The associations between smoking and obesity in northeast China: a quantile regression analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Sun M
PROVIDER: S-EPMC6418137 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
Publications
The associations between smoking and obesity in northeast China: a quantile regression analysis.
Sun Mengzi M Jiang Yan Y Sun Chong C Li Jiagen J Guo Xin X Lv Yaogai Y Yu Yaqin Y Yao Yan Y Jin Lina L
Scientific reports 20190314 1
Obesity is a risk factors of chronic diseases, and smoking is associated with both chronic diseases and obesity. There were some controversies about the associations between smoking and obesity. Thus, our study aimed to explore the associations of smoking with obesity, using body mass index (BMI) and waist circumference (WC) as obesity indices in northeast China. We enrolled a sample of 16,412 participants in Jilin province aged 18-79 in this study, which were derived from a cross-sectional surv ...[more]
Similar Datasets
Project description:Background: Diabetes mellitus (DM) has become a major public health problem in China. Although a number of researchers have investigated DM risk factors, little is known about the associations between values of fasting blood glucose (FBG) and influencing factors. This study aims to explore these associations by the quantile regression (QR) model. Methods: A cross-sectional survey based on a sample of 23,050 adults aged 18 to 79 years was conducted in Jilin in 2012, and some subjects were excluded due to missing values with respect to necessary variables or having glycemic control, in accordance with the purposes of this study. Finally, in total 14,698 people were included in this study. QR was performed to identify the factors influencing the level of FBG in different quantiles of FBG. Results: The distribution of FBG status was different between males and females (?² = 175.30, p < 0.001). The QR model provided more detailed views on the associations of FBG with different factors and revealed apparent quantile-related patterns separately for different factors. Body mass index (BMI) was positively associated with the low and middle quantiles of FBG. Waist circumference (WC) had a positive association with the high quantiles of FBG. Conclusions: FBG had a positive association with BMI in normal FBG, and a positive association with WC in high FBG. Diet and alcohol intake were associated with FBG in normal FBG. FBG was more likely to be elevated in the elderly, female workers, and people with family history of DM.
| S-EPMC5708007 | biostudies-other
Project description:IntroductionWe investigated the extent to which associations of ambient air pollutant concentrations and birth weight varied across birth weight quantiles.MethodsWe analyzed singleton births ≥27 weeks of gestation from 20-county metropolitan Atlanta with conception dates between January 1, 2002 and February 28, 2006 (N = 273,711). Trimester-specific and total pregnancy average concentrations for 10 pollutants, obtained from ground observations that were interpolated using 12-km Community Multiscale Air Quality model outputs, were assigned using maternal residence at delivery. We estimated associations between interquartile range width (IQRw) increases in pollutant concentrations and changes in birth weight using quantile regression.ResultsGestational age-adjusted associations were of greater magnitude at higher percentiles of the birth weight distribution. Pollutants with large vehicle source contributions (carbon monoxide, nitrogen dioxide, PM2.5 elemental carbon, and total PM2.5 mass), as well as PM2.5 sulfate and PM2.5 ammonium, were associated with birth weight decreases for the higher birth weight percentiles. For example, whereas the decrease in mean birthweight per IQRw increase in PM2.5 averaged over pregnancy was -7.8 g (95% confidence interval = -13.6, -2.0 g), the quantile-specific associations were: 10th percentile -2.4 g (-11.5, 6.7 g); 50th percentile -8.9 g (-15.7, -2.0g); and 90th percentile -19.3 g (-30.6, -7.9 g). Associations for the intermediate and high birth weight quantiles were not sensitive to gestational age adjustment. For some pollutants, we saw associations at the lowest quantile (10th percentile) when not adjusting for gestational age.ConclusionsAssociations between air pollution and reduced birth weight were of greater magnitude for newborns at relatively heavy birth weights.
| S-EPMC6691899 | biostudies-literature
Project description:PURPOSE:We aimed to determine whether moderate to vigorous physical activity (MVPA) and sedentary behavior (SB) were independently associated with body mass index (BMI) and waist circumference (WC) in children and adolescents. METHODS:Data from the International Children's Accelerometry Database were used to address our objectives (N = 11,115; 6-18 yr; 51% female). We calculated age- and gender-specific BMI and WC z-scores and used accelerometry to estimate MVPA and total SB. Self-reported television viewing was used as a measure of leisure time SB. Quantile regression was used to analyze the data. RESULTS:MVPA and total SB were associated with lower and higher BMI and WC z-scores, respectively. These associations were strongest at the higher percentiles of the z-score distributions. After including MVPA and total SB in the same model, the MVPA associations remained, but the SB associations were no longer present. For example, each additional hour per day of MVPA was not associated with BMI z-score at the 10th percentile (b = -0.02, P = 0.170) but was associated with lower BMI z-score at the 50th (b = -0.19, P < 0.001) and 90th percentiles (b = -0.41, P < 0.001). More television viewing was associated with higher BMI and WC, and the associations were strongest at the higher percentiles of the z-score distributions, with adjustment for MVPA and total SB. CONCLUSIONS:Our observation of stronger associations at the higher percentiles indicates that increasing MVPA and decreasing television viewing at the population-level could shift the upper tails of the BMI and WC frequency distributions to lower values, thereby lowering the number of children and adolescents classified as obese.
| S-EPMC5321492 | biostudies-literature
Project description:We examined associations between prenatal oxidative stress (OS) and child autism-related outcomes. Women with an autistic child were followed through a subsequent pregnancy and that younger sibling's childhood. Associations between glutathione (GSH), glutathione disulfide (GSSG), 8-oxo-deoxyguanine (8-OHdG), and nitrotyrosine and younger sibling Social Responsiveness Scale (SRS) scores were examined using quantile regression. Increasing GSH:GSSG (suggesting decreasing OS) was associated with minor increases in SRS scores (50th percentile β: 1.78, 95% CI: 0.67, 3.06); no other associations were observed. Results from this cohort with increased risk for autism do not support a strong relationship between OS in late pregnancy and autism-related outcomes. Results may be specific to those with enriched autism risk; future work should consider other timepoints and biomarkers.
| S-EPMC9732143 | biostudies-literature
Project description:Censored quantile regression models, which offer great flexibility in assessing covariate effects on event times, have attracted considerable research interest. In this study, we consider flexible estimation and inference procedures for competing risks quantile regression, which not only provides meaningful interpretations by using cumulative incidence quantiles but also extends the conventional accelerated failure time model by relaxing some of the stringent model assumptions, such as global linearity and unconditional independence. Current method for censored quantile regressions often involves the minimization of the L1 -type convex function or solving the nonsmoothed estimating equations. This approach could lead to multiple roots in practical settings, particularly with multiple covariates. Moreover, variance estimation involves an unknown error distribution and most methods rely on computationally intensive resampling techniques such as bootstrapping. We consider the induced smoothing procedure for censored quantile regressions to the competing risks setting. The proposed procedure permits the fast and accurate computation of quantile regression parameter estimates and standard variances by using conventional numerical methods such as the Newton-Raphson algorithm. Numerical studies show that the proposed estimators perform well and the resulting inference is reliable in practical settings. The method is finally applied to data from a soft tissue sarcoma study.
| S-EPMC6156950 | biostudies-literature
Project description:ObjectiveOur study aimed to explore the association between maternal iron supplementation and newborn birth weight (BW) in Shaanxi Province using quantile regression (QR).MethodThe data used in this study were derived from a large cross-sectional survey of a population in Shaanxi Province, Northwest China. A total of 28,209 women and their infants were selected using a stratified multistage random sampling method. The effect of iron supplementation on the newborn BW was assessed by a multiple linear regression model and QR.ResultsA total of 5.15% of the women took iron supplements during pregnancy. Multiple linear regression showed that the iron supplementation during pregnancy had positive effects on the BW, with an average increase of 43.07 g (β = 43.07, t = 3.55, and p < 0.001). The QR showed that the iron supplementation during pregnancy was associated with an increased newborn BW from very low to higher percentiles (quantiles: 0 ~ 0.40), with the β ranging from 136.51 to 43.86. As the percentiles of the BW increased, the neonatal BW gain gradually declined in the iron supplementation group compared with the group that did not receive iron supplementation (quantiles: 0 ~ 0.40, with the β ranging from 136.51 to 43.86). Iron supplementation was more effective among women who suffered from anemia during pregnancy (β = 45.84, t = 2.05, and p = 0.04; quantiles: 0 ~ 0.15, 0.30, 0.80, with β ranging from 150.00 to 39.29) than it was in any other group (β = 38.18, t = 2.62, and p = 0.009; quantiles: 0 ~ 0.15, with β ranging from 133.33 to 28.32).ConclusionsIron supplementation during pregnancy is associated with an increased newborn BW, and the effect was more obvious in the newborns with the lower BW and newborns whose mothers suffered from anemia during pregnancy.
| S-EPMC8180103 | biostudies-literature
Project description:An important goal of censored quantile regression is to provide reliable predictions of survival quantiles, which are often reported in practice to offer robust and comprehensive biomedical summaries. However, formal methods for evaluating and comparing working quantile regression models in terms of their performance in predicting survival quantiles have been lacking, especially when the working models are subject to model mis-specification. In this article, we proposes a sensible and rigorous framework to fill in this gap. We introduce and justify a predictive performance measure defined based on the check loss function. We derive estimators of the proposed predictive performance measure and study their distributional properties and the corresponding inference procedures. More importantly, we develop model comparison procedures that enable thorough evaluations of model predictive performance among nested or non-nested models. Our proposals properly accommodate random censoring to the survival outcome and the realistic complication of model mis-specification, and thus are generally applicable. Extensive simulations and a real data example demonstrate satisfactory performances of the proposed methods in real life settings.
| S-EPMC5462897 | biostudies-literature
Project description:Hypertension has become a major public health challenge. However, numerous research results reported in the literature focus primarily on risk factors of hypertension, little is known about how the whole continuum of blood pressure (BP) is associated with risk factors of hypertension. This study aims to reveal quantile-specific associations of BP with its risk factors. A cross-sectional survey based on a sample of 23,050 adults aged 18 to 79 years was conducted in Jilin Province in 2012, and some subjects were excluded due to missing values in BP or having BP control according to the purpose of this study. Quantile regression (QR) was employed to investigate the associations between systolic/diastolic blood pressure (SBP/DBP) and the risk factors. The SBP and DBP in males presented statistically higher than females (P?<?0.001). High-salt diet for males manifested a slightly increasing positive association with higher SBP only for high quantiles (?70), but with a higher DBP for middle part of the quantiles (30~75), compared with bland diet. High-salt diet, drinking and high-density lipoprotein cholesterol (HDL-C) were positively associated with BP measures in males. And the coefficient of total cholesterol (TC) in QR increased with BP in females who used to live in town.
| S-EPMC5648827 | biostudies-other
Project description:Dependent censoring occurs in many biomedical studies and poses considerable methodological challenges for survival analysis. In this work, we develop a new approach for analyzing dependently censored data by adopting quantile regression models. We formulate covariate effects on the quantiles of the marginal distribution of the event time of interest. Such a modeling strategy can accommodate a more dynamic relationship between covariates and survival time compared to traditional regression models in survival analysis, which usually assume constant covariate effects. We propose estimation and inference procedures, along with an efficient and stable algorithm. We establish the uniform consistency and weak convergence of the resulting estimators. Extensive simulation studies demonstrate good finite-sample performance of the proposed inferential procedures. We illustrate the practical utility of our method via an application to a multicenter clinical trial that compared warfarin and aspirin in treating symptomatic intracranial arterial stenosis.
| S-EPMC4222253 | biostudies-literature
Project description:Radiomics involves the study of tumor images to identify quantitative markers explaining cancer heterogeneity. The predominant approach is to extract hundreds to thousands of image features, including histogram features comprised of summaries of the marginal distribution of pixel intensities, which leads to multiple testing problems and can miss out on insights not contained in the selected features. In this paper, we present methods to model the entire marginal distribution of pixel intensities via the quantile function as functional data, regressed on a set of demographic, clinical, and genetic predictors to investigate their effects of imaging-based cancer heterogeneity. We call this approach quantile functional regression, regressing subject-specific marginal distributions across repeated measurements on a set of covariates, allowing us to assess which covariates are associated with the distribution in a global sense, as well as to identify distributional features characterizing these differences, including mean, variance, skewness, heavy-tailedness, and various upper and lower quantiles. To account for smoothness in the quantile functions, account for intrafunctional correlation, and gain statistical power, we introduce custom basis functions we call quantlets that are sparse, regularized, near-lossless, and empirically defined, adapting to the features of a given data set and containing a Gaussian subspace so non-Gaussianness can be assessed. We fit this model using a Bayesian framework that uses nonlinear shrinkage of quantlet coefficients to regularize the functional regression coefficients and provides fully Bayesian inference after fitting a Markov chain Monte Carlo. We demonstrate the benefit of the basis space modeling through simulation studies, and apply the method to Magnetic resonance imaging (MRI) based radiomic dataset from Glioblastoma Multiforme to relate imaging-based quantile functions to various demographic, clinical, and genetic predictors, finding specific differences in tumor pixel intensity distribution between males and females and between tumors with and without DDIT3 mutations.
| S-EPMC7517594 | biostudies-literature