Survival after Wilms tumor has significantly increased and focus on late effects has become increasingly important. However, knowledge about long‐term renal function in survivors of Wilms tumor is missing. Our aim was to investigate evidence of kidney disease in 20‐ or more‐year survivors of Wilms tumor in a clinical setting, with siblings as comparisons.In this cross‐sectional study, we established a cohort of Danish 20‐plus‐year survivors of Wilms tumor and siblings as controls. Participants answered a comprehensive health questionnaire supplemented by measurements of estimated glomerular filtration rate (eGFR), urine albumin‐to‐creatinine ratio, and blood pressure and were categorized according to the chronic kidney disease classification. Multiple linear regression analysis, taking family membership into account, was used to describe the differences in eGFR. Logistic regression analysis was performed to describe risk factors for the development of kidney disease.2  lower when compared to sibling control. Evidence of kidney disease, with risk factors as hypertension and diabetes, was found in 19% of the Wilms tumor survivors and 2% developed end‐stage renal disease. Ninety‐two percent of the Wilms tumor survivors had an eGFR >60 ml/min/1.732.We included 99 survivors of Wilms tumor and 38 sibling controls with a median of 37 years of follow‐up. The eGFR of Wilms tumor survivors was 13 ml/min/1.73 mLong‐term Wilms tumor survivors have on average a significantly decreased renal function along with the increased prevalence of kidney disease and end‐stage renal disease when compared to sibling controls. Still, most survivors had kidney function within the normal range. Long‐term Wilms tumor survivors have on average a significantly decreased renal function along with increased prevalence of kidney disease and end stage renal disease when compared to sibling controls. Still, most survivors had kidney function within normal range. The information included a questionnaire, a consent form with the possibility to decline participation, and a prepaid return envelope. Patients not responding to the invitation received a reminder by post 4 weeks later. Those not responding within 4 weeks of the reminder were considered “non‐responders” Figure . Followi2.3The questionnaire was based on the Childhood Cancer Survivor Studies2.42.5All participants were invited to a clinical examination at either Copenhagen University Hospital, Odense University Hospital, or Aarhus University Hospital depending on their preference. The follow‐up included a clinical examination with blood pressure measurements, biometric measurements, urine dipstick analyses, a blood‐ and urine sampling, and an echocardiography. The clinical examinations were all performed by the same doctor (SH). The biochemical evaluation included a broad range of organ‐specific analyses. The focus of this study is on serum creatinine, cystatin C, and glycated hemoglobin A1c, along with urine albumin and creatinine. Biochemical analyses were performed at the local laboratory using standardized assays. Estimated glomerular filtration ratio (eGFR) was calculated using the combined creatinine and cystatin C equation; Chronic Kidney Disease‐Epidemiology Collaboration (CKD‐EPI).2.6Duplicate blood pressure measurements were performed in the supine position after a minimum of 5 min rest. The mean of the two measures was used for analysis. Hypertension was defined as either systolic blood pressure > 140 mmHg, diastolic blood pressure > 90 mmHg, current treatment with antihypertensive agents, or self‐reported diagnosis with hypertension from a doctor. Information on the use of antihypertensive agents and hypertension diagnosis were self‐reported in the questionnaire.2.7Details of treatment for Wilms tumor were retrospectively collected from medical records and abstraction of all treatment including treatment for relapse if relevant was completed. The total cumulative dose was calculated for specific chemotherapeutic agents. Cumulative epirubicin dose was converted to doxorubicin doses using a conversion factor of 0.5.2.8To assess potential bias resulting from systematic differences between responders and non‐responders, we obtained additional information on all patients with Wilms tumor available from the ALiCCS database holding information from nationwide hospital registries such as The Danish Cancer Registry, The Danish Civil Registration System, and The Danish National Patient Register Table .182.9t‐test. Multiple linear regression analysis taking family membership into account was used to compare the eGFR of Wilms tumor survivors with sibling controls. The model included sex, age at follow‐up (continuous), and irradiation (yes/no). In analyses of CKD, the outcome was treated dichotomous according to Figure Descriptive statistics were used to summarize demographic, cancer, and treatment variables for Wilms tumor survivors and sibling controls. Variables were compared using Student's 2.10The study's ethical approval included the possibility to contact the survivors and their siblings and to review and abstract the received treatments. The study was approved by the Danish National Committee on Health Research Ethics (1–10–72‐315‐14).33.1Responses to the invitation were received from 106 of 165 (64%) eligible Wilms tumor survivors. Clinical examination was performed on 99 of the 106 survivors  of the Wilms tumor survivors had received chemotherapy, most of them a combination of actinomycin and vincristine, and 54% received radiotherapy. All Wilms tumors patients were treated with nephrectomy except for one with bilateral tumor .3.22  vs. 101 ml/min/1.73 m2 , Figure n = 91), the results did not change this finding (data not shown). A multiple linear regression analysis taking sex, Wilms tumor diagnosis, age at follow‐up, and radiation therapy into consideration, showed that Wilms tumor survivors had eGFR that was 13 ml/min/1.73 m2  lower than their sibling controls. A total of six (6%) (without the two patients in ESRD) Wilms tumor survivors had an eGFR <60 ml/min/1.73 m2, while none (0%) of the siblings had an eGFR <60 ml/min/1.73 m2.The mean eGFR in the 97 Wilms tumor survivors was significantly lower in Wilms tumor survivors compared to the sibling control group (90 ml/min/1.73 m3.3n = 19) was significantly higher compared with the survivors not classified with CKD (n = 80) (46 vs. 40 years). The two Wilms tumor survivors on dialysis were classified as CKD stage G5/A2 and G5/A3, respectively.Albuminuria was detected in 14 (14%) Wilms tumor survivors with 4 (4%) Wilms tumor survivors revealing an ACR above 300 mg/g. In contrast, only 1 (3%) sibling had an ACR between 30 and 300 mg/g. Based on a single test, 19 (19%) Wilms tumor survivors may be defined as having CKD with moderate, high, or very high risk. The one in the sibling control group would qualify as having CKD with moderate risk. The mean age for the Wilms tumor survivors with CKD  against 101 ml/min/1.73 m2 , Figure n = 8) not treated with chemotherapy, and not that being treated with chemotherapy decreases the risk of CKD  was classified with CKD, characterized by decreased eGFR with or without proteinuria.2, and 19% were classified with CKD might be due to the differences in cohorts regarding risk factors for decreased GFR, such as age, ethnicity, comorbidity, or simply due to the differences in sample size. We also evaluated renal function as the estimated glomerular function renal calculated from the combined creatinine–cystatin C equation (CKD‐EPI) taking age, sex, and race into consideration. This equation using the two plasma markers is proven to provide the most precise and accurate estimate of GFR compared with equations based on either creatinine or cystatin C alone.In a recent study with a mean follow‐up time of 27–30 years, Green et. al demonstrated a lower eGFR in 40 survivors of Wilms tumor receiving abdominal irradiation than in controls.There were no patients in our cohort with Denys–Drash or WAGR syndrome. These patients have been reported to have a higher incidence of ESRD than unilateral, non‐syndromic Wilms tumor survivors.The results of this study should be evaluated in the light of certain limitations. Firstly, our study is a cross‐sectional study based on a single follow‐up visit. Due to this study design, we do not have repeated measurements and our data do not enable us to describe the development of renal function over time. We can only conclude from the one‐time measurements, and we do not have the information on whether or not any renal outcome is developed earlier in life, for example, in relation to the treatment for Wilms tumor and persisted, or if it has developed over time. Additionally, we cannot conclude whether or not the renal outcome is chronic, as this would require two separate examinations with a minimum of 3 months between.2 A significant fraction had albuminuria, and 2% of the Wilms tumor survivors developed ESRD and were in need of treatment with dialysis. The results of this study underline that most patients will have a good lifelong kidney health despite tumor location and treatment with nephrotoxic potential. This may be comforting for the parents and health‐care professionals of newly diagnosed Wilms tumor patients regarding risks of kidney disease. However, our study also emphasizes the importance of following Wilms tumor survivors and identifies modifiable risk factors as hypertension and diabetes in the advantage of the risk of developing chronic kidney disease.To conclude, we found that a fraction of the 20‐plus‐year survivors of Wilms tumor has a significantly increased risk for ESRD, decreased renal function, increased prevalence of albuminuria, and CKD with moderate, high, or very high risk in comparison to their non‐cancer sibling controls. The decrease in eGFR among survivors of Wilms tumor is likely to be minor, and importantly 92% of the Wilms tumor survivors had an eGFR >60 ml/min/1.73.Stine Høgsholt: conceptualization, funding acquisition, investigation, methodology, project administration, resources, validation, visualization, writing ‐ original draft.Peter Haubjerg Asdahl: supervision, methodology, validation, visualization, writing review, and editing.Catherine Rechnitzer: supervision, validation, visualization, writing review, and editing.Jeanette Falck Winther: supervision, validation, visualization, writing review, and editing.Henrik Birn: conceptualization, methodology, supervision, validation, visualization, writing review, and editing.Henrik Hasle: conceptualization, methodology, supervision, resources, validation, visualization, writing review, and editing.This study was supported by grants from the Danish Cancer Society (Grant number: R150‐A10178‐16‐S48) and the Danish Childhood Cancer Foundation (Grant number: 2014–33). The funding sources played no role in the design or analysis of the study nor in the interpretation of its findings. No conflicts of interest were declared.None of the authors have conflict of interests to declare.Table S1Click here for additional data file.


There are few analyses of the 15 red blood group system antigen coding genes found in the Yunnan Yi nationality. This has caused many poteintial dangers relating to clinical blood transfusion. In this report, the coding genes and distribution of 15 blood group antigens system in the Yi nationality were tested and compared with those of Han nationality and other ethnic minorities.χ2 test was used to analyze observed and expected values of gene distribution to verify conformation to the Hardy‐Weinberg equilibrium law. Fisher's exact test was used to analyze gene frequency distribution, and the statistical significance was set at p < 0.05.The samples came from the healthy subjects in the first people's Hospital of Qujing, Yunnan Province. Two hundred and three Yunnan Yi and 197 Han nationality individuals were included. Thirty‐three blood group antigens with a low frequency from the 15 blood group systems of Yunnan Yi blood donors were genotyped and analyzed by PCR‐SSP. Sanger sequencing was used to detect A4GALT from the Yunnan Yi nationality. The p < 0.05), but there was no significant difference in the composition ratio of D antigen in the Rh blood group system (p > 0.05). Compared with Tibetan (Tibet), Zhuang (Nanning), and Dong (Guangxi), the gene distribution frequencies of Rh blood group system phenotype CC were significantly lower in the Yunnan Yi nationality (p < 0.05). There were significant differences in six erythrocyte phenotypic antigens in the Yi nationality in Yunnan compared with Han nationality, such as LW(a−b−), JK(a−b+), MMSs, Di(a−b+), Wr(a−b−), and Kp(a−b+) (p < 0.05). There were gene phenotypes with a low frequency in the four rare blood group systems: LW, MNS, Wright, and Colton. Several different mutation types occurred in the P1PK blood group system's A4GALT gene.The ABO blood group examination results for the Yi nationality and the local Han nationality in Qujing City, Yunnan Province, showed the majority were type A and type O, while the least prevalent was type AB. RhD+ accounts for more than 98% of the Yi and Han populations. There was a significant difference in ABO blood group antigen distribution between these two nationalities (Yunnan Yi nationality has a unique genetic background. There are some significantly different distributions of blood group system genes with a low frequency in different regions and groups in China. Multiple mutations in the A4GALT gene of the P1PK blood group system may be related to their environment and ethnic evolution. The system has three antigens, respectively: P1, PThe Yi nationality is the largest ethnic minority in Yunnan, China, with a unique genetic background due to ethnic migration and integration. In this study, PCR‐SSP genotype analysis of P1PK blood type A4GALT, and the study of distribution characteristics in their gene polymorphisms, provide a data basis and assist in the establishment of a comprehensive rare blood type database.22.1Samples of three generations of unrelated Han and Yi people in Fuyuan County, Qujing City, Yunnan Province, China, were randomly collected from December 9 to December 12th, 2018, with a total of 400 blood samples from healthy people, including 203 Yi, 197 Han, 203 men, and 197 women. Healthy population EDTA anticoagulant samples were 8 ml, centrifuged at 1500 g for 5 min, and patient serum (plasma) were isolated and stored at 4°C. This experiment was subject to informed consent from the hospital ethics committee and patients, ethics number is IRB2018‐001(S)‐01.2.2260/280 ratio was extracted from whole blood between 1.8 and 2.0 using the TIAN amp Blood DNA Kit  and kept for standby at −20°C.Genomic DNA, at an OD2.3A PCR reaction system was prepared, and bidirectional primers were added at a concentration of 10  pmol/L . The antigen frequency of RhD+ was 99.5% (202/203) and RhD− was 0.5% (1/203). Han nationality (197 cases) type A was 31.5% (62/197), type B was 27.4% (54/197), type O was 28.4% (56/197); type AB was 12.7% (25/197); the RhD+ antigen frequency was 99.0% (195/197), and RhD− was 0.5% (1/197). The Yi nationality had mostly A and O blood, similar to the Han.From the collection of 203 Yunnan Yi samples and 197 Han samples, ABO blood type was analyzed (Supporting Information: Table p < 0.001), when compared with Tibetan (Tibet) and Dong (Guangxi), while EE was significantly increased when compared to the above (p < 0.001), with exception of Tibetan, where it was significantly lower (p < 0.01). This shows that the Rh phenotypes CC and EE in the Yunnan Yi nationality have a unique genetic background and measurable differences compared with ethnic minorities in other regions.The distribution of Rh blood group system alleles is also significantly different among ethnic minorities in different regions of China (Supporting Information: Table 3.2p < 0.001), the genotype distribution of blood groups with a low frequency of Yi nationality accorded with the Hardy‐Weinberg equilibrium (p > 0.05). The gene frequency of blood groups with a low frequency in the Yi population remained stable. It was found that there are four rare blood group systems and rare phenotypes in the Yunnan Yi nationality: LW(a−b−) = 0.0246 (five cases); MMSS = 0.0049 (one case); MNSS = 0.0049 (one case); MM = 0.0394 (eight cases); MN = 0.0148 (three cases); Wr(a−b−) = 0.0591 (12 cases); Co(a−b−) = 0.0049 (one case).Rare blood type genotype and gene frequency in the Yunnan Yi nationality Table . Except 3.3p < 0.05) , Jk(a−b+), MMss, Di(a−b+), Wr(a−b−), and Kp(a−b+) had significant differences (5) Table .3.4p < 0.001). Compared with other ethnic minorities, the Yi nationality in Yunnan has significant difference (p < 0.05). , while the D antigen composition ratio of Rh blood group system was not significant (p > 0.05). Compared with Tibetan Tibetan, Nanning Zhuang, and Guangxi Dong, the distribution frequencies of CC and EE genes in the Rh blood group system were significantly lower in Yunnan Yi (p < 0.05). There were significant differences between the six antigens of Yunnan Yi people, including Lw(a−b−), Jk(a−b+), MMss, Di(a−b+), Wr(a−b−), Kp(a−b+) (p < 0.05). There are rare genotypes in the four rare blood group systems of LW, MNS, Wright and Colton. Due to the limited data collected, it may not fully represent the blood group status of the Yi people in Yunnan.In this study, results indicated that the Yi and local Han people in Qujing City, Yunnan Province are mostly A‐type and O‐type. There was a significant difference in the antigen distribution of ABO blood group system between the two ethnic groups  and Rh  blood group systems are the two most important systems in the human erythroid blood group system, both of which are autosomal dominant, according to Mendel's Law.p < 0.001). this may be related to the small number of individual samples collected in the clinic, resulting in certain deviations in the statistics.Through the hardy‐Weinberg fit test, the observed and expected values of the distribution of 13 erythrocyte blood type genotypes in 203 Yunnan Yi people were basically in line with the hardy‐Weinberg genetic balance rule, but the LW blood group system had genetic changes, and the difference was statistically significant  and Wr(a+b+) blood groups were not detected in the Han population, while the frequencies of 0.0099 and 0.0493 were found in the Yunnan Yi population, respectively. The expression difference between the two populations has statistical significance.The results of this study suggest that in the LW blood group system, Lw(a−b+) and Lw(a+b+) blood groups were not detected in the Han population, while in the Yunnan Yi people, the Lw(a−b+) blood group accounted for 0.0099, the proportion of Lw(a+b+) blood group is 0.0099, which is statistically different from the distribution of the Han population in the LW blood group system.In this study, the distribution of blood group system genotypes with a low frequency in Yunnan was found significantly different among ethnic minorities in different regions of China.Subsequently, with the polymorphism of P antigen A4GALT gene polymorphism of P1PK was detected. P1PK blood group system antigen which has a common molecular basis, is encoded by the A4GALT gene.5The Yunnan Yi nationality has a unique genetic background. There are some significantly different distributions of rare blood group system genes in different regions and groups in China. Multiple mutations in the A4GALT gene of the P1PK blood group system may be related to their environment and ethnic evolution.Kun‐Hua He: Conceptualization; methodology; project administration; supervision; writing–original draft; writing–review and editing. Lu‐Qiong Xu: Investigation; validation; visualization. Ying‐Feng Hu: Investigation; validation; visualization. Yin‐Xia Xu: Investigation; validation; visualization. Yu Zhao: Data curation; formal analysis; software. Jing‐Yan Bao: Investigation; validation; visualization. Bu‐Qiang Wang: Investigation; validation; visualization.The authors have no conflicts of interest to declare. All authors have read and approved the final version of the manuscript. They had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis. Kun‐hua He affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; No important aspects of the study have been omitted; Any discrepancies from the study as planned have been explained.This study was approved by the Medical Ethical Committee of Qujing No.1 Hospital of Yunnan Province, and the ethics number is IRB2018‐001(S)‐01.The lead author Kun‐Hua He affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned  have been explained.Supporting information.Click here for additional data file.


The associations between blood pressure and cannabis use remain inconsistent. The purpose of our study was to examine gender stratified associations of cannabis use and blood pressure  levels among the general UK Biobank population based study. Among 91,161 volunteers of the UK Biobank population, cannabis use status was assessed by questionnaire and range as heavy, moderate, low and never users. Associations between cannabis use and BP were estimated using multiple gender linear regressions. In adjusted covariates models, lifetime heavy cannabis use was associated with decrease in both SBP, DBP and PP in both genders, but with a higher effect among women , p < 0.001; in women, b = − 1.85 (0.36), p < 0.001; for DBP in men, b = − 0.50 (0.15), p < 0.001; in women, b = − 0.87 (0.17), p < 0.001; and for PP in men, b = − 0.60 (0.20), p < 0.001; in women, b = − 0.97 (0.27), p < 0.001. Among men, lower SBP and DBP levels were observed with participants without dyslipidemia and lower PP in participants with high income levels. Among women, lower SBP, DBP and PP were observed with current smokers, moderate/low alcohol levels and participants without dyslipidemia. Current cannabis use was associated with lower SBP levels in men (b = − 0.63 (0.25), p = 0.012) and in women (b = − 1.17 (0.31), p < 0.001). Same results were observed for DBP and PP. Negative association between BP in men was found but not in women. The small association in BP differences between heavy users and never users remains too small to adopt cannabis-blood pressure public policy in clinical practice. Nevertheless, these studies focused on limited populations leading to influence the impact of cannabis use on CV health9 and few studies have examined gender differences in cannabis use11. The use of medical cannabis is growing rapidly12, but on a limited knowledge regarding safety and efficacy in varied indications13. High values in blood pressure (BP) have been correlated with CV morbidity and mortality14. However, the association between BP and the use of cannabis remains inconsistent15. Nevertheless, a study has described that cannabis can lead to decrease BP due to vasodilatation along with tachycardia16. The cannabidiol (CBD), one of the major compound of cannabis, could reduce blood pressure17. CBD may have a sympathoinhibition action leading to decrease BP17. Old studies have focused on the relation between BP levels and cannabis use. Chronic use of cannabis was associated with decrease in BP20 leading to studies showing that endocannabinoid system could be a novel therapeutic way in hypertension treatment21. Moreover, a recent longitudinal studies showed a negative association with BP only in men22 whereas non-gender stratified cross-sectional studies showed positive association15. To date, the association between BP and cannabis use remains few studied in general populations. Thus, the purpose of our study was to examine gender stratified associations and interactions of the different lifetime aspects of cannabis use and BP levels among the general UK Biobank population.Cannabis is the main used illicit drug. There is a worldwide trend toward to legalize cannabis, thus, it remains important to better understand the health impacts associated with its regular use. Recent studies have shown growing evidence in better cardiometabolic health associated with cannabis use23. Data included socio-economic, behavior and lifestyle, mental health battery, clinical diagnoses and therapies, genetics, imaging and physiological biomarkers from blood and urine samples. The cohort protocol can be found in literature24.The UK Biobank is a prospective cohort for the investigation, prevention, diagnosis and treatment of chronic diseases, such as CV diseases in adults. 502,478 Britons across 22 UK cities from the UK National Health Service Register were included between 2006 and 2010. The cohort was phenotyped and genotyped, by participants who responded to a questionnaire; a computer-assisted interview; physical and functional measures; and blood, urine, and saliva sampleshttps://www.ukbiobank.ac.uk/learn-more-about-uk-biobank/about-us/ethics.All participants provided electronic informed consent and UK Biobank received ethical approval from the North-West Multi-center Research Ethics Committee (MREC) covering the whole of UK. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the North West—Haydock Research Ethics Committee . For details: 25. Antidepressant drugs use were excluded due to the association between cannabis use and depression26. The list of antidepressant drugs was available at27. We therefore analyzed 91,161 volunteers  were measured twice at the assessment center by the use of an automated BP device , or manually by the use of a sphygmomanometer with an inflatable cuff in association with a stethoscope if the blood pressure device failed to measure the BP or if the largest inflatable cuff of the device did not fit around the individual’s arm29. Multiple available measures for one participant were averaged. The Omron 705 IT BP monitor has satisfied the Association for the Advancement of Medical Instrumentation SP10 standard and was validated by the British Hypertension Society protocol, with an overall “A” grade for both SBP and DBP30. 5295 participants (5.8% of the study population) had a manual sphygmomanometer BP measurement. Nevertheless, automated devices measure lower BP in comparison to manual sphygmomanometers31, thus, and according to previous works for UK Biobank data34, we adjusted both SBP and DBP which were measured using the automated device using algorithms:The participant was sitting in a chair for performing all the measures. The measures were carried out by nurses trained in performing BP measuresFor SBP, we performed the following algorithm:For DBP, we performed the following algorithm:Pulse pressure (PP) was calculated as = SBP − DBP.Cannabis use was reported by self-reported questionnaire. Participants were asked about their cumulative lifetime cannabis use: ‘Have you taken cannabis , even if it was a long time ago?’. Those who responded ‘no’ were classified as controls and those endorsing ‘yes’ options were classified as cannabis users. We separated these users into three groups according to categories reported in the questionnaire: those reporting initial cannabis use  and continued cannabis use . Cannabis users were asked “About how old were you when you last had cannabis?”. Cannabis user participants reporting this information and showing difference between age at inclusion and age of last cannabis use strictly inferior to 1 year were classified as “current users”, the others as “past users”. Among cannabis users, participants were asked about their cannabis frequencies use during taking: ‘Considering when you were taking cannabis most regularly, how often did you take it?’. The participants were classified into four groups, as: ‘every day’, ‘once a week or more, but not every day’, ‘once a month or more, but nor every week’, ‘less than once a month’.35. Hypertension was defined as systolic blood pressure (SBP) at least 140 mm Hg and/or diastolic BP (DBP) at least 90 mm Hg36. Medications were characterized by the question: “Do you regularly take any of the following medications?”.Diabetes status was defined on either receiving anti-diabetic medication or diabetes diagnosed by a doctor or a fasting glucose concentration ≥ 7 mmol/L. Dyslipidemia was defined as having a fasting plasma total-cholesterol or triglycerides level of ≥ 6.61 mmol/L (255 mg/dL) or > 1.7 mmol/L (150 mg/dL) respectively or having statins medication2 (meter), and categorized as high (BMI > 30 kg/m2), moderate (BMI between 25 and 30 kg/m2) and low (less than 25 kg/m2). Biological parameters were detailed in the UK Biobank protocol37. Education level was defined in three categories high (college or university degree), intermediate , and low (none of the aforementioned)38. Income level was defined as, high level , moderate level , and low level 39. Alcohol level consumption was defined as reported in questionnaire: high level , moderate level , and low level .Current tobacco smokers were defined as participants who responded “yes, on most or all days” at the question “do you smoke tobacco now”. CV diseases were defined by heart attack, angina and stroke, as diagnosed by a doctor and reported in questionnaires. Body mass index was calculated as weight (in kg) divided by height2 test was performed for categorical variables. Statistical analyses were stratified on gender since blood pressure differs between men and women40 and a difference in cannabis consumption between gender41.Characteristics of the study population were described as the means with standard deviation (SD) for continuous variables. Categorical variables were described as numbers and proportions. Comparisons between groups were performed using Student’s test for continuous variables. Pearson’s χFirstly, this study explored the association between cumulative lifetime cannabis use and BP levels, secondly, the current or past use of cannabis consumption with BP and then, the frequency of cannabis use during taking with BP.Associations between cannabis use and BP levels were examined with linear regression models computing regression coefficients (b) and their standard errors (SE). Firstly, gender models were adjusted for age. Secondly, gender models were adjusted for age, education, income level, alcohol consumption, tobacco habits, BMI categories, diabetes and dyslipidemia. “Never users” was considered as the referent group in the analyses. Subgroup analyses by education, income level, BMI, diabetes, dyslipidemia, alcohol and tobacco habits were performed. Interactions were examined by including simultaneously cannabis use status and one of the covariates, their interaction term and adjustment for all other covariates. Statistics were performed using SAS software . A p value < 0.05 was considered statistically significant.Written informed consent has been obtained from the patients.Men presented higher BP levels compared to women (SBP: 137 (15) mmHg for men vs. 124 (16) mmHg for women p < 0.001 and DBP: 84 (8) mmHg for men vs. 79 (8) mmHg for women, p < 0.001), higher proportion of heavy cannabis users , higher proportion of current cannabis users , higher proportion of current smokers , and higher proportion of high alcohol level .In comparison to never users, heavy users were younger, more likely current smokers and presented higher alcohol consumption, higher levels of income and education, but lower BMI levels in both genders Table . The canCompared to never users, heavy cannabis use was associated with lower SBP in men (b = − 1.25 (0.28), p < 0.001) in age-adjusted model. Adjustment for all covariates did not affect the negative association (b = − 1.09 (0.27), p < 0.001). Same results have been observed for DBP in men with a negative association in both models (after adjustment for covariates: b = − 0.50 (0.15), p < 0.001) and for PP in men (after adjustment for covariates: b = − 0.60 (0.20), p = 0.002 , p < 0.001) in age-adjusted model. Adjustment for all covariates did not affect the negative association (b = − 1.85 (0.36), p < 0.001). Same results have been observed for DBP in women with a negative association in both models (after adjustment for covariates: b = − 0.87 (0.17), p < 0.001) and for PP in women (after adjustment for covariates: b = − 0.97 (0.26), p < 0.001 , p = 0.005) in age-adjusted model. Adjustment for all covariates did not affect the negative association (b = − 0.63 (0.25), p = 0.012). In women, compared to never users, current cannabis use was associated with lower SBP (b = − 1.35 (0.31), p < 0.001) in age-adjusted model. Adjustment for all covariates did not affect the negative association (b = − 1.17 (0.31), p < 0.001). Same results were observed for DBP and PP  levels in both genders among the different groups of cannabis users , p < 0.001, with a gender interaction effect with cannabis use (p for interaction < 0.001). Same results were observed for DBP (b = − 0.68 (0.11), p < 0.001, with a p for interaction = 0.008 between gender and cannabis use), and for PP (b = − 0.74 (0.16), p < 0.001, with a p for interaction < 0.001). Same results were observed in overall study population for current cannabis use with SBP (b = − 0.73 (0.20), p < 0.001), with DBP (b = − 0.36 (0.10), p < 0.001) and with PP (b = − 0.37 (0.14), p = 0.009), with a p for interaction with gender, p < 0.001). This interaction between gender and cannabis use allows us to compare the BP effects of cannabis use between gender.To consider the possible effect of white coat hypertension, a sensitivity analysis was performed only on the second BP measure. Spearman correlation between first and second SBP measures was very high (measure one: 131 (18) mmHg, measure two: 129 (17) mmHg, ρ = 0.895, p < 0.001), as between first and second DBP measures (measure on 81 (9) mmHg, measure two: 81 (8) mmHg, ρ = 0.869, p < 0.001). The results remained consistent for both SBP, DBP and PP when only considering second BP measurement  levels in both genders but in a higher manner in women . It seems that a lifetime cannabis use was mainly associated with decrease in BP, as observed with smoking pack year43. A cumulative joint-years could be estimated by the equivalent of daily cannabis use for one year. At this effect, recent studies showed that the cumulative consumption of cannabis was not associate with decline in health compared to tobacco smoking22. Nevertheless, the cannabinoid system remains complex and it remains unclear if it can associated with worsening or improvement of metabolic health44.As observed in our study the potential impact of time effect of cannabis use (as number of times participants took cannabis), future studies could investigated the role of cannabis with BP through a cannabis joint-years. Pack-years, for tobacco, investigates the combination of information about smoking duration and intensity46. Nevertheless, the relationship between cannabis and BP remains unclear. Prospective studies have found that the increase in SBP observed for cannabis use could be mainly cofounded by a higher alcohol consumption in cannabis users47. In our study, we have shown an interaction between cannabis use and alcohol consumption among women, which could partly explain the higher decrease in SBP and DBP in women compared to men. In contrast, men presented an interaction between alcohol and cannabis for PP. PP is a marker of CV risk factors and arterial stiffness48. This relationship allows us to the possibility of cannabis use against arterial stiffness. Other recent studies have shown a better cardio-metabolic profile of cannabis users compared to non-users50, this could be added by the interaction observed in our study between dyslipidemia and cannabis use for SBP and DBP among men and for PP among women.Recent studies have suggested a strongly association between cannabis use and SBP than cannabis use and DBP51 while the other main phytocannainoid is the cannabidiol (CBD) which does not have psychoactive properties but interesting properties in several diseases52. CBD presented vasorelaxation actions in arteries53. Recent studies showed that CBD could reduce blood pressure17. This effect may be secondary to the anxiolytic properties of CBD. CBD was also responsible for endothelium-dependent vasorelaxation in mesenteric arteries. CBD could have a sympathoinhibition action leading to decrease BP17. Endocannabinoid system can activate CB1 receptor which increases cardiac contractile performance and reduces peripheral vascular resistance leading to lowered BP21. However, studies conducted in blood vessel vasomotion remain inconsistent. Even if THC may be associated with vasorelaxation, THC could enhance methoxamine-induced vasoconstriction25. These results may suggest that THC present different effects on vessels depending on central or peripheral properties of arteries. Nevertheless, the abrupt cessation of cannabis use was associated with increase in BP54.Cannabinoids (CBs) are compounds of the Cannabis sativa plant. There are over 80 types of phytocannabinoids. The THC (Delta-9-tetrahydrocannabinol) is responsible for the psychoactive properties of cannabis47. In our study, high levels of alcohol consumption and current tobacco smoking showed associations with BP in both genders. However, interactions between heavy cannabis use with alcohol consumption and tobacco were observed only in women but not in men (except for DBP in men). This showed that the effect of heavy cannabis use on BP was higher among current women smokers than among no current women smokers. However, the effect of heavy cannabis use on BP was higher among low women alcohol users than among high women alcohol users. Alcohol consumption was considered as a main confounding factor of cannabis use impact55. The use of both cannabis and alcohol was the most frequent combination observed worldwide among cannabis users47. However, pharmacokinetic interactions have not been yet explained in depth. Nevertheless, cannabis in association with alcohol is a common administration route. A recent study has shown that high alcohol consumption was associated with increased blood THC concentration55. Other studies provided limited pharmacokinetics information for cannabis and alcohol due to their controlled-administration experiments56. Nevertheless, the mode of administration could be important in the impact of BP levels. Alcohol before smoking cannabis should not affect THC blood levels57. However, blood THC level was lower over 4 h after smoking with alcohol than placebo57 but this effect did not consider the individual cannabis use history of participants.Prospective studies showed a possible cofounding action of alcohol consumption on the association between cannabis use and systolic BP10. Some evidence from animal models may suggest that gonadal hormones are implicated in the cannabinoid modulation of metabolism balance and can influence cannabinoid receptor density in a gender-dependent manner58. Sensitivity of cannabinoid receptors were differently modulated by estrogen and testosterone probably explaining the gender differences observed. However, for the similar time duration of consumption, a previous study have shown that women smoked fewer cigarettes of cannabis compared to men and received low concentrations levels of THC in blood due to different titrate of amount cannabis smoked in response to different cannabis potencies59. However, higher effect has been observed among women in our study, the endocannabinoid system could mainly affect this relation even if women may have lower titrate in cannabis smoked use.Gender difference effects of cannabis use have been observed in our study for BP levels with lower BP effect of heavy cannabis consumption in women compared to men. When considering all the study population, an interaction was observed between gender and cannabis use . Previous studies presented gender differences in frequency of cannabis use and cardiovascular response61. Moreover, the study investigation was focused on middle-aged UK participants, so our results could not be generalized to other age and ethnic populations. Nevertheless, the UK Biobank used standardized protocols to collect data, such as BP measurements. This standardization ensures replication of data collection for all participants regardless of when, where and by whom they are performed and adds external validity to our findings. Nevertheless, our study shows many limitations: socio-economic data, medical history and comorbidities were collected by self-reported questionnaires or by physician assertion during medical examination in health centers. Data of the UK Biobank were collected from 2006 to 2010. This could bias the generalization of the results to actual existing cannabis use patterns and risks. Cannabis use was self-reported by questionnaire and not by urine or blood testing. Nevertheless, the validity of self-reported cannabis use presented an overall congruence estimated at 89.8% compared to drug tests of urine specimens62. In our study, no data on the frequency of cannabis use around the 30 days prior to the interview was established and hence it is difficult to distinguish whether the interrelationship of cannabis use and BP is of a short term or of a chronic nature. Moreover, no data indicated current, recent or past use and should limit the results observed. No clear data were covered for THC estimation or CBD considerations. Moreover, no data were presented for smoking method, as vaping vs oral. These lack of information should be a major limitation in this study and should be investigated in further studies.The major strength of the study is the large sample size of the UK Biobank cohort. The cross-sectional design can limit the causality relationship, thus reverse causation can’t be ruled out. The UK Biobank study presented a low 5.5% rate of response leading to the involvement of possible participants bias. However, given the large sample size and high internal validity, these limitations may unlikely affect the observed associationsWe found a negative association between BP and cannabis use in both genders but with a higher manner in women. As observed for tobacco, it would be interested to develop a pack year cannabis smoking to clearly investigated the relationship between cannabis time effect consumption (as cannabis joint-years) and BP. Nevertheless, the small association in BP differences between heavy cannabis users and never users or between current cannabis users and never users remain too small to adopt cannabis-blood pressure policy in clinical practice. Longitudinal studies are needed in general populations and then, in hypertensive patients to highlight the potential lowered BP effect of cannabis in a medical use.Supplementary Tables.


Optimism bias refers to the tendency to display unjustified high/low expectations of future positive/negative events. This study asked 202 participants to estimate the likelihood of 96 different events. We investigated optimism biases for both oneself and the general population, and how these biases are influenced by gender, valence of the event, sociality of the event, as well as attachment anxiety and attachment avoidance. We found that sociality interacted with gender, with the difference in optimism bias for social vs. alone events being larger among women than among men. Attachment anxiety mainly reduced the optimism bias among men deliberating over future alone situations, while attachment avoidance primarily reduced optimism bias among female respondents deliberating over future social interactions. These results may have implications for the well-being and motivation of differently attached men and women and ultimately inspire psychotherapy interventions. Research has shown that most people are in fact overly optimistic about their personal future5, but one pending question is whether this optimism bias results from expecting more positive outcomes or less negative ones than would otherwise be warranted9. Most previous studies have predominantly focused on negative outcomes such as accidents and illnesses. In addition, the majority of studies comparing optimism for both positive and negative outcomes have not matched these outcomes on critical characteristics such as perceived frequency or controllability in the general population6, which can significantly influence the magnitude of optimism displayed10. Hence, to adequately investigate valence aspects in optimism bias, the current work controlled for influences of diverse critical characteristics.Optimism bias refers to the tendency to display unjustified high expectations of future positive outcomes and/or unjustified low expectations of future negative events13), where men and women have different perceptions of and attitudes toward risk . Other studies focused on a single positive event (“having a happy marriage”) and a single negative event (“getting divorced”), which were not matched on any characteristics apart from their complementarity18. These studies also revealed that men were more optimistically biased than were women—but only for the negative event. Yet, to draw firm conclusions about gender differences in optimism bias, a broader consideration of multiple positive vs. negative scenarios is strongly indicated. To our knowledge, no studies have investigated gender differences in optimistic expectations across a diverse range of both positive and negative situations.Another open question concerns gender differences in optimistic expectancies. Some studies found that men are more optimistic than women, but these findings relate to financial and economic contexts , and emotional intensity. Correspondingly, our construction of the events allowed for the determination of how respondents’ answers for themselves deviate from their own expectations for the general population: Do they display lowered expectancies for the negative events ; do they reveal heightened expectancies for the positive events; or are they characterized by both?21. Specifically, social interactions represent a meeting of two minds. Thus, when estimating future happenings, the individual not only takes the self into account but also other people. Moreover, because one has limited control over other people’s comprehension, reactions, and opinions, deliberating over social interactions  is inherently more complex. It remains, however, unanswered whether such varying complexity has an impact on the expected likelihood of future events. For example, do people show similar overoptimism when they anticipate enjoying a quiet afternoon by oneself and enjoying a vacation together with the significant other? How about having an argument with a relative and having a migraine? To answer this question, our positive and negative events contained an equal number of alone and social situations. To our knowledge, to date, no other study has taken the sociality of future outcomes into consideration when investigating optimism bias.Notably, the current investigation had a third and final aim, namely whether the sociality of future outcomes moderates the magnitude of the optimism bias. There is consensus that people evaluate themselves differently from other people and they also evaluate social interactions differently from single-person scenariostarget , valence (positive vs. negative situations), and gender . We expected that the respondents would rate positive and negative events in the general population as equally likely  but that, overall, they would expect more positive than negative events when thinking about their own future . We predicted that this optimism bias would be generated by both participants displaying lowered estimates for personal negative events and enhanced estimates for positive personal events . Lastly, we expected that men would display a stronger optimism bias than would women and that this effect would be driven mainly by men more strongly downsizing their personal likelihood of facing negative events  than women13 .We tested the first two research questions  separately from the third one . Because of a lack of direct precedent in the optimism literature which, to date, has ignored sociality aspects, we based our hypotheses about the sociality of future outcomes on attachment theory. Attachment theory posits that the habitual interactions with our caregivers during childhood continue into adulthood as cognitive and emotional schemas23 that influence how adults perceive themselves and others24. We therefore included attachment anxiety (ANX) and attachment avoidance (AVO) as additional continuous predictors of optimism bias. Notably, it appears important to investigate attachment  together with gender and in the context of event valence, as the literature on the topic indicates their interrelatedness27. It is necessary to consider the multiple interactions between those interrelated factors in the current study, because focusing on them individually and subsequently could easily lead to wrong intermittent conclusions.To assess the effect of sociality on optimism bias , we looked at the estimations that the respondents made for themselves  and kept the variables 28, human interactions are at the forefront of our minds (on account of an availability heuristic29). As a result, we expected that respondents would generally rate social situations as more frequent than alone situations , and that this effect would be more pronounced for women than for men . Moreover, we hypothesized that, because of higher personal relevance, respondents would manifest stronger optimism for social events than alone events  and that this difference would be more pronounced for women than for men .Because we all strive to achieve meaningful and mutually caring relationships with others32, with advantages for health and subjective well-being34, attachment styles in the form of cognitive and emotional schemas about self and others24 should moderate the effects of the valence of events on the likelihood estimates  depending on the sociality of events. AVO predisposes individuals toward chronic self-reliance, meaning more time engaged in alone situations than social situations38. This is fueled by a positive image of oneself and a negative image of others39. By contrast, ANX predisposes individuals toward clinging and co-dependent behaviors, as well as gravitation toward social interactions and away from alone situations40. This is fueled by a negative image of oneself and a positive image of others39. Considering this research, we anticipated that respondents high on AVO would rate social situations to be overall less frequent than alone situations , and that optimism bias would be smaller in social vs. alone scenarios . By contrast, we predicted that respondents high on ANX would expect alone situations to be overall less likely to occur than social situations , and that their optimism bias would be smaller for alone vs. social situations . Lastly, we made no predictions about gender differences in (a) attachment styles or (b) the moderating effects of attachment styles on the effects of sociality and valence, because previous research did not reveal consistent gender differences in ANX and AVO43.Although optimism bias is believed to be a basic human heuristicANX and AVO, respectively to determine potential gender differences. Male respondents  reported lower ANX scores than did female respondents  = 3.35, p < 0.001, Cohen’s d = 0.497). Similarly, male respondents  reported lower AVO scores than did female respondents  = 1.88, p < 0.001, Cohen’s d = 280). Both dimensions of ANX  and AVO  had a normal distribution of scores. Levene’s test showed that the variances for ANX  = 0.703, p = 0.403) and AVO  = 0.783, p = 0.377) were equal for male and female respondents. Finally, scores of ANX and AVO were equally positively correlated among female respondents (Pearson’s r (133) = 0.407, p < 0.001) and male respondents (Pearson’s r (69) = 0.302, p = 0.012; comparison male–female: z = 0.80, p = 0.42).Two independent t-tests (two-tailed) were performed on scores of target and valence  = 147.87, p < 0.001), revealing, as expected, that respondents rated positive and negative events as equally likely to occur in the general population (H1a: t (46.5) = 1.54, p = 0.131; Mpos = 57.8%, Mneg = 50.8%), whereas they rated themselves as more likely to encounter the positive situations than the negative ones (H1b: t (46.5) = 3.32, p = 0.002; Mpos = 67.5%, Mneg = 52.5%). Additionally, there was a significant three-way interaction effect between target, valence, and gender  = 7.03, p = 0.008; Fig. diff = 8.76%, t (48.2) = 1.92, p = 0.061; Mpos = 59.1%, Mneg = 50.3%) and female  = 1.14, p = 0.261; Mpos = 56.5%, Mneg = 51.4%) respondents. However, an optimism bias (i.e. the difference between estimates for positive events and negative events) was displayed by both male  = 3.30, p = 0.002; Mpos = 67.4%, Mneg = 52.3%) and female  = 3.31, p = 0.002; Mpos = 67.7%, Mneg = 52.7%) respondents when they evaluated their own likelihood of experiencing the events  = 9.48, p = 0.004). Post hoc independent group t tests based on aggregated data indicated that the optimism bias (positive–negative events) for self vs. general population was larger for women than men (t (200) = 2.20, p = 0.029), going in opposite direction of H2.The first linear mixed model  = 20.34, p < 0.001) and male  = 10.92, p < 0.001) participants. Both men  = 2.63, p = 0.009) and women  = 2.42, p = 0.016) were also characterized by heightened expectancies of experiencing negative events . However, these differences were overcompensated by the effect observed for positive events , so that the net result was a significant optimism bias present for both genders (see above for H2c and H2d).This optimism bias when evaluating oneself was driven exclusively by heightened expectancies regarding the chances of experiencing positive events compared to the general population and this pattern was present for both female  = 5.93, p = 0.019; Mpos = 62.7%, Mneg = 51.7%) and an interaction effect between valence and gender  = 7.59, p = 0.006; males: Mpos = 63.3%, Mneg = 51.3%; females: Mpos = 62.1%, Mneg = 52.0%), that were both driven exclusively by the ratings for the self, as seen in the interactions above. Lastly, there was no main effect of gender (F (200) = 0.07, p = 0.796) nor an interaction between target and gender  = 2.66, p = 0.103).Furthermore, there were a main effect of sociality  = 0.170, p = 0.682), suggesting that the alone (M = 59.0%) and the social events (M = 61.0%) did not differ concerning the respective overall likelihood participants assigned to them. The predicted interaction effect between sociality and gender was significant  = 7.100, p = 0.008; Fig. sociality and valence  = 0.017, p = 0.897), or between sociality, valence, and gender  = 0.403, p = 0.526) were not significant.The second linear mixed model  = 0.526, p = 0.469) was not significant either, suggesting that variations in AVO did not affect the overall differentiation of social vs. alone scenarios. However, AVO moderated the magnitude of optimism bias  = 12.07, p < 0.001), and this was further dependent on the gender of the participants  = 7.233, p = 0.007; Fig. ociality of the outcomes  = 4.852, p = 0.028). The simple effects revealed that optimism bias was present in all respondents, regardless of their levels of AVO, but that its magnitude decreased as scores of reported AVO increased  = 3.52, p < 0.001; Mean AVO: Mdiff = 14.5%, t (44.2) = 3.10, p = 0.003; Mean AVO + 1SD: Mdiff = 12.5%, t (45.8) = 2.64, p = 0.011). This decrease was sharper among female respondents  = 4.10, p < 0.001; Mean AVO: Mdiff = 15.8%, t (44.6) = 3.36, p = 0.002; Mean AVO + 1SD: Mdiff = 12.1%, t (46.2) = 2.56, p = 0.014) than male respondents  = 2.85, p = 0.006; Mean AVO: Mdiff = 13.3%, t (46.3) = 2.80, p = 0.007; Mean AVO + 1SD: Mdiff = 12.8%, t (51.2) = 2.64, p = 0.011), and also sharper for social outcomes  = 2.77, p = 0.008; Mean AVO: Mdiff = 15.1%, t (44.2) = 2.29, p = 0.027; Mean AVO + 1SD: Mdiff = 11.8%, t (45.8) = 1.76, p = 0.084) than for alone outcomes  = 2.20, p = 0.033; Mean AVO: Mdiff = 13.9%, t (44.2) = 2.10, p = 0.041; Mean AVO + 1SD: Mdiff = 13.2%, t (45.8) = 1.97, p = 0.055). The gender of respondents and the sociality of events did not have multiplicative effects on the moderation of AVO on optimism bias, as suggested by the lack of a significant four-way interaction AVO × sociality × valence × gender (F (1.9432) = 0.792, p = 0.373). Although at high levels of AVO (Mean + 1SD), there was no significant difference in the assessment of alone and social outcomes  = 1.09, p = 0.300), the pattern of a sharper decrease in optimism bias for social outcomes than alone outcomes is consistent with our hypothesis H8.The predicted interaction effect between 7; F 1,942 = 0.526sociality and ANX  = 0.487, p = 0.485) was not significant, suggesting that ANX did not affect the overall differentiation of social vs. alone scenarios. However, ANX moderated the magnitude of optimism bias  = 45.743, p < 0.001), and this was further dependent on the sociality of the outcomes  = 5.110, p = 0.02431), the gender of the participants  = 5.415, p = 0.020; Supplementary Fig. gender and the sociality  = 5.288, p = 0.021; Fig. ANX, its magnitude decreased as scores of reported ANX increased  = 3.93, p < 0.001; Mean ANX: Mdiff = 14.5%, t (44.2) = 3.10, p = 0.003; Mean ANX + 1SD: Mdiff = 10.6%, t (46.0) = 2.23, p = 0.030). This decrease was sharper among male respondents  = 3.89, p < 0.001; Mean ANX: Mdiff = 13.28%, t (46.3) = 2.80, p = 0.007; Mean ANX + 1SD: Mdiff = 7.95%, t (52.3) = 1.63, p = 0.109) than female respondents  = 3.87, p < 0.001; Mean ANX: Mdiff = 15.78%, t (44.6) = 3.36, p = 0.002; Mean ANX + 1SD: Mdiff = 13.18%, t (46.0) = 2.79, p = 0.008), and also sharper for alone outcomes  = 2.89, p = 0.006; Mean ANX: Mdiff = 13.92%, t (44.2) = 2.10, p = 0.041; Mean ANX + 1SD: Mdiff = 8.63%, t (46.0) = 1.29, p = 0.203) than social outcomes  = 2.67, p = 0.010; Mean ANX: Mdiff = 15.14%, t (44.2) = 2.29, p = 0.027; Mean ANX + 1SD: Mdiff = 12.50%, t (46.0) = 1.87, p = 0.068). Additionally, sociality and gender had a multiplicative effect on the moderating effect of ANX on optimism bias. Specifically, optimism bias decreased as a function of increasing scores of ANX and this decrease was the sharpest for male respondents in alone situations  = 3.15, p = 0.003; Mean ANX: Mdiff = 15.53%, t (44.0) = 2.15, p = 0.023; Mean ANX + 1SD: Mdiff = 7.98%, t (47.0) = 1.09, p = 0.282). Although at high levels of ANX (Mean + 1SD), there were no significant differences in the assessment of alone and social outcomes  = 0.19, p = 0.664), the pattern of a sharper decrease in optimism bias for alone outcomes than social outcomes is consistent with our hypothesis H10.Similarly, the predicted interaction effect between H9; F 1,932 = 0.48Our study had three aims: (1) To reveal whether optimism bias stems from heightened expectations of self-relevant positive future outcomes and/or lowered expectations of self-relevant negative future outcomes , (2) to determine whether there are gender differences in the magnitude of optimism (gender question), and (3) whether the sociality of future outcomes  plays a role in optimism bias .44). Other studies used two unique sets of negative and positive events, but they did not match them on potentially confounding characteristics such as controllability or frequency48. A more in-depth comparison of optimism bias toward positive vs. negative outcomes should be based on events that are matched on as many potentially confounding characteristics as possible10. In our study, therefore, we chose a balanced set of positive and negative events that had been matched on multiple characteristics: perceived frequency in the general population, controllability, emotional intensity, and valence . We then asked participants to rate their own likelihood as well as that of the general population to experience a series of positive and negative events.Our first aim has not been entirely satisfactorily addressed by the previous literature in the field. For example, some studies chose negative events for which epidemiological data or national statistics exist  and constructed positive events as their complement . Moreover, our study suggests that direction and strength of gender differences are shaped by the nature of the events investigated as well as attachment characteristics. This was true for both model 1, where gender interacted with the target  and valence (H2), as well as for model 2, where there were also numerous three- and four-way interactions involving gender with sociality , valence, and attachment measures (see next paragraph for specifications). Our study therefore suggests that it very much matters how studies assess optimism bias and what other factors are included when it comes to gender differences.For our second research question, we explored potential gender differences in the magnitude of optimism bias. Previously, studies have suggested that men might be more optimistic than womenThird, we wanted to determine whether the magnitude of optimism bias is moderated by the sociality of the target event. For example, do people equally deliberate the chance of having food poisoning and the chance of having an argument with a relative? Our results suggest that respondents overall manifest a similarly sized optimism bias regardless of whether the future event concerns the respondent alone or an interaction with someone else. However, attachment styles moderated this relationship. Increasing scores of attachment insecurity  decreased the magnitude of optimism bias both independently from the gender of respondents and the sociality of the outcomes as well as synergistically with them. High scores on attachment avoidance and attachment anxiety acted in complementary patterns and in line with our hypotheses . Moreover, this was further stratified by gender effects. Specifically, high avoidance decreased the magnitude of optimism bias significantly more for social than alone outcomes and more among female than male respondents. By contrast, high scores of attachment anxiety decreased optimism bias more strongly for alone than social outcomes and more among male than female respondents. Interestingly, in contrast to attachment avoidance, attachment anxiety also had multiplicative effects with the gender of the participants and the sociality of the outcomes: of all our gender-sociality combinations, high scores of attachment anxiety decreased optimism bias the most among male respondents in alone outcomes.38, on account of a positive image of themselves and a negative image of others39. Such a working model of self-others is expected to eliminate an otherwise normal optimism bias for social interactions. By contrast, anxiously attached individuals exhibit clinging and co-dependent behaviors and they gravitate toward social interactions and away from alone situations40, on account of a negative image of themselves and a positive image of others39. This predisposes anxious individuals to a lack of optimism bias for alone situations.The effects of the sociality of outcomes and attachment insecurity on optimism bias are in line with our hypotheses and with the past literature. Individuals with an avoidant attachment style are predisposed toward chronic self-reliance and engage more in alone versus social situations6), which, in turn, is predictive of lower subjective well-being55 and is a risk factor for depression56. Future studies in positive and clinical psychology should remain aware of these gender-attachment insecurity interactions, which may affect some of the findings. Specifically, it might be worthwhile to identify potential attachment insecurities in order to develop individually tailored interventions that focus on strengthening resources in the most critical conditions. Whereas it may be indicated to target optimism in alone situations for male patients with high attachment anxiety, treatment of women with high attachment avoidance may best benefit from a consideration of optimistic expectancies in social situations. Before drawing firm conclusions on these points, however, our results clearly need to be replicated and further explored in subsequent studies.Interestingly, attachment insecurity interacted with the gender of respondents to moderate optimism bias in our study. We are not aware of other studies reporting interactions between gender and attachment dimensions to predict any psychological construct. Our study suggests that anxious males and avoidant females are particularly at risk for an absent optimism bias .Our research may be criticized on several accounts. First, our participant sample of young (18–30 years old) full time-students cannot be considered as representing the general population. The current findings hence need to interpreted against this backdrop and replicated with a more diverse  sample. Second, we acknowledge that there might be several interesting effects that our research was unable to uncover. To keep statistical complexity and interpretability of the data at an acceptable level, we decided against including the variable In sum, our study sheds light on the complexity of human social behavior and its associated biases and shows that men and women can be affected differently depending on their kind of attachment insecurity and the nature of the situation under investigation.valence: positive and negative; sociality: alone and social; target: self and general population) and one between-subject factor . Additionally, attachment anxiety (ANX) and attachment avoidance (AVO), measured with the short version of the Attachment Style Questionnaire (ASQ57), were used as continuous predictors. The ASQ-short form consists of 29 items (16 items measuring AVO and 13 items measuring ANX). Responses are given on a 6-point scale . The questionnaire’s two factor structure has been investigated in relation to other attachment questionnaires and successfully validated. Reported internal reliability and retest reliability both amount to α > 0.8658. In the current study, Cronbach’s α for the attachment anxiety subscale was 0.87, and the one for the attachment avoidance subscale was 0.78.The design was mixed, with three within-subject factors pertaining to the scenarios , placing particular emphasis on the underrepresented quadrants . These scenarios were brainstormed with two constraints in mind. First, they must reflect everyday situations that most people encounter without ‘favoring’ any particular social group. This was paramount to ensure that all participants could rightfully imagine themselves in those situations. Second, the situations had to reflect both rare and frequent events closer to the mean rather than extremely rare or extremely frequent situations, because the latter have raised concerns that they might artificially increase the magnitude of the optimism bias46.Our stimuli consisted of 48 scenarios  that were balanced on (a) extent of deviation from theoretical midpoint in the direction of alone vs. social, (b) valence deviation from neutral, (c) frequency in the general population, (d) controllability, and (e) emotional intensity. To achieve this balancing, an initial pilot study was run. In a first step, we brainstormed social and alone events. A starting place were the 32 events used in6. We then collected data on five perceived event characteristics  valence, emotional intensity, and personal experience with the event under investigation) among one hundred and nineteen respondents from Germany (n = 95), Austria (n = 20) and Switzerland (n = 5), who were recruited on www.prolific.co . Next, we determined the average scores for each of the five event characteristics separately for each of the one hundred and seventy-seven events. We removed fifty-seven events whose 95% confidence interval included the value “50”  on any scale, ending up with 120 events. Subsequently, we agreed on the final pool of 48 scenarios by using a jackknife technique. This technique is a simple and popular resampling method that allows estimation of bias and variance in a sample and can then appropriately reduce the bias within the sample60. We added events in the analysis while excluding others until the events were perfectly balanced on the five event characteristics. The complete battery of stimuli used is presented in the Supplementary Table Following these efforts and constraints, we generated one hundred and seventy-seven events, including the original events in Dricu et al.Subsequent to data acquisition, we performed manipulation checks for all 48 events using a 2  × 2  design. We found that all events were rated as expected: Negatively valenced events all had a negative mean valence, and positively valenced events all had a positive mean valence, while perceived sociality was consistently higher for social scenarios than for alone scenarios. Importantly, there was no overlap between the stimuli belonging to the resulting four different categories (M [SD] of the different categories: (a) social-negative: valence = − 25.7 [9.9], sociality = 75.6 [4.2]; (b) alone-negative: valence = − 27.6 [12.6], sociality = 39.9 [8.1]); (c) social-positive: valence = 24.9 [9.0], sociality = 76.7 [4.4]; (d) alone-positive: valence = 24.6 [9.0], sociality = 35.7 [10.2]; see Fig. 62, we chose a sample size of 200 participants, which is double than the most conservative recommendation63. For our study, participants were recruited via the Department of Psychology’s SONA system of a Swiss university (for reasons of convenience) and were given 2 ECTS credits in exchange for their participation. Inclusion criteria were: 18–30 years old, full-time students, German as mother tongue or proficiency. Self-reported mental illness served as an exclusion criterion. Data collection was conducted exclusively online and ended after 202 respondents had been enrolled .Although there is no gold standard for determining a minimum sample size when designing linear mixed modelsQualtrics Software  was used to design the online survey and collect the data. All participants received explanations regarding the alleged nature of the study. The study’s experimental protocols along with the written informed consent had been previously approved by the ethics committee of the Institute of Psychology at the University of Bern  and are in accordance with the Declaration of Helsinki. The communicated purpose of the study was the ability to foresee social situations. After signing the informed consent form, the participants could proceed with the online experiment. The experimental task required participants to give likelihood estimates for experiencing the 48 events in a fully randomized fashion and started with a familiarization period, which included three examples. Each trial/scenario was displayed for 10 s and showed a single still animation of a male or female silhouette (whose gender was congruent with the participant’s gender) in the middle upper part of the screen, above a one-sentence description of the target situation. Participants had been instructed before the start of the experiment that they should state their subjective likelihood of occurrence for each situation displayed. Each scenario was presented twice, once in a personal and once in in a general population condition (wherefore each participant saw 96 scenarios). In the personal condition, participants rated the likelihood for themselves experiencing the described scenario in the future. In the general population condition, they provided an average regarding all persons constituting the general population . At the bottom of the screen there was a visual analogue scale (VAS) with which the participants selected a percentage from 0% (left side) to 100% (right side). The VAS always started with the slider on the middle position (50%). Participants had ten seconds to decide: if the time window passed and the slider of the VAS had not been moved, a reminder was shown on the top of the screen that one cannot proceed to the next trial until a decision is made.https://www.jamovi.org). To answer the first two research questions (H1 and H2), i.e., the valence and gender questions, we ran a linear mixed model with gender as between-subjects factor and target  and valence of scenarios (positive and negative) as within-subjects factors. To investigate the effects of sociality and attachment anxiety and avoidance on optimism bias , we ran a separate linear mixed model with gender as between-subjects factor and the following within-subjects factors: sociality  and valence of scenarios (positive and negative). ANX and AVO (both continuous predictors) were between-subjects variables as well. We used the simple effects as implemented in jamovi to investigate individual condition differences for sociality, valence, target, and gender. Significant interactions for attachment were post hoc assessed using the estimated marginal means as implemented in jamovi. For all figures and to elucidate interaction effects where the prior simple effects testing did not elucidate the origin, we aggregated data across scenarios for each participant. Subsequently, gender differences were specified using t tests.We used linear mixed modeling as implemented in the GAMLj module in jamovi (The jamovi project (2020). jamovi. (Version 1.6.16) [Computer Software]. Retrieved from We performed 1000 Monte Carlo style simulations using a custom-build script in MATLAB R2017  that simulated each trial for each participant prior to running the same analyses as in the current paper. See “Supplementary Materials S1” for further information on this power analysis.Supplementary Information.


The aim of this study was to evaluate the influence of the body mass index (BMI) on laboratory, clinical outcomes and treatment costs of assisted reproduction, as there are still controversial and inconclusive studies on this subject.2): Group 1 < 25; Group 2, 25–29.9 and Group 3, ≥ 30. A total of 1753 in vitro fertilization (IVF) fresh embryo transfer (ET) cycles were included for assisted reproduction outcomes analysis and 1869 IVF-ET plus frozen embryo transfer (FET) for cumulative pregnancy analysis.This research was retrospective cohort study, including women undergoing assisted reproduction in a Reproductive Medicine Center between 2013 and 2020. The participants were divided into groups according to BMI (kg/mp = 0.002) and gonadotropin’s total dose (IU) and treatment costs  vs. G2  vs. G3 , p = 0.001). A greater number of mature oocytes was observed in G1 and G2 , which was not found in oocyte maturity rate (p = 0.877). A significant linear tendency (p = 0.042) was found in cumulative pregnancy rates, pointing to worse clinical outcomes in overweight and obese patients.As higher the BMI, higher was the proportion of canceled IVF cycles (G1 (6.9%) vs. G2 (7.8%) vs. G3 (10.4%), These findings highlight the importance of considering the higher treatment costs for these patients, beyond all the well-known risks regarding weight excess, fertility, and pregnancy, before starting IVF treatments. Obesity and infertility are in growing prevalence in the world, being considered as concerning public health conditions –4. Also,In assisted reproduction, the needs for higher doses of gonadotropins during ovarian controlled stimulation is well established for obese patients in the literature, with a direct association between these group of patients and in vitro fertilization (IVF) canceled cycles –8.Despite the expected effect of obesity in oocyte quality, studies on laboratory outcomes after assisted reproduction techniques (ART) remains controversial. Some studies found significantly lower numbers of mature oocytes retrieved and fertilization rates, which is a known oocyte quality marker, while others have not found differences .Also, it is still not clear whether the weight effect in women’s fertility is translated into worse clinical outcomes after embryo transfer (ET), with most of the studies analyzing frozen ET cycles (FET) in association with IVF-ET cycles. Only a few studies considered the possibility of bias since FET cycles are associated with better outcomes when compared to fresh cycles –13.Therefore, assisted reproduction treatment costs are expected to be higher in overweight and obese women; however, this is also still inconclusive in the literature, with some studies having found association while others have not –16.Thus, the aim of this study was to analyze whether the laboratory and clinical outcomes of assisted reproduction are influenced by the BMI’s categories, considering also the treatment costs. The main hypothesis was there is a negative effect from BMI on these outcomes.The present study performed a retrospective cohort study in a reproductive medicine center in the south of Brazil, which receives patients from the country’s south and southeast as it is considered one of the major region’s reproductive centers, performing about one thousand cycles per year. All data were collected from electronic records from 2013 to 2020.This manuscript was structured following STROBE  .Women undergoing follicle stimulation cycles at the reproductive medicine center which had weight and height registered in electronic records. The population included were mostly Caucasian women with complete high school education and considered to be in a social economical class capable of affording the high costs related to assisted reproduction in Brazil. Some of these patients performed more than one ART cycle and each one was considered as a new patient for statistical analysis and that’s why this study’s population is based on ART cycles and not patients.Women with previous chemotherapy or radiotherapy and with previous oophorectomy were excluded from the present study’s analysis. Also, patients older than 40 years old were not considered, as well as patients whose embryos were biopsied before implantation to avoid bias in the analysis of clinical outcomes.2, Group 2: BMI 25–29.9 kg/m2, Group 3: BMI > 30 kg/m2), as shown in Fig. Each analysis was made by dividing samples into three groups according to the BMI, in line with WHO classification   were compared between groups. For this analysis, it was taken into consideration individual ovarian stimulation protocol adjusted by infertility causes and it was also analyzed the canceled cycles rate. For ovarian response analysis, the IVF canceled cycles were excluded since patients have not completed it, resulting in 1835 IVF cycles.In the second step, ART clinical outcomes were analyzed, when fresh embryo transfer (ET) cycles were performed, totaling 1753 IVF-ET cycles.FET cycles were included into second step analysis only for cumulative pregnancy rate calculation, resulting in 1869 ET cycles (IVF-ET fresh cycles plus FET-ET cycles).It was also performed an analysis to evaluate the impact of female obesity on ART costs. Evaluating the average gonadotropin costs in Brazil, each IU of menotropin (hMG) is U$ 0.32, and the average recombinant FSH (FSHr) and FSHr + LHr costs per IU are U$ 0.44. Then, the average value of these three gonadotropins is U$ 0.40/IU.All laboratory definitions followed Vienna Consensus . BiochemThe controlled ovarian stimulation was performed with gonadotropin-releasing hormone (GnRH) agonist or antagonist protocols and gonadotropins (75–300 IU/daily) adjusted according to each patient’s response and selected considering individual clinical indications. The gonadotropin choice was made among corifollitropin alfa, recombinant follicle-stimulating hormone (FSHr), human urinary gonadotropin (hMG), combination of recombinant FSH and luteinizing hormone (LHr) and eventually an association was indicated. The trigger was performed by recombinant hCG 250 mcg or 0,2 mg triptorelin (GnRH agonist) 34–36 hours before ultrasonography-guided oocyte retrieval, according to each patient’s indications, when three or more follicles reached 17 mm, or one follicle achieved 20 mm. The oocyte retrieval was performed, and the oocyte maturity was analyzed. Intracytoplasmic Sperm Injection (ICSI) was the technique used in the embryo laboratory for all fertilization. The embryos were transferred on days 2–6 of development. The luteal phase was supported using 600–800 mg of intravaginal micronized progesterone per day.The spare embryos (not transferred) were vitrified and, depending on the clinical outcome, were transferred at appropriate time. The frozen technique followed a unique laboratory vitrification protocol. For FET-ET the endometrial preparation was made with oral or transdermal oestrogen.For pregnancy diagnosis, serum beta-hCG was collected after 10–12 days of ET, and an obstetric ultrasound was performed after 2 weeks of hCG result. After clinical pregnancy confirmation, patients were referred to prenatal care with their chosen obstetrician.p < 0.05.Social Package for Social Sciences (SPSS) for Windows, version 22.0  was used for statistical analysis. Data were expressed as median with interquartile range (IR) when not normally distributed. When normally distributed, it was expressed as mean ± standard deviation (SD) or frequency (%) when appropriated. Continuous variables were compared using ANOVA, categorical variables with the Chi-square test and nonparametric with U Mann-Whitney or Kruskal-Wallis tests when appropriated. Multiple logistic regression and post-hoc curve analysis were performed on groups comparison. To consider patients and the number of cycles for these analyses, generalized estimating equations (GEE) was performed. Statistical significance was defined as o protocol 4.085.223; CAAE 78763917.5.0000.5336) approved this study and waived the informed consent term for participants. All authors signed a data compromise and confidentiality responsibility term before collecting data. Declaration of Helsinki guidelines and regulations were considered for all methodology performed.Research Ethics Committee of Pontifical Catholic University of Rio Grande do Sul (n2) was 23.6 ± 3.7 in the whole sample. When comparing groups 1, 2 and 3, respectively, the following results regarding maternal age and BMI were found: 35.5 ± 3.6 vs. 35.9 ± 3.6 vs. 35.0 ± 4.3 (p = 0.040) and 21.7 ± 1.7 vs. 26.8 ± 1.3 vs. 32.9 ± 2.3 (p < 0.05). Other baseline characteristics, such as paternal age and infertility diagnosis, are presented in Table p = 0.001).The mean maternal age was 35.5 ± 3.6 years old (yo) and the mean BMI (kg/mp = 0.017), while recombinant FSH (FSHr) and corifollitropin alfa (CFA), analyzed separately, were more frequent in group 1 . No differences were found regarding GnRH protocol chosen or triggering. Gonadotropin’s total doses (IU) when comparing groups 1, 2 and 3 were, respectively: 1685 ± 595 vs. 1779 ± 610 vs. 1805 ± 563 (p = 0.001). Significant higher gonadotropin doses were necessary for groups 2 and 3 responses, with no significant difference between both, as shown in Fig. Regarding controlled ovarian stimulation, the laboratory outcomes compared between groups are presented in Table p = 0.014) and retrieved mature oocytes  in group 3. An analysis grouping groups 2 and 3 is also shown, with a significantly higher number of total retrieved oocytes  found in group 1.The ovarian stimulation response analysis is presented in Table p = 0.042).Regarding other laboratory and clinical outcomes after ART analysis Table , fertilip = 0.001), even considering that group 1 presented the largest sample. When comparing groups 1, 2 and 3, the cancellation cycles’ rate was found to be, respectively: 6.9% vs. 7.8% vs. 10.4% (p = 0.002). When cycles were not canceled, gonadotropins total dose performed was lower in group 1  and, hence, lower treatment costs were associated .The treatment costs’ analysis and cancellation cycles’ rate are shown in Table All data analysis performed in this study for each variable of interest did not consider cycles with missing data information from medical records.According to this study’s hypothesis, and considering the proposed objective, the results found suggest that overweight and obesity does have a negative impact on laboratory and clinical ART outcomes.The mean maternal age was clinically similar between groups, but a significant difference was found, probably regarding the unequal sample size. As shown in Table Regarding ovarian controlled stimulation, the study’s findings on gonadotropins’ doses Table  have agrFurthermore, it is possible that the higher proportion of canceled IVF cycles, more frequently found in overweight and obesity patients, was related to the same poor ovarian response that required higher gonadotropins doses. This need of increased doses requires, hence, higher treatment costs and the probability of more than one cycle for achieving pregnancy, which could be the reason why more overweight and obese women discontinued cycles initiated. Kawwas et al.  analyzedThe low number of retrieved and mature oocytes found in overweight and obese patients, as demonstrated in Table Even with higher gonadotropin doses performed in overweight and obese patients for achieving better ovarian response, this was not translated into better total number of retrieved oocytes and mature. However, the significant difference was not maintained for oocyte maturity rate, with low but not statistically different in the obese group.The canceled IVF cycles found in our study seems to be, thus, related to worsen controlled ovarian stimulation found in overweight and obese women. Those obese patients who did not discontinue cycles and had the oocyte retrieval performed were probably women with a similar hormonal profile than eutrophic, despite BMI. This could be the explanation for the lack of significant difference found in oocyte maturity rate.Regarding clinical outcomes, the laboratory outcomes’ results were not translated into fertilization rates differences, as shown in Table Biochemical and clinical pregnancy rates tended to be higher when a blastocyst ET was performed in eutrophic, overweight and obese women  measure was demonstrated by Christofolini et al.  to be a Furthermore, the limited sample size in this study was an important limitation to statistical power analysis, leading to some non-significant results found to be still considered as clinically relevant for patients in reproductive treatment. Studies considering more cycles could achieve 80% power and find statistical significant differences.As a retrospective study, limitations regarding data collection were considered. Analysis of other ovarian function markers, such as FSH, LH and AMH, were not included due to lack of information on medical records. More studies including this marker could bring better conclusions.In conclusion, overweight and obesity are associated with worse clinical outcomes in assisted reproduction, with worse ovarian response even using higher gonadotropin doses for stimulus and lower chances of implantation and clinical pregnancy rates.These findings also highlight the importance of considering the higher treatment costs for overweight and obese patients, beyond all the well-known risks regarding weight excess, fertility, and pregnancy, before starting assisted reproduction treatments.It is important to reinforce that, regardless of assisted reproduction, as obese pregnant women are at well-established increased risk for maternal, perinatal, and fetal complications, the benefit of pre conceptional maternal weight loss should be widely recommended for a benefit before and during pregnancy.