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The past half-century has seen enormous changes in the demographic makeup of Latin America and the Caribbean (LAC). In the 1950s, LAC had a small population of about 160 million people, less than today's population of Brazil. Two-thirds of Latin Americans lived in rural areas. Families were large and women had one of the highest fertility rates in the world, low levels of education, and few opportunities for work outside the household. Investments in health and education reached only a small fraction of the children, many of whom died before reaching age five. Since then, the size of the LAC population has tripled and the mostly rural population has been transformed into a largely urban population. There have been steep reductions in child mortality, and investments in health and education have increased, today reaching a majority of children. Fertility has been more than halved and the opportunities for women in education and for work outside the household have improved significantly. Life expectancy has grown by 22 years. Less obvious to the casual observer, but of significance for policy makers, a population with a large fraction of dependent children has evolved into a population with fewer dependents and a very large proportion of working-age adults. This overview seeks to introduce the reader to three groups of issues related to population aging in LAC. First is a group of issues related to the support of the aging and poverty in the life cycle. Second is the question of the health transition. Third is an understanding of the fiscal pressures that are likely to accompany population aging and to disentangle the role of demography from the role of policy in that process.

This report is organized in such a way that the key policy options and strategic priorities are based on the country context, including the burden of non-communicable diseases (NCDs) and associated risk factors and the existing capacity of the health system. Chapter one describes the country and regional contexts and the evidence of the demographic and epidemiological transitions in Bangladesh; chapter two outlines the disease burden of major NCDs, including the equity and economic impact and the common risk factors; chapter three provides an assessment of the health system and its capacity to prevent and control major NCDs; chapter four summarizes ongoing NCD interventions and activities in Bangladesh and highlights the remaining gaps and challenges; and chapter five presents key policy options and strategic priorities to prevent and control NCDs.

Injuries continue to be a public health concern in Canada. National injury death data are essential for understanding the magnitude and pattern of injuries. This paper used the Vital Statistics - Death database to examine deaths associated with injuries in 2015. Injuries were ranked against causes of death, and more in-depth analysis of injury categories was conducted by sex and age. Unintentional injuries were the 6th leading causes of death overall, with different ranking by sex. Among unintentional injury deaths, leading causes included falls, poisonings, motor vehicle traffic collisions, and suffocation, which varied by age group.

This chapter contains sections titled: Learning Outcomes Introduction Infection Control Risk Management Conclusion References

This chapter contains sections titled: Overview Clinical significance Pathophysiology Clinical features Diagnosis Treatment Complications Prevention Conclusion Suggested reading

ObjectivesTo analyse trends in mortality and causes of death among children aged under 5 years in Beijing, China between 1992 and 2015 and to forecast under-5 mortality rates (U5MRs) for the period 2016–2020.MethodsAn entire population-based epidemiological study was conducted. Data collection was based on the Child Death Reporting Card of the Beijing Under-5 Mortality Rate Surveillance Network. Trends in mortality and leading causes of death were analysed using the χ2 test and SPSS 19.0 software. An autoregressive integrated moving average (ARIMA) model was fitted to forecast U5MRs between 2016 and 2020 using the EViews 8.0 software.ResultsMortality in neonates, infants and children aged under 5 years decreased by 84.06%, 80.04% and 80.17% from 1992 to 2015, respectively. However, the U5MR increased by 7.20% from 2013 to 2015. Birth asphyxia, congenital heart disease, preterm/low birth weight and other congenital abnormalities comprised the top five causes of death. The greatest, most rapid reduction was that of pneumonia by 92.26%, with an annual average rate of reduction of 10.53%. The distribution of causes of death differed among children of different ages. Accidental asphyxia and sepsis were among the top five causes of death in children aged 28 days to 1 year and accident was among the top five causes in children aged 1–4 years. The U5MRs in Beijing are projected to be 2.88‰, 2.87‰, 2.90‰, 2.97‰ and 3.09‰ for the period 2016–2020, based on the predictive model.ConclusionBeijing has made considerable progress in reducing U5MRs from 1992 to 2015. However, U5MRs could show a slight upward trend from 2016 to 2020. Future considerations for child healthcare include the management of birth asphyxia, congenital heart disease, preterm/low birth weight and other congenital abnormalities. Specific preventative measures should be implemented for children of various age groups.

This chapter contains sections titled: Overview Pathophysiology Diagnosis and workup Management Follow‐up Suggested reading

The aim of the study was to analyze changes and demographic inequalities in the mortality of the Lithuanian population in 2020 and 2021 compared to the period of 2015–2019, assess the major causes of death that contributed to the changes, and identify the groups of the society that suffered most. Methods Mortality rates for 2015–2021 from all causes, cardiovascular diseases, malignant neoplasms, external causes, diseases of the digestive system, diseases of the respiratory system, and COVID-19 in Lithuania by sex and age were calculated per 100,000 population. Mortality changes compared with the previous year and between the average of 2015–2019 years were calculated. The average annual percentage change was calculated to determine the aggregated 2015–2019 change in mortality from the leading causes of death. Coefficients of linear regression multiplied by 100 were presented as average annual changes, which were statistically significant at p  < 0.05. Mortality rate differences between 2020 and 2021 years and the average of 2015–2019 years were calculated. Results Lithuania has recorded 9.4% higher overall mortality among males in 2020 and 18% higher mortality in 2021 compared with a period unaffected by the COVID-19 pandemic ( p  < 0.05). Among females – 10.7% higher mortality in 2020 and 22.6% in 2021 ( p  < 0.05). Male and female mortality from COVID-19 in all age groups in 2021 was higher than that in 2020, and mortality rates increased with an increase in age. Negative changes in mortality from 2015 to 2019 to 2020 among males and females of all age groups were mainly determined by COVID-19. The most significant impact of COVID-19 in 2021 on the overall mortality changes was estimated in the 55–64 and 65–74 male age groups, while female overall mortality was in the 45–54 and 65–74 age groups. Conclusions Negative changes in mortality from 2015 to 2019 to 2020 among males and females of all age groups were mainly determined by COVID-19. The most significant impact of COVID-19 in 2021 on the overall mortality changes was estimated in the 55–74 male age group, while on female overall mortality in the 45–54 and 65–74 age groups.

Background The ranking lists used by most countries for leading causes of death (CODs) comprise broad category such as cancer, heart disease, and accidents. To provide more specific information, the World Health Organization (WHO) and the Institute of Health Metrics and Evaluation (IHME) proposed lists that splitting broad categories into specific categories. We examined the changes in rankings of leading CODs according to different lists in Japan, Korea, and Taiwan from 1998 to 2018. Methods We obtained the number of deaths for three countries from the WHO mortality database for 1998, 2008, and 2018. Age-standardized death rates were calculated for rankings 10 leading CODs using WHO 2000 age structure as standard. Results The first leading COD was cancer in Japan, Korea, and Taiwan from 1998 to 2018 based on government list; nevertheless, became stroke based on WHO list, and was stroke and ischemic heart disease based on IHME list. In the WHO and IHME lists, cancer is categorized based on cancer site. The number of cancer sites included in the 10 leading CODs in 2018 was 4, 4, and 3 in Japan, Korea, and Taiwan, respectively according to the WHO list and was 4, 4, and 2, respectively according to IHME list. The only difference was the rank of liver cancer in Taiwan, which was 6th according to WHO list and was 18th according to IHME list. The ranking and number of deaths for some CODs differed greatly between the WHO and IHME lists due to the reallocation of “garbage codes” into relevant specific COD in IHME list. Conclusions Through the use of WHO and the IHME lists, the relative importance of several specific and avoidable causes could be revealed in 10 leading CODs, which could not be discerned if the government lists were used. The information is more relevant for health policy decision making.

This chapter contains sections titled: Overview Pathophysiology Pregestational diabetes mellitus Gestational diabetes Suggested reading