The American journal of clinical nutrition · 2026
Construct validity of the Planetary Health Diet Index relative to global food group-based measures of a healthy diet: a multicountry analysis of 24-hour dietary intake data on the FAO/WHO Global Individual Food Consumption Data Tool.
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Hanley-Cook Giles T, van der Meulen Emma, Beal Ty, Cacau Leandro Texeira
Аннотация
BACKGROUND: The Planetary Health Diet Index (PHDI) was developed as a measure of adherence to the Planetary Health Diet proposed by the EAT-Lancet Commissions; however, its construct validity for accurately reflecting a healthy diet as compared with other global dietary measures remain to be evaluated.
OBJECTIVES: The construct validity of PHDI was assessed by comparing the strength of its associations with reference metrics of nutrient adequacy and moderation of foods associated with greater risks of diet-related noncommunicable diseases against food group diversity score (FGDS) and Global Diet Quality Score (GDQS), and its positive (GDQS+) and negative (GDQS-) submetrics.
METHODS: Cross-sectional quantitative 24-h recall and food record data from 152,004 nonpregnant females and males (≥15 y) from 45 surveys in 26 countries accessed from the FAO/WHO Global Individual Food Consumption Data Tool were analyzed. Multilevel linear and modified Poisson regression models quantified associations between PHDI, FGDS, GDQS+, and GDQS- with reference measures [e.g., mean adequacy ratio (MAR), % energy from ultraprocessed food (UPF)] or indicators of a healthy diet [e.g., ≥400 g/d of fruits and vegetables (F&V)], respectively.
RESULTS: Adherence to PHDI was highest in low income (LIC) and lower-middle income countries (LMIC), and lowest in upper-middle income (UMIC) and high income countries (HIC). One-SD increments in PHDI were associated with higher MAR {β: 5.49 percentage points [pp]; [95% confidence interval (CI): 3.65 pp, 7.33 pp] in LIC to β: 1.41 pp [95% CI: 1.23 pp, 1.58 pp] in UMIC}, appropriate F&V intakes [relative risk (RR): 2.41 (95% CI: 1.85, 2.49) in UMIC to RR: 1.19 (95% CI: 1.05, 1.34) in LMIC], lower unprocessed red meat [β: -10.0 g/d (95% CI: -11.4 g/d, -8.73 g/d) in LIC to β: -6.86 g/d (95% CI: -7.54 g/d, -6.17 g/d) in UMIC], and lower proportions of energy from UPF [β: -2.47 pp (95% CI: -3.77 pp, -1.18 pp) in LMIC to β: -1.21 pp (95% CI: -2.32 pp, 0.105 pp) in LIC]; however, 1-SD increases in FGDS and GDQS+ outperformed PHDI in predicting measures of nutrient adequacy, particularly MAR [β for FGDS: 11.2 pp (95% CI: 9.13 pp, 13.3 pp) in LIC to β for FGDS: 8.57 pp (95% CI: 8.42 pp, 8.72 pp) in UMIC; β for GDQS+: 9.82 pp (95% CI: 7.26 pp, 12.4 pp) in LMIC to β for GDQS+: 7.18 pp (95% CI: 6.00 pp, 8.36 pp) in HIC] and appropriate F&V intakes [RR for FGDS: 2.78 (95% CI: 2.26, 3.41) in LMIC to RR for FGDS: 1.63 (95% CI: 1.22, 2.19) in HIC; RR for GDQS+: 2.39 (95% CI: 1.89, 2.89) in LMIC to RR for GDQS+: 1.55 (95% CI: 1.16, 1.96) in LIC].
CONCLUSIONS: PHDI may serve as a robust, dual-purpose measure for monitoring adherence to diets that are both sustainable and healthy in contexts with regular quantitative dietary intake assessments and low burdens of diet-related undernutrition. However, simpler food group-based measures, such as the FGDS, often show stronger associations with healthy diet subconstructs, such as nutrient adequacy, and are more feasible for large-scale, routine monitoring of diets.
OBJECTIVES: The construct validity of PHDI was assessed by comparing the strength of its associations with reference metrics of nutrient adequacy and moderation of foods associated with greater risks of diet-related noncommunicable diseases against food group diversity score (FGDS) and Global Diet Quality Score (GDQS), and its positive (GDQS+) and negative (GDQS-) submetrics.
METHODS: Cross-sectional quantitative 24-h recall and food record data from 152,004 nonpregnant females and males (≥15 y) from 45 surveys in 26 countries accessed from the FAO/WHO Global Individual Food Consumption Data Tool were analyzed. Multilevel linear and modified Poisson regression models quantified associations between PHDI, FGDS, GDQS+, and GDQS- with reference measures [e.g., mean adequacy ratio (MAR), % energy from ultraprocessed food (UPF)] or indicators of a healthy diet [e.g., ≥400 g/d of fruits and vegetables (F&V)], respectively.
RESULTS: Adherence to PHDI was highest in low income (LIC) and lower-middle income countries (LMIC), and lowest in upper-middle income (UMIC) and high income countries (HIC). One-SD increments in PHDI were associated with higher MAR {β: 5.49 percentage points [pp]; [95% confidence interval (CI): 3.65 pp, 7.33 pp] in LIC to β: 1.41 pp [95% CI: 1.23 pp, 1.58 pp] in UMIC}, appropriate F&V intakes [relative risk (RR): 2.41 (95% CI: 1.85, 2.49) in UMIC to RR: 1.19 (95% CI: 1.05, 1.34) in LMIC], lower unprocessed red meat [β: -10.0 g/d (95% CI: -11.4 g/d, -8.73 g/d) in LIC to β: -6.86 g/d (95% CI: -7.54 g/d, -6.17 g/d) in UMIC], and lower proportions of energy from UPF [β: -2.47 pp (95% CI: -3.77 pp, -1.18 pp) in LMIC to β: -1.21 pp (95% CI: -2.32 pp, 0.105 pp) in LIC]; however, 1-SD increases in FGDS and GDQS+ outperformed PHDI in predicting measures of nutrient adequacy, particularly MAR [β for FGDS: 11.2 pp (95% CI: 9.13 pp, 13.3 pp) in LIC to β for FGDS: 8.57 pp (95% CI: 8.42 pp, 8.72 pp) in UMIC; β for GDQS+: 9.82 pp (95% CI: 7.26 pp, 12.4 pp) in LMIC to β for GDQS+: 7.18 pp (95% CI: 6.00 pp, 8.36 pp) in HIC] and appropriate F&V intakes [RR for FGDS: 2.78 (95% CI: 2.26, 3.41) in LMIC to RR for FGDS: 1.63 (95% CI: 1.22, 2.19) in HIC; RR for GDQS+: 2.39 (95% CI: 1.89, 2.89) in LMIC to RR for GDQS+: 1.55 (95% CI: 1.16, 1.96) in LIC].
CONCLUSIONS: PHDI may serve as a robust, dual-purpose measure for monitoring adherence to diets that are both sustainable and healthy in contexts with regular quantitative dietary intake assessments and low burdens of diet-related undernutrition. However, simpler food group-based measures, such as the FGDS, often show stronger associations with healthy diet subconstructs, such as nutrient adequacy, and are more feasible for large-scale, routine monitoring of diets.