BackgroundEpidemiological studies have found that high whole grain intake may be associated with a reduced risk of breast cancer. However, the evidence has not been consistent. We conducted a meta-analysis to quantitatively assess the association between whole grain intake and breast cancer risk.MethodsRelevant observational studies were identified by searching PubMed, Embase, Cochrane library databases, and Google Scholar through April 2017. Summary relative risk (RR) estimates were calculated using random-effects meta-analysis.ResultsA total of 11 studies, including 4 cohort and 7 case-control studies and involving 131,151 participants and 11,589 breast cancer cases, were included in the current meta-analysis. The pooled RR of breast cancer for those with high versus low whole grain intake was 0.84 (95% confidence interval [CI]: 0.74 to 0.96, p = 0.009; I2 = 63.8%, p for heterogeneity = 0.002). Subgroup analysis by study design found a significant inverse association in the case-control studies (RR: 0.69; 95% CI: 0.56 to 0.87, p = 0.001; I2 = 58.2%, p for heterogeneity = 0.026), but not in the cohort studies (RR, 0.96; 95% CI: 0.82 to 1.14, p = 0.69; I2 = 66.7%, p for heterogeneity = 0.029). In addition, stratified analysis suggested that sample size could be a potential source of heterogeneity.ConclusionsResults of the current meta-analysis suggest that high intake of whole grains might be inversely associated with a reduced risk of breast cancer, and the inverse association was only observed in case-control but not cohort studies. More large-scale cohort studies are needed to confirm the inverse association observed.Electronic supplementary materialThe online version of this article (10.1186/s12937-018-0394-2) contains supplementary material, which is available to authorized users.

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The present study aimed to use the autoregressive integrated moving average (ARIMA) model to forecast foodborne disease incidence in Shenzhen city and help guide efforts to prevent foodborne disease. The data of foodborne diseases in Shenzhen comes from the infectious diarrhea surveillance network, community foodborne disease surveillance network, and student foodborne disease surveillance network. The incidence data from January 2012 to December 2017 was used for the model-constructing, while the data from January 2018 to December 2018 was used for the model-validating. The mean absolute percentage error (MAPE) was used to assess the performance of the model. The monthly foodborne disease incidence from January 2012 to December 2017 in Shenzhen was between 954 and 32,863 with an incidence rate between 4.77 and 164.32/100,000 inhabitants. The ARIMA (1,1,0) was an adequate model for the change in monthly foodborne disease incidence series, yielding a MAPE of 5.34%. The mathematical formula of the ARIMA (1,1,0) model was (1 − B) × log(incidencet) = 0.04338 + εt/(1 + 0.51106B). The predicted foodborne disease incidences in the next three years were 635,751, 1,069,993, 1,800,838, respectively. Monthly foodborne disease incidence in Shenzhen were shown to follow the ARIMA (1,1,0) model. This model can be considered adequate for predicting future foodborne disease incidence in Shenzhen and can aid in the decision-making processes.

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