Spatio-Temporal Variation of Gender-Specific Hypertension Risk: Evidence from China.
ABSTRACT: Previous studies which have shown the existence of gender disparities in hypertension risks often failed to take into account the participants' spatial and temporal information. In this study, we explored the spatio-temporal variation for gender-specific hypertension risks in not only single-disease settings but also multiple-disease settings. From the longitudinal data of the China Health and Nutrition Survey (CHNS), 70,374 records of 21,006 individuals aged 12 years and over were selected for this study. Bayesian B-spline techniques along with the Besag, York, and Mollie (BYM) model and the Shared Component Model (SCM) model were then used to construct the spatio-temporal models. Our study found that the prevalence of hypertension in China increased from 11.7% to 34.5% during 1991 and 2015, with a higher rate in males than that in females. Moreover, hypertension was found mainly clustered in spatially adjacent regions, with a significant high-risk pattern in Eastern and Central China while a low-risk pattern in Western China, especially for males. The spatio-temporal variation of hypertension risks was associated with regional covariates, such as age, overweight, alcohol consumption, and smoking, with similar effects of age shared by both genders whereas gender-specific effects for other covariates. Thus, gender-specific hypertension prevention and control should be emphasized in the future in China, especially for the elderly population, overweight population, and females with a history of alcohol consumption and smoking who live in Eastern China and Central China.
Project description:BACKGROUND: Small area analysis is the most prevalent methodological approach in the study of unwarranted and systematic variation in medical practice at geographical level. Several of its limitations drive researchers to use disease mapping methods -deemed as a valuable alternative. This work aims at exploring these techniques using - as a case of study- the gender differences in rates of hospitalization in elderly patients with chronic diseases. METHODS: Design and study setting: An empirical study of 538,358 hospitalizations affecting individuals aged over 75, who were admitted due to a chronic condition in 2006, were used to compare Small Area Analysis (SAVA), the Besag-York-Mollie (BYM) modelling and the Shared Component Modelling (SCM). Main endpoint: Gender spatial variation was measured, as follows: SAVA estimated gender-specific utilization ratio; BYM estimated the fraction of variance attributable to spatial correlation in each gender; and, SCM estimated the fraction of variance shared by the two genders, and those specific for each one. RESULTS: Hospitalization rates due to chronic diseases in the elderly were higher in men (median per area 21.4 per 100 inhabitants, interquartile range: 17.6 to 25.0) than in women (median per area 13.7 per 100, interquartile range: 10.8 to 16.6). Whereas Utilization Ratios showed a similar geographical pattern of variation in both genders, BYM found a high fraction of variation attributable to spatial correlation in both men (71%, CI95%: 50 to 94) and women (62%, CI95%: 45 to 77). In turn, SCM showed that the geographical admission pattern was mainly shared, with just 6% (CI95%: 4 to 8) of variation specific to the women component. CONCLUSIONS: Whereas SAVA and BYM focused on the magnitude of variation and on allocating where variability cannot be due to chance, SCM signalled discrepant areas where latent factors would differently affect men and women.
Project description:Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial-temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women.
Project description:<h4>Background</h4>Failure to promote early detection and better management of hypertension will contribute to the increasing burden of cardiovascular diseases. This study aims to assess the gender differences in the prevalence, awareness, treatment and control of hypertension, together with its associated factors, in China and Sweden.<h4>Methods</h4>We used data from two cross-sectional studies: the Västerbotten Intervention Program in northern Sweden (n =?25,511) and the Shanghai survey in eastern China (n?=?25,356). We employed multivariable logistic regression to examine the socio-demographics, lifestyle behaviours, and biological factors associated with the prevalence, awareness, treatment and control of hypertension.<h4>Results</h4>Men had a higher prevalence of hypertension (43% in Sweden, 39% in China) than their female counterparts (29 and 36%, respectively). In Sweden, men were less aware of, less treated for, and had less control over their hypertension than women. Chinese men were more aware of, had similar levels of treatment for, and had less control over their hypertension compared to women. Awareness and control of hypertension was lower in China compared to Sweden. Only 33 and 38% of hypertensive Chinese men and women who were treated reached the treatment goals, compared with a respective 48 and 59% in Sweden. Old age, impaired glucose tolerance or diabetes, a family history of hypertension or cardiovascular diseases, low physical activity and overweight or obesity were found to increase the odds of hypertension and its diagnosis.<h4>Conclusions</h4>This study shows the age and gender differences in the prevalence, awareness, treatment and control of hypertension among adults in China and Sweden. Multisectoral intervention should be developed to address the increasing burden of sedentary lifestyle, overweight and obesity and diabetes, all of which are linked to the prevention and control of hypertension. Development and implementation of the gender- and context-specific intervention for the prevention and control of hypertension facilitates understanding with regard to the implementation barriers and facilitators.
Project description:In recent years, with rapid industrialization and massive energy consumption, ground-level ozone ( O 3 ) has become one of the most severe air pollutants. In this paper, we propose a functional spatio-temporal statistical model to analyze air quality data. Firstly, since the pollutant data from the monitoring network usually have a strong spatial and temporal correlation, the spatio-temporal statistical model is a reasonable method to reveal spatial correlation structure and temporal dynamic mechanism in data. Secondly, effects from the covariates are introduced to explore the formation mechanism of ozone pollution. Thirdly, considering the obvious diurnal pattern of ozone data, we explore the diurnal cycle of O 3 pollution using the functional data analysis approach. The spatio-temporal model shows great applicational potential by comparison with other models. With application to O 3 pollution data of 36 stations in Beijing, China, we give explanations of the covariate effects on ozone pollution, such as other pollutants and meteorological variables, and meanwhile we discuss the diurnal cycle of ozone pollution.
Project description:Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning is a preventable cause of morbidity and mortality. Epidemiological data on UNFR CO poisoning can help monitor changes in the magnitude of this burden, particularly through comparisons of multiple countries, and to identify vulnerable sub-groups of the population which may be more at risk. Here, we collected data on age- and sex- specific number of hospital admissions with a primary diagnosis of UNFR CO poisoning in England (2002-2016), aggregated to small areas, alongside area-level characteristics (i.e. deprivation, rurality and ethnicity). We analysed temporal trends using piecewise log-linear models and compared them to analogous data obtained for Canada, France, Spain and the US. We estimated age-standardized rates per 100,000 inhabitants by area-level characteristics using the WHO standard population (2000-2025). We then fitted the Besag York Mollie (BYM) model, a Bayesian hierarchical spatial model, to assess the independent effect of each area-level characteristic on the standardized risk of hospitalization. Temporal trends showed significant decreases after 2010. Decreasing trends were also observed across all countries studied, yet France had a 5-fold higher risk. Based on 3399 UNFR CO poisoning hospitalizations, we found an increased risk in areas classified as rural (0.69, 95% CrI: 0.67; 0.80), highly deprived (1.77, 95% CrI: 1.66; 2.10) or with the largest proportion of Asian (1.15, 95% CrI: 1.03; 1.49) or Black population (1.35, 95% CrI: 1.20; 1.80). Our multivariate approach provides strong evidence for the identification of vulnerable populations which can inform prevention policies and targeted interventions.
Project description:Long noncoding RNA profile in the plasma of human with hypertension and healthy controls from North China. Overall design: In the study presented here, we identified the genome-wide expression level of lncRNAs for hypertension healthy control samples from North China. Each sample (total RNA) was pooled from the total RNA of three age and gender matched subjects (hypertension patients or healthy controls).
Project description:Health outcomes are linked to air pollution, demographic, or socioeconomic factors which vary across space and time. Thus, it is often found that relative risks in space-time health data have locally different temporal patterns. In such cases, latent modeling is useful in the disaggregation of risk profiles. In particular, spatio-temporal mixture models can help to isolate spatial clusters each of which has a homogeneous temporal pattern in relative risks. In mixture modeling, various weight structures can be used and two situations can be considered: the number of underlying components is known or unknown. In this paper, we compare spatio-temporal mixture models with different weight structures in both situations. In addition, spatio-temporal Dirichlet process mixture models are compared to them when the number of components is unknown. For comparison, we propose a set of spatial cluster detection diagnostics based on the posterior distribution of the weights. We also develop new accuracy measures to assess the recovery of true relative risks. Based on the simulation study, we examine the performance of various spatio-temporal mixture models in terms of proposed methods and goodness-of-fit measures. We apply our models to a county-level chronic obstructive pulmonary disease data set from the state of Georgia.
Project description:BACKGROUND:Tuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it. METHODS:The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff's retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level. RESULTS:A total of 10?200?528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5?283?983 SS- TB cases and 4?631?734 SS?+?TB cases with specific sputum smear results, 284?811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff's scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR?=?3.27, P?<? 0.001) was mainly located in Xinjiang Uygur Autonomous Region of western China, covering five prefectures and clustering in the time frame from September 2012 to November 2015. The spatio-temporal clustering results of SS+ TB and SS- TB also showed the most likely clusters distributed in the western China. However, the clustering time of SS+ TB was concentrated before 2010 while SS- TB was mainly concentrated after 2010. CONCLUSIONS:This study identified the time and region of TB, SS+ TB and SS- TB clustered easily in 340 prefectures in the mainland of China, which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas, and to formulate powerful strategy to prevention and control TB.
Project description:Human immunodeficiency virus infection and obesity are pro-inflammatory conditions that, when occurring together, may pose a synergistic risk for diabetes and cardiovascular disease.The aim of the current study was (i) to document the prevalence of obesity in HIV+ patients treated at the Miriam Hospital Immunology Center (Providence, RI) and (ii) to investigate the relationship between obesity and comorbidities.The study population consisted of 1,489 HIV+ adults (70% men; average age 48 ± 11 years) treated between 01/01/2012 and 06/30/2014. Separate logistic regressions tested the associations between overweight and obesity and comorbid diagnoses (diabetes, hypertension and cardiovascular disease), as compared with normal weight. Covariates included age, gender and smoking status.Approximately 37% of patients were overweight (body mass index 25.0-29.9), and an additional 28% were obese (body mass index ≥30.0). Obesity was associated with higher odds of comorbid diabetes (OR = 3.26, CI = 1.98-5.39) and hypertension (OR = 2.11, CI = 1.49-2.98). There was no significant association between obesity and the presence of cardiovascular disease (OR = 1.12, CI = 0.66-1.90). Overweight was associated only with higher odds of comorbid diabetes (OR = 1.72; CI = 1.02-2.88).Our findings demonstrate a heightened risk of comorbidities in overweight and obese HIV + patients. Future studies should investigate whether weight loss interventions for this population can reduce cardiovascular and metabolic risk factors as they do in other populations.
Project description:Long noncoding RNA profile in the plasma of human with hypertension and healthy controls from South China. Overall design: In the study presented here, we identified the genome-wide expression level of lncRNAs for one hypertension sample and one healthy control sample. Each sample (total RNA) was pooled from the total RNA of fifteen age and gender matched subjects (hypertension patients or healthy controls).