Disability-free life expectancy at old ages in Egypt

Secular trends of epidemiologic patterns of chronic kidney disease over three decades: an updated analysis of the Global Burden of Disease Study 2019

OBJECTIVES

To assess the characteristics of the global death burden imposed by chronic kidney disease (CKD) and the attributable risk factors from 1990 to 2019 to help inform a framework for policy discussions, resource allocation and research priorities.

DESIGN

A population-based observational study.

SETTING

The death data and relative risk factors were obtained from the Global Burden of Disease (GBD) Study 2019 database.

MAIN OUTCOME MEASURES

Based on the GBD database, we estimated the death burden attributable to CKD stratified by sociodemographic index (SDI), geographic location, sex, age group, time period and risk factors from 1990 to 2019.

RESULTS

Over three decade study period, the global number of CKD-related deaths increased from 0.60 million (95% uncertainty interval (UI): 0.57-0.63 million) in 1990 to 1.43 million (95% UI: 1.31-1.52 million) in 2019. The age-standardised death rate (ASDR) of CKD, among all causes, increased from 15th in 1990 to 10th in 2019. Globally, the ASDR in males was higher than that in females. CKD-related deaths mainly occurred in those aged over 50 years, especially in regions with higher SDIs. The ASDR was negatively related to SDI (ρ=-0.603, p<0.0001). Among risk factors, metabolic risk factors, especially systolic blood pressure, fasting plasma glucose and body mass index, were the main contributors to CKD-related deaths. Although the high-temperature-related death burden was low, the trend increased sharply in lower SDI regions.

CONCLUSIONS

CKD-related deaths continue to increase, with the majority occurring in elderly adults. The CKD-related death burden is higher in males than in females. Additionally, the increasing high-temperature-related death burdens in lower SDI regions should receive social attention.

Quantifying non-communicable diseases' burden in Egypt using State-Space model

The study aimed to model and quantify the health burden induced by four non-communicable diseases (NCDs) in Egypt, the first to be conducted in the context of a less developing county. The study used the State-Space model and adopted two Bayesian methods: Particle Filter and Particle Independent Metropolis-Hastings to model and estimate the NCDs’ health burden trajectories. We drew on time-series data of the International Health Metric Evaluation, the Central Agency for Public Mobilization and Statistics (CAPMAS) Annual Bulletin of Health Services Statistics, the World Bank, and WHO data. Both Bayesian methods showed that the burden trajectories are on the rise. Most of the findings agreed with our assumptions and are in line with the literature. Previous year burden strongly predicts the burden of the current year. High prevalence of the risk factors, disease prevalence, and the disease’s severity level all increase illness burden. Years of life lost due to death has high loadings in most of the diseases. Contrary to the study assumption, results found a negative relationship between disease burden and health services utilization which can be attributed to the lack of full health insurance coverage and the pattern of health care seeking behavior in Egypt. Our study highlights that Particle Independent Metropolis-Hastings is sufficient in estimating the parameters of the study model, in the case of time-constant parameters. The study recommends using state Space models with Bayesian estimation approaches with time-series data in public health and epidemiology research.