Correlates associated with participation in physical activity among adults: a systematic review of reviews and update

Background Understanding which factors influence participation in physical activity is important to improve the public health. The aim of the present review of reviews was to summarize and present updated evidence on personal and environmental factors associated with physical activity. Methods MEDLINE and EMBASE were searched for reviews published up to 31 Jan. 2017 reporting on potential factors of physical activity in adults aged over 18 years. The quality of each review was appraised with the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) checklist. The corrected covered area (CCA) was calculated as a measure of overlap for the primary publications in each review. Results Twenty-five articles met the inclusion criteria which reviewed 90 personal and 27 environmental factors. The average quality of the studies was moderate, and the CCA ranged from 0 to 4.3%. For personal factors, self-efficacy was shown as the strongest factor for participation in physical activity (7 out of 9). Intention to exercise, outcome expectation, perceived behavioral control and perceived fitness were positively associated with physical activity in more than 3 reviews, while age and bad status of health or fitness were negatively associated with participation in physical activity in more than 3 reviews. For environmental factors, accessibility to facilities, presence of sidewalks, and aesthetics were positively associated with participation in physical activity. Conclusions The findings of this review of reviews suggest that some personal and environmental factors were related with participation in physical activity. However, an association of various factors with physical activity could not be established because of the lack of primary studies to build up the organized evidence. More studies with a prospective design should be conducted to understand the potential causes for physical activity

Optimal cutoff values for anthropometric indices of obesity as discriminators of metabolic abnormalities in Korea: results from a Health Examinees study

Background Obesity is well known as a risk factor for cardiovascular disease. We aimed to determine the performance of and the optimal cutoff values for obesity indices to discriminate the presence of metabolic abnormalities as a primary risk factor for cardiovascular diseases in a Health Examinees study (HEXA). Methods The current study analyzed 134,195 participants with complete anthropometric and laboratory information in a Health Examinees study, consisting of the Korean population aged 40 to 69 years. The presence of metabolic abnormality was defined as having at least one of the following: hypertension, hyperglycemia, or dyslipidemia. The area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs) were calculated for body mass index, waist to hip ratio, waist to height ratio, waist circumference, and conicity index. Results The AUC of metabolic abnormalities was the highest for waist-to-height ratio (AUC [95% CIs], 0.677 [0.672–0.683] among men; 0.691 [0.687–0.694] among women), and the lowest for the C index (0.616 [0.611–0.622] among men; 0.645 [0.641–0.649] among women) among both men and women. The optimal cutoff values were 24.3 kg/m2 for the body mass index, 0.887 for the waist-to-hip ratio, 0.499 for the waist-to-height ratio, 84.4 cm for waist circumference and 1.20 m3/2/kg1/2 for the conicity index among men, and 23.4 kg/m2 for the body mass index, 0.832 for the waist-to-hip ratio, 0.496 for the waist-to-height ratio, 77.0 cm for the waist circumference and 1.18 m3/2/kg1/2 for the conicity index among women. Conclusion The waist-to-height ratio is the best index to discriminate metabolic abnormalities among middle-aged Koreans. The optimal cutoff of obesity indices is lower than the international guidelines for obesity. It would be appropriate to use the indices for abdominal obesity rather than general obesity and to consider a lower level of body mass index and waist circumference than the current guidelines to determine obesity-related health problems in Koreans.This study was supported by the Korea Centers for Disease Control and Prevention [funding codes 2004-E71004–00, 2007-E71006–00, 2005-E71011–00, 2008-E71006–00, 2005-E71009–00, 2008-E71008–00, 2006-E71001–00, 2009-E71009–00, 2006-E71004–00, 2010-E71006–00, 2006-E71010–00, 2011-E71006–00, 2006-E71003–00, 2012-E71001–00, 2007-E71004–00, and 2013-E71009–00]. The funder had a role in the design of the study and data collection. We declare that the funder had no role in the analysis or writing of the manuscript

A time-dependent subdistribution hazard model for major dental treatment events in cancer patients: a nationwide cohort study

Abstract Background Dental care in cancer patients tends to be less prioritized. However, limited research has focused on major dental treatment events in cancer patients after the diagnosis. This study aimed to examine dental treatment delays in cancer patients compared to the general population using a national claims database in South Korea. Method The Korea National Health Insurance Service-National Sample Cohort version 2.0, collected from 2002 to 2015, was analyzed. Treatment events were considered for stomatitis, tooth loss, dental caries/pulp disease, and gingivitis/periodontal disease. For each considered event, time-dependent hazard ratios and associated 95% confidence intervals were calculated by applying a subdistribution hazard model with time-varying covariates. Mortality was treated as a competing event. Subgroup analyses were conducted by type of cancer. Results The time-dependent subdistribution hazard ratios (SHRs) of stomatitis treatment were greater than 1 in cancer patients in all time intervals, 2.04 within 30 days after cancer diagnosis, and gradually decreased to 1.15 after 5 years. The SHR for tooth loss was less than 0.70 within 3 months after cancer diagnosis and increased to 1 after 5 years. The trends in SHRs of treatment events for other dental diseases were similar to those observed for tooth loss. Subgroup analyses by cancer type suggested that probability of all dental treatment event occurrence was higher in head and neck cancer patients, particularly in the early phase after cancer diagnosis. Conclusion Apart from treatments that are associated with cancer therapy, dental treatments in cancer patients are generally delayed and cancer patients tend to refrain from dental treatments. Consideration should be given to seeking more active and effective means for oral health promotion in cancer patients

Strong association between herpes simplex virus-1 and chemotherapy-induced oral mucositis in patients with hematologic malignancies

Background/Aims: A link between oral cavity infections and chemotherapy-induced oral mucositis (CIOM) in patients with hematological malignancies (HMs) undergoing intensive chemotherapy (IC) or hematopoietic stem cell transplantation (HSCT) has been suggested. However, conclusive data are lacking, and there are no current guidelines for the prophylactic use of antimicrobials to prevent CIOM in these populations. Methods: The relationships between herpes simplex virus (HSV) reactivation and Candida colonization in the oral cavity and CIOM in patients with HMs undergoing IC or HSCT were evaluated. Patients aged >= 19 years with HMs undergoing IC or HSCT were enrolled. Each patient was evaluated for HSV and Candida in the oral cavity along with CIOM at baseline and during the and, 3rd, and 4th weeks. Results: Seventy presentations among 56 patients were analyzed. CIOM was observed in 23 presentations (32.9%), with a higher incidence associated with HSCT (17 of 35 presentations, 48.6%) than with IC (six of 35 presentations, 8.6%). The reactivation of HSV-1 was significantly associated with an increased incidence of CIOM after adjusting for age, sex, type of disease, and treatment stage. A higher HSV-1 viral load was associated with an increased incidence of CIOM. The presence of Candida was not associated with CIOM. Conclusions: HSV-1 reactivation in the oral cavity was highly associated with CIOM in patients with HMs undergoing high-dose chemotherapy.Y

Genetic Polymorphism of Geranylgeranyl Diphosphate Synthase (GGSP1) Predicts Bone Density Response to Bisphosphonate Therapy in Korean Women

Purpose: Genetic factor is an important predisposing element influencing the susceptibility to osteoporosis and related complications. The purpose of the present study is to investigate whether genetic polymorphisms of farnesyl diphosphate synthase (FDPS) or geranylgeranyl diphosphate synthase (GGPS) genes were associated with the response to bisphosphonate therapy. Materials and Methods: In the present study, 144 Korean women with osteoporosis were included. Among 13 genetic polymorphisms found within the FDPS and GGPS1 gene, 4 genetic polymorphisms with frequencies > 5% were selected for further study. Bone mineral density (BMD) response after 1 year treatment of bisphosphonate therapy was analyzed according to the genotypes. Results: Women with 2 deletion allele of GGPS1 -8188A ins/del (rs3840452) had significantly higher femoral neck BMD at baseline compared with those with one or no deletion allele (0.768 +/- 0.127 vs. 0.695 +/- 0.090 respectively; p = 0.041). The response rate of women with 2 deletion allele of GGPS1 -8188A ins/del (28.6%) was significantly lower than the rate of women with one (81.4%) or no deletion allele (75.0%) (p = 0.011). Women with 2 deletion allele of GGPS1 -8188A ins/del had 7-fold higher risk of non-response to bisphosphonate therapy compared with women with other genotypes in GGPS1 -8188 after adjusting for baseline BMD (OR = 7.48; 95% CI = 1.3242.30; p = 0.023). Other polymorphisms in FDPS or GGPS1 were not associated with lumbar spine BMD or femoral neck BMD. Conclusion: Our Study suggested that GGPS1 -8188A ins/del polymorphism may confer susceptibility to femoral heck BMD response to bisphosphonate therapy in Korean women. However, further study should be done to confirm the results in a larger population.This work was supported by a grant from Ministry of Health, Welfare and Family of Korea (03-PJ10-PG13- GD01-0002).Guo RT, 2007, P NATL ACAD SCI USA, V104, P10022, DOI 10.1073/pnas.0702254104Gallagher JC, 2006, BONE, V39, P1268, DOI 10.1016/j.bone.2006.06.007Bonnick S, 2006, J CLIN ENDOCR METAB, V91, P2631, DOI 10.1210/jc.2005-2602BONNICK SL, 2006, AM J MED S1, V119, pS25Kim SW, 2005, ENDOCR J, V52, P667Palomba S, 2005, OSTEOPOROSIS INT, V16, P943, DOI 10.1007/s00198-004-1800-5Lewiecki EM, 2003, J CLIN DENSITOM, V6, P307Palomba S, 2003, CLIN ENDOCRINOL, V58, P365Qureshi AM, 2002, CALCIFIED TISSUE INT, V70, P158Turner CH, 2002, OSTEOPOROSIS INT, V13, P97Mann V, 2001, J CLIN INVEST, V107, P899Keen RW, 2001, RHEUMATOLOGY, V40, P48Bergstrom JD, 2000, ARCH BIOCHEM BIOPHYS, V373, P231Crilly RG, 2000, OSTEOPOROSIS INT, V11, P607Eisman JA, 1999, ENDOCR REV, V20, P788Tsukamoto K, 1999, J HUM GENET, V44, P148Keen RW, 1998, BONE, V23, P367Masi L, 1998, BIOCHEM BIOPH RES CO, V248, P190Uitterlinden AG, 1998, NEW ENGL J MED, V338, P1016Mizunuma H, 1997, BONE, V21, P379Kurland ES, 1997, J CLIN ENDOCR METAB, V82, P2799Shiraki M, 1997, J BONE MINER RES, V12, P1438Sainz J, 1997, NEW ENGL J MED, V337, P77Johnson ML, 1997, AM J HUM GENET, V60, P1326Langdahl BL, 1997, BONE, V20, P289SILVERMAN SL, 1992, CALCIFIED TISSUE INT, V50, P101

The Effect of Breastfeeding Duration and Parity on the Risk of Epithelial Ovarian Cancer: A Systematic Review and Meta-analysis

Review Objectives: We conducted a systematic review and meta-analysis to summarize current evidence regarding the association of parity and duration of breastfeeding with the risk of epithelial ovarian cancer (EOC). Methods: A systematic search of relevant studies published by December 31, 2015 was performed in PubMed and EMBASE. A random-effect model was used to obtain the summary relative risks (RRs) and 95% confidence intervals (CIs). Results: Thirty-two studies had parity categories of 1, 2, and ≥3. The summary RRs for EOC were 0.72 (95% CI, 0.65 to 0.79), 0.57 (95% CI, 0.49 to 0.65), and 0.46 (95% CI, 0.41 to 0.52), respectively. Small to moderate heterogeneity was observed for one birth (p<0.01; Q=59.46; I 2 =47.9%). Fifteen studies had breastfeeding categories of <6 months, 6-12 months, and >13 months. The summary RRs were 0.79 (95% CI, 0.72 to 0.87), 0.72 (95% CI, 0.64 to 0.81), and 0.67 (95% CI, 0.56 to 0.79), respectively. Only small heterogeneity was observed for <6 months of breastfeeding (p=0.17; Q=18.79, I 2 =25.5%). Compared to nulliparous women with no history of breastfeeding, the joint effects of two births and <6 months of breastfeeding resulted in a 0.5-fold reduced risk for EOC. Conclusions: The first birth and breastfeeding for <6 months were associated with significant reductions in EOC risk. Key words: Ovarian neoplasms, Parity, Breast feeding, Reproduction, Risk factors, Meta-analysis Received: June 29, 2016 Accepted: September 8, 2016 Corresponding author: Suekyung Park, MD, PhD 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea Tel: +82-2-740-8338, Fax: +82-2-747-4830 E-mail: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. INTRODUCTION Worldwide, ovarian cancer is the seventh most common cancer in women. Furthermore, it is the sixth leading cause of cancer deaths in women and the second most common cause of death among those with gynecologic cancers 350 to 8%), germ cell tumors (3% to 5%), and other rare types of ovarian cancer Most ovarian cancers are life-threatening and are notorious for having a poor prognosis, as they are usually diagnosed at an advanced stage. Moreover, screening results based on pelvic imaging or tumor markers for early detection remain unsatisfactory Reproductive risk factors for epithelial ovarian cancer (EOC) have been extensively explored in epidemiologic studies. For instance, a pooled analysis of 12 US case-control studies in 1992 showed that parous women and those who had breastfed had a lower risk of EOC Since 1992, many studies from around the world have reported associations of parity and breastfeeding with ovarian cancer. However, findings concerning the protective role of increasing parity and duration of breastfeeding remain inconsistent. For parity, some studies have indicated that the first birth reduces ovarian cancer risk more than subsequent births Therefore, we conducted a systematic review and metaanalysis to summarize the current evidence regarding the association of parity and duration of breastfeeding with EOC risk. The aim of this study was to clarify the threshold for risk reduction among the studies without heterogeneity across the results. An additional aim was to perform a meta-analysis to estimate the joint risk reductions associated with parity and breastfeeding. METHODS Search Strategy We performed a literature search including studies published through December 2015 using the following search terms in the PubMed and EMBASE databases (1) (parity or "number of live births") and (ovary or ovarian) and (cancer or tumor or neoplasm or malignancy) or (2) (breastfeeding or lactation) and (ovary or ovarian) and (cancer or tumor or neoplasm or malignancy). Furthermore, to find any additional published studies, a manual search was performed by checking all references of prior meta-analyses [5,6.8,20-23] and of all the original studies. This systematic review was planned, conducted, and reported in adherence to the standards of quality for reporting meta-analyses Study Selection To be included, studies had to meet the following criteria: (1) the studies were observational (case-control or cohort studies), (2) the exposures of interest were the number of live births and the total duration of breastfeeding, (3) the outcome of interest was EOC, (4) odds ratios (ORs) or relative risk (RR) estimates with 95% confidence intervals (CIs) were reported or sufficient data were present to allow the calculation of these effect measures, and (5) articles were published in the English language. In the case of overlapping data, the study with the largest number of cases was included. As fertility treatments and BRCA mutation effects on EOC may alter the association between parity/breastfeeding and EOC [26], we excluded studies conducted on specific populations, such as BRCA-1 or BRCA-2 mutation carriers or infertile women treated with fertility drugs. The detailed steps of our literature search are shown in Data Extraction Data extraction was conducted independently by two authors. Disagreements were discussed and resolved by consensus. The following data were collected from each study: the first author's last name, publication year, study region and design, study period, participant age, sample size (cases and 351 Parity and Breastfeeding Effects on Ovarian Cancer Risk controls or cohort size), exposure variables (parity or total breastfeeding duration), study-specific adjusted RR or OR with 95% CIs for each exposure category, and factors matched or adjusted for in the design or data analysis. If no adjusted RR or OR was presented, we included crude estimates. If no RRs or ORs were presented in a given study, we calculated them and the 95% CIs according to the raw frequencies presented in the article. The quality of the study was assessed independently by two authors using the 9-star Newcastle-Ottawa Scale (range, 0 to 9 stars) Statistical Analysis The study-specific RRs or ORs with 95% CIs were used to determine the principal outcome. Because the OR closely approximates the RR for rare diseases, the RR can be estimated from a case-control study using the OR as an approximation One study did not provide the required risk estimates for analysis or separate the risk estimates for different categories of parity or breastfeeding duration. For this study, we used the method proposed by Fleiss and Gross [30]. This method allows adjusted effect estimates and CIs to be calculated for any alternative comparison of levels and can help in a dose-response meta-analysis. Briefly, we combined risk estimates obtained through a simple fixed-effects meta-analysis wherein the subjects were divided into unexposed groups (i=0) and exposed groups (i=1, …, n), and estimates (Ri) with lower and upper 95% CIs were available. To obtain the R1+, we meta-analyzed R1, R2, R3, …, Rn using a fixed-effect model. The categories of parity or breastfeeding duration varied across studies; accordingly, the number of studies included in each metaanalysis and the summary RRs in each meta-analysis were different depending upon the number of categories. Statistical heterogeneity among studies was evaluated with the Cochran Q and I-squared statistics 352 with ≤7 stars considered low-quality as per the 9-star Newcastle-Ottawa Scale; and (3) year of publication (<2000, ≥ 2000), respectively. Publication bias was evaluated using the Begg rank correlation and the Egger linear regression test, in which p-vlaue <0.05 were considered representative of statistically significant publication bias From the meta-analyzed result, to calculate the RR for the joint effect of parity and breastfeeding, we applied the log-linear dose-response model proposed by Berlin et al. We configured the following formula for the multivariate linear logit regression of two factors: Logit P=α + β1χ1 + β2χ2; where P is the probability of a particular outcome (EOC risk), α is the intercept from the linear regression equation, β is the regression coefficient multiplied by some value of the predictor, and χ is the risk factor (parity and breastfeeding). Using this equation yields the value of the RR for the joint effects of parity and breastfeeding duration. For example, in the case of a subject who has no risk factors, logit(P) is α. In this case, the probability of EOC is exp(α)=1.0. In the case of a subject with only χ1, logit(P) is α+β1. In the case of a subject with both χ1 and χ2, logit(P) is α+β1+β2. Accordingly, the probability of EOC is exp(β1+β2)=OR1×OR2. Since the category of parity and breastfeeding duration varied across studies, to calculate the RR for the joint effect of parity and breastfeeding, we used the summary RR for parity and breastfeeding duration that contained the largest number of studies. All statistical analyses were performed with Stata version 12.0 (StataCorp., College Station, TX, USA). RESULTS Study Characteristics The characteristics of the 32 studies included with data regarding parity and the 15 studies included with data regarding breastfeeding are shown in Supplemental 353 Parity and Breastfeeding Effects on Ovarian Cancer Risk Africa. For breastfeeding, two cohort studies and 13 case-control studies were included. The included studies were conducted between 1978 and 2008. Of the 15 studies, seven were performed in North America, six in Europe, one in Asia, and one in Australia. Parity and Epithelial Ovarian Cancer Risk Thirty-two studies had parity categories of 1, 2, and ≥3. The summary RRs for the first, second, and third births were 0.72 (95% CI, 0.65 to 0.79), 0.57 (95% CI, 0.49 to 0.65), and 0.46 (95% CI, 0.41 to 0.52), respectively Duration of Breastfeeding and Epithelial Ovarian Cancer Risk Fifteen studies had breastfeeding categories of <6 months, 6-12 months, and ≥13 months. The summary RRs for these categories were 0.79 (95% CI, 0.72 to 0.87), 0.72 (95% CI, 0.64 to 0.81) and 0.67 (95% CI, 0.56 to 0.79), respectively Subgroup Analysis According to Study Design, Study Quality, and Publication Year The results from the subgroup analysis according to study design, study quality, and publication year are shown in Relative Risk for the Joint Effect of Parity and Breastfeeding The RR for the joint effect of parity and breastfeeding, obtained using the summary RR from the analysis of 32 studies with parity categories of 1, 2, and ≥3 and 15 studies with breastfeeding categories of <6 months, 6-12 months, and ≥ 13 months, is shown in DISCUSSION The findings of this meta-analysis indicate that parity and breastfeeding experiences in women can help prevent EOC, which is typically life-threatening and has a poor prognosis. In particular, the first birth and the first six months of breastfeeding had a greater protective effect than did subsequent births and/or additional breastfeeding, although multiparity and additional breastfeeding did provide some additional protection. The risk reduction effect of the first birth on EOC risk was almost 30%, and the combined effect of the first birth and <6 months of breastfeeding was 40%; thus, breastfeeding provided a nearly 10% greater risk reduction. In regards to parity, the EOC risk reduction was highest for the first birth, with some additional protection from the second birth. However, slightly less risk reduction was observed for the third birth Pregnancy and breastfeeding are thought to reduce EOC risk Ho Kyung Sung, et al. 354 by decreasing pituitary gonadotropin levels and inducing anovulation [7,35]. Pregnancy and breastfeeding are expected to decrease the likelihood of spontaneous genetic mutation under the incessant ovulation hypothesis and of the hyperproliferation of inclusion cysts under the gonadotropin hypothesis. However, the observation that multiparity and additional breastfeeding did not provide an equal amount of protection does not provide evidence for either of these hypotheses. Nev- The summary RRs (95% CIs) in each meta-analysis were estimated using a random effect model. 3 Studies with ≥8 stars were considered high-quality as per the 9-star Newcastle-Ottawa Scale. 4 Studies with ≤7 stars were considered low-quality as per the 9-star Newcastle-Ottawa Scale. 355 Parity and Breastfeeding Effects on Ovarian Cancer Risk ertheless, the results of two experimental studies provide biological evidence for the relatively weaker protective effect of additional parity and breastfeeding [36,37]. For instance, high progesterone levels during pregnancy can increase apoptosis, which may clear transformed cells from the ovarian epithelium, meaning that all the accumulated transformed cells are washed fully out by the first pregnancy. Therefore, the first pregnancy provides a stronger protective effect than subsequent pregnancies [36]. In regards to breastfeeding, breastfeeding in the first few months completely inhibits the pulsatile secretion of gonadotropin-releasing hormone and luteinizing hormone, leading to suppression of ovulation [37]. After a couple of months, ovulatory activity may return, even though breastfeeding continues [37]; thus, a longer duration of breastfeeding does not provide an additional protective effect. Our finding of decreased EOC risk with longer breastfeeding is similar to that reported by prior meta-analyses in 2013 and 2014 [22,23], but differs from that of a meta-analysis of nine case-control studies conducted in developed countries in 2001, in which breastfeeding for ≥12 months was associated with a significant 0.72-fold reduced risk of EOC compared to never having breastfed, while breastfeeding <12 months did not show such an association (OR, 0.95; 95% CI, 0.80 to 1.12) The strength of this meta-analysis is that it included all available studies, and the large number of EOC cases allowed for the investigation of the risk associated with different categories of parity and breastfeeding duration. However, the current study also has several limitations. First, our meta-analysis wa

Appraising the role of previously reported risk factors in epithelial ovarian cancer risk: A Mendelian randomization analysis

Background Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours. Methods and findings Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10−8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case–control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR–Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06–1.15; P = 6.94 × 10−7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04–1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15–1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02–1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82–0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk. Conclusions Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer