Evidence map›Paper›PMID 37892526›Full record

ArticleNutrients2023

Generational Differences in Food Consumption among Chinese Adults of Different Ages.

Lijie Guo, Feifei Huang, Mengran Liu, Yueyang Zhang, Jiguo Zhang, Bing Zhang, Huijun Wang

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Generational Influence on Diet Quality: An Analysis Based on Vigitel 2023.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026
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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

7 authors at 2 institutions in 2 countries.

Lijie GuoNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Feifei HuangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0002-7496-4908
Mengran LiuDepartment of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Yueyang ZhangDepartment of Health Services, Policy & Practice, School of Public Health, Brown University, Providence, RI 02903, USA.
Jiguo ZhangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0003-3266-8999
Bing ZhangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Huijun WangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Chinese Center For Disease Control and Prevention · CNBrown University · US

Funding

MONITORING SOCIAL CHANGE: HEALTH, REPRODUCTION, AGINGR01HD030880 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 1994 to 2024
$27.0M
Monitoring Social Change: Dynamics Of Aging And Cognitive FunctionR01AG065357 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 2020 to 2024
$3.6M
Emergence of Cardiometabolic Risk Across the Lifecycle in ChinaR01HL108427 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2012 to 2015
$2.7M
Transition to a Western diet and cardiometabolic risk: biomarkers derived from the microbiomeR01DK104371 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2015 to 2018
$2.5M
Nutrition-Related NCD Prevention Training in ChinaD43TW009077 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2011 to 2015
$1.1M
FIC NIH HHS D43 TW009077NHLBI NIH HHS R01 HL108427NIA NIH HHS R01 AG065357NICHD NIH HHS R01 HD030880NIDDK NIH HHS R01 DK104371
6 · The paper itself

Abstract

Limited knowledge currently exists regarding the dynamics of generational shifts in food consumption among adult residents in China. This study aimed to investigate the generational differences in dietary status among different generations of Chinese adult residents aged 20 years and older. Survey participants from four waves (1991, 2000, 2009, and 2018) of the China Health and Nutrition Survey (CHNS) cohort were included in the study (N = 40,704), providing three-day 24 h dietary data. Participants were categorized into six age groups (20-29, 30-39, 40-49, 50-59, 60-69, and ≥70 years old), each corresponding to specific generations (Gen 10, 20, 30, 40, 50, 60, 70, 80, and 90) based on their age at the time of the survey. This study examined generational differences in the intake of cereals, animal-based foods, vegetables, fruits, dairy, energy, and the contribution of macronutrients to energy using chi-square tests and Kruskal-Wallis tests. All analyses were stratified by gender. Our findings revealed that younger generations exhibited lower daily intake of cereals, vegetables, energy, and contribution of carbohydrates to energy, compared to their older counterparts, regardless of gender. Conversely, regardless of male or female, younger generations showed higher daily consumption of animal-based foods, average fruit and dairy intake, fruit and dairy consumption rates, as well as contributions of protein and fat to energy, compared to older generations. The magnitude of generational differences in food consumption varied by age and gender. In addition, cereal and vegetable intake, energy intake, and contribution of carbohydrates to energy declined with age across all generations, while average dairy intake, fruit and dairy consumption rates, and the contribution of fat to energy tended to increase, regardless of gender. In conclusion, generational differences in food consumption were evident among different generations of Chinese adult residents, characterized by an increase in animal-based food intake and the contribution of fat to energy among generations. Attention should be directed towards addressing the eating behavior of younger generations.

Indexed as

DietEast Asian PeopleAdultAgedAge FactorsCarbohydratesEnergy IntakeFeeding BehaviorFemaleFruitHumansMaleNutrition SurveysVegetablesCarbohydratesChina Health and Nutrition Surveydietaryfood consumptiongenerational differences

Identifiers

PMID37892526
PMCPMC10610285
OpenAlexW4387812512

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.