To explore the epidemiological associations, potential mechanisms, and intervention strategies between four age-related eye diseases—cataract, glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR)—and cognitive impairment in the elderly, thus providing scientific evidence for interdisciplinary comprehensive management.

Relevant articles published from January 1, 2010 to November 2025 were systematically retrieved from CNKI, Wanfang Data, Web of Science, and PubMed databases, and 44 eligible research articles were included for analysis.

Patients with cataract had a 78% increased risk of all-cause dementia, which decreased by 36.8% after surgery (with a 60.1% reduction in Alzheimer′s disease risk). Patients with glaucoma had a 57%–89% increased risk of dementia, significantly associated with Alzheimer′s disease (+39% risk) and vascular dementia (+66% risk). The prevalence of cognitive impairment in patients with advanced AMD was 30%–40% higher than that in the general elderly population, and individuals with cognitive impairment had a 42% increased risk of progressing to advanced AMD within 5 years. Cognitive impairment in DR patients was dose-dependent. Regarding interventions, cataract surgery effectively reduced dementia risk, and nutritional regulation, lifestyle optimization, and multidisciplinary collaboration delayed disease progression. Community rehabilitation activities achieved an 82% functional maintenance rate, and county-level medical consortium management reduced severe visual impairment from DR by 40%.

Aging-related eye diseases and cognitive impairment have close bidirectional associations. Eye diseases are risk factors for cognitive decline and reflect central neurodegeneration. Early screening, multidisciplinary collaboration, and comprehensive management are crucial for improving physical and mental health outcomes.

To analyze the associations of early-pregnancy body mass index (BMI), body fat percentage, and comprehensive indexes with the risk of macrosomia under the updated international obesity definition.

The study was part of the Peking University-Weifang Birth Cohort. Between March 2024 and February 2025, 650 pregnant women who had registered, undergone physical examinations during early pregnancy (6 weeks to 13 weeks and 6 days of gestation), and subsequently delivered before August 1, 2025 at Weifang Maternal and Child Health Hospital were recruited. Researchers collected basic demographic information and calculated BMI based on on-site measurements of body height and body weight during early pregnancy. Body fat percentage was assessed via bioelectrical impedance analysis (BIA) and delivery data, including gestational age, fetal sex, and birth weight, were obtained during childbirth. The obesity of mothers in early pregnancy was determined by three methods: BMI, body fat percentage, and new international definition of obesity, and the association between obesity in early pregnancy and macrosomia was analyzed by multivariate logistic regression and trend test.

Among the 650 participants, 26.31% were overweight and 14.00% were obese according to BMI criteria, and 66.46% had excessive body fat. The incidence of macrosomia was 8.62%. Compared with normal BMI, overweight did not have a significant association with macrosomia (P = 0.079), whereas obese pregnant women had a 4.155-fold increased risk of delivering macrosomic infants (OR = 5.155, 95%CI: 2.451–10.843). Compared with women with normal body fat percentage, those with excessive body fat had a 1.546-fold increased risk of delivering macrosomic infants (OR = 2.546, 95%CI: 1.243–5.215). Compared with the pregnant women with both normal BMI and normal body fat, those with BMI indicating overweight combined with excessive body fat had a 1.318-fold increased risk (OR = 2.318, 95%CI: 1.006–5.338), and those with BMI indicating obesity combined with excessive body fat had a 5.437-fold increased risk (OR = 6.437, 95%CI: 2.670–15.516). An increasing trend in the risk of macrosomia with increases in early-pregnancy BMI and body fat percentage was identified (P < 0.05).

According to the new international definition of obesity that combines BMI and body fat percentage, our analysis shows a strong association between obesity in early pregnancy and macrosomia. This finding supports early prevention strategies targeting pregnant women with BMI indicating normal weight or overweight and excessive body fat.

To analyze the long-term trends, growth rates, and population disparities of overweight and obesity among Chinese adults from 1982 to 2015, thereby providing evidence for targeted prevention and control.

This study used data from the national nutrition surveys and health monitoring conducted in 1982, 1992, 2002, 2012, and 2015. The weighted prevalence of overweight and obesity was calculated. Long-term trends were analyzed by inverse variance-weighted linear regression for prediction, and the geometric growth model was employed to calculate the compound annual growth rates (CAGRs) in different periods.

From 1982 to 2015, the prevalence of overweight among Chinese adults increased from 11.0% to 33.3%, while that of obesity rose from 1.9% to 14.1%. Projections indicated these figures would reach 43.2% and 17.3%, respectively, in 2030. The increasing trends in both overweight and obesity prevalence show significant temporal fluctuations and population disparities: The CAGRs for both overweight and obesity decelerated during 2002–2012 (2.1% and 4.8%, respectively) but rebounded in 2012–2015 (3.3% and 7.9%, respectively). During 1982–2015, the CAGRs for both overweight and obesity were consistently higher in men than in women, with the disparity being most pronounced during 2012–2015 (the CAGR of obesity reached 10.5% in men versus 5.4% in women). The 45–59 age group consistently had the highest prevalence of overweight, and it surpassed the ≥60 age group to become the group with the highest obesity prevalence (40.3% for overweight and 16.2% for obesity in 2015) after 2002. The 18–44 age group, despite its currently lower prevalence, exhibited the highest CAGRs for both overweight and obesity across most periods, particularly surging to the top during 2012–2015 (CAGR: 4.0% for overweight and 10.2% for obesity). The western region emerged as a new growth hotspot, with CAGRs for overweight and obesity soaring to 8.0% and 13.4%, respectively, during 2012–2015.

The epidemic of overweight and obesity among Chinese adults continues to worsen. The growth pattern has shifted from a generalized increase to a structural shift driven by gender, age, and geographical factors.

To investigate body mass index (BMI) level of older adults aged 80 years and above in China under the new BMI recommendation standard and analyze the distribution characteristics of people with different BMI levels.

A total of 3 262 older adults of advanced ages from the China Nutrition and Health Surveillance (2015– 2017) were included. The appropriate BMI level of them was determined by the latest The Appropriate Range of Body Mass Index and Body Weight Management Standards for the Oldest Old published in 2025. The results were weighted and adjusted by the sixth census data of the National Bureau of Statistics. The Rao-Scott chi-square test based on complex sampling design correction was performed to analyze the distribution characteristics of BMI among the older adults of advanced ages.

The weighted mean BMI of the older adults aged 80 years and above in China was (23.5±0.2) kg/m² in urban areas and (22.4±0.2) kg/m² in rural areas in 2015–2017. The overall distribution trends of BMI among the older adults of advanced ages were similar in urban and rural areas in China, while the BMI level in rural areas was slightly lower than that in urban areas (F = 20.94, P < 0.01). Under the new standard, 44.6% of the older adults of advanced ages had a BMI in the appropriate range, and 43.0% had a BMI below the appropriate range. The proportions of the older adults of advanced ages living in rural areas (65.3%) or in the central and western China (34.4% and 25.0%), with primary school education or below (89.8%), and with lower per capita annual dietary expenditure (23.0%) who had BMI below the appropriate range were higher (P < 0.01).

Under the new appropriate BMI range standard, the BMI of older adults aged 80 or above in China is at a medium to low level, suggesting that the current nutritional problems of this population in China are still dominated by undernutrition. Understanding the BMI level and distribution characteristics of this population under the new standard can provide new data support for the health management of key populations.

To develop a weight management knowledge assessment scale for primary and secondary school students and evaluate its reliability and validity.

Literature review and Delphi expert consultation (2 rounds) were used to form the initial weight management knowledge assessment scale for primary and secondary school students. A total of 2 611 students from the third grade of primary school to the third grade of senior high school were selected through the convenient sampling method from primary and secondary schools in Tianjin city, Jiangsu province, Hebei province, Hubei province, Sichuan province, and Ningxia Hui Autonomous Region to conduct a formal survey of their weight management knowledge in April to May 2025. The critical ratio method, discrete trend method, factor analysis method, and correlation coefficient method were employed to screen the scale items. The Cronbach′s α coefficient and intra-class correlation coefficient (ICC) were adopted to evaluate the reliability of the scale. The validity of the scale was evaluated based on the item-level content validity index (I-CVI), scale-level content validity index (S-CVI), exploratory factor analysis, intrinsic correlation test, average variance extracted (AVE), composite reliability (CR), factor AVE square root, and comparison of correlation coefficients between this factor and other factors.

Through exploratory factor analysis, the weight management knowledge assessment scale for primary and secondary school students was determined to include 40 items in 8 dimensions: preventive cognition, lifelong management, monitoring and evaluation, dietary nutrition, reasonable exercise, sleep psychology, scientific weight loss, and family action, which showed a cumulative variance contribution rate of 76.342%. The Cronbach′s α coefficient of the total scale was 0.825, and that of each subscale was within the range of 0.801–0.896. The ICC was 0.833, and the ICC correlation coefficients varied in the range of 0.811–0.882. The I-CVI of the scale items and the S-CVI were 0.851–1.000 and 0.872, respectively. The results of confirmatory factor analysis showed that the correlation coefficients of the eight common factors—prevention cognition, lifelong management, monitoring and evaluation, dietary nutrition, reasonable exercise, sleep psychology, scientific weight loss, and family action—with the scale were 0.804, 0.811, 0.768, 0.702, 0.811, 0.739, 0.714, and 0.775 (all P<0.01), and the model fit well (χ² = 2 681.847, CFI = 0.901, TLI = 0.891, GFI = 0.869, IFI = 0.903, NFI = 0.882, RMSEA = 0.071). The AVE and CR were in the ranges of 0.532–0.721 and 0.735–0.796, respectively. The dimensional correlation tests of the scale all met the standard and were less than the square root of AVE, and the scale had good validity.

The weight management knowledge assessment scale for primary and secondary school students encompasses preventive cognition, lifelong management, monitoring and evaluation, dietary nutrition, reasonable exercise, sleep psychology, scientific weight loss, and family action, demonstrating good reliability and validity. It can be used to measure the weight management knowledge of primary and secondary school students in China.

To investigate the association between dietary patterns and obesity among adult residents in rural Hebei province, providing a theoretical foundation for formulating dietary interventions tailored to reducing the obesity rate in this population.

The data were obtained from the Nutrition and Health Status Surveillance of Chinese Residents in 2022, including food frequency, personal information, health records, and physical examination results of permanent rural residents aged ≥ 18 years in Hebei province. Dietary patterns were identified through factor analysis. Multivariate logistic regression models were employed to examine the relationship between dietary patterns and the risk of obesity in rural adults.

Among the 2 479 rural residents aged ≥ 18 years included in the study, the prevalence rate of obesity was 25.78%. The obesity rate was higher in non-smokers (26.74%) than in smokers (22.20%). Additionally, the obesity rate was higher in the populations with hypertension (34.16%), diabetes (38.60%), and dyslipidemia (32.74%) than in non-diseased populations. Four distinct dietary patterns were extracted via factor analysis as the animal protein-snack pattern, vegetable-fruit pattern, staple food pattern, and pasta-alcohol pattern, with a cumulative variance contribution rate of 38.77%. Logistic regression analysis indicated that after adjusting for confounding factors, individuals in the high-intake group of animal protein-snack pattern had higher risk of obesity than those in the low-intake group (Q3 high group OR = 1.491, 95%CI: 1.177–1.889, P = 0.001).

Dietary patterns are associated with obesity among rural adult residents in Hebei province, and a diet rich in animal protein-snack may elevate the risk of obesity.

To comprehensively assess the establishment and service provision of weight management clinics in healthcare institutions in Shenzhen city, Guangdong province, thus providing robust evidence to support the standardized and scientific development of weight management services in China.

In June 2025, a census survey was conducted among 62 secondary- and tertiary-level medical institutions (STLMIs) and 734 community health service organizations (CHSOs) in Shenzhen. A structured questionnaire was employed to investigate the weight management clinics in terms of establishment, service capacity, equipment configuration, extended services, participation in professional skills training, and existing problems.

The establishment rates of weight management clinics were 83.87% in STLMIs and 11.58% in CHSOs, being higher in STLMIs than in CHSOs (χ² = 209.68, P < 0.001). In terms of service capacity, STLMIs demonstrated generally strong capabilities in weight management clinics, except for bariatric and metabolic surgery. CHSOs exhibited satisfactory basic service capacity but limited specialized intervention capabilities, with significantly weaker overall capacity than STLMIs. For services targeting children and adolescents as well as pregnant and postpartum women, the proportion of CHSOs with corresponding service capacity was lower than that of STLMIs (all P < 0.01). Regarding equipment configuration, both STLMIs and CHSOs reported over 80% availability of basic examination and assessment equipment (excluding body fat scales and body composition analyzers), with no statistically significant differences (P > 0.05). However, STLMIs showed higher availability of body fat scales, body composition analyzers, and metabolic assessment equipment than CHSOs (all P < 0.01). In terms of extended services, the proportions of STLMIs conducting weight management-related skills training and providing school-based health education and free medical consultations were 50.00% and 40.38%, respectively, both higher than those of CHSOs (17.65% and 21.18%, respectively; both P < 0.05). With respect to professional skills training, the proportions of STLMIs receiving training in endocrine and metabolic diseases, nutrition guidance, exercise guidance, and psychological and behavioral interventions were 80.77%, 76.92%, 78.85%, and 59.62%, respectively, all higher than those of CHSOs (51.76%, 48.24%, 52.94%, and 32.94%, respectively; all P < 0.01). The major problems reported by STLMIs included information systems failing to meet work demands, insufficient publicity coupled with low outpatient volume, and lack of effective incentive mechanisms. CHSOs mainly reported inadequate equipment and facilities, information systems failing to meet work demands, and limited professional skills among healthcare staff.

The overall establishment of weight management clinics in healthcare institutions in Shenzhen is relatively satisfactory, while substantial room for improvement remains in CHSOs.

To evaluate the current diagnosis and treatment capacity of primary healthcare institutions in Beijing for weight management in patients with multimorbidity and identify key problems, thus providing evidence for improving primary care services.

From October to November 2025, a multi-stage random sampling method was employed to select 60 primary healthcare institutions in Beijing, from which 71 general practitioners, 69 pharmacists, and 131 patients with multimorbidity were surveyed. Four self-developed questionnaires were administered to institutions, general practitioners, pharmacists, and patients. Descriptive analysis, content analysis, and subject framework analysis were conducted.

Only 36.67% of the institutions had established weight management clinics, and specialized equipment and multidisciplinary teams were generally insufficient. The availability rate of weight-loss drugs was 71.67%. Less than 40% of general practitioners were proficient in exercise/diet planning, and only 9.86% could independently develop weight-loss plans. A total of 34.35% of patients reported insufficient follow-up on weight management. Family doctor contract rates were low, and referral procedures and criteria remained unclear.

The capacity of primary healthcare institutions in Beijing for weight management in patients with multimorbidity remains notably weak. It is recommended that comprehensive measures should be implemented in domains such as guideline development, resource allocation, and capacity training to enhance weight management and chronic disease prevention and control at primary healthcare institutions.

To explore the relationship between vegetable and fruit intake and sleep duration among Chinese adults aged over 80 years, thereby providing a scientific basis for improving sleep quality in this population.

Multistage stratified cluster random sampling was conducted for data from the China Nutrition and Health Surveillance (2015–2017). A total of 2319 elderly participants from 31 provinces (autonomous regions, municipalities directly under the Central Government) in China were selected to complete a questionnaire survey, physical measurements, and laboratory tests. The average daily intake of vegetables, fruits, and total vegetable and fruit intake was investigated, and the population was divided into quintiles in ascending order. Those with the daily sleep duration of 7–9 h were defined as the healthy sleep duration group, and those with the daily sleep duration of < 7 h or > 9 h were defined as the unhealthy sleep duration group. Multivariate unconditional logistic regression was adopted to explore the association between the two. Restricted cubic spline (RCS) analysis was performed to explore the dose-response relationship between fruit and vegetable intake and unhealthy sleep duration.

Among the 2319 elderly participants in China, 52.13% had unhealthy sleep duration. Different sleep duration groups varied in sex (χ² = 6.672), place of residence (χ² = 8.422), educational background (χ² = 15.573), per capita annual household income (χ² = 23.021), marital status (χ² = 8.894), physical activity level (χ² = 9.873), and sedentary behavior distribution (χ² = 6.631) (all P < 0.05). In addition, there were also differences in age (t = 2.220), vegetable intake (t = 3.420), fruit intake (t = 3.470), and total vegetable and fruit intake (t = 4.190) among different groups (all P < 0.05). Multivariate unconditional logistic regression showed that after adjusting for age, sex, BMI, place of residence, educational background, per capita annual household income, marital status, number of cohabitants, current smoking, current alcohol consumption, physical activity level, sedentary behavior, participation in health checkups within the past year, and the prevalence of hypertension, diabetes, and dyslipidemia, vegetable intake, fruit intake, and total vegetable and fruit intake were negatively associated with the risk of unhealthy sleep duration. Compared with the lowest group, the highest group showed reductions of 26% (vegetable intake: OR = 0.74, 95%CI: 0.56–0.97), 28% (fruit intake: OR = 0.72, 95%CI: 0.55–0.95), and 29% (total fruit and vegetable intake: OR = 0.71, 95%CI: 0.54–0.94) in the risk of unhealthy sleep duration (all P_trend < 0.05). RCS analysis revealed that both fruit intake and total vegetable and fruit intake had significantly negatively linearly associations with unhealthy sleep duration (both P_{non-linearity} ≥ 0.05).

The vegetable intake, fruit intake, and total vegetable and fruit intake are negatively correlated with the risk of unhealthy sleep duration in Chinese adults aged 80 and above. The findings provide a potential intervention target to promote healthy sleep duration in this population.

To explore the associations between insulin resistance surrogate indices and hyperuricemia among Chinese older adults aged over 80 years and evaluate the predictive performance of different indices for hyperuricemia, thus providing a scientific basis for the prevention and control of hyperuricemia in this population.

On the basis of the data from the China Nutrition and Health Surveillance (2015–2017), multistage stratified cluster random sampling was employed to select 2 667 participants aged over 80 years from 31 provinces (autonomous regions, municipalities) in China. A questionnaire survey, physical measurements, and laboratory tests were conducted. The triglyceride-glucose (TyG) index was combined with body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) to derive the TyG-BMI, TyG-WC, and TyG-WHtR indices, which, together with the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR), were used as insulin resistance surrogate indices. The participants were categorized by ascending quartiles. Hyperuricemia was defined as a serum uric acid concentration ≥ 420 μmol/L in men and ≥ 360 μmol/L in women. Multivariable unconditional logistic regression was adopted to explore the associations between insulin resistance surrogate indices and hyperuricemia. Receiver operating characteristic (ROC) curves were established to compare the predictive performance of different indices for hyperuricemia.

Among the 2 667 Chinese older adults, 23.24% had hyperuricemia, and the prevalence of hyperuricemia was statistically different among different groups of body mass index (BMI) (χ² = 38.167), marital status (χ² = 4.012), sleep duration (χ² = 6.452), hypertension (χ² = 12.320), diabetes (χ² = 4.922), and dyslipidemia (χ² = 38.541) (all P < 0.05). The results of multivariable unconditional logistic regression showed that after adjusting for age, sex, BMI, place of residence, educational background, marital status, annual household income per capita, current smoking, current drinking, physical activity level, sleep duration, and the prevalence of hypertension, diabetes, and dyslipidemia, each insulin resistance surrogate index was positively associated with the risk of hyperuricemia. Compared with the lowest group, the highest group of TyG (OR = 1.79, 95%CI: 1.30–2.45), TyG-BMI (OR = 2.41, 95%CI: 1.41–4.13), TyG-WC (OR = 1.84, 95%CI: 1.27–2.67), TyG-WHtR (OR = 1.99, 95%CI: 1.39–2.86), TG/HDL-C (OR = 1.81, 95%CI: 1.31–2.50), and MET-IR (OR = 2.20, 95%CI: 1.32–3.69) had a significantly higher risk of hyperuricemia. ROC analysis suggested that the TyG-WC index had the best predictive performance for the prevalence of hyperuricemia in this population.

TyG, TyG-BMI, TyG-WC, TyG-WHtR, TG/HDL-C, and METS-IR are independent risk factors for hyperuricemia in the Chinese older adults aged over 80 years. The TyG-WC index could be used as an elite predictor of hyperuricemia risk, providing a new target for the prevention and treatment of hyperuricemia in this population.