Background With China's socio-economic development, the dietary structure of Chinese residents has gradually shifted from a traditional Eastern pattern characterized by high carbohydrate intake to a relatively high-fat Western dietary model, alongside a growing burden of chronic diseases. However, dietary changes may vary across different occupational groups. Objective To analyze the long-term trends in dietary energy and three major macronutrient intake among various occupational groups aged 18-59 years in nine provinces of China from 1989 to 2018, providing a scientific basis for developing occupation-specific dietary intervention strategies. Methods Based on 11 waves of data (1989–2018) from the China Health and Nutrition Survey (CHNS), 57458 employed individuals aged 18-59 years were selected as observation subjects after applying inclusion and exclusion criteria. Joinpoint regression was used to analyze temporal trends by calculating the annual percentage change (APC) and average annual percentage change (AAPC) with 95% confidence intervals. The analysis covered the energy supply ratio from the three major macronutrients and the proportion of the participants within the acceptable macronutrient distribution ranges (AMDR) for the total occupational population and specific occupational group. Results From 1989 to 2018, the dietary structure of the occupational population in the nine provinces gradually Westernized. The carbohydrate energy supply ratio showed a decreasing trend (AAPC=−0.77%, 95%CI: −1.00%, −0.55%, P<0.05), while the fat energy supply ratio increased (AAPC=1.42%, 95%CI: 1.07%, 1.77%, P<0.05). The protein energy supply ratio remained largely unchanged (AAPC=−0.19%, 95%CI: −0.08%, 0.46%, P>0.05), and the total energy intake declined (AAPC=−0.62%, 95%CI: −0.94%, −0.30%, P<0.05). Among the occupational groups studied, white-collar workers were the first to show characteristics of dietary Westernization. Using the AMDR as the criterion, their average fat energy supply ratio first exceeded the AMDR upper limit (30%) in 1993, and their average carbohydrate energy supply ratio first fell below the AMDR lower limit (50%) in 2006, both time points being earlier than other occupational groups. Agricultural workers lagged in this transition (their average fat energy supply ratio first reached ≥30% in 2011), but their rate of increase in the fat energy supply ratio was the fastest among all occupational groups (AAPC=1.59%, 95%CI: 0.90%, 2.30%, P<0.05; P for trend comparison between groups<0.05). The other three occupational groups (blue-collar workers, service workers, and others) generally fell between these two extremes. Taking the fat energy supply ratio as an example, their AAPCs of increase were 1.02% (95%CI: 0.73%, 1.32%, P<0.05) for blue-collar workers, 0.85% (95%CI: 0.61%, 1.09%, P<0.05) for service workers, and 0.88% (95%CI: 0.58%, 1.17%, P<0.05) for others. Conclusion From 1989 to 2018, the macronutrient structure of the occupational population aged 18-59 years in nine China provinces is gradually Westernized. The energy supply ratios of carbohydrates and proteins primarily face issues of potential inadequacy, while the fat energy supply ratio is excessively high. Furthermore, the patterns of change vary among different occupational groups. It is recommended to propose personalized dietary advice tailored to specific occupations.

Background With China's socioeconomic development, significant lifestyle changes have occurred among occupational groups, leading to alterations in cardiovascular metabolic risk factors. However, few studies have examined the secular trends of these risk factors in China's working population. Objective To analyze the trends in cardiovascular metabolic risk factors among the occupational population in nine provinces of China from 2009 to 2018, and to explore the associations between different occupational types and these risk factors, along with their clustering patterns, thereby providing evidence for targeted interventions. Methods This study utilized data from the China Health and Nutrition Survey (CHNS) in 2009, 2015, and 2018. The dataset covered 13274 employed individuals aged 18-59 years. Only participants with complete blood test results and physical measurement data were included in the final analysis. The average annual percentage change (AAPC) in the positive rates of risk factors was calculated using Joinpoint regression to analyze temporal trends. Multinomial logistic regression and binary logistic regression models were employed to examine the cross-sectional associations between occupational types (categorized as white-collar workers, agricultural workers, blue-collar workers, service workers, and others) and nine cardiovascular metabolic risk factors and their clustering (defined as having ≥2 risk factors) in 2018. Results A total of 8451 participants were included. From 2009 to 2018, significant increasing trends (AAPC>0, P<0.05) were observed for overweight, obesity, central obesity, borderline elevated triglycerides (TG), borderline elevated to elevated total cholesterol (TC), borderline elevated low-density lipoprotein cholesterol (LDL-C), elevated blood pressure and hypertension, diabetes. The most rapid increases were found for obesity (AAPC=6.07%, 95%CI: 3.42%, 8.88%), hypertension (AAPC=4.10%, 95%CI: 0.62%, 7.77%), and central obesity (AAPC=3.27%, 95%CI: 1.24%, 5.36%). The clustering rate of risk factors increased from 62.3% in 2009 to 73.2% in 2018 (AAPC=1.87%, 95%CI: 1.02%, 2.73%). The cross-sectional analysis in 2018, after adjusting for confounders, showed that compared with white-collar workers, blue-collar workers had a significantly lower risk of overweight (OR=0.67, 95%CI: 0.48, 0.95), central obesity (OR=0.65, 95%CI: 0.45, 0.92), and borderline high TG (OR=0.54, 95%CI: 0.35, 0.82). In contrast, agricultural workers had a higher risk of hypertension (OR=1.76, 95%CI: 1.14, 2.72). Conclusion Between 2009 and 2015, the burden of most cardiometabolic risk factors increases significantly among the Chinese occupational population, with the rate of increase slowing by 2018. Risks vary across occupational types, among which blue- collar workers report lower target outcomes. Targeted interventions focusing on the rapidly increasing risk factors and high-risk occupational groups are recommended.

Background The global prevalence of obesity is on the rise and is closely associated with various chronic non-communicable diseases such as cardiovascular diseases and diabetes. There is a relative lack of long-term dynamic studies on compound obesity among occupational populations. Objective To explore the changing trends of compound obesity among different occupational groups aged 18–59 years in nine provinces (autonomous regions, municipalities) of China from 1993 to 2018, and to provide a scientific basis for formulating targeted weight management strategies for occupational populations. Methods A total of 34519 employed adults aged 18–59 years from nine waves of the China Health and Nutrition Survey in1993, 1997, 2000, 2004, 2006, 2009, 2011, 2015, and 2018 were included. Obesity types were determined according to the Chinese Adult Weight Management Guidelines. The Joinpoint regression model was used to calculate the average annual percentage change (AAPC) and annual percentage change (APC) of compound obesity rates. Results From 1993 to 2018, the age-standardized compound obesity rate among the occupational population aged 18–59 years showed an upward trend (AAPC=6.24%, 95%CI: 5.09%, 7.41%, P<0.05). The AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, other occupational groups, service workers, and white-collar workers were 9.55% (7.51%, 11.64%), 6.18% (4.70%, 7.69%), 5.53% (2.27%, 8.90%), 4.07% (2.40%, 5.77%), and 3.89% (2.16%, 5.65%), respectively, with statistically significant differences (P<0.05). Among males, the AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, other occupational groups, service workers, and white-collar workers were 11.52% (7.71%, 15.47%), 7.28% (6.18%, 8.40%), 5.92% (2.28%, 9.69%), 5.56% (2.11%, 9.12%), and 4.22% (2.33%, 6.15%), respectively, with statistically significant differences (P<0.05). Among females, the AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, and white-collar workers were 7.45% (6.22%, 8.69%), 3.72% (0.84%, 6.67%), and 2.41% (0.17%, 4.70%), respectively, with statistically significant differences (P<0.05). A turning point was observed in the compound obesity rate among female white-collar workers in 2006, with an APC (95%CI) of 9.69% (5.24%, 14.33%) from 2006 to 2008, showing a statistically significant difference (P<0.05), while no significant trend was found from 1993 to 2006 (P>0.05). No significant trends were observed in the age-standardized compound obesity rates among females in other occupational groups and service workers (P>0.05). Conclusion The compound obesity rate among China's occupational population is increasing rapidly, with the growth rate among agricultural workers being particularly prominent. In 2018, male white-collar workers and female agricultural workers exhibit relatively high compound obesity rates, warranting focused attention. Although the overall growth rate among service workers is slower, the expanding workforce in this sector indicates that obesity remains a serious issue. Targeted occupational health and weight management interventions are needed in the future.

Background With rising obesity rates and earlier hypertension onset among occupational populations, there is an urgent need to elucidate the long-term cardiovascular impacts of dynamic body weight patterns. Current evidence lacks trajectory modeling studies examining occupation-specific prevention strategies. Objective To investigate the association between long-term body mass index (BMI) trajectories and incident hypertension risk in Chinese working adults, and to examine occupation-specific heterogeneity in this relationship. Methods A dynamic sub-cohort of 4 413 occupational participants was constructed from ten survey waves (1991–2018) of the China Health and Nutrition Survey (CHNS). Eligible individuals had valid key BMI records at three or more independent follow-ups before the outcome event; the individual baseline was set as the year of their first participation in the survey. Group-based trajectory modeling (GBTM) was used to identify BMI change patterns. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% confidence interval (CI) for hypertension incidence across trajectory groups, with stratified analysis by occupational categories. Results Among 4413 occupational participants, 1441 incident hypertension cases were reported during the follow-up window. Three long-term BMI trajectories were identified: low-stable, moderate-slowly rising, and high-rising. In Model 3 with all selected confounders adjusted, compared with the low-stable group, the moderate-slowly rising group showed a significantly higher risk of incident hypertension (HR=1.28, 95%CI: 1.12, 1.45; P < 0.001), as did the high-increasing group (HR=1.80, 95%CI: 1.45, 2.23; P < 0.001). The stratified analyses revealed occupational differences in the association. Among agricultural workers, the moderate-slowly rising group (HR=1.35, 95%CI: 1.15, 1.57) and the high-rising group (HR=2.00, 95%CI: 1.50, 2.66) both exhibited significantly increased risks of hypertension (P<0.001). Conversely, among white-collar workers, an increased risk of hypertension was observed only in the high-rising group (HR=1.97, 95%CI: 1.23, 3.17; P<0.05). Conclusion Rapid BMI escalation constitutes a significant risk factor for incident hypertension in occupational populations. Targeted long-term weight monitoring and tailored interventions are recommended for high-risk occupations.

Objective:Analyze the mediating and moderating effects of the relationship between food intake and blood glucose levels.Methods:This study uses data from the China Health and Nutrition Survey project in the survey 2018, involving 11 043 adults aged 18 years or older, who have complete dietary data, waist circumference (WC), glycated hemoglobin A1c (HbA1c) indicators, and other key variables. Food consumption data was gathered via three consecutive 24-hour dietary recalls and weighing accounting method, which included two weekdays and one weekend day. The average daily intake of various foods and total energy intake were calculated. The mediation effect and moderation effect analysis were conducted using simple mediation models, direct moderation effect models, and moderated mediation analysis theoretical models. The confidence interval method (bootstrap method) was performed for testing and analysis.Results:A total of 4 951 males and 6 092 females were included in the stratified analysis by gender. The mediating effects on the rice, wheat, and red meat→WC→HbA1c were all statistically significant in males. The standardized coefficients were -0.009 ( P<0.001), 0.013 ( P<0.001), and -0.005 ( P=0.008), respectively. In females, the mediating effect on the wheat→WC→HbA1c was statistically significant, and the standardized coefficient was 0.017 ( P<0.001); the impact of red meat intake on HbA1c is negatively regulated by the intake of dark vegetables, with a direct moderating effect; the standardized coefficient of the interaction term between red meat and dark vegetables was -0.024 ( P=0.008). Dark vegetables have a moderated mediator on the pathway from rice to WC and HbA1c ( a3b1=-0.003, P=0.041) in males. The mediating effect of WC is negatively regulated by the intake of dark vegetables (mediation effect difference U1/-1=-0.006, P=0.048). Dark vegetables showed a moderated mediator on the pathway from wheat to WC and HbA1c ( a3b1=-0.004, P=0.045) in females. The mediating effect of WC is negatively regulated by the intake of dark vegetables (mediation effect difference U1/-1=-0.009, P=0.049). Conclusions:Changes in WC indicators caused by rice, wheat, and red meat intake. WC could mediate between rice, wheat, red meat, and HbA1c. Dark vegetables directly or indirectly regulate HbA1c levels by interacting with rice, wheat, and red meat.

Background Multimorbidity imposes a heavy burden on individuals, families, and society. There are relatively few studies exploring patterns of multimorbidity among middle-aged adults in China. Objective To explore the current status of multimorbidity, associated risk factors, and multimorbidity patterns among adults aged 45-64 years in China, so as to provide a scientific basis to prevent and control multimorbidity in China. Methods A total of 5494 adults aged 45-64 years from the Chinese Health and Nutrition Survey (CHNS) in 2018 were selected. Of these, 2494 (45.39%) were men and 3000 (54.61%) were women. The nine diseases included were hypertension, diabetes, dyslipidaemia, obesity, mild cognitive impairment (MCI), myocardial infarction, stroke, asthma, and tumor. The prevalence of each disease or multimorbidity was expressed as N (%). Comparisons of multimorbidity prevalence between different groups were performed using the χ² test or Cochran-Armitage trend test. Association rule with the Apriori algorithm was used to explore the pattern of multimorbidity, with parameters set at a minimum conditional support of 3.00%, a minimum rule confidence of 50.00%, and a lift of >1.20. Logistic regression was used to evaluate the associations between selected risk factors and multimorbidity. Results In 2018, 37.44% of participants reported multimorbidity in 15 provinces of China. The prevalence of diseases in descending order was dyslipidaemia (39.99%), hypertension (39.48%), obesity (16.42%), MCI (14.47%), diabetes (14.16%), tumor (1.09%), stroke (1.04%), myocardial infarction (0.71%), and asthma (0.64%). A total of seven multimorbidity patterns were identified in this group. Obesity paired with hypertension, and diabetes paired with dyslipidemia were the two major patterns of multimorbidity in the general population and age or sex subgroups. The multimorbidity patterns of different populations were concentrated in the combination of obesity, hypertension, diabetes, and dyslipidemia. The risk of multimorbidity was lower in females than in males (OR=0.85, 95%CI: 0.75, 0.97). The multimorbidity risk was 1.56 times higher in the 55-64 years group than in the 45-54 years group (OR=1.56, 95%CI: 1.40, 1.75). Drinking in the past year increased the risk of multimorbidity by 25% (OR=1.25, 95%CI: 1.08, 1.45) compared to no alcohol comsumption in the past year. High and medium levels of physical activity were associated with a decreased OR (high: OR=0.74, 95%CI: 0.65, 0.85; medium: OR=0.81, 95%CI: 0.70, 0.93) with low level of physical activity as reference. Conclusion In 2018, there was a high prevalence rate of multimorbidity among middle-aged adults in China. The main multimorbidity patterns were obesity-hypertension and diabetes-dyslipidemia. Surveillance and interventions should be strengthened particularly for men, individuals with alcohol consumption or insufficient physical activity, and those with major multimorbidity patterns.

Objective:To analyze probability of prodromal Parkinson's disease (pPD) and assess the association between global cognitive function and cognitive domain function and probability of pPD in ≥55 years old middle-aged and elderly people in Hebei, Zhejiang, Shaanxi and Hunan Provinces in China.Methods:Data were collected from dataset of the Community-based Cohort Study on Nervous System Disease 2020. We selected 4 634 Alzheimer disease and Parkinson's disease free persons aged ≥55 years with completed information on demographics, disease history, cognitive test, and risk factors of Parkinson's disease for this study. Cognitive function was assessed using Montreal Cognitive Assessment Scale (Chinese version). Calculation of probability of pPD and assessment of possible/probable pPD were performed according to the criteria published by the International Parkinson and Movement Disorder Society. Multivariate linear regression model was used to analyze the association between cognitive function and probability of pPD.Results:The M ( Q1, Q3) of global cognitive function and cognitive domains in terms of memory, execution, visuospatial function, language, attention and orientation were 25 (20, 30), 13 (11, 15), 10 (7, 12), 6 (4, 7), 5 (4, 6), 15 (12, 18) and 6 (6, 6) points, respectively. The M( Q1, Q3) of probability of pPD was 0.42% (0.80%, 1.73%), and the proportion of the study subjects with possible/probable pPD was 0.4%. Differences in the distribution of probability of pPD were significant among groups by total cognitive score quartiles ( P<0.001), and the difference in proportions of study subjects with possible/probable pPD was significant and showed decline trend ( P=0.001). After adjusted for confounders, the results of multivariate linear regression analyses showed that probability of pPD in the Q2, Q3 and Q4 group decreased by 23.4%, 31.2% and 20.1% compared with Q1 group, and corresponding β values were 0.766 (95% CI: 0.702-0.836), 0.688 (95% CI: 0.631-0.751) and 0.799 (95% CI: 0.730-0.875), respectively, the trend was significant ( P<0.001). Higher index scores of execution, visuospatial function, language, attention and orientation were highly related to lower probability of pPD ( P<0.001). Conclusion:Declines in global cognitive function and cognitive domains of execution, visuospatial function, language, attention and orientation might increase the probability of pPD in middle-aged and elderly people, suggesting the importance of cognitive intervention in early stage for pPD prevention.

Background China is witnessing an accelerated aging process and an increasingly serious situation of Parkinson's disease. Research on the pre-disease stage and its related influencing factors has gained more and more attention. Objective To analyze the current situation of prodromal Parkinson's disease (pPD) of people aged 55 years and above in four provinces of China, and to explore its influencing demographic and socio-economic characteristics. Methods Using the data of Community-based Cohort Study on Nervous System Disease in 2020, a total of 10724 participants with complete data on demographic and socio-economic factors and risk factors on Parkinson's disease were selected. Based on the criteria recommended by the International Parkinson and Movement Disorder Society (MDS), we evaluated risk level (i.e., post-test probability) of pPd, prevalence of possible or probable pPD, and number of pPD-related risk/prodromal markers in the participants. Multiple linear regression and multiple logistic regression models were used to analyze the influencing socio-demographic factors of risk level of pPd and prevalence of possible or probable pPD, and Poisson regression and multinomial logit regression models were used to analyze the influencing socio-demographic factors of the number of pPD-related risk/prodromal markers in the total sample, men, and women, respectively. Results The median (P₂₅, P₇₅) of post-test probability of pPD in 2020 was 0.78% (0.42%, 1.66%), the prevalence rate of possible or probable pPD was 0.34%, and 69.03% of the participants reported 3-5 pPD-related risk/prodromal markers. The post-test probabilities of men, those with older age, lower education level, per capita monthly household income < 1000 yuan, urban residency, or without active employment were higher (P<0.05). Men and being aged ≥ 75 years had a higher prevalence of possible or probable pPD (P<0.05). The OR of possible or probable pPD was 8.404 (95%CI: 2.839−24.879) in subjects aged ≥ 75 years versus those aged 55−64 years. Males, those without active employment, being less educated, with older age, and urban residents were more likely to report pPD-related risk/prodromal markers than those of the opposite groups (P<0.05). Conclusion Men, subjects aged ≥75 years, those with lower education level, urban residents, and those without active employment have higher risk levels of pPD and are more likely to report pPD-related risk/prodromal markers among people aged 55 years and above in the four provinces of China, poor economic situation is also associated with higher risk levels of pPD.

Background Gastrointestinal microbiota plays an important role in the development of Parkinson's disease (PD), and dietary factors have a great impact on intestinal micro ecology. At present, few studies focus on red meat and PD, especially prodromal PD (pPD). Objective To understand the relationships of the intake of red meat and processed meat products with pPD and the number of risk/prodromal markers, and to explore the association of dietary factors with pPD. Methods Based on the data of Community-based Cohort Study on Nervous System Disease in 2018 and 2020, adults aged 55 years and older with complete demographic information, dietary survey information, and information on risk factors related to PD were selected from four provinces of China. After excluding those reporting abnormal total energy intake or those reporting alcohol drinking or abused drugs for a long period of time, and confirmed mental diseases with prescribed drugs, a total of 10003 subjects were included. Food frequency questionnaire was used to calculate the intake of red meat and processed meat products. The pPD-related risk/prodromal markers were selected following the International Parkinson and Movement Disorder Society criteria for pPD, and the risk level and the number of markers of pPD were then calculated. The relationship between the intake of red meat and processed meat and the risk level of pPD was analyzed by multiple linear regression. The relationship between the intake of red meat and processed meat and the pPD marker number groups was analyzed by multinomial logit regression model. Results In 2018, the intake of red meat and processed meat was 28.57 g·d⁻¹ in the target population. In 2020, the median of the number of risk/prodromal markers was 3, and the median M (P₂₅, P₇₅) of the posterior probability of pPD was 0.74% (0.42%, 1.49%). The multiple linear regression analysis showed that the higher the intake of red meat and processed meat, the higher the risk level of pPD in follow-up (b=0.021, P<0.05). The multiple logit regression model showed that compared with the lowest quartile (Q1), the highest quartile (Q4) group of red meat and processed meat intake were more likely reporting 3−5 risk/prodromal markers than ≤ 2 risk/prodromal markers (OR=1.185, 95%CI: 1.015−1.382). Conclusion The intake level of red meat and processed meat is related to the risk level of pPD, and a higher intake of red meat and processed meat may be a potential risk factor of pPD.

Background It has been reported that a high intake of dairy products might be associated with an increased risk of Parkinson's disease (PD) in foreign studies, but no such study has yet been conducted on prodromal Parkinson's disease (pPD) and the Chinese population. Objective To investigate the prospective relationship between the intake of dairy products and pPD among people aged 55 and above in four provinces of China. Methods The research data were obtained from the baseline 2018 and follow-up 2020 surveys of Community-based Cohort Study on Nervous System Disease. A total of 9984 residents were selected who participated in both waves of surveys and had complete data on demographics, dietary products intake, and risk factors for PD. We evaluated the risk level and the numbers of related risk/prodromal markers of pPD in the participants based on a criteria recommended by the International Parkinson and Movement Disorder Society (MDS). Food Frequency Questionnaire was used to obtain food consumption data in the past 12 months, and the intake of dairy products was calculated and divided into non-consumption and tertiles of consumption (T1, T2, and T3 from low to high). Multiple linear regression was used to analyze the association between baseline dairy intake and risk level of follow-up pPD. Poisson regression and multinomial logit regression models were used to analyze the relationship of baseline dairy products and the number of risk/prodromal markers of follow-up pPD in the population, and multiple logistic regression was used to analyze each risk/prodromal marker of follow-up pPD according to baseline levels of dairy products intake. Results The percentage of residents without dairy products consumption was 58.02% in 2018, and the dairy products intakes were relatively high among residents being female, aged 55 to 74 years, with an education level of middle school and above, with a per capita monthly household income ≥ 1000 yuan, living in urban areas, and without active employment (P<0.05). The median risk level of pPD was 0.74% in 2020, and the proportion of residents with 3 to 5 markers was 66.74%. The multiple linear regression analysis results suggested no association between baseline dairy intake and follow-up risk level of pPD. The Poisson regression model showed that the high dairy products intake group at baseline (T3, median=250.00 g·d⁻¹) was found to be 1.159 (95%CI: 1.065~1.261, P_trend<0.001) times more likely to have the risk/prodromal markers of pPD at follow-up than non-consumers. When the number of markers was grouped, no statistically significant association was found by multiple logistic regression analysis. Conclusion Although high dairy products intake levels might be associated with pPD risk/prodromal markers among people aged 55 and above in four provinces of China, no direct association is found between dairy products intake and pPD risk levels in this study.