scholarly journals The COVID-19 mortality effects of underlying health conditions in India: a modelling study

2020 ◽  
Author(s):  
Paul Novosad ◽  
Radhika Jain ◽  
Alison Campion ◽  
Sam Asher
Keyword(s):  
Risk Factors ◽  
Heart Disease ◽  
Kidney Disease ◽  
Mortality Risk ◽  
Age Distribution ◽  
Chronic Respiratory Disease ◽  
Health Conditions ◽  
Middle Income ◽  
Middle Income Countries ◽  
Chronic Heart Disease

ABSTRACTObjectiveTo model how known COVID-19 comorbidities will affect mortality rates and the age distribution of mortality in a large lower middle income country (India), as compared with a high income country (England), and to identify which health conditions drive any differences.DesignModelling study.SettingEngland and India.Participants1,375,548 respondents aged 18 to 99 to the District Level Household Survey-4 and Annual Health Survey in India. Additional information on health condition prevalence on individuals aged 18 to 99 was obtained from the Health Survey for England and the Global Burden of Diseases, Risk Factors, and Injuries Studies (GBD).Main outcome measuresThe primary outcome was the proportional increase in age-specific mortality in each country due to the prevalence of each COVID-19 mortality risk factor (diabetes, hypertension, obesity, chronic heart disease, respiratory illness, kidney disease, liver disease, and cancer, among others). The combined change in overall mortality and the share of deaths under 60 from the combination of risk factors was estimated in each country.ResultsRelative to England, Indians have higher rates of diabetes (10.6% vs. 8.5%), chronic respiratory disease (4.8% vs. 2.5%), and kidney disease (9.7% vs. 5.6%), and lower rates of obesity (4.4% vs. 27.9%), chronic heart disease (4.4% vs. 5.9%), and cancer (0.3% vs. 2.8%). Population COVID-19 mortality in India relative to England is most increased by diabetes (+5.4%) and chronic respiratory disease (+2.3%), and most reduced by obesity (−9.7%), cancer (−3.2%), and chronic heart disease (−1.9%). Overall, comorbidities lower mortality in India relative to England by 9.7%. Accounting for demographics and population health explains a third of the difference in share of deaths under age 60 between the two countries.ConclusionsKnown COVID-19 health risk factors are not expected to have a large effect on aggregate mortality or its age distribution in India relative to England. The high share of COVID-19 deaths from people under 60 in low- and middle-income countries (LMICs) remains unexplained. Understanding mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is essential for understanding differential mortality.SUMMARY BOXWhat is already known on this topicCOVID-19 infections in low- and middle-income countries (LMICs) are rising rapidly, with the burden of mortality concentrated at much younger ages than in rich countries.A range of pre-existing health conditions can increase the severity of COVID-19 infections.It is feared that poor population health may worsen the severity of the pandemic in LMICs.What this study addsThe COVID-19 comorbidities that have been studied to date may have only a very small effect on aggregate mortality in India relative to England and do not shift the mortality burden toward lower ages at all.India’s younger demographics can explain only a third of the substantial difference in the share of deaths under age 60 between India and England.However, mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is unknown and research on this topic is urgently needed.

scholarly journals COVID-19 mortality effects of underlying health conditions in India: a modelling study

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e043165
Author(s):  
Paul Novosad ◽  
Radhika Jain ◽  
Alison Campion ◽  
Sam Asher
Keyword(s):  
Risk Factors ◽  
Heart Disease ◽  
Respiratory Disease ◽  
Health Survey ◽  
Mortality Risk ◽  
Age Distribution ◽  
Chronic Respiratory Disease ◽  
Health Conditions ◽  
Middle Income ◽  
Chronic Heart Disease

ObjectiveTo model how known COVID-19 comorbidities affect mortality rates and the age distribution of mortality in a large lower-middle-income country (India), and to identify which health conditions drive differences with high-income countries.DesignModelling study.SettingEngland and India.ParticipantsIndividual data were obtained from the fourth round of the District Level Household Survey and Annual Health Survey in India, and aggregate data were obtained from the Health Survey for England and the Global Burden of Disease, Risk Factors and Injuries Studies.Main outcome measuresThe primary outcome was the modelled age-specific mortality in each country due to each COVID-19 mortality risk factor (diabetes, hypertension, obesity and respiratory illness, among others). The change in overall mortality and in the share of deaths under age 60 from the combination of risk factors was estimated in each country.ResultsRelative to England, Indians have higher rates of diabetes (10.6% vs 8.5%) and chronic respiratory disease (4.8% vs 2.5%), and lower rates of obesity (4.4% vs 27.9%), chronic heart disease (4.4% vs 5.9%) and cancer (0.3% vs 2.8%). Population COVID-19 mortality in India, relative to England, is most increased by uncontrolled diabetes (+5.67%) and chronic respiratory disease (+1.88%), and most reduced by obesity (−5.47%), cancer (−3.65%) and chronic heart disease (−1.20%). Comorbidities were associated with a 6.26% lower risk of mortality in India compared with England. Demographics and population health explain a third of the difference in share of deaths under age 60 between the two countries.ConclusionsKnown COVID-19 health risk factors are not expected to have a large effect on mortality or its age distribution in India relative to England. The high share of COVID-19 deaths from people under age 60 in low- and middle-income countries (LMICs) remains unexplained. Understanding the mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is essential for understanding differential mortality.

scholarly journals The incidence of and risk factors for late presentation of childhood chronic kidney disease: A systematic review and meta-analysis

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244709
Author(s):  
Lucy Plumb ◽  
Emily J. Boother ◽  
Fergus J. Caskey ◽  
Manish D. Sinha ◽  
Yoav Ben-Shlomo
Keyword(s):  
Risk Factors ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Kidney Failure ◽  
Meta Analysis ◽  
Late Presentation ◽  
Cochrane Library ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low Middle Income Countries

Background When detected early, inexpensive measures can slow chronic kidney disease progression to kidney failure which, for children, confers significant morbidity and impacts growth and development. Our objective was to determine the incidence of late presentation of childhood chronic kidney disease and its associated risk factors. Methods We searched MEDLINE, Embase, PubMed, Web of Science, Cochrane Library and CINAHL, grey literature and registry websites for observational data describing children <21 years presenting to nephrology services, with reference to late presentation (or synonyms thereof). Independent second review of eligibility, data extraction, and risk of bias was undertaken. Meta-analysis was used to generate pooled proportions for late presentation by definition and investigate risk factors. Meta-regression was undertaken to explore heterogeneity. Results Forty-five sources containing data from 30 countries were included, comprising 19,339 children. Most studies (37, n = 15,772) described children first presenting in kidney failure as a proportion of the chronic kidney disease population (mean proportion 0.43, 95% CI 0.34–0.54). Using this definition, the median incidence was 2.1 (IQR 0.9–3.9) per million age-related population. Risk associations included non-congenital disease and older age. Studies of hospitalised patients, or from low- or middle-income countries, that had older study populations than high-income countries, had higher proportions of late presentation. Conclusions Late presentation is a global problem among children with chronic kidney disease, with higher proportions seen in studies of hospitalised children or from low/middle-income countries. Children presenting late are older and more likely to have non-congenital kidney disease than timely presenting children. A consensus definition is important to further our understanding and local populations should identify modifiable barriers beyond age and disease to improve access to care.

scholarly journals Risk‐Attributable Burden of Ischemic Heart Disease in 137 Low‐ and Middle‐Income Countries From 2000 to 2019

2021 ◽  
Author(s):  
Chenran Wang ◽  
Yanghua Sun ◽  
Di Jiang ◽  
Chunping Wang ◽  
Shiwei Liu
Keyword(s):  
Risk Factors ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Low Income ◽  
Population Attributable Fraction ◽  
Attributable Fraction ◽  
Low Income Countries ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low And Middle Income

Background Ischemic heart disease (IHD) imposes the greatest disease burden globally, especially in low‐ and middle‐income countries (LMICs). We aim to examine the population‐attributable fraction and risk‐attributable death and disability‐adjusted life years (DALYs) for IHD in 137 low‐ and middle‐income countries. Methods and Results Using comparative risk assessment framework from the 2019 Global Burden of Disease study, the population‐attributable fraction and IHD burden (death and DALYs) attributable to risk factors in low‐income countries, lower‐middle‐income countries (LMCs), and upper‐middle‐income countries were assessed from 2000 to 2019. In 2019, the population‐attributable fraction (%) of IHD deaths in relation to all modifiable risk factors combined was highest in lower‐middle‐income countries (94.2; 95% uncertainty interval, 91.9–96.2), followed by upper‐middle‐income countries (93.5; 90.4–95.8) and low‐income countries (92.5; 90.0–94.7). There was a >13‐fold difference between Peru and Uzbekistan in age‐standardized rates (per 100 000) of attributable death (44.3 versus 660.4) and DALYs (786.7 versus 10506.1). Dietary risks accounted for the largest proportion of IHD’s behavioral burden in low‐ and middle‐income countries, primarily attributable to diets low in whole grains. High systolic blood pressure and high low‐density lipoprotein cholesterol remained the 2 leading causes of DALYs, with the former topping the list in 116 countries, while the latter led in 21 of the 137 countries. Compared with 2000 to 2010, the increases in risk‐attributable deaths and DALYs among upper‐middle income countries were slower from 2010 to 2019, while the trends in low‐income countries and lower‐middle income countries were opposite. Conclusions IHD’s attributable burden remains high in low‐ and middle‐income countries. Considerable heterogeneity was observed among different income‐classified regions and countries.

scholarly journals A Feature-Driven Decision Support System for Heart Disease Prediction Based on Fisher's Discriminant Ratio and Backpropagation Algorithm

2020 ◽  
Vol 11 (2) ◽  
pp. 65
Author(s):  
Muh Dimas Yudianto ◽  
Tresna Maulana Fahrudin ◽  
Aryo Nugroho
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Feature Selection ◽  
Heart Disease ◽  
Disease Classification ◽  
Classification Model ◽  
Backpropagation Algorithm ◽  
Middle Income ◽  
Know How ◽  
Middle Income Countries

Coronary heart disease included a group of cardiovascular, and it is a leading cause of death in low and middle-income countries. Risk factors for coronary heart disease are divided into two, namely primary and secondary risk factors. The need to identify characteristics or risk factors in heart disease patients by making the classification model. The modeling of heart disease classification to know how the system can able to reach the best prediction accuracy. Fisher's Discriminant Ratio is one of the methods for feature selection, which is used to get high discriminant features. While Backpropagation is one of the classification models to recognize patterns in heart disease patients. The experiment results showed that the accuracy of the classification model using 13 original features reached 92%. By reducing the features based on the score of the feature selection, then the lowest feature was removed from original features and left there were 12 features involved in the classification model which the accuracy increased to 93%. Furthermore, the results of determining the threshold (accuracy does not decrease continuously) and consider the effect of eliminating the lowest features that are considered quite fluctuating on accuracy. The accuracy reached 90% by eliminating the five lowest features and left eight existing features.

Risk Factors of Mortality Among Patients with Stroke in Low Middle-Income Countries:  A Series of 180 Patients

2020 ◽  
Author(s):  
Larrey Kamabu ◽  
Hervé Monka Lekuya ◽  
Bienvenu Muhindo Kasusula ◽  
Nicole Kavugho Mutimani ◽  
Louange Maha Kathaka ◽  
...  
Keyword(s):  
Risk Factors ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low Middle Income Countries

scholarly journals Maternal mortality in six low and lower-middle income countries from 2010 to 2018: risk factors and trends

2020 ◽  
Vol 17 (S3) ◽  
Author(s):  
Melissa Bauserman ◽  
Vanessa R. Thorsten ◽  
Tracy L. Nolen ◽  
Jackie Patterson ◽  
Adrien Lokangaka ◽  
...  
Keyword(s):  
Risk Factors ◽  
Maternal Mortality ◽  
Maternal Deaths ◽  
Middle Income ◽  
Maternal Risk ◽  
Live Births ◽  
Middle Income Countries ◽  
Risk Of Death ◽  
Increased Risk ◽  
Over Time

Abstract Background Maternal mortality is a public health problem that disproportionately affects low and lower-middle income countries (LMICs). Appropriate data sources are lacking to effectively track maternal mortality and monitor changes in this health indicator over time. Methods We analyzed data from women enrolled in the NICHD Global Network for Women’s and Children’s Health Research Maternal Newborn Health Registry (MNHR) from 2010 through 2018. Women delivering within research sites in the Democratic Republic of Congo, Guatemala, India (Nagpur and Belagavi), Kenya, Pakistan, and Zambia are included. We evaluated maternal and delivery characteristics using log-binomial models and multivariable models to obtain relative risk estimates for mortality. We used running averages to track maternal mortality ratio (MMR, maternal deaths per 100,000 live births) over time. Results We evaluated 571,321 pregnancies and 842 maternal deaths. We observed an MMR of 157 / 100,000 live births (95% CI 147, 167) across all sites, with a range of MMRs from 97 (76, 118) in the Guatemala site to 327 (293, 361) in the Pakistan site. When adjusted for maternal risk factors, risks of maternal mortality were higher with maternal age > 35 (RR 1.43 (1.06, 1.92)), no maternal education (RR 3.40 (2.08, 5.55)), lower education (RR 2.46 (1.54, 3.94)), nulliparity (RR 1.24 (1.01, 1.52)) and parity > 2 (RR 1.48 (1.15, 1.89)). Increased risk of maternal mortality was also associated with occurrence of obstructed labor (RR 1.58 (1.14, 2.19)), severe antepartum hemorrhage (RR 2.59 (1.83, 3.66)) and hypertensive disorders (RR 6.87 (5.05, 9.34)). Before and after adjusting for other characteristics, physician attendance at delivery, delivery in hospital and Caesarean delivery were associated with increased risk. We observed variable changes over time in the MMR within sites. Conclusions The MNHR is a useful tool for tracking MMRs in these LMICs. We identified maternal and delivery characteristics associated with increased risk of death, some might be confounded by indication. Despite declines in MMR in some sites, all sites had an MMR higher than the Sustainable Development Goals target of below 70 per 100,000 live births by 2030. Trial registration The MNHR is registered at NCT01073475.

scholarly journals Hierarchical disentanglement of contextual from compositional risk factors of diarrhoea among under-five children in low- and middle-income countries

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
A. Olalekan Uthman ◽  
Latifat Ibisomi
Keyword(s):  
Risk Factors ◽  
National Level ◽  
Cross Sectional ◽  
Middle Income ◽  
Contextual Risk ◽  
Under Five ◽  
Factors Associated ◽  
Under Five Children ◽  
Middle Income Countries ◽  
Low And Middle Income

AbstractSeveral studies have documented the burden and risk factors associated with diarrhoea in low and middle-income countries (LMIC). To the best of our knowledge, the contextual and compositional factors associated with diarrhoea across LMIC were poorly operationalized, explored and understood in these studies. We investigated multilevel risk factors associated with diarrhoea among under-five children in LMIC. We analysed diarrhoea-related information of 796,150 under-five children (Level 1) nested within 63,378 neighbourhoods (Level 2) from 57 LMIC (Level 3) using the latest data from cross-sectional and nationally representative Demographic Health Survey conducted between 2010 and 2018. We used multivariable hierarchical Bayesian logistic regression models for data analysis. The overall prevalence of diarrhoea was 14.4% (95% confidence interval 14.2–14.7) ranging from 3.8% in Armenia to 31.4% in Yemen. The odds of diarrhoea was highest among male children, infants, having small birth weights, households in poorer wealth quintiles, children whose mothers had only primary education, and children who had no access to media. Children from neighbourhoods with high illiteracy [adjusted odds ratio (aOR) = 1.07, 95% credible interval (CrI) 1.04–1.10] rates were more likely to have diarrhoea. At the country-level, the odds of diarrhoea nearly doubled (aOR = 1.88, 95% CrI 1.23–2.83) and tripled (aOR = 2.66, 95% CrI 1.65–3.89) among children from countries with middle and lowest human development index respectively. Diarrhoea remains a major health challenge among under-five children in most LMIC. We identified diverse individual-level, community-level and national-level factors associated with the development of diarrhoea among under-five children in these countries and disentangled the associated contextual risk factors from the compositional risk factors. Our findings underscore the need to revitalize existing policies on child and maternal health and implement interventions to prevent diarrhoea at the individual-, community- and societal-levels. The current study showed how the drive to the attainment of SDGs 1, 2, 4, 6 and 10 will enhance the attainment of SDG 3.

Mortality and associated risk factors in diabetics

1985 ◽  
Vol 110 (4_Suppl) ◽  
pp. S21-S26 ◽  
Author(s):  
R. J. Jarrett ◽  
M. J. Shipley
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Mortality Risk ◽  
Mortality Rates ◽  
Potential Risk Factors ◽  
Diabetic Population ◽  
Associated Risk Factors ◽  
The Relationship

Summary. In 168 male diabetics aged 40-64 years participating in the Whitehall Study, ten-year age adjusted mortality rates were significantly higher than in non-diabetics for all causes, coronary heart disease, all cardiovascular disease and, in addition, causes other than cardiovascular. Mortality rates were not significantly related to known duration of the diabetes. The predictive effects of several major mortality risk factors were similar in diabetics and non-diabetics. Excess mortality rates in the diabetics could not be attributed to differences in levels of blood pressure or any other of the major risk factors measured. Key words: diabetics; mortality rates; risk factors; coronary heart disease. There are many studies documenting higher mortality rates - particularly from cardiovascular disease -in diabetics compared with age and sex matched diabetics from the same population (see Jarrett et al. (1982) for review). However, there is sparse information relating potential risk factors to subsequent mortality within a diabetic population, information which might help to explain the increased mortality risk and also suggest preventive therapeutic approaches. In the Whitehall Study, a number of established diabetics participated in the screening programme and data on mortality rates up to ten years after screening are available. We present here a comparison of diabetics and non-diabetics in terms of relative mortality rates and the influence of conventional risk factors as well as an analysis of the relationship between duration of diabetes and mortality risk.

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