N-Nitroso compounds (NOC) are potent animal carcinogens and potential human carcinogens. The primary source of exposure for most individuals may be endogenous formation, a process that can be inhibited by dietary polyphenols. To estimate the risk of gastric cancer (GC) in relation to the individual and combined consumption of polyphenols and NOC precursors (nitrate and nitrite), a population-based case-control study was carried out in Mexico City from 2004 to 2005 including 257 histologically confirmed GC cases and 478 controls. Intake of polyphenols, nitrate and nitrite were estimated using a food frequency questionnaire. High intakes of cinnamic acids, secoisolariciresinol and coumestrol were associated with an 50% reduction in GC risk. A high intake of total nitrite as well as nitrate and nitrite from animal sources doubled the GC risk. Odds ratios around 2-fold were observed among individuals with both low intake of cinnamic acids, secoisolariciresinol or coumestrol and high intake of animal-derived nitrate or nitrite, compared to high intake of the polyphenols and low animal nitrate or nitrite intake, respectively. Results were similar for both the intestinal and diffuse types of GC. Our results show, for the first time, a protective effect for GC because of higher intake of cinnamic acids, secoisolariciresinol and coumestrol, and suggest that these polyphenols reduce GC risk through inhibition of endogenous nitrosation. The main sources of these polyphenols were pears, mangos and beans for cinnamic acids; beans, carrots and squash for secoisolariciresinol and legumes for coumestrol. ' UICCKey words: nitrate; nitrite; diet; polyphenols; gastric cancer In Mexico, gastric cancer (GC) rates show an increasing trend with time, 1 in contrast to other countries, and remains the 2nd leading cause of cancer mortality. 2 Nitrate and nitrite are precursors for the endogenous formation of N-nitroso compounds (NOC), which are carcinogenic in animals and, potentially, in humans. 3 Ingested nitrate is absorbed in the small intestine and 25% is excreted in the mouth, where oral bacteria reduce about 20% to nitrite (about 5% of ingested nitrate).In the acidic stomach, nitrite forms nitrous acid, which decomposes into various reactive nitrogen species (RNS). Nitrite and RNS react with nitrosatable compounds, mainly amines and amides, to form NOC. 4 The formation of NOC is inhibited by some antioxidants, such as polyphenols 5,6 and vitamins C and E. 4,7 For this reason, a low consumption of these inhibitors of NOC formation, (INC) together with a high consumption of nitrate and/or nitrite, results in an increase in the endogenous formation of NOC. 3 Contrasting with consistent results showing an increase in the risk of GC because of nitrite consumption, 8 the association with nitrate intake is less certain. Some investigators observed no association with nitrate consumption 9-16 ; whereas, others have observed a decrease in GC risk with increasing nitrate consumption. 17,18 These apparent contradictory results reflect the...

The consumption of processed meat has been associated with noncardia gastric cancer, but evidence regarding a possible role of red meat is more limited. Our study aims to quantify the association between meat consumption, namely white, red and processed meat, and the risk of gastric cancer, through individual participant data meta-analysis of studies participating in the "Stomach cancer Pooling (StoP) Project". Data from 22 studies, including 11,443 cases and 28,029 controls, were used. Studyspecific odds ratios (ORs) were pooled through a two-stage approach based on random-effects models. An exposure-response relationship was modeled, using one and two-order fractional polynomials, to evaluate the possible nonlinear association between meat intake and gastric cancer. An increased risk of gastric cancer was observed for the consumption of all types of meat (highest vs. lowest tertile), which was statistically significant for red (OR: 1.24; 95% CI: 1.00-1.53), processed (OR: 1.23; 95% CI: 1.06-1.43) and total meat (OR: 1.30; 95% CI: 1.09-1.55). Exposure-response analyses showed an increasing risk of gastric cancer with increasing consumption of both processed and red meat, with the highest OR being observed for an intake of 150 g/day of red meat (OR: 1.85; 95% CI: 1.56-2.20). This work provides robust evidence on the relation between the consumption of different types of meat and gastric cancer. Adherence to dietary recommendations to reduce meat consumption may contribute to a reduction in the burden of gastric cancer. What's new?Consumption of processed meat has been associated with non-cardia gastric cancer, but evidence regarding a possible role of red meat is more limited. Here, the authors explore associations between white, red, and processed meat consumption and gastric cancer risk through an individual participant data meta-analysis of case-control studies within the Stomach cancer Pooling Project. An increased risk of gastric cancer was observed with high intakes of red and processed meat, with further confirmation through the computational and graphical depiction of the exposure-response associations. Adherence to dietary recommendations to reduce meat consumption may contribute to reducing the burden of gastric cancer.

To accelerate tuberculosis (TB) control and elimination, reliable data is needed to improve the quality of TB care. We assessed agreement between a surveillance dataset routinely collected for Uganda’s national TB program and a high-fidelity dataset collected from the same source documents for a research study from 32 health facilities in 2017 and 2019 for six measurements: 1) Smear-positive and 2) GeneXpert-positive diagnoses, 3) bacteriologically confirmed and 4) clinically diagnosed treatment initiations, and the number of people initiating TB treatment who were also 5) living with HIV or 6) taking antiretroviral therapy. We measured agreement as the average difference between the two methods, expressed as the average ratio of the surveillance counts to the research data counts, its 95% limits of agreement (LOA), and the concordance correlation coefficient. We used linear mixed models to investigate whether agreement changed over time or was associated with facility characteristics. We found good overall agreement with some variation in the expected facility-level agreement for the number of smear positive diagnoses (average ratio [95% LOA]: 1.04 [0.38–2.82]; CCC: 0.78), bacteriologically confirmed treatment initiations (1.07 [0.67–1.70]; 0.82), and people living with HIV (1.11 [0.51–2.41]; 0.82). Agreement was poor for Xpert positives, with surveillance data undercounting relative to research data (0.45 [0.099–2.07]; 0.36). Although surveillance data overcounted relative to research data for clinically diagnosed treatment initiations (1.52 [0.71–3.26]) and number of people taking antiretroviral therapy (1.71 [0.71–4.12]), their agreement as assessed by CCC was not poor (0.82 and 0.62, respectively). Average agreement was similar across study years for all six measurements, but facility-level agreement varied from year to year and was not explained by facility characteristics. In conclusion, the agreement of TB surveillance data with high-fidelity research data was highly variable across measurements and facilities. To advance the use of routine TB data as a quality improvement tool, future research should elucidate and address reasons for variability in its quality.

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