Previous epidemiological and other studies have shown an association between ischemic stroke (IS) and frozen shoulder (FS). However, the causal relationship between them remains unclear. Therefore, the present study aimed to investigate the causal relationship between IS and FS using a two-sample Mendelian randomization method.n = 440, 328) and its subtypes (large-artery atherosclerotic stroke (LAS), cardioembolic stroke (CES), and stroke caused by small-vessel disease (SVS) and lacunar stroke  as exposure data. Additionally, we selected a large sample of FS as outcome data . Inverse variance weighting (IVW) was applied as the primary analysis method. The weighted median, MR-Egger, simple model, and weighted model were used as complementary analysis methods to assess causal effects. Moreover, heterogeneity was analyzed using Cochran's Q-test with IVW and MR-Egger. The MR-Egger intercept and MR-PRESSO analysis methods were used for pleiotropy testing. The stability of the results was also assessed using a leave-one-out analysis.Our research was divided into two stages: discovery and replication. The data were extracted from publicly available genome-wide association studies (GWAS). We selected a large sample of IS  of 1.207 with a 95% confidence interval (CI) of 1.027–1.417 and a Our study confirmed the causal relationship between any IS level and increased risk of FS. Furthermore, the same results were obtained in the replication stage with lacunar stroke as an exposure factor. However, there was no direct causal relationship between the subtypes of IS and FS. Our study provides theoretical support for shoulder care for patients with IS. Frozen shoulder (FS), which is also referred to as adhesive capsulitis, has a prevalence rate of 2–5% in the population , more coP < 0.001)  . On the < 0.001) , 14. EarFrom observational studies, it is suggested that IS and FS show a positive association , 15. HowOur study used a large-scale genome-wide association study (GWAS) database to assess the causal relationship between IS and its subtypes and FS through a two-sample MR study analysis.To be an effective tool for causal reasoning in MR studies, genetic variation must meet three core assumptions. Assumption 1: Genetic variation as an instrumental variable must be truly correlated with exposure (IS). Assumption 2: Genetic variation was not associated with exposure-outcome confounders. Assumption 3: Genetic variation affects outcome (FS) only through exposure (IS), independent of other pathways , 21. FigP < 5.00E-09) and its subtypes (P < 5.00E-06). We eliminated linkage disequilibrium  and excluded palindromic SNPs with moderate allele frequencies. In addition, we quantified the strength of the genetic instrument for all SNPs with an F-statistic calculated as (β2/se2) and as a follow-up analysis for instrumental variables (IVs) with an F-statistic higher than 10 , cardioembolic stroke (CES), and stroke caused by small-vessel disease (SVS). The data on IS and its subtypes used in our study were obtained from a GWAS summary encompassing 520,000 individuals and carried out by multiple consortia, including the International Stroke Federation . The IS  than 10 . We used than 10 .P < 5.00E-08), eliminated linkage disequilibrium , and excluded palindromic SNPs with medium allele frequencies. Finally, three SNPs were left as instrumental variables for the validation phase of the analysis. Detailed information on the IVs is provided in In the replication stage, we relied on a GWAS meta-analysis of a European population that included 6,030 cases and 248,929 controls, which covered almost 7 million SNPs. The meta-analysis combined data from prior GWAS, the International Stroke Genetics Consortium, and the UK DNA Luminal Stroke Study, providing an abundant and comprehensive dataset  in R (version 4.1.2) was used to analyze the data between exposures and outcomes . The priIn addition, we will perform a series of sensitivity analyses, including heterogeneity and pleiotropy. IVW and MR-Egger regression were used to test for heterogeneity, and Q statistics were produced to quantify it . In caseTo prevent bias in the results caused by individual SNP pleiotropy, we conducted a leave-one-out analysis to examine the impact of each SNP on the causal relationship between IS and FS risk . The preThe causal relationship between the levels of IS and its subtypes and FS risk was explored by two-sample MR analysis and validated using lacunar stroke data. Our MR results revealed a causal association between genetic susceptibility to IS and increased risk of FS, but no association was found in subtypes of IS. Moreover, a causal association between lacunar stroke and increased risk of FS was also revealed in the replication phase.P = 0.022). However, no correlation was found between subtypes of IS and FS risk  (P = 0.567) and IVW  indicated that there was no heterogeneity in the study  and the MRPRESSO global test  showed no signs of pleiotropy  . In the he study . Additioeiotropy . Figure eiotropy . SupplemP = 0.0004; Weighted median, OR = 1.241, 95% CI: 1.062–1.450, P = 0.007) (P = 0.597), simple mode , and weighted mode . Nevertheless, the conversion of odds ratio values indicated a consistent direction, indicating that the level of lacunar stroke is a risk factor for FS. Additionally, the MR-Egger intercept test showed no indication of pleiotropy . The number of final IVs was too small and did not allow for the MRPRESSO test. Our examination of the PhenoScanner database (www.phenoScanner.medschl.cam.ac.uk) failed to reveal any SNPs associated with potential confounders for FS, confirming the robustness of our findings. As lacunar stroke represents a significant indication of cerebral small vessel disease and comprises 25% of IS cases, we opted for lacunar stroke as our replicated exposure data stage . We fina= 0.007) . No signDamage to the blood vessels in the brain often causes abnormalities in the central nervous system, which can result in somatosensory abnormalities, manifesting symptoms such as shoulder and low back pain. In addition, stroke often causes hemiplegia of one limb, resulting in hemiplegic shoulder pain. According to a study that followed 416 patients for a year, roughly 33% of the patients experienced shoulder pain following a stroke, and the majority of these patients reported moderate to severe levels of pain . In a reHowever, the causal relationship between IS and FS remains unclear. Most of the previous epidemiological studies were case-control designs or cross-sectional studies with a hazy chronological order that failed to clarify causality. Furthermore, past observational studies were plagued by insufficient sample numbers, difficulty avoiding reverse causation, and confounding factors. Therefore, we performed an MR analysis to explore the relationship between IS and FS from a genetic perspective.In the current investigation, we discovered a causative relationship between IS and FS and confirmed this association by observing the same causal relationship in patients with lacunar stroke. However, no connection was discovered in the three most frequent IS subtypes. We believe that more research is needed to analyze our findings, maybe due to the small sample size of IS subtypes. The analysis of a larger sample of IS subtypes may be pursued in the future. The risk of developing FS is elevated with any IS, likely due to the somatosensory abnormalities resulting from lesions in the central nervous system post-stroke . On the F > 10) as instrumental variables, and the experimental design was similar to randomized controlled trials. Randomized controlled trials are commonly employed in clinical practice and are considered to provide a high level of evidence. However, they have drawbacks, such as being costly and having limited sample sizes. The MR study approach effectively avoids reversing causality and confounding factors. Second, the data we used were all from the GWAS database, which is European population samples, effectively reducing the bias of population heterogeneity. Third, we validated the results of the discovery phase to confirm that the results obtained were reliable. The results of our analysis may have implications for healthcare policy. Revealing a causal relationship between IS and FS may influence public health policies regarding prevention and treatment.The advantages of our two-sample MR study are as follows. First, we used the MR analysis method, using SNPs with high association strength (Nonetheless, our study does have certain limitations. First, the leave-one-out method for the subtypes of IS in this study needed to be revised, possibly due to the small sample size. Our study found a causal association between lacunar stroke on the increased risk of FS during the replication phase but did not find an association in subtypes of IS. This implies that we should interpret the correlation between FS and IS subtypes with caution and investigate their association in future studies with larger sample sizes. Second, the prevalence of IS and FS differed between males and females. However, our data were all obtained from public databases, which did not allow for factor-specific subgroup analyses such as age and sex. Third, all subjects included in the GWAS data were of European descent, and further research is necessary to determine whether the findings can be extrapolated to other populations. Fourth, increasing the sample size of GWAS can improve the strength of IV, and we need larger scale GWAS for in-depth study.In conclusion, our MR study supports a causal association between IS and increased FS risk, but no relationship was found in IS subtypes.The original contributions presented in the study are included in the article/XL, ZH, FL, SL, HG, JD, and XD: study design, data collection, and statistical analysis. J-HQ, QN, and JL: supervision. XL, ZH, and FL: writing—original draft. SL, HG, J-HQ, QN, and JL: writing—review and editing. All authors contributed to the article and approved the submitted version.


Environmental tobacco smoke (ETS) is associated with several congenital anomalies, including non-syndromic orofacial clefts (NSOFCs). This systematic review aimed to update the literature on the association between ETS and NSOFCs.Four databases were searched up to March 2022, and studies that evaluated the association between ETS and NSOFCs were selected. Two authors selected the studies, extracted the data, and evaluated the risk of bias. Comparing the association of maternal exposure to ETS and active parental smoking with NSOFCs allowed for the creation of pooled effect estimates for the included studies.Twenty-six studies were deemed eligible for this review, of which 14 were reported in a previous systematic review. Twenty five were case-control studies, and one was a cohort study. In total, these studies included 2142 NSOFC cases compared to 118129 controls. All meta-analyses showed an association between ETS and the risk of having a child with NSOFC, based on the cleft phenotype, risk of bias, and year of publication, with a pooled increased odds ratio of 1.80 (95% CI: 1.51–2.15). These studies had a marked heterogeneity, which decreased upon subgrouping based on the recent year of publication and the risk of bias.ETS exposure was associated with more than a 1.5-fold increase in the risk of having a child with NSOFC, showing a higher odds ratio than paternal and maternal active smoking.The study is registered on the International Prospective Register of Systematic Reviews database # CRD42021272909. Smoking may be active or passive. According to the World Health Organization, active smoking is defined as smoking at least one cigarette a day. In contrast, passive smoking is the inhalation of tobacco smoke, also known as secondhand smoke or environmental tobacco smoke (ETS)3.Smoking has been a controversial topic for decades; it remains one of the leading causes of lung cancer in men and breast cancer in women4. ETS and active smoking have also been positively associated with congenital anomalies such as neural tube defects5, congenital heart defects6, and non-syndromic orofacial clefts (NSOFCs)9.A recent study reported that ETS increased the risk of developing cardiovascular diseases by 28% and its associated mortality rate by 12%. Individuals affected by ETS are exposed to tobacco smoke at home, at work, and in public places10. This condition affects the quality of life; many patients with OFC develop depression, anxiety, lack of self-esteem11, speech defects, facial deformities, and several dental problems, including malocclusion12. The treatment of OFCs necessitates a multidisciplinary approach, with treatment ranging from infancy through late adolescence13.Syndromic orofacial clefts (OFC) are associated with structural or developmental defects, whereas NSOFCs are isolated and unrelated to other abnormalities14. In 2004, a systematic review and meta-analysis, including 24 case-control studies, evaluated the association between maternal active smoking and the risk of having a child with NSOFC. They reported a modest dose-response effect for cleft lip with or without cleft palate15. In 2014, a systematic review and meta-analysis, including 14 case-control studies, evaluated the association between ETS and the risk of having a child with NSOFC and reported a positive odds ratio8. They also recommended further investigation to provide solid grounds for nicotine exposure8.Globally, the prevalence of NSOFCs is 1.25 per 1000 live birthsSince then, many studies have assessed the association between ETS and NSOFCs, and there is a need to update newly published evidence and evaluate the current evidence. Therefore, this systematic review and meta-analysis aimed to update the previous systematic review that pooled studies published up to 2013 by evaluating and comparing the evidence that investigates the association between maternal ETS exposure and NSOFCs in recent studies and published meta-analyses. In addition, it evaluates and compares paternal smoking with ETS exposure, which was not previously assessed.16 were followed, and the findings were reported according to the PRISMA statement17.The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines8. The search was not limited to studies published in English-language articles. A manual search of reference lists from identified published work and Google Scholar were also used to search for potentially eligible studies. Medical Subject Headings keywords were used to build a comprehensive search query. Repeated studies were detected and deleted using the EndNote reference manager .All relevant studies from 1980 to 2022 were identified. A comprehensive search of electronic databases, PubMed, Web of Science, Scopus, and ScienceDirect, between 2013 and March 2022. Studies published before 2013 were identified and recruited from the previous systematic reviewThe following search terms were used: [(cleft lip) OR  OR ] AND [(passive smoking) OR (tobacco smoke pollution) OR  OR (smoking)].Two researchers (AB and SG) were involved in the search strategy. All titles were independently reviewed by two researchers (OA and KH). All duplicates were excluded. Case-control, cohort, and cross-sectional studies that investigated the association between ETS and NSOFCs were included. Studies associated with syndromic OFCs, those that measured active smoking only, and those including genetic models were excluded.18: Participants (studies assessing the etiology of NSOFCs), Intervention or exposure (ETS), Comparison , and Outcomes (NSOFCs).Studies included in this review were selected in accordance with the PICO elementsThe inclusion criteria included case-control, cohort, and cross-sectional studies investigating the association between ETS and NSOFCs. Studies with a design other than the types mentioned in the inclusion criteria, those associated with syndromic OFCs, those that measured active smoking only, and those including genetic models, were excluded.in vitro studies, and descriptive studies, including case reports and case series, were also excluded.Other studies, such as editorials, letters to the editor, pilot studies, historical and literature reviews, Two reviewers (KB and HJ) independently assessed the titles and abstracts of all the identified studies to determine if they met the inclusion criteria. The full-text articles of the selected studies were independently assessed by the same reviewers. Any disagreement between the two reviewers was resolved by consulting a third reviewer (HS). For studies performed on the same sample, studies with additional data were chosen. Two reviewers (KB and HS) assessed the selected articles using a standardized protocol, and the extracted data were recorded in a specific extraction datasheet. The extracted data included author names and citations, site, country, duration of data collection, study design, reported period of maternal exposure, total sample size, percentage of non-smoking mothers exposed to passive smoking and total non-smoking mothers, reported adjusted p-value, and adjusted odds ratio  for passive smoking, maternal smoking and total sample size, and paternal smoking and total sample size.Quality assessment and the risk of bias19. The scale has a minimum score of 0 and a maximum of 9. It measures the selection of the cases, controls, and cohorts and how they represent the general population; the compatibility of cases, controls, and cohorts based on design and analysis; the exposure ascertainment of case controls; and the outcome of cohorts and the adequacy of their follow-up period. Studies that scored >6, 4–6, and ≤3 showed a low, moderate, and high risk of bias, respectively. Studies of moderate and high methodological quality (>5 stars) were included in the meta-analysis8. In case of any discrepancy between the two authors, the values were discussed until agreement. The level of agreement between the two authors was evaluated using the kappa score. Grading of Recommendations, Assessment, Development and Evaluations (GRADE) was used to summarize and assess the confidence of evidence and the strength of recommendations. It consists of five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias.Both cohort and case-control studies in this review were assessed independently using NOSData from the included studies were compiled. The data were organized according to author names and citations, site, duration of the data collection, study design, reported period of maternal ETS exposure, total sample size, percentage of mothers exposed to ETS with their respective p-values and odds ratios, percentage of maternal smoking and total sample size with their respective odds ratios, percentage of paternal smoking, and total sample size with their respective odds ratios, and risk of bias. If needed, a meta-analysis of the association between NSOFCs and ETS was performed.2 index were used to check for study heterogeneity. I2 statistic was classified into moderate heterogeneity (30% to 60%), substantial heterogeneity (50% to 90%) and considerable heterogeneity (75% to 100%)20. When there was a study’s heterogeneity, a random-effects model was conducted.Both quantitative and qualitative syntheses were performed wherever possible. Studies that compared the association of ETS with different cleft subtypes, including cleft lip (CL) and cleft palate (CP), were presented separately. Quantitative synthesis requires a minimum of two investigations. RevMan was used to conduct the meta-analysis . Cochran’s test and Higgin’s ISensitivity analyses based on subgroups were carried out according to the quality of the studies, the year of publication, and cleft types. Additionally, we assessed active parental smoking in the included studies and compared the results. The formal method of combining individual study data was the odds ratio for individual studies. Subgroup differences were tested using chi-squared. A funnel plot was used to visually assess the probability of small-study effects. Egger’s test was used to evaluate publication bias. The significance level was set at p<0.05.http://www.hrc.es/investigacion/metadisc_en.htm) to assess the possible effects of the year of publication, the quality of the study, and the type of smoking on the association between ETS and NSOFCs. All variables entered in the model were binary.Additionally, meta-regression analysis was performed using Meta-DiSc version 1.4 , focusing on the genetic effects of smoking on newborns (one study) and an overlapping population (one study) . Finally, 12 articles met the inclusion criteria for this systematic review and were suitable for inclusion in the qualitative synthesis (Supplementary file Table 1).30 from the primary systematic review8 were included to update the review of this topic and study its effects over multiple decades. Totally, 26 studies were deemed eligible for this review; 25 were case-control studies40, and one was a prospective cohort study41. The data from the two centers were presented separately in a systematic review by Pi et al.42 (2018 A and B). To collect data on smoking, all of the included studies used self-reported questionnaires. Case-control studies were population-based, hospital-based39, or multi-hospital-based33 . The Supplementary file Table 1 shows the included 11 studies distributed according to the NOS risk of bias scores. Out of these, only two were found to have a low risk of bias42 study to have two parts, A and B), which were then sub-grouped to assess sensitivity . The analysis included 12142 NSOFC cases and 118129 controls. There was a highly significant relationship between ETS and NSOFCs (p<0.01) with an increased odds ratio of having a child with NSOFC   .Year of publication2 =88%), it decreased to 74% in studies published after 2013 compared to those published before 2013. Nevertheless, there were no significant differences between the subgroups (p=0.49) , similar to earlier studies. Even though the overall heterogeneity between studies was high (I(p=0.49) .NSOFC phenotypes7 and one with an extremely high CI28, the odds ratio remained high and significant  , with increased odds ratio of 1.85 (95% CI: 1.46–2.34) for CL or CP and 1.80 (95% CI: 1.47–2.21) for CP. After removing the two studies, one with a high odds ratio for CP) .40. Only one of these studies had a low risk of bias40. Maternal ETS exposure showed a non-significant increase in the OR for both CL  and CP .Only three studies evaluated the CL or CP subphenotypesThe forest plot for the meta-analysis of the association between the risk of having a child with NSOFC and parental active smoking among studies that evaluated ETS showed a significant association with an increased OR between maternal  and paternal active smoking  and NSOFCs. Among the studies that evaluated the paternal active smoking effect on NSOFCs, maternal ETS showed a higher OR . However, there was no significant difference between maternal ETS and paternal smoking subgrouping (p=0.17) .To demonstrate the stability and reliability of the meta-analysis results, a sensitivity analysis was conducted between different study subgroups according to cleft phenotype , the excThe funnel plots for all included studies that assessed the relationship between NSOFC phenotypes (CL or CP and CP) and passive smoking did not have the shape of a funnel. However, it was almost a symmetrical funnel plot around the central line, which indicates a publication bias . However, Egger’s test detected no publication bias.The cumulative meta-analysis figure shows the stability of the evidence from 2011 to 2021. Regarding sufficiency , from the beginning of this cumulative meta-analysis, the 95% CIs around the OR included the final average effect size (ES) obtained at the end of the cumulative meta-analysis. Regarding stability , from the beginning of this cumulative meta-analysis, the mean ES appeared to be stable. Therefore, it would be difficult to argue that a subsequent study would alter the emergent picture of this effect beyond the evidence that the first few studies have produced .2 indicated that 33% of the heterogeneity was accounted for by the addition of predictors to the model compared to an ‘empty’ model. In other words, this represented the percentage of heterogeneity explained by group-level variables in the model .A significant model implies that ES is associated with the variables . There i8. However, paternal smoking in ETS studies and the association between ETS and CL/P subphenotypes (CL vs CLP) were not sufficiently discussed. Therefore, this systematic review was conducted to update the literature. This study consistently suggests a more than 1.5 increase in the risk of NSOFC phenotypes associated with paternal active smoking. A corresponding value of 2.21 was observed with ETS exposure.A systematic review conducted in 2015 assessed the association between maternal ETS exposure and NSOFCs that included studies published between 1980 and 201343. Maternal ETS exposure is associated with multiple birth defects and stillbirth44. ETS has been reported to cause fetal hypoxia, which leads to fetal growth retardation46. In this systematic review, the association and OR between maternal ETS exposure and having a child with NSOFC were significant. The difference between the outcomes of the studies published before and after 2013 was not significant. However, there was a small decrease in the OR (from 1.92 to 1.67), a smaller 95% CI range [from (1.35–2.71) to (1.40–1.99)], and heterogeneity (I2= 93% to 74%), which could be related to the recent improvement in study design and data collection method. Additionally, the studies published after 2013 showed less heterogeneity.In 2020, the World Health Organization highlighted a wide range of adverse health effects of nicotine exposure on infant and child development that result from ETS. They have urged protective policies directed toward smoke-free generations49. Our findings suggest a possible association between ETS and NSOFCs (OR=2.21) that is stronger than that with active paternal smoking (OR=1.51) which could support the indirect effect of paternal smoking by increasing maternal ETS exposure. However, as the difference between the two associations was not significant, this suggestion needs further investigation to verify it.Furthermore, paternal smoking could be associated with having a child with NSOFC either directly by affecting sperm development or indirectly by increasing maternal ETS exposure8. Additionally, this study further assessed the NSOFC phenotype by including three articles investigating ETS association with CL, CLP, and CP formation. The study found an association between an increased risk of CL and CLP, though the available information was inadequate for reporting significant findings. Thus, further studies are needed to evaluate the effects of ETS on different NSOFC subphenotypes.In this systematic review, the OR of maternal ETS exposure and having a child with CL or CP was higher than that of having a child with CP . However50. Although they found no significant reduction in NSOFC prevalence, their results highlight the importance of public health measures, including smoke-free legislation in restaurants and prevention programs among pregnant females in controlling active smoking51.Our study supports the importance of implementing smoke-free legislation. In England and Northern Ireland, a study assessed the impact of smoke-free legislation on the prevalence of NSOFC. A reduction of 37% and 8%, respectively, in smoking was detected among active female smokers between 2000 and 201852. The COVID-19 pandemic has influenced the lifestyles of individuals, affecting their nicotine use and exposure54. However, a slight decrease in ETS was reported due to the lockdown53. This systematic review did not find any studies that evaluated nicotine exposure in NSOFCs after the COVID-19 pandemic. Therefore, future studies should evaluate this period.The current worldwide response to the coronavirus disease 2019 (COVID-19) was a significant and widespread effect on stress and psychological conditionsEven though our meta-analysis included 26 articles, there were a few limitations. The heterogeneity between studies and the restricted high-quality case-control studies were the two main limitations. Thus, meta-analyses of some findings might lack adequate power and not allow accurate evaluation of heterogeneity with small-study effects and reporting biases. Combining evidence is also more challenging in the presence of different confounding variables, such as the frequency and distance of passive smoking. Moreover, there is still limited evidence supporting the effect of ETS on the development of different NSOFC sub-phenotypes and severity. These limitations and gaps in the literature highlight the need for well-conducted cohort studies that consider the definition of passive smoking and the evaluation of nicotine exposure using a validated, exact method instead of a subjective method like a questionnaire.There was a highly significant association between maternal ETS exposure and NSOFCs in children, indicating the importance of implementing smoke-free legislation and maternal pregnancy care. However, the included studies showed marked heterogeneity. Future case-control studies to examine the association between ETS exposure and NSOFCs should consider the definition of ETS and the evaluation of nicotine exposure using an objective measuring tool.Click here for additional data file.


Objective: To evaluate the genetic causality between alcohol intake, smoking, coffee consumption, and arthritis. Methods: Mendelian randomization (MR) studies with alcohol, smoking, and coffee consumption behaviors as exposures, and osteoarthritis (OA) and rheumatoid arthritis (RA) as outcomes were retrieved from up to July 2023. Two researchers with relevant professional backgrounds independently assessed the quality and extracted data from the included studies. Meanwhile, we applied MR analyses of four lifestyle exposures and five arthritis outcomes (two for OA and three for RA) with gene-wide association study (GWAS) data that were different from the included studies, and the results were also included in the meta-analysis. Statistical analyses were performed using Stata 16.0 and R software version 4.3.1. Results: A total of 84 studies were assessed. Of these, 11 were selected for meta-analysis. As a whole, the included studies were considered to be at a low risk of bias and were of high quality. Results of the meta-analysis showed no significant genetic causality between alcohol intake and arthritis (odds ratio (OR): 1.02 (0.94–1.11)). Smoking and arthritis had a positive genetic causal association (OR: 1.44 (1.27–1.64)) with both OA (1.44 (1.22–1.71)) and RA (1.37 (1.26–1.50)). Coffee consumption and arthritis also had a positive genetic causal association (OR: 1.02 (1.01–1.03)). Results from the subgroup analysis showed a positive genetic causality between coffee consumption and both OA (OR: 1.02 (1.00–1.03)) and RA (OR: 1.56 (1.19–2.05)). Conclusion: There is positive genetic causality between smoking and coffee consumption and arthritis (OA and RA), while there is insufficient evidence for genetic causality between alcohol intake and arthritis. Arthritis is an inflammatory disease that occurs in the joints and causes structural damage and pain, with osteoarthritis (OA) and rheumatoid arthritis (RA) being the most common types of arthritis . OsteoarLifestyle provides great influences on arthritis onset and progression, and such is the case for OA and RA ,8. ObserMendelian randomization (MR) is an epidemiological study method that uses genetic variants associated with potential risk factors as instrumental variables (IVs) to explore the genetic causality between exposure and outcome . In MR, In the past few years, the potential causal relationships between arthritis and alcohol, smoking, and coffee consumption have been examined using MR methods ,25,26,27We obtained GWAS datasets from a study of 1.2 million people with alcoholic drinks per week and cigarette smoking initiation . Meanwhiwww.finngen.fi/en, accessed on 7 September 2023), and the three outcomes of seropositive rheumatoid arthritis, seronegative rheumatoid arthritis, and rheumatoid arthritis meeting the definition of M13  were selected.For outcomes, we obtained the GWAS dataset for OA from a genome-wide meta-analysis of up to 826,690 individuals  . The sump < 5 × 10−8 were selected and the SNPs with the linkage disequilibrium effect were removed . We then screened and excluded SNPs (p < 5 × 10−8) associated with confounders (body mass index was removed when OA was used as the outcome) using the PhenoScanner database . In addition, to further exclude possible associations between IVs and outcome, we excluded SNPs associated with outcome (p < 5 × 10−8). We also excluded palindromic variants that could not be oriented . F statistics were also computed, and the selected IVs all satisfied F > 10 to avoid possible bias caused by weak instrumental variables [To ensure that the IVs met the three basic assumptions of MR with sufficient validity, we used stringent conditions to screen single nucleotide polymorphisms (SNPs). First, SNPs significantly associated with exposure at the genome-wide level ariables .2 index and Cochran’s Q statistic were calculated using IVW analyses to assess heterogeneity. Potential horizontal pleiotropy between IVs was demonstrated by the intercept of the MR-Egger method [p < 0.05 and returns the corrected causal effects [The inverse-variance weighted (IVW) method was used for primary analysis, and the weighted model was used for secondary analyses. The IVW method assumes that all IVs are valid, and provides the most accurate estimates based on the calculation of Wald ratios . The weir method . MR-PRES effects .All statistical data analyses were performed using the TwoSampleMR package and the MendelR package in R software version 4.3.1.This study is based on the 2020 update of the (PRISMA-P) guidelines and is registered with PROSPERO (CRD42022375445). We searched the MEDLINE, EMBASE, and Cochrane Library databases using the following key words: alcohol, drinking, smoking, cigarette, coffee, Mendelian randomization, and osteoarthritis, rheumatoid arthritis, arthritis. The search period was from the time that each database was created to July 2023. The search process was not qualified otherwise.Any studies using the MR method to investigate causality between risk factors and osteoarthritis/rheumatoid arthritis or related phenotypes.Any studies on gender, age, cohort, and race.Any studies that include MR as part of their analysis.The inclusion criteria for the retrieved studies were as follows:Any case reports, narrative reviews, or other non-research-based studies.Any studies that did not include alcohol/smoking/coffee consumption in the exposures or OA/RA in the outcomes.Any studies of non-European origin cohorts.Any studies for which the complete English manuscript is not available.The exclusion criteria were as follows:Two trained researchers with relevant professional backgrounds independently read titles and abstracts of the literature. By reading the full text of all articles that met the inclusion criteria, researchers extracted information about specific methods and measures from the study design. We extracted data from the included literature and assessed the study quality based on the Guidelines for Strengthening the Reporting of Mendelian Randomization Studies (STROBE-MR) and its expansion statement, while referring to the Mendelian Randomization Reading Guide ,36,37.p value < 0.05 under a random-effects model was considered statistically significant. Inverse variance weighted (IVW) estimates were used as the primary analysis and the results of the weighted median method (WM) were used as a sensitivity analysis.Meta-analyses were performed using the “metan” command in Stata 16.0 to obtain pooled effect estimates. The primary outcome was the risk of diagnosis and development of arthritis, and subgroup analyses were performed for OA and RA. Since alcohol, smoking, and coffee consumption affect all parts of the body, OA and RA in different parts of the body or different subtypes are considered the same outcome to explore the overall impact on the disease. We used ORs and 95% confidence intervals to report pooled estimates of the causal effect between lifestyle and arthritis, and a two-sided p > 0.05), as well as no outliers in the MR-PRESSO method. Detailed results of the analyses and sensitivity analyses are available in the The results of the MR analyses of lifestyle on OA and RA are displayed in From the databases Medline, Embase, and the Cochrane Library, 23, 52, and 9 studies, were included, respectively. After reading the abstracts of the literature titles by the evaluators and excluding other apparently irrelevant studies, 14 studies were initially included. After reading the full text and excluding three studies that did not contain the index of interest, 11 studies were finally included. All 11 studies were in the English language and conducted by applying MR to alcohol intake, smoking, and coffee consumption as exposures, with OA and RA as the primary outcomes. The studies were published between 2018 and 2022. The included populations were of European origin, and the UK Biobank was the most used study cohort. Study characteristics of all the 11 included literature are shown in To examine the causal relationship between lifestyle and arthritis, a total of two studies related to alcohol intake ,18, fiveWe performed a meta-analysis using a random-effects model on the inverse variance weighted method estimates of the two included studies and our 10 MR analyses. The results showed that alcohol intake was positively associated with arthritis overall (OR: 1.02 (0.94–1.11)), but not statistically significant . SubgrouWe then performed a meta-analysis of the estimates obtained using the weighted median method as a sensitivity analysis to assess the robustness of the IVW analysis. The combined results of the weighted median method under a random-effects model were consistent with previous results, with insufficient evidence of genetic causality between alcohol intake and arthritis overall (OR: 1.09 (0.99–1.19)). Subgroup analyses also reported insufficient evidence to support a genetic causality between alcohol and OA or RA (ORs: OA: 1.08 (0.98–1.20), RA: 1.09 (0.91–1.30)) .We performed a meta-analysis of the estimates of genetic causal effects between smoking behavior and arthritis, with outcomes obtained by the inverse variance weighted method using a random-effects model. The results revealed a positive causal association between smoking behavior and arthritis (OR: 1.44 (1.27–1.64)) . A subgrAs a sensitivity analysis, a meta-analysis of the genetic causal effect estimates of smoking behavior for all arthritis outcomes obtained using the weighted median method was performed. The results of the random-effects model remained consistent with previous studies, reporting a positive genetic causality between smoking behavior and arthritis (OR: 1.42 (1.24–1.63)) . The subA meta-analysis was performed on the estimates of the genetic causal effects between coffee consumption and arthritis with outcomes obtained by the inverse variance weighted method using a random-effects model. The results revealed a positive causal association between coffee consumption and arthritis (OR: 1.02 (1.01–1.03)) . DividedAs a sensitivity analysis, a meta-analysis of the genetic causal effect estimates of coffee consumption for all arthritis outcomes obtained using the weighted median method was performed. The results of the random effects model remained consistent with the findings of previous studies, and suggested a positive genetic causality between coffee consumption and arthritis (OR: 1.01 (1.00–1.02)) . The subThis study assessed the genetic causality between lifestyle and arthritis by applying MR methods and a meta-analysis of past MR studies, leading to the following findings: there was a significant positive causal relationship between smoking behavior and coffee consumption and arthritis (OA and RA). The strength of the genetic causal relationship of smoking for OA and RA were roughly equivalent, and the genetic causal relationship between coffee consumption and RA was more significant than that between coffee consumption and OA. There is insufficient evidence of a genetic causal relationship between alcohol intake and arthritis. These findings are consistent with the vast majority of qualitative analyses of alcohol, smoking, and coffee consumption. Overall, the included studies and this meta-analysis were considered to be of high quality.For alcohol intake and arthritis, the results of our meta-analysis showed that overall, there was insufficient evidence of genetic causality between them. There are many studies with differing opinions about alcohol and OA. It has been reported that alcohol consumption is negatively associated with the prevalence of osteoarthritis of the knee in the Korean population . AnotherPrevious studies have also reported an association between alcohol intake and RA. A research study using data from the UK biobank showed a protective effect of alcohol on RA, with weekly or daily drinking associated with a reduced risk of RA compared with less than three drinks per month, and similar results were obtained in a cohort study of Swedish women ,43. In cAs one of the most common lifestyles, alcohol intake affects the primary skeletal–muscular system as well as other systems of the body, and this compounding effect may be the reason for its unclear relationship with arthritis. For example, alcohol is associated with obesity, and increased joint loading is a risk factor for OA . AlcoholThe results of our meta-analysis support a positive genetic causality between smoking behavior and arthritis, consistent with almost all the results included, and differing only from Lee’s study . PreviouSmoking has been recognized as a relatively clear risk factor for RA development . A prospCigarette smoke contains thousands of substances, including nicotine, polycyclic aromatic hydrocarbons, and nitric oxide, which can affect arthritis through various pathways. Chen et al. found that cigarette smoke extracts mediate cartilage destruction by increasing oxidative-stress-induced cell death . AnotherFor the results of a positive causal association between coffee consumption and arthritis, our meta-analysis was consistent with the results of several studies included in the systematic review ,25,26,27This is the first systematic review and meta-analysis of Mendelian Randomization studies on the causal relationship between arthritis and alcohol intake, smoking, and coffee consumption, to our knowledge. Owing to the increasing prevalence of MR studies, a pooled analysis of heterogeneous studies of the same outcome is necessary and meaningful.This study has a number of strengths. Compared to traditional epidemiological studies, using the MR method can explore causality at the genetic level and can largely avoid bias caused by confounders and reverse causality, with highly reliable results. MR is a GWAS-based method, and the strength of evidence for outcomes is related to the sample size of GWAS participants. Our study meta-analyzed studies that used different GWAS in exposure or outcome, expanding the study cohort and sample size. We assessed the study quality in various aspects by referring to the STROBE-MR guidelines and MR reading guidelines. The results showed that the quality of the included literature, from the study design to the discussion of the results, was high and the risk of bias was low. This guarantees the robustness of the data and the results of this study.For the meta-analysis, considering the heterogeneity across the literature, we applied a random-effects model for the analysis, and the results were still significant under conservative estimation. We estimated the results of the WM method as a sensitivity analysis in addition to the pooled IVW results to verify the robustness of the combined effects of the meta-analysis. The sensitivity analysis showed high agreement with the results of the main analysis, suggesting reliable results. Additionally, we performed a stratified analysis of two different types of arthritis, OA and RA, to assess the impact of a single lifestyle on specific outcomes.This study has some limitations. The GWAS dataset was selected from populations of European ancestry, which avoids the effects of population stratification, but also means that more caution should be exercised when applying the findings to other ethnic groups. The GWAS datasets used in some of the earlier published studies included in the systematic review may not be the most recent and comprehensive, which may have affected the accuracy of the results. The absence of GWAS data on different age groups and sexes rendered stratified analyses of the individual-level characteristics challenging. Some sex-specific phenotypic differences may not be distinguishable because of this. As an emerging epidemiological method, the small number of included studies makes it difficult to assess publication bias for individual exposure factors, which can affect the reliability of results.The influence of lifestyle as a part of the external environment on the development of arthritis is unquestionable . HoweverIn the future, GWAS cohorts with different regional populations, races, and behaviors will be further enriched, and MR studies will be available to determine additional genetic causal relationships between lifestyle habits as risk factors for diseases. Meanwhile, for the identified risk factors such as alcohol intake, smoking, and coffee consumption, exploring their mechanisms of action in the development of arthritis will be the next research direction.This study performed a meta-analysis of lifestyle and arthritis and showed positive genetic causality between smoking and coffee consumption with arthritis (OA and RA), while there was insufficient evidence of genetic causality between alcohol intake and arthritis. The results provide a basis for tertiary prevention in clinical practice and a potential direction for further arthritis-related research.


Rosacea is a chronic inflammatory skin condition that predominantly manifests as facial flushing, irritation, and acne. Rosacea and cancer are thought to be linked by the commonality of inflammatory and immune response dysfunction. Studies that have looked into this possible association have reported mixed results.Given the conflicting literature on this topic, our study sought to evaluate the overall association between rosacea and several cancers commonly investigated in the literature.A systematic review was conducted using the Cochrane, PubMed, Embase, and Ovid databases. Studies were screened independently for inclusion of rosacea and glioma and breast, thyroid, hepatic, or skin cancers. Using information from the articles, rosacea and each cancer were categorized as having a positive, negative, or unclear association.Our systematic review included 39 full-text studies that investigated the association between rosacea and various malignancies. Among the malignancies of concern, 41% (16/39) of the studies reported an association with basal cell carcinoma, with 2 cohorts revealing an adjusted risk ratio (RR) of 1.50 (95% CI 1.35-1.67) and 0.72 (95% CI 0.56-0.93). In total, 33% (13/39) of the studies reported an association with squamous cell carcinoma, with 2 cohorts revealing an adjusted RR of 1.4 (95% CI 1.02-1.93) and 1.30 (95% CI 0.90-1.88). A total of 8% (3/39) of the studies reported an association between breast cancer and melanoma, with breast cancer cohorts revealing an adjusted RR of 8.453 (95% CI 1.638-43.606), 1.03 (95% CI 0.89-1.20), and 1.36 (95% CI 1.18-1.58) and melanoma cohorts revealing an adjusted RR of 1.10 (95% CI 0.95-1.27), 0.63 (95% CI 0.47-0.85), and 0.96 (95% CI 0.57-1.62). A total of 5% (2/39) of the studies reported an association among nonmelanoma skin cancers, hepatic cancer, and thyroid carcinomas, with nonmelanoma skin cancer cohorts revealing an adjusted RR of 1.36 (95% CI 1.26-1.47) and 2.66 (95% CI 1.53-4.61), hepatic cancer cohorts revealing an adjusted RR of 1.42 (95% CI 1.06-1.90) and 1.32 (95% CI 0.89-1.95), and thyroid carcinoma cohorts revealing an adjusted RR of 1.06 (95% CI 0.68-1.65) and 1.59 (95% CI 1.07-2.36). Only 1 cohort reported an association with glioma, revealing an adjusted RR of 1.36 (95% CI 1.18-1.58). According to our review, patients with rosacea were statistically more likely to have nonmelanoma skin cancers, breast cancer, and glioma. Rosacea was not found to be substantially associated with melanoma. The associations between rosacea and hepatic and thyroid cancers were unclear because of conflicting results.The current literature shows that rosacea is significantly associated with increased odds of nonmelanoma skin cancers, glioma, and breast cancer. Rosacea does not appear to be associated with melanoma. Further studies should be conducted to clarify the association between thyroid and hepatic cancers and rosacea. Rosacea is a chronic inflammatory skin condition that predominantly manifests as persistent facial flushing, irritation, and acneiform papules or pustules. Although the etiology of rosacea remains unclear, a variety of factors both genetic and environmental seem to play a role in its pathogenesis. It has been hypothesized that elements of immune system dysregulation, deregulation of neurovascular signaling, and overgrowth of cutaneous pathogens are involved . These aIn addition to the aforementioned illnesses, there have also been many studies that have examined the association between rosacea and various cancers. The current understanding of the pathophysiology of this relationship is limited. However, it is hypothesized that patients with rosacea may have an increased risk of skin cancer because of inflammatory changes in the skin barrier, including reduced epidermal levels of photoreceptive transurocanic acid .Studies that have investigated the relationship between rosacea and cancer have reported inconsistent results. A recent study in Denmark ,6 found In accordance with the PRISMA  guidelines, we conducted a review of observational studies on the association between rosacea and various cancers. Case reports, case series, case-control studies, cross-sectional studies, and cohort studies were included.The Cochrane, PubMed, Embase, and Ovid databases were searched for relevant studies from inception to March 3, 2021. The search was then updated on June 9, 2023. The search terms are provided in detail in Studies were included or excluded from a meta-analysis based on the criteria outlined in All studies were screened by 2 independent reviewers (LT and JX), and eligibility for inclusion was determined by screening the titles and reviewing the full texts. Any conflicts of eligibility were resolved by a third-party reviewer (WG). Using information obtained from the articles, rosacea and each cancer were categorized as likely or unlikely associated, whereas cancers with conflicting results were categorized as having an unclear association.Inclusion criteriaStudies that investigated patients with a diagnosis of basal cell carcinoma; nonmelanoma skin cancer; squamous cell carcinoma; Merkel cell carcinoma; melanoma; glioma; or hepatic, breast, or thyroid carcinoma and a diagnosis of rosaceaPatients diagnosed with erythematotelangiectatic rosacea, papulopustular (or acne) rosacea, rhinophyma, or ocular rosaceaPapers studying populations in different countriesCase reports; series; and case-control, cohort, or cross-sectional studiesPatients of all ages, sexes, and nationalitiesExclusion criteriaPapers for which full text was not availableN<1 patientsPapers not written in EnglishStudies conducted on nonhuman subjectsStudies including concurrent acne and rosaceaStudies including diagnoses of perioral dermatitisP value, odds ratio , hazard ratio (HR), incidence rate ratio, risk ratio (RR), and any adjustments made to the statistical values. To assess the risk of bias of the included studies, the Newcastle-Ottawa Quality Assessment Scale was used.Data extracted from the included studies comprised author, publication year, title, study location, study type, total number of patients, number of patients with rosacea vs control patients without rosacea, general mean age, mean age of patients presenting with rosacea, general percentage of female patients, percentage of female patients presenting with rosacea, number of patients who presented with a history of smoking, drinking, confounding diseases, type of rosacea, inclusion and exclusion criteria used for the study, method of diagnosis of rosacea, mean duration of rosacea, socioeconomic status association with prevalent rosacea, number of patients with cancer in general, number of patients with cancer and rosacea, Among the 3004 articles originally identified, 2786 (92.74%) remained after deduplication and were screened. After initial screening, of the 2786 remaining articles, 104 (3.73%) full-text articles were assessed for eligibility, of which 39 (37.5%) were eligible for our systematic review . A totalThe risk of bias of the studies included for the statistical analysis is summarized in Our search returned 41% (16/39) of papers examining the relationship between rosacea and BCC. Of these 16 papers, 2 (12%) were cohort studies, the first investigating the impact of a personal history of rosacea on the risk of developing BCC in females in the United States and the second investigating the impact of a personal history of rosacea on the risk of developing facial BCC in females in the Providence, Rhode Island, region . In the R statistic analysis indicated that facial BCC in patients with a history of rosacea was significantly lower than in patients without rosacea . When comparing BCC of the body, no significant difference was found between patients with a history of rosacea and patients without rosacea  [In the second study, of the 4537 patients diagnosed with BCC from October 2016 to November 2020 in the Rhode Island region, 2453 had BCC on the face, and of them, 267 had a history of rosacea. A multivariate model with adjustments for age, sex, smoking history, skin color, and other cancer risk factors was developed. Results for chi-square and The other 88% 14/16) of papers on rosacea and BCC comprised case series or case reports. Notably, all reported cases detailed male patients with rhinophymatous rosacea who were later diagnosed with BCC in the area of the nodular lesion . Lazzeri of paperOur search returned 33% (13/39) of studies examining the relationship between rosacea and SCC. Of these, one was a cohort study investigating the impact of a personal history of rosacea on the risk of developing SCC in females in the United States. In this study, 577 cases of SCC were isolated from a population of 90,238 females. A Cox proportional hazard model and multivariate model with adjustments for age and other cancer risk factors were developed. The results indicated that rosacea was significantly associated with overall cutaneous SCC . In this study, the location of SCC was also divided into 2 groups—head and neck and non–head and neck—which were also compared with the history of rosacea. The results indicated that rosacea was significantly associated with head and neck SCC . Findings indicated no significant statistical associations between rosacea and non–head and neck SCC  .The second study investigated various cancer risks among females in the United States with a history of rosacea. Among a total of 75,088 females, 6015 patients were diagnosed with rosacea from 1991 to 2011, with 452 SCC diagnoses documented. A Cox proportional hazard model and multivariate model with adjustments for age, BMI, alcohol consumption, smoking history, and other cancer risk factors were developed. The results indicated that there were no statistically significant associations between rosacea and SCC  [The other 85% (11/13) of the studies were case series and reports that examined the association between rosacea and SCC. Again, all studies identified SCC development in patients with long-standing rhinophyma . NotablyOur search returned 5% (2/39) of studies that did not differentiate between NMSCs. In the first case, Egeberg et al  conducteA total of 8% (3/39) of the studies analyzed the association between rosacea and breast cancer. Of these 3 studies, 2 67%) were cohort studies. Egeberg et al [7% were cLi et al  also conOwing to the directionality of the studied relationship, we were unable to include in the meta-analysis a case-control study by Long et al  that looA total of 8% (3/39) of the studies analyzed the association between rosacea and malignant melanoma. Egeberg et al  found noAlthough excluded from the meta-analysis because of not being in full text, an abstract by Erickson et al  investigA total of 5% (2/39) of studies were found that examined the association between rosacea and hepatic cancer. Egeberg et al  noted thIn total, 3% (1/39) of studies were found that examined the association between rosacea and glioma. Egeberg et al [In addition, the excluded case-control study by Long et al  found thA total of 5% (2/39) of the studies analyzed the association between rosacea and thyroid cancer, reporting conflicting results. Egeberg et al  found noOur review found that, based on the available literature, there is a positive association between rosacea and glioma, NMSC, and breast cancer. Rosacea was not found in any study to be significantly associated with melanoma. Regarding BCC, SCC, and thyroid and hepatic cancers, a clear conclusion could not be drawn because of conflicting results across 2 studies.Our review found conflicting evidence regarding the association between BCC and rosacea. Although Li et al  found a Our review found a positive association between rosacea and NMSC. It should be noted that actinic keratosis was also found to be associated with rosacea in one cohort study . UV expoIt should be noted that, regarding melanoma, all comparative studies  analyzed in our review found no association between melanoma and rosacea. Wu et al  proposedOther than one study indicating no association, the relationship between rosacea and breast cancer seemed to be positive. Given the prevalence of both rosacea and breast cancer in females, there may be a component of hormonal changes and estrogen mediating some common inflammatory and immune-related causes . HoweverStudies examining the association between rosacea and thyroid cancer reported conflicting results. Accumulating evidence demonstrates that chronic inflammation plays a pivotal role in the pathogenesis of thyroid cancer ,46. TherOur study was not able to conduct a meta-analysis because of the statistical heterogeneity between the studies. A meta-analysis would have further clarified the association between rosacea and the various cancers. In addition, there were a small number of studies on most of the cancers included in our review. Other limitations include a lack of studies examining the association between rosacea and cancer in skins of color. Most of the research described in this review was conducted on White, middle-aged, and female populations; further studies are needed regarding rosacea and cancer incidence in skins of color and male populations. In addition, the field of literature regarding BCC and rhinophyma or ocular rosacea is shallow and only comprises case reports/case series. These case series or case reports were included; however, they have an inherent bias because of the absence of a comparative group.Our review of the current literature found that rosacea is significantly associated with NMSC, glioma, and breast cancer. An association between rosacea and thyroid cancer as well as between rosacea and hepatic cancer was also reported, but more studies are needed because of the limited amount of data. Rosacea does not appear to be associated with melanoma. Further studies should be conducted to determine whether there is an association between thyroid cancer and rosacea.


The SMD of the IMF score was 1.25  . Our meta-analysis indicates that the addition of vitamin A could decrease intramuscular fat in cattle steers.Vitamin A, a fat-soluble vitamin, is the basic substance required to maintain healthy vision and the main physiological functions of cattle. The results from previous studies regarding the effect of vitamin A on intramuscular fat varied. This meta-analysis aimed to generate a more comprehensive understanding of the relationship between vitamin A and intramuscular fat content and to provide potential clues for future research and commercial practice. Electronic databases such as MEDLINE and Ovid were systematically searched, and studies investigating the relationship between vitamin A and intramuscular fat content were included. Standardized mean differences (SMDs) in intramuscular fat percentage and intramuscular fat score, with their respective 95% confidence intervals (CIs), were calculated. The heterogeneity and publication bias were evaluated. A total of 152 articles were identified through searches of databases. Seven articles were confirmed for inclusion in this meta-analysis. The SMD of IMF percentage derived from the analysis was−0.78  (Q = 246.84,  With improvement in their living standards, people expect good quality beef replete with taste-enhancing features, such as a lean meat rate, nice meat flavor, and sensory satisfaction. Marbling, also known as intramuscular fat, is a collection of white stripes and spots on the surface of a beef muscle . The concarotenoids or provitamin A) and feed additives (such as retinol or retinyl ester or preformed vitamin A) . Many phVitamin A has been found to be negatively correlated with the marbling score of Japanese black cattle carcass for the first time . SimilarThe meta-analysis was conducted under the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) rather than a self-designed protocol . This ReAll included studies had already declared ethical approvals in the original articles; therefore, no ethical approval was necessary for this study.We conducted a comprehensive search of the electronic databases, MEDLINE and Ovid, from inception to 30 November 2021. Only articles in English language were considered.The following strategy was used for the database research: MEDLINE: (((beef[Title/Abstract]) AND (Intramuscular fat[Title/Abstract])) AND (vitamin[Title/Abstract])). Ovid: (((beef[Title/Abstract]) AND (Intramuscular fat[Title/Abstract])) AND (vitamin[Title/Abstract])). Furthermore, the references in the articles were also screened for any potentially eligible studies. The inclusion criteria for the present study were as follows: (1) studies evaluating the effects of Vitamin A on intramuscular fat in cattle; (2) intramuscular fat percentage (IMF%) and/or intramuscular fat score were used for the measurement of intramuscular fat; (3) results for the vitamin A group and the control group were reported; and (4) the number of cattle in each group, in which mean and standard deviation of indicators were extracted or calculated. The exclusion criteria for the present study were as follows: (1) the data to be analyzed could not be extracted or calculated; (2) articles that were case reports, reviews, letters, news, conference abstracts, and studies regarding other types of animals; (3) the absence of a control group; and (4) duplication or overlap in the research animals. If studies were conducted by an identical research group, those studies with the largest sample size or those studies with the most comprehensive and detailed information were included. Cochrane collaboration's tool for assessing the risk of bias was used to judge the risk of bias for each included study. Two independent researchers (Name) undertook the literature search and study screening. Disagreements were resolved through discussions.Two investigators (WL and FW) independently performed the title and abstract screening of articles on the basis of the aforementioned inclusion criteria. Then, a full-text evaluation of the studies was conducted for the final inclusion. Moreover, the following information about each included study was extracted from or calculated based on details such as: first author's name, year of publication, type of steer, study design, total number of steers, weight of steers at the start, addition of vitamin A, and indicators in each group.p-value of < 0.05 was considered to be statistically significant. We calculated pooled estimates of the standardized mean difference (SMD), the difference between an indicator of the experimental group (steers added with vitamin A) and that of the control group, and the respective 95% confidence intervals (CIs) of each indicator. The Cochran Q values and the I2 statistics were introduced to qualitatively and quantitatively explore the heterogeneity in the included studies. Insignificant, low, moderate, and high heterogeneities were identified to have I2 values of 0–25, 25–50, 50–75, and 75–100%, respectively  (see p = 0.539)  (419) see . The SMD= 0.539) .p < 0.01). Heterogeneity was observed in the analysis of IMF percentage . With regard to the analysis of IMF score, the Q value and I2 were 87.20 and 97.7%, respectively. Deek's tests for publication bias yielded p-values of 0.535 and 0.281 for the analysis of IMF percentage and IMF score, respectively.In the pooled analysis of IMF percentage, the test of heterogeneity product showed a Q value of 246.84  in the studies enrolled. We planned to perform a subgroup analysis and meta-regression to explore the potential source of heterogeneity in the studies enrolled. Unfortunately, we were not able to complete these analyses due to the limited number of studies eligible for the inclusion criteria. Deek's funnel-plot asymmetry tests for publication bias revealed that there was no potential publication bias in the meta-analysis of IMF percentage and IMF score. Sensitivity analysis indicated that the pooled outcomes were robust after omitting one study after another in this meta-analysis. The present study showed that the addition of vitamin A reduced the percentage of intramuscular fat and increased intramuscular fat score in steers. Nevertheless, both the outcomes did not reach a statistical significance. The possible reasons for not achieving statistical significance may be attributed to the different numbers of studies included in each pooled analysis or other confounders, including the type of study design and steers' characteristics. This needs further investigation. Furthermore, significant statistical heterogeneity, which cannot be ignored in the interpretation of the present findings, was detected in this study.In this meta-analysis, we first endeavored to complete a detailed and comprehensive literature search in the MEDLINE and Ovid databases to retrieve as many related studies as we could. Two independent reviewers screened the titles, abstracts, and full text of the articles and undertook the process of data extraction. In addition, heterogeneity in the studies included was assessed. Nevertheless, the results displayed significant heterogeneity (Despite the limitations of the current study, we conclude that the addition of vitamin A could decrease intramuscular fat in cattle steers. More well-designed trials are needed in the future.The original contributions presented in the study are included in the article/WL and FW conceived and designed this study. FS, YQ, CL, and YH were responsible for the collection, extraction, and analysis of the data. WL, FW, HW, BJ, and PZ were responsible for writing the article. JW, XS, MH, and DD polished the English language. All authors and participants reviewed the article and approved the final manuscript.


To identify variables that affect the feasibility of 2-dimensional right ventricular speckle tracking echocardiography (RV-STE) in the intensive care unit.Trans-thoracic echocardiography (TTE) of the right ventricle is challenging. RV-STE is a novel echocardiography method thought to measure global RV function more fully than conventional TTE parameters. The feasibility of RV-STE in ICU populations has not been well described, and variables influencing RV-STE in ICU have not been investigated. This study aimed to address this.A literature review using Ovid MEDLINE(R) was undertaken. We performed meta-analysis with subgroup analysis of; RV-STE type , study design (prospective versus retrospective), coronavirus disease-19 (COVID-19) study or not, and strain software used. This was followed by meta-regression of proportion of invasive mechanical ventilation (IMV), with and without COVID-19 studies as a co-variate.Eleven relevant studies from the literature search were identified, reporting an overall feasibility of RV-STE of 83.3% (95%CI 74.6–89.4%). Prospective study design was associated with higher feasibility compared with retrospective studies (p = 0.02). There were no statistical differences on univariate analysis between RVFWLS versus RVGLS, COVID-19 study or not, or strain software used. Meta-regression with COVID-19 study as a covariate demonstrated that higher proportions of IMV were significantly associated with worse feasibility (p = 0.04), as were COVID-19 studies (p < 0.01).We have identified three variables associated with poor feasibility; retrospective study design, COVID-19 studies, and proportion of IMV. A prospective study design should be viewed as gold standard to maximise RV-STE feasibility.The online version contains supplementary material available at 10.1186/s44156-023-00021-0. Right ventricular (RV) dysfunction is prevalent, and associated with poor outcomes in critically ill patients in the intensive care unit (ICU) . Owing tTo identify factors that might affect feasibility of RV-STE strain analysis in ICU, and determine strategies that might improve feasibility, we performed a literature review and meta-analysis. Feasibility was defined as the percentage of echocardiography studies with images of sufficient quality to allow RV-STE strain analysis. A literature search was performed using Ovid MEDLINE(R) . A random effects model was employed. In the overall meta-analysis, and subgroup meta-analyses, if both RV free-wall (RVFWLS) and global longitudinal strain (RVGLS) were reported, RVFWLS was used due to its more rigorous validation . If RVFW2 63.5 vs 90.4 Fig. Subgroup meta-analysis did not show any statistical difference in feasibility between RVFWLS versus RVGLS. Prospective studies showed significantly higher RV-STE feasibility, and appeared to have lower heterogeneity, compared with retrospective studies (p = 0.02, I2 demonstrates that 46.1% of the variability in the observed effects is attributable to true effects variability. R2 is 73%, showing that the majority of this variance in true effects is explained by the meta-regression model incorporating IMV proportion and COVID-19 study status as co-variates. We were unable to include additional co-variates in our meta-regression due to the small number of studies.The impact of IMV was analysed using meta-regression, with the proportion of patients receiving IMV as a continuous variable Fig. B. We firMeta-analysis and meta-regression have identified three factors that affect the feasibility of RV-STE strain analysis; study design, COVID-19 study status, and proportion of IMV. Prospective studies allow optimisation of imaging for STE strain analysis, leading to better feasibility. Lemarie et al. reported 100% feasibility for RV-STE in patients with ARDS undergoing IMV . They usLimitations of our study include the small number of studies available for meta-analyses and the variation of strain software used across the studies. Different strain software use different proprietary algorithms to derive strain and therefore will report slightly different strain results. Strengths of our study include that it addresses an important clinical subject with an overall aim to improve the feasibility of RV-STE analysis on ICU, additionally we used a comprehensive array of subgroup meta-analyses with meta-regression to elucidate factors affecting RV-STE feasibility.As TTE is increasingly utilised on ICU, interest in RV-STE strain continues to intensify. A prospective study design should be viewed as gold standard to maximise feasibility. Prospective design affords optimal patient positioning, the ability to pause ventilation, and to mandate an RV focused view; modifiable factors that will enhance RV-STE feasibility.Additional file 1: Figure S1.Literature search strategy. Figure S2. Flow diagram of literature search. Figure S3. Overall Meta-analysis. Figure S4. Meta-regression: studies with COVID-19.


Current evidence of the association between a single nucleotide polymorphism (SNP) in ADAMTS14 (rs4747096) and osteoarthritis (OA) is controversial. This study aimed to determine whether the ADAMTS14 SNP is closely related to OA risk.An electronic search of for the association between the rs4747096 polymorphisms and OA was performed using four online databases . The association between susceptibility to OA and rs4747096 polymorphism was evaluated in four genetic models: the allele (mutation [A] vs. wild type [G]), additive (AA vs. GG and AG vs. GG), recessive (AA vs. AG + GG), and dominant (AA + AG vs. GG). This meta-analysis was performed in the R software, and effects were assessed using odds ratios (ORs) and 95% confidence intervals (CI).P < 0.001), additive , and dominant (OR [95% CI)] = 1.72 [1.34–2.2], P < 0.001) genetic models.Four studies (707 cases in the case group and 859 cases in the control group) were included. The results of the meta-analysis showed that, except in the recessive genetic model, there was a significant correlation between OA risk and the rs4747096 polymorphism using the allele (OR [95% CI] = 1.48 [1.26–1.73], The ADAMTS14 rs4747096 polymorphism is associated with susceptibility to OA. Osteoarthritis (OA), a common form of arthritis, contributes to disability and impairs quality of life . ApproxiSingle nucleotide polymorphisms (SNPs), the most common and stable variations, account for ~ 90% of gene polymorphisms in humans . SeveralADAMTS14 gene is closely related to knee OA susceptibility in the Chinese Han population [ADAMTS14 SNP rs4747096 [ADAMTS14 gene rs4747096 was significantly higher in women with OA who required knee replacement than in the control group, further indicating that the ADAMTS14 polymorphism is closely related to knee OA [ADAMTS14 is a member of the ADAMTS  metalloproteinase family, which is associated with knee OA . The rs4pulation . ADAMTS1pulation . It can pulation . Based os4747096 . Rodrigu knee OA . In cont knee OA . Thus, t knee OA . To obtaThe search was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Relevant studies were searched from electronic databases, including PubMed, Embase, Wanfang Data, and CNKI. The main searching keywords included: “osteoarthritis” OR “ostarthritis” OR “ostearthritis,” “ADAMTS14” OR “rs4747096,” and “polymorphism” OR “mutation.” The search steps and corresponding results for each database are shown in Fig. The inclusion criteria for selecting studies comprised: (i) case–control studies with case (patients with OA) and control groups ; (ii) published literature on the relationship between the ADAMTS14 rs4747096 polymorphism and OA; and iii) provision or calculation of the number of genotypes/alleles in both the case and control groups. Reviews, reports, comments, and letters were excluded.Two researchers independently extracted articles according to the selection criteria. Next, the following data were independently collected from each eligible study: first author, year of publication, country, research time, gold standard of diagnosis, gene detection method, number of genotype distribution in the case and control groups, and general demographic data characteristics (such as sex ratio and age composition). If the extracted data were different between the two researchers, a consensus was reached through group discussion with a third scientist.The quality assessment of all included studies was performed using the Newcastle–Ottawa Scale (NOS) recommended by the Agency for Healthcare Research and Quality (AHRQ) . AccordiP < 0.05) were excluded [Q test and I2 [P < 0.05 or I2 > 50%); otherwise, a fixed-effects model was applied (P ≥ 0.05 or I2 ≤ 50%). Moreover, sensitivity analysis and the Egger’s test were performed to investigate the stability and publication bias in the combined results, respectively [Evaluation of the Hardy–Weinberg equilibrium (HWE) was performed on the population in the control group using the chi-square test , and theexcluded . The R st and I2 . If heteectively .A total of 175 studies were extracted based on all searched databases. After eliminating the duplicate literature, 109 studies were retained. Of these, 87 articles were excluded after reading titles and abstracts. Of the remaining 22 studies, 18, including literature reviews, case series, non-case–control studies, and studies that did not describe specific genotypes, were excluded after full-text reading. Finally, four studies , 27 withA total of 1566 cases were included: 707 cases in the case group (382 men and 325 women) and 859 cases (449 men and 410 women) in the control group. The publication years of the four studies ranged from 2013 to 2021 and the ages of the patients from 31 to 70 years. There were no significant differences in age or sex between the two groups. The study locations were China, Turkey, and Thailand. OA detection mainly included RDC/TMD, ACR, and the Kellgren–Lawrence grading system. The quality evaluation showed that the quality of the included studies was ideal (NOS score: 6–8). The detailed characteristics of the four studies are listed in Table P = 0.14, I2 = 46%) among these studies in the allele genetic model (A vs. G), the fixed-effect model was adopted. The pooled results  showed that there was a significant correlation between the rs17222919 polymorphism and OA risk in the allele genetic model  and AA versus GG , the fixed-effect model was used to pool results. The pooled results revealed that the rs4747096 polymorphism was significantly associated with increased risk of OA using the additive model   using the additive genetic model. The pooled results  showed a significant correlation between rs4747096 polymorphism and OA risk using the additive genetic model , the random-effects model was used. The pooled results showed that, compared with the AA genotype, rs4747096 variants (GG + AG) did not increase the risk of OA . Finally, because the heterogeneity among these studies was not significant  in the dominant genetic model (AA + AG vs.GG), the fixed-effects model was applied. The pooled results showed that the polymorphism of rs4747096 (GG) was a risk factor for OA compared with the AA/AG genotype combination  and recessive (P = 0.0077) genetic models, no publication bias was observed in the other models  there were some differences with regard to races and regions, differences in regional living habits and environments, sex, age, and other confounding factors among the different models; (ii) due to the incomplete data in some studies, the covariates, which may affect the results of the meta-analysis as potential confounders, were not corrected; (iii) in this study, only one locus of ADAMTS14 (rs4747096) was selected for analysis (other ADAMTS14 loci were not included in relevant eligible literature), which could lead to inappropriate judgment of the overall genetic effect on OA risk; (iv) the pathological type and clinical staging data of OA were not analyzed in current study due to incomplete data; (v) no subgroup analysis of age and race was performed, given that only four studies were included in this analysis; (vi) there was publication bias in the allele (A vs. G) and recessive (AA vs. GG + AG) genetic models; and (vii) the sensitivity analysis results showed that the allele genetic model (A vs. G) was not stable. Thus, these may arise due to the small size of samples and limited number of eligible studies.The ADAMTS14 rs4747096 polymorphism was significantly associated with susceptibility to OA using the allele, additive, and dominant genetic models. The rs4747096 polymorphism may be a candidate marker for the screening, diagnosis, and treatment of OA. A larger-scale, independent replicated association analysis or larger sample sizes of updated meta-analyses are needed to verify the authenticity of the results.


The most prevalent sustained arrhythmia in medical practice, atrial fibrillation (AF) is closely associated with a high risk of cardiovascular disease. Nevertheless, the risk of AF associated with cardiovascular risk factors has not been well elucidated. We pooled all published studies to provide a better depiction of the relationship among cardiovascular risk factors with AF.Studies were searched in the MEDLINE, Web of Science, and EMBASE databases since initiation until January 15, 2022. Prospective cohort studies assessing the relationship a minimum of single cardiovascular risk factors to AF incidence were included if they contained adequate data for obtaining relative risks (RR) and 95% confidence intervals (CI). Random-effects models were utilized to perform independent meta-analyses on each cardiovascular risk factor. PROSPERO registry number: CRD42022310882.2 for increase in body mass index, 1.19  for former smokers, 1.23  for current smokers, 1.31  for diabetes mellitus, 1.68  for hypertension, and 1.12  for dyslipidemia.A total of 17,098,955 individuals and 738,843 incident cases were reported for data from 101 studies included in the analysis. In all, the risk of AF was 1.39  for obesity, 1.27  per 5 kg/mAdverse cardiovascular risk factors correlate with an increased risk of AF, yet dyslipidemia does not increase the risk of AF in the general population, potentially providing new insights for AF screening strategies among patients with these risk factors.https://www.crd.york.ac.uk/PROSPERO/, PROSPERO identifier (CRD42022310882). As is wWithin this research, a systematic review and meta-analysis of prospective cohort studies were conducted performed to assess relationships among main cardiovascular risk factors, such as hypertension, diabetes mellitus, obesity, smoking, and dyslipidemia and the incidence of AF, focusing specifically on the intensity of effects of single risk factors.2.2.1.We conducted and reported this systematic review based on the prespecified standards  outlined2.2.Abstracts and titles from searched articles were screened for eligibility independently by two reviewers (Wu G and Wu J). A third reviewer (Cheng Y) adjudicated disagreement. All studies deemed eligible based on title and abstract screening were reviewed for full text by two independent reviewers  using the same criteria. Discussion or involvement of a third reviewer (Cheng Y) was used to resolve inconsistent eligibility ratings. Studies were eligible for inclusion if they (1) were prospective cohort studies. (2) assessed the relationship for a minimum of one cardiovascular risk factor with occurrence of AF. (3) reported outcomes for hazard ratio (HR) or relative risk (RR) with 95% confidence intervals (CI), or offered adequate data to compute these outcomes. In case of a number of publications from an identical population, we included the most informative data (having enough baseline features and the most fully adjusted risk estimates). Exclusion criteria in detail can be found in the supplement.2.3.Data were extracted individually by two authors (Wu G and Lu Q) using a standardized data extraction table. We extracted the following features from each qualifying study: name of the first author, year of publication, population source, geo-location, gender category, mean age at baseline, mean follow-up time, number of enrollees, number of incidents, approach of evaluating exposures and results, RR with respective 95% CIs, and adjusted covariates in multivariate analysis. The quality of included studies was assessed using the Newcastle-Ottawa scale (NOS)  for asse2.4.χ2 test to evaluate heterogeneity across studies, with quantification by the Cochran's Q and I2 statistics. A value in the range of 0–25% represented minimal heterogeneity, in the range of 26–75% indicated moderate heterogeneity, whereas in the range of over 75% denoted substantial heterogeneity . We expressed continuous outcome data as weighted mean differences (WMDs) or mean differences (MDs) with 95% CIs. We used the Cochran's ogeneity .P values <0.05 were deemed statistically significant.The publication bias was tested using funnel plots and Egger's and Begg's regression tests , 35. Fur3.3.1.The systematic search of articles published before January 15, 2022, identified 7,556 results. After title and abstract screening, 471 articles were considered potentially relevant. Ultimately, 101 articles were included in the meta-analysis after a full-text review . The chaOn the quality of research, 91% of enrolled studies were considered to be of excellent quality (NOS ≥ 6). There were 22 studies from occupational populations, 14 community-based researches, and 65 population-based researches among the 101 enrolled studies. Risk factor exposure was measured in 17 studies, self-reported in 2 studies, and established by additional approaches  in 82 studies. Adjusted RRs were provided for 87 studies, 77 of which adjusted for age and 76 for at least 3 significant comorbidity factors. Non-adjusted RRs were reported in 14 studies, and adjusted confounders were not available in a single study.3.2.2; 95% CI, 0.52 -0.95), and there was statistically significant heterogeneity between studies   . Neither funnel plot, Egger's test, nor Begg's test published evidence of bias  . With a  < 0.01) . After a < 0.01) . There w < 0.01) . Neverth of bias ,B.3.3.I2 ranged from 59.5% to 89.8% for current smokers and 1.9% to 74.0% for former smokers, t = − 0.79, P = 0.44; Begg's, z = 0.68, P = 0.50) and former smokers , no statistical proof of publication bias was available (data not shown).This analysis included 18 studies reporting risk estimates for AF among former and current smokers as compared to never smokers, involving 412,307 participants and 19,907 events. Totally, for current smokers vs. never smokers and former smokers vs. never smokers, the pooled RRs were 1.23  and 1.19 , separately ,B. Consi3.4.I2 = 87.8%, P < 0.01) , and sensitivity analysis omitting one outlier study from the main analysis showed no material variation in the results  and Begg's test  (data not shown). For assessing the effect of underlying publication bias, the trim and fill approach along with 15 extra estimation studies were applied to balance the funnel plot and an adjusted summary random-effects RR was calculated, which showed a statistically significant relationship of diabetes and AF [RR = 1.12 ], indicating that when we considered the effect of publication bias, there was still a positive association , with a high degree of heterogeneity between studies ( < 0.01) . The poo < 0.01) . Heterog results . Potentiociation .3.5.I2 = 99.3%, P < 0.01)  or the Begg's test , no significant publication bias was observed (data not shown).Reported 12,834,666 individuals and 634,988 events in 44 studies were included to assess the risk of AF among participants with hypertension. Altogether, compared with normotensive participants, hypertensive participants had an increased risk of AF  . There w < 0.01) . There w < 0.01) . Accordi3.6.I2 = 92.9%, P < 0.01) . High-density lipoprotein cholesterol (HDL-C) levels were on average 0.05 mmol/L  lower in patients with atrial fibrillation than in controls, again with significant heterogeneity . The results of sensitivity analyses showed no substantial change in the risk estimates for AF associated with dyslipidemia according to various exclusion and inclusion criteria, whereas heterogeneity persisted , but disappeared in analyses of studies adjusted for at least 3 confounders and studies with large cohorts , with a high degree of heterogeneity between studies ( < 0.01) . The mea < 0.01) ,B. In adersisted . When weersisted . Regardiersisted . The neg cohorts . No evid cohorts ,S6.4.The major risk factors for cardiovascular disease were discovered in association with enhanced risk of AF in this meta-analysis of a large sample size (over 17 million participants). The findings of our study broaden previous reports by showing not only that individual with well-established risk factors always underwent a heightened risk of AF, as well as demonstrating the relationship between AF and less well-defined risk factors. As far as we know, this is the first meta-analysis based entirely on prospective cohort studies summarizing literature on the association between hypertension with new-onset AF. Our pooled data reinforce findings from single studies. It is worth noting that there is no significant association between dyslipidemia and AF risk. Consistent to prior studies, the positive relationships among diabetes, smoking, increased BMI, obesity and AF were also demonstrated in our study. Despite the fact that obesity has been identified as a risk factor for AF, it is commonly found in conjunction with additional metabolic abnormalities, like dyslipidemia, hypertension and hyperglycemia, potentially mediating the relationship of obesity with the risk of AF , 38, 39.Regarding hypertension, studies are numerous, but inconclusive. Several prospective cohort studies have shown that a strong risk factor for cardiovascular disease (CVD), including atrial fibrillation, is hypertension . FurtherDespite our demonstration of an increased risk of AF in patients with hypertension and diabetes, it remains uncertain whether changing risk factors reduces the risk of AF. A meta-analysis conducted by Healey, J.S. et al. in 2005 included 11 randomized controlled human trials and demonstrated a 28% reduction in the risk of AF in angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB) users compared to non-users . In addiThe specific bio-mechanisms behind these correlations are not completely clear, but can be attributed to some extent to the effects of structural , hemodynamic , electrical , neurological , and inflammatory changes.4.1.It has been shown that accumulation of pericardial fat  and a sy4.2.+ channels. In addition, there is microRNA downregulation and transforming growth factor upregulation by nicotine, which leads to proarrhythmic atrial fibrosis (Levels of nicotine in cigarettes produce an increase in plasma catecholamine levels , blood pfibrosis .4.3.The relationship between increased blood pressure and atrial fibrillation exists for several explanations. It is directly related to the increase in left atrial diameter and blood pressure . Further4.4.The cardiac autonomic neuropathy, similar to the peripheral autonomic neuropathy observed in diabetes, is a serious but neglected complication of diabetes , 61. Whe4.5.Despite limited research on the mechanisms of dyslipidemia and AF, corresponding alterations in cardiac load , alteratOur findings may be useful in informing public health policy and allocating scarce resources for prevention. The RRs of each included study were pooled in our study to assess the intensity of the correlation, perform sensitivity analyses to examine the coherence of the relationship, and discuss potential biological mechanisms. In addition, the temporal nature of the prior exposure of the results was supported by the fact that all studies included in our analysis were prospective cohort designs. Moreover, the proof that treating several risk factors can decrease AF risk has been added. With this indicating that risk factors for CVD might as well be causative contributors to AF, more in-depth screening for AF in individuals having such risk factors is warranted.To be acknowledged, the present meta-analysis was limited in the following aspects. First, we limited our analysis to individual risk elements, and there was a clear potential for the intensity of correlation to be weaker when multi-factor analysis was used. Second, there was substantial heterogeneity noted among the analyses of cardiovascular risk factors in spite of attempts at managing cross-study heterogeneity through proper meta-analysis techniques. However, in several sensitivity analyses, the risk estimates did not differ substantially, suggesting that heterogeneity may not affect the main results. Third, the potential for remnant or non-measured confounders could not be excluded, although the studies we included made attempts at controlling for a variety of identified risk factors. Fourth, some evidence suggested that publication bias was present solely within the analysis of diabetes. As shown in the funnel plot, there were some studies that lacked neutral or negative findings, indicating a potential overvaluation in the relationship. Fifth, the causal relationship cannot be determined in light of our present data based on observational studies, even though our results were robust and coherent across various sensitivity analyses. Sixth, cohorts of patients in some of the studies included in our meta-analysis were comparatively young and followed up for a short period of time, possibly contributing to the low prevalence of AF. The pooled RRs, nevertheless, did not materially vary when we performed repeated analyses of studies followed for over 10 years. Seventh, it was important to note that to extend such discoveries into African populations should be approached cautiously and would warrant additional inquiry, as our meta-analysis was primarily grounded in non-African research. Eighth, The studies we assessed might not have consistently differentiated between the various types of AF and diabetes. This disparity could lead to result discrepancies owing to variations in pathophysiological mechanisms and clinical implications within these subtypes. Future studies could enhance their insights by employing stratified analyses based on AF and diabetes subtypes.Collectively, adverse cardiovascular risk factors were related to elevated risk of AF. Nevertheless, dyslipidemia does not increase the risk of AF. People with hypertension have a 68% increased relative risk of developing AF compared to those without hypertension, while obese patients had a 39% increased risk. In addition, current and former smoking were also associated with an increased risk of AF. Meanwhile, there is a need for caution in explaining the relationship of diabetes with AF, as publication bias is required to be considered.