-
The Lancet. Global Health Jul 2023
Topics: Humans; Female; Peripartum Period; Postpartum Hemorrhage; Risk Factors; Retrospective Studies; Maternal Mortality
PubMed: 37349041
DOI: 10.1016/S2214-109X(23)00259-0 -
The Lancet. Global Health Feb 2024The reduction of maternal mortality and the promotion of maternal health and wellbeing are complex tasks. This Series paper analyses the distal and proximal determinants... (Review)
Review
The reduction of maternal mortality and the promotion of maternal health and wellbeing are complex tasks. This Series paper analyses the distal and proximal determinants of maternal health, as well as the exposures, risk factors, and micro-correlates related to maternal mortality. This paper also examines the relationship between these determinants and the gradual shift over time from a pattern of high maternal mortality to a pattern of low maternal mortality (a phenomenon described as the maternal mortality transition). We conducted two systematic reviews of the literature and we analysed publicly available data on indicators related to the Sustainable Development Goals, specifically, estimates prepared by international organisations, including the UN and the World Bank. We considered 23 frameworks depicting maternal health and wellbeing as a multifactorial process, with superdeterminants that broadly affect women's health and wellbeing before, during, and after pregnancy. We explore the role of social determinants of maternal health, individual characteristics, and health-system features in the production of maternal health and wellbeing. This paper argues that the preventable deaths of millions of women each decade are not solely due to biomedical complications of pregnancy, childbirth, and the postnatal period, but are also tangible manifestations of the prevailing determinants of maternal health and persistent inequities in global health and socioeconomic development. This paper underscores the need for broader, multipronged actions to improve maternal health and wellbeing and accelerate sustainable reductions in maternal mortality. For women who have pregnancy, childbirth, or postpartum complications, the health system provides a crucial opportunity to interrupt the chain of events that can potentially end in maternal death. Ultimately, expanding the health sector ecosystem to mitigate maternal health determinants and tailoring the configuration of health systems to counter the detrimental effects of eco-social forces, including though increased access to quality-assured commodities and services, are essential to improve maternal health and wellbeing and reduce maternal mortality.
Topics: Pregnancy; Female; Humans; Maternal Health; Maternal Mortality; Ecosystem; Maternal Health Services; Women's Health
PubMed: 38070536
DOI: 10.1016/S2214-109X(23)00468-0 -
Annals of Epidemiology Aug 2023Since the start of the COVID-19 pandemic, countries have scrambled to set up data collection and dissemination pipelines for various online datasets. This study aims to... (Review)
Review
PURPOSE
Since the start of the COVID-19 pandemic, countries have scrambled to set up data collection and dissemination pipelines for various online datasets. This study aims to evaluate the reliability of the preliminary COVID-19 mortality data from Serbia, which has been included in major COVID-19 databases and utilized for research purposes worldwide.
METHODS
Discrepancies between the preliminary mortality data and the final mortality data in Serbia were analyzed. The preliminary data were reported through an emergency-necessitated system, while the final data were generated by the regular vital statistics pipeline. We identified databases that include these data and conducted a literature review of articles that utilized them.
RESULTS
The number of deaths due to COVID-19 in Serbia, as reported preliminarily, does not align with the final death toll, which is more than three times higher. Our literature review identified at least 86 studies that were impacted by these problematic data.
CONCLUSIONS
We strongly advise researchers to disregard the preliminary COVID-19 mortality data from Serbia due to the significant discrepancies with the final data. We recommend validating any preliminary data using excess mortality if all-cause mortality data are available.
Topics: Humans; COVID-19; Mortality; Pandemics; Reproducibility of Results; Serbia
PubMed: 37196849
DOI: 10.1016/j.annepidem.2023.05.006 -
The Lancet. Public Health Sep 2023
Topics: Humans; Mexico; Mortality, Premature; Socioeconomic Factors
PubMed: 37633671
DOI: 10.1016/S2468-2667(23)00177-9 -
Arquivos Brasileiros de Cardiologia 2023Previous studies have identified inequalities in the variation of mortality rates from ischemic heart disease (IHD) and cerebrovascular disease (CBVD) when comparing...
BACKGROUND
Previous studies have identified inequalities in the variation of mortality rates from ischemic heart disease (IHD) and cerebrovascular disease (CBVD) when comparing regions with different levels of socioeconomic development indicators.
OBJECTIVE
To analyze the variation in IHD and CBVD mortality rates and economic development, evaluated by the sociodemographic index (SDI) and social vulnerability index (SVI) in Brazil over a period of 20 years.
METHODS
Ecological study of time series of crude and standardized mortality rates (direct method, based on the Brazilian population in year 2000) from IHD and CBVD by sex and Federative Unit (FU) between 2000 and 2019, compared using the SDI and SVI.
RESULTS
There was an improvement in SDI and SVI concomitantly to a reduction in age-standardized mortality rate from IHD and CBVD in the country; however, this occurred unevenly across the FUs. The FUs with the best socioeconomic indicators had the greatest reduction in mortality rates.
DISCUSSION
The variations in mortality rates from IHD and CBVD, compared using variations in socioeconomic development, are aligned with those from previous studies, but the present study goes further by including the indicators SDI and SVI in the comparison. The limitations include the observational nature of the study, the use of databases, and the vulnerability to ecological bias.
CONCLUSION
The observed data raise the hypothesis that the improvement in socioeconomic conditions is one of the factors responsible for the reduction in mortality rates from IHD and CBVD.
Topics: Humans; Brazil; Cerebrovascular Disorders; Myocardial Ischemia; Socioeconomic Factors; Time Factors; Mortality
PubMed: 37971046
DOI: 10.36660/abc.20220832 -
American Journal of Health Promotion :... Jul 2023In the United States, mortality due to alcohol, opioid overdose, and suicide has increased dramatically in the last decades. These deaths of despair have been the focus...
In the United States, mortality due to alcohol, opioid overdose, and suicide has increased dramatically in the last decades. These deaths of despair have been the focus of recent and fast-growing literature. Yet little is known about the factors that are involved in despair. This article moves this area of research forward by highlighting the role that physical pain plays in the deaths of despair. This piece critically analyses the link between physical pain, the psychological states that precede pain, and the premature mortality that follows physical pain as well as the bidirectional relationships among these aspects.
Topics: Humans; United States; Pain; Suicide; Mortality, Premature
PubMed: 37199706
DOI: 10.1177/08901171231177849 -
Global Health Action Dec 2023Half of global under-five mortalities is neonatal. The highest rates are found in low-income countries such as Ethiopia. Ethiopia has made progress in reducing...
BACKGROUND
Half of global under-five mortalities is neonatal. The highest rates are found in low-income countries such as Ethiopia. Ethiopia has made progress in reducing under-five mortality, but neonatal mortality remains high. Evidence collected continuously at the community level is crucial for understanding the trends and causes of neonatal mortality.
OBJECTIVES
To analyse the trends and causes of neonatal mortality at the Kilte-Awlelo Health and Demographic Surveillance System (KAHDSS) site in Ethiopia from 2010 to 2017.
METHODS
A descriptive study was conducted using data from neonates born between 2010 and 2017 at the KAHDSS site. Data were collected using interviewer-administered questionnaires. Causes of death were examined, and neonatal mortality trends were described using simple linear regression.
RESULTS
The overall average neonatal mortality rate was 17/1000 live births (LBs). The rate increased from 12 per 1000 LBs in 2010 to 15 per 1000 LBs in 2017. The majority of neonatal deaths occurred during the first week of life, and more than one-half died at home. The leading causes were sepsis, pre-term birth (including respiratory distress), disease related to the perinatal period, birth asphyxia, and neonatal pneumonia.
CONCLUSIONS
The high neonatal mortality in Ethiopia requires urgent attention and action. Sepsis, preterm birth, perinatal diseases, asphyxia, and neonatal pneumonia are the leading causes of death in neonates. Facility- and community-based health services should target the leading causes of neonatal deaths.
Topics: Pregnancy; Female; Infant, Newborn; Humans; Perinatal Death; Ethiopia; Asphyxia; Cause of Death; Premature Birth; Infant Mortality; Sepsis; Pneumonia
PubMed: 38126362
DOI: 10.1080/16549716.2023.2289710 -
JAMA Network Open May 2024Higher adherence to the Mediterranean diet has been associated with reduced risk of all-cause mortality, but data on underlying molecular mechanisms over long follow-up...
IMPORTANCE
Higher adherence to the Mediterranean diet has been associated with reduced risk of all-cause mortality, but data on underlying molecular mechanisms over long follow-up are limited.
OBJECTIVES
To investigate Mediterranean diet adherence and risk of all-cause mortality and to examine the relative contribution of cardiometabolic factors to this risk reduction.
DESIGN, SETTING, AND PARTICIPANTS
This cohort study included initially healthy women from the Women's Health Study, who had provided blood samples, biomarker measurements, and dietary information. Baseline data included self-reported demographics and a validated food-frequency questionnaire. The data collection period was from April 1993 to January 1996, and data analysis took place from June 2018 to November 2023.
EXPOSURES
Mediterranean diet score (range, 0-9) was computed based on 9 dietary components.
MAIN OUTCOME AND MEASURES
Thirty-three blood biomarkers, including traditional and novel lipid, lipoprotein, apolipoprotein, inflammation, insulin resistance, and metabolism measurements, were evaluated at baseline using standard assays and nuclear magnetic resonance spectroscopy. Mortality and cause of death were determined from medical and death records. Cox proportional hazards regression was used to calculate hazard ratios (HRs) for Mediterranean diet adherence and mortality risk, and mediation analyses were used to calculate the mediated effect of different biomarkers in understanding this association.
RESULTS
Among 25 315 participants, the mean (SD) baseline age was 54.6 (7.1) years, with 329 (1.3%) Asian women, 406 (1.6%) Black women, 240 (0.9%) Hispanic women, 24 036 (94.9%) White women, and 95 (0.4%) women with other race and ethnicity; the median (IQR) Mediterranean diet adherence score was 4.0 (3.0-5.0). Over a mean (SD) of 24.7 (4.8) years of follow-up, 3879 deaths occurred. Compared with low Mediterranean diet adherence (score 0-3), adjusted risk reductions were observed for middle (score 4-5) and upper (score 6-9) groups, with HRs of 0.84 (95% CI, 0.78-0.90) and 0.77 (95% CI, 0.70-0.84), respectively (P for trend < .001). Further adjusting for lifestyle factors attenuated the risk reductions, but they remained statistically significant (middle adherence group: HR, 0.92 [95% CI, 0.85-0.99]; upper adherence group: HR, 0.89 [95% CI, 0.82-0.98]; P for trend = .001). Of the biomarkers examined, small molecule metabolites and inflammatory biomarkers contributed most to the lower mortality risk (explaining 14.8% and 13.0%, respectively, of the association), followed by triglyceride-rich lipoproteins (10.2%), body mass index (10.2%), and insulin resistance (7.4%). Other pathways, including branched-chain amino acids, high-density lipoproteins, low-density lipoproteins, glycemic measures, and hypertension, had smaller contributions (<3%).
CONCLUSIONS AND RELEVANCE
In this cohort study, higher adherence to the Mediterranean diet was associated with 23% lower risk of all-cause mortality. This inverse association was partially explained by multiple cardiometabolic factors.
Topics: Humans; Diet, Mediterranean; Female; Middle Aged; Biomarkers; Cohort Studies; Patient Compliance; Mortality; Cause of Death; Aged; Adult; Proportional Hazards Models; Risk Factors
PubMed: 38819819
DOI: 10.1001/jamanetworkopen.2024.14322 -
Medical Care Jul 2023The COVID-19 pandemic resulted in excess mortality among the general US population and at Veterans Health Administration (VHA) facilities. It is critical to understand...
IMPORTANCE
The COVID-19 pandemic resulted in excess mortality among the general US population and at Veterans Health Administration (VHA) facilities. It is critical to understand the characteristics of facilities that experienced the highest and lowest pandemic-related mortality to inform future mitigation efforts.
OBJECTIVE
To identify facility-level excess mortality during the pandemic and to correlate these estimates with facility characteristics and community-wide rates of COVID-19 burden.
DESIGN
We used pre-pandemic data to estimate mortality risk prediction models using 5-fold cross-validation and Poisson quasi-likelihood regression. We then estimated excess mortality and observed versus expected (O/E) mortality ratios by the VHA facility from March to December 2020. We examined facility-level characteristics by excess mortality quartile.
PARTICIPANTS
Overall, there were 11.4 million VHA enrollees during 2016 and 2020.
MAIN MEASURES
Facility-level O/E mortality ratios and excess all-cause mortality.
RESULT
VHA-enrolled veterans experienced 52,038 excess deaths from March to December 2020, equating to 16.8% excess mortality. Facility-specific rates ranged from -5.5% to +63.7%. Facilities in the lowest quartile for excess mortality experienced fewer COVID-19 deaths (0.7-1.51, P <0.001) and cases (52.0-63.0, P =0.002) per 1,000 population compared with the highest quartile. The highest quartile facilities had more hospital beds (276.7-187.6, P =0.024) and a higher percent change in the share of visits conducted via telehealth from 2019 to 2020 (183%-133%, P <0.008).
CONCLUSIONS
There was a large variation in mortality across VHA facilities during the pandemic, which was only partially explained by the local COVID-19 burden. Our work provides a framework for large health care systems to identify changes in facility-level mortality during a public health emergency.
Topics: Humans; COVID-19; Pandemics; Veterans Health; Veterans; Mortality
PubMed: 37219062
DOI: 10.1097/MLR.0000000000001866 -
Scientific Reports Oct 2023This study intends to predict in-hospital and 6-month mortality, as well as 30-day and 90-day hospital readmission, using Machine Learning (ML) approach via conventional...
This study intends to predict in-hospital and 6-month mortality, as well as 30-day and 90-day hospital readmission, using Machine Learning (ML) approach via conventional features. A total of 737 patients remained after applying the exclusion criteria to 1101 heart failure patients. Thirty-four conventional features were collected for each patient. First, the data were divided into train and test cohorts with a 70-30% ratio. Then train data were normalized using the Z-score method, and its mean and standard deviation were applied to the test data. Subsequently, Boruta, RFE, and MRMR feature selection methods were utilized to select more important features in the training set. In the next step, eight ML approaches were used for modeling. Next, hyperparameters were optimized using tenfold cross-validation and grid search in the train dataset. All model development steps (normalization, feature selection, and hyperparameter optimization) were performed on a train set without touching the hold-out test set. Then, bootstrapping was done 1000 times on the hold-out test data. Finally, the obtained results were evaluated using four metrics: area under the ROC curve (AUC), accuracy (ACC), specificity (SPE), and sensitivity (SEN). The RFE-LR (AUC: 0.91, ACC: 0.84, SPE: 0.84, SEN: 0.83) and Boruta-LR (AUC: 0.90, ACC: 0.85, SPE: 0.85, SEN: 0.83) models generated the best results in terms of in-hospital mortality. In terms of 30-day rehospitalization, Boruta-SVM (AUC: 0.73, ACC: 0.81, SPE: 0.85, SEN: 0.50) and MRMR-LR (AUC: 0.71, ACC: 0.68, SPE: 0.69, SEN: 0.63) models performed the best. The best model for 3-month rehospitalization was MRMR-KNN (AUC: 0.60, ACC: 0.63, SPE: 0.66, SEN: 0.53) and regarding 6-month mortality, the MRMR-LR (AUC: 0.61, ACC: 0.63, SPE: 0.44, SEN: 0.66) and MRMR-NB (AUC: 0.59, ACC: 0.61, SPE: 0.48, SEN: 0.63) models outperformed the others. Reliable models were developed in 30-day rehospitalization and in-hospital mortality using conventional features and ML techniques. Such models can effectively personalize treatment, decision-making, and wiser budget allocation. Obtained results in 3-month rehospitalization and 6-month mortality endpoints were not astonishing and further experiments with additional information are needed to fetch promising results in these endpoints.
Topics: Humans; Patient Readmission; Hospital Mortality; Machine Learning; Heart Failure
PubMed: 37907666
DOI: 10.1038/s41598-023-45925-3