Evidence map›Paper›PMID 25636348›Full record

ArticleBMC public health2015

Four major dietary patterns identified for a target-population of adults residing in Newfoundland and Labrador, Canada.

Zhi Chen, Lin Liu, Barbara Roebothan, Ann Ryan, Jennifer Colbourne, Natasha Baker, Jing Yan, Peizhong Peter Wang

Abstract read
In one paragraph

Article in BMC public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Natural Food for Sarcopenia: A Narrative Review.The Malaysian journal of medical sciences : MJMS · 2022
    Review
  3. Article
  4. Article
  5. Article
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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

8 authors.

Zhi ChenDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. zc1476@mun.ca.
Lin LiuDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. ll3332@mun.ca.
Barbara RoebothanDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. broeboth@mun.ca.
Ann RyanDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. annr@mun.ca.
Jennifer ColbourneDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. jennifer_colbourne@hotmail.com.
Natasha BakerDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. natashabaker2729@gmail.com.
Jing YanSchool of Public Health, Tianjin Medical University, Tianjin, China. yanjing@tijmu.edu.cn.
Peizhong Peter WangDivision of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada. pwang@mun.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVery limited nutritional epidemiological studies conducted to explore the unique dietary exposure in Newfoundland and Labrador (NL). This study aims to identify and characterize major dietary patterns in the target-population from general adult NL residents and assess the associations with selected demographic factors.

methodsA total of 192 participants, aged 35-70 years, completed and returned a food-frequency questionnaire (FFQ) and participated in a telephone interview to collect demographic information. Dietary patterns were identified by common factor analysis. Univariate and multivariate linear regression analyses were used to assess determinants of the different food consumption patterns. Pearson's correlation coefficients were calculated for food scores of each pattern, total energy, and energy-adjusted nutrient intakes.

resultsFactor analyses identified four dietary patterns, which were labeled as "Meat", "Vegetable/fruit", "Fish", and "Grain" patterns. In combination, the four dietary patterns explained 63% of the variance in dietary habits of the study population. Multivariate linear regression analysis indicated an increasing trend of factor scores for Meat and Grain pattern with age. Male participants were found to be more likely to choose the Meat and Fish patterns. Current smokers and those married/living together tend to choose the Grain pattern. Pearson's correlation coefficients showed positive correlations between fat and cholesterol and the Meat pattern, fiber and the Vegetable/fruits pattern, protein and the Fish pattern, and carbohydrates and the Grain pattern.

conclusionThis study derived four dietary patterns and obtained their significant associations with specific demographic characteristics in this population. It identified one dietary consumption pattern (Fish) not yet seen in other studied populations. These findings will update the current dietary-health information published in this province, and contribute to further research into the association between dietary practices and health.

Indexed as

Feeding BehaviorAdultAgedCanadaFactor Analysis, StatisticalFemaleHumansInterviews as TopicLinear ModelsMaleMiddle AgedMultivariate AnalysisNewfoundland and LabradorSurveys and Questionnaires

Identifiers

PMID25636348
PMCPMC4318430

What OpenQuestion holds

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LicenceCC BY
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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.