INTRODUCTION

Diet is a major modifiable risk factor for cardiometabolic disease; however, interpretable measures capturing impacts of overall diet on health that can be easily used by policymakers at the global/national levels are not readily available.

METHODS

We developed the International Diet-Health Index (IDHI) to measure health impacts of dietary intake across 186 countries in 2010, using age-specific and sex-specific data on country-level dietary intake, effects of dietary factors on cardiometabolic diseases and country-specific cardiometabolic disease profiles. The index encompasses the impact of 11 foods/nutrients on 12 cardiometabolic diseases, the mediation of health effects of specific dietary intakes through blood pressure and body mass index and background disease prevalence in each country-age-sex group. We decomposed the index into IDHI for risk-reducing factors, and IDHI for risk-increasing factors. The flexible functional form of the IDHI allows inclusion of additional risk factors and diseases as data become available.

RESULTS

By sex, women experienced smaller detrimental cardiometabolic effects of diet than men: (females IDHI range: -0.480 (5th percentile, 95th percentile: -0.932, -0.300) to -0.314 (-0.543, -0.213); males IDHI range: (-0.617 (-1.054, -0.384) to -0.346 (-0.624, -0.222)). By age, middle-aged adults had highest IDHI (females: 0.392 (0.235, 0.763); males: 0.415 (0.243, 0.949)) and younger adults had most extreme IDHI (females: -0.480 (-0.932, -0.300); males: -0.617 (-1.054, -0.384)). Regionally, Central Latin America had the lowest IDHI (-0.466 (-0.892, -0.159)), while Southeast Asia had the highest IDHI (0.272 (-0.224, 0.903)). IDHI was highest in low-income countries and lowest in upper middle-income countries (-0.039 (-0.317, 0.227) and -0.146 (-0.605, 0.303), respectively). Among 186 countries, Honduras had lowest IDHI (-0.721 (-0.916, -0.207)), while Malaysia had highest IDHI (0.904 (0.435, 1.190)).

CONCLUSION

IDHI encompasses dietary intakes, health effects and country disease profiles into a single index, allowing policymakers a useful means of assessing/comparing health impacts of diet quality between populations.