ArticleCancer epidemiology2020
Dietary glycemic index, glycemic load, and lung cancer risk: A case-control study in Los Angeles County.
Article in Cancer epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
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Authors and funding
11 authors.
Funding
Abstract
backgroundAlthough there is some evidence of positive associations between both the glycemic index (GI) and glycemic load (GL) with cancer risk, the relationships with lung cancer risk remain largely unexplored. We evaluated the associations between GI and GL with lung cancer.
methodsThe analyses were performed using data from a population-based case-control study recruited between 1999 and 2004 in Los Angeles County. Dietary factors were collected from 593 incident lung cancer cases and 1026 controls using a modified food frequency questionnaire. GI and GL were estimated using a food composition table. Adjusted odds ratios (ORs) and 95 % confidence intervals (CI) were estimated using unconditional logistic regression adjusting for potential confounders.
resultsDietary GI was positively associated with lung cancer (OR for upper vs. lower tertile = 1.62; 95 % CI: 1.17, 2.25). For histologic subtypes, positive associations were observed between GI and adenocarcinoma (OR for upper vs. lower tertile = 1.82; 95 % CI: 1.22, 2.70) and small cell carcinoma (OR for upper vs. lower tertile = 2.68; 95 % CI: 1.25, 5.74). No clear association between GL and lung cancer was observed.
conclusionThese findings suggest that high dietary GI was associated with increased lung cancer risk, and the positive associations were observed for both lung adenocarcinoma and small cell lung carcinoma. Replication in an independent dataset is merited for a broader interpretation of our results.
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