**Background:** Cardiovascular diseases (CVDs), principally ischemic heart disease and stroke, remain the leading causes of premature mortality worldwide. The World Health Organization reported that the burden of premature mortality is notably high in low- and middle-income countries (LMICs). Although CVD mortality rates have declined in the past two decades, LMICs face an increasing number of premature CVD deaths. Using Global Burden of Disease (GBD) data from 1990 and 2013, Gregory et al. projected approximately 7.8 million premature CVD deaths in 2025 if current risk factor trends continue. The WHO Sustainable Development Goal (SDG) target 3.4 aims to reduce premature mortality from non-communicable diseases (NCDs) by one-third by 2030. Despite the growing number of individual studies reporting years of life lost (YLL), age-standardized mortality rates (ASMR), or standardized mortality ratios (SMR) for premature CVD mortality, no comprehensive meta-analysis has synthesized this evidence. This protocol describes a systematic review and meta-analysis designed to fill this gap.
**Methods:** The protocol was registered with PROSPERO (CRD42021288415) and will follow PRISMA and MOOSE guidelines. The review will include original English-language articles reporting YLL (using YPLL or SEYLL methods), ASMR, or SMR as indicators of premature CVD mortality, with any upper age limit defining premature mortality. CVD death must be determined using ICD codes (any version). Studies investigating modifiable risk factors (e.g., diabetes, hypertension, hypercholesterolemia, obesity, tobacco smoking, alcohol use, unhealthy diet, physical inactivity, low socioeconomic status) will be considered. Any observational study design (cross-sectional, cohort, case-control) or intervention studies reporting premature CVD mortality will be included. Exclusion criteria include studies assessing causes of premature mortality other than CVD, reviews, case studies, commentaries, qualitative studies, and very specific populations (e.g., epilepsy, congenital disease, post-surgical groups, pregnant women).
Five electronic databases will be searched: PubMed, Scopus, Web of Science (WoS), CINAHL, and Cochrane CENTRAL, supplemented by Google Scholar and hand-searching of reference lists. Searches will be conducted up to August 2022 with no restriction on publication date. Two reviewers will independently screen titles/abstracts and full texts, with disagreements resolved by consensus or arbitration by two additional authors. Data extraction will use a standardized Microsoft Excel form. Study quality will be assessed using the Newcastle-Ottawa Scale (NOS) for observational studies (maximum 9 stars; classified as good, fair, or poor quality) and the ACROBAT-NRSi tool for non-randomized intervention studies.
**Key Results:** This is a protocol paper; no results are reported. The planned statistical analysis will use R software with the 'meta' and 'metafor' packages. Pooled estimates of YLL, ASMR, and SMR will be calculated using random-effects meta-analysis. For YLL and SEYLL, weighted averages with 95% CIs will be calculated; if uncertainty measures are not reported, average values will be weighted by study population size. For ASMR and SMR, the most basic adjusted model will be used when multiple estimates are reported. Heterogeneity will be assessed using the I² statistic (25%, 50%, and 75% representing low, moderate, and high heterogeneity) and the Q statistic (significance level set at 0.01). If I² > 50% or significant Q-test results are found, subgroup analyses and meta-regression will explore sources of heterogeneity. Publication bias will be assessed using funnel plots, trim-and-fill method, Begg's rank correlation, and Egger's weighted regression test when more than ten studies are pooled. Subgroup analyses are planned by sex, geographic location (six continents), main CVD types (ischemic heart disease and cerebrovascular disease), and study time.
**Clinical Implications:** The meta-analysis aims to provide a comprehensive synthesis of available evidence on premature CVD mortality, which is a major public health concern worldwide. The results are expected to have important implications for clinical practice and public health policy, providing insights into strategies to prevent and manage premature CVD mortality. The findings could help track progress toward SDG target 3.4, inform the development of mathematical models or cost-effectiveness analyses to forecast future premature CVD death burden, and identify settings or population subgroups where the risk of CVD death is of higher concern and requires special prevention priorities (e.g., specific continents or gender-based interventions). Unlike previous global reports, this review will not be limited to high-income countries and will include records from LMICs. Limitations may include high heterogeneity due to different study designs and characteristics, which will be addressed through subgroup analyses and meta-regression. The inclusion of observational studies may introduce bias and confounding, but synthesizing evidence from multiple observational studies can strengthen conclusions.