 (95% CI, 1.22–1.79) (p for trend < 0.001) for hypertension, respectively. Compared without periodontal disease group, the multivariable-adjusted OR of periodontal disease for hypertension was 1.21 (95% CI ,1.09–1.35) (p for trend < 0.001). Furthermore, we found the interactions between periodontal disease and smoking, oral health and smoking, periodontal disease and age, oral health and age were p < 0.001. Conclusions: An association between oral health and periodontal disease with the prevalence of hypertension was identified. There exists interactive effect of periodontal disease and smoking, oral health and smoking, periodontal disease and age, oral health and age on hypertension in American population over 30 years of age and older.

Learning disability (LD) is a group of heterogeneous disorders manifested by substantial difficulties in listening, speaking, reading, writing, reasoning, or mathematical abilities.¹ Research indicates that LD has become a major health concern for children in the US.² Literature reported that the prevalence of LD among children varied from 8.7% to 9.7% based on data from the National Health Interview Survey (NHIS) from 2004 to 2006 and the 2003 National Survey of Children’s Health, respectively.^1,3 However, research on long-term trend over the past decades is lacking. The aim of this cross-sectional study was to estimate the prevalence of LD and its long-term trend among US children and adolescents aged 6 to 17 years from 1997 to 2021.

Many studies reported the influence of infants' gut microbiota on atopic dermatitis (AD) postnatally, yet the role of maternal gut microbiota and plasma metabolites in infants’ AD remains largely unexplored. Sixty-three pregnant mother-infants were enrolled and followed after childbirth in Guangzhou, China. Demographic information, maternal stool and plasma samples, and records for infants’ AD were collected. Maternal gut microbiota/metabolome and plasma metabolome were profiled using shotgun metagenomics and non-targeted metabolomics. Logistic regression and multi-omics analysis were used to explore characteristic maternal gut microbiota in the AD and health groups. The α-diversity of maternal gut microbiota in health group was significantly higher than AD group (Shannon diversity P = 0.02, Simpson diversity P = 0.04). Short-chain fatty acids (SCFAs) producing microorganisms, including Faecalibacterium, Roseburia, Butyricicoccus, and Ruminococcus, as well as the abundance of phenylalanine, tyrosine, and tryptophan biosynthesis pathway, were enriched in health group (LDA>2 and P < 0.05). Virulent factors (VFs) involved in immune modulation were enriched in the health group, while VFs involving in adhesin were enriched in the AD group (P < 0.05). Metabolomic analysis showed that a polyunsaturated fatty acid/linoleic acid, 13S-hydroxyoctadecadienoic, were negatively associated with AD in both the gut and plasma samples (FDR<0.05). Several other linoleic acids and flavonoids were negatively associated with AD (FDR<0.05). Neural network analysis revealed that microorganisms enriched in health group may produce these protective fatty acids. Our findings show that maternal gut microorganisms/metabolites and plasma metabolites during pregnancy impact subsequent pathogenesis of infants AD. This illuminates new strategies against early AD in offspring.

Background: The relationship between physical activity and hyperuricemia (HUA) remains inconsistent, and the dose-response association between moderate-to- vigorous physical activity (MVPA) level and HUA still unclear. In this study, we aimed to investigate the dose-response association of MVPA with HUA, and to explore an appropriate range of MVPA level for preventing HUA. Methods: Data from the US National Health and Nutrition Examination Survey (NHANES) 2007–2018 were used, including 28740 non-gout adult Americans. MVPA level was self-reported using the Global Physical Activity Questionnaire and serum uric acid was measured using timed endpoint method. The dose-response relationship between MVPA level and HUA was modeled with restricted cubic spline analysis. Logistic regression analysis were applied to estimate odd ratios (ORs) and 95% confidence intervals (CIs) of the relationships between MVPA level and HUA. Results: A total of 28740 adults were included in the study (weighted mean age, 47.3 years; 46.5% men), with a prevalence rate of HUA was 17.6%. The restricted cubic spline functions depicted a general U-shaped relationship between MVPA level and HUA. The MVPA level of 933 and 3423 metabolic equivalent (MET) -min/wk were the cut-off discriminating for the risk of HUA. Participants with MVPA levels in the range of 933–3423 MET-min/wk had lower risk of HUA and they had the lowest risk when MVPA levels at around 1556 MET-min/wk. Compared with the moderate-activity group (600–2999 Met-min/wk), the low-activity group (< 600 Met-min/wk) had a greater risk of HUA (OR, 1.13 [95%CI, 1.02–1.26]) after fully adjusting for potential confounders. Conclusions: Compared with the moderate MVPA level, the low MVPA level was associated with the higher risk of HUA. And there may be a U-shaped dose-response relationship between MVPA level and HUA. When MVPA level was approximately 933–3423 MET-min/wk, the risk of HUA may at a lower level and the risk reached the lowest when MVPA level at around 1556 MET-min/wk.