Non-linear association between long-term air pollution exposure and risk of metabolic dysfunction-associated steatotic liver disease

BACKGROUND@#Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD) has become a global epidemic, and air pollution has been identified as a potential risk factor. This study aims to investigate the non-linear relationship between ambient air pollution and MASLD prevalence.@*METHOD@#In this cross-sectional study, participants undergoing health checkups were assessed for three-year average air pollution exposure. MASLD diagnosis required hepatic steatosis with at least 1 out of 5 cardiometabolic criteria. A stepwise approach combining data visualization and regression modeling was used to determine the most appropriate link function between each of the six air pollutants and MASLD. A covariate-adjusted six-pollutant model was constructed accordingly.@*RESULTS@#A total of 131,592 participants were included, with 40.6% met the criteria of MASLD. "Threshold link function," "interaction link function," and "restricted cubic spline (RCS) link functions" best-fitted associations between MASLD and PM2.5, PM10/CO, and O3 /SO2/NO2, respectively. In the six-pollutant model, significant positive associations were observed when pollutant concentrations were over: 34.64 µg/m3 for PM2.5, 57.93 µg/m3 for PM10, 56 µg/m3 for O3, below 643.6 µg/m3 for CO, and within 33 and 48 µg/m3 for NO2. The six-pollutant model using these best-fitted link functions demonstrated superior model fitting compared to exposure-categorized model or linear link function model assuming proportionality of odds.@*CONCLUSION@#Non-linear associations were found between air pollutants and MASLD prevalence. PM2.5, PM10, O3, CO, and NO2 exhibited positive associations with MASLD in specific concentration ranges, highlighting the need to consider non-linear relationships in assessing the impact of air pollution on MASLD.

Analysis of risk factors of multidrug-resistant organism infection in lung transplant recipients based on restricted cubic spline model / 器官移植

Objective To summarize current status of multidrug-resistant organism (MDRO) infection in lung transplant recipients and analyze the risk factors of MDRO infection. Methods Clinical data of 321 lung transplant recipients were retrospectively analyzed. According to the incidence of postoperative MDRO infection, they were divided into the MDRO group (n=122) and non-MDRO infection group (n=199). The incidence of MDRO infection in lung transplant recipients was summarized. The risk factors of MDRO infection in lung transplant recipients were analyzed by logistic regression model. The dose-response relationship between MDRO infection and time of ventilator use was determined by restricted cubic spline model. Results Among 321 lung transplant recipients, 122 cases developed MDRO infection, with an infection rate of 38.0%. Two hundred and twenty-nine strains of pathogenic bacteria were detected in the MDRO infection group, mainly Gram-negative bacteria (92.6%), and the top three strains were carbapenem-resistant acinetobacter baumannii (46.3%), carbapenem-resistant pseudomonas aeruginosa (22.3%) and carbapenem-resistant klebsiella pneumoniae (14.8%), respectively. MDRO infection mainly consisted of lower respiratory tract infection (61.5%), followed by ventilator-associated pneumonia (26.2%). Univariate analysis showed that the risk factors of MDRO infection in lung transplant recipients were single-lung transplantation, long-time postoperative use of extracorporeal membrane oxygenation (ECMO), long operation time, long-time urinary catheterization, long-time central venous catheterization and long-time ventilator use (all P < 0.05). Multivariate logistic regression analysis indicated that single-lung transplantation and long-time ventilator use were the independent risk factors for MDRO infection in lung transplant recipients (both P < 0.05). Results of restricted cubic spline model analysis showed that the risk of infection continued to increase with the prolongation of ventilator use time within 20 d. After 20 d, prolonging the time of ventilator use failed to increase the risk of infection, showing a plateau effect. Conclusions The MDRO infection rate tends to decline in lung transplant recipients year by year. Single-lung transplantation and long-time ventilator use are the independent risk factors for MDRO infection in lung transplant recipients.

Comparison of prediction ability of two extended Cox models in nonlinear survival data analysis / 南方医科大学学报

OBJECTIVE@#To compare the predictive ability of two extended Cox models in nonlinear survival data analysis.@*METHODS@#Through Monte Carlo simulation and empirical study and with the conventional Cox Proportional Hazards model and Random Survival Forests as the reference models, we compared restricted cubic spline Cox model (Cox_RCS) and DeepSurv neural network Cox model (Cox_DNN) for their prediction ability in nonlinear survival data analysis. Concordance index was used to evaluate the differentiation of the prediction results (a larger concordance index indicates a better prediction ability of the model). Integrated Brier Score was used to evaluate the calibration degree of the prediction (a smaller index indicates a better prediction ability).@*RESULTS@#For data that met requirement of the proportion risk, the Cox_RCS model had the best prediction ability regardless of the sample size or deletion rate. For data that failed to meet the proportion risk, the prediction ability of Cox_DNN was optimal for a large sample size (≥500) with a low deletion (< 40%); the prediction ability of Cox_RCS was superior to those of other models in all other scenarios. For example data, the Cox_RCS model showed the best performance.@*CONCLUSION@#In analysis of nonlinear low maintenance data, Cox_RCS and Cox_DNN have their respective advantages and disadvantages in prediction. The conventional survival analysis methods are not inferior to machine learning or deep learning methods under certain conditions.

Correlation between the changing trajectories of serum uric acid and new onset nonalcoholic fatty liver disease / 中华健康管理学杂志

Objective:To explore the correlation between changing trajectories of serum uric acid and the onset of nonalcoholic fatty liver disease (NAFLD).Methods:A longitudinal cohort study. Total of 3 353 subjects who had routine health examination every year from January 2017 to December 2019 in the Health Management Center of the Second Affiliated Hospital of Dalian Medical University and met the inclusion criteria were selected as the research subjects. Four different serum uric acid trajectory groups were determined by using the group-based trajectory model: the low stability group, medium stability group, medium-high stability group and high stability group. During the follow-up to December 2021, the differences in cumulative incidence of NAFLD in different serum uric acid trajectory groups were calculated and compared. Cox proportional hazard regression model was used to evaluate the hazard ratio ( HR) and 95% confidence interval ( CI) of the NAFLD onset in different serum uric acid trajectory groups. The dose-response relationship between baseline serum uric acid and NAFLD was evaluated by a restricted cubic spline regression model. Results:The cumulative incidence of NAFLD in two years was 10.77%, and the cumulative incidence increased with the rising trajectory of serum uric acid, it was the highestin the high stability group ( P<0.05). Compared that in the low stability group, the risk of NAFLD in the other three groups was as follows: 2.24 (95% CI: 1.59-3.14) in the medium stability group, 2.89 (95% CI: 1.92-4.33) in the medium-high stability group and 4.55 (95% CI:2.83-7.31) in the high stability group (all P<0.05). The risk of NAFLD gradually increased with the rising of serum uric acid level, and the cut-off value of serum uric acid for women and men was 260.32 μmol/L and 365.09 μmol/L, respectively. Conclusions:Long-term moderate and high levels of serum uric acid are independent risk factors for the occurrence of NAFLD. With the rising of serum uric acid trajectory, the risk of NAFLD increases. Attention should be paid to the longitudinal change trend of serum uric acid level in the prevention of NAFLD, and it should be controlled within lower level of the normal range.

Interaction between hyperuricemia and gender on dyslipidemia in the elderly / 中华健康管理学杂志

Objective:To explore the interaction between hyperuricemia and gender on dyslipidemia in the elderly.Methods:A cross-sectional study. The permanent residents aged≥65 years in Kunshan City were selected by the cluster sampling method. The selected residents underwent physical examination and blood biochemical tests such as blood glucose, blood lipid, uric acid, hyaluronic acid, gamma glutamyltransferase and creatinine, and history of schistosomiasis infection was investigated. Multivariate logistic regression analysis was used to analyze the relationship between various factors and dyslipidemia. Synergy index (S), relative excess risk of interaction (RERI) and the attributable proportion due to interaction (AP) were used to evaluate the association between hyperuricemia and female interaction on dyslipidemia.. The dose-response relationship between serum uric acid level and dyslipidemia was analyzed by a restricted cubic spline regression model.Results:The prevalence of dyslipidemia in the elderly aged 65 years and obove was 31.9% (1 450/4 536), and it was 23.7% (517/2 180) and 39.6% (933/2 356) in men and women, respectively ( χ2=131.38, P<0.001). Multivariate regression showed that female, high waist circumference, overweight and obesity, hypertension, diabetes, low glomerular filtration rate, high gamma-glutamyltranspeptidase, high uric acid to creatinine ratio, low neutral to lymphocyte ratio were associated with dyslipidemia (all P<0.05). Additionally, additive interaction association was found between the dyslipidemia and advanced uric acid levels ( OR=1.09, 95% CI: 1.07-1.12) and female ( OR=1.12, 95% CI: 1.11-1.14), and the contribution rate of interaction effects was 19.8% (RERI=0.74, 95% CI: 0.06-1.42; AP=0.20, 95% CI: 0.04-0.36, S=1.37, 95% CI: 1.02-1.84). Non-linear dose response relationship was identified by the restricted cubic spline regression model between the continuously rising serum uric acid and dyslipidemia ( χ2=101.23, P<0.001). Conclusions:The proportion of dyslipidemia in elderly permanent residents is high. Demographics and physical measurement indicators comprehensively affected the prevalence of dyslipidemia. In addition, both hyperuric acid and female have additive interaction on dyslipidemia.

Development of Respiratory Signal Extraction System Based on Photoplethysmography / 中国医疗器械杂志

Oxygen saturation and respiratory signals are important physiological signals of human body, respiratory monitoring plays an important role in clinical and daily life. A system was established to extract respiratory signals from photoplethysmography in this study. Including the collection of pulse wave signal, the extraction of respiratory signal, and the calculation of respiratory rate and pulse rate transmitted from the slave computer to the host computer in real time.

The dose-response relationship between low-dose ionizing radiation and thyroid hormone of medical workers / 中国辐射卫生

Objectives To explore the dose-response relationship between low-dose ionizing radiation and thyroid hormone levels of radiation medical workers and provide theoretical basis for occupational health protection to this population. Methods Using a prospective cohort study design, we collected health examination reports on employees that worked on jobs with occupational exposure to radiation at hospital with individually dose monitoring data for 1 237 workers. The effective cumulative radiation dose was divided into three groups: 0～2.586 mSv, 2.586～3.757 mSv, 3.758～31.272 mSv by the interquartile range. The low-dose group was used as a reference to compare the changes in thyroid hormones of medical workers in different cumulative radiation dose groups. The generalized linear models and restricted cubic spline model were used to examine the association and dose-response relationship between the cumulative effective dose and changing thyroid hormones. Results There were statistically significant differences in changing thyroxine (T4) and Free triiodothyronine (FT3) levels among three different dose groups of 1237 subjects (P < 0.05). The results of generalized linear models analysis revealed that 2.586～3.757 mSv was a significant risk factors of changing T4, with β of 3.514 (95% confidence interval [95% CI]: 0.900～6.128) after adjusting for gender, age, working duration, occupation, medical level and smoking, while the association with changing FT3 was not observed (P > 0.05). The restrictive cubic spline (RCS) model analysis indicated a non-linear dose-response correlation between cumulative radiation dose with changing T4 (P = 0.023). Conclusion Long-term exposure to low-dose ionizing radiation could induce the thyroid damage among medical occupational population. And there is a dose-response relationship between cumulative radiation dose and changing thyroxine.

Association between fatty acid consumption and hypertension among rural residents in Hanzhong of Shaanxi Province / 西安交通大学学报(医学版)

【Objective】 To evaluate the associations of total fat and fatty acid consumption with the risk of hypertension among rural residents in Hanzhong, Shaanxi Province. 【Methods】 A cross-sectional survey on dietary status with a semi-quantitative food frequency questionnaire was conducted among rural residents aged between 18 and 80 years old in Hanzhong of Shaanxi. Multivariate log-binomial regression models and restricted cubic spline were used to explore the associations of dietary total fat, saturated fatty acid, polyunsaturated fatty acid and monounsaturated fatty acids with hypertension and as well as association between dose and response. 【Results】 A total of 2241 individuals were included, with 774 males and 1467 females. Monounsaturated fatty acid accounted for 51.9% of total dietary fat intake, while the other two fatty acids for 48.1%. The intake of dietary fat and any fatty acid in men was significantly in men higher than in women (P<0.001). Results of multivariable log-binomial regression indicated that after adjustment of energy, socio-demographic and lifestyles, the risk of hypertension reduced significantly in Q4 group, compared with that in Q1 (PR: 0.71, 95% CI: 0.54-0.92; P-trend: 0.022) in females. A nonlinear dose-response relationship between monounsaturated fatty acids and hypertension was detected by restricted cubic spline in women (Pnon-linear<0.01). No association was observed of total fat, saturated fatty acid and polyunsaturated fatty acid with hypertension regardless of the gender. 【Conclusion】 In women, increased consumption of monounsaturated fats might play a positive role in reducing the risk of hypertension. Further research is warranted to verify the rationality of causal inference and break-point.

Dose-response relationship between light at night and nonalcoholic fatty liver in steel workers / 中华疾病控制杂志

Objective To explore the relationship between light at night (LAN) and nonalcoholic fatty liver (NAFLD) in steel workers. Methods Relevant information was collected through questionnaires, physical examinations and blood biochemical analysis. Using restricted cubic spline (RCS) and mutiple Logistic regression model to explore the relationship between LAN and NAFLD based on a cross-sectional study. Results The prevalence of NAFLD was 33.8% (2 594 / 7 664) in steel workers. After adjusting for age, sex, marriage, educational level, smoking, drinking, body mass index, luminous intensity in life, liver enzyme metabolism, blood lipid level, physical activity, diet, sleep duration, shift work, high temperature, noise, dust, and carbon monoxide exposure, the RCS model showed a nonlinear dose-response relationship between LAN and NAFLD ( 2=71.59, P<0.001 for overall association test and 2=16.92, P<0.001 for nonlinear test); Multivariate Logistic regression model showed that after adjusting for all confounding factors, when the LAN in the 1 178 d ~ 2 017 d and 2 017 d ~ group, the prevalence of NAFLD increased by 21.7% (OR=1.217, 95% CI: 1.027-1.441) and 47.9% (OR=1.479, 95% CI: 1.240-1.763), respectively, when compared with the group LAN<1 178 d. Conclusion There is a nonlinear dose-response relationship between LAN and NAFLD in steel works.

Dose-response meta-analysis: application and practice using the R software / 한국역학회지

The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.

Dose-response relationship between maternal hemoglobin concentration and preterm birth, in pregnant women / 中华流行病学杂志

Objective@#To investigate the dose-response relationship between hemoglobin concentration and preterm birth, during pregnancy.@*Methods@#With Zhuang ethnicity, a total of 12 780 pregnant women and their infants that admitted to Wuming、Pingguo、Jingxi、Debao、Longan and Tiandong hospitals, were recruited, in Guangxi Zhuang Autonomous Region, from January 2015 to December 2017. Non-conditional logistic regression method was used to analyze the effect of anemia on preterm birth during pregnancy. Dose-response relationship between hemoglobin concentration and preterm birth was explored, using the restrictive cubic spline model.@*Results@#After excluding 2 053 pregnant women with hypertension or aged 35 years and over, results from the non-conditional logistic regression analysis showed that the risk of preterm birth in the anemia group was 1.29 times (OR=1.29, 95%CI: 1.04-1.59, P=0.019) of the non-anemia group in the first trimester. Data from the restricted cubic sample showed that there appeared nonlinear "L" dose-response relationship between hemoglobin concentration and preterm birth in the first trimester and "U" shape in the third trimester (non-linearity test P<0.001).@*Conclusion@#There appeared nonlinear dose-response relationship between the hemoglobin concentration and preterm birth, both in the first and third trimesters.

Dose-response meta-analysis: application and practice using the R software / 한국역학회지

The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.

Association between sedentary behavior and mortality in patients with type 2 diabetes: A dose-response relationship analysis / 中华内分泌代谢杂志

Objective To estimate the dose-response relationship between sedentary behavior with mortality in patients with type 2 diabetes. Methods A total of 17786 type 2 diabetic patients were recruited as participants, who were included in National Basic Public Health Service in Changshu County of Suzhou City, Qinghe District and Huai'an District in Huai'an City of Jiangsu Province. Cox proportional hazards regression model and restricted cubic spline model were employed to estimate the dose-response relationship between sedentary behavior with all-cause and cause specific mortality in patients with type 2 diabetes. Results Among 78114.34 person-years of the fo1low-up, the median of follow-up time was 4 years, and 1285 deaths occurred during that period. Compared to patients with sedentary behavior≤2 h/d, the multivariate adjusted hazard ratios of all-cause death associated with sedentary behavior levels of 3-4 h/d, 5-6 h/d, and≥7 h/d were 1.05(95％CI 0.92-1.20), 1.20(95％CI 1.03-1.42), and 1.39 (95％CI 1.16-1.65), respectively. Eevry increase of 1 h/d in sedentary behavior was associated with an increased hazard of death from cardiovascular disease(CVD) of 4％(HR=1.04, 95％CI 1.01-1.07) and from other causes of 6％( HR=1.06, 95％CI 1.03-1.09) . However, no significant association between sedentary behavior and malignant tumor death was found. The multivariable restrictive cubic spline regression indicated that the linear dose-response relationships were found between sedentary time with the all-cause, CVD cause, and other cause of mortality ( Non-linear test, P>0.05) . Conclusion Longer sedentary behavior could increase the risk of mortality in patients with type 2 diabetes.

Research on Kalman interpolation prediction model based on micro-region PM2.5 concentration / 生物医学工程学杂志

In recent years, the pollution problem of particulate matter, especially PM2.5, is becoming more and more serious, which has attracted many people's attention from all over the world. In this paper, a Kalman prediction model combined with cubic spline interpolation is proposed, which is applied to predict the concentration of PM2.5 in the micro-regional environment of campus, and to realize interpolation simulation diagram of concentration of PM2.5 and simulate the spatial distribution of PM2.5. The experiment data are based on the environmental information monitoring system which has been set up by our laboratory. And the predicted and actual values of PM2.5 concentration data have been checked by the way of Wilcoxon signed-rank test. We find that the value of bilateral progressive significance probability was 0.527, which is much greater than the significant level = 0.05. The mean absolute error (MEA) of Kalman prediction model was 1.8 μg/m , the average relative error (MER) was 6%, and the correlation coefficient was 0.87. Thus, the Kalman prediction model has a better effect on the prediction of concentration of PM2.5 than those of the back propagation (BP) prediction and support vector machine (SVM) prediction. In addition, with the combination of Kalman prediction model and the spline interpolation method, the spatial distribution and local pollution characteristics of PM2.5 can be simulated.

Dose-Response Relationship between Alanine Aminotransferase Levels within the Reference Interval and Metabolic Syndrome in Chinese Adults

PURPOSE: Elevation in serum alanine aminotransferase (ALT) levels is a biomarker for metabolic syndrome (MS); however, the relationship has not been fully investigated within the reference interval of ALT levels. Our objective was to explore the relationship between serum ALT levels within the reference interval and MS in Chinese adults. MATERIALS AND METHODS: This cross-sectional study included 16028 adults, who attended routine health check-ups at Shengli Oilfield Central Hospital from January 2006 to March 2012. The reference interval of serum ALT level was defined as less than 40 U/L. Logistic regression models and restricted cubic spline were used to evaluate the association of ALT with MS. RESULTS: The prevalence of MS in the total population was 13.7% (6.4% for females and 18.4% for males). Multiple logistic regression showed that ALT levels were positively associated with MS after adjustment for potential confounding factors. The odds ratio of MS in the top quartile was 4.830 [95% confidence interval (CI): 2.980–7.829] in females and 3.168 (95% CI: 2.649–3.790) in males, compared with the ALT levels in the bottom quartile. The restricted cubic spline models revealed a positive non-linear dose-response relationship between ALT levels and the risk of MS in women (p for nonlinearity was 0.0327), but a positive linear dose-response relationship in men (p for nonlinearity was 0.0659). CONCLUSION: Serum ALT levels within the reference interval are positively associated with MS in a dose-response manner. Elevated ALT levels, even within the reference interval, may reflect early dysmetabolic changes.

A dose-response analysis on the association of gestational weight gain rate and the normal term neonate birth weight / 中华流行病学杂志

Objective To examine the dose-response relationship between gestational weight gain rate and the neonate birth weight.Methods A total of 18 868 women with singleton gestations who delivered between January 2006 and December 2013 were included in this study.Maternal and neonate details of these women were drawn from the Perinatal Monitoring System database.Gestational weight gain rate was defined as the total weight gain during the last and first prenatal care visits divided by the interval weeks.Both Multiple logistic regression analysis and restricted cubic spline methods were performed.Confounding factors included maternal age,education,pre-pregnancy body mass index (BMI),state of residence,parity,gestational weeks of prenatal care entry,and sex of the neonate.Results The adjusted odds ratio for macrosomia was associated with gestational weight gain rate in lower pre-pregnancy BMI (OR=3.15,95％CI:1.40-7.07),normal (OR=3.64,95％CI:2.84-4.66) or overweight (OR=2.37,95％CI:1.71-3.27).The odds ratios of low birth weight appeared a decrease in those women with lower pre-pregnancy BMI (OR=0.28,95％CI:0.13-0.61) while the normal weight (OR=0.37,95％CI:0.22-0.64) group with gestational weight gain,the rate showed an increase.Association of gestational weight gain rate for macrosomia was found a S-curve in those term delivery women (non-linearity test P＜0.000 1).However,L-curve was observed for low birth weight and gestational weight gain rate in term births (non-linearity test P＜0.000 1).Conclusion A S-curve was seen between gestational weight gain rate and term delivered macrosomia while L-curve was observed among term delivered low birth weight neonates.

Construction of National Standards of Growth Curves of Height and Weight for Children Using Cross-sectional Data.

Objectives: Growth curves are the most important tools for the assessment of growth of children, which could further helps to develop preventive interventions. Geographical and physical differences necessitate using national growth curves. This study aims to construct growth curves using anthropometric measurements namely weight and height for Indian children using cross-sectional data from National Family and Health Surveys. Materials and Methods: Box- Cox power exponential, a flexible distribution, was used that offers to adjust kurtosis and improves the estimation of extreme percentiles. LMS-methods that fit skewed data adequately and generate fitted curves that follow closely the empirical data, with maximum penalized likelihood, Akaike information criteria (AIC) and generalized AIC with penalty 3 were used to construct the growth curves. Before fittings this model factors which influence the nutritional status of children were examined, similar to World Health Organization (WHO) (2006) factors, namely standard infant feeding practices, sanitation, non-smoking mothers additionally poverty (household consumable assets based). Results: Model fitted in LMS-model and standard based on height and weight for children aged 0–60 months was obtained after iteration for degrees of freedom for the parameters. Growth curves for mean Z-scores and percentiles were constructed for both sexes and significant lower values were noticeably found to be set as growth-standard compared to WHO-standards. Conclusion: Study showed the prospect of constructing regional/national growth curve and their need for the assessment of children’s growth, which could help to identify undernourished-children at national level. There is an urgent need to collect longitudinal data of children to fit the growth curve of children in India.

Application of spline-based Cox regression on analyzing data from follow-up studies / 中华流行病学杂志

With R,this study involved the application of the spline- based Cox regression to analyze data related to follow-up studies when the two basic assunptions of Cox proportional hazards regression were not satisfactory.Results showed that most of the continuous covariatcs contributed nonlincarly to mortality risk while the effects of three covariates were timc- depcndent.After considering multiple covariatcs in spline-based Cox regression,when the ankle brachial index (ABI) decreased by 0.1,the hazard ratio (HR) for all-cause death was 1.071.The spline-based Cox regression method could be applied to analyze the data related to follow-up studies when the assumptions of Cox proportional hazards regression were violatcd.

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e) ,quadratic regression, (y = β0 + β1X + β2X2 + e) cubic regression (y = β0 + β1X + β2X2 + β3X3 + e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9 percent. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.

Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model

Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.