The present umbrella review evaluated risk factors prior to conception associated with placental abruption based on meta-analyses and systematic reviews.I2, 95% prediction interval, small-study effects, excess significance biases, and sensitive analysis. The quality of the meta-analyses was evaluated with A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2).We searched PubMed, Scopus, and Web of Science until June 25, 2021. All meta-analyses that had focused on assessing the risk factors associated with placental abruption were included. We calculated summary effect estimates, 95% CI, heterogeneity There was no risk factor in the present umbrella review with the high level of evidence (class I or II). Eight risk factors including maternal asthma , prior cesarean section , cocaine using , endometriosis , chronic hypertension , advanced maternal age , maternal smoking  , and use of assisted reproductive techniques (ART)  were graded as suggestive evidence (class III). The other four risk factors including pre-pregnancy underweight , preeclampsia , uterine leiomyoma , and marijuana use  were graded as risk factors with weak evidence (class IV).Maternal asthma, prior cesarean section, cocaine use, endometriosis, chronic hypertension, advanced maternal age, maternal smoking, and use of ART, pre-pregnancy underweight, preeclampsia, uterine leiomyoma, and marijuana use were risk factors associated with placental abruption. Although factors associated with placental abruption have been investigated, the current meta-analytic associations cannot disentangle the complex etiology of placental abruption mainly due to their low quality of evidence.The online version contains supplementary material available at 10.1186/s13643-022-01915-6. The complete or partial separation of site implanted placental before delivery is defined as placental abruption . It happTo our knowledge, no umbrella reviews have been conducted to assess risk factors associated with placental abruption on meta-analyses and systematic reviews. Therefore, the present umbrella review evaluated risk factors prior to conception associated with placental abruption based on meta-analyses and systematic reviews.In this manuscript, we used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for conducting the umbrella review and reporting the findings . Also, wThe identified articles through systematic database searching along with the additional articles identified through forward and backward searching were screened for eligible articles, firstly at title-screening level, then at the abstract level, and finally at full-text-level, independently, by EJ and AS. Disagreements were resolved by SB.We looked for all systematic reviews and meta-analyses that were performed focusing on environmental risk factors prior to conception associated with mothers for placental abruption. The systematic reviews were included if they considered observational studies  and included meta-analyses, with no language or date restrictions. Partial or complete placental abruption needs to be clinically diagnosed. Both journal papers and conference full papers were included.Systematic reviews were excluded if they did not identify environmental risk factor(s) prior to conception for placental abruption. Also, if the information needed to reanalyze the meta-analyses was not included or could not be retrieved, the review was excluded. Animal studies and genetic studies were excluded. Conference abstracts were also excluded. In case there were multiple reviews considering the same risk factor(s), the one that included the largest number of studies was selected. The excluded papers, with reasons to exclude, are listed in supplementary table PubMed, Scopus, and Web of Science databases were searched from inception to June 25, 2021, with no restrictions on language or date of publication. These databases were searched for systematic reviews and meta-analyses that had focused on risk factors associated with placental abruption. The search strategy and the search terms used for Scopus and PubMed are included in supplementary We used Endnote software to manage the search results. Two authors (EJ and AS) independently searched the databases to identify eligible articles. Then, the reference of the identified articles was manually searched for potential related systematic reviews not identified by the search engines (backward searching). Also, the authors of the identified articles were contacted for their potential works that are missed or not published yet (forward-searching).p-values, study design, participant demographics, baseline characteristics, and finally, metrics used in their own included articles , and all the necessary information needed for re-analysis such as the contingency table. If this information was not included in the meta-analysis, the original articles used in that meta-analysis were retrieved or their authors were contacted. Data storage was on Microsoft Excel spreadsheets.EJ extracted the information and EA checked the extracted data. Disagreement between them was resolved by SB. The included reviews were assessed and the below information was extracted: first author, publication year, risk factor(s), heterogeneity, effect size, sample size, study estimates, EJ and AS independently determined the quality of the identified papers using AMSTAR2 . DisagreEach of the above items was scored as yes, partial yes, or no, and items 2, 4, 7, 9, 11, 13, and 15 are rated as critical, with a higher weight in scoring. The overall score was used to rate the quality of the meta-analyses as high, moderate, low, or critically low.p-value, and sample size from the original papers. Where this information was not provided, the authors of the original papers were contacted for this information. If the information needed could not be retrieved, the original papers were excluded from the re-analyses.ZS performed the statistical analyses using R Version 4.0.5. R packages that were used included Metafor, xlsx, epiR, ConfoundedMeta, and reporter. All statistical tests were two-tailed. The included meta-analyses were re-analyzed by extracting the metrics such as contingency table, p-values were found. Statistical significance was ascertained at p < 0.05. We used Cochrane’s Q test to calculate I2 which is a measure that determines the heterogeneity between studies so that a high heterogeneity is indicated by I2 > 50%. Also, we found the 95% prediction interval, which is the interval that future mean effect estimates will lie in 95% of the time. Additionally, the Egger regression asymmetry test was used to determine if there exists a small study effect in the original studies. The small study effect deals with the phenomenon that smaller studies typically report larger effect sizes. Furthermore, an excess significance bias test was applied for statistically significant original studies to see if their reported significant results are more than their expected number of significant results, based on the power of their studies (p < 0.05).We used the random-effect model to re-analyze the included meta-analyses and found odds ratio, relative risk, or hazard ratio, based on the effect estimate used for each meta-analysis, and summary effect size, 95% confidence interval, and Sensitivity analysis was done for all meta-analyses using Mathur’s method . This mep-value of the random-effect model< 10−6, # cases > 1000, no sign of excess significant bias or small study effect, prediction interval not including the null value, robustness to unmeasured confounding, significant result (p < 0.05) for the largest study, and I2 < 50%Convincing (class I): p-value of the random-effect model< 10−6, # cases > 1000 , and significant result (p < 0.05) for the largest studyHighly suggestive (class II): Similar to the previously-published umbrella reviews , 16, thep-value of the random-effect model < 10−3 and # cases > 1000Suggestive (class III): p-value of the random-effect model < 0.05Weak (class IV): evidence was assigned to the remaining significant association with a p-value of the random-effect model > 0.05(Class V): In the present umbrella review, 572 studies until June 25, 2021, were identified. In total, 12 studies that were eligible for inclusion in the present umbrella review .p < 0.001), 12 studies included at least 1000 placental abruption cases, eight studies reported heterogeneity (I2) less than 50%, two studies had small study effects, and six had excess significance bias  were not statistically confirmed as a risk factor.The other four factors  were relatively robust to unmeasured confounding, considering a bias factor of more than 1.9 for each of their included studies was needed to reduce the proportion of studies with a true odds ratio greater than 1.1 to less than 10%  . Eight risk factors including maternal asthma , prior cesarean section , cocaine using , endometriosis , chronic hypertension , advanced maternal age , maternal smoking  , and use of ART  were graded as suggestive evidence (class III).The other four risk factors including pre-pregnancy underweight , preeclampsia , uterine leiomyoma , and Marijuana use  were graded as risk factors with weak evidence (class IV). Fetal sex  was not confirmed as a risk factor for placental abruption (not significant). Pre-pregnancy overweight  and obese  were protective factors for placental abruption graded in class IV and class III, respectively  credibility and underweight, overweight, preeclampsia, uterine leiomyoma, and marijuana use with weak (class IV) credibility.There were no meta-analyses with a high level of credibility, including convincing (class I) and highly suggestive (class II). It means that further large cohort studies with homogeneous study groups and with a consistent and reliable definition of risk factors and placental abruption are needed. Moreover, studies included in each meta-analysis on risk factors of placental abruption should involve both studies with statistically significant and non-significant results for precluding potential excess significance bias .The mechanisms involved in the association of placental abruption and risk factors are not well understood. Previous studies suggest that subfertility plays a role in abnormal placentation in singleton pregnancies. Therefore, the use of ART pregnancy can be associated with placental abruption . SmokingAssociation between maternal smoking during pregnancy and placental abruption was studied more than other risk factors so that in the study by Shobeiri et al. , 27 studT = 3.19 and G = 5.85). Because marijuana was positively associated with placental abruption (pooled OR = 1.78), it seems combinations of cocaine and marijuana have a synergistic effect on placental abruption. It is not an unexpected fact that a woman during pregnancy experiences multiple substances such as illicit drugs, cocaine, and marijuana [This study found a fourfold increased risk of placental abruption among those who use cocaine versus those who do not use it. According to AMSTAR, overall confidence in the results was low, and it can be inferred that the degree of selection bias, information bias, and/or confounding did not control or adjust among individual studies that address the association between cocaine use and placental abruption. In other words, the cocaine can be measured using different methods, e.g., urine analysis, maternal interview, chart review, or it may be cocaine alone and polydrug including cocaine . The difarijuana . One of arijuana . FurtherAfter cocaine use, chronic hypertension had the strongest effect on placental abruption (pooled OR = 3.13). In the meta-analysis by Ananth et al. , women wAlthough a dose-response pattern was found between maternal pre-pregnancy BMI and placental abruption, underweight as a risk factor and overweight and obesity as protective factors, respectively ; howeverAlthough this study was the first umbrella review to summarize evidence about the etiology of placental abruption, several issues should be considered when interpreting the results. A valid inference about the association can be obtained by considering more databases and grey literature. Definition and ascertainment of the variables of interest should be clearly and homogenous across all individual studies. Stratification of evidence may be along with the degree of error because, for example, risk factors, e.g., uterine leiomyoma, may have a notable effect on placental abruption (OR = 2.63). However, it may be evaluated in a few studies (9 studies), leading to stratified as class IV evidence.Eight risk factors including maternal asthma, prior cesarean section, cocaine use, endometriosis, chronic hypertension, advanced maternal age, maternal smoking, and use of ART were graded as suggestive evidence (class III). The other four risk factors including pre-pregnancy underweight, preeclampsia, uterine leiomyoma, and marijuana use were graded as risk factors with weak evidence (class IV). Pre-pregnancy overweight and obesity were protective factors for placental abruption. Although factors associated with placental abruption have been investigated, the current meta-analytic associations cannot disentangle the complex etiology of placental abruption mainly due to their low quality of evidence.Additional file 1: S1. Search strategy. S 2. Excluded references with reasons. S 3. Quality of studies based on AMSTAR2 items.


To study the association between sleep duration and the incidence of type 2 diabetes mellitus (T2DM) and to provide a theoretical basis for the prevention of T2DM through a meta-analysis.  PubMed, Web of Science, Scopus, Embase, Cochrane Library, ProQuest, CNKI, Wanfang, VIP, and SINOMED were searched from their inception until May 2020. All cohort studies on the relationship between sleep duration and T2DM in adults were included. According to the inclusion and exclusion criteria, two authors independently assessed the literature and extracted the data. Metaregression and publication bias were evaluated, and sensitivity and meta-analyses were conducted with RevMan 5.3. t ≤ 6 h), 4.39% in normal sleep duration (NSD) (6 h < t < 9 h), and 4.99% in long sleep duration (LSD) (t ≥ 9 h). The meta-analysis demonstrated that SSD increased the risk of T2DM compared with NSD , LSD increased the risk of T2DM compared with NSD , and the risk of T2DM has no significant difference between SSD and LSD . The sensitivity of each study was robust and the publication bias was weak.  A total of 17 studies were collected, involving 737002 adults. The incidence of T2DM was 4.73% in short sleep duration (SSD) ( SSD or LSD can increase the risk of T2DM. Diabetes mellitus (DM) is an epidemic disease in recent years. According to the International Diabetes Federation Diabetes Atlas Ninth Edition published in 2019, it is estimated that 463 million adults (aged between 20 and 79 years) have DM worldwide, and the prevalence has reached 9.3%. This number is expected to reach 578 million (10.2%) by 2030 and 700 million (10.9%) by 2045 [DM is one of the leading causes of retinopathy, vascular disease, neuropathy, amputation, heart disease, kidney failure, and premature death . There a∗,” “concurrent stud∗,” and “cohort analy∗.” To search for all terms that begin with a word, enter the word followed by an asterisk. We followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines in conducting this systematic review and meta-analysis . We perfTwo authors independently determined study eligibility. Any differences in opinion about eligibility were resolved through another author as a third-party consensus. The inclusion criteria were as follows: (1) cohort studies on the relationship between sleep duration and T2DM in adults, (2) reported sleep duration, (3) diagnosed T2DM, and (4) published English and non-English papers. Studies were not included if (1) they are cross-sectional studies, case-control studies, case reports, and review commentaries; (2) they do not report the incidence of T2DM; (3) they have participants < 10; (4) the subjects were special groups, such as pregnant women and patients after organ transplantation; (5) sleep duration was not reported clearly; (6) they were a duplicate report; and (7) they reported incomplete data and the relevant data were not available.t < 9 hours as a reference, it is categorized as short sleep duration (SSD) (t ≤ 6 hours), normal sleep duration (NSD) (6 hours < t < 9 hours), and long sleep duration (LSD) (t ≥ 9 hours).DM was defined as fasting glucose over 126 mg/dl or 2-hour postprandial glucose (at a glucose tolerance test) over 200 mg/dl or if the subjects were on diabetic drugs or insulin medication. The number of hours of sleep was defined as the average length of their sleep in whole hours at night. The usual sleep duration was self-reported. Taking sleep duration 6 hours < Data were independently recruited from all included studies on a template adopted from the Cochrane collaboration . For allThe risk bias of the included studies was independently assessed by two authors. The cohort study was evaluated by the Newcastle-Ottawa Scale (NOS), which included eight items, categorized into three groups: the selection of study groups, comparability of groups, and ascertainment of outcome . Each sthttps://community.cochrane.org/help/tools-and-software/revman-5). Dichotomous outcomes eligible in each study are reported as a risk ratio (RR) with an estimated 95% confidence interval (CI). Continuous outcomes are shown as the weighted mean difference (WMD) with the 95% CI, which were calculated from the mean, standard deviation (SD), P value, and sample size in each study. Heterogeneity was assessed using Higgins I2, which evaluates the percentage of total variation across studies that were due to heterogeneity rather than by chance. Thus, if I2 > 50%, which was considered to reflect substantial heterogeneity, a random effect model was used. If I2 ≤ 50%, which was considered to reflect no heterogeneity, a fixed effect model was employed. The chi-square tests were also used to evaluate the heterogeneity: P < 0.1 indicates heterogeneity, while P > 0.1 indicates no heterogeneity. Based on clinical knowledge, the study location and study period were considered to be responsible for heterogeneity, and so, these parameters were set as covariates in the meta-regression. Funnel plots judged the publication biases, and a P < 0.05 was considered statistically significant [The meta-analyses were conducted using Review Manager software, version 5.3 , reported incomplete data (n = 23), commentary (n = 12), case report (n = 5), and duplicate report (n = 4). Finally, seventeen cohort studies were included in the present meta-analysis [A total of 1540 studies were identified, and 325 duplicated articles were excluded. One thousand one hundred and twenty-one studies were excluded after screening the title and abstract. After full-text screening, an additional 77 studies were excluded due to the following criteria: review article  and 4.39% (21652/493140) in NSD (6 h < t < 9 h). There was high heterogeneity among the studies, and the random effect model was used. Meta-analysis showed that the incidence of T2DM in SSD was higher than that in NSD   .P = 0.02). Meta-analysis showed that the incidence of T2DM in SSD was higher than that in NSD in female subgroups . Meta-analysis showed that the incidence of T2DM in SSD was higher than that in NSD in the mixed male and female subgroup   .P = 0.003). Meta-analysis showed that the incidence of T2DM in SSD was higher than that in NSD in the America subgroups . Meta-analysis showed that the incidence of T2DM in SSD was higher than that in NSD in the Europe subgroup   .t ≥ 9 h) and 4.39% (21652/493140) in NSD (6 h < t < 9 h). There was high heterogeneity among the studies, and the random effect model was used. Meta-analysis showed that the incidence of T2DM in LSD was higher than that in NSD   .P = 0.02). Meta-analysis showed that the incidence of T2DM in LSD was higher than that in NSD in female subgroups . Meta-analysis showed that the incidence of T2DM in LSD was higher than that in NSD in the mixed male and female subgroup   .P = 0.03). Meta-analysis showed that the incidence of T2DM in LSD was higher than that in NSD in the America subgroups . Meta-analysis showed that the incidence of T2DM in LSD was higher than that in NSD in the Europe subgroup   .P = 0.41)  .Sensitivity analyses of the association between SSD, LSD, and T2DM were conducted. The results indicated that the sensitivity of the association between SSD and T2DM was robust after each study was excluded one by one. The RR was 1.22 and 95% CI was 1.15-1.29 . The rest = 0.42, P = 0.678, 95% CI: −0.085 to 0.127) nor the study period  was responsible for this heterogeneity. Other factors, such as age, cannot be fully extracted from the text.Metaregression analyses were performed in the meta-analysis of the relationship between SSD and T2DM. The results indicated that neither the study location . And no significant association was observed in the study period .Metaregression analyses were performed in the meta-analysis of the relationship between LSD and T2DM. Metaregression indicated that study location may have been responsible for this heterogeneity , respectively, and are anticipated to remain so in 2030 . With thβ cell response ability, the inhibition of insulin secretion, and the further development of insulin resistance and T2DM. Lack of sleep may also cause the release of a large number of inflammatory factors, inhibits the activity of islet receptor L-arginine kinase, and leads to insulin resistance. Some studies found that slow-wave sleep duration decreased insulin sensitivity and increased the risk of T2DM [In this meta-analysis of the association between SSD and T2DM, the risk of T2DM with SSD was 1.22 times higher than that with NSD, which was consistent with the conclusions of other cohort studies –45. The  of T2DM –48.In this meta-analysis of the association between LSD and T2DM, the risk of T2DM with LSD was 1.26 times higher than that with NSD, which was consistent with the conclusions of other cohort studies –45. The The meta-analysis found that LSD or SSD will increase the risk of T2DM. Some studies suggest that LSD or SSD can lead to impaired fasting blood glucose, abnormal HbA1, and insulin resistance –56. TherLimitations are listed as follows: (1) some studies have not been retrieved. All the included studies are published in Chinese and English, and there may be incomplete literature retrieval, (2) the overall heterogeneity of the study is high, suggesting that there is heterogeneity among the studies. However, after subgroup analyses were performed, the heterogeneity of subgroups decreased significantly, (3) the study explored the association between sleep duration and T2DM but paid less attention to the association between sleep quality and T2DM, which also indicated that we should focus on it in later research, and (4) for special populations such as gestational diabetes, postpartum diabetes, and posttransplant diabetes, there is less attention.More and more studies have confirmed that an unhealthy lifestyle plays an important role in the pathogenesis of T2DM and glucose control in DM . From thThe purpose of the current study was to determine the cohort studies of the relationship between sleep duration and T2DM in adults with a systematic review and meta-analysis. This study provides the first systematic assessment of the cohort study of the relationship between sleep duration and T2DM. The findings indicate that SSD or LSD is a risk factor for T2DM. The findings of this study have several important implications for future practice. Further research is required to attend to the association between sleep quality and T2DM.


Current studies showed that idiopathic pulmonary fibrosis (IPF) may lead to a poor prognosis of lung cancer. We conducted a meta-analysis to explore the impact of concomitant IPF in lung cancer and its prognostic value.th, 2021 for relevant researches and merged the hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the association between concomitant IPF and overall survival (OS) in patients with lung cancer.We searched the databases of PubMed, Web of Science, Embase up to Feb 10Twelve studies involving 58424 patients were included in our meta-analysis. The results indicated that concomitant IPF was correlated with poor prognosis of lung cancer patients . The association remained consistent after subgroup analysis and meta-regression stratified by study region, sample size, tumor histology, and therapy. In addition, our results were robust even after sensitivity analysis.Concomitant IPF may be a prognostic factor of lung cancer, which can lead to poor survival. However, further studies were necessary for evidence in clinical application. Novel cancer statistics revealed that lung cancer is still a common form of cancer and the leading cause of cancer death with a terribly high incident and mortality rate . DespiteIPF has many comorbidities and complications such as pulmonary hypertension (PH) , 14, obs.This meta-analysis is reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement  and was S2 File.We performed a systematic search in the following databases, Web of Science, Embase, and PubMed for cohort studies and case-control studies evaluating the association between coexistent idiopathic pulmonary fibrosis and the prognosis of lung cancer patients until Feb 10th, 2021, without any restrictions of language or publication status. The following keywords were used: “idiopathic pulmonary fibrosis”, “IPF”, “lung cancer”, “pulmonary tumor”, “lung carcinoma”, “prognosis”, “survival”. In addition, we also searched for potential articles from the reference lists of relevant articles manually. The search strategy for PubMed was presented in The following inclusion criteria were used: 1) all patients were pathologically diagnosed with lung cancer; 2) the outcomes included OS with a hazard ratio (HR) and corresponding 95% confidence interval (95% CI); 3) full-text papers published in English.The exclusion criteria were as follows: 1) reviews, conference abstracts, cases reports, letters, or comments; 2) laboratory researches of clinical samples, animals, or cell lines; 3) insufficient data for estimating hazard ratios of concomitant IPF; 4) lack of control.Two researchers extracted the following data independently from the eligible studies, including family names of the first author, year of publication, study design, region, follow-up (months), sample size, therapy, and survival data. Any disagreement was resolved by discussion and consensus.The risk of bias of each enrolled study was assessed by applying the Newcastle-Ottawa quality assessment Scale (NOS) . Studies2, I2, and Tau2 statistics. The significant heterogeneity was defined as p-value < 0.05 and I2 > 50%. Sensitivity analysis was conducted by excluding each study independently from our meta-analysis to find out the over-representation of every single study. Subgroup analysis and meta-regression were performed to investigate potential confounding factors of this meta-analysis. Publication bias was evaluated by Begg’s test, funnel plots, and Baujat plot [Statistical analysis was conducted via R (version 4.0.3). HRs from multivariate analysis were used wherever available, and HRs from univariate models were substitutes if only univariate analysis was performed. Moreover, HRs and corresponding 95% CIs were estimated from Kaplan–Meier curves via the method by Tierney et al , if theyjat plot , and a tjat plot  was usedFig 1 and S3 File. A total of 664 separate publications were retrieved through our search strategy. We reduced these to a list of 473 articles after removing duplicates. We found 60 potentially eligible studies according to titles and abstracts and then screened full-text versions of them. Finally, twelve studies were included in this meta-analysis. The NOS scores varied from 7 to 9, which demonstrated a low risk of bias in these studies.The PRISMA flow diagram and checklist of this meta-analysis were presented in Table 1 [The main characteristics of all 12 studies that met our inclusion and exclusion criteria were displayed in Table 1 –45.Of all included studies, 10 were conducted in Asia , 44, 45 Fig 2). The result indicated that concomitant IPF is associated with OS of lung cancer patients . We found significant heterogeneity among studies .12 studies involving a total of 58424 patients (1361 with IPF and lung cancer and 57063 with lung cancer only) contributed to the primary analysis . In the analysis of the study region, patients from Asia and USA showed both insignificant heterogeneities, and the results were  and , respectively. In the analysis of sample size, studies with sample size of more than 500 [2 = 48%, p = 0.13) whereas studies with a sample size of no more than 500 [2 = 53%, p = 0.04). Similarly, patients receiving surgery had insignificant heterogeneity  while non-surgery patients were opposite . For the tumor stage, the results for all subgroups were significant, but there weren’t any differences among all subgroups, and only the subgroup of Stage I-IV was with low heterogeneity after stratification .In order to detect the potential cause of heterogeneity, we performed subgroup analyses stratified by study region, sample size, tumor histology, and therapy . In the univariate model, the study region appeared to be the main source of heterogeneity , however, when performing multivariate analysis, the significance disappeared .Subsequently, we performed meta-regression to quantificationally analyze the potential source of heterogeneity .We then conducted a sensitivity analysis to evaluate the impact of every single study on the combined HRs by excluding each study independently from the meta-analysis. All HRs were in the 95%CI of our primary analysis, which demonstrated that our pooled HRs for OS were robust . The p-value of Begg’s test was less than 0.01, which showed an indication of publication bias. So we drew a Baujat plot to detect the source of bias and heterogeneity  and we subsequently conducted a meta-analysis after removing two studies with possibly high heterogeneity . We then conducted a trim and fill analysis . The study of Lee contributed most to heterogeneity while Brown had the highest influence on the overall result. The results after a trim and fill analysis were still significant .Finally, we conducted Begg’s test and drew funnel plots to assess the publication bias of all included studies . Then we attempted to find out the source of heterogeneity by conducting subgroup analyses and meta-regression. The subgroup analyses revealed that concomitant IPF could consistently be a prognostic factor of lung cancer patients when stratified by study region, sample size, tumor histology, and therapy. In addition, the results also showed that stratification according to study region, sample size, and therapy may reduce the heterogeneity, which suggested these factors might contribute to the heterogeneity of studies. However, the results of meta-regression demonstrated that the study region, sample size, and therapy may not be the main source of heterogeneity even though the study region displayed statistical significance in univariate analysis. Interestingly, when analyzing the impact of tumor histology, we found that both NSCLC and SCLC subgroups remained high heterogeneity and maybe it’s due to the subtypes of histology. Furthermore, our meta-analysis proved to be robust after sensitivity analysis. Although there was publication bias, which meant some studies with negative results may not be published, the result modified by a trim and fill method confirmed that concomitant IPF had identical prognostic value in patients with lung cancer.Our current meta-analysis suggested that concomitant IPF may be associated with poor prognosis of patients with lung cancer . However, the I2 and p-value indicated that there was high heterogeneity among the studies included (I1), which is known as a profibrotic mediator [Previous studies suggested that IPF and cancer are similar and multiple pathological processes were involved, for instance, genetic or epigenetic alterations and abnormal cell phenotypes like proliferation and apoptosis exist in both IPF and cancer . For lunmediator , 49. In mediator , which imediator , charactmediator , which cmediator , 53. In Our study conclusion was partly similar to those of another study by JafariNezhad , howeverHowever, the current research has some limitations, too. The most obvious one is that there was high heterogeneity and publication bias. The heterogeneity was considerably reduced after omitting studies of Lee and Kim without attenuating the pooled HRs, which suggested that these two studies may be the main source of heterogeneity although they had no significant bias after our reassessment . Our resGenerally speaking, our meta-analysis demonstrated the prognostic value and adverse effect of concomitant IPF in lung cancer patients. Nevertheless, our findings must be applied carefully and discreetly and more prospective cohort studies are required.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigThe subgroup analyses stratified by (a) study region, (b) sample size, (c) tumor histology, (d) therapy, and (e) tumor stage.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S1 File(PDF)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(DOC)Click here for additional data file.S4 File(XLSX)Click here for additional data file.


The serine protease inhibitor-1 (SERPINE1) rs1799889 single nucleotide polymorphism (SNP) has been constantly associated with diabetes mellitus (DM) and its vascular complications. The aim of this meta-analysis was to evaluate this association with combined evidences.The systematic search was performed for studies published up to March 2021 which assess the associations between SERPINE1 rs1799889 SNP and the risks of DM, diabetic retinopathy (DR), diabetic cardiovascular disease (CVD) and diabetic nephropathy (DN). Only case-control studies were identified, and the linkage between SERPINE1 rs1799889 polymorphism and diabetic vascular risks were evaluated using genetic models.51 comparisons were enrolled. The results revealed a significant association with diabetes risk in overall population  as well as in Asian descents . A significant association was observed with DR risk  for overall population, as for the European subgroup . A significant association were shown with DN risk for overall population  and for Asian subgroup  after ethnicity stratification. No obvious association was implied with overall diabetic CVD risk in any genetic models, or after ethnicity stratification.SERPINE1 rs1799889 4G polymorphism may outstand for serving as a genetic synergistic factor in overall DM and DN populations, positively for individuals with Asian descent. The association of SERPINE1 rs1799889 SNP and DR or diabetic CVD risks was not revealed.The online version contains supplementary material available at 10.1186/s12902-021-00837-z. Diabetes mellitus (DM) is a major worldwide epidemic that has gained significant public attention. According to recent data from the latest WHO report on diabetes, its world prevalence has been estimated at 8.4 % . Added tTo date, advances in epidemiological and pathophysiological research on DM have improved our understanding of the underlying pathogenic mechanism of diabetes. The determinants of DM consist of a matrix of genetic susceptibility and epigenetic and lifestyle factors that interact with one another and operate within the larger physical-sociocultural environment , 4. GeneTo date, there have been extensive studies conducted investigating the potential role of SERPINE1 rs1799889 polymorphism in DM and subsequent complications. However, former meta-analyses reached inconsistent conclusions on this topic as they might be restrained by sample sizes or an insufficiency of studies , 11. ConThe current meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement . PotentiA study included in this meta-analysis must meet with the following criteria: (1) case-control study on correlation analysis between SERPINE1 rs1799889 SNP and the risk of diabetes and associated complications to be assessed; (2) the study must include original and adequate data to allow calculation of odds ratios (ORs) with 95 % confidence intervals (CIs) (independence among studies); (3) evaluation of SERPINE1 rs1799889 polymorphism and the risk of diabetes and its complications.A study was excluded when fulfilling one of the following criteria: (1) for overlapping-data study, only the most recent and complete one was enrolled; (2) study with missing information (particularly genotype distributions), while the required information could not be acquired from the corresponding author; (3) genome scans investigating linkages with no detailed genotype frequencies between cases and controls. If inclusions have disagreements, we reached a consensus through discussion. Two reviewers (JY Chen and CN Zhai) independently screened the titles and abstracts for the eligibility criteria. Subsequently, reviewers both read the full text of the studies which potentially met with the inclusion criteria, and the literature was reviewed to determine final inclusive data.P value) of Hardy-Weinberg equilibrium (HWE) test was also calculated on the basis of allele frequencies of certain SERPINE1 rs1799889 polymorphisms in the control group.Two reviewers (JY Chen and CN Zhai) conducted the data extraction from each study independently. Any disagreement between the two reviewers was solved by discussion with the third reviewer (ZQ Wang) until reaching a consensus. Three reviewers  independently evaluated the quality of each case-control study by using the Newcastle–Ottawa Scale criteria . We summP < 0.1 was considered statistically significant. The Mantel-Haenszel method for fixed effects and the Der-Simonian and Laird method for random effects were used to estimate pooled effects [2, was used to quantify the inconsistency among the studies’ results with values of 50 % or higher and the large heterogeneity for values of 75 % or higher [P-values; statistical significance was set at P < 0.05 (two-tailed). Meta-regression analysis was applied to evaluate the heterogeneity of the studies. Publication bias was conducted statistically via Begg’s and Egger’s bias test, which measures the degree of funnel plot asymmetry [All statistical analyses were conducted using STATA 12.0  and Review Manager Version 5.3.3 . The associations between the SERPINE1 rs1799889 polymorphism and DM and its complications’ susceptibility were assessed using the following genetic models: 4G vs. 5G , 4G4G vs. 5G5G (homozygous), 4G5G vs. 5G5G (heterozygous), 4G4G + 4G5G vs. 5G5G (dominant), and 4G4G vs. 5G5G + 5G4G (recessive). Between-study heterogeneity was tested using Q statistics, and  effects . We used effects . A recenr higher . The datsymmetry , 21. TheThe study flow chart is summarized in Fig. In overall population, our meta-analysis revealed a significant association between the SERPINE1 rs1799889 polymorphism and overall diabetes risk, in allelic , homozygous , heterozygous , dominant ,and recessive  models. When analyses were subdivided by ethnicity, no obvious associations were noted for the European using any of the five genetic models. For the Asian subgroup, significant associations were observed in all of the five genetic models . Results of pooled analyses are summarized and presented in Table p < 0.01), but no association was observed in the allelic, heterozygote, and dominant models. No significant associations were indicated among Asian descent in all genetic models. Results of pooled analyses are summarized and presented in Table In overall population, a significant association between the SERPINE1 rs1799889 polymorphism and DR risk was observed in homozygous  and recessive  models, but no association was found in the other three genetic models. For the European subgroup, a significant association was revealed by homozygous  and recessive model , homozygous , dominant , and recessive  models. After subdivided by ethnicity, remarkable associations were observed in allelic , homozygous , and recessive  models for Asian subgroup. On the contrary, no obvious associations were noted for the European using any of the five genetic models. Results of pooled analyses are summarized and presented in Table p values calculated were larger than 0.05.A meta-regression analysis for the discovery of potential origins of heterogeneity, such as study type, published years, sample sizes, age, gender, ethnicity and outcomes, was conducted. Single covariates were added in the allelic, homozygous, heterozygous, dominant and recessive models. However, the results of meta-regression indicated that none of the above sources contributed to the heterogeneity across all studies of the association between SERPINE1 rs1799889 polymorphism and diabetic vascular susceptibility, since all the Sensitivity analysis with stratified analyses were conducted to examine the stability of our meta-analysis results. The high heterogeneity in some of the genetic models was obvious among studies except for the association with DR risk. On the association with DM and DN risk, a heterogeneity was detected within the overall analysis for the allelic model. On the association with DM, DR and DN risks, the heterogeneity in any genetic model was not significantly varied after either sensitivity analysis or sub-group analysis by ethnicity stratification. On the association with diabetic CVD risk, heterogeneity was noted for allelic/homozygote/recessive models, except for the European sub-group. After the sensitivity analysis, the study from Li et al.  were maiPotential publication bias in the current study was evaluated with Begg’s and Egger’s bias test. Publication bias was noted within DM sub-group with Egger test and DN sub-group for recessive model. Except for that, no obvious publication bias was observed in other comparisons, which confirmed that the results our meta-analysis presented were statistically robust Table .Table 6The current meta-analysis suggests that the SERPINE1 rs1799889 4G polymorphism possesses a genetic modulatory function in overall DM populations and in diabetic renal vascular complications, which can be ethnically divergent according to the results. Genetic factors have long been considered a substantial determinant within the diabetic physical-sociocultural environment . PositivPAI-1 is a serine protease inhibitor protein encoded by the SERPINE1 gene that plays an important role in regulating fibrinolysis and thrombosis by inhibiting the activity of tissue plasminogen activator and urokinase plasminogen activator, whose activation is driven by tissue-type plasminogen activator (tPA) cleavage of plasminogen . PreviouPrevious studies of the distribution of the SERPINE1 rs1799889 SNP have been controversial concerning the susceptibility of diabetes among various populations. Saely et al.  demonstrOur results revealed an obvious difference in the association of the SERPINE1 rs1799889 SNP among individuals with Asian and European descent, implying that the heterogeneity is based on ethnicity. Concerning the association with diabetes risk, our results suggested that the 4G polymorphism is a genetic risk factor in overall populations. Moreover, after stratification by ethnicity, the results revealed a remarkable association with Asian descent, while no association was found for European diabetic populations. A previous meta-analysis showed different results . RegardiSince our meta-analysis was conducted with stratified ethnicity, the origins of heterogeneity must be given thorough discussion. In our analysis, heterogeneity was revealed among people of Asian descent both in the CVD and DN subgroups. We speculate that the sources of heterogeneity in studies might include age and gender proportion, ethnic traits, environmental factors, medication status, health care quality and cultural differences. A meta-regression analysis was done by study type, published years, age, gender, ethnicity, sample sizes, and outcomes. However, the results did not indicate the sources of heterogeneity, since all the p values calculated above were larger than 0.05. As we speculated, meta-regression is usually conducted in studies with larger sample sizes and study sub-groups, whose effect might be restrained in this case. Moreover, the gene-gene and gene-environmental interactions might also trigger the heterogeneity of genetic effects between individual studies.There were several limitations included in our meta-analysis: (1) insufficient genotyping data of SERPINE1 rs1799889 SNP in mix ethnicity, which limited the possibility to further discussions regarding this population, and (2) potential heterogeneity of study variables, such as the biological parameters of study subjects, clinical history, medication compliance, other diabetic complications, etc. and (3) the Begg’s and Egger’s test have given some potential publication bias, indicating the importance of a well-matched case-control study population. (4) Sample size is another limitation, some of the original studies analyzed presented relatively small control groups, and the minor allele frequency  of the control populations analyzed are heterogeneous, between 34.2 and 71 %, including among studies in the same ethnicity group and also in the same study among different analyzed groups. (5) Insufficiency of original studies of type 1 DM has restrained a further subgroup analysis concerning the classification of DM.Collectively, our meta-analysis demonstrates that the SERPINE1 rs1799889 4G polymorphism may outstand for serving as a genetic synergistic factor in overall DM populations, and overall DN populations. Moreover, it can be positively associated with increased DM and DN risks for individuals with Asian descent. The association of SERPINE1 rs1799889 polymorphisms and DR or diabetic CVD risks was not revealed by our meta-analysis. However, future studies with multiple ethnicities and rigorous designs are still in-need to confirm our conclusions.Additional file 1:Supplementary Table 1. Newcastle–Ottawa scale (NOS) for assessing quality of observational studies.Additional file 2:Supplementary Table 2. Search strategy for PubMed.Additional file 3:Supplementary Fig. 1. Cumulative meta-analysis of the chronologic integration between SERPINE1 rs1799889 SNP and diabetes risk. (A) allelic model, (B) homozygote model, (C) heterozygote model, (D) dominant model, and (E) recessive model.Additional file 4:Supplementary Fig. 2. Begg’s funnel plot of bias for studies of the association between SERPINE1 rs1799889 SNP and diabetes risk. (A) allelic model, (B) homozygote model, (C) heterozygote model, (D) dominant model, and (E) recessive model.Additional file 5:Supplementary Fig. 3. Begg’s funnel plot of bias for studies of the association between SERPINE1 rs1799889 SNP and DR risk. (A) allelic model, (B) homozygote model, (C) heterozygote model, (D) dominant model, and (E) recessive model.Additional file 6:Supplementary Fig. 4. Begg’s funnel plot of bias for studies of the association between SERPINE1 rs1799889 SNP and CVD risk. (A) allelic model, (B) homozygote model, (C) heterozygote model, (D) dominant model, and (E) recessive model.Additional file 7:Supplementary Fig. 5. Begg’s funnel plot of bias for studies of the association between SERPINE1 rs1799889 SNP and DN risk. (A) allelic model, (B) homozygote model, (C) heterozygote model, (D) dominant model, and (E) recessive model.


MTHFR) polymorphism and essential hypertension (EH). Nevertheless, their conclusions were controversial. So far, six previous meta-analyses discussed the internal relationship between the MTHFR polymorphism and EH, respectively. However, they did not evaluate the credibility of the positive associations. To build on previous meta-analyses, we updated the literature by including previously included papers as well as nine new articles, improved the inclusion criteria by also considering the quality of the papers, and applied new statistical techniques to assess the observed associations. Objectives: This study aims to explore the degree of risk correlation between two MTHFR polymorphisms and EH. Methods: PubMed, EMBASE, the Cochrane Library, CNKI, and Wan Fang electronic databases were searched to identify relevant studies. We evaluated the relation between the MTHFR C677T (rs1801133) and A1298C (rs1801131) polymorphisms and EH by calculating the odds ratios (OR) as well as 95% confidence intervals (CI). Here we used subgroup analysis, sensitivity analysis, cumulative meta-analysis, assessment of publication bias, meta-regression meta, False-positive report probability (FPRP), Bayesian false discovery probability (BFDP), and Venice criterion. Results: Overall, harboring the variant of MTHFR C677T was associated with an increased risk of EH in the overall populations, East Asians, Southeast Asians, South Asians, Caucasians/Europeans, and Africans. After the sensitivity analysis, positive results were found only in the overall population  and Asian population . However, after further statistical assessment by FPRP, BFDP, and Venice criteria, the positive associations reported here could be deemed to be false-positives and present only weak evidence for a causal relationship. In addition, when we performed pooled analysis and sensitivity analysis on MTHFR A1298C; all the results were negative. Conclusion: The positive relationships between MTHFR C677T and A1298C polymorphisms with the susceptibility to present with hypertension were not robust enough to withstand statistical interrogation by FPRP, BFDP, and Venice criteria. Therefore, these SNPs are probably not important in EH etiology.Background: Since the 1990s, there have been a lot of research on single-nucleotide polymorphism (SNP) and different diseases, including many studies on 5,10-methylenetetrahydrofolate reductase ( This is of great significance for the genetic research of EH  is a common disease in the world and a threat to the health of people. If blood pressure is not well controlled, it can lead to serious consequences, such as coronary heart disease, enlarged heart, heart failure, cerebral hemorrhage, optic papillary edema, and renal insufficiency. At the same time, chronic high blood pressure could lead to clinical symptoms such as dizziness, headache, chest pain, tinnitus, vomiting, palpitation, and blurred vision . EH is aus trait . Throughch of EH .MTHFR) plays an important role in folate metabolism–methionine cycle. Together with methionine synthase reductase (MTRR), it maintains the normal metabolism of folate and participates in the maintenance of normal homocysteine (Hcy) levels in the body. Specific MTHFR gene mutations can lead to a decrease in the activity of key enzymes and disorders in folate metabolism, which increased the demand for folate to maintain Hcy methylation to methionine (Met) and ultimately lead to the increase of Hcy level and hHcy  and A1298C (rs1801131) are two common gene sites. The 677C-T gene mutation is located in exon 4 of the catalytic activity of the N-terminal region, where cytosine is replaced by thymine, and the corresponding protein is changed from alanine (Ala) to valine . The 1298A-C mutation is located in the C-terminal regulatory region of exon 7, where adenosine mutates to cytosine, causing the glutamate (Glu) encoding to be replaced by alanine (Ala) (MTHFR SNPs and blood pressure were unclear (Studies have shown that hyperhomocysteinemia (hHcy) is an important risk factor for hypertension. 5,10-Methylenetetrahydrofolate reductase (and hHcy . The humne (Ala) . Globallne (Ala) . Therefone (Ala) . Althoug unclear . Studiesvia the MTHFR gene polymorphisms to develop EH. There are many published meta-analyses, but the conclusions were controversial  AND (MTHFR A1298C OR rs1801131 OR Glu429Ala) AND (polymorphism OR mutation OR variant OR genotype) AND . Two researchers who were familiar with the literature search process and meta-analysis methods conducted a literature search to identify all possible original studies. The search deadline was December 2020.Databases, including PubMed, EMBASE, the Cochrane Library, CNKI, and Wan Fang databases, were searched for evidence between the carrier status of the MTHFR polymorphisms and EH.The inclusion criteria were as follows: (1) case–control study, (2) complete study of genotype data, and (3) study exploring the relationship between The exclusion criteria were as follows: (1) unrelated diseases or other diseases associated with hypertension or secondary hypertension, (2) incomplete study of genotype data and genotype frequency, (3) duplicate study, and (4) letters, reviews, animal experiments, other analysis.According to the abovementioned inclusion and exclusion criteria, two researchers searched independently the abovementioned databases and finally checked them to ensure a comprehensive search and information extraction of all relevant studies. If there was a difference in opinion, it would be discussed with a third researcher. The extraction will be based on the following information: last name of the first author, publication year, country, geographical location, ethnicity of the study subjects, source of the case group, source of the control group, matching, diagnostic criteria for EH, genotype data in cases and controls, sample size, genotype examination, and adjustments.All studies were independently evaluated and verified by two investigators. According to previously published articles  togethern: genotype sample size): A: n ≥ 1,000; B: 100 ≤ n < 1,000; C: n < 100; (2) reproducibility: A: I2 <25%; B: I2 >25% and I2 < 50%; C: I2 >50% or higher; and (3) bias control: A: no bias; B: no obvious bias but data is missing; C: obvious bias. A, B, and C represent strong, moderate, and weak cumulative epidemiological evidence, respectively , Bayesian false discovery probability (BFDP) test, and Venice criterion . When FPectively .MTHFR gene polymorphisms and EH. Evaluation of heterogeneity was by Cochran Q test and I2 test. When P >0.10 and/or I2 ≤50%, a fixed-effect model was selected to combine the effect sizes. When P ≤0.10 and/or I2 >50%, a random-effects model was selected  on the included control group and to select the studies conforming to HWE. We calculated the combined odds ratio (OR) and 95% confidence intervals (CI) to determine the association between selected . Allelicselected . We coulselected . Cumulatselected . STATA12C677T polymorphism and 11 articles on A1298C polymorphism .In vs. CC: OR = 1.74, 95% CI: 1.43–2.12; TC vs. CC: OR = 1.34, 95% CI: 1.21–1.48; TT + TC vs. CC: OR = 1.44, 95% CI: 1.28–1.61; TT vs. TC + CC: OR = 1.49, 95% CI: 1.26–1.77; T vs. C: OR = 1.35, 95% CI: 1.24–1.46), Caucasian , and African . The same happened in the East Asia region , South Asia region , Southeast Asia region , Europe region , and Africa region .Next, a subgroup analysis was performed by ethnicity and geographic region. An increased risk of hypertension could be found in Asian . A conservation correlation has been found in the West Asia region .The association between vs. CC: P = 0.035; TT + TC vs. CC: P = 0.042).In A1298C genotype. However, the results of the C677T genotype changed significantly in the overall population , Asian population , Caucasian population , and East Asia region . All results are shown in A sensitivity analysis was performed to rule out individual studies one by one, and the results were found to be stable. When we restricted the high-quality and HWE studies, there was no significant change in MTHFR C677T polymorphism, there was publication bias in four genetic models  .Begg’s funnel plot and Egger test were used to evaluate publication bias. For = 0.005) . In orde= 0.005) . For MTHAccording to year, the literature was included sequentially to evaluate the stability of cumulative effect size. The results showed that the correlation degree tended to be stable .vs. CC) and recessive model (TT vs. CT + CC). After FPRP, BFDP, and Venice criterion evaluation, results that met both FPRP <0.2, BFDP <0.8, and above moderate epidemiological evidence were only in the heterozygote , and Africans. It was possible that both were linked in the study population from African, South Asia region, and Southeast Asia region  and the Asian population . When we used the FPRP, BFDP test, and the Venice criterion for evaluation, all significant associations were less-credible positive results, indicating that the association could not be noteworthy and could therefore be regarded as weak-level evidence. These tests are necessary to avoid random error and confounding bias, but sometimes they can alter the results of the epidemiological studies (A1298C polymorphism was associated with EH. The South Asia , South a region ], and Soa region ], these a region . Then, w studies . At the e report ] and Soue report ] resultse report –7. In cocultures . Hcy is cultures . Alam et Indians . Howevern the UK . FurtherWe could find a significant heterogeneity between the articles included in the final results . HeterogMTHFR C677T polymorphism, 63 studies were collected, including 11,556 case groups and 12,523 control groups. For MTHFR A1298C polymorphism, there were 11 studies with 2,504 case groups and 2,979 control groups. Secondly, we analyzed the sensitivity of the combined results by excluding individual studies one by one and limiting high-quality and HWE studies. Thirdly, meta-regression, cumulative meta-analysis, trim-and-fill method, and geographic origin subgroup analysis were used to verify the qualified combined effect size. Fourthly, we used the FPRP and BFDP tests that were first introduced to judge the credibility of the positive results. The Venice criterion was used to assess the cumulative level of epidemiological evidence for genetic association. The GWAS on Europeans was an association study for the detection of multiple SNPs. The method was regression analysis. An assumption of regression analysis is the independent distribution of data. However, the fact is that many individuals may have distant relationships, which will lead to false-positive results in an association analysis (Compared with previously published meta-analyses, this study has several advantages. Firstly, we have the largest sample size to date. A total of 66 case–control studies were included. For analysis . HoweverMTHFR C677T polymorphism in Africa, South Asia, Southeast Asia, and West Asia. Therefore, heterogeneity may exist. More research should be done in these areas. Fifthly, with regard to the MTHFR A1298C polymorphism, since there were only two studies in West Asia, it is still uncertain whether this SNP is associated with EH.However, there are also shortcomings to our meta-analysis that should be kept in mind. Firstly, only Chinese and English studies were included in this study; studies in other languages were not included. There is a certain degree of heterogeneity. Secondly, this study did not include the data of family genetic aggregation, smoking, body weight, body mass index, gender, age, and medication history. Therefore, the results may be affected by confounding factors. Thirdly, the sources of the control group were not uniform, which may have classification bias. Fourthly, there were few studies on MTHFR polymorphisms on the risk of EH in different populations worldwide. The results showed that MTHFR C677T gene polymorphism was associated with increased EH risks in overall population, East Asian, and Caucasian. However, after FPRP, BFDP, and Venice Criteria tests, the above-mentioned associations became less reliable. These results should be treated with caution because they could be false-positives. The final conclusion highlighted weak epidemiological credibility for a higher risk of EH of the MTHFR 677T allele. Therefore, more investigations are needed to provide researchers with conclusive evidence of whether MTHFR C677T is a genetic predictor of EH. Similarly, there was no significant association between the MTHFR A1298C polymorphism and EH. Therefore, MTHFR polymorphisms could not contribute to the development of hypertension. In the future, more studies are needed to repeatedly verify the current conclusions.In summary, this study provided a comprehensive analysis of


Age, body mass index, waist circumference, systolic blood pressure, and diastolic blood pressure (DBP) had significantly higher estimates in lean NAFLD patients than in lean non‐NAFLD controls. Fasting blood sugar , HbA1c , and insulin resistance [HOMA‐IR] ) were higher in lean NAFLD patients than in lean non‐NAFLD controls. All components of the lipid profile were raised significantly in the former group except high‐density lipoprotein. An increased uric acid (UA) level was found to be associated with the presence of NAFLD among lean. Cardio‐metabolic profiles of nonlean NAFLD patients significantly differs from the counter group. However, the magnitude of the difference of lipid and glycemic profile barely reached statistical significance when subjects were grouped according to lean and nonlean NAFLD. But DBP , HOMA‐IR , and UA  were significantly higher if NAFLD was present compared to that of non‐NAFLD group. Lean and nonlean NAFLD patients are metabolically similar and share common risk factors.The pathophysiology and risk factors of nonalcoholic fatty liver disease (NAFLD) among lean patients is poorly understood and therefore investigated. We performed a meta‐analysis of observational studies. Of 1175 articles found through searching from Medline/PubMed, Banglajol, and Google Scholar by two independent investigators, 22 were selected. Data from lean ( n = 6768) and obese (n = 9253) patients with nonalcoholic fatty liver disease (NAFLD), and lean (n = 43398) and obese (n = 9619) subjects without NAFLD  revealed that both lean and obese patients shared similar risk factors associated with NAFLD including age, body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, HbA1c, insulin resistance (HOMA‐IR), total cholesterol, low‐density lipoprotein, high‐density lipoprotein, triglycerides, and uric acid.A meta‐analysis of 22 articles comprising data from lean ( Nonalcoholic fatty liver disease (NAFLD) is an emerging public health problem.2 has changed that thought.The pathogenesis of the NAFLD is multifactorial and the underlying mechanism yet to be fully understood. Most mechanisms for developing NAFLD are linked with changes in lipid metabolism and development of insulin resistance.Overall prevalence of lean NAFLD among general population was 10.2%, and among the NAFLD population the prevalence of lean NAFLD was 19.2% with a broad countrywide variation.This work was delineated on the basis of the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis Protocols (PRISMA‐P) guidelinesEthical clearance was waivered as there was no involvement of live subjects. However, formal notification and permission was taken from Institutional Review Board (IRB) of Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh. IRB registration no: BSMMU/2020/1012.This meta‐analysis was based on systematic searches in several electronic databases comprising Medline/PubMed, BanglaJOL, and Google Scholar from inception to 30 March 2020. The keywords used during searching were made before final searching in collaboration with an experienced medical librarian so that as many relevant articles as could be retrieved. To enhance the sensitivity, bibliographic search of the selected article was also performed for additional article. Our search term for PubMed (from inception to 30 March 2020) with details of our search strategy and data collection, including terms for other databases, are described in the 2 and nonlean was defined when BMI ≥25 kg/m2. Hence only studies using this cut‐off point for differentiating nonlean (obese) from lean (nonobese) were included. Studies that described possible risk factors of NAFLD or lean NAFLD/NASH patients were considered for initial inclusion and there was no restriction in accordance with study setting either hospital or community. We included prospective comparative cohort studies of which baseline data is available, case–control studies, and cross‐sectional studies which detailed the risk factors of lean NAFLD.We included original research articles that defined their population as nonobese or lean individuals aged 18‐years or older and defined NAFLD with stratification according to weight status (nonobese or lean). In this review, lean was defined as patients with a BMI <25 kg/mThe exclusion criteria for studies were: reporting population <18 years of age including children, or people with mental disorders or studies concerning patients with other liver diseases or causes for steatosis, and alcoholic fatty liver disease or articles including patients who have a daily alcohol consumption ≥30 g for men and ≥20 g for women.In order to exclude articles irrelevant to the systematic review, two investigators (Mohammad Jahid Hasan and Md Abdullah Saeed Khan) initially independently reviewed the title and abstract of each the references using rigorous inclusion criteria. Any dispute between two investigators were resolved through discussion with the principal investigator (Shahinul Alam). Then search results passed on to Mendeley (reference management software) which excluded the duplicates. In the second stage, the two investigators independently read the full texts of the articles that were included in the initial stage, and then selected the articles that met the inclusion criteria. Differences of ideas regarding the selection of articles were resolved through group discussion. In cases where details were missing on study design, population, intervention, or outcomes, the authors of included studies were contacted by email. After the first contact attempt, if no response received, the study authors were contacted two more times approximately 3 to 4 weeks apart. The searches were re‐run just before the final analyses and further studies retrieved for inclusion were checked. The literature search, data review, and data extraction were done with a case report form to provide consistency throughout the data collection process. Data were extracted independently by two investigators . Discordance and disagreements were resolved by consensus between the two investigators or by consultation with the principal investigator (Shahinul Alam).We used a quality assessment scale based on the Newcastle‐Ottawa Scale (NOS) for this study, ranging from 0 to 9, with 7–9 representing high quality scores, 4–6 representing medium scores, and 1–3 representing low scores.vs nonlean, NAFLD vs non‐NAFLD), effect estimates for age, WC, BMI, systolic blood pressure, diastolic blood pressure, fasting blood sugar (FBS), HbA1c, insulin resistance (HOMA‐IR), total cholesterol (TC), high‐density lipoprotein (HDL), low‐density lipoprotein (LDL), triglycerides (TG), and uric acid (UA). Besides this, the search results and necessary notes were uploaded and managed using Microsoft Excel 2016.The data extraction was done by two researchers  using a standardized and pretested format. Data extraction included: title, first author, publication year, study design, settings , sample size, ethnicity, participant groups , we used the difference in means. All the data presented as median (range), and median (interquartile range [IQR]) were converted to mean (SD) using an online calculatoret al.et al.To summarize effects sizes a random effect model was adopted to allow for the variability of measurements across the studies included in the analysis. To specifically provide measures of the absolute difference between the mean values of each variable of interest calculated for any two groups  of liver in 15 studiesEight studies were of Caucasian originTwo studiesI2 = 95%). Hence, a random effect model was used. Subgroup analysis across ethnicity showed that studies of Korean, Japanese, and Chinese origin  were more heterogenous than that of Caucasian origin (I2 = 68%)  did not show any significant change in heterogeneity (vs other) showed less heterogeneity in other studies (I2 = 93 vs 68% respectively)  . Studiesogeneity . Howeverctively) .2, 95% CI 0.63–2.18). The studies were considerably heterogenous (I2 = 100%). Subgroup analysis across ethnicity did not show any change in heterogeneity  and by geographic location (Eastern vs other) showed similar heterogeneity . Subgroup analysis across ethnicity showed that Chinese studies explained the most heterogeneity (I2 = 98%). Korean (I2 = 78%) and Caucasian (I2 = 74%) studies were less heterogenous than that of Japanese (I2 = 89%) and Chinese studies  had similar high heterogeneity (vs other) showed less heterogeneity in other studies   .I2 = 94% for SBP and 98% for DBP). Ethnicity showed that Chinese studies were relatively homogenous for SBP  than other. Heterogeneity was mostly explained by Korean studies (I2 = 100%) (I2 = 99%) and Chinese (I2 = 96%) studies (I2 = 77 vs 100% respectively for SBP and 63 vs 99% respectively for DBP) (vs others) did not reveal any difference as only one study in the latter group reported BP (Ten studies = 100%) . Heterog studies . Studiesfor DBP) . Howeverorted BP .I2 = 99%). Subgroup analysis across ethnicity showed that heterogeneity was mostly explained by Korean (I2 = 100%), Japanese (I2 = 87%), and Chinese (I2 = 87%) studies . Subgroup analysis by ethnicity showed similar heterogeneity (Only three studiesogeneity .I2 = 100%). Subgroup analysis did not show any difference in heterogeneity across any stratification . Subgroup analysis by ethnicity is shown in vs hospital‐based) showed that heterogeneity in TC is completely explained by population‐based studies (I2 = 83%), but heterogeneity in LDL and HDL is explained by hospital‐based studies (I2 = 74% each) (vs other) showed that Eastern studies were overall more heterogenous than other studies for LDL, HDL, and TG and other way around for TC  . However4% each) . Stratifd for TC .I2 = 86%). Subgroup analysis by ethnicity and study settings are shown in For risk of NAFLD in lean people, only six studiesvs hospital‐based) showed that heterogeneity was mainly due to hospital‐based studies (versus other studies showed that heterogeneity was higher among Eastern studies for ALT and higher among other studies for AST (Alanine aminotransferase (ALT) was reported in 13 studies. studies . Subgrou for AST .A summary of the meta‐analysis results along with subgroup analysis for individual demographic, anthropometric, and cardiometabolic risk factors for NAFLD in lean people are given in For risk factors with 10 or more studies, funnel plot analysis was conducted . Almost P‐value: 5.62 kg/m2, P < 0.001), WC , SBP , DBP , FBS , HbA1c , HOMA‐IR , HDL , TG , UA , ALT , AST , and GGT . Similarly nonlean controls had significantly different values in cardiometabolic risk than lean control: BMI , WC , SBP , DBP , FBS , HbA1c , HOMA‐IR , TC , LDL , HDL , TG , UA , ALT , AST , and GGT . In addition, nonlean controls were significantly older than lean controls .A summary of differences in effect size between lean and nonlean NAFLD patients, and lean and nonlean controls are given in Table P < 0.037), HOMA‐IR , UA . Also, the presence of NAFLD is associated with significantly higher values of AST  and GGT  in blood.The differences in values of individual risk factors between lean and nonlean patients and controls could be explained by the significant differences in BMI and WC. However, the meta‐regression analysis showed that the magnitude of the difference in the value of the lipid profile and glycemic profile barely reached statistical significance when subjects were grouped according to the presence or absence of NAFLD Table . But forI2 = 79%)NAFLD in lean persons is now a widely recognized problem. Initially, described in Asian populations and considered as a “third world phenotype,” this subset of NAFLD has since been described in other populations, including in Europe and the United States.et al.et al. studied the effect of aging on NAFLD in detail and found that aging is a significant nonmodifiable risk factor for NAFLD in premenopausal women independent of weight gain and metabolic syndrome.P < 0.01) older than lean non‐NAFLD individuals, while this difference was reported to be 3.79 (95% CI 2.38–5.20) years in the previous study.Our study found that lean NAFLD patients were significantly older than lean non‐NAFLD controls. This is different from that found by Sookoian All components of metabolic syndrome  along with UA were present in both lean and nonlean NAFLD patients. Even in lean patients, NAFLD was characterized by the presence of significantly higher BMI and WC than non‐NAFLD controls. WC is a surrogate of visceral obesity.vs others) where some interesting findings were noted. A significantly higher mean difference was noted in BMI, WC, HOMA‐IR, ALT, and AST for hospital‐based studies and in BP, lipid profiles, uric acid, and GGT for population‐based studies. Several possible reasons could explain this difference. As some of the participants in hospital were more likely to have some sorts of illness or comorbidities, they might have been taking medications for BP, lipid profile, or even uric acid. This may explain the lower values of these pooled parameters in the hospital‐based population. While the anthropometric parameters, which do not change immediately on medication and which are expected to be higher in symptomatic NAFLD individuals coming to take health care service, were found high in the hospital‐based population. On the other hand, nearly all the parameters showed a higher mean difference in Eastern studies rather the non‐Eastern ones. Although overall population of the Eastern studies were highly heterogenous, the ethnic characteristics shared by Japanese, Chinese, and Korean population might explain the difference than other studies comprising Indian, Iranian, and American population of mixed ethnicity. Overall, our findings suggest that if lean people have any suspicious rise of these risk factors' parameters, they should be screened for NAFLD. Also, lean‐NAFLD patients with symptoms and/or comorbidities need to be treated aggressively and monitored closely for compliance, and lean people of Eastern origin if screened positive for NAFLD should be given proper attention as required.FBS showed less heterogeneity among Caucasian people and in population‐based studies. Most of the heterogeneity in FBS was explained by Asian, and hospital‐based studies. HbA1c, BP (SBP and DBP), lipid profiles , and UA showed considerable heterogeneity across different ethnicity and study design. The random effect model analysis showed that all these variables were significantly higher in lean NAFLD patients than non‐NAFLD controls (except HDL which was significantly lower). These findings are consistent with that of Sookoian and PirolaUric acid was found to be an independent risk factor for NAFLD in lean person by several other studies conducted in IranThe meta‐regression analysis showed that the presence of higher DBP, HOMA‐IR, and UA in both lean and nonlean patients were independently associated with NAFLD irrespective of BMI and WC. Therefore, NAFLD could be considered an important but separate component within the spectrum of metabolic syndrome which interacts with other components and influences each other. This hypothesis is strengthened by several other studies where the authors suggest that NAFLD works as a precursor of metabolic syndromePNPLA3 (rs738409 C > G), TM6SF2 (rs58542926 C > T), MBOAT7 (rs641738 C > T), and GCKR (rs1260326 C > T). However, there is a paucity of literature regarding specific genetic markers among lean NAFLD patients. Mixed findings are reported regarding frequency of PNPLA3 and TM6SF2 variants when compared between lean and nonlean NAFLD patients.IFNL3, CETP, and PEMT has been shown to be associated with the progression of NAFLD among lean or nonobese individuals by several studies.Taken together, patients with lean NAFLD, who do not have any infectious‐inflammatory and drug causeet al. found that NAFLD patients showed a distinct bacterial community with a lower biodiversity and a far distant phylotype compared to control group, and fecal and blood microbiota profiles showed different patterns between subjects with obese and lean NAFLDFecal, gut, and blood microbiome has recently been brought into focus as probable risk factors for NAFLD in lean patients.Several studies also found significant associations of serum sialic acid,et al.The meta‐regression results also indicated that serum levels of AST and GGT, but not ALT were markedly modulated by the presence of NAFLD. Sookoian and Pirolaversus nonlean NAFLD in our study found that almost all the components were present in significantly higher amount among nonlean subjects. A higher BMI and visceral obesity may explain this difference. It is obvious that nonlean (overweight/obese) NAFLD patients are in need of stringent management of weight and other metabolic parameters. However, our study results emphasize the importance of this strategy for both lean and nonlean NAFLD patients.Finally, the comparison of risk factors between lean To summarize, lean and nonlean NAFLD patients share similar cardiovascular and metabolic risk factors. Genetic, microbiological, and other metabolic factors warrant further investigation to identify unique determinants of NAFLD in lean individuals. Regardless of the underlying mechanisms, lean NAFLD needs to be given appropriate clinical attention similar to that of nonlean NAFLD.The current study was limited in several aspects. Selected articles were mostly heterogenous and mostly it was due to the inclusion of the studies from different ethnic origin as well as inclusion of both hospital‐ and population‐based studies. Even within a unique ethnic setting, separate studies were considerably heterogenous with respect to different variables under consideration. This indicates remarkable individual differences in risk factors within same ethnic population. Also, a separate analysis for different BMI cut‐off points used in definition of lean and nonlean was not possible. Therefore, implication of the risk factors of NAFLD with respect to Asian population, where a different BMI cut‐off point for overweight and obesity often used could not be determined. Many authors did not report separate analysis for male and female. Therefore, a sex‐based subgroup analysis was not possible. Multivariate analysis to determine independent associations between risk factors and lean‐NAFLD could not be done, because of unavailability of data, leading to an inference of only general associations among different risk factors and NAFLD.The strength of the study was its large sample size of 69 038 individuals, comprising 6768 lean NAFLD patients, 9253 nonlean NAFLD patients, 43 398 lean controls, and 9619 nonlean controls. Also, consistent findings across different cardiovascular and metabolic risk factors strengthened our results. Hope that the study could be used as an update of previous metanalysis in this topic and will be evident for future clinicians as well as policy makers.NAFLD could be considered a part of an interactome of metabolic syndrome components working in a coordinated fashion to develop chronic diseases and complications involving different systems of the body. Therefore, to incorporate NAFLD within the definition of metabolic syndrome extensive research is necessary. Well‐designed case–control and cohort studies for risk factor analysis of both lean and non‐NAFLD are lacking. Multivariate analysis of risk factors is also warranted. Further explorative research on unique determinants of lean‐NAFLD are recommended.In conclusion, Age, BMI, WC, BP, FBS, HbA1c, insulin resistance, uric acid, TC, LDL, HDL, and TG are the important risk factors of NAFLD shared equally among lean and nonlean. In other words, lean and nonlean NAFLD are anthropometrically different but metabolically similar entities. The findings provide a scientific basis for a further understanding of the nature of NAFLD in lean individual, and might provide a guide to determine the management strategies for lean‐NAFLD.AppendixS1. Supporting information.Click here for additional data file.


It is known that lifestyle factors affect sporadic miscarriage, but the extent of this on RPL (recurrent pregnancy loss) is less well known. A systematic review and meta-analysis was performed to assess the associations between lifestyle factors and RPL. Studies that analysed RPL in the context of BMI, smoking, alcohol and caffeine intake were included. The primary and secondary outcomes were odds of having RPL in the general population and odds of further miscarriage, respectively. Underweight and women with BMI > 25 are at higher odds of RPL in the general population . In women with RPL, having BMI > 30 and BMI > 25 has increased odds of further miscarriages . The quality of the evidence for our findings was low or very low. Being underweight and BMI > 25 contributes significantly to increased risk of RPL . BMI > 25 or BMI > 30 increases the risk of further miscarriages (RPL population). Larger studies addressing the effects of alcohol, cigarette smoking and caffeine on the risk of RPL with optimisation of BMI in this cohort of women are now needed. It is the most common complication of early pregnancy, affecting 15–20% of all pregnancies2. Recurrent pregnancy loss (RPL) is defined by the European Society of Human Reproduction and Embryology (ESHRE) as 2 or more consecutive miscarriages, occurring in 1–2% of couples3. However, many other countries have adopted the term ‘recurrent miscarriage’ (RM), defined as the occurrence of 3 or more consecutive miscarriages occurring in 1% of couples.Spontaneous early pregnancy loss (or miscarriage) is described as any pregnancy that fails to progress beyond 24 weeks, resulting in death and often expulsion of the embryo or fetus4. Standard investigations will be normal for many couples and the cause of RPL is deemed ‘unexplained’ in around 50% of cases.RPL is a complex disease where causation has been attributed to numerous factors including those related to chromosomal abnormalities, immunological and immunogenic, endocrinological, DNA fragmentation in the sperm, impairment in the biosensor function of the endometrium as well as lifestyle influences5. It is now clear that the peri-implantation intrauterine environment is a key determinant of pre-implantation embryo development and early programming6. For example, differences in a women’s diet can significantly alter the amino acid milieu within human uterine fluid7. The literature studying the effects of various lifestyle factors on RPL has not been comprehensively reviewed and current recommendations3 are based on evidence from studies on a population who have had sporadic miscarriages. These findings may not be extrapolated to those with RPL. Isolated miscarriages are associated with an abnormal embryonic karyotype, however as the number of consecutive miscarriage increases, the frequency of abnormal embryonic karyotype significantly reduces8. This suggests that the impact of lifestyle may be more significant on the RPL population compared to those with an isolated early miscarriage.Lifestyle factors are modifiable and in many instances optimisation of these enhances the chances of a positive reproductive outcome. Whilst the specific mechanisms leading to early pregnancy loss is still relatively unknown, poor lifestyle is associated with a hostile reproductive environment whereby optimal embryo implantation and securement of a pregnancy is compromisedThis systematic review and meta-analysis will investigate the impact of female lifestyle factors, namely BMI, smoking, caffeine and alcohol on RPL in the general population as well as further miscarriage in the RPL population. This would help in understanding probable associations to improve patient management.Electronic databases: Medline, Embase, Cochrane Library and CINHL were used to conduct a comprehensive search of original and review articles addressing lifestyle and miscarriage history (see Full text manuscripts were reviewed for relevancy (KYBN and GC). Studies were included if they explored women of reproductive age who had been exposed to an aspect of female lifestyle, such as obesity, being overweight or underweight, smoking, alcohol intake and caffeine intake. We excluded studies which assessed the effectiveness of an intervention aimed at altering lifestyle and studies which assessed lifestyle factors in the context of IVF outcomes or associations with PCOS. The primary outcome assessed was the risk of having RPL in the general population. The secondary outcome was the risk of having a further miscarriage in the RPL population. We define RPL as 2 or more consecutive spontaneous early pregnancy losses (or miscarriages). We define spontaneous early pregnancy loss as any pregnancy that fails to progress beyond 24 weeks.We screened all studies, reviewing full papers where required and disregarding those that did not meet the eligibility criteria using a double-blind approach. All studies were assessed by KYBN and GC independently and any disagreement was discussed and then a decision made for inclusion or exclusion. A third reviewer was called to settle any disagreements where necessary. Authorships and data sources were crosschecked and any duplications were excluded.9.Each study was assessed for quality of parameters including study design, population size, RPL definition, classification of lifestyle parameter, and miscarriage confounding factors. These are detailed in the Supplementary Table The association of female lifestyle factors and risk of RPL are presented in this review. Results from all studies that fulfilled the inclusion criteria were summarised together with the information about the study (Supplementary Tables 2 ≥ 50%) or fixed effects  meta-analysis10. Mantel–Haenszel was the statistical test used for the meta-analyses as it allows for the investigation of association between a binary predictor and binary outcome for observational studies10. Results are presented as odds ratios (ORs) and 95% confidence intervals (95% CI) for the association between lifestyle factors and risk of RPL in the general population or risk of further miscarriage in the RPL population. Results were deemed as significant when P < 0.05. For statistical analysis and generation of forest plots, RevMan version 5.4  was used. Where the data were recorded in differing methods or units, a meta-analysis was not performed. In these cases a narrative summary of the findings was carried out.Results from different study designs were reviewed separately. Individual study estimates were pooled using random effects , resulting in a discrepancy of up to a BMI of 1.5. Despite this, the ‘underweight’ and ‘normal’ BMI categories from different papers were combined for the purposes of meta-analyses. With the effect of BMI on RPL, a distinction was made in the analysis of RPL within the general population and further miscarriage in the RPL population.Analysis of the effect of caffeine intake, cigarette smoking and alcohol consumption on RPL looked at RPL within the general population. For meta-analysis of the association between caffeine intake and RPL, datasets were combined for lower caffeine intake of < 99 mg/day and higher caffeine intake of > 99 mg/day. For cigarette smoking, datasets of non-smokers and current smokers were combined. For consumption of alcohol, datasets of non-drinkers and women who consumed alcohol were combined.11. The systematic search identified a total of 24, 705 records and an additional 194 records through hand-searching of references. 16 studies were included in this systematic review and meta-analysis27. None of these studies were RCTs; there were 8 case control studies, 6 cohort studies, 1 survey-based study and 1 cross-sectional study. Supplementary Tables The PRISMA flow diagram details our search results Fig. 11. The s27.Supplementary Table 15 showed that within the general population, the odds of having RPL is significantly higher in women with BMI > 25 compared to those with normal BMI   . The quality of evidence for the association between caffeine intake and RPL risk was low as they were all observational studies  and high stress levels  in women with RPL compared to those who did not16. However, with both studies it is not possible to determine whether increased stress is the result of RPL or a contributing factor to RPL (i.e. stress being an exposure prior to pregnancy losses).Supplementary Table 14. Although plasma folate levels were not significantly associated with repeat miscarriages, women taking folate supplements were found to have an increased risk of RPL compared to women who were not taking daily folic acid supplements  in crude analyses. However, in this cohort, women taking folic acid supplements were significantly older and took longer to conceive compared to non-supplement takers.Only one study  (Supplementary Table 9. This implies that the true effect may differ from the estimate (when evidence is low) or the true effect is likely to be substantially different from the estimated effect (when evidence is very low). The main limiting factor in the quality of the evidence is clinical heterogeneity and inconsistency of results across a small number of studies. We did not identify any RCTs from this review.In this systematic review and meta-analysis, we showed that the odds of having RPL in the general population is increased in the underweight and BMI > 25 subgroups by 1.2-fold compared to those with normal BMI. The risk of having further miscarriage in the RPL population is higher for raised BMI and this effect is further exaggerated when performing subgroup analyses on women with a BMI of > 30; there is a 1.3-fold and 1.7-fold increase in risk of further miscarriage in the BMI > 25 and BMI > 30 subgroups respectively. Meta-analyses of other lifestyle risk factors, including alcohol intake, cigarette smoking and higher caffeine intake have shown no increased risk of RPL, although evidence is limited to very few studies. All studies in this review were observational, with the quality of the evidence presented being low or very low28. The epigenetic effects on the fetus and the transgenerational effects has provided even stronger arguments for optimising lifestyle in early pregnancy establishment. Studies have shown significant impacts of preconception maternal diet on fecundity; lower intakes of fruit and higher intakes of fast food are both associated with longer time to pregnancy and infertility29. Although there have been meta-analyses on lifestyle and its effects on fertility and sporadic miscarriage or spontaneous abortion, the effect of modifiable factors, including lifestyle on RPL has been less well explored. The cause of RPL remains elusive, and although commonly clinicians and patients look to optimising lifestyle, there is limited data available on lifestyle impacts in the cohort of patients affected by RPL.Optimising lifestyle parameters in the peri-conceptional period has been the focus of management of reproductive failures including RPL and infertility30. The effects of being overweight and obese are exaggerated in the RPL population compared to the population with an isolated miscarriage; a meta-analysis of 32 studies identified an increase in the relative risk (RR) of clinical miscarriage in overweight women  and obese women 31. Obesity has significant impacts on female reproductive health and an increased BMI is associated with infertility, poor outcomes after fertility treatment, and pregnancy loss33. Although gradual weight loss has been shown to improve fertility outcomes33, there have been no studies to date assessing the effect of weight loss on RPL. Moreover, the exact cause of obesity related increase risk of RPL is unknown. An unfavourable endometrial milieu associated with obesity is one possible explanation, and the possibility of oocyte abnormality in obese women is another explanation34. However, the latter has been refuted by a study of obese women receiving oocyte donation who experienced a higher rate of miscarriage compared with those of normal BMI35. There are also various immunological pathways that may play a role in miscarriage. For example, high levels of C-reactive protein (CRP) and interleukin- 6 (IL-6) are present in obesity as well as women with RPL38, and this state of ‘chronic inflammation’ may contribute to impaired implantation and placentation, as well as complications in pregnancy and post-partum39. It is likely that unfavourable reproductive environmental exposures within obese women negatively impact the development of the oocyte, the ability for oocyte to be fertilised and the ability for healthy embryo implantation and development.In this review we have identified BMI > 25 to be a significant modifiable risk factor for RPL within the general population and further miscarriage within the RPL population, compared to those with normal BMI. These results are in agreement with an earlier meta-analysis performed which included 2 studies, showing an increased odds of further miscarriage in the RPL group in obese women compared to those with normal BMI 40. However, when focussing on the risk of RPL the evidence remains conflicting and the meta-analysis performed in this study shows an increase in RPL risk in underweight women in the general population but no increase in the risk of further miscarriage in the RPL population. The quality of evidence is very low given the inconsistency in findings across a small number of studies.One large case control study has previously shown that being underweight is associated with sporadic first trimester miscarriage41. Several components of tobacco smoke are toxic for the fetus; these include nicotine, carbon monoxide and cyanide. Nicotine reduces blood flow through the placenta through its vasocontrictive effects, and carbon monoxide binds to haemoglobin, causing both fetal and maternal hypoxia, which may interfere with the development of the conceptus42. We did not identify any studies that assessed the associations between e-cigarettes/vaping and RPL risk in this review. Further studies exploring the impact of e-cigarettes and vaping on miscarriage and RPL risk are warranted, especially as these behaviours are increasingly common in women and their partners who are attempting to either reduce or stop cigarette smoking with the aim of achieving a successful pregnancy. The data for alcohol consumption has been inconsistent but various studies have suggested that alcohol consumption during pregnancy increases the risk of miscarriage, with an upper limit of 2–4 drinks per week44. Additionally, a recent systematic review of quasi-experimental studies have shown a likely causal detrimental role of prenatal alcohol exposure on cognitive outcomes and effects on lowered birth weights45; hence the latest guidance from the NHS is to abstain from alcohol whilst trying to get pregnant, as well as through the duration of the pregnancy46. Caffeine crosses the placenta, reaching the fetus whose metabolic rate is low secondary to low enzyme levels. Previous studies have associated increasing caffeine intake  with early and late miscarriage and stillbirth risk49. However, in this review we did not perform meta-analyses on caffeine intake of > 300 mg/day as the two studies included had very low numbers of women with this level of caffeine intake.Our review has shown no increased risk of RPL in the general population in cigarette smokers compared with non-smokers, in women who consume alcohol compared to those who do not consume alcohol, or in women with a higher level of caffeine intake compared to lower intake. We were not able to further stratify risk based on quantity of cigarettes smoked, intake of alcohol or caffeine due to variations in recording of data between studies. A systematic review performed showed that cigarette smoking does mildly increase the risk of sporadic miscarriage  and that exposure to secondhand smoke increases the risk of miscarriage by 11%The main limitations of this systematic review and meta-analyses is the diversity in the methodology and methods of reporting RPL. Although most studies included women with ‘three or more consecutive miscarriages’, some studies included women with ‘two or more miscarriages’ and some have not been strict in whether it is consecutive. The heterogeneity of the populations may also limit conclusions drawn from our study. For example, the confounding effects of diabetes or PCOS have not been addressed and may affect the risk of RPL. The data captured by studies in this review relate to the lifestyle reported at the time of the study and does not capture the pre-pregnancy lifestyle parameters and whether there have been any behavioural modifications. This systematic review was also limited to studies in English. We did not explore the impact of male lifestyle parameters on the risk of RPL.Despite the limitations, we have shown that several lifestyle parameters are associated with risk of RPL in the general population and further miscarriage in the RPL population. Further large observational or clinical studies are required to delineate the true effects. The biological mechanisms of possible effect also need exploring. For example, the immunological contributions of increased BMI to RPL risk, and the effect of interventions aimed at weight loss in overweight/obese women with history of RPL are areas still needing review.Being underweight and having BMI > 25 contributes significantly to RPL in the general population by 1.2-fold. BMI > 25 also significantly increases the risk of further miscarriage in the RPL population by 1.2-fold and in women with BMI > 30 the risk of further miscarriage is increased by over 1.7-fold. Although our systematic review and meta-analysis has not shown an increased risk of RPL with lifestyle parameters such as smoking, alcohol intake and higher caffeine intake, these require further exploration. Current studies are heterogeneous and there remain difficulties in pooling the data due to inconsistencies in methodology and reporting. There is a need for larger observational or clinical studies addressing the dose effects of alcohol, cigarette smoking and caffeine in this cohort of patients. Studies addressing the impact of lifestyle interventions in the RPL population would also be of benefit to improve patient management.Supplementary Information.