In 2021, COVID-19 caused around **** million deaths in upper-middle-income countries, making it the third leading cause of death. The leading causes of death in upper-middle-income countries that year were stroke and ischemic heart disease. This statistic displays the number of deaths from the leading causes of death in upper-middle-income countries in 2021.

In 2021, the leading causes of death in lower-middle income countries worldwide were COVID-19, ischemic heart disease, and stroke. That year, COVID-19 resulted in around 3.94 million deaths in lower-middle income countries, over a million more deaths than ischemic heart disease, the second leading cause of death for countries in this income group. This statistic displays the number of deaths for the leading causes of death in lower-middle income countries in 2021.

The average for 2022 based on 52 countries was 8.01 deaths per 1000 people. The highest value was in Bulgaria: 18.4 deaths per 1000 people and the lowest value was in the Maldives: 2.33 deaths per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

IntroductionAlthough child and adolescent health is the core of the global health agenda, the cause of death and its expected contribution to life expectancy (LE) among those aged 5–14 are under-researched across countries, especially in low- and middle-income countries (LMICs).MethodsDeath rates per 10 years age group including a 5–14-year-old group were calculated by the formula, which used the population and the number of deaths segmented by the cause of death and gender from the 2019 Global Burden of Disease (GBD) study. LE and cause-eliminated LE in 10-year intervals were calculated by using life tables.ResultsIn 2019, the global mortality rate for children and adolescents aged 5–14 years was 0.522 (0.476–0.575) per 1,000, and its LF was 71.377 years. In different-income regions, considerable heterogeneity remains in the ranking of cause of death aged 5–14 years. The top three causes of death in low-income countries (LICs) are enteric infections [0.141 (0.098–0.201) per 1,000], other infectious diseases [0.103 (0.073–0.148) per 1,000], and neglected tropical diseases and malaria [0.102 (0.054–0.172) per 1,000]. Eliminating these mortality rates can increase the life expectancy of the 5–14 age group by 0.085, 0.062, and 0.061 years, respectively. The top three causes of death in upper-middle income countries (upper MICs) are unintentional injuries [0.066 (0.061–0.072) per 1,000], neoplasm [0.046 (0.041–0.050) per 1,000], and transport injuries [0.045 (0.041–0.049) per 1,000]. Eliminating these mortality rates can increase the life expectancy of the 5–14 age group by 0.045, 0.031, and 0.030 years, respectively.ConclusionThe mortality rate for children and adolescents aged 5–14 years among LMICs remains high. Considerable heterogeneity was observed in the main causes of death among regions. According to the main causes of death at 5–14 years old in different regions and countries at different economic levels, governments should put their priority in tailoring their own strategies to decrease preventable mortality.

Minimum to maximum probability of death (45q15) on different levels of assignment of deaths with missing ethnicity: from assignment based on population proportion (0% re-assignment), to 10%, 20%, 30%, 40%, and 50% death re-assignment.

The COVID-19 pandemic has brought about massive declines in well-being around the world. This paper seeks to quantify and compare two important components of those losses—increased mortality and higher poverty—using years of human life as a common metric. The paper estimates that almost 20 million life-years were lost to COVID-19 by December 2020. Over the same period and by the most conservative definition, more than 120 million additional years were spent in poverty because of the pandemic. The mortality burden, whether estimated in lives or years of life lost, increases sharply with gross domestic product per capita. By contrast, the poverty burden declines with per capita national income when a constant absolute poverty line is used, or is uncorrelated with national income when a more relative approach is taken to poverty lines. In both cases, the poverty burden of the pandemic, relative to the mortality burden, is much higher for poor countries. The distribution of aggregate welfare losses—combining mortality and poverty and expressed in terms of life-years —depends on the choice of poverty line(s) and the relative weights placed on mortality and poverty. With a constant absolute poverty line and a relatively low welfare weight on mortality, poorer countries are found to bear a greater welfare loss from the pandemic. When poverty lines are set differently for poor, middle-income, and high-income countries and/or a greater welfare weight is placed on mortality, upper-middle-income and rich countries suffer the most.

The Accidental Death and Dismemberment (AD&D) insurance market is experiencing robust growth, driven by increasing awareness of the need for financial protection against unforeseen events and rising disposable incomes globally. The market's Compound Annual Growth Rate (CAGR) is estimated at approximately 5-7% between 2025 and 2033. This growth is fueled by several key factors. Firstly, the expanding middle class in developing economies is leading to a rise in demand for insurance products, including AD&D policies, offering crucial financial safety nets. Secondly, the increasing prevalence of workplace accidents and unforeseen circumstances underscores the importance of AD&D coverage. Furthermore, innovative product offerings, such as bundled AD&D insurance with other life insurance products or critical illness coverage, are driving market expansion. The rising adoption of digital distribution channels and online platforms is also simplifying access to AD&D policies, further fueling growth. Leading players like Allianz, Assicurazioni Generali, and MetLife, along with significant regional players in Asia and Europe, are actively shaping the market landscape through product diversification and strategic partnerships. However, certain restraints exist. Regulatory changes and stringent compliance requirements in various markets can impact operational costs and market penetration. Also, the inherent difficulty in accurately predicting accidental deaths and dismemberments can create challenges in accurate risk assessment and pricing. Despite these challenges, the long-term outlook for the AD&D insurance market remains positive, driven by the persistent need for financial security and the continued expansion of the global middle class. The market segmentation reflects varying levels of demand across geographic regions, driven by factors such as economic development, insurance penetration rates, and demographic trends. Strategic alliances and innovative product development are likely to define future competitive dynamics in this expanding market.

Background: In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. Methods: We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1000 admissions with 95% confidence intervals (95%CI). Findings: ur search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95%CI 3.4-4.7%]. The most common causes of mortality (deaths/1000 admissions) were infectious (12 [95%CI 9-14]); respiratory (9 [95%CI 5-13]); and gastrointestinal (9 [95%CI 6-11]). Common causes of admission (cases/1000 admissions) were respiratory (255 [95%CI 231-280]); infectious (214 [95%CI193-234]); and gastrointestinal (166 [95%CI 143-190]). We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Implications: Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

This statistic presents the death rates for the five leading causes of deaths among adolescents aged 10 to 19 years in each WHO region in 2015 (per 100,000 population). In low- and middle-income countries in Africa the leading cause of death among those aged 10 to 19 years was lower respiratory infections with a death rate of **** per 100,000 population. In high income WHO countries road injury was the leading cause of death among adolescents with a rate of ***. Road injury was the only cause to be in the five leading causes of death among adolescents in every WHO region.

ObjectiveThe aim of the study was to depict the global death burden of atrial fibrillation and/or flutter (AFF) between 1990 and 2019 and predict this burden in the next decade.MethodsWe retrieved annual death data on cases and rates of AFF between 1990 and 2019 from the Global Burden of Disease (GBD) Study 2019 and projected the trends for 2020–2029 by developing the Bayesian age-period-cohort model.ResultsThe global number of deaths from AFF increased from 117,038.00 in 1990 to 315,336.80 in 2019. This number is projected to reach 404,593.40 by 2029. The age-standardized mortality rates (ASMRs) of AFF have increased significantly in low- to middle-sociodemographic index (SDI) regions, which will surpass that in high SDI regions and reach above 4.60 per 100,000 by 2029. Globally, women have a higher ASMR than men, which is largely attributed to disproportionately higher mortality in women than men in lower SDI regions. Notably, AFF-related premature mortality continues to worsen worldwide. A pandemic of high systolic blood pressure and high body mass index (BMI) largely contributes to AFF-associated death. In particular, low- to middle-SDI regions and younger populations are increasingly affected by the rapidly growing current and future risk of high BMI.ConclusionThe global death burden of AFF in low-income countries and younger generations have not been sufficiently controlled in the past and will continue growing in the future, which is largely attributed to metabolic risks, particularly for high BMI. There is an urgent need to implement effective measures to control AFF-related mortality.

IntroductionOur study explores how New York City (NYC) communities of various socioeconomic strata were uniquely impacted by the COVID-19 pandemic.MethodsNew York City ZIP codes were stratified into three bins by median income: high-income, middle-income, and low-income. Case, hospitalization, and death rates obtained from NYCHealth were compared for the period between March 2020 and April 2022.ResultsCOVID-19 transmission rates among high-income populations during off-peak waves were higher than transmission rates among low-income populations. Hospitalization rates among low-income populations were higher during off-peak waves despite a lower transmission rate. Death rates during both off-peak and peak waves were higher for low-income ZIP codes.DiscussionThis study presents evidence that while high-income areas had higher transmission rates during off-peak periods, low-income areas suffered greater adverse outcomes in terms of hospitalization and death rates. The importance of this study is that it focuses on the social inequalities that were amplified by the pandemic.

The countries with the lowest life expectancy worldwide include the Nigeria, Chad, and Lesotho. As of 2023, people born in Nigeria could be expected to live only up to 54 years. This is almost 20 years shorter than the global life expectancy. Life expectancy The global life expectancy has gradually increased over the past couple decades, rising from 70.4 years in 2011 to 73.2 years in 2023. However, the years 2020 and 2021 saw a decrease in global life expectancy due to the COVID-19 pandemic. Furthermore, life expectancy can vary greatly depending on the country and region. For example, all the top 20 countries with the lowest life expectancy worldwide are in Africa. The countries with the highest life expectancy include Liechtenstein, Switzerland, and Japan. Causes of death The countries with the lowest life expectancy worldwide are all low-income or developing countries that lack health care access and treatment that more developed countries can provide. The leading causes of death in these countries therefore differ from those of middle-income and upper-income countries. The leading causes of death in low-income countries include diseases such as HIV/AIDS and malaria, as well as preterm birth complications, which do not cause substantial death in higher income countries.

Objective: The objective of this scoping review is to describe the prevalence and causes of death in people with HIV (PHIV) receiving antiretroviral therapy (ART) in low- and middle-income countries (LMICs) and identify research gaps. Introduction: Much of the focus on reducing mortality in PHIV has been placed on early initiation of ART and prevention of opportunistic infections. This has resulted in significant improvements in life expectancy in PHIV. However, little is known about the mortality rate and causes of death in PHIV established on ART in LMICs. Inclusion criteria: The scoping review will be restricted to research on the causes of death in adults (age 18 and above) with HIV established on ART in LMIC settings. We will exclude studies evaluating causes of early mortality in the first six months after initiation of ART. Methods: A search will be performed in PubMed(NLM), EMBASE (Ovid), Web of Science(Clarivate), Cochrane Database of Systematic Reviews, and CENTRAL in June and July of 2022. Studies will be limited to those involving human subjects and in English. The search strategy was crafted to find studies discussing cause of death in HIV patients treated with antiretroviral therapy, using a combination of keywords and subject headings.

Background and MethodsTo guide achievement of the Millennium Development Goals, we used the Lives Saved Tool to provide a novel simulation of potential maternal, fetal, and newborn lives and costs saved by scaling up midwifery and obstetrics services, including family planning, in 58 low- and middle-income countries. Typical midwifery and obstetrics interventions were scaled to either 60% of the national population (modest coverage) or 99% (universal coverage).FindingsUnder even a modest scale-up, midwifery services including family planning reduce maternal, fetal, and neonatal deaths by 34%. Increasing midwifery alone or integrated with obstetrics is more cost-effective than scaling up obstetrics alone; when family planning was included, the midwifery model was almost twice as cost-effective as the obstetrics model, at $2,200 versus $4,200 per death averted. The most effective strategy was the most comprehensive: increasing midwives, obstetricians, and family planning could prevent 69% of total deaths under universal scale-up, yielding a cost per death prevented of just $2,100. Within this analysis, the interventions which midwifery and obstetrics are poised to deliver most effectively are different, with midwifery benefits delivered across the continuum of pre-pregnancy, prenatal, labor and delivery, and postpartum-postnatal care, and obstetrics benefits focused mostly on delivery. Including family planning within each scope of practice reduced the number of likely births, and thus deaths, and increased the cost-effectiveness of the entire package (e.g., a 52% reduction in deaths with midwifery and obstetrics increased to 69% when family planning was added; cost decreased from $4,000 to $2,100 per death averted).ConclusionsThis analysis suggests that scaling up midwifery and obstetrics could bring many countries closer to achieving mortality reductions. Midwives alone can achieve remarkable mortality reductions, particularly when they also perform family planning services - the greatest return on investment occurs with the scale-up of midwives and obstetricians together.

Background # Seasonal influenza virus is a common cause of acute lower respiratory infection (ALRI) in young children. In 2008, we estimated that 20 million influenza-virus-associated ALRI and 1 million influenza-virus-associated severe ALRI occurred in children under 5 years globally. Despite this substantial burden, only a few low-income and middle-income countries have adopted routine influenza vaccination policies for children and, where present, these have achieved only low or unknown levels of vaccine uptake. Moreover, the influenza burden might have changed due to the emergence and circulation of influenza A/H1N1pdm09. We aimed to incorporate new data to update estimates of the global number of cases, hospital admissions, and mortality from influenza-virus-associated respiratory infections in children under 5 years in 2018. # Methods # We estimated the regional and global burden of influenza-associated respiratory infections in children under 5 years from a systematic review of 100 studies published between Jan 1, 1995, and Dec 31, 2018, and a further 57 high-quality unpublished studies. We adapted the Newcastle-Ottawa Scale to assess the risk of bias. We estimated incidence and hospitalisation rates of influenza-virus-associated respiratory infections by severity, case ascertainment, region, and age. We estimated in-hospital deaths from influenza virus ALRI by combining hospital admissions and in-hospital case-fatality ratios of influenza virus ALRI. We estimated the upper bound of influenza virus-associated ALRI deaths based on the number of in-hospital deaths, US paediatric influenza-associated death data, and population-based childhood all-cause pneumonia mortality data in six sites in low-income and lower-middle-income countries. # Findings # In 2018, among children under 5 years globally, there were an estimated 109*5 million influenza virus episodes (uncertainty range [UR] 63*1-190*6), 10*1 million influenza-virus-associated ALRI cases (6*8-15*1); 870 000 influenza-virus-associated ALRI hospital admissions (543 000-1 415 000), 15 300 in-hospital deaths (5800-43 800), and up to 34 800 (13 200-97 200) overall influenza-virus-associated ALRI deaths. Influenza virus accounted for 7% of ALRI cases, 5% of ALRI hospital admissions, and 4% of ALRI deaths in children under 5 years. About 23% of the hospital admissions and 36% of the in-hospital deaths were in infants under 6 months. About 82% of the in-hospital deaths occurred in low-income and lower-middle-income countries. # Interpretation # A large proportion of the influenza-associated burden occurs among young infants and in low-income and lower middle-income countries. Our findings provide new and important evidence for maternal and paediatric influenza immunisation, and should inform future immunisation policy particularly in low-income and middle-income countries.

Objectives: Understanding treatment seeking for severe febrile illness (SFI) is methodologically challenging. In this scoping review, we investigate definitions of severe febrile illness in treatment seeking studies on children under 5 years of age in low and middle income countries. We analyze the association of SFI definitions with different concepts of treatment seeking and identify related research gaps.Methods: We searched Pubmed, Scopus and WHOLIS, and screened references of included publications for eligibility.Results: Definitions of SFI had either a biomedical perspective (predominantly in quantitative studies) or a caregiver perspective (predominantly in qualitative studies). In quantitative analyses of treatment seeking, severity was more often conceptualized as a determinant rather than an outcome of a treatment seeking process. The majority of quantitative analyses only included surviving children or did not explicitly mention dead children.Conclusion: Different research questions lead to diverse definitions and concepts of severity and treatment seeking outcomes, which limits the comparability of the available evidence. Systematic exclusion of dead children is likely to bias inferences on the association of treatment seeking and health outcomes of children with SFI in low and middle income countries.

In 2021, high-income countries saw the highest number of deaths from drug use disorder, reaching over **** thousand deaths. This was followed by Upper-middle-income countries, where nearly **** thousand deaths from drug use disorder were reported in the same year.

The fertility rate in a country decreases with an increasing income level. For instance, the least developed and low-income countries had the highest fertility rates between 2000 and 2022, with 3.95 and 4.55 children per woman, respectively, as of 2022. On the other hand, high-income and upper-middle-income countries had fertility rates of *** and ****, respectively. Furthermore, fertility rates fell in all the countries worldwide, regardless of income level.

BackgroundAccording to the most recent estimates, 842,000 deaths in low- to middle-income countries were attributable to inadequate water, sanitation and hygiene in 2012. Despite billions of dollars and decades of effort, we still lack a sound understanding of which kinds of WASH interventions are most effective in improving public health outcomes, and an important corollary–whether the right things are being measured. The World Health Organization (WHO) has made a concerted effort to compile comprehensive data on drinking water quality and sanitation in the developing world. A recent 2014 report provides information on three phenotypes (responses): Unsafe Water Deaths, Unsafe Sanitation Deaths, Unsafe Hygiene Deaths; two grouped phenotypes: Unsafe Water and Sanitation Deaths and Unsafe Water, Sanitation and Hygiene Deaths; and six explanatory variables (predictors): Improved Sanitation, Unimproved Water Source, Piped Water To Premises, Other Improved Water Source, Filtered and Bottled Water in the Household and Handwashing.Methods and FindingsRegression analyses were performed to identify statistically significant associations between these mortality responses and predictors. Good fitted-model performance required: (1) the use of population-normalized death fractions as opposed to number of deaths; (2) transformed response (logit or power); and (3) square-root predictor transformation. Given the complexity and heterogeneity of the relationships and countries being studied, these models exhibited remarkable performance and explained, for example, about 85% of the observed variance in population-normalized Unsafe Sanitation Death fraction, with a high F-statistic and highly statistically significant predictor p-values. Similar performance was found for all other responses, which was an unexpected result (the expected associations between responses and predictors–i.e., water-related with water-related, etc. did not occur). The set of statistically significant predictors remains the same across all responses. That is, Unsafe Water Source (UWS), Improved Sanitation (IS) and Filtered and Bottled Water in the Household (FBH) were the only statistically significant predictors whether the response was Unsafe Sanitation Death Fraction, Unsafe Hygiene Death Fraction or Unsafe Water Death Fraction. Moreover, the fraction of variance explained for all fitted models remained relatively high (adjusted R2 ranges from 0.7605 to 0.8533). We find that two of the statistically significant predictors–Improved Sanitation and Unimproved Water Sources–are particularly influential. We also find that some predictors (Piped Water to Premises, Other Improved Water Sources) have very little explanatory power for predicting mortality and one (Other Improved Water Sources) has a counterintuitive effect on response (Unsafe Sanitary Death Fraction increases with increases in OIWS) and one predictor (Hand Washing) to have essentially no explanatory usefulness.ConclusionsOur results suggest that a higher priority may need to be given to improved sanitation than has been the case. Nevertheless, while our focus in this paper is mortality, morbidity is a staggering consequence of inadequate water, sanitation and hygiene, and lower impact on mortality may not mean a similarly low impact on morbidity. More specifically, those predictors that we found uninfluential for predicting mortality-related responses may indeed be important when morbidity is the response.

This statistic shows the share of occurrence and death tolls for weather-related disasters worldwide in the period from 1995 to 2015, by national income level. During the past 20 years, around ** percent of weather-related disasters affected lower-income countries.

Natural disasters and loss – additional information

The years 2014 and 2015 are two of the hottest years recorded since the 1880s. In 2014, there were ** deaths caused by extreme heat in the United States. The increased risk of extreme weather due to climate change has put pressure on countries to develop regulations to better protect infrastructure and human health. Between 1995 and 2015, about a third of the global weather-related disasters occurred in lower-middle income countries, however, almost half of the deaths due to these events affected these countries. The number of deaths caused by the Cyclone Nargis in Myanmar contributed significantly to these statistics. In high-income countries, weather-related deaths are largely due to heat waves. The actual number of casualties in low-income countries is estimated to be much higher and may reflect a lack of reporting.

China and India have been among the most severely impacted countries in the world in terms of weather catastrophes, accounting for some * billion people that have been affected between 1995 and 2015. Economic loss due to these events totaled some ** billion U.S. dollars in the Asia and Oceania regions. Millions of houses as well as public institutions such as schools, clinics, and hospitals have been damaged by weather-related disasters, primarily due to floods and storms. Over the last decades, countries have improved their preparedness as well as their response to natural disasters. Several countries in Asia have begun to follow the Hyogo Framework for Action, a guideline developed to help reduce disaster risk, in efforts to reduce the losses derived from these catastrophes.