ABSTRACT
Background: Geographical terrains of Indonesia pose a major hindrance to transportation. The difficulty of transportation affects the provision of acute time-dependent therapy such as percutaneous coronary intervention (PCI). Also, Indonesia's aging population would have a significant impact on the prevalence of acute coronary syndrome in the next decade. Therefore, the analysis and enhancement of cardiovascular care are crucial. The catheterisation laboratory performs PCI procedures. In the current study, we mapped the number and distribution of catheterisation laboratories in Indonesia. Methods: A direct survey was used to collect data related to catheterisation laboratory locations in July 2022. The population data was sourced from the Ministry of Home Affairs. The recent growth of catheterisation laboratories was examined and evaluated based on geographical areas. The main instruments for comparing regions and changes throughout time are the ratio of catheterisation laboratories per 100,000 population and the Gini index (a measure of economic and healthcare inequality. Gini index ranges from 0 to 1, with greater values indicating more significant levels of inequality). Regression analysis was carried out to see how the number of catheterisation laboratories was affected by health demand (prevalence) and economic capacity (Gross Domestic Regional Product [GDRP] per Capita). Findings: The number of catheterisation laboratories in Indonesia significantly increased from 181 to 310 during 2017-2022, with 44 of the 119 new labs built in an area that did not have one. Java has the most catheterisation laboratories (208, 67%). The catheterisation laboratory ratio in the provinces of Indonesia ranges from 0.0 in West Papua and Maluku to 4.46 in Jakarta; the median is 1.09 (IQR 0.71-1.18). The distribution remains a problem, as shown by the high catheterisation laboratory Gini index (0.48). Regression shows that distribution of catheterisation laboratories was significantly affected by GDRP and the prevalence of heart disease. Interpretation: The number of catheterisation laboratories in Indonesia has increased significantly recently, however, maldistribution remains a concern. To improve Indonesia's cardiovascular emergency services, future development of catheterisation laboratories must be better planned considering the facility's accessibility and density. Funding: Airlangga Research Fund - Universitas Airlangga.
ABSTRACT
BACKGROUND: In the last two decades, there has been a discernible shift in the distribution of mortality attributed to cardiovascular disease (CVD) between developing and developed nations; in developed nations, the percentage of deaths caused by CVD decreased from 48% in 1990 to 43% in 2010, while in developing nations, they increased from 18% to 25%. In Indonesia, CVD death has increased substantially and remained elevated in the last ten years. Current behavioral and metabolic risk factors, including hyperglycemia, obesity, dyslipidemia, hypertension, and smoking, enhance the risk of CVD mortality, according to several studies. AIMS: We undertook a study to determine whether the increase in mortality and incidence of CVD can be attributed to changes in the most common metabolic and behavioral risk factors from 2000 to 2019 across 34 Indonesian provinces. MATERIALS AND METHODS: Data from 34 province for CVD incidence and mortality and data on changes in metabolic and behavioural risk factors between 2000 and 2019 in Indonesia were obtained from the Global Burden study (GBD) by The Institute of Health Metrics and Evaluation (IHME). A statistical model was applied to calculate the fatalities attributable to the risk factors change using Population attributable fractions (PAF) and baseline year death numbers. Furthermore, we ran multivariate regressions on Summary Exposure Value of risk factors associated with the increasing mortality, incidence rates in a lag year analysis. R software used to measure heteroscedasticity-consistent standard errors with coeftest and coefci. Covariates were added to adjusted models, including the Socio-demographic Index, Primary health care facilities coverage, and GDP per capita. RESULTS: The age-standardized mortality rate for CVD from 2000 to 2019 in Indonesia, increased from 356.05 to 412.46 deaths per 100,000 population among men and decreased from 357.52 to 354.07 deaths per 100,000 population among women, resulting in an increase of 270.928 per 100,0000 inhabitants of CVD deaths. In the same period, there was an increase in exposure to risk factors such as obesity by +9%, smoking by +1%, dyslipidemia by +1.3%, hyperglycemia by +2%, and hypertension by +1.2%. During this time span, an additional 14,517 men and 17,917 women died from CVD, which was attributable to higher obesity exposure. We apply multivariate regression with province-fixed and year-fixed analysis and find strong correlation between hyperglycemia in women (6; 95%CI 0 to 12, death per 1-point increase in hyperglycemia exposure) with an increasing death rate in ischemic heart disease. We also performed a year lag analysis and discovered a robust association between high low density lipoprotein (LDL) levels in men and women and the growing incidence of ischemic heart disease. The association between a 10-year lag of high LDL and the incidence of ischemic heart disease was five times stronger than that observed for other risk factors, particularly in men (5; 95%CI 2 to 8, incidence per 1-point increase in high LDL exposure). CONCLUSION: Hyperglycemia in women is an important risk factor associated with increasing mortality due to Ischemic Heart Disease (IHD) in Indonesia This study also revealed that the presence of high LDL in both men and women were associated with an increase incidence of IHD that manifested several years subsequent to exposure to the risk factor. Additionally, the highest cardiovascular death portion were attributed to obesity. These findings suggest that policymakers should control high LDL and hyperglycemia 10 years earlier prior to the occurrence of IHD and employ personalized therapy to regulate associated risks.
