OBJECTIVE: To explore the dose-effect relationship between the number of acupuncture sessions and the efficacy for cervical vertigo (CV). METHODS: Literature regarding randomized controlled trials (RCTs) of acupuncture for CV was retrieved from CNKI, Wanfang, VIP, Web of Science, and PubMed databases from inception to June 28th, 2024. Studies were included if patients were treated solely with acupuncture and the core prescription included Baihui (GV20)-Fengchi (GB20)-neck-jiaji (EX-B2). Outcomes included the evaluation scale for cervical vertigo symptoms and function (ESCV) score and the mean blood flow velocity of vertebrobasilar arteries. The Cochrane risk of bias assessment tool 2.0 was used to evaluate study quality. Dose-effect Meta-regression analysis was performed using the robust-error Meta-regression (REMR) method in Stata 17.0 software. RESULTS: Nineteen RCTs were included with a total of 747 patients in the experimental groups. After 10 sessions of acupuncture, the ESCV score increased to 20.29 (95% CI: 16.77, 23.80), with a pre-post ESCV difference of 4.60 (95% CI: 2.59, 6.60) and an improvement rate of 0.36 (95% CI: 0.26, 0.46). After 20 sessions of acupuncture, the ESCV score increased to 21.55 (95% CI: 18.87, 24.22), with a difference of 5.42 (95% CI: 3.87, 6.97) and an improvement rate of 0.39 (95% CI: 0.31, 0.48). After 10 sessions of acupuncture, the improvement rates for left vertebral artery (LVA), right vertebral artery (RVA), and basilar artery (BA) mean blood flow velocities were 0.08 (95% CI: 0.05, 0.12), 0.09 (95% CI: 0.05, 0.12), and 0.11 (95% CI: 0.06, 0.15), respectively. After 14 sessions of acupuncture, the improvement rates reached their peaks: LVA [0.09 (95% CI: 0.06, 0.12)], RVA [0.10 (95% CI: 0.07, 0.13)], and BA [0.12 (95% CI: 0.07, 0.16)]. CONCLUSION A nonlinear dose-effect relationship existed between the number of acupuncture sessions and the efficacy for CV. Fourteen sessions were recommended as the optimal number of acupuncture treatments.
Humans ; Acupuncture Therapy ; Randomized Controlled Trials as Topic ; Vertigo/physiopathology* ; Treatment Outcome ; Acupuncture Points ; Regression Analysis ; Male ; Female

OBJECTIVES: To construct a Z-score regression model for coronary artery diameter based on echocardiographic data from children in Sichuan Province and to establish a Z-score calculation formula. METHODS: A total of 744 healthy children who underwent physical examinations at Sichuan Provincial People's Hospital from January 2020 to December 2022 were selected as the modeling group, while 251 children diagnosed with Kawasaki disease at the same hospital from January 2018 to December 2022 were selected as the validation group. Pearson correlation analysis was conducted to analyze the relationships between coronary artery diameter values and age, height, weight, and body surface area. A regression model was constructed using function transformation to identify the optimal regression model and establish the Z-score calculation formula, which was then validated. RESULTS: The Pearson correlation analysis showed that the correlation coefficients for the diameters of the left main coronary artery, left anterior descending artery, left circumflex artery, and right coronary artery with body surface area were 0.815, 0.793, 0.704, and 0.802, respectively (P<0.05). Among the constructed regression models, the power function regression model demonstrated the best performance and was therefore chosen as the optimal model for establishing the Z-score calculation formula. Based on this Z-score calculation formula, the detection rate of coronary artery lesions was found to be 21.5% (54/251), which was higher than the detection rate based on absolute values of coronary artery diameter. Notably, in the left anterior descending and left circumflex arteries, the detection rate of coronary artery lesions using this Z-score calculation formula was higher than that of previous classic Z-score calculation formulas. CONCLUSIONS The Z-score calculation formula established based on the power function regression model has a higher detection rate for coronary artery lesions, providing a strong reference for clinicians, particularly in assessing coronary artery lesions in children with Kawasaki disease.
Humans ; Male ; Female ; Child, Preschool ; Child ; Coronary Artery Disease/diagnostic imaging* ; Infant ; Mucocutaneous Lymph Node Syndrome ; Regression Analysis ; Coronary Vessels/diagnostic imaging* ; Echocardiography ; Adolescent

OBJECTIVES: To explore the risk factors for malnutrition in patients with ulcerative colitis complicated with pyoderma gangrenosum and establish a nutritional risk prediction model for these patients. METHODS: A total of 277 patients with ulcerative colitis complicated with pyoderma gangrenosum treated from 2019 to 2024 were divided into malnutrition group (n=185) and normal nutrition group (n=92) according to whether malnutrition occurred. The data of 25 potential related factors pertaining to general demography, living and eating habits, and disease-related data were compared between the two groups. Lasso regression was used to screen the risk factors, and a nomogram model was established based on the screened factors and its prediction performance was assessed. RESULTS: The patients in the malnutrition group and normal nutrition group showed significant differences in 21 factors including gender, age, education level, BMI, place of residence, course of disease, and SAS language score (P<0.05). Lasso regression analysis identified 6 factors associated with malnutrition in these patients, namely the duration of ulcerative colitis, activity of ulcerative colitis, duration of pyoderma gangrenosum, number of chronic diseases, SAS score, and sleep quality. The nomogram prediction model established based on these 6 factors had an AUC of 0.992 (95% CI: 0.984-1.000) for predicting malnutrition in these patients, and its application in 14 clinical cases achieved an accuracy rate of 100%. CONCLUSIONS The duration of ulcerative colitis, activity of colitis, duration of pyoderma gangrenosum, number of chronic diseases, anxiety, and sleep quality are closely related with malnutrition in patients with ulcerative colitis complicated by pyoderma gangrenosum, and the nomogram prediction model based on these factors can provide assistance for predicting malnutrition in these patients.
Humans ; Colitis, Ulcerative/complications* ; Malnutrition/etiology* ; Risk Factors ; Pyoderma Gangrenosum/complications* ; Female ; Male ; Adult ; Nomograms ; Middle Aged ; Nutritional Status ; Regression Analysis

Multicollinearity is an important issue affecting the results of regression analysis. LASSO developed in recent years has great advantages in selecting explanatory variables, processing high-dimensional data, and solving multicollinearity problems. This method adds a penalty term to the model estimation, which can compress the regression coefficients of some unnecessary variables to zero and then remove them from the model to achieve the purpose of variable screening. This paper focuses on the LASSO method and compares it with optimal subsets, ridge regression, adaptive LASSO, and elastic net results. It is found that both LASSO and adaptive LASSO have good performance in solving independent variable multicollinearity problems and enhancing model interpretation and prediction accuracy.
Humans ; Regression Analysis

OBJECTIVE: To describe the secular trends of age at menarche and age at natural menopause of women from a county of Shandong Province. METHODS: Based on the data of the Premarital Medical Examination and the Cervical Cancer and Breast Cancer Screening of the county, the secular trends of age at menarche in women born in 1951 to 1998 and age at menopause in women born in 1951 to 1975 were studied. Joinpoint regression was used to identify potential inflection points regarding the trend of age at menarche. Average hazard ratios (AHR) of early menopause among women born in different generations were estimated by performing multivariate weighted Cox regression. RESULTS: The average age at menarche was (16.43±1.89) years for women born in 1951 and (13.99±1.22) years for women born in 1998. The average age at menarche was lower for urban women than that for rural women, and the higher the education level, the lower the average age at menarche. Joinpoint regression analysis identified three inflection points: 1959, 1973 and 1993. The average age at menarche decreased annually by 0.03 (P < 0.001), 0.08 (P < 0.001), and 0.03 (P < 0.001) years respectively for women born during 1951-1959, 1960-1973, and 1974-1993, while it remained stable for those born during 1994-1998 (P=0.968). As for age at menopause, compared with women born during 1951-1960, those born during 1961-1965, 1966-1970 and 1971-1975 showed a gradual decrease in the risk of early menopause and a tendency to delay the age at menopause. The stratified analysis presented that the risk of early menopause gradually decreased and the age of menopause showed a significant delay among those with education level of junior high school and below, but this trend was not obvious among those with education level of senior high school and above, where the risk of early menopause decreased and then increased among those with education level of college and above, and the corresponding AHRs were 0.90 (0.66-1.22), 1.07 (0.79-1.44) and 1.14 (0.79-1.66). CONCLUSION The age at menarche for women born since 1951 gradually declined until 1994 and leveled off, with a decrease of nearly 2.5 years in these years. The age at menopause for women born between 1951 and 1975 was generally delayed over time, but the trend of first increase and then decrease was observed among those with relatively higher education levels. In the context of the increasing delay in age at marriage and childbearing and the decline of fertility, this study highlights the necessity of the assessment and monitoring of women' s basic reproductive health status, especially the risk of early menopause.
Female ; Humans ; Aged ; Menarche ; Menopause ; Regression Analysis ; Fertility ; China/epidemiology* ; Age Factors

Objective: To investigate the current situation of job involvement of nurses in military hospitals in Henan Province and analyze the influencing factors, so as to provide reference for improving the level of job involvement of military nurses. Methods: In February 2022, the employed nurses of 4 military hospitals in Henan Province were investigated by convenient sampling method. A total of 663 questionnaires were collected, including 632 valid questionnaires, with an effective recovery rate of 95.32%. The self-designed questionnaire was used to investigate the basic information of nurses, the Job Involvement Scale was used to investigate the job involvement of nurses, the Emotional Labor Scale for Nurses was used to investigate nurses' emotions, and the Work-Family Conflict Scale was used to investigate the work-family conflict of nurses. Independent sample t-test and univariate analysis of variance were used to compare the job involvement of military employed nurses with different demographic characteristics, Pearson correlation analysis was used to explore the correlation between emotional labor, work-family conflict and job involvement, and hierarchical regression analysis was used to explore the impact of relevant variables on the job involvement of military employed nurses. Results: The total average score of job involvement of military employed nurses was (3.68±1.13), and the scores of vitality, dedication and focus were (3.64±1.15), (3.74±1.25) and (3.67±1.21) respectively. The total score of emotional labor of nurses was 33-80 (62.95±8.12), with an average score of (3.93±0.51). The total score of work-family conflict was 18-94 (55.16±13.53), with an average score of (3.06±0.75). Professional emotional regulation, patient-centered emotional inhibition and standardized emotional play were positively related to the job involvement (r=0.46, 0.41, 0.22, P<0.01). Time-based conflict, stress-based conflict and behavior-based conflict had negative correlation with the job involvement (r=-0.12, -0.23, -0.20, P<0.01). In hierarchical regression analysis, after controlling demographic variables, emotional labor and work-family conflict accounted for 17.2% and 4.2% of the variation of job involvement. Conclusion: The job involvement of military employed nurses tends to be at a moderate level. Emotional labor and work-family conflict can significantly affect their job involvement.
United States ; Humans ; Hospitals, Military ; Family Conflict ; Surveys and Questionnaires ; Regression Analysis ; Nurses ; Job Satisfaction

Body mass index (BMI) has been increasing globally in recent decades. Previous studies reported that BMI was associated with sex hormone levels, but the results were generated via linear regression or logistic regression, which would lose part of information. Quantile regression analysis can maximize the use of variable information. Our study compared the associations among different regression models. The participants were recruited from the Center of Reproductive Medicine, The First Hospital of Jilin University (Changchun, China) between June 2018 and June 2019. We used linear, logistic, and quantile regression models to calculate the associations between sex hormone levels and BMI. In total, 448 men were included in this study. The average BMI was 25.7 (standard deviation [s.d.]: 3.7) kg m^-2; 29.7% (n = 133) of the participants were normal weight, 45.3% (n = 203) of the participants were overweight, and 23.4% (n = 105) of the participants were obese. The levels of testosterone and estradiol significantly differed among BMI groups (all P < 0.05). In linear regression and logistic regression, BMI was associated with testosterone and estradiol levels (both P < 0.05). In quantile regression, BMI was negatively associated with testosterone levels in all quantiles after adjustment for age (all P < 0.05). BMI was positively associated with estradiol levels in most quantiles (≤80^th) after adjustment for age (all P < 0.05). Our study suggested that BMI was one of the influencing factors of testosterone and estradiol. Of note, the quantile regression showed that BMI was associated with estradiol only up to the 80^th percentile of estradiol.
Male ; Humans ; Body Mass Index ; Cross-Sectional Studies ; Gonadal Steroid Hormones ; Regression Analysis ; Estradiol ; Testosterone

Objective: To understand the characteristics and trend of the premature death rate of 4 major chronic diseases in Ji'nan from 2015 to 2020. Methods: The death cause surveillance data and population data during 2015-2020 in Ji'nan were collected, and abbreviated life table, Joinpoint regression analysis and other methods were used to analyze the characteristics and change trends of the premature death rates of 4 major chronic diseases. Results: The crude mortality rate and age standardized mortality rate changes for the 4 major chronic diseases from 2015 to 2020 range from 568.65/100 000 to 604.06/100 000 and 366.77/100 000 to 432.48/100 000, respectively. The annual premature death rate of 4 major chronic diseases declined by 3.33% averagely from 2015 to 2020 (95%CI: -6.25%--0.32%), which might be explained by the declines of the premature death rates of cardiovascular and cerebrovascular diseases [average annual percentage change (AAPC)=-3.23%, 95%CI: -6.32%--0.05%] and cancer (AAPC=-3.58%,95%CI:-6.83%--0.21%). The average decline rate in women (AAPC=-4.19%,95%CI:-7.56%- -0.70%) was higher than that in men (AAPC=-2.92%,95%CI: -5.65%--0.11%). Conclusions: The premature death rate of 4 major chronic diseases showed a downward trend in Ji'nan from 2015 to 2020. Men should be considered as a key population in the prevention and control of 4 major chronic diseases, and attention should also be paid to the non-significant declines in the premature death rates of chronic respiratory diseases and diabetes.
Cerebrovascular Disorders ; Chronic Disease ; Diabetes Mellitus ; Female ; Humans ; Male ; Mortality, Premature ; Regression Analysis

Reduced rank regression is an extended multivariate linear regression model with the function of dimension reduction. It has been more and more widely used in nutritional epidemiology research to understand people's dietary patterns in recent years. However, there has been no existing Stata package or command to implement reduced rank regression independently. Therefore, we developed a new user-written package named "rrr" for its implementation in Stata. This paper summarizes the methodology of reduced rank regression, the development and functions of the Stata rrr package and its application in the China Kadoorie Biobank dataset, with the aim of facilitating the future wide use of this statistical method in epidemiology and public health research.
China ; Humans ; Models, Statistical ; Public Health ; Regression Analysis

Objective: To introduce and compare four analysis methods of multiple parallel mediation model, including pure regression method, method based on inverse probability weighting, extended natural effect model method and weight-based imputation strategies. Methods: For the multiple parallel mediation model, the simulation experiments of three scenarios were carried out to compare the performance of different methods in estimating direct and indirect effects in different situations. Dataset from UK Biobank was then analyzed by using the four methods. Results: The estimation biases of the regression method and the inverse probability weighting method were relatively small, followed by the extended natural effect model method, and the estimation results of the weight-based imputation strategies were quite different from the other three methods. Conclusions: Different multiple parallel mediation analysis methods have different application situations and their own advantages and disadvantages. The regression method is more suitable for continuous mediator, and the inverse probability weighting method is more suitable for binary mediator. The extended natural effect model method has better performances when the residuals of two parallel mediators are positively correlated and the correlation degree is small. The weight-based imputation strategies might not be appropriate for parallel mediation analysis. Therefore, appropriate methods should be selected according to the specific situation in practice.
Bias ; Computer Simulation ; Humans ; Mediation Analysis ; Models, Statistical ; Probability ; Regression Analysis ; Research Design