BACKGROUND: Epidemiological evidence on weight change and atrial fibrillation (AF) remains limited and inconsistent. Previous studies on body mass index (BMI) in youth and AF rarely considered subsequent BMI. This study aimed to assess the associations of AF with weight change and BMI in youth, as well as modified effect by genetic susceptibility of AF.
METHODS: The study included 21,761 individuals (mean age 57.8 years) from the Malmö Diet and Cancer cohort. Weight information was obtained at three time points, including recalled weight at age 20 years, measured weight at baseline (middle adulthood), and reported weight at 5-year follow-up examination (late middle adulthood). A weighted genetic risk score of AF was created using 134 variants.
RESULTS: During a median follow-up of 23.2 years, a total of 4038 participants developed AF. The association between weight change from early to middle adulthood and AF risk was modified by sex (Pinteraction = 0.004); weight loss was associated with a lower AF risk in females, but not in males. Conversely, weight gain was positively associated with AF risk in a linear manner in females, whereas increased AF risk appeared only when weight gain exceeded a threshold in males. Participants with weight gain of > 5 kg from middle to late middle adulthood had a 19% higher risk of AF relative to those with stable weight, whereas weight loss showed a null association. Compared to individuals with a lower BMI at age 20 years, those with a BMI above 25 kg/m2 had an increased risk of AF (HR = 1.14; 95% CI: 1.02-1.28), after controlling for baseline BMI; this association was more pronounced in males or those with a lower genetic risk of AF.
CONCLUSIONS: Weight gain in middle adulthood was associated with higher AF risk. Weight loss from early to middle adulthood, but not from middle to late middle adulthood, was associated with a lower risk of AF only in females. Higher BMI in youth was associated with an increased risk of AF, particularly among males or those with a lower genetic risk of AF.

The association between air pollutants and hepatobiliary pancreatic diseases remains inconclusive. This study analyzed up to 247,091 participants of White European ancestry (aged 37 to 73 years at recruitment) from the UK Biobank, a large-scale prospective cohort with open access. An air pollution score was utilized to assess the combined effect of PM2.5, PM2.5-10, PM10, NO2, and NOX on total hepatobiliary pancreatic diseases, liver diseases, cholecyst diseases, and pancreatic diseases. Cox proportional hazard models were employed to evaluate the relationships between air pollutants and the incidence of these diseases. Restricted cubic spline regressions were used to examine the dose-response association between air pollutants and the risk of hepatobiliary pancreatic diseases. We identified 4865 cases of total hepatobiliary pancreatic diseases, over a median follow-up of 10.86 years. The air pollution scores were moderately associated with increased liver disease risk (HR = 1.009, 95 % CI: 1.004, 1.014), but not with cholecyst and pancreatic diseases. Among the individual air pollutants, PM2.5 (HR = 1.069, 95 % CI: 1.025, 1.115) and PM10 (HR = 1.036, 95 % CI: 1.011, 1.061) significantly increased liver disease risk. Males showed a higher risk of liver diseases with PM2.5 (HR = 1.075, 95 % CI: 1.015, 1.139). Additionally, individuals with overweight (HR = 1.125, 95 % CI: 1.052, 1.203), age ≥ 60 and ≤73 (HR = 1.098, 95 % CI: 1.028, 1.172), and alcohol intake ≥ 14 unit/week (HR = 1.078, 95 % CI: 1.006, 1.155) had a higher risk of developing liver diseases at high expose to PM2.5. This study suggests that prolonged exposure to ambient air pollutants may elevate the risk of liver diseases.

BACKGROUND: A history of fracture has been associated with increased risk of dementia; however, it is uncertain whether sex difference exists in the association between prior fracture and subsequent risk of incident dementia.
OBJECTIVE: To investigate whether sex modified the relationship between prior fracture and subsequent risk of dementia.
METHODS: Prospective cohort study.
METHODS: UK Biobank.
METHODS: 496,331 participants (54.6% women) free of dementia at baseline.
METHODS: History of fracture was self-reported via touchscreen questionnaires at baseline. The primary outcome was all-cause dementia.
RESULTS: Both any fracture and fragility fracture were significantly associated with an increased risk of subsequent all-cause dementia in men (adjusted hazard ratio (HR): 1.28; 95% confidence interval (CI): 1.14-1.43; adjusted HR: 1.48; 95% CI: 1.18-1.87, respectively), but not in women (adjusted HR: 1.04; 95% CI 0.95-1.15; adjusted HR: 1.01; 95% CI: 0.87-1.18, respectively); and these sex-differences were significant (P interaction = 0.006; P interaction = 0.007, respectively). The sex differences in the impacts of different fracture sites (including upper limb, lower limb, spine, and multiple sites) were consistent on all-cause dementia.
CONCLUSIONS: This study demonstrated that prior fracture was associated with an increased risk of dementia in men but not in women, and the sex difference was significant. Previous fracture may be an important marker for identifying subsequent dementia in middle-aged and older men.

UNASSIGNED: Numerous studies have established the role of inflammation in osteoarthritis (OA) progression, yet limited research explores the association between systemic inflammatory indicators and pre-diagnosis OA risk. This study aimed to investigate the association between peripheral inflammatory indicators and the risk of OA using data from the UK Biobank.
UNASSIGNED: The study analyzed data from 417,507 participants in the UK Biobank, including neutrophil count, lymphocyte count, monocyte count, platelet count, and C-reactive protein meter. Additionally, derived ratios such as NLR(neutrophils-lymphocytes ratio), PLR(Platelets-lymphocytes ratio), SII(systemic immune-inflammation index), and LMR (lymphocytes-monocytes ratio) were examined. Cox proportional hazards models and restricted cubic spline models were used to assess both linear and nonlinear associations.
UNASSIGNED: Over a mean follow-up period of 12.7 years, a total of 49,509 OA events were identified. The findings revealed that CRP (HR:1.06, 95%CI:1.05-1.07), NLR (HR:1.02, 95%CI:1.01-1.03), PLR (HR:1.02, 95%CI:1.01-1.03), and SII (HR:1.03, 95%CI:1.01-1.04) were associated with an increased risk of OA, while LMR (HR:0.97, 95%CI:0.96-0.99) showed a significant negative correlation with OA risk. Subgroup analyses further emphasized that these associations were significant across most of the population. Although neutrophils, lymphocytes, monocytes, and platelets showed a nominal association with the risk of OA, the results were unreliable, especially for specific joint OA.
UNASSIGNED: The study provides evidence of a significant association between elevated peripheral inflammatory indicators and OA risk. These findings underscore the importance of low-grade chronic inflammation in OA development. The potential clinical utility of these indicators as early predictors of OA is suggested, warranting further exploration.

UNASSIGNED: We prospectively analyzed the correlation between fasting plasma glucose (FPG) and the risk of breast cancer in women; explored the independent risk factors for breast cancer in women, and compared the effect of FPG level on the risk of young and non-young breast cancer. Our study provides new evidence and ideas for research into breast cancer etiology in China, improves the accuracy of secondary prevention of breast cancer, and provides options for the clinical diagnosis and treatment of breast cancer patients with diabetes.
UNASSIGNED: Three cohorts of women participating in the first health examination of the Kailuan Group in 2006, 2008 and 2010 were assembled to conduct a descriptive analysis of the baseline data on FPG. The cumulative incidence of breast cancer in different groups over 13 years was calculated using the Kaplan-Meier method and groups were compared using the log-rank test. A Cox proportional hazards regression model was used to analyze the association between FPG level and the risk of breast cancer.
UNASSIGNED: The cumulative incidence of breast cancer increased in people with FPG higher than 5.29 mmol/L, but there was no significant difference in the effect of different levels of FPG on the risk of young breast cancer in the population. Different degrees of fasting glucose can affect the risk of non-young breast cancer in the population.
UNASSIGNED: The results of this study suggest that the risk of breast cancer can be reversed by early intervention to control levels of FPG. Regular monitoring of FPG may reduce the misdiagnosis rate of breast cancer in the population.

Our study aimed to investigate the relationship between sleep-wake changes and depressive symptoms events among midlife women. We enrolled 1579 women aged 44-56 years who had no clinically relevant depressive symptoms at baseline. Depressive symptoms were assessed at each visit using the Center for Epidemiologic Studies Depression scale. At the third and fourth follow-up visits, women reported their sleep habits. The sleep midpoint was defined as the time to fall asleep plus one-half of the sleep duration. Sleep-wake changes were determined by the difference in the midpoint of sleep between the third and fourth visits, which were 1 year apart. The median follow-up time was 7 years (range 1-7 years). Cox proportional hazard models were fitted to calculate hazard ratios and 95% confidence intervals for the incidence of depressive symptoms associated with sleep-wake changes. After adjusting for potential confounding factors, the hazard ratio (95% confidence interval) of depressive symptoms for severe sleep midpoint changes was 1.51 (1.12, 2.05) compared with mild sleep midpoint changes. This relationship remained statistically significant and changed little when additionally controlling for sleep duration, sleep quality, insomnia symptoms, use of sleep medications, use of nervous medications, glucose, insulin, lipids, dietary energy intake, and C-reactive protein. Our findings indicate that exposure to long-term severe sleep-wake changes increases the risk of depressive symptoms in midlife women.

BACKGROUND: This study evaluated the relationship between controlling multiple risk factors and diabetes-related heart failure and all-cause mortality, and the extent to which the excess risk can be reduced.
METHODS: 17,676 patients with diabetes and 69,493 matched non-diabetic control subjects were included in the Kailuan study, with a median follow-up of 11.19 years. The risk factor control was defined by the attainment of target values for systolic blood pressure, body mass index, low-density lipoprotein cholesterol, fasting blood glucose, high-sensitive C-reactive protein and smoking. Fine-Gray and Cox models were used to estimate associations between the degree of risk factor control and risk of heart failure and all-cause mortality respectively.
RESULTS: Among diabetes patients, there was a gradual reduction in the risk of outcomes as the degree of risk factor control increased. For each additional risk factor that was controlled, there was an associated 16 % decrease in heart failure risk and a 10 % decrease in all-cause mortality risk. Among diabetes patients with ≥5 well-controlled risk factors, the adjusted hazard ratio compared to controls for heart failure and all-cause mortality was 1.25 (95 %CI: 0.99-1.56) and 1.17(95 %CI: 1.05-1.31) respectively. The protective effect of comprehensive risk factor control on the risk of heart failure was more pronounced in men and those using antihypertensive medications.
CONCLUSIONS: Control for multiple risk factors is associated with reduced heart failure and all-cause mortality risks in a cumulative and sex-specific manner. However, despite optimization of risk factor control, diabetes patients still face increased risks compared to the general population.

BACKGROUND: A gut-microbial metabolite, trimethylamine N-oxide (TMAO), has been associated with type 2 diabetes mellitus (T2DM). Few previous prospective studies have addressed associations between the changes in TMAO and T2DM incidence.
METHODS: Data were derived from a longitudinal cohort conducted from 2019 to 2021 in rural areas of Fuxin County, Liaoning Province, China, and 1515 diabetes-free participants aged above 35 years were included. The concentrations of serum TMAO and its precursors were measured at two time points, namely in 2019 and 2021. TMAO and TMAO changes (ΔTMAO) were separately tested in a logistic regression model. For further examination, the odds ratios (ORs) for T2DM were calculated according to a combination of TMAO levels and ΔTMAO levels.
RESULTS: During a median follow-up of 1.85 years, 81 incident cases of T2DM (5.35%) were identified. Baseline TMAO levels exhibited a nonlinear relationship, first decreasing and then increasing, and only at the highest quartile was it associated with the risk of T2DM. The OR for T2DM in the highest quartile of serum TMAO was 3.35 (95%CI: 1.55-7.26, p = 0.002), compared with the lowest quartile. As for its precursors, only choline level was associated with T2DM risk and the OR for T2DM in the Q3 and Q4 of serum choline was 3.37 (95%CI: 1.41-8.05, p = 0.006) and 4.72 (95%CI: 1.47-15.13, p = 0.009), respectively. When considering both baseline TMAO levels and ΔTMAO over time, participants with sustained high TMAO levels demonstrated a significantly increased risk of T2DM, with a multivariable-adjusted OR of 8.68 (95%CI: 1.97, 38.34).
CONCLUSIONS: Both initial serum TMAO levels and long-term serum TMAO changes were collectively and significantly associated with the occurrence of subsequent T2DM events. Interventions aimed at normalizing TMAO levels, such as adopting a healthy dietary pattern, may be particularly beneficial in T2DM prevention.

Diet is one of the most important ways to intervene and promote the health of older adults and reduce all-cause mortality. This study aimed to investigate the association between dietary patterns and all-cause mortality in the Chinese old. This study involved 11,958 subjects aged 65-116 years in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2008 to 2018. Dietary patterns were derived from principal component analysis (PCA) with varimax rotation. Four dietary patterns were derived: the \'milk-egg-sugar pattern\', \'carnivorous pattern\', \'healthy pattern\', and \'northeastern pattern\'. Cox proportional hazard models were built for males and females separately to estimate the relationship between different dietary patterns and all-cause mortality. After adjusting for all covariates, the milk-egg-sugar pattern played a reverse role in mortality risk in males and females in different quartiles. In the carnivorous pattern, only males in the fourth quartile were observed to have a significantly reduced mortality risk (HR = 0.84 (95% CI: 0.77-0.93)). Both genders benefited from the healthy pattern, which consistently lowered mortality risk across all quartiles (males: HR = 0.87 (95% CI: 0.84-0.89); females: HR = 0.95 (95% CI: 0.92-0.97)). The northeastern pattern also showed an inverse association with all-cause mortality in males (HR = 0.94 (95% CI: 0.92-0.97)) and females (HR = 0.96 (95% CI: 0.93-0.98)). This study showed the association between dietary patterns and all-cause mortality in the Chinese old, which is significant for further quantitative studies.

OBJECTIVE: To compare the association between body mass index (BMI) trajectories determined by different methods and the risk of overweight in early childhood in a prospective cohort study, and to identify children with higher risk of obesity during critical growth windows of early childhood.
METHODS: A total of 1 330 children from Peking University Birth Cohort in Tongzhou (PKUBC-T) were included in this study. The children were followed up at birth, 1, 3, 6, 9, 12, 18, and 24 months and 3 years of age to obtain their height/length and weight data, and calculate BMI Z-score. Latent class growth mixture modeling (GMM) and longitudinal data-based k-means clustering algorithm (KML) were used to determine the grouping of early childhood BMI trajectories from birth to 24 mouths. Linear regression was used to compare the association between early childhood BMI trajectories determined by different methods and BMI Z-score at 3 years of age. The predictive performance of early childhood BMI trajectories determined by different methods in predicting the risk of overweight (BMI Z-score > 1) at 3 years was compared using the average area under the curve (AUC) of 5-fold cross-validation in Logistic regression models.
RESULTS: In the study population included in this research, the three-category trajectories determined using GMM were classified as low, medium, and high, accounting for 39.7%, 54.1%, and 6.2% of the participants, respectively. The two-category trajectories determined using the KML method were classified as low and high, representing 50. 3% and 49. 7% of the participants, respectively. The three-category trajectories determined using the KML method were classified as low, medium, and high, accounting for 31.1%, 47.4%, and 21.5% of the participants, respectively. There were certain differences in the growth patterns reflected by the early childhood BMI trajectories determined using different methods. Linear regression analysis found that after adjusting for maternal ethnicity, educational level, delivery mode, parity, maternal age at delivery, gestational week at delivery, children\' s gender, and breastfeeding at 1 month of age, the association between the high trajectory group in the three-category trajectories determined by the KML method (manifested by a slightly higher BMI at birth, followed by rapid growth during infancy and a stable-high BMI until 24 months) and BMI Z-scores at 3 years was the strongest. Logistic regression analysis revealed that the three-category trajectory grouping determined by the KML method had the best predictive performance for the risk of overweight at 3 years. The results were basically consistent after additional adjustment for the high bound score of the child\' s diet balanced index, average daily physical activity time, and screen time.
CONCLUSIONS: This study used different methods to identify early childhood BMI trajectories with varying characteristics, and found that the high trajectory group determined by the KML method was better able to identify children with a higher risk of overweight in early childhood. This provides scientific evidence for selecting appropriate methods to define early childhood BMI trajectories.