Analysis of factors influencing the outpatient workload at Chinese health centres

<p>Abstract</p> <p>Background</p> <p>Although the community health service system is now established in China, the utilisation of the community health service institutions is low due to the lack of a gate-keeping role of the primary health service providers and referrals among the three-tiered health service institutions. In addition to this, patients who can afford to pay, often seek best services in big hospitals to guarantee the quality of care. Thus, the need of guiding the patients to the community health services and increasing the utilisation of the community health service institutions is becoming an urgent problem, which hinders the future development of community health services. This study focuses on the question of how to increase the utilisation of Chinese community health centres (HCs).</p> <p>Methods</p> <p>A cross-sectional Base-line Survey of Chinese City Community Health Service System Building using the multi-staged cluster sampling was conducted to collect data from all HCs in 28 key contact cities. Relevant indicators of totally 1790 HCs were analysed. The statistical methods included ANONVA and logistic regression.</p> <p>Results and Conclusions</p> <p>The analysis suggested several key factors for increasing the outpatient workload (OW) at the HCs: establishing an adequate referral system among the different levels of the health system; enhancing the qualification of health personnel and increasing the compensation by the health insurance for services provided at HCs. Other key factors with a positive effect on the OW included: the government ownership of the HCs, the scale of the institutions, the medical equipment used, the mix of health services provided, and the women in childbearing age in the residence.</p

Cardiovascular Health and Atrial Fibrillation or Flutter: A Cross-Sectional Study from ELSA-Brasil

Abstract Background The association between ideal cardiovascular health (ICVH) status and atrial fibrillation or flutter (AFF) diagnosis has been less studied compared to other cardiovascular diseases. Objective To analyze the association between AFF diagnosis and ICVH metrics and scores in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Methods This study analyzed data from 13,141 participants with complete data. Electrocardiographic tracings were coded according to the Minnesota Coding System, in a centralized reading center. ICVH metrics (diet, physical activity, body mass index, smoking, blood pressure, fasting plasma glucose, and total cholesterol) and scores were calculated as proposed by the American Heart Association. Crude and adjusted binary logistic regression models were built to analyze the association of ICVH metrics and scores with AFF diagnosis. Significance level was set at 0.05. Results The sample had a median age of 55 years and 54.4% were women. In adjusted models, ICVH scores were not significantly associated with prevalent AFF diagnosis (odds ratio [OR]:0.96; 95% confidence interval [95% CI]:0.80-1.16; p=0.70). Ideal blood pressure (OR:0.33; 95% CI:0.15–0.74; p=0.007) and total cholesterol (OR:1.88; 95% CI:1.19–2.98; p=0.007) profiles were significantly associated with AFF diagnosis. Conclusions No significant associations were identified between global ICVH scores and AFF diagnosis after multivariable adjustment in our analyses, at least partially due to the antagonistic associations of AFF with blood pressure and total cholesterol ICVH metrics. Our results suggest that estimating the prevention of AFF burden using global ICVH scores may not be adequate, and ICVH metrics should be considered in separate

Cardiovascular Health and Atrial Fibrillation or Flutter: A Cross-Sectional Study from ELSA-Brasil

Abstract Background The association between ideal cardiovascular health (ICVH) status and atrial fibrillation or flutter (AFF) diagnosis has been less studied compared to other cardiovascular diseases. Objective To analyze the association between AFF diagnosis and ICVH metrics and scores in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Methods This study analyzed data from 13,141 participants with complete data. Electrocardiographic tracings were coded according to the Minnesota Coding System, in a centralized reading center. ICVH metrics (diet, physical activity, body mass index, smoking, blood pressure, fasting plasma glucose, and total cholesterol) and scores were calculated as proposed by the American Heart Association. Crude and adjusted binary logistic regression models were built to analyze the association of ICVH metrics and scores with AFF diagnosis. Significance level was set at 0.05. Results The sample had a median age of 55 years and 54.4% were women. In adjusted models, ICVH scores were not significantly associated with prevalent AFF diagnosis (odds ratio [OR]:0.96; 95% confidence interval [95% CI]:0.80-1.16; p=0.70). Ideal blood pressure (OR:0.33; 95% CI:0.15–0.74; p=0.007) and total cholesterol (OR:1.88; 95% CI:1.19–2.98; p=0.007) profiles were significantly associated with AFF diagnosis. Conclusions No significant associations were identified between global ICVH scores and AFF diagnosis after multivariable adjustment in our analyses, at least partially due to the antagonistic associations of AFF with blood pressure and total cholesterol ICVH metrics. Our results suggest that estimating the prevention of AFF burden using global ICVH scores may not be adequate, and ICVH metrics should be considered in separate

Additional file 27 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Additional file 27: Table S17. Sex-stratified effect sizes in UK Biobank considering all individuals or only those not on cholesterol lowering medications

Additional file 8 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Additional file 8: Table S6. Association of lipid index variants with CAD, T2D and NAFLD

Additional file 4 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Additional file 4: Table S3. Text mining results for the PoPS+ prioritized genes

Additional file 10 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Additional file 10: Table S7. DESE phenotype-tissue association results using both GTEx gene-level and transcript-level selective expression