The current study aimed to investigate the relationship between red and white meat subtypes, processed meat (divided into traditional “Khlii, Kaddid” and industrially processed meat) and colorectal cancer (CRC) risk, considering CRC subsites, in Moroccan adults. A case–control study was conducted including 2,906 matched case–control pairs recruited from the five largest university hospitals in Morocco. Dietary data were collected through a validated Food Frequency Questionnaire (FFQ). Multivariable odds ratios (OR) and 95% confidence intervals (CI), for the association of CRC risk with meat consumption (high vs. low intake), were estimated using conditional logistic regression models, adjusted for relevant confounding variables. Overall, consumption of red meat was positively associated with colon cancer and CRC risk (OR = 1.23, 95% CI = 1.05–1.44; OR = 1.14, 95% CI = 1.02–1.27), respectively. In contrast, no significant association was observed between the consumption of red meat and rectal cancer risk (OR = 1.05, 95% = 0.90–1.23). Interestingly, while processed meat from industrial processes was positively associated with colon cancer, rectal cancer and CRC (OR = 1.61, 95% CI = 1.27–2.04; OR = 1.73, 95% CI = 1.34–2.23; OR = 1.67, 95% CI = 1.41–1.98), processed meat prepared using traditional methods was inversely associated with colon cancer and CRC risk (OR = 0.74, 95% CI = 0.57–0.98; OR = 0.77, 95% CI = 0.64–0.93), respectively. Furthermore, positive associations were observed between poultry intake and colon cancer risk among men (OR = 1.27, 95% CI = 1.01–1.59). Our study showed similar associations between the consumption of red meat and CRC risk in Morocco as in developed countries, while inverse associations were found for traditionally processed meat products. This is the first study to investigate the differential effects of traditional vs. westernized processed meat products in a developing country. Other studies are needed to confirm these findings and to understand the physiological pathways underlying these associations.
Background: Colorectal cancer (CRC) is a global public health problem, an estimated of 1.4 million cases were diagnosed worldwide in 2012. Studies in health and nutrition confirmed that dietary factors were strongly associated with CRC risk. Aim: The objective of this empirically study was to reveal unobserved dietary profiles that were associated favorably or unfavorably with CRC risk in Moroccan study population. Methods: This case-control study included a total of 2906 participants in five centers, 1453 cases and 1453 controls, and was gender, age and center matched. Statistical exploratory data reduction methods were performed in this study population based on a specific scientific hypothesis linking dietary behavior and colorectal cancer risk. Principal component analysis (PCA) was applied separately in cases and in controls as individuals and with FFQ nutritional group's heads items as variables. The correlation matrix of food variables was examined to explain most of the variation in the data, reducing a large number of food variables to a smaller set that captures the major dietary factors differences in Moroccan population. Results: Three alimentary profiles were identified for controls based on three principal component analysis, which the first one was highly positive with high cereals, fruits and nuts, legumes, fish, olive oil, dairy products and legumes consumption, and was highly negative with an increasing consumption of poultry and red meat. This component explained 26.5% of the variance in initial data and described a healthy pattern characterized with high fiber intake. In opposite, five principal components were identified for cases that indicated five nutritional profiles with a predominance of dairy products, nuts, fish consumption and low legumes, olive oil and fruits intake: its explained 15.37% of total variance. Conclusion: PCA analysis is a multidimensional factor analysis method that was used in this epidemiologic study to describe the variance in our big database in relation with CRC risk among Moroccan people. This method needs a supervised analysis such as linear discriminant analysis (LDA) to give interpretation and prediction models of CRC risk related to nutritional behavior among this study population.
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