Dietary factors and risk for endometriosis: a Mendelian randomization analysis

Dietary factors and risk for endometriosis: a Mendelian randomization analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dietary factors and risk for endometriosis: a Mendelian randomization analysis Xia Zhang, Qiaomei Zheng, Lihong Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4062748/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Aims Observational studies have reported an association between dietary factors and endometriosis, but the causality remains unknown. The study aimed to evaluate the potential causal effect of dietary factors on endometriosis. Methods We performed a two-sample Mendelian randomization (MR) analysis to investigate the effects of 18 diet-related exposure factors (alcoholic drinks per week, alcohol intake frequency, processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, salad/raw vegetable intake, coffee intake, dried fruit intake) on the risk of endometriosis using summary statistics from the genome-wide association study (GWAS). The inverse variance weighted (IVW) method was used to deduce the causal association between dietary factors and endometriosis, and sensitivity analyses were further performed. Results Processed meat intake (OR=0.550; 95%CI:0.314-0.965; p=0.037) and salad / raw vegetable intake (OR=0.346; 95%CI:0.127-0.943; p=0.038) were discovered as protective factors for endometriosis. Heterogeneity test revealed no significant heterogeneity (processed meat intake: p IVW =0.607, p MR-Egger =0.548; salad / raw vegetable intake: p IVW =0.678, p MR-Egger =0.620). MR-Egger regression test didn’t support any evidence for horizontal pleiotropy (processed meat intake: p for intercept=0.865; salad / raw vegetable intake: p for intercept=0.725). No causal relationship was found between other dietary intakes and endometriosis. Conclusion These findings suggest that processed meat intake and salad/raw vegetable intake are associated with a decreased risk of endometriosis, but further investigation is required. dietary intake endometriosis mendelian randomization causal association Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Endometriosis is an oestrogen-dependent chronic inflammatory process characterized by the presence of endometrial-like tissue outside the uterus, primarily on pelvic tissues [ 1 ] . Common disease symptoms, including severe chronic pelvic pain, secondary dysmenorrhea and infertility, substantially alter the patient’s work productivity, social life and psychological well-being. This condition affects 6%-10% of reproductive-age women worldwide and represents a considerable burden on society [ 2 , 3 ] . The core goals of endometriosis treatment proclaimed by the UK Endometriosis Association are to minimize diagnosis time and ensure patients have access to comprehensive treatment and support [ 4 ] . However, the diagnosis is often delayed because symptom severity does not correlate with the extent of endometrial lesions. Therefore, we must fully understand the etiology of endometriosis to mitigate its health consequences. The causes of this condition include epigenetic, autoimmune, hormonal and environmental factors such as exercise and diet [ 5 ] . A previous study has reported the role of diet in several chronic diseases [ 6 ] . Dietary factors may directly contribute to the progression and severity of endometriosis due to their involvement in oxidative stress, muscle contraction, inflammation and steroid hormone metabolism [ 7 ] . Understanding how dietary changes affect patients with endometriosis holds significant implications for both clinicians and patients. Some observational studies [ 8 – 10 ] have found an association between the consumption of green vegetables, fresh fruit, red meat, dairy and fish with endometriosis. However, the observational study is susceptible to confounding variables such as geographical and ethnic disparities, age differences, and environmental factors. Compared with other research methods, mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to estimate the causal relationships between exposure and disease outcome, which is not affected by common confounding factors or reverse causation bias. [ 11 ] As far as we know, there have been few MR studies on the association between dietary factors and endometriosis. Therefore, we performed an MR analysis to explore the causal effect of dietary factors on endometriosis. Materials and methods Study design The study design is given in Fig. 1 . The genome-wide association study (GWAS) summary statistics used in this work are available from IEU Open GWAS (( https://gwas.mrcieu.ac.uk/ ), and the samples are all from people of European ancestry in order to mitigate potential bias from population stratification. Also, the ethics vote is not necessary for this study due to IEU Open GWAS is a publicly available database and each study included in it was approved by the local Ethical Review Authority. In MR analysis, eligible single nucleotide polymorphisms (SNPs) used as valid IVs should satisfy three basic assumptions: relevance, independence and the exclusion restriction, as shown in Fig. 2 . Data sources We performed a standard two-sample MR analysis to investigate the causal relationship between dietary factors and endometriosis. In total, eighteen diet-related exposure factors were identified: alcoholic drinks per week, alcohol intake frequency, processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, salad/raw vegetable intake, coffee intake and dried fruit intake. Summary GWAS data for exposure and outcome were extracted directly from the IEU Open GWAS database. More detailed information is presented in Table 1 . Table 1 Information of the exposures and outcome datasets IEU GWAS id Exposure and Outcome Population Identified SNPs Participants included in analysis F- statistics ieu-b-73 Alcoholic drinks per week European 33 335394 21.4413 ukb-b-5779 Alcohol intake frequency European 92 462346 18.6053 ukb-b-6324 Processed meat intake European 23 461981 15.1311 ukb-b-8006 Poultry intake European 7 461990 15.0437 ukb-b-2862 Beef intake European 14 461053 15.9647 ukb-b-17627 Non-oily fish intake European 11 460880 18.0146 ukb-b-2209 Oily fish intake European 60 460443 17.5199 ukb-b-5640 Pork intake European 13 460162 15.0602 ukb-b-14179 Lamb/mutton intake European 30 460006 14.6486 ukb-b-11348 Bread intake European 25 452236 17.9552 ukb-b-1489 Cheese intake European 60 451486 13.9740 ukb-b-8089 Cooked vegetable intake European 17 448651 16.8211 ukb-b-6066 Tea intake European 39 447485 24.9048 ukb-b-3881 Fresh fruit intake European 52 446462 18.8879 ukb-b-15926 Cereal intake European 38 441640 17.4987 ukb-b-1996 Salad / raw vegetable intake European 18 435435 14.4590 ukb-b-5237 Coffee intake European 38 428860 29.1311 ukb-b-16576 Dried fruit intake European 39 421764 17.1519 finn-b-N14_ENDOMETRIOSIS Endometriosis European NA 77257 IVs selection To ensure that the conclusion regarding the causal effect of diet-related factors on endometriosis was accurate, we used a series of quality control criteria to satisfy the three fundamental assumptions of MR analysis. Firstly, we obtained the SNPs using a GWAS p-value < 5×10 − 8 and excluded SNPs that were in linkage disequilibrium (LD) (clumping window = 10000kb; r2 < 0.001). Then, we calculated the F-statistics, using the rigorous mathematical formula: F = R 2 ×(N-K-1)/[K×(1-R 2 )] (R 2 : the proportion of exposure variance explained by each genetic variant, R 2 = 2×MAF×(1-MAF)×(Beta/SD) 2 ; N: the sample size of the GWAS; K: the number of SNP), to eliminate the bias arising from weak instrumental variables in the findings (F statistic > 10) [ 12 ] . Finally, SNPs harmonization was also performed by removing palindrome SNPs with intermediate allele frequencies or SNPs with incompatible alleles. Statistical analysis In the current study, we adopted inverse variance weighting (IVW) as the primary MR approach to calculate the causal effect of all SNPs. In addition, we ran MR Egger, weighted median, simple mode, and weighted mode as a complement to test the reliability and stability of the results. When utilizing the IVW method, it is necessary to ensure that all IVs in the analysis are of robust validity [ 13 ] . In contrast to IVW, the MR Egger method allows all IVs to be voided [ 14 ] . And the weighted median method provides a less biased causal estimation as long as no more than 50% of IVs are invalid [ 15 ] . Therefore, when the three methods are consistent, the results will be more persuasive. In addition, the weighted mode is less capable of detecting causation, but it is sensitive when the largest subset of IVs with similar causal effects is valid [ 16 ] . And finally, the estimated causal effects of individual SNPs were quantified as the odds ratios (ORs) from the Wald ratio method. Sensitivity analysis After MR analysis, we performed sensitivity analysis, including heterogeneity and pleiotropy, to further validate the robustness of the results. We used the Cochran’s Q statistic of the IVW method and Rucker’s Q statistic of the MR Egger method to identify heterogeneity, where p 0.05 suggested a lack of horizontal pleiotropy [ 14 ] . More rigorously, we conducted leave-one-out analysis to detect if there was any single SNP disproportionately responsible for the results by removing each instrumental SNP in turn. Finally, we utilized scatter and forest plots to visualize the results of the MR analysis. All statistical analyses were performed in R using the TwoSampleMR package. Results Overall, we systematically curated genome-wide significant SNPs associated with 18 kinds of food intake exposures to examine the potential causal effects of dietary factors on the risk of endometriosis. These different exposure factors could be categorized into six groups, including vegetable intake (salad/raw vegetable intake and cooked vegetable intake), meat intake (processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, and lamb/mutton intake), staple food intake (bread intake and cereal intake), beverage intake (alcoholic drinks per week, alcohol intake frequency, tea intake, and coffee intake), fruit intake(dried fruit intake and fresh fruit intake), and another food intake (cheese intake). As shown in Table 1 , the number of SNPs chosen as IVs for each diet-related factor ranged from 7 to 92 after a series of quality control steps. Moreover, the F statistics were calculated for each instrument-exposure association and none was less than 10 (range: 13.9740 to 29.1311), suggesting that all SNPs were strong IVs (Table 1 ). The MR estimates from different methods are presented in Table 2 . In this study, two causal associations from 18 food intakes were observed for endometriosis (p < 0.05 by IVW method). As the Figs. 3 ,4A,4Bshow, the IVW method showed that processed meat intake (OR = 0.550; 95%CI:0.314–0.965; p = 0.037) was significantly associated with a decreased risk of endometriosis. Similarly, salad / raw vegetable intake (OR = 0.346; 95%CI:0.127–0.943; p = 0.038) was discovered as a protective factor. Heterogeneity test revealed no significant heterogeneity of these IVs (processed meat intake: p IVW =0.607, p MR−Egger =0.548; salad / raw vegetable intake: p IVW =0.678, p MR−Egger =0.620), so we chose the fixed-effect IVW model for MR analysis. In addition, MR-Egger regression test didn’t support any evidence for horizontal pleiotropy (processed meat intake: p for intercept = 0.865; salad / raw vegetable intake: p for intercept = 0.725), which suggested the findings were stable in the sensitivity analysis. Also, the same conclusion could be drawn based on the symmetry of the funnel plot (Fig. 4C). Furthermore, the leave-one-out analysis indicated that the causal relationships of the positive findings were highly robust (Fig. 4D). This study also found that alcoholic drinks per week (OR = 0.599; 95%CI:0.353–2.029; p = 0.059), alcohol intake frequency (OR = 0.998; 95%CI:0.815–1.223; p = 0.986), poultry intake (OR = 1.543; 95%CI:0.420–5.664; p = 0.513), beef intake (OR = 0.799; 95%CI:0.340–1.879; p = 0.608), non-oily fish intake (OR = 0.815; 95%CI:0.305–2.174; p = 0.683), oily fish intake (OR = 0.658; 95%CI:0.415–1.045; p = 0.076), pork intake (OR = 1.611; 95%CI:0.447–5.803; p = 0.466), lamb/mutton intake (OR = 0.795; 95%CI:0.367–1.721; p = 0.560), bread intake (OR = 0.816; 95%CI:0.476–1.398; p = 0.459), cheese intake (OR = 0.775; 95%CI:0.523–1.148; p = 0.203), cooked vegetable intake (OR = 1.237; 95%CI:0.511–2.994; p = 0.637), tea intake (OR = 0.839; 95%CI:0.600-1.173; p = 0.304), fresh fruit intake (OR = 0.818; 95%CI:0.444–1.505; p = 0.518), cereal intake (OR = 1.048; 95%CI:0.634–1.733; p = 0.855), coffee intake (OR = 0.675; 95%CI:0.388–1.176; p = 0.165), dried fruit intake (OR = 0.652; 95%CI:0.355–1.198; p = 0.168) were not associated with endometriosis. Table 2 Results of the MR study testing causal association between risk factors and endometriosis. Exposure Nsnp Methods OR (95%CI) SE P value Heterogeneity Pleiotropy Q P value Intercept SE P value Alcoholic drinks per week 33 MR Egger 0.6799611(0.20067025-2.3040140) 0.6226391 0.54011925 48.69891 0.02252655 -0.002386181 0.01064136 0.8240447 Weighted median 0.5104808(0.26488741–0.9837789) 0.3347185 0.04455207 IVW 0.5998892(0.35293857–1.0196307) 0.2706382 0.05900343 48.77790 0.02912858 Simple mode 0.3047015(0.08780881–1.0573316) 0.6347811 0.07034556 Weighted mode 0.4198007(0.18212788–0.9676314) 0.4260567 0.04996868 Alcohol intake frequency 92 MR Egger 1.2317646(0.6584468–2.304277) 0.3195506 0.5158604 121.0288 0.01623148 -0.005279614 0.007591067 0.4885318 Weighted median 1.1248844(0.8450627–1.497362) 0.1459310 0.4200061 IVW 0.9982444(0.8150073–1.222678) 0.1034700 0.9864507 121.6793 0.01753362 Simple mode 1.5390133(0.7466547–3.172232) 0.2690275 0.2457303 Weighted mode 1.4721473(0.9023407–2.401773) 0.2497374 0.1249692 Processed meat intake 23 MR Egger 0.7003871(0.04212152–11.6458778) 1.4342216 0.80631169 19.58499 0.5476674 -0.003659114 0.02132451 0.8654011 Weighted median 0.5888974(0.26408387–1.3132198) 0.4091762 0.19564065 IVW 0.5503184(0.31378483–0.9651528) 0.2866273 0.03718333 19.61443 0.6071440 Simple mode 0.9598536(0.23415938–3.9345802) 0.7197851 0.95511794 Weighted mode 0.8732611(0.23621423–3.2283612) 0.6670895 0.84088325 Poultry intake 7 MR Egger 2.74594e + 8(3.134708e-9-2.636064e + 25) 19.9272051 0.3732653 3.501481 0.6231635 -0.2062342 0.2156904 0.382904 Weighted median 1.030427e + 0(1.760731e-1-6.030330e + 0) 0.9014433 0.9734754 IVW 1.542800e + 0(4.202084e-1-5.664410e + 0) 0.6635733 0.5134787 4.415720 0.6206069 Simple mode 1.206582e + 0(1.003651e-1-1.450545e + 1) 1.2687411 0.8871804 Weighted mode 1.257689e + 0(9.968395e-2-1.586797e + 1) 1.2933809 0.8651301 Beef intake 14 MR Egger 0.09886097(0.0005654361-17.284873) 2.6346288 0.3970171 11.12160 0.5185276 0.02654839 0.0329939 0.4366765 Weighted median 0.92442572(0.2876770998-2.970563) 0.5955786 0.8950292 IVW 0.79985579(0.3403398977-1.879795) 0.4359626 0.6084728 11.76905 0.5466666 Simple mode 1.30532283(0.1406898229-12.110810) 1.1365551 0.8182977 Weighted mode 1.17137413(0.1493950877-9.184488) 1.0506829 0.8826436 Non-oily fish intake 11 MR Egger 0.3269077(0.00301906–35.397978) 2.3901695 0.6510609 7.107159 0.6259636 0.0113446 0.02902972 0.7050401 Weighted median 0.6266212(0.16554312-2.371915) 0.6791381 0.4912989 IVW 0.8148537(0.30536776-2.174383) 0.5007611 0.6826344 7.259878 0.7007042 Simple mode 1.1742494(0.09284320–14.851509) 1.2946288 0.9037156 Weighted mode 0.3372051(0.04428872-2.567409) 1.0356945 0.3186064 Oily fish intake 60 MR Egger 0.07307496(0.01126129–0.4741868) 0.9541406 0.008107066 90.13825 0.0043719548 0.03274721 0.0138072 0.02104418 Weighted median 0.49480798(0.29047666-0.8428730) 0.2717584 0.009625208 IVW 0.65820639(0.41471293-1.0446640) 0.2356796 0.075964151 98.88040 0.0008835476 Simple mode 0.45722149(0.13688647–1.5271888) 0.6153143 0.208416984 Weighted mode 0.42356198(0.15109819–1.1873388) 0.5259030 0.107682503 Pork intake 13 MR Egger 9268.385355(13.1818421-6.516765e + 6) 3.3446552 0.01954221 11.08815 0.4359084 0.03275721 0.0138072 0.02104418 Weighted median 2.178053(0.4676982-1.014311e + 1) 0.7848792 0.32130255 IVW 1.610895(0.4471416-5.803492e + 0) 0.6539132 0.46592013 18.01993 0.1150867 Simple mode 4.973622(0.2597666-9.522745e + 1) 1.5061836 0.30781825 Weighted mode 5.470902(0.3050026-9.813284e + 1) 1.4728972 0.27104104 Lamb/mutton intake 30 MR Egger 3.5207859(0.13537663–91.566273) 1.6624381 0.4552956 34.46473 0.1859890 -0.01652047 0.01792748 0.3646531 Weighted median 0.7803791(0.27246715-2.235101) 0.5368683 0.6441584 IVW 0.7950207(0.36723406-1.721131) 0.3940657 0.5604967 35.50998 0.1882797 Simple mode 0.7977381(0.08216618-7.745108) 1.1597124 0.8468658 Weighted mode 0.7977381(0.08590309-7.408185) 1.1370206 0.8438505 Bread intake 25 MR Egger 0.8167080(0.06498125–10.264683) 1.2914198 0.8767834 23.59235 0.4266601 -1.885567e-5 0.01830933 0.9991872 Weighted median 0.7586259(0.35747596-1.609936) 0.3838983 0.4717821 IVW 0.8156480(0.47581489-1.398194) 0.2749765 0.4586609 23.59236 0.4850946 Simple mode 1.3727804(0.35718998-5.275977) 0.6869009 0.6487670 Weighted mode 0.8530625(0.27336453-2.662070) 0.5806258 0.7866502 Cheese intake 60 MR Egger 1.4716544(0.2745982–7.887039) 0.8565477 0.6536008 88.56395 0.006004752 -0.01109754 0.01439416 0.4438511 Weighted median 0.7218269(0.4496696–1.158704) 0.2414655 0.1770273 IVW 0.7745676(0.5225161–1.148204) 0.2008414 0.2034083 89.47158 0.0064-2571 Simple mode 0.5819706(0.1865571–1.815476) 0.5804504 0.3548210 Weighted mode 0.5819706(0.2291573-1.477980) 0.4755160 0.2595481 Cooked vegetable intake 17 MR Egger 0.02153056(1.302945e-6-355.782553) 4.9554090 0.4506349 9.256952 0.8637034 0.04183715 0.05096536 0.4245614 Weighted median 1.45016440(4.426309e-1-4.751084) 0.6054571 0.5392958 IVW 1.23702390(5.111789e-1-2.993527) 0.4508898 0.6371034 9.930819 0.8702161 Simple mode 3.55717501(3.544853e-1-35.695399) 1.1765587 0.2967845 Weighted mode 3.26581587(3.414508e01031.235986) 1.1520720 0.3195659 Tea intake 39 MR Egger 0.6488238(0.3121183–1.348759) 0.3733567 0.2540180 36.05134 0.5133518 0.005520632 0.007131025 0.4437487 Weighted median 0.8040689(0.4928318–1.311861) 0.2497535 0.3825856 IVW 0.8389649(0.6002371-1.172640) 0.1708388 0.3040486 36.65068 0.5318238 Simple mode 0.7736123(0.3359621–1.781379) 0.4255471 0.5499679 Weighted mode 0.8048054(0.4833783–1.339968) 0.2601025 0.4090026 Fresh fruit intake 52 MR Egger 0.3153998(0.03959906-2.512107) 1.0586917 0.2809632 54.82165 0.2967764 0.009166867 0.009735467 0.3509273 Weighted median 0.6690702(0.26988739-1.658673) 0.4632062 0.3856268 IVW 0.8177357(0.44428410–1.505106) 0.3112638 0.5179933 55.79375 0.2994038 Simple mode 0.4575179(0.05190750–4.032609) 1.1103841 0.4845076 Weighted mode 0.9147670(0.19179403-4.363007) 0.7970650 0.9114465 Cereal intake 38 MR Egger 1.085036(0.1228284–9.584938) 1.1115203 0.9418746 44.81808 0.1487208 -0.0005070992 0.015838 0.9746347 Weighted median 1.085747(0.5746325-2.051480) 0.3246393 0.7999477 IVW 1.048136(0.6338577–1.733178) 0.2566040 0.8546314 44.81936 0.1766613 Simple mode 1.104417(0.2631960–4.634328) 0.7317213 0.8927695 Weighted mode 1.079126(0.2982640–3.904299) 0.6560853 0.9082256 Salad / raw vegetable intake 18 MR Egger 0.7918080(0.007688996-81.5398910) 2.3645555 0.92258436 13.71304 0.6200822 -0.008965366 0.02500743 0.7246497 Weighted median 0.4188380(0.106730523-1.6436282) 0.6975393 0.21216659 IVW 0.3460800(0.127019424-0.9429372) 0.5113928 0.03799643 13.84157 0.6782833 Simple mode 0.6199623(0.066894403-5.7456717) 1.1359915 0.67912780 Weighted mode 0.7066735(0.076042459-6.5672188) 1.1373862 0.76388199 Coffee intake 38 MR Egger 0.7950176(0.2569709–2.459629) 0.5762252 0.6929129 68.77989 0.0008110811 − .003090777 0.00945166 0.745555 Weighted median 0.7924395(0.4417506–1.421527) 0.2981483 0.4352261 IVW 0.6751180(0.3876248–1.175839) 0.2830866 0.1651977 68.98419 0.0010984926 Simple mode 0.7911779(0.2172841–2.262702) 0.5977319 0.5561907 Weighted mode 0.7444069(0.4129803–1.341812) 0.3006062 0.3325228 Dried fruit intake 39 MR Egger 0.04834605(0.003620156-0.6456462) 1.3223812 0.02776678 50.76414 0.06533906 0.03251612 0.01609938 0.05069982 Weighted median 0.70170073(0.326232080–1.5093056) 0.3907643 0.36464356 IVW 0.65220676(0.355105393-1.1978800) 0.3101770 0.16823346 Simple mode 1.17581395(0.209038342-6.6138032) 0.8812236 0.85515495 56.36086 0.02788563 Weighted mode 1.02463576(0.209522012-5.0108264) 0.8098284 0.97618264 Discussion The etiology of endometriosis is complex, involving immune imbalance, hormone alteration, and inflammation [ 5 ] . To our knowledge, there is mounting evidence suggesting that certain foods may potentially influence the development of endometriosis in susceptible individuals. However, this is the first MR analysis to evaluate the potential causality between dietary factors and the risk of endometriosis using large-scale summary statistics from food intake GWAS and endometriosis GWAS, which provide unconfounded causal estimates. In our analysis, it has been found that consuming salad / raw vegetable has a protective effect on endometriosis while processed meat intake is associated with a decrease risk factor for the condition. However, there is little evidence supporting an association between endometriosis risk and alcoholic drinks per week, alcohol intake frequency, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, coffee intake and dried fruit intake. The findings of our study can assist clinicians in enhancing their health education for patients with endometriosis, as well as motivating these patients to change their dietary patterns (such as increasing salad / raw vegetable intake and processed meat intake). For those at high risk for endometriosis, changing dietary habits can also decrease the likelihood of onset. There have been numerous observational studies on the correlation between vegetable intake and the risk of endometriosis. Most of these have shown that increasing vegetable consumption is linked to a reduction in endometriosis risk. Ashrafi M et al. [ 17 ] found that people who kept higher green vegetables intake took a lower endometriosis risk (OR = 0.39, 95% CI = 0.21–0.74; p = 0.004) in a retrospective case-control study from Iranian. In another hospital-based case-control study by Parazzini et al., comparing 504 women with endometriosis and 504 women without endometriosis confirmed through laparoscopy, the authors indicated a statistically significant decrease in the consumption of green vegetables among cases (OR = 0.3, 95% CI = 0.2–0.5) [ 8 ] . Likewise, several similar studies conducted in other countries also demonstrated a decreased endometriosis risk for those who increased their vegetables consumption [ 18 , 19 ] . However, not all studies shown the effect of vegetable intake on endometriosis. Based on a population-based case-control study involving 944 participants (284 cases and 660 controls), Trabert et al. reported total vegetable intake was not associated with incident endometriosis [ 20 ] . The authors hypothesized that this finding could be attributed to pesticide exposure, which might generate reactive oxygen species and reduce the antioxidant capacity of vegetables. Some studies [ 21 ] , on the other hand, have demonstrated that certain class of pesticides can cause estrogenic effects, thereby promoting the development of endometriosis lesions. Alternatively, a meta-analysis indicated an insignificant correlation between eating vegetable and the risk of developing endometriosis [ 22 ] . Furthermore, Harris et al. [ 7 ] reported that a high intake of some vegetables such as cruciferous vegetables, particularly cauliflower, cabbage was related to an increase in endometriosis risk. Through MR analysis, our study indicated that a high level of vegetables intake might be associated with a decreased risk of endometriosis. Endometriosis is an oestrogen-dependent disease. Typically, populations on a diet rich in green vegetables have higher levels of sex-hormone binding globulin (SHBG), which can attenuate the oestrogenic stimulation of the endometrium and restrict the proliferation of prostaglandin-producing tissues. Additionally, dietary fiber can interrupt enterohepatic circulation of oestrogen conjugates, thereby reducing the risk of endometriosis [ 17 ] . Studies have indicated that a number of nutrients found in vegetables potentially benefit endometriosis. First of all, vitamins, especially vitamin C, are important antioxidants that strongly neutralize free radicals and improve oxidative status to reduce the chances of developing endometriosis [ 23 ] . This finding aligns with a randomized, triple-blind placebo-controlled clinical study that reported a decrease in systemic indicators of oxidative stress in patients with endometriosis after receiving a boost of vitamin C [ 24 ] . Furthermore, the influence of vitamin C on the expression and production of the VEGF gene was investigated in peritoneal macrophages from women diagnosed with endometriosis [ 25 ] . Vitamin A can also play a role in influencing aberrant cytokines production in endometriosis, such as suppressing the transcription and translational processes of IL-6 and VEGF [ 26 ] . Secondly, vegetables are packed with bioactive plant compounds, especially polyphenols (such as curcumin, resveratrol and epigallocatechin gallate). Natural polyphenols have been proven to possess anti-inflammatory and antioxidative properties, making them a cost-effective and easily accessible treatment option for endometriosis [ 27 ] . In addition to these properties, polyphenols can be used as estrogen receptor agonists to combat the condition due to their structural similarity with estradiol [ 28 ] . Thirdly, many vegetables contain phytoestrogens that can be classified into three classes: flavonoids, lignans and stilbenes. These compounds are structural and functional homologies with estrogen and act as weak estrogenic factors by binding to the estrogen receptor and interfering with ER mediated responses [ 29 ] . Furthermore, the mechanism of action of flavonoids is pleiotropic and includes promoting autophagy, down-regulating nuclear factor (NF)-κB activity, reducing interleukin (IL)-6 and tumor necrosis factor α (TNFα), as well as inhibiting oxidative stress, thereby generating proapoptotic, anti-inflammatory, and anti-proliferative effects [ 30 ] . Our MR analysis also indicated a decreased endometriosis risk for those with processed meat intake, which was consistent with the result of a case-control study by Ashrafi M et al. [ 17 ] (OR = 0.61, 95% CI = 0.41–0.91, P = 0.015). However, different results were obtained by other studies. In a large Italian study, endometriosis risk was notably higher among women in the highest intake of red meat, both processed and unprocessed, compared to those in the lowest (OR = 2.0, 95% CI = 1.4–2.8; P = 0.0004) [ 8 ] . In a Nurses’ Health Study II (NHSII) prospective cohort including 81908 participants, red meat consumption, especially non-processed rea meat consumption, was correlated with a greater risk of laparoscopically-confirmed endometriosis by approximately 56% (95% CI = 1.22–1.99; P < 0.0001) [ 9 ] . Likewise, a meta-analysis of observational studies reported that women eating red meat had a 17% higher risk in endometriosis [ 22 ] . In contrast to these findings, a Washington state based case-control study [ 20 ] and a Belgian matched case-control study with prospective recruitment [ 31 ] showed no association between red meat intake and incident endometriosis. Owing to the inconsistency between our results and those reported in previous studies, our conclusion must be viewed cautiously. Also, we must correctly understand the correlation between MR analysis and observational studies. MR analysis makes a terrific addition to observational studies because it is not affected by common confounding factors or reverse causation bias but cannot serve as their substitute. Previous studies provide solid evidence linking red meat consumption to an increased risk of many chronic diseases, including diabetes, hypertension, cardiovascular disease and some cancers [ 22 ] . Although the physiological mechanism of how red meat affects endometriosis remains incompletely understood, it has been postulated to involve several ways. On the one hand, a high intake of animal fat in a meat-based diet such as palmitic acid can further increase endogenous estrogens, which stimulate the formation of proinflammatory PGs. These PGs can also induce the release of aromatase P450, promoting inflammatory conditions in endometriosis [ 9 ] . On the other hand, diets rich in red meat seem to correlate with decreased SHBG and increased estradiol concentrations, that influence pain in women with endometriosis [ 32 ] . Another possible mechanism is iron overload in women with a high intake of red meat, which is related to increased oxidative stress and inflammatory status in endometriosis [ 9 ] . Furthermore, iron overload in the peritoneal fluid of women with endometriosis can decrease GPX4 expression, cause embryotoxicity and induce ferroptosis, which probably participates in endometriosis-associated reproductive failure [ 33 ] . To date, the dietary structure is complex and the contribution of diet to endometriosis has not been sufficiently studied. Observational studies that assess the relationship between dietary factors and endometriosis have certain limitations, including recall bias, confounding introduced by self-reported food questionnaires, and reverse causation bias. Therefore, more future observational studies and ingenious MR studies are needed to elucidate the role of diet in endometriosis. Notably, our MR analysis possesses several significant strengths. Firstly, to the best of our knowledge, this MR study is the first to systematically analyze the causality between dietary factors and endometriosis by using genetic variation as IVs, effectively overcoming the reverse causality and confounding bias. Moreover, we utilized European populations as both the exposure and outcome groups to minimize potential biases. Secondly, some of the findings from this study contradict current knowledge, thereby providing valuable insights for future research directions. Thirdly, we took several steps to meet the core assumptions of MR analysis and utilized a large sample size along with SNPs derived from GWAS, thus significantly enhancing the credibility of our findings. Inevitably, this study also has some limitations. Firstly, this analysis was conducted solely with European participants, which hinders the generalizability of these findings to other populations. Furthermore, we were unable to differentiate the specific effects of different dietary combinations. Secondly, food intake GWAS is still in its early stages due to small sample sizes, which may compromise statistical power. Therefore, the absence of significant associations does not necessarily imply that food intake has no effect. Thirdly, due to the lack of summary-level GWAS data for various ages groups, we cannot conduct an age-stratified analysis further. Lastly, it remains uncertain whether dose-response relationships exist between dietary factors and the risk of endometriosis. Additionally, the food intake data used in our study were obtained through a self-reported questionnaire instead of objective measurements, potentially introducing recall bias. Conclusion Overall, we thoroughly examined the potential causal association between dietary intake and endometriosis. Two specific types of food consumption (salad / raw vegetable intake and processed meat intake) are associated with a decreased risk of developing endometriosis. However, further research is required to elucidate the precise causal relationship and underlying mechanisms linking specific dietary patterns to endometriosis. Declarations Availability of data and material The datasets analyzed in this study are publicly available summary statistics. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Acknowledgments The authors sincerely thank the researchers and the participants of the original GWASs for the collection and management of the large-scale data resources. Author contributions XZ conducted the data analysis and drafted the manuscript. QZ took responsibility of the tables and figures of the results. LC designed the study, revised the manuscript, and provided technical support. All authors contributed to the article and approved the submitted version. Compliance with ethical standards Competing interest The authors declare no competing interests. Ethical approval Ethical approval was not needed for this current study because it is a secondary analysis of previously published data. Informed consent For this type of article, informed consent is not required. References Rowlands IJ, Abbott JA, Montgomery GW, et al. Prevalence and incidence of endometriosis in Australian women: a data linkage cohort study[J]. Bjog, 2021, 128(4): 657-665. Saunders PTK, Horne AW. Endometriosis: Etiology, pathobiology, and therapeutic prospects[J]. Cell, 2021, 184(11): 2807-2824. Edgley K, Horne AW, Saunders PTK, et al. Symptom tracking in endometriosis using digital technologies: Knowns, unknowns, and future prospects[J]. Cell Rep Med, 2023, 4(9): 101192. Shining a light on endometriosis: time to listen and take action[J]. BMC Med, 2023, 21(1): 107. Smolarz B, Szyłło K, Romanowicz H. Endometriosis: Epidemiology, Classification, Pathogenesis, Treatment and Genetics (Review of Literature)[J]. Int J Mol Sci, 2021, 22(19). Harvie M, Howell A, Evans DG. Can diet and lifestyle prevent breast cancer: what is the evidence?[J]. Am Soc Clin Oncol Educ Book, 2015: e66-73. Harris HR, Chavarro JE, Malspeis S, et al. Dairy-food, calcium, magnesium, and vitamin D intake and endometriosis: a prospective cohort study[J]. Am J Epidemiol, 2013, 177(5): 420-430. Parazzini F, Chiaffarino F, Surace M, et al. Selected food intake and risk of endometriosis[J]. Hum Reprod, 2004, 19(8): 1755-1759. Yamamoto A, Harris HR, Vitonis AF, et al. A prospective cohort study of meat and fish consumption and endometriosis risk[J]. Am J Obstet Gynecol, 2018, 219(2): 178.e171-178.e110. Nodler JL, Harris HR, Chavarro JE, et al. Dairy consumption during adolescence and endometriosis risk[J]. Am J Obstet Gynecol, 2020, 222(3): 257.e251-257.e216. Emdin CA, Khera AV, Kathiresan S. Mendelian Randomization[J]. Jama, 2017, 318(19): 1925-1926. Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians[J]. Bmj, 2018, 362: k601. Bowden J, Del Greco MF, Minelli C, et al. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization[J]. Stat Med, 2017, 36(11): 1783-1802. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method[J]. Eur J Epidemiol, 2017, 32(5): 377-389. Bowden J, Davey Smith G, Haycock PC, et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator[J]. Genet Epidemiol, 2016, 40(4): 304-314. Zhang D, Hu Y, Guo W, et al. Mendelian randomization study reveals a causal relationship between rheumatoid arthritis and risk for pre-eclampsia[J]. Front Immunol, 2022, 13: 1080980. Ashrafi M, Jahangiri N, Jahanian Sadatmahalleh SH, et al. Diet and The Risk of Endometriosis in Iranian Women: A Case-Control Study[J]. Int J Fertil Steril, 2020, 14(3): 193-200. Msyamboza KP, Ngwira B, Dzowela T, et al. The burden of selected chronic non-communicable diseases and their risk factors in Malawi: nationwide STEPS survey[J]. PLoS One, 2011, 6(5): e20316. Almeida-de-Souza J, Santos R, Lopes L, et al. Associations between fruit and vegetable variety and low-grade inflammation in Portuguese adolescents from LabMed Physical Activity Study[J]. Eur J Nutr, 2018, 57(6): 2055-2068. Trabert B, Peters U, De Roos AJ, et al. Diet and risk of endometriosis in a population-based case-control study[J]. Br J Nutr, 2011, 105(3): 459-467. Mier-Cabrera J, Aburto-Soto T, Burrola-Méndez S, et al. Women with endometriosis improved their peripheral antioxidant markers after the application of a high antioxidant diet[J]. Reprod Biol Endocrinol, 2009, 7: 54. Arab A, Karimi E, Vingrys K, et al. Food groups and nutrients consumption and risk of endometriosis: a systematic review and meta-analysis of observational studies[J]. Nutr J, 2022, 21(1): 58. Yalçın Bahat P, Ayhan I, Üreyen Özdemir E, et al. Dietary supplements for treatment of endometriosis: A review[J]. Acta Biomed, 2022, 93(1): e2022159. Amini L, Chekini R, Nateghi MR, et al. The Effect of Combined Vitamin C and Vitamin E Supplementation on Oxidative Stress Markers in Women with Endometriosis: A Randomized, Triple-Blind Placebo-Controlled Clinical Trial[J]. Pain Res Manag, 2021, 2021: 5529741. Ansariniya H, Hadinedoushan H, Javaheri A, et al. Vitamin C and E supplementation effects on secretory and molecular aspects of vascular endothelial growth factor derived from peritoneal fluids of patients with endometriosis[J]. J Obstet Gynaecol, 2019, 39(8): 1137-1142. Harris HR, Eke AC, Chavarro JE, et al. Fruit and vegetable consumption and risk of endometriosis[J]. Hum Reprod, 2018, 33(4): 715-727. Piecuch M, Garbicz J, Waliczek M, et al. I Am the 1 in 10-What Should I Eat? A Research Review of Nutrition in Endometriosis[J]. Nutrients, 2022, 14(24). Gołąbek A, Kowalska K, Olejnik A. Polyphenols as a Diet Therapy Concept for Endometriosis-Current Opinion and Future Perspectives[J]. Nutrients, 2021, 13(4). Cai X, Liu M, Zhang B, et al. Phytoestrogens for the Management of Endometriosis: Findings and Issues[J]. Pharmaceuticals (Basel), 2021, 14(6). Saguyod SJU, Kelley AS, Velarde MC, et al. Diet and endometriosis-revisiting the linkages to inflammation[J]. Journal of Endometriosis and Pelvic Pain Disorders, 2018, 10(2): 51-58. Heilier JF, Donnez J, Nackers F, et al. Environmental and host-associated risk factors in endometriosis and deep endometriotic nodules: a matched case-control study[J]. Environ Res, 2007, 103(1): 121-129. Brinkman MT, Baglietto L, Krishnan K, et al. Consumption of animal products, their nutrient components and postmenopausal circulating steroid hormone concentrations[J]. Eur J Clin Nutr, 2010, 64(2): 176-183. Li S, Zhou Y, Huang Q, et al. Iron overload in endometriosis peritoneal fluid induces early embryo ferroptosis mediated by HMOX1[J]. Cell Death Discov, 2021, 7(1): 355. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 07 May, 2024 Submission checks completed at journal 11 Mar, 2024 First submitted to journal 10 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4062748","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278543704,"identity":"f31b054b-8033-4741-a0d0-4a25e9b19365","order_by":0,"name":"Xia Zhang","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Zhang","suffix":""},{"id":278543708,"identity":"711244ce-9d37-46c9-a42c-1a890b885ded","order_by":1,"name":"Qiaomei Zheng","email":"","orcid":"","institution":"Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiaomei","middleName":"","lastName":"Zheng","suffix":""},{"id":278543710,"identity":"c5561285-e1d9-4ecc-a9a3-93334b42e784","order_by":2,"name":"Lihong Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIie3QMQrCMBSA4YTA6/JQx1eEeAIhUBCnepWGDm4quDi2COnSA+gtnJwjgl6jxQvo5qZ1c0tGwfxbIN8LeYyFQj9YVPCGF8+XhKgs27sPQSsUL2uR9PC8TcibFCC0pLkZoBehnD92CBnErWHEUjku3ETEhykuYKhNs2J5MrEOMqPlhTdI645UipjVRxfpXgHegNImPhlCb3KATBvivgRvIt7XNgHU3ZKVx18w6jZWP60cVde2vW9S6SRskH2flOv6p75zaCgUCv19b6v0Pc7RubP3AAAAAElFTkSuQmCC","orcid":"","institution":"Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Lihong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-03-10 07:29:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4062748/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4062748/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52657906,"identity":"7d39fefb-ba48-4f00-a155-fe09a4f9128d","added_by":"auto","created_at":"2024-03-14 07:19:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":80635,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of MR analysis in this study. GWAS, genome-wide association studies; SNPs, single-nucleotide polymorphisms; MAF, minor allele frequency; MR, mendelian Randomization.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4062748/v1/50c04d952f406eabadbad0e4.jpg"},{"id":52657905,"identity":"a308e5ff-ab54-445b-8341-d92c130d89ef","added_by":"auto","created_at":"2024-03-14 07:19:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49184,"visible":true,"origin":"","legend":"\u003cp\u003eAssumption of the Mendelian randomization study.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4062748/v1/ded161084776106bd39dc305.jpg"},{"id":52657908,"identity":"1c6381f3-d690-45bb-b5c9-6717c192aa8d","added_by":"auto","created_at":"2024-03-14 07:19:43","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":59691,"visible":true,"origin":"","legend":"\u003cp\u003eThe causal effect of 18 dietary factors on endometriosis based on the IVW method. IVW, inverse-variance weighted.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4062748/v1/9615591fa08fc5e5ffc1a98a.jpg"},{"id":52657907,"identity":"5e266efc-2b0d-4f06-98d2-3858864114d7","added_by":"auto","created_at":"2024-03-14 07:19:42","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":693518,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot (A: A1 for salad / raw vegetable intake, A2 for processed meat intake), forest plot (B: B1 for salad / raw vegetable intake, B2 for processed meat intake), funnel plot (C: C1 for salad / raw vegetable intake, C2 for processed meat intake) and leave-one-out analysis (D: D1 for salad / raw vegetable intake, D2 for processed meat intake) of the causal effect of dietary factors on endometriosis risk.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4062748/v1/db4da5c362c01b9e56658d30.jpg"},{"id":52658820,"identity":"d6bf6591-3e8b-4b0d-ad65-e6dc63367285","added_by":"auto","created_at":"2024-03-14 07:27:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":504830,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4062748/v1/c4fe0b27-025a-4511-84d1-7661d572c562.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dietary factors and risk for endometriosis: a Mendelian randomization analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEndometriosis is an oestrogen-dependent chronic inflammatory process characterized by the presence of endometrial-like tissue outside the uterus, primarily on pelvic tissues\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Common disease symptoms, including severe chronic pelvic pain, secondary dysmenorrhea and infertility, substantially alter the patient\u0026rsquo;s work productivity, social life and psychological well-being. This condition affects 6%-10% of reproductive-age women worldwide and represents a considerable burden on society\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The core goals of endometriosis treatment proclaimed by the UK Endometriosis Association are to minimize diagnosis time and ensure patients have access to comprehensive treatment and support\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. However, the diagnosis is often delayed because symptom severity does not correlate with the extent of endometrial lesions. Therefore, we must fully understand the etiology of endometriosis to mitigate its health consequences.\u003c/p\u003e \u003cp\u003eThe causes of this condition include epigenetic, autoimmune, hormonal and environmental factors such as exercise and diet\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. A previous study has reported the role of diet in several chronic diseases\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Dietary factors may directly contribute to the progression and severity of endometriosis due to their involvement in oxidative stress, muscle contraction, inflammation and steroid hormone metabolism\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Understanding how dietary changes affect patients with endometriosis holds significant implications for both clinicians and patients. Some observational studies\u003csup\u003e[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e have found an association between the consumption of green vegetables, fresh fruit, red meat, dairy and fish with endometriosis.\u003c/p\u003e \u003cp\u003eHowever, the observational study is susceptible to confounding variables such as geographical and ethnic disparities, age differences, and environmental factors. Compared with other research methods, mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to estimate the causal relationships between exposure and disease outcome, which is not affected by common confounding factors or reverse causation bias.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e As far as we know, there have been few MR studies on the association between dietary factors and endometriosis. Therefore, we performed an MR analysis to explore the causal effect of dietary factors on endometriosis.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThe study design is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The genome-wide association study (GWAS) summary statistics used in this work are available from IEU Open GWAS ((\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and the samples are all from people of European ancestry in order to mitigate potential bias from population stratification. Also, the ethics vote is not necessary for this study due to IEU Open GWAS is a publicly available database and each study included in it was approved by the local Ethical Review Authority. In MR analysis, eligible single nucleotide polymorphisms (SNPs) used as valid IVs should satisfy three basic assumptions: relevance, independence and the exclusion restriction, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eWe performed a standard two-sample MR analysis to investigate the causal relationship between dietary factors and endometriosis. In total, eighteen diet-related exposure factors were identified: alcoholic drinks per week, alcohol intake frequency, processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, salad/raw vegetable intake, coffee intake and dried fruit intake. Summary GWAS data for exposure and outcome were extracted directly from the IEU Open GWAS database. More detailed information is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInformation of the exposures and outcome datasets\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIEU GWAS id\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExposure and Outcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentified SNPs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParticipants included in analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF- statistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eieu-b-73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlcoholic drinks per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e335394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.4413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-5779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlcohol intake frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e462346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.6053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-6324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcessed meat intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e461981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.1311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-8006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoultry intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e461990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.0437\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-2862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeef intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e461053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.9647\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-17627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-oily fish intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e460880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.0146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-2209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOily fish intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e460443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.5199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-5640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePork intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e460162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.0602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-14179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLamb/mutton intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e460006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.6486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-11348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBread intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e452236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.9552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-1489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCheese intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e451486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.9740\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-8089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCooked vegetable intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e448651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.8211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-6066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTea intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e447485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.9048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-3881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFresh fruit intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e446462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.8879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-15926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCereal intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e441640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.4987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-1996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSalad / raw vegetable intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e435435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.4590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-5237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoffee intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e428860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29.1311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eukb-b-16576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDried fruit intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e421764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.1519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efinn-b-N14_ENDOMETRIOSIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndometriosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eIVs selection\u003c/h2\u003e \u003cp\u003eTo ensure that the conclusion regarding the causal effect of diet-related factors on endometriosis was accurate, we used a series of quality control criteria to satisfy the three fundamental assumptions of MR analysis. Firstly, we obtained the SNPs using a GWAS p-value\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;8 and excluded SNPs that were in linkage disequilibrium (LD) (clumping window\u0026thinsp;=\u0026thinsp;10000kb; r2\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Then, we calculated the F-statistics, using the rigorous mathematical formula: F\u0026thinsp;=\u0026thinsp;R\u003csup\u003e2\u003c/sup\u003e\u0026times;(N-K-1)/[K\u0026times;(1-R\u003csup\u003e2\u003c/sup\u003e)] (R\u003csup\u003e2\u003c/sup\u003e: the proportion of exposure variance explained by each genetic variant, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2\u0026times;MAF\u0026times;(1-MAF)\u0026times;(Beta/SD)\u003csup\u003e2\u003c/sup\u003e; N: the sample size of the GWAS; K: the number of SNP), to eliminate the bias arising from weak instrumental variables in the findings (F statistic\u0026thinsp;\u0026gt;\u0026thinsp;10)\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Finally, SNPs harmonization was also performed by removing palindrome SNPs with intermediate allele frequencies or SNPs with incompatible alleles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eIn the current study, we adopted inverse variance weighting (IVW) as the primary MR approach to calculate the causal effect of all SNPs. In addition, we ran MR Egger, weighted median, simple mode, and weighted mode as a complement to test the reliability and stability of the results. When utilizing the IVW method, it is necessary to ensure that all IVs in the analysis are of robust validity\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. In contrast to IVW, the MR Egger method allows all IVs to be voided\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. And the weighted median method provides a less biased causal estimation as long as no more than 50% of IVs are invalid\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Therefore, when the three methods are consistent, the results will be more persuasive. In addition, the weighted mode is less capable of detecting causation, but it is sensitive when the largest subset of IVs with similar causal effects is valid\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. And finally, the estimated causal effects of individual SNPs were quantified as the odds ratios (ORs) from the Wald ratio method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eAfter MR analysis, we performed sensitivity analysis, including heterogeneity and pleiotropy, to further validate the robustness of the results. We used the Cochran\u0026rsquo;s Q statistic of the IVW method and Rucker\u0026rsquo;s Q statistic of the MR Egger method to identify heterogeneity, where p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated heterogeneity. In addition, the MR Egger intercept test was used to assess the possibility of pleiotropy and p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 suggested a lack of horizontal pleiotropy\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. More rigorously, we conducted leave-one-out analysis to detect if there was any single SNP disproportionately responsible for the results by removing each instrumental SNP in turn. Finally, we utilized scatter and forest plots to visualize the results of the MR analysis. All statistical analyses were performed in R using the TwoSampleMR package.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, we systematically curated genome-wide significant SNPs associated with 18 kinds of food intake exposures to examine the potential causal effects of dietary factors on the risk of endometriosis. These different exposure factors could be categorized into six groups, including vegetable intake (salad/raw vegetable intake and cooked vegetable intake), meat intake (processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, and lamb/mutton intake), staple food intake (bread intake and cereal intake), beverage intake (alcoholic drinks per week, alcohol intake frequency, tea intake, and coffee intake), fruit intake(dried fruit intake and fresh fruit intake), and another food intake (cheese intake). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the number of SNPs chosen as IVs for each diet-related factor ranged from 7 to 92 after a series of quality control steps. Moreover, the F statistics were calculated for each instrument-exposure association and none was less than 10 (range: 13.9740 to 29.1311), suggesting that all SNPs were strong IVs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe MR estimates from different methods are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In this study, two causal associations from 18 food intakes were observed for endometriosis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 by IVW method). As the Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e,4A,4Bshow, the IVW method showed that processed meat intake (OR\u0026thinsp;=\u0026thinsp;0.550; 95%CI:0.314\u0026ndash;0.965; p\u0026thinsp;=\u0026thinsp;0.037) was significantly associated with a decreased risk of endometriosis. Similarly, salad / raw vegetable intake (OR\u0026thinsp;=\u0026thinsp;0.346; 95%CI:0.127\u0026ndash;0.943; p\u0026thinsp;=\u0026thinsp;0.038) was discovered as a protective factor. Heterogeneity test revealed no significant heterogeneity of these IVs (processed meat intake: p\u003csub\u003eIVW\u003c/sub\u003e=0.607, p\u003csub\u003eMR\u0026minus;Egger\u003c/sub\u003e=0.548; salad / raw vegetable intake: p\u003csub\u003eIVW\u003c/sub\u003e=0.678, p\u003csub\u003eMR\u0026minus;Egger\u003c/sub\u003e=0.620), so we chose the fixed-effect IVW model for MR analysis. In addition, MR-Egger regression test didn\u0026rsquo;t support any evidence for horizontal pleiotropy (processed meat intake: p for intercept\u0026thinsp;=\u0026thinsp;0.865; salad / raw vegetable intake: p for intercept\u0026thinsp;=\u0026thinsp;0.725), which suggested the findings were stable in the sensitivity analysis. Also, the same conclusion could be drawn based on the symmetry of the funnel plot (Fig.\u0026nbsp;4C). Furthermore, the leave-one-out analysis indicated that the causal relationships of the positive findings were highly robust (Fig.\u0026nbsp;4D). This study also found that alcoholic drinks per week (OR\u0026thinsp;=\u0026thinsp;0.599; 95%CI:0.353\u0026ndash;2.029; p\u0026thinsp;=\u0026thinsp;0.059), alcohol intake frequency (OR\u0026thinsp;=\u0026thinsp;0.998; 95%CI:0.815\u0026ndash;1.223; p\u0026thinsp;=\u0026thinsp;0.986), poultry intake (OR\u0026thinsp;=\u0026thinsp;1.543; 95%CI:0.420\u0026ndash;5.664; p\u0026thinsp;=\u0026thinsp;0.513), beef intake (OR\u0026thinsp;=\u0026thinsp;0.799; 95%CI:0.340\u0026ndash;1.879; p\u0026thinsp;=\u0026thinsp;0.608), non-oily fish intake (OR\u0026thinsp;=\u0026thinsp;0.815; 95%CI:0.305\u0026ndash;2.174; p\u0026thinsp;=\u0026thinsp;0.683), oily fish intake (OR\u0026thinsp;=\u0026thinsp;0.658; 95%CI:0.415\u0026ndash;1.045; p\u0026thinsp;=\u0026thinsp;0.076), pork intake (OR\u0026thinsp;=\u0026thinsp;1.611; 95%CI:0.447\u0026ndash;5.803; p\u0026thinsp;=\u0026thinsp;0.466), lamb/mutton intake (OR\u0026thinsp;=\u0026thinsp;0.795; 95%CI:0.367\u0026ndash;1.721; p\u0026thinsp;=\u0026thinsp;0.560), bread intake (OR\u0026thinsp;=\u0026thinsp;0.816; 95%CI:0.476\u0026ndash;1.398; p\u0026thinsp;=\u0026thinsp;0.459), cheese intake (OR\u0026thinsp;=\u0026thinsp;0.775; 95%CI:0.523\u0026ndash;1.148; p\u0026thinsp;=\u0026thinsp;0.203), cooked vegetable intake (OR\u0026thinsp;=\u0026thinsp;1.237; 95%CI:0.511\u0026ndash;2.994; p\u0026thinsp;=\u0026thinsp;0.637), tea intake (OR\u0026thinsp;=\u0026thinsp;0.839; 95%CI:0.600-1.173; p\u0026thinsp;=\u0026thinsp;0.304), fresh fruit intake (OR\u0026thinsp;=\u0026thinsp;0.818; 95%CI:0.444\u0026ndash;1.505; p\u0026thinsp;=\u0026thinsp;0.518), cereal intake (OR\u0026thinsp;=\u0026thinsp;1.048; 95%CI:0.634\u0026ndash;1.733; p\u0026thinsp;=\u0026thinsp;0.855), coffee intake (OR\u0026thinsp;=\u0026thinsp;0.675; 95%CI:0.388\u0026ndash;1.176; p\u0026thinsp;=\u0026thinsp;0.165), dried fruit intake (OR\u0026thinsp;=\u0026thinsp;0.652; 95%CI:0.355\u0026ndash;1.198; p\u0026thinsp;=\u0026thinsp;0.168) were not associated with endometriosis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the MR study testing causal association between risk factors and endometriosis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNsnp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMethods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eHeterogeneity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003ePleiotropy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAlcoholic drinks per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6799611(0.20067025-2.3040140)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6226391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54011925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.69891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02252655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.002386181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01064136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.8240447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5104808(0.26488741\u0026ndash;0.9837789)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3347185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04455207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5998892(0.35293857\u0026ndash;1.0196307)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2706382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05900343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.77790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02912858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3047015(0.08780881\u0026ndash;1.0573316)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6347811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07034556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4198007(0.18212788\u0026ndash;0.9676314)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4260567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04996868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAlcohol intake frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2317646(0.6584468\u0026ndash;2.304277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3195506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5158604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121.0288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01623148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.005279614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.007591067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4885318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1248844(0.8450627\u0026ndash;1.497362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1459310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4200061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9982444(0.8150073\u0026ndash;1.222678)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1034700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9864507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121.6793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01753362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5390133(0.7466547\u0026ndash;3.172232)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2690275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2457303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4721473(0.9023407\u0026ndash;2.401773)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2497374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1249692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eProcessed meat intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7003871(0.04212152\u0026ndash;11.6458778)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4342216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80631169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.58499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5476674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.003659114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.02132451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.8654011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5888974(0.26408387\u0026ndash;1.3132198)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4091762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19564065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5503184(0.31378483\u0026ndash;0.9651528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2866273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03718333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.61443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6071440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9598536(0.23415938\u0026ndash;3.9345802)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7197851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95511794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8732611(0.23621423\u0026ndash;3.2283612)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6670895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84088325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePoultry intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.74594e\u0026thinsp;+\u0026thinsp;8(3.134708e-9-2.636064e\u0026thinsp;+\u0026thinsp;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.9272051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3732653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.501481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6231635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.2062342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.2156904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.382904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.030427e\u0026thinsp;+\u0026thinsp;0(1.760731e-1-6.030330e\u0026thinsp;+\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9014433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9734754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.542800e\u0026thinsp;+\u0026thinsp;0(4.202084e-1-5.664410e\u0026thinsp;+\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6635733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5134787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.415720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6206069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.206582e\u0026thinsp;+\u0026thinsp;0(1.003651e-1-1.450545e\u0026thinsp;+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2687411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8871804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.257689e\u0026thinsp;+\u0026thinsp;0(9.968395e-2-1.586797e\u0026thinsp;+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2933809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8651301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eBeef intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09886097(0.0005654361-17.284873)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6346288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3970171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.12160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5185276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02654839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0329939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4366765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92442572(0.2876770998-2.970563)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5955786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8950292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79985579(0.3403398977-1.879795)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4359626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6084728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.76905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5466666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.30532283(0.1406898229-12.110810)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1365551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8182977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17137413(0.1493950877-9.184488)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0506829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8826436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eNon-oily fish intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3269077(0.00301906\u0026ndash;35.397978)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3901695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6510609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.107159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6259636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0113446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.02902972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.7050401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6266212(0.16554312-2.371915)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6791381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4912989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8148537(0.30536776-2.174383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5007611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6826344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.259878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.7007042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1742494(0.09284320\u0026ndash;14.851509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2946288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9037156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3372051(0.04428872-2.567409)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0356945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3186064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eOily fish intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07307496(0.01126129\u0026ndash;0.4741868)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9541406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008107066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.13825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0043719548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.03274721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0138072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.02104418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.49480798(0.29047666-0.8428730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2717584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009625208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65820639(0.41471293-1.0446640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2356796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.075964151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.88040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0008835476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45722149(0.13688647\u0026ndash;1.5271888)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6153143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.208416984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42356198(0.15109819\u0026ndash;1.1873388)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5259030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.107682503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePork intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9268.385355(13.1818421-6.516765e\u0026thinsp;+\u0026thinsp;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.3446552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01954221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.08815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4359084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.03275721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0138072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.02104418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.178053(0.4676982-1.014311e\u0026thinsp;+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7848792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32130255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.610895(0.4471416-5.803492e\u0026thinsp;+\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6539132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46592013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.01993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1150867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.973622(0.2597666-9.522745e\u0026thinsp;+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5061836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30781825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.470902(0.3050026-9.813284e\u0026thinsp;+\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4728972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27104104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eLamb/mutton intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5207859(0.13537663\u0026ndash;91.566273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6624381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4552956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.46473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1859890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.01652047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01792748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.3646531\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7803791(0.27246715-2.235101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5368683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6441584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7950207(0.36723406-1.721131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3940657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5604967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.50998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1882797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7977381(0.08216618-7.745108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1597124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8468658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7977381(0.08590309-7.408185)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1370206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8438505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eBread intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8167080(0.06498125\u0026ndash;10.264683)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2914198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8767834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.59235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4266601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.885567e-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01830933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.9991872\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7586259(0.35747596-1.609936)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3838983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4717821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8156480(0.47581489-1.398194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2749765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4586609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.59236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4850946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3727804(0.35718998-5.275977)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6869009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6487670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8530625(0.27336453-2.662070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5806258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7866502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCheese intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4716544(0.2745982\u0026ndash;7.887039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8565477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6536008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.56395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.006004752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.01109754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01439416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4438511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7218269(0.4496696\u0026ndash;1.158704)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2414655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1770273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7745676(0.5225161\u0026ndash;1.148204)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2008414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2034083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.47158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0064-2571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5819706(0.1865571\u0026ndash;1.815476)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5804504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3548210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5819706(0.2291573-1.477980)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4755160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2595481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCooked vegetable intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02153056(1.302945e-6-355.782553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.9554090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4506349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.256952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.8637034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.04183715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05096536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4245614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.45016440(4.426309e-1-4.751084)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6054571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5392958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.23702390(5.111789e-1-2.993527)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4508898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6371034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.930819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.8702161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.55717501(3.544853e-1-35.695399)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1765587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2967845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.26581587(3.414508e01031.235986)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1520720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3195659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTea intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6488238(0.3121183\u0026ndash;1.348759)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3733567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2540180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.05134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5133518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.005520632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.007131025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4437487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8040689(0.4928318\u0026ndash;1.311861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2497535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3825856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8389649(0.6002371-1.172640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1708388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3040486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.65068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5318238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7736123(0.3359621\u0026ndash;1.781379)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4255471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5499679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8048054(0.4833783\u0026ndash;1.339968)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2601025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4090026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFresh fruit intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3153998(0.03959906-2.512107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0586917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2809632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.82165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2967764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.009166867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.009735467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.3509273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6690702(0.26988739-1.658673)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4632062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3856268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8177357(0.44428410\u0026ndash;1.505106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3112638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5179933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.79375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2994038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4575179(0.05190750\u0026ndash;4.032609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1103841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4845076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9147670(0.19179403-4.363007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7970650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9114465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCereal intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.085036(0.1228284\u0026ndash;9.584938)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1115203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9418746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.81808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1487208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.0005070992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.015838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.9746347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.085747(0.5746325-2.051480)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3246393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7999477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.048136(0.6338577\u0026ndash;1.733178)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2566040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8546314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.81936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1766613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.104417(0.2631960\u0026ndash;4.634328)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7317213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8927695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.079126(0.2982640\u0026ndash;3.904299)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6560853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9082256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSalad / raw vegetable intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7918080(0.007688996-81.5398910)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3645555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92258436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.71304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6200822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.008965366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.02500743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.7246497\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4188380(0.106730523-1.6436282)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6975393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21216659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3460800(0.127019424-0.9429372)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5113928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03799643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.84157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6782833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6199623(0.066894403-5.7456717)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1359915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67912780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7066735(0.076042459-6.5672188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1373862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76388199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCoffee intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7950176(0.2569709\u0026ndash;2.459629)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5762252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6929129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.77989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0008110811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.003090777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00945166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.745555\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7924395(0.4417506\u0026ndash;1.421527)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2981483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4352261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6751180(0.3876248\u0026ndash;1.175839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2830866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1651977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.98419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0010984926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7911779(0.2172841\u0026ndash;2.262702)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5977319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5561907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7444069(0.4129803\u0026ndash;1.341812)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3006062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3325228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDried fruit intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04834605(0.003620156-0.6456462)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.3223812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02776678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50.76414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06533906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.03251612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01609938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.05069982\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70170073(0.326232080\u0026ndash;1.5093056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3907643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.36464356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65220676(0.355105393-1.1978800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3101770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16823346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17581395(0.209038342-6.6138032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8812236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.85515495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.36086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02788563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02463576(0.209522012-5.0108264)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8098284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97618264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eThe etiology of endometriosis is complex, involving immune imbalance, hormone alteration, and inflammation\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. To our knowledge, there is mounting evidence suggesting that certain foods may potentially influence the development of endometriosis in susceptible individuals. However, this is the first MR analysis to evaluate the potential causality between dietary factors and the risk of endometriosis using large-scale summary statistics from food intake GWAS and endometriosis GWAS, which provide unconfounded causal estimates. In our analysis, it has been found that consuming salad / raw vegetable has a protective effect on endometriosis while processed meat intake is associated with a decrease risk factor for the condition. However, there is little evidence supporting an association between endometriosis risk and alcoholic drinks per week, alcohol intake frequency, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, coffee intake and dried fruit intake. The findings of our study can assist clinicians in enhancing their health education for patients with endometriosis, as well as motivating these patients to change their dietary patterns (such as increasing salad / raw vegetable intake and processed meat intake). For those at high risk for endometriosis, changing dietary habits can also decrease the likelihood of onset.\u003c/p\u003e \u003cp\u003eThere have been numerous observational studies on the correlation between vegetable intake and the risk of endometriosis. Most of these have shown that increasing vegetable consumption is linked to a reduction in endometriosis risk. Ashrafi M et al. \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003efound that people who kept higher green vegetables intake took a lower endometriosis risk (OR\u0026thinsp;=\u0026thinsp;0.39, 95% CI\u0026thinsp;=\u0026thinsp;0.21\u0026ndash;0.74; p\u0026thinsp;=\u0026thinsp;0.004) in a retrospective case-control study from Iranian. In another hospital-based case-control study by Parazzini et al., comparing 504 women with endometriosis and 504 women without endometriosis confirmed through laparoscopy, the authors indicated a statistically significant decrease in the consumption of green vegetables among cases (OR\u0026thinsp;=\u0026thinsp;0.3, 95% CI\u0026thinsp;=\u0026thinsp;0.2\u0026ndash;0.5)\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Likewise, several similar studies conducted in other countries also demonstrated a decreased endometriosis risk for those who increased their vegetables consumption\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. However, not all studies shown the effect of vegetable intake on endometriosis. Based on a population-based case-control study involving 944 participants (284 cases and 660 controls), Trabert et al. reported total vegetable intake was not associated with incident endometriosis\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. The authors hypothesized that this finding could be attributed to pesticide exposure, which might generate reactive oxygen species and reduce the antioxidant capacity of vegetables. Some studies\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, on the other hand, have demonstrated that certain class of pesticides can cause estrogenic effects, thereby promoting the development of endometriosis lesions. Alternatively, a meta-analysis indicated an insignificant correlation between eating vegetable and the risk of developing endometriosis\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Furthermore, Harris et al.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e reported that a high intake of some vegetables such as cruciferous vegetables, particularly cauliflower, cabbage was related to an increase in endometriosis risk. Through MR analysis, our study indicated that a high level of vegetables intake might be associated with a decreased risk of endometriosis.\u003c/p\u003e \u003cp\u003eEndometriosis is an oestrogen-dependent disease. Typically, populations on a diet rich in green vegetables have higher levels of sex-hormone binding globulin (SHBG), which can attenuate the oestrogenic stimulation of the endometrium and restrict the proliferation of prostaglandin-producing tissues. Additionally, dietary fiber can interrupt enterohepatic circulation of oestrogen conjugates, thereby reducing the risk of endometriosis\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Studies have indicated that a number of nutrients found in vegetables potentially benefit endometriosis. First of all, vitamins, especially vitamin C, are important antioxidants that strongly neutralize free radicals and improve oxidative status to reduce the chances of developing endometriosis\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. This finding aligns with a randomized, triple-blind placebo-controlled clinical study that reported a decrease in systemic indicators of oxidative stress in patients with endometriosis after receiving a boost of vitamin C \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Furthermore, the influence of vitamin C on the expression and production of the VEGF gene was investigated in peritoneal macrophages from women diagnosed with endometriosis\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Vitamin A can also play a role in influencing aberrant cytokines production in endometriosis, such as suppressing the transcription and translational processes of IL-6 and VEGF\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Secondly, vegetables are packed with bioactive plant compounds, especially polyphenols (such as curcumin, resveratrol and epigallocatechin gallate). Natural polyphenols have been proven to possess anti-inflammatory and antioxidative properties, making them a cost-effective and easily accessible treatment option for endometriosis\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. In addition to these properties, polyphenols can be used as estrogen receptor agonists to combat the condition due to their structural similarity with estradiol\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Thirdly, many vegetables contain phytoestrogens that can be classified into three classes: flavonoids, lignans and stilbenes. These compounds are structural and functional homologies with estrogen and act as weak estrogenic factors by binding to the estrogen receptor and interfering with ER mediated responses\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Furthermore, the mechanism of action of flavonoids is pleiotropic and includes promoting autophagy, down-regulating nuclear factor (NF)-κB activity, reducing interleukin (IL)-6 and tumor necrosis factor α (TNFα), as well as inhibiting oxidative stress, thereby generating proapoptotic, anti-inflammatory, and anti-proliferative effects\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur MR analysis also indicated a decreased endometriosis risk for those with processed meat intake, which was consistent with the result of a case-control study by Ashrafi M et al.\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e(OR\u0026thinsp;=\u0026thinsp;0.61, 95% CI\u0026thinsp;=\u0026thinsp;0.41\u0026ndash;0.91, P\u0026thinsp;=\u0026thinsp;0.015). However, different results were obtained by other studies. In a large Italian study, endometriosis risk was notably higher among women in the highest intake of red meat, both processed and unprocessed, compared to those in the lowest (OR\u0026thinsp;=\u0026thinsp;2.0, 95% CI\u0026thinsp;=\u0026thinsp;1.4\u0026ndash;2.8; P\u0026thinsp;=\u0026thinsp;0.0004)\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. In a Nurses\u0026rsquo; Health Study II (NHSII) prospective cohort including 81908 participants, red meat consumption, especially non-processed rea meat consumption, was correlated with a greater risk of laparoscopically-confirmed endometriosis by approximately 56% (95% CI\u0026thinsp;=\u0026thinsp;1.22\u0026ndash;1.99; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Likewise, a meta-analysis of observational studies reported that women eating red meat had a 17% higher risk in endometriosis\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. In contrast to these findings, a Washington state based case-control study\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e and a Belgian matched case-control study with prospective recruitment\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e showed no association between red meat intake and incident endometriosis. Owing to the inconsistency between our results and those reported in previous studies, our conclusion must be viewed cautiously. Also, we must correctly understand the correlation between MR analysis and observational studies. MR analysis makes a terrific addition to observational studies because it is not affected by common confounding factors or reverse causation bias but cannot serve as their substitute.\u003c/p\u003e \u003cp\u003ePrevious studies provide solid evidence linking red meat consumption to an increased risk of many chronic diseases, including diabetes, hypertension, cardiovascular disease and some cancers\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Although the physiological mechanism of how red meat affects endometriosis remains incompletely understood, it has been postulated to involve several ways. On the one hand, a high intake of animal fat in a meat-based diet such as palmitic acid can further increase endogenous estrogens, which stimulate the formation of proinflammatory PGs. These PGs can also induce the release of aromatase P450, promoting inflammatory conditions in endometriosis\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. On the other hand, diets rich in red meat seem to correlate with decreased SHBG and increased estradiol concentrations, that influence pain in women with endometriosis\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Another possible mechanism is iron overload in women with a high intake of red meat, which is related to increased oxidative stress and inflammatory status in endometriosis\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Furthermore, iron overload in the peritoneal fluid of women with endometriosis can decrease GPX4 expression, cause embryotoxicity and induce ferroptosis, which probably participates in endometriosis-associated reproductive failure\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo date, the dietary structure is complex and the contribution of diet to endometriosis has not been sufficiently studied. Observational studies that assess the relationship between dietary factors and endometriosis have certain limitations, including recall bias, confounding introduced by self-reported food questionnaires, and reverse causation bias. Therefore, more future observational studies and ingenious MR studies are needed to elucidate the role of diet in endometriosis.\u003c/p\u003e \u003cp\u003eNotably, our MR analysis possesses several significant strengths. Firstly, to the best of our knowledge, this MR study is the first to systematically analyze the causality between dietary factors and endometriosis by using genetic variation as IVs, effectively overcoming the reverse causality and confounding bias. Moreover, we utilized European populations as both the exposure and outcome groups to minimize potential biases. Secondly, some of the findings from this study contradict current knowledge, thereby providing valuable insights for future research directions. Thirdly, we took several steps to meet the core assumptions of MR analysis and utilized a large sample size along with SNPs derived from GWAS, thus significantly enhancing the credibility of our findings.\u003c/p\u003e \u003cp\u003eInevitably, this study also has some limitations. Firstly, this analysis was conducted solely with European participants, which hinders the generalizability of these findings to other populations. Furthermore, we were unable to differentiate the specific effects of different dietary combinations. Secondly, food intake GWAS is still in its early stages due to small sample sizes, which may compromise statistical power. Therefore, the absence of significant associations does not necessarily imply that food intake has no effect. Thirdly, due to the lack of summary-level GWAS data for various ages groups, we cannot conduct an age-stratified analysis further. Lastly, it remains uncertain whether dose-response relationships exist between dietary factors and the risk of endometriosis. Additionally, the food intake data used in our study were obtained through a self-reported questionnaire instead of objective measurements, potentially introducing recall bias.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOverall, we thoroughly examined the potential causal association between dietary intake and endometriosis. Two specific types of food consumption (salad / raw vegetable intake and processed meat intake) are associated with a decreased risk of developing endometriosis. However, further research is required to elucidate the precise causal relationship and underlying mechanisms linking specific dietary patterns to endometriosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed in this study are publicly available summary statistics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s note\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely thank the researchers and the participants of the original GWASs for the collection and management of the large-scale data resources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXZ conducted the data analysis and drafted the manuscript. QZ took responsibility of the tables and figures of the results. LC designed the study, revised the manuscript, and provided technical support. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with ethical standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e Ethical approval was not needed for this current study because it is a secondary analysis of previously published data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e For this type of article, informed consent is not required.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRowlands IJ, Abbott JA, Montgomery GW, et al. Prevalence and incidence of endometriosis in Australian women: a data linkage cohort study[J]. Bjog, 2021, 128(4): 657-665.\u003c/li\u003e\n\u003cli\u003eSaunders PTK, Horne AW. 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Int J Fertil Steril, 2020, 14(3): 193-200.\u003c/li\u003e\n\u003cli\u003eMsyamboza KP, Ngwira B, Dzowela T, et al. The burden of selected chronic non-communicable diseases and their risk factors in Malawi: nationwide STEPS survey[J]. PLoS One, 2011, 6(5): e20316.\u003c/li\u003e\n\u003cli\u003eAlmeida-de-Souza J, Santos R, Lopes L, et al. Associations between fruit and vegetable variety and low-grade inflammation in Portuguese adolescents from LabMed Physical Activity Study[J]. Eur J Nutr, 2018, 57(6): 2055-2068.\u003c/li\u003e\n\u003cli\u003eTrabert B, Peters U, De Roos AJ, et al. Diet and risk of endometriosis in a population-based case-control study[J]. Br J Nutr, 2011, 105(3): 459-467.\u003c/li\u003e\n\u003cli\u003eMier-Cabrera J, Aburto-Soto T, Burrola-M\u0026eacute;ndez S, et al. Women with endometriosis improved their peripheral antioxidant markers after the application of a high antioxidant diet[J]. 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Pharmaceuticals (Basel), 2021, 14(6).\u003c/li\u003e\n\u003cli\u003eSaguyod SJU, Kelley AS, Velarde MC, et al. Diet and endometriosis-revisiting the linkages to inflammation[J]. Journal of Endometriosis and Pelvic Pain Disorders, 2018, 10(2): 51-58.\u003c/li\u003e\n\u003cli\u003eHeilier JF, Donnez J, Nackers F, et al. Environmental and host-associated risk factors in endometriosis and deep endometriotic nodules: a matched case-control study[J]. Environ Res, 2007, 103(1): 121-129.\u003c/li\u003e\n\u003cli\u003eBrinkman MT, Baglietto L, Krishnan K, et al. Consumption of animal products, their nutrient components and postmenopausal circulating steroid hormone concentrations[J]. Eur J Clin Nutr, 2010, 64(2): 176-183.\u003c/li\u003e\n\u003cli\u003eLi S, Zhou Y, Huang Q, et al. Iron overload in endometriosis peritoneal fluid induces early embryo ferroptosis mediated by HMOX1[J]. Cell Death Discov, 2021, 7(1): 355.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nutrition-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutj","sideBox":"Learn more about [Nutrition Journal](http://nutritionj.biomedcentral.com/)","snPcode":"12937","submissionUrl":"https://submission.nature.com/new-submission/12937/3","title":"Nutrition Journal","twitterHandle":"@NutrJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"dietary intake, endometriosis, mendelian randomization, causal association","lastPublishedDoi":"10.21203/rs.3.rs-4062748/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4062748/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObservational studies have reported an association between dietary factors and endometriosis, but the causality remains unknown. The study aimed to evaluate the potential causal effect of dietary factors on endometriosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed a two-sample Mendelian randomization (MR) analysis to investigate the effects of 18 diet-related exposure factors (alcoholic drinks per week, alcohol intake frequency, processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, salad/raw vegetable intake, coffee intake, dried fruit intake) on the risk of endometriosis using summary statistics from the genome-wide association study (GWAS). The inverse variance weighted (IVW) method was used to deduce the causal association between dietary factors and endometriosis, and sensitivity analyses were further performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProcessed meat intake (OR=0.550; 95%CI:0.314-0.965; p=0.037) and salad / raw vegetable intake (OR=0.346; 95%CI:0.127-0.943; p=0.038) were discovered as protective factors for endometriosis. Heterogeneity test revealed no significant heterogeneity (processed meat intake: p\u003csub\u003eIVW\u003c/sub\u003e=0.607, p\u003csub\u003eMR-Egger\u003c/sub\u003e=0.548; salad / raw vegetable intake: p\u003csub\u003eIVW\u003c/sub\u003e=0.678, p\u003csub\u003eMR-Egger\u003c/sub\u003e=0.620). MR-Egger regression test didn’t support any evidence for horizontal pleiotropy (processed meat intake: p for intercept=0.865; salad / raw vegetable intake: p for intercept=0.725). No causal relationship was found between other dietary intakes and endometriosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese findings suggest that processed meat intake and salad/raw vegetable intake are associated with a decreased risk of endometriosis, but further investigation is required.\u003c/p\u003e","manuscriptTitle":"Dietary factors and risk for endometriosis: a Mendelian randomization analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-14 07:19:37","doi":"10.21203/rs.3.rs-4062748/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-05-07T13:43:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-12T03:35:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Nutrition Journal","date":"2024-03-10T07:20:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nutrition-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutj","sideBox":"Learn more about [Nutrition Journal](http://nutritionj.biomedcentral.com/)","snPcode":"12937","submissionUrl":"https://submission.nature.com/new-submission/12937/3","title":"Nutrition Journal","twitterHandle":"@NutrJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"22188c8b-a55f-4fc7-acae-ffd1782a4ccb","owner":[],"postedDate":"March 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-03-14T07:19:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-14 07:19:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4062748","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4062748","identity":"rs-4062748","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}