Evidence map›Paper›PMID 39985957›Full record

ArticleThe journal of nutrition, health & aging2025

Temporal trends in the planetary health diet index and its association with cardiovascular, kidney, and metabolic diseases: A comprehensive analysis from global and individual perspectives.

Haoxian Tang, Xuan Zhang, Nan Luo, Jingtao Huang, Qinglong Yang, Hanyuan Lin, Mengyue Lin, Shiwan Wu, Jiasheng Wen, Jianan Hong and 4 more

Abstract read
In one paragraph

Article in The journal of nutrition, health & aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Haoxian TangShantou University Medical College, Shantou, Guangdong, China; Department of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Xuan ZhangShantou University Medical College, Shantou, Guangdong, China; Department of Bone & Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Nan LuoShantou University Medical College, Shantou, Guangdong, China; Department of Psychiatry, Shantou University Mental Health Center, Shantou, Guangdong, China.
Jingtao HuangShantou University Medical College, Shantou, Guangdong, China; Department of Sports Medicine and Rehabilitation, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Qinglong YangShantou University Medical College, Shantou, Guangdong, China; Department of Urology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Hanyuan LinShantou University Medical College, Shantou, Guangdong, China; Department of Urology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Mengyue LinShantou University Medical College, Shantou, Guangdong, China; Department of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Shiwan WuShantou University Medical College, Shantou, Guangdong, China; Department of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Jiasheng WenShantou University Medical College, Shantou, Guangdong, China; Department of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Jianan HongDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China; Shantou University Medical College, Shantou, Guangdong, China.
Pan ChenShantou University Medical College, Shantou, Guangdong, China; Department of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Liwen JiangShantou University Medical College, Shantou, Guangdong, China; Department of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Yequn ChenDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China; Clinical Research Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China; Human Phenome Institute, Shantou University Medical College, Shantou, Guangdong, China; Guangdong Engineering Research Center of Human Phenomics, Shantou, Guangdong, China. Electronic address: gdcycyq@163.com.
Xuerui TanDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China; Clinical Research Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China; Human Phenome Institute, Shantou University Medical College, Shantou, Guangdong, China; Guangdong Engineering Research Center of Human Phenomics, Shantou, Guangdong, China. Electronic address: doctortxr@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiet plays a critical role in human health and environmental sustainability, particularly in cardiovascular, kidney, and metabolic (CKM) diseases. However, the variations in the Planetary Health Diet Index (PHDI) across populations, regions, and over time, as well as its association with CKM disease burdens, remain insufficiently explored.

methodsWe assessed PHDI scores using data from 185 countries (1990-2018) from the Global Dietary Database, examining demographic characteristics and temporal trends. The Global Burden of Disease Study was used to evaluate the associations between PHDI and CKM disease burdens, including incidence, prevalence, mortality, and disability-adjusted life years. CKM syndrome was defined by the American Heart Association. Individual-level data from the National Health and Nutrition Examination Survey (NHANES) were also used to assess the impact of PHDI on CKM risks and mortality.

resultsFrom 1990 to 2018, while overall PHDI scores remained relatively stable between sexes, the composition of PHDI scores shifted across different age groups. In 2018, the mean PHDI score was 42.80 (95% uncertainty interval [UI] 42.49-46.50) for males and 44.65 (95% UI 44.53-47.82) for females. Higher PHDI scores were observed among females, older adults, urban residents, individuals with higher education, and those from South Asia. Globally, consumption of red/processed meat, saturated oils/trans fats, and added sugars substantially exceeded the EAT-Lancet Commission's reference values. Higher PHDI scores were generally associated with lower CKM disease burdens, although these associations varied by disease subtype. In individual-level analysis, including 45,460 NHANES participants (weighted mean age: 47.21 years, 51.4% female), each 10-point increase in PHDI was linked to a 13.7% reduction in stage 3/4 CKM syndrome risk, an 11.1% reduction in stage 4 CKM syndrome risk, and lower incidences and mortality rates for cardiovascular diseases, metabolic diseases, and chronic kidney disease.

conclusionsFrom 1990 to 2018, significant changes occurred in the components of the PHDI, with notable variations by demographics and region. Higher PHDI scores may reduce CKM disease burdens, warranting further investigation into specific disease subtypes.

Indexed as

Cardiovascular DiseasesDietDiet, HealthyGlobal HealthKidney DiseasesMetabolic DiseasesAdultAgedFemaleGlobal Burden of DiseaseHumansIncidenceMaleMiddle AgedNutrition SurveysCardiovascular, kidney, and metabolic diseasesGlobal burden of diseaseGlobal dietary databaseNational health and nutrition examination surveyPlanetary health diet index

Identifiers

PMID39985957
PMCPMC12180045

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.