Evidence map›Paper›PMID 38762743›Full record

ArticleNutrition journal2024

Trends in the contribution of greenhouse gas emissions from food and beverage purchases in Mexico: 1989-2020.

Francisco Canto-Osorio, Brent A Langellier, Mishel Unar-Munguia, Tonatiuh Barrientos-Gutiérrez, Juan A Rivera, Ana V Diez-Roux, Dalia Stern, Nancy López-Olmedo

Abstract read
In one paragraph

Article in Nutrition journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. Urban Environments, Health, and Environmental Sustainability: Findings From the SALURBAL Study.Journal of urban health : bulletin of the New York Academy of Medicine · 2024
    Review
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

8 authors.

Francisco Canto-OsorioCenter for Research in Population Health, National Institute of Public Health, Av. Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos, 62100, Mexico.
Brent A LangellierDornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Mishel Unar-MunguiaCenter for Research on Health and Nutrition, National Institute of Public Health, Cuernavaca, Morelos, Mexico.
Tonatiuh Barrientos-GutiérrezCenter for Research in Population Health, National Institute of Public Health, Av. Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos, 62100, Mexico.
Juan A RiveraCenter for Research in Population Health, National Institute of Public Health, Av. Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos, 62100, Mexico.
Ana V Diez-RouxDornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Dalia SternCenter for Research in Population Health, National Institute of Public Health, Av. Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos, 62100, Mexico. dalia.stern@insp.mx.
Nancy López-OlmedoCenter for Research in Population Health, National Institute of Public Health, Av. Universidad 655, Santa María Ahuacatitlán, Cuernavaca, Morelos, 62100, Mexico. nancy.lopez@insp.mx.

Funding

Wellcome TrustWellcome Trust 205177/Z/16/Z
6 · The paper itself

Abstract

backgroundAssessing the trends in dietary GHGE considering the social patterning is critical for understanding the role that food systems have played and will play in global emissions in countries of the global south. Our aim is to describe dietary greenhouse gas emissions (GHGE) trends (overall and by food group) using data from household food purchase surveys from 1989 to 2020 in Mexico, overall and by education levels and urbanicity.

methodsWe used cross-sectional data from 16 rounds of Mexico's National Income and Expenditure Survey, a nationally representative survey. The sample size ranged from 11,051 in 1989 to 88,398 in 2020. We estimated the mean total GHGE per adult-equivalent per day (kg CO2-eq/ad-eq/d) for every survey year. Then, we estimated the relative GHGE contribution by food group for each household. These same analyses were conducted stratifying by education and urbanicity.

resultsThe mean total GHGE increased from 3.70 (95%CI: 3.57, 3.82) to 4.90 (95% CI 4.62, 5.18) kg CO2-eq/ad-eq/d between 1989 and 2014 and stayed stable between 4.63 (95% CI: 4.53, 4.72) and 4.89 (95% CI: 4.81, 4.96) kg CO2-eq/ad-eq/d from 2016 onwards. In 1989, beef (19.89%, 95% CI: 19.18, 20.59), dairy (16.87%, 95% CI: 16.30, 17.42)), corn (9.61%, 95% CI: 9.00, 10.22), legumes (7.03%, 95% CI: 6.59, 7.46), and beverages (6.99%, 95% CI: 6.66, 7.32) had the highest relative contribution to food GHGE; by 2020, beef was the top contributor (17.68%, 95%CI: 17.46, 17.89) followed by fast food (14.17%, 95% CI: 13.90, 14.43), dairy (11.21%, 95%CI: 11.06, 11.36), beverages (10.09%, 95%CI: 9.94, 10.23), and chicken (10.04%, 95%CI: 9.90, 10.17). Households with higher education levels and those in more urbanized areas contributed more to dietary GHGE across the full period. However, households with lower education levels and those in rural areas had the highest increase in these emissions from 1989 to 2020.

conclusionsOur results provide insights into the food groups in which the 2023 Mexican Dietary Guidelines may require to focus on improving human and planetary health.

Indexed as

Greenhouse GasesBeveragesCross-Sectional StudiesDietFamily CharacteristicsFoodGreenhouse EffectHumansMexicoGreenhouse GasesDietGreenhouse gas emissionsMexicoSocioeconomic statusTrends

Identifiers

PMID38762743
PMCPMC11102158

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.