Grasgruber · Economics and human biology 2014 · ecological cross-sectional study · n=45 countries

The role of nutrition and genetics as key determinants of the positive height trend.

Cited 136 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional ecological correlation study across 45 countries (by design analogy, not clinical CEBM).

PubMed 25190282 · doi:10.1016/j.ehb.2014.07.002 · record verified 2026-08-28

What was done

Ecological study comparing average height data of young men across 45 countries (Europe, Australia, New Zealand, and USA) with national-level metrics: long-term food consumption averages from the FAOSTAT database, development indicators from the World Bank and CIA World Factbook, and population frequencies of select genetic markers (Y haplogroups I-M170 and R1b-U106, as well as lactose tolerance phenotypic distribution).

What was found

The abstract reports relational directions without exact numerical statistics or effect sizes. The ratio of high-quality protein intake (dairy, pork, fish) to low-quality protein intake (wheat) was identified as the strongest explanatory dietary factor. Genetic marker frequencies (I-M170, R1b-U106, and lactose tolerance) appeared comparably important. Moderately significant positive correlations were observed with GDP per capita, health expenditure, and urbanization (specifically in Western Europe), whereas height correlated inversely with child mortality and the Gini index.

Why it matters

Highlights the potential combined contributions of protein quality, socioeconomic development, and population genetics in explaining national-level height variations among populations of European descent.

Limits

The abstract provides no exact numerical results, effect sizes, or confidence intervals. Country-level ecological associations are vulnerable to ecological fallacy and residual confounding, precluding causal inference. Findings are restricted to young men in 45 predominantly European-descended populations, and genetic marker data were more limited than nutritional metrics.

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