Ann. Anim. Sci., Vol. 21, No. 2 (2021) 721–730 DOI: 10.2478/Aoas-2020-0070 Meta-Analysis of Escherichia Coli O157 Prevalen

Ann. Anim. Sci., Vol. 21, No. 2 (2021) 721–730 DOI: 10.2478/aoas-2020-0070

Meta-analysis of Escherichia coli O157 prevalence in foods of animal origin in Turkey

Serhat Al1♦, Aytaç Akçay2, Elif Çelik3, Güven Güngör3, Candan Güngör1, Harun Hızlısoy4

1Department of Food Hygiene and Technology, Faculty of Veterinary Medicine, Erciyes University, 38039 Kayseri, Turkey 2Department of Biostatistics, Faculty of Veterinary Medicine, Ankara University, 06110 Ankara, Turkey 3Department of Biometrics, Faculty of Veterinary Medicine, Erciyes University, 38039 Kayseri, Turkey 4Department of Veterinary Public Health, Faculty of Veterinary Medicine, Erciyes University, 38039 Kayseri, Turkey ♦Corresponding author: [email protected]

Abstract The present study aims to analyze the prevalence of E. coli O157 detected in foods of animal origin by meta-analysis. The prevalence of E. coli O157 detected in the different studies was combined to provide a common prevalence estimate, and heterogeneities between studies were investigated. The study material consisted of 49 studies investigating E. coli O157 prevalence in a total of 9600 food samples, including milk and dairy products, red meat and products, poultry meat and products, and cold appetizers between the years 1997 and 2019 in Turkey. In the meta-analysis, the Der- Simonian-Laird method was used. Meta-analyses were performed using the R 3.6.1. As a result of the meta-analysis, the common prevalence of E. coli O157 was 0.024 (0.018–0.029). As a result of the Egger’s Linear Regression Test, the study samples were found to be biased (t-value=6.092, P<0.001). To determine the source of heterogeneity between studies, sub-group and meta-regression analyses were performed in milk and dairy products, red meat and products, poultry meat and products, and ready-to-eat foods (RTEs). Accordingly, the prevalence of E. coli O157 in milk and dairy products, red meat and products, poultry meat and products, and RTEs was determined as 0.017, 0.031, 0.023, and 0.080 in Turkey, respectively. This study provides a stronger and more accurate estimation of the prevalence of E. coli O157 in foods of animal origin with the meta- analysis by eliminating inconsistencies in the effect of the sampling size of independent prevalence studies. However, in order to obtain accurate prevalence results in practice, it is necessary carefully to select the studies to be included in the analysis, to use the appropriate statistical model, and to interpret the results of the analysis correctly.

Key words: foodborne infections, E. coli O157, meta-analysis, occurrence

Enterohemorrhagic E. coli are epidemiologically important worldwide pathogens (Chapman et al., 2001). The primary source of the spread of these pathogens is ani- 722 S. Al et al. mal foods and waters. It can easily reach the minimal infective dose in foods in case of errors and omissions in food safety systems in the production chain (Levine et al., 1993). Meat and meat products are one of the primary sources of E. coli O157 (Parry et al., 1998; Slutsker et al., 1998). However, all animal originated foods pose a risk due to the lack of hygienic conditions and heat treatment in the production chain (Kimman et al., 2013). Asymptomatic carriers play an essential role in the epidemiology of infections (World Health Organization, 2018 a). E. coli O157 infections are characterized by moderate diarrhea becoming severe and hemorrhagic with individual differences (Ostroff et al., 1989). As well as severe hemorrhagic colitis, significant complications such as hemolytic uremic syndrome (HUS) and thrombotic thrombocytopenic purpura (TTP) are also seen (Morrison et al., 1986; Spika et al., 1986). The studies focused on prevalence of pathogenic E. coli in foods remain important (Gonzalez and Cerqueira, 2019; Goma et al., 2019; Khan et al., 2018) and various studies have been published regarding the determination of E. coli O157 prevalence in animal-originated food in Turkey (see supplementary file – available from the author). Since the results revealed in these studies differ from each other, more accurate and reliable results related to the prevalence of E. coli O157 are needed. Combining the results is an alternative solution since it is not possible to carry out studies in the entire population to see the exact prevalence. For this purpose, one of the most suitable methods is meta-analysis, which is a statistical procedure for syn- thesizing data from multiple studies (Hedges, 1992). This study aimed to determine the overall prevalence of E. coli O157, an important food pathogen in Turkey, by applying the meta-analysis. Besides, it was evaluated whether the statistical difference in the prevalence of the E. coli O157 was according to food types. E. coli O157 is an important food pathogen that is up to date in terms of food hygiene, and prevalence studies are continuing. The results obtained by the meta-analysis are of great importance for public health in terms of revealing the dangers of E. coli O157 and establishing the literature infrastructure for epidemiological studies.

Material and methods

Study selection Raw data for meta-analysis was formed from 49 studies regarding the prevalence of E. coli O157 in animal originated food products conducted in Turkey between the years 1997 and 2018 (see supplementary table for details – available from the author). Sub-groups of types of food were determined as red meat products, dairy products, poultry related foods, and ready to eat foods (RTEs). A total of 9600 samples from these sub-groups were included in the meta-analysis. The food types were determined according to the statistically sufficient number of E. coli O157 prevalence data to be used in sub-group analysis. The flow diagram showing the literature search and selection of eligible studies for meta-analysis was created according to recom- mendations from Vu-Ngoc et al. (2018) and given in Figure 1. Properties of studies included in the meta-analysis are given in the supplementary file. Meta-analysis of E. coli O157 prevalence in foods 723

Figure 1. Flow diagram of the literature search and selection of E. coli O157 prevalence studies conducted in Turkey

Statistical analysis After determining the studies that met the criteria for inclusion in the meta-analysis, publication bias was assessed using Egger’s Linear Regression test. In case significant publication bias was present, Trim and Fill method was used to evaluate the impact on model estimates (Duval and Tweedie, 2000). The random-effects model at a 95% confidence interval (CI) was used to determine the variance between the studies (DerSimonian and Laird, 1986). The statistical heterogeneity across the studies estimated in the random-effects model was assessed and quantified using Cochran’s Q test with (k-1) degrees of freedom and inverse variance index (I2) (Higgins et al., 2003). The variance component (τ2) statistic was used to determine between studies variance. Cochran’s Q statistic shows the sum of the weighted squares of the observed effect sizes. In meta-regression analysis, the dependent variable is the effect size (E. coli O157 prevalence) and its relationship with the independent variables (food types) was modeled with reference group (Dairy products). Statistical analysis and drawings of funnel and forest plot were performed with R 3.6.1 (www.r-project. org). 724 S. Al et al.

Results

As a result of the meta-analysis, a high level of heterogeneity was found between studies, and variance in observed effects was detected as 90.85% of the real variance (Q=529.90, df=48, I2=90.85). Egger’s linear regression test showed that the study sample was biased (t-value: 6.092, P<0.001). Therefore, a random-effect model was used. Main E. coli O157 prevalence in a different type of foods in Turkey was calculated as 0.024 (95% CI: 0.018–0.029) and was found to be statistically significant (P<0.001). Twenty-two studies on the asymmetric part of the funnel plot obtained as a result of the Trim and Fill method applied to eliminate publication bias were trimmed. The funnel plot created by the Trim and Fill method is shown in Figure 2. The trimmed studies and their missing counterparts were included in the study. Thus, main prevalence of E. coli O157 and Cochran’s Q statistic was corrected as 0.005 (95% CI: <0.001–0.011) and 1019.03, df=70, P<0.001, respectively. Forest plot of the meta-analysis of prevalence of E. coli O157 in Turkey was given in Figure 3.

Figure 2. Funnel plot for estimates in meta-analysis of E. coli O157 prevalence studies published from 1997 to 2018 (n = 49). Asymmetry of funnel shows publication bias in the meta-analysis. Proportion axis indicates logit event rate

Sub-group analysis was subjected to compare prevalence between dairy products, red meat products, RTEs, and poultry products; besides, meta-regression analysis was used to assess the relationship between E. coli O157 prevalence and food types. Table 1 shows the main prevalence of E. coli O157, CI of prevalence, Cochran’s Q, I2 and τ2 test statistics in the sub-group analysis by food types. Accordingly, the lowest prevalence of E. coli O157 was found in dairy products, and the highest prevalence was found in RTEs in the sub-group analysis. Moreover, it was determined that there was a significant difference betweenE. coli O157 prevalence of food types (Q=12.49, df=3, P<0.05). In the regression model, 57% of the variance in real effects is expressed by food sub-groups (R2 = 0.57). Meta-regression results of E. coli O157 prevalence of food types are shown in Table 2. According to the meta-regression analysis, food types were not found to have a statistically significant effect on the prevalence of E. coli O157 (P>0.05). Also, E. coli O157 risk of RTEs, poultry, red Meta-analysis of E. coli O157 prevalence in foods 725 meat products is higher than dairy products. Only the effect of RTEs was statistically significant (P<0.05).

Figure 3. Forest plot of the meta-analysis of prevalence of E. coli O157 in Turkey. The squares in the plot show the estimated effect sizes, and the lines on both sides of the squares show 95% confidence intervals for the effect sizes. The diamond at the bottom of the plot indicates the common effect size obtained by meta-analysis. The 95% confidence interval of the common effect size is expressed by the width of the diamond shape 726 S. Al et al.

Table 1. Sub-group analysis according to food types Main prevalence of E. coli O157 Heterogeneity E. coli O157 Food types number number Cochran’s positive prevalence 95% CI I2 (%) τ2 of study of sample Q sample Milk and dairy 14 2097 58 0.017 (0.008–0.027) 54.87 76.3 <0.000 products Red meat and 17 2822 109 0.031 (0.019–0.044) 85.19 81.2 <0.000 meat products RTEs 5 1362 154 0.080 (0.044–0.116) 280.92 98.6 <0.001 Poultry and 13 3319 74 0.023 (0.011–0.035) 77.41 84.5 <0.000 poultry products Total 49 9600 395 0.024 (0.018–0.029) 529.90 90.85 <0.000 Cochran’s Q: Differences of frequencies; I2 %: Inverse variance index; τ2: Variance component; CI: Confidence interval.

Table 2. Meta-regression analysis of the prevalence of E. coli O157 in food sub-groups Statistical significance Food types n Coefficient SE z values P values (Cochran’s Q) Dairy (reference) 14 – – – –

Poultry 13 0.01 0.01 0.06 0.954 Q=6,85 Red meat 17 0.01 0.01 0.82 0.413 df=3 RTEs 5 0.04 0.01 2.44 0.015 P=0.077 Intercept 49 0.02 0.01 3.17 0.002

n: Number of studies; SE: Standard Error; R2 Analog=0.57.

Discussion

Effective implementation of food-safety management systems plays an essential role in the prevention of food-borne infections at every point of the food chain from the production of raw materials to the kitchen. The usage of instruments such as risk assessments, mathematical modelling, and meta-analysis has been increasing to un- derstand epidemiological kinetics and provide adequate data to ensure food safety. Studies on the prevalence and incidence of food pathogens are still ongoing and these studies are performed with investigating the limited number of food samples. Moreover, sampling size and prevalence data presented as a result of the studies are seen to be insufficient to provide transparent information about the comparison of risk posed food types. According to the WHO, there are around 200 different types of pathogens that may spread via foods, and thus complex and long-term health problems can be formed, especially in sensitive individuals such as infants, elders, and pregnant women (World Health Organization, 2018 b). For this reason, in order to establish food safety in terms of public health, epidemiological data should be presented at the national, regional, and international Meta-analysis of E. coli O157 prevalence in foods 727 levels. Numerous studies have been conducted to estimate the prevalence of E. coli O157 in different animal-originated foods in Turkey. The prevalence obtained from these studies differs among themselves. Also, in order to obtain a more accurate estimation of the population, the number of samples should be increased. Meta-analysis is a statistical model that makes it possible to eliminate the prevalence differences in independent studies and increase the number of samples to increase representation (Hedges, 1992; Normand, 2005). Meta-analysis provides the opportunity to observe a more comprehensive sample, and therefore its accuracy is higher than in primary studies with a small sample size. The selection of a study to be included in the meta- analysis is crucial since the consistent effect sizes of the studies provide a more accurate estimate of the overall effect size (Blettner et al., 1999). This study aims to determine the main prevalence of E. coli O157 in animal- -originated foods in Turkey by analyzing with meta-analysis method. Besides, this study aims to make more powerful and accurate predictions and to reveal the E. coli O157 prevalence in the food of animal origin with eliminating inconsistencies regarding the effect size in the population in independent studies in Turkey. In the study, 9600 samples from 49 independent studies were implemented in meta analyses and main E. coli O157 prevalence in a different type of foods in Turkey was calculated as 2.4%. Since bias was found to be among the studies included in the meta-analysis, the main prevalence of E. coli O157 was corrected to 0.5% as a result of analyzes. The funnel plot (Figure 2) contributes to comment on whether the studies are published according to their statistical significance (Mavridis and Salanti, 2014). Symmetry was not provided in the plot drawn to determine the publication bias in the studies included in the meta-analysis. The results of the studies included in the meta-analysis are synthesized according to the random effects model and the findings are summarized with the forest plot (Figure 3). One of the most critical steps in the application of meta-analysis is the evaluation of heterogeneity between studies. Sampling error, study design, and population evaluation differences between studies may be the causes of heterogeneity. Sampling errors are of a random error type, and the causes are often unknown. The prevalence of E. coli O157 in animal foods was found to be very heterogeneous and due to the high heterogeneity, a random effect model was applied. I2 and τ2 statistics were used to determine the heterogeneity level and determine the true variance between studies, respectively. I2 was evaluated by using three categories considered low for <25%, modest for 25–50%, and large for 50% (Higgins et al., 2003). The highest heterogeneity was revealed in RTEs and this result could be related to the low number of E. coli O157 prevalence studies performed in Turkey (n=5). The sources of the differences between the studies can be determined by sub- group and meta-regression analyses. Comparisons can be made in terms of common effect sizes by measuring heterogeneity among the sub-groups formed in sub-group analyses. In the sub-group analysis to compare prevalence among the types of animal foods, the prevalence of E. coli O157 was the lowest with 0.017 (0.008–0.027) in dairy products and the highest with 0.080 (0.044–0.116) in RTEs. In the meta-regression analysis, the dependent variable is the effect size (prevalence of E. coli O157) and can be modeled by determining the relationship between 728 S. Al et al. the independent variable (food types) (Blettner et al., 1999; Borenstein et al., 2009). In the study, calculated coefficient of determination (R2) shows that 57% of the variance in real effects is explained by the independent variable and it was determined that RTEs pose a greater risk than dairy products regarding E. coli O157. Various meta-analysis studies have been performed on the E. coli in different food types. For instance, de Oliveira Elias et al. (2019) reported that the worldwide prevalence of EHEC in lettuce is 0.041 (95% CI: 0.005–0.078). In another study, the prevalence of Shiga-toxigenic E. coli in the European sub-region A (29 countries) categorized by the WHO was reported to be 1.429 (95% CI: 1.044–1.956) and 0.670 (95% CI: 0.507–0.886) in red meat and dairy products, respectively (Devleesschau- wer et al., 2019). In another meta-analysis, the prevalence of food-borne pathogenic E. coli was reported to be 0.043 (95% CI: 0.033–0.052) in China (Paudyal et al., 2018). In a meta-analysis study on the prevalence of foodborne pathogens in Afri- can countries, the prevalence of foodborne E. coli (including ETEC, VTEC, STEC, EHEC) was reported to be at the level of 0.354 (95% CI) (Paudyal et al., 2017). In another study, the prevalence of E. coli O157 was found to be 0.040 (95% CI: 0.030–0.050) in Ethiopia using meta-analysis (Assefa, 2019). In a study conducted in Iran, the prevalence of genes encoding ESBL among E. coli isolates was subjected to meta-analysis and it was reported that the frequency of blaTEM, blaSHV, and blaCTX-M was 51, 37 and 45%, respectively (Ghaderi et al., 2020). Other aspects have been increasing in recent years as well as the widespread use of meta-analysis in the prevalence of foodborne pathogens. A meta-analysis study was performed on the frequency of Shiga toxigenic E. coli infections, antibiotic treatment, and risk of HUS complication (Freedman et al., 2016). Garg et al. (2003) conducted a meta-analysis of the long-term renal prognosis of diarrhea-associated HUS patients. The risk of HUS was determined by a meta-analysis after antibiotic treatment of E. coli O157:H7 infections (Safdar et al., 2002). A meta-analysis study was conducted on Ciprofloxacin (a second-generation quinolone) resistance in community and hospital-acquired E. coli urinary tract infections (Fasugba et al., 2015). In a meta-analysis study on the risks posed by coliforms in drinking waters, it was revealed that there was no statistical relationship between diarrhea and E. coli that could exist in drinking waters (Gruber et al., 2014). Combining small individual studies with the meta-analysis allows for stronger and more accurate estimation of population impact size and to work with large samples. Besides, allowing for the removal of inconsistencies has made this method increasingly important. In order to obtain accurate results in practice, it is necessary carefully to select the papers, use the appropriate statistical model, and interpret the results of the analysis correctly. Conflict of Interest The authors declare that there is no conflict of interest in this study.

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Received: 26 II 2020 Accepted: 2 VII 2020