Evidence map›Paper›PMID 35845764›Full record

ArticleFrontiers in nutrition2022

Effect of red meat, vegetable, tobacco, and alcohol consumption on national cancer mortality index: Data from 1989 to 2013 in 37 developed countries.

Myung-Bae Park

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Consumption of Meat in Brazil: A Perspective on Social Inequalities and Food and Nutrition Security.International journal of environmental research and public health · 2024
    Article
  4. Article
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

1 author.

Myung-Bae ParkDepartment of Health and Welfare, Pai Chai University, Daejeon, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to examine the association between red meat (RM) and death from all types of cancer, as well as its association with the incidence of colon cancer in developed countries. We selected RM, vegetable, tobacco, alcohol consumption, and socioeconomic status as the dependent variables' risk factors and performed ordinary least squares (OLS) and a fixed-effect model (FEM) analysis. Data from 1989 to 2013 for 37 Organization for Economic Cooperation and Development (OECD) countries. According to the FEM, cancer death had statistically significant associations with education level (Coef = -0.022, P = 0.009), total health expenditure (Coef = -0.049, P = 0.000), aging rate (Coef = -0.178, P = 0.000), tobacco consumption (Coef = 0.096, P = 0.000), RM consumption (Coef = 0.107, P = 0.000), and vegetable consumption (Coef = -0.034, P = 0.000). A similar trend was also observed in the 3 and 5-year lagged models. RM consumption also demonstrated a significantly positive association with the incidence of colon cancer in the OLS. According to the scatter plots and fitted lines based on the recommended allowance RM consumption, cancer deaths and incidence of colon cancer increased as consumption increased in the excess consumption group. Regarding vegetable consumption, cancer deaths and incidence of colon cancer decreased as consumption increased in the group exceeding the recommended allowance level. RM consumption was found to be higher than the recommended allowance level. RM consumption increased cancer deaths and the incidence of colon cancer. There is justification for public health interventions to limit RM consumption in major developed countries.

Indexed as

alcoholcancercolon cancermortalityred meattobaccovegetable

Identifiers

PMID35845764
PMCPMC9277575

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Registered trials

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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.