scholarly journals Level of inequality and the role of governance indicators in the coverage of reproductive maternal and child healthcare services: Findings from India

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0258244
Author(s):  
Sumirtha Gandhi ◽  
Tulasi Malini Maharatha ◽  
Umakant Dash ◽  
Suresh Babu M.

Background Diligent monitoring of inequalities in the coverage of essential reproductive, maternal, new-born and child health related (RMNCH) services becomes imperative to smoothen the journey towards Sustainable Development Goals (SDGs). In this study, we aim to measure the magnitude of inequalities in the coverage of RMNCH services. We also made an attempt to divulge the relationship between the various themes of governance and RMNCH indices. Methods We used National Family Health Survey dataset (2015–16) and Public Affairs Index (PAI), 2016 for the analysis. Two summative indices, namely Composite Coverage Index (CCI) and Co-Coverage (Co-Cov) indicator were constructed to measure the RMNCH coverage. Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were employed to measure inequality in the distribution of coverage of RMNCH. In addition, we have used Spearman’s rank correlation matrix to glean the association between governance indicator and coverage indices. Results & conclusions Our study indicates an erratic distribution in the coverage of CCI and Co-Cov across wealth quintiles and state groups. We found that the distribution of RII values for Punjab, Tamil Nadu, and West Bengal hovered around 1. Whereas, RII values for Haryana was 2.01 indicating maximum inequality across wealth quintiles. Furthermore, the essential interventions like adequate antenatal care services (ANC4) and skilled birth attendants (SBA) were the most inequitable interventions, while tetanus toxoid and Bacilli Calmette- Guerin (BCG) were least inequitable. The Spearman’s rank correlation matrix demonstrated a strong and positive correlation between governance indicators and coverage indices.

2013 ◽  
Vol 94 (5) ◽  
pp. 677-681
Author(s):  
T I Dolgikh ◽  
D A Serbaev ◽  
G V Chekmarev ◽  
T V Kadcyna

Aim. To develop the software product for of medical data analysis and public health indicators presentation. Methods. R_MED software - an interface for typical experimental, clinical and laboratory, epidemiologic analysis using the R system opportunities - was developed. Results. Functionally, the program consists of the following blocks: «Load Data», «Settings», «Basic calculations», «Data Mining», «Presentation of health indicators». Interface simplifying is also achieved by the inclusion of only those methods that are most often required in medical data analysis. So, the «Basic calculation» unit includes the following statistical calculations: descriptive statistics for quantitative variables, frequency tables, bar charts and box plots, Pearson’s correlation matrix, Pearson’s linear correlation, Spearman’s rank correlation, Spearman’s correlation matrix, 2D scatter plots, defining the difference in two independent sample groups using Student’s test and the Mann-Whitney test, analysis of variance (ANOVA). In the «Settings» unit, a user can choose a set of variables and observations for analysis, to change the set of features for any value, to add, delete, rename the variable, and optionally customize the «Load Data» mode, the basic calculation, and data output. The program provides the ability to visualize data using «Presentation of health indicators» block in the context of territory, year and variant. Territorial cuts can be differentiated into three levels: municipal, regional, district (Federal District) level. To construct the maps, vector data on all 3 spatial levels are stored in the R_MED system, including the Federal Districts of Russian Federation. Conclusion. Originally developed for research problems solving of pathology risk forecasting, the R_MED program, if configured properly, can also be used in other clinical diagnostic and epidemiological studies to monitor problems of socially significant diseases and of health services, as well as in the preparation of annual statistical reports, including the regional level.


2015 ◽  
Vol 43 (6) ◽  
pp. 2588-2623 ◽  
Author(s):  
Zhigang Bao ◽  
Liang-Ching Lin ◽  
Guangming Pan ◽  
Wang Zhou

Author(s):  
Fu-Ju Tsai ◽  
Cheng-Yu Chen ◽  
Gwo-Liang Yeh ◽  
Yih-Jin Hu ◽  
Chie-Chien Tseng ◽  
...  

Background: Nursing educators should train nursing students to pursue physical, psychological, spiritual, and social health promotion. The purpose of this study was to explore relationships between nursing students’ meaning of life, positive beliefs, and well-being. Methods: A cross-sectional correlational study with a quantitative approach was adopted. Purposive sampling was used. A total of 170 nursing students voluntarily participated in this study. A 56-item questionnaire was used to examine nursing students’ meaning of life (1-25 items), positive beliefs (1-11 items), and well-being (1-20 items). The content validity index (CVI) of the study questionnaire was established as 0.95 by seven expert scholars. The reliability values for the three parts of the measure were as follows: meaning of life, Cronbach’s α 0.96; positive beliefs, Cronbach’s α 0.93; and well-being, Cronbach’s α 0.95. Percentages, frequencies, means, SDs, Kruskal-Wallis one-way analysis of variance by rank, Spearman’s rank correlation, one-way analysis of variance, Spearman’s rho correlation, and regression analysis were used for the data analysis. Results: Nursing students had the following mean scores: meaning of life with 4.02 (SD 0.56); positive beliefs with 3.92 (SD 0.62); and well-being with 3.95 (SD 0.57). The results indicate that for all nursing students, meaning of life was positively correlated with positive beliefs, r=0.83 (P<.01); similarly, all nursing students had positive beliefs that were positively correlated with meaning of life, r=0.83 (P<.01). In the results of the study, the nursing students’ background, meaning of life and positive beliefs explained 63% of the variance in well-being (Adjusted R2 squared =0.63, F=33.41, P<.001). Conclusions: Nursing students’ sense of meaning of life and positive beliefs may impact their well-being. Therefore, nursing educators can promote meaning of life and positive beliefs to nursing students as a way to increase their well-being for physical, psychological, spiritual, and social health promotion.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Hui Jiang ◽  
Peian Lou ◽  
Xiaoluo Chen ◽  
Chenguang Wu ◽  
Shihe Shao

Abstract Background Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown. Methods Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman’s rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. Results The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman’s rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively). Conclusion The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.


Author(s):  
Rei Nakamichi ◽  
Toshiaki Taoka ◽  
Hisashi Kawai ◽  
Tadao Yoshida ◽  
Michihiko Sone ◽  
...  

Abstract Purpose To identify magnetic resonance cisternography (MRC) imaging findings related to Gadolinium-based contrast agent (GBCA) leakage into the subarachnoid space. Materials and methods The number of voxels of GBCA leakage (V-leak) on 3D-real inversion recovery images was measured in 56 patients scanned 4 h post-intravenous GBCA injection. Bridging veins (BVs) were identified on MRC. The numbers of BVs with surrounding cystic structures (BV-cyst), with arachnoid granulations protruding into the superior sagittal sinus (BV-AG-SSS) and the skull (BV-AG-skull), and including any of these factors (BV-incl) were recorded. Correlations between these variables and V-leak were examined based on the Spearman’s rank correlation coefficient. Receiver-operating characteristic (ROC) curves were generated to investigate the predictive performance of GBCA leakage. Results V-leak and the number of BV-incl were strongly correlated (r = 0.609, p < 0.0001). The numbers of BV-cyst and BV-AG-skull had weaker correlations with V-leak (r = 0.364, p = 0.006; r = 0.311, p = 0.020, respectively). The number of BV-AG-SSS was not correlated with V-leak. The ROC curve for contrast leakage exceeding 1000 voxels and the number of BV-incl had moderate accuracy, with an area under the curve of 0.871. Conclusion The number of BV-incl may be a predictor of GBCA leakage and a biomarker for waste drainage function without using GBCA.


Author(s):  
Cheryl Jones ◽  
Katherine Payne ◽  
Alexander Thompson ◽  
Suzanne M. M. Verstappen

Abstract Objectives To identify whether it is feasible to develop a mapping algorithm to predict presenteeism using multiattribute measures of health status. Methods Data were collected using a bespoke online survey in a purposive sample (n = 472) of working individuals with a self-reported diagnosis of Rheumatoid arthritis (RA). Survey respondents were recruited using an online panel company (ResearchNow). This study used data captured using two multiattribute measures of health status (EQ5D-5 level; SF6D) and a measure of presenteeism (WPAI, Work Productivity Activity Index). Statistical correlation between the WPAI and the two measures of health status (EQ5D-5 level; SF6D) was assessed using Spearman’s rank correlation. Five regression models were estimated to quantify the relationship between WPAI and predict presenteeism using health status. The models were specified based in index and domain scores and included covariates (age; gender). Estimated and observed presenteeism were compared using tenfold cross-validation and evaluated using Root mean square error (RMSE). Results A strong and negative correlation was found between WPAI and: EQ5D-5 level and WPAI (r = − 0.64); SF6D (r =− 0.60). Two models, using ordinary least squares regression were identified as the best performing models specifying health status using: SF6D domains with age interacted with gender (RMSE = 1.7858); EQ5D-5 Level domains and age interacted with gender (RMSE = 1.7859). Conclusions This study provides indicative evidence that two existing measures of health status (SF6D and EQ5D-5L) have a quantifiable relationship with a measure of presenteeism (WPAI) for an exemplar application of working individuals with RA. A future study should assess the external validity of the proposed mapping algorithms.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sonica Singhal ◽  
Sarah Orr ◽  
Harkirat Singh ◽  
Menaka Shanmuganantha ◽  
Heather Manson

Abstract Background Hospitals’ emergency rooms (ERs) are generally the first point of contact of domestic violence and abuse (DVA) victims to the health care system. For efficient management and resource allocation for ERs to manage DVA-related emergencies in Canada, it is important to quantify and assess the pattern of these visits. Methods Aggregate DVA-related ER visits data, using relevant ICD-10-CA codes, from 2012 to 2016 were retrieved from IntelliHealth Ontario. The 2011 ON-Marg (Ontario Marginalization) indices were linked at the Dissemination Area level to ER data. Descriptive analyses including total number and rate of visits per 100,000 people were calculated, stratified by age and sex. The Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were also assessed. Results From 2012 to 2016, 10,935 (81.2% by females and 18.8% by males) DVA-related visits were made to ERs in Ontario. An annual average of 25.5 visits per 100,000 females and 6.1 visits per 100,000 males was observed. Residential instability and deprivation were significant predictors of DVA-related ER visits. No particular site of injury was indicated in 38.5% of visits, 24.7% presented with cranio-maxillofacial (CMF) trauma in isolation, 28.9% presented with non-CMF injuries, and 7.9% visits presented with both CMF and non-CMF injuries. Conclusion This study identified that the burden of DVA-related ER visits is large enough to warrant timely public health interventions, and observed that certain populations in Ontario experience more DVA and/or are more prone to its impact. Our findings have important implications for various stakeholders involved in planning and implementing relevant policies and programs.


Author(s):  
Ian Howard ◽  
Peter Cameron ◽  
Maaret Castrén ◽  
Lee Wallis ◽  
Veronica Lindström

ABSTRACT Background Quality Indicator (QI) appraisal protocols are a novel methodology that combines multiple appraisal methods to comprehensively assess the "appropriateness" of QIs for a particular healthcare setting. However, they remain inadequately explored compared to the single appraisal method approach. This paper aimed to describe and test a QI appraisal protocol versus the single method approach, against a series of QIs potentially relevant to the South African Prehospital Emergency Care setting. Methods An appraisal protocol was developed consisting of two categorical-based appraisal methods, combined with the qualitative analysis of the discussion generated during the consensus application of each method. The output of the protocol was assessed and compared with the application and output of each method. Inter-rater reliability of each particular method was evaluated prior to group consensus rating. Variation in the number of non-valid QIs and the proportion of non-valid QIs identified between each method and the protocol were compared and assessed. Results There was mixed IRR of the individual methods. There was similarly low to moderate correlation of the results obtained between the particular methods (Spearman’s rank correlation=0.42,p&lt;0.001). From a series of 104 QIs, 11 non-valid QIs were identified that were shared between the individual methods. A further 19 non-valid QIs were identified and not shared by each method, highlighting the benefits of a multi-method approach. The outcomes were additionally evident in the group discussion analysis, which in and of itself added further input that would not have otherwise been captured by the individual methods alone. Conclusion The utilization of a multi-method appraisal protocol offers multiple benefits, when compared to the single appraisal approach, and can provide the confidence that the outcomes of the appraisal will ensure a strong foundation on which the QI framework can be successfully implemented.


2021 ◽  
Vol 10 (Supplement_1) ◽  
Author(s):  
M Stratinaki ◽  
K Milaki ◽  
S Stavrakis ◽  
M Pitarokoilis ◽  
E Charitakis ◽  
...  

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Hospitalization due to acute coronary syndromes (ACS) usually is the occasion that leads to diagnosis of type 2 diabetes mellitus (T2DM). Current literature suggests that the severity of the ACS could be associated with the presence and the severity of DM. Purpose To study the reliability of HbA1c in the diagnosis of T2DM in the acute phase of ACS, as well as the presence of possible correlation between the HbA1c and the severity of ACS. Methods We evaluated 160 consecutive patients admitted due to ACS. HbA1c was measured on day 1 and day 90. HbA1c &gt;6.5% was used to diagnose T2DM and HbA1c 5.7-6.4% was used to diagnose pre-diabetes. The severity of ACS was assessed via Gensini score. Results are interpreted as mean ± SD. Comparisons were made by one way ANOVA(p &lt; 0.05 was regarded statistically significant).Spearman’s rank correlation was used to study the correlation between Gensini score and the other parameters. Results Mean age was 59.73 ± 12.21 years. 103/160(64.37%) were male and 57/160(35.63%) were female. 19/160(11.87%) were diagnosed as STEMI and 141/160(88.13%) as NSTEMI. Mean BMI was 29.55 ± 8.41 kg/m2 and mean Hb 12.62 ± 2.08 g/dl. On day 1, 43/160 (26.87%) had HbA1c &gt; 6.5% and 41/160(25.62%) HbA1c 5.7-6.4%. On day 90, 28/160 (17.5%) had HbA1c &gt; 6.5% and 52/160(32.5%) HbA1c 5.7-6.4%. Gensini score varied between 0-144 with mean value 40.26 ±35.9. A strong correlation was found between Gensini score and HbA1c on admission as well as on day 90 (rho-0.36, p &lt; 0.05 and rho = 0.32, p &lt; 0.05 respectively). Conclusion HbA1c seems to be reliable in the identification of pre-diabetes but not T2DM in the acute phase of ACS. The correlation of the severity between ACS and HbA1c seems to relate with the worst prognosis of T2DM patients.


Author(s):  
Heming Jia ◽  
Kangjian Sun ◽  
Wanying Zhang ◽  
Xin Leng

AbstractChimp optimization algorithm (ChOA) is a recently proposed metaheuristic. Interestingly, it simulates the social status relationship and hunting behavior of chimps. Due to the more flexible and complex application fields, researchers have higher requirements for native algorithms. In this paper, an enhanced chimp optimization algorithm (EChOA) is proposed to improve the accuracy of solutions. First, the highly disruptive polynomial mutation is used to initialize the population, which provides the foundation for global search. Next, Spearman’s rank correlation coefficient of the chimps with the lowest social status is calculated with respect to the leader chimp. To reduce the probability of falling into the local optimum, the beetle antennae operator is used to improve the less fit chimps while gaining visual capability. Three strategies enhance the exploration and exploitation of the native algorithm. To verify the function optimization performance, EChOA is comprehensively analyzed on 12 classical benchmark functions and 15 CEC2017 benchmark functions. Besides, the practicability of EChOA is also highlighted by three engineering design problems and training multilayer perceptron. Compared with ChOA and five state-of-the-art algorithms, the statistical results show that EChOA has strong competitive capabilities and promising prospects.


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