This study examines the effects of population density, unemployment rate, inflation, and economic growth on life expectancy in emerging market economies during the period 2000–2023 using a panel ARDL model. The stationarity of the variables was analyzed with IPS and LLC unit root tests, and cointegration relationships were tested using Pedroni and Kao tests. The panel ARDL model was applied to investigate the short- and long-term relationships among the variables, while causality relationships were examined using the Dumitrescu–Hurlin (2012) test. Additionally, long-term coefficients were estimated using a static panel data model and compared with the ARDL results. Empirical findings indicate that population density positively affects life expectancy in both the short and long term, while per capita income contributes positively to life expectancy in the long term. Conversely, the unemployment rate negatively impacts life expectancy in both periods. The negative and significant error correction term suggests that short-term deviations from equilibrium are corrected in the long run. A bidirectional causality relationship was observed between population density, life expectancy, and per capita income, whereas no significant causality was found from other variables to unemployment or inflation. These results imply that, in E7 countries, promoting economic growth, increasing income levels, managing population density effectively, and reducing unemployment should be prioritized in policy planning. Furthermore, future studies could explore the indirect effects of inflation and the role of income inequality on life expectancy to provide deeper insights into health and well-being outcomes.