Evidence map›Paper›PMID 22729968›Full record

ArticleEuropean journal of nutrition2013

Dietary patterns and breast cancer risk among women in northern Tanzania: a case-control study.

Irmgard Jordan, Antje Hebestreit, Britta Swai, Michael B Krawinkel

Abstract read
In one paragraph

Article in European journal of nutrition, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Dietary patterns in Tanzania's transitioning rural and urban areas.Journal of health, population, and nutrition · 2025
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  17. Breast cancer in Sub-Saharan Africa: opportunities for prevention.Breast cancer research and treatment · 2014
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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

4 authors.

Irmgard JordanInstitute of Nutritional Sciences, Justus-Liebig-University Giessen, Wilhelmstr. 20, 35392, Giessen, Germany. Irmgard.Jordan@ernaehrung.uni-giessen.de
Antje Hebestreit
Britta Swai
Michael B Krawinkel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is the second most common cancer among women in the Kilimanjaro Region of Tanzania. It was tested within a case-control study in this region whether a specific dietary pattern impacts on the breast cancer risk.

methodsA validated semi-quantitative Food Frequency Questionnaire was used to assess the dietary intake of 115 female breast cancer patients and 230 healthy age-matched women living in the same districts. A logistic regression was performed to estimate breast cancer risk. Dietary patterns were obtained using principal component analysis with Varimax rotation.

resultsThe adjusted logistic regression estimated an increased risk for a "Fatty Diet", characterized by a higher consumption of milk, vegetable oils and fats, butter, lard and red meat (OR = 1.42, 95 % CI 1.08-1.87; P = 0.01), and for a "Fruity Diet", characterized by a higher consumption of fish, mango, papaya, avocado and watery fruits (OR = 1.61, 95 % CI 1.14-2.28; P = 0.01). Both diets showed an inverse association with the ratio between polyunsaturated and saturated fatty acids (P/S ratio).

conclusionA diet characterized by a low P/S ratio seems to be more important for the development of breast cancer than total fat intake.

Indexed as

DietAdultAgedAged, 80 and overAlgorithmsBreast NeoplasmsCase-Control StudiesDietary FatsDiet, High-FatFatty AcidsFatty Acids, UnsaturatedFemaleHumansLogistic ModelsMiddle AgedPrincipal Component AnalysisDietary FatsFatty AcidsFatty Acids, Unsaturated

Identifiers

PMID22729968
PMCPMC3611024

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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.