Time series decomposition into dyslipidemia prevalence among urban Chinese population: secular and seasonal trends

Background Previous epidemiological studies have indicated the seasonal variability of serum lipid levels. However, little research has explicitly examined the separate secular and seasonal trends of dyslipidemia. The present study aimed to identify secular and seasonal trends for the prevalence of dyslipidemia and the 4 clinical classifications among the urban Chinese population by time series decomposition. Methods A total of 306,335 participants with metabolic-related indicators from January 2011 to December 2017 were recruited based on routine health check-up systems. Multivariate direct standardization was used to eliminate uneven distributions of the age, sex, and BMI of participants over time. Seasonal and trend decomposition using LOESS (STL decomposition) was performed to break dyslipidemia prevalence down into trend component, seasonal component and remainder component. Results A total of 21.52 % of participants were diagnosed with dyslipidemia, and significant differences in dyslipidemia and the 4 clinical classifications were observed by sex (P <0.001). The secular trends of dyslipidemia prevalence fluctuated in 2011–2017 with the lowest point in September 2016. The dyslipidemia prevalence from January to March and May to July was higher than the annual average (λ = 1.00, 1.16, 1.06, 1.01, 1.02, 1.03), with the highest point in February. Different seasonal trends were observed among the 4 clinical classifications. Compared to females, a higher point was observed among males in February, which was similar to participants aged < 55 years (vs. ≥ 55 years) and participants with a BMI ≤ 23.9 (vs. BMI > 23.9). Conclusions There were significant secular and seasonal features for dyslipidemia prevalence among the urban Chinese population. Different seasonal trends were found in the 4 clinical classifications of dyslipidemia. Precautionary measures should be implemented to control elevated dyslipidemia prevalence in specific seasons, especially in the winter and during traditional holidays.

Abstract P179: Explaining The Increase Of Hypertension Prevalence In Bangladesh From 2011 To 2018: Evidence From National Surveys

Objective: General trends in the epidemiology of hypertension are best described by studying the same population over time, but studies are limited. Using surveys from Bangladesh in 2011 and 2017-18, we examined i) the change in the prevalence of hypertension, ii) the extent to which changes in traditional hypertension risk factors explained the increase, and iii) the change in the distribution of systolic and diastolic blood pressure over time. Methods: Two independent Bangladesh Demographic and Health Surveys were undertaken in 2011 and 2017-18 using similar methodology in adults aged 35 years and older. Hypertension was defined as having systolic blood pressure (SBP) ≥140 mmHg and/or a diastolic blood pressure (DBP) ≥90 mmHg and/or taking antihypertensive drugs to control blood pressure. Age-standardized prevalence of hypertension was estimated with direct standardization using population census 2011, and a multilevel mixed-effects Poisson regression model with robust variance was used to explain the increase of hypertension from 2011 to 2018. Results: The age-standardized prevalence of hypertension in 2017-18 was 43.4% (95% CI 40.2-46.6) in men and 53.4% (95% CI 50.8-56.0) in women, representing an increase since 2011 of 54% and 8% in men and women, respectively. The age, body mass index, education, and diabetes explained the increase in the prevalence of hypertension from 2011 to 2017-18. We observed statistically significant sex-differences in the increase of hypertension in 2018 (p-difference <0.0001). Increases in SBP and DBP were also seen across the population over the period. Conclusions: In Bangladesh, there has been a marked increase in hypertension prevalence over seven years, especially in men. This largely results from changes in traditional risk factors, leading to population-wide increases in blood pressure levels. Interventions to control this exacerbation of hypertension should focus on population-wide strategies.

A Comparison of statistical methods for hospital performance assessment

During hospital quality improvement activities, statistical approaches are critical to help assess hospital performance for benchmarking. Current statistical approaches are used primarily for research and reimbursement purposes. In this multiinstitutional study, these established statistical methods were evaluated for quality improvement applications. Leveraging a dataset of 42,199 patients who underwent coronary artery bypass grafting surgery from 2014 to 2016 across 90 hospitals, six statistical approaches were applied. The non-shrinkage methods were: (1) indirect standardization without hospital effect; (2) indirect standardization with hospital fixed effect; (3) direct standardization with hospital fixed effect. The shrinkage methods were: (4) indirect standardization with hospital random effect; (5) direct standardization with hospital random effect; (6) Bayesian method. Hospital performance related to operative mortality and major morbidity or mortality was compared across methods based on variation in adjusted rates, rankings, and performance outliers. Method performance was evaluated across procedure volume terciles: small (< 96 cases/year), medium (96-171), and large (> 171). Shrinkage methods reduced inter-hospital variation (min-max) for mortality (observed: 0%-10%; adjusted: 1.5%-2.4%) and major morbidity or mortality (observed: 2.6%-35%; adjusted: 6.9%-17.5%). Shrinkage methods shrunk hospital rates toward the group mean. Direct standardization with hospital random effect, compared to fixed effect, resulted in 16.7%-38.9% of hospitals changing quintile mortality ranking. Indirect standardization with hospital random effect resulted in no performance outliers among small and medium hospitals for mortality, while logistic and fixed effect methods identified one small and three medium outlier hospitals. The choice of statistical method greatly impacts hospital ranking and performance outlier’ status. These findings should be considered when benchmarking hospital performance for hospital quality improvement activities.

Comparison of Mortality by Gender and Regions in Tanzania using Direct Standardized Death Rates (DSDR) Method

Background: Comparison of mortality is very useful in assessing population health. Crude rates can easily be computed from the mortality but they are not good for comparison across groups of the population. The aim of this paper was to compare mortality in Tanzania by region and gender using the 2012 Tanzania Population and Housing Census. Methods: Age-specific death rates for regions, Tanzania Mainland, Tanzania Zanzibar and entire Tanzania were obtained from Mortality and Health monograph data downloadable from the National Bureau of Statistics website. The direct standardization method was used to compare the mortality for male and female populations across all regions of Tanzania Mainland and Zanzibar. Results: Findings show that the mortality is low in Arusha, Manyara, and Kilimanjaro compared to other regions in Tanzania mainland implying that health status for both male and female population in those regions is better than the other regions while it is the worst in Njombe, Iringa, and Kagera implying the poor health status for those regions as compared to the rest regions in Tanzania Mainland. In Tanzania Zanzibar, high mortality was observed in Kusini Unguja and the lowest in Kaskazini Unguja for both male and female populations. By national wise and for almost all regions, the mortality for the male population is higher than that for the female population. Conclusion: Direct standardization methods can save as the best way for comparing mortality because it takes into consideration both the population at risk and the age structure. However, in estimating mortality, crude death rates should be used to give the magnitude while direct standardized death rates should be used for comparison purposes.

Model Maintenance of RC-PLSR for Moisture Content Measurement of Dried Scallop

HighlightsThe RC-PLSR model for Haiwan scallop can be transferred to Xiayi scallop.The direct standardization method is suggested for model maintenance.The VSWS-PDS method can be further improved in precision.Abstract. A prediction model for evaluating the moisture content in dried Haiwan scallops was established using hyperspectral imaging (HSI) technology in a previously published study. The accuracy of such models is usually affected by differences in sample species, different environmental conditions such as temperature or humidity, and aging of instruments. In this study, the prediction ability of the RC-PLSR model is improved by correcting the spectra of the tested species of dried scallop (i.e., Xiayi) to solve the problem of model failure caused by sample differences. The results of model maintenance by direct standardization (DS) are compared with those of variety sensitive wavelength selection - piecewise direct standardization (VSWS-PDS). The results showed that after using VSWS-PDS to modify the spectral data of the dried scallop samples, the correlation coefficient of prediction (Rp) of the updated model increased from 0.0890 to 0.9190. However, the root mean square error of prediction (RMSEP) also increased, indicating a need for improved precision. The RC-PLSR model based on DS correction showed Rp of 0.790 and RMSEP of 9.7481%. Model maintenance using the DS method is suggested because DS generally outperformed VSWS-PDS, even with a lower correlation coefficient. Future work on error reduction and sample input is suggested for VSWS-PDS optimization. Keywords: Direct standardization, Hyperspectral images, Model maintenance, Scallop, VSWS-PDS.

Identification of occupational risk for arterial hypertension. 1: elimination of the modifyng influence of factors of cardiovascular risk

On results of research in 13 occupational groups (3842 workers, men) there were performed an analysis of a contribution of non-occupational factors of cardiovascular risk (FCVRs) and the elimination of their modifying influence on risks for the development of the arterial hypertension (AH). In the capacity of non-occupational FCVRs there were considered 16 predictors of AH. There were calculated the relative risk of AH and 95% the confidential interval (CI) in occupational groups on benchmark data of the prevalence rate of AH and after the elimination of the modifying influence of FCVRs. Reference group was the general sample, that is, all the occupations. Modifying influence of FCVR was eliminated by means of direct standardization. With the aid of trees of classification from the number of FCVRs in occupational groups the presence of obesity and age of the worker (respectively, 100 and 78 conditional points) was shown to have the maximum impact on the development of AH. Elimination of the influence of data of FCVRs led to the change of benchmark values of occupational risks of AH in the average for 10%, in four occupations level of the statistical importance of risks of AH changed. In top-managers, and also in operating personnel and technical workers the risk for AH from the high decreased to not significant, respectively to 1,00 at 95%, CI: 0,74-1,36 and 1,20 at 95%, CI: 0,97-1,49. On the contrary, the risk for AH increased from low to statistically not significant in underground equipment operators (0,85 at 95%, CI: 0,71-1,01) and labourers (0,89 at 95%, CI:0,69-1,14).

NIR model transfer of alkali-soluble polysaccharides in Poria cocos with piecewise direct standardization

Objective To investigate the feasibility for establishing near-infrared spectra model transfer with traditional Chinese medicine. Method Poria cocos, a kind of fungi (called “ Fuling” in Chinese), was used as an investigative object. NIR quantification model transfer of alkali-soluble polysaccharides in Poria cocos was studied. Spectra were obtained from Thermo Antaris II (master device) and Buchi NIRFlex N-500 (slave device), respectively. Procedures and factors that may have effects on the performance of spectral standardization have been investigated. Spline interpolation was applied to align spectra from two different instruments, and piecewise direct standardization was employed to standardize spectra from slave instrument. Full cross-validation was used to evaluate the result of model transfer. Results Spectral pre-processing including multiplicative signal correction and wavelength selection played an important role in operating the model transfer. Spectra within the region of 9000–6500 cm−1 provided relatively good transfer result. In addition, increasing window size had positive effect on improving the spectral transfer. In this study, a window size of 13 provided the best spectra standardization result. Test validation with five samples produced the best full cross-validation result with the values of correlation coefficient of calibration ([Formula: see text]), correlation coefficient of prediction ([Formula: see text]) and root mean square error of prediction as 0.86, 0.73 and 2.3, respectively. Conclusion In this study, many factors influenced the quality of the transferred slave spectra. And it is hard to provide a pretty good quantitative model transfer result about alkali-soluble polysaccharide in Poria cocos. The following factors have great effects on the quality of model transfer: (i) multiplicative signal correction which is necessary for model building; (ii) increasing the window size which has a positive effect on slave spectra standardization; (iii) a proper wavelength region benefits for model building; (iv) a proper scale of standardization group including proper samples is necessary.