Ebeling · European journal of population = Revue europeenne de demographie 2025 · longitudinal demographic trend study · n=20 countries

National Life Expectancy Lags Behind Benchmark Progress and the Role of Smoking: An International Comparison.

Cited 1 times in the scientific literature.

Level 3 - non-randomized controlled study

Longitudinal aggregate demographic analysis across 20 countries (1950–2019); level assigned by design analogy.

PubMed 41366587 · doi:10.1007/s10680-025-09760-8 · record verified 2026-08-26

What was done

The authors analyzed national mortality records from 20 low-mortality countries from 1950 to 2019. They evaluated national life expectancy and age-specific mortality differences quantified as calendar years lagging behind the longevity frontier, defined as the record smoking-eliminated life expectancy, assessing the distinct contributions of smoking and other mortality drivers by age and sex.

What was found

The abstract reports no specific numerical estimates or confidence intervals. Qualitatively, current life expectancy reflects smoking-eliminated benchmark records from two decades ago. A gender paradox was observed across most countries: men are closing the gap to optimal health benchmarks while women are drifting further away, despite men still carrying a greater overall burden of past smoking. Longevity leaders differ from lagging countries primarily in old-age mortality, whereas lagging countries also demonstrate developmental mortality delays across working ages. Removing smoking substantially reduces calculated development delays.

Why it matters

This framework separates the historical mortality impact of tobacco from other health headwinds, demonstrating that closing modern longevity gaps will increasingly depend on managing non-smoking chronic health risks in both working-age and older adults.

Limits

The abstract reports no exact numeric values, error margins, or country-specific results. The dataset is limited to 20 low-mortality countries, limiting generalizability to middle- and low-income nations. Findings rely on population-level counterfactual modeling of smoking elimination rather than direct individual-level exposure tracking, and specific non-smoking chronic disease factors were not individually quantified.

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