ABCA1) gene. In this study, four meta-analyses were conducted to assess the effect of R219K on lipid levels, including high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol, total cholesterol, and triglycerides (TG). A total of 125 samples of 87 studies  were included. The effect of each study was expressed using the standard mean difference (SMD) and 95% confidence interval (95% CI) and pooled by meta-analysis in the random-effects model. Subgroup and meta-regression analyses were conducted to explore potential heterogeneity sources. The overall pooled effect showed the following results. (1) The R219K was significantly associated with HDLC level . People with different genotypes had significantly different HDLC levels under the recessive, codominant and dominant genetic models . (2) A weak and indeterminate relationship between R219K and TG level was observed . These findings suggested that R219K was associated with HDLC and TG levels, which might implicate a promising clinical application for lipid-related disorders, though the influences of race, health status, BMI, and other heterogeneity sources should be considered when interpreting current findings. The protocol was registered at PROSPERO (registration number: CRD42021231178). Conflicting evidence was found about the relationship between lipid profiles and R219K polymorphism in adenosine triphosphate-binding cassette exporter A1 ( The lipid profile generally serves as an initial screening tool for lipid abnormalities and an important predictor of the above diseases. Investigations to explore the sources that contribute to the difference of lipid levels amongst individuals have attracted the interest of clinicians and researchers.An optimal blood lipid level is important. Abnormalities in blood lipid levels are causally linked to several common human diseases, such as cardiovascular disease (CVD), diabetes, obesity and stroke7. Consequently, understanding the genetic architecture and regulation of lipid profiles will help in predicting, monitoring and treating the above human diseases8. To date, many genes which involved in lipid metabolism have been identified to be associated with variations in individual lipid levels10.The lipid levels in the blood, which are usually presented by four traditional lipids , have high heritability. Approximately 10–15% of the variances amongst individual blood lipid levels can be explained by genetic effectsABCA1 gene are generally believed to cause individual differences in lipid levels13 because of its important role in controlling the circulating lipoprotein levels between cellular and extracellular media14. An arg219-to-lys  polymorphism in the seventh exon of the ABCA1 gene has been extensively studied, although its biological function remains not fully understood. The association between R219K and lipid levels is often used as an endophenotype of patients and is combined with clinical diagnosis to help identify the causal genetic factors of human diseases, including hypercholesterolaemia15, heart disease16 and CVD17. However, those reported correlations remain inconsistent and are ambiguous.The ABCA1 is an ATP-binding cassette (ABC) subfamily A transporter. Genetic variants of the 18; (2) the difference in the effect of R219K on lipids level between the general population and patients is due to abnormal levels of certain lipids. Given that the significant difference in the effect between two populations, genetic detection is valuable and promising for the above diseases’ diagnosis, monitoring and strategic therapeutic approach design; (3) the influence of potential modulators on the correlation between R219K and lipid profile should be estimated. The effect of R219K on the level of lipids is still not well defined because every study is evaluated in various cohorts , healthy or with all kind of diseases and others). Previous meta-analyses34 are mainly emphasised the genetic variants of R219K and the risk of diseases rather than the consistency of their relationship amongst the general population. Furthermore, results from new studies remain inconsistent with those based on previous meta-analyses. The difference of the correlations between R219K and lipid profile in patients and general population is not extensively discussed and estimated quantitatively.The links observed between the R219K polymorphism and risk of above diseases have resulted in other questions from clinicians and scientists. (1) Do the genotypes of R219K significantly contribute to the difference in human blood lipid levels no matter in patients or general/healthy population? This issue means that individuals born with a favourable genotype have already some advantages in CVD, diabetes, obesity, stroke and other diseases events compared with those born with other genotypesFour updated meta-analyses of the correlations between R219K polymorphism and HDLC, LDLC, TC and TG levels are conducted to reach conclusive answers. This work aims to: (1) investigate the relationship between R219K polymorphism and individual lipid levels within both the general population and patients with common diseases; (2) assess the consistency of this relationship amongst different populations; and (3) estimate the influence of other external factors on this correlation.http://www.crd.york.ac.uk/prospero) on 5 February 2021 and published on 8 March 2021 (Registration ID: CRD42021231178). Two authors (Shi Z and Tian Y) searched for studies published before 31 March 2021 and extracted useful data from the databases of BIOSIS, CENTRAL and Clinical trials, Derwent Innovations Index, EMBASE, InspecR, ISI Web of Science, KCI-Korean Journal Database, MEDLINE, PubMed, SciELO Citation Index and Scopus for papers in English and the Chinese National Knowledge Infrastructure and Wanfang databases for papers in Chinese. The full search strategy and literature terms used for searching the above databases are described in Fig. This systematic review protocol was submitted for registration to the International Prospective Register of Systematic Reviews  the original document was unavailable.The inclusion criteria were as follows: (1) the mean lipids and standard deviations (SD) and/or standard errors (SE) were available for each group according to R219K genotypes; (2) at least one of the four variables  was available; (3) the frequency of R219K genotype and the deviation of genotypes from the Hardy–Weinberg equilibrium (HWE) was also described; and (4) other related information that can be used to calculate the effect size of R219K on the four lipid variables or the required data could be collected from other publications. Similarly, the exclusion criteria were as follows: (1) duplication and meeting summary; (2) no relevance of the R219K polymorphism on the 35. Comparing the frequencies of studies categorized by the median NOS score of included studies, two authors’ consensus assessments had high inter-rater reliability . The deviation from the HWE for each sample’s distribution of R219K genotypes was assessed using the HardyWeinberg package36 and used as one of important index of NOS.Information extracted from the eligible literature included the following: (1) name of the first-author, time of publication and number of samples; (2) health status, ethnicity, BMI and mean age of subjects and sex ; (3) mean lipid levels, standard deviation and/or standard error for different groups according to R219K genotype; and (4) other format data that could be used to calculate the effect size value. Required data were extracted and formatted as described in the online supplementary material (Supplementary Tables meta and metaphor38. The effect size of R219K on lipid levels in each study was presented in the standardised mean difference (SMD) and 95% confidence interval (95% CI) format since various measurements and methods were involved with different scales39. The random-effects model, which considered within- and between-study variances40, was adopted to estimate the pooled effect size of all studies because of the potential sources of heterogenous  amongst eligible studies. Heterogeneity was assessed using the Cochran’s Q-statistic and I2 statistics41. Regarding R219K polymorphism’s inconsistent genetic structure in different population and diverse genetic models reports, three codominant models , dominant (RR + RK vs. KK), recessive (RR vs. RK + KK) and codominant (RK vs. RR + KK) models were used to estimate this variant’s effect size on human lipid levels.We conducted meta-analysis by using two R programs of 42 and (3) estimating the influence of interested potential moderators on the effect of R219K. A meta-regression analysis was performed using the mixed-effects model 43. The differences of the effect of R219K on lipid profiles between groups were tested using the method of DerSimonian-Laird estimator for tau244. Simultaneously, the omnibus test (QM) and goodness of fit test (QG) were carried out to access the influence of all target moderators on the effect and calculate whether other unknown moderators also contributed to the variance of effect of R219K on lipid profiles.The sources of heterogeneity were explored and their influences were assessed by (1) pooling the effect of each subgroup defined by categorical variables  and (2) comparing the effects of the subgroups as recommended by Borenstein and Higgins45. So, the influence analyses were performed to detect and remove outliers amongst all eligible studies by using the R function of influence.analysis. The publication bias was examined using the Begg’s rank correlation46 and Egger’s weighted regression tests47, visualised by funnel plots with based on “trim and fill” test48. The sensitivity of the results was examined using the leave1out function. Permutation tests, which assumed normality of the observed effects and relied on the asymptotic behaviour of the test statistics, were also performed using the permutest function with 1000 iterations to control the Type I error rate. All significance tests were two-tailed, and the significance threshold was set to < 0.05.Some studies with extreme effect sizes (outliers) might cause concerns and distort our pooled effectn = 27,548) and 50.35%  of the subjects were Asians and Caucasians, respectively. One sample (n = 128) was from Africa49, and three samples  were mixed population51. According to the participants’ clinical information, 52 patient samples , 47 random samples  and mixed samples  were obtained from all studies. More than 12 kinds of diseases, including coronary artery disease (samples = 13), coronary artery disease (samples = 8), dyslipidaemia (samples = 7), type 2 diabetes (samples = 6), overweight (samples = 6), Alzheimer’s disease (samples = 2), acute myocardial infarction (samples = 2), Parkinson’s disease, cerebral infarction, frontotemporal dementia, abdominal aortic aneurysm, ischemic heart disease and preeclampsia, were included in these eligible studies. Amongst 125 samples, the distribution of R219K genotypes in seven samples57 was reported to significantly deviate from the HWE, and another seven samples  in which the distribution of R219K genotypes were also not in HWE assessed with R package of HardyWeinberg36.A total of 87 studies met the inclusion criteria. Figure Ps < 0.01). This consistent result was observed after the detection and removal of outliers . For instance, under the recessive genetic model, the homozygous R allele had a significantly lower HDLC level than the K allele carrier , as observed using the random-effects model. Extreme heterogeneity  was also observed amongst eligible studies. A consistent relationship was observed after running 1000 iterations for the approximate permutation test (Ppermutation = 0.01). Amongst the eligible studies, six samples  were identified as outliers with low-quality data and extreme effect size  than K allele carriers in the random-effects model.Table Ps < 0.01) with extremely heterogeneity  were observed under codominant, dominant and recessive genetic models. Under difference genetic models, Caucasian populations did not show a consistent result  and a weak difference under the recessive model . No significant difference was observed under other genetic models , random population  and mixed population . For instance, under the recessive genetic model, the average HDLC level in the RR genotype group was significantly lower than that in K allele carriers within patient samples , and the same trend was also observed in random and mixed populations . Additionally, under the codominant 1 (RK vs. KK) and dominant (RR + RK vs. KK) models, the effect of R219K was significantly different in accordance with the clinical conditions of different participants . Comparing to mix health status participants, the effect of R219K in patients was higher than that of general population  under the recessive genetic model. Additionally, the sex of participants  showed a significant influence on the effect of R219K . Race did not influence the R219K effect, although different relationships were observed in different subgroups  and numerical  variables, which might contribute to such observed extreme heterogeneity, were analysed using the meta-regression analysis. The influence of each variable on the effect of R219K was estimated. Table tau = − 0.28, P < 0.01; Egger’s test: z = − 4.36, P < 0.01). The funnel plot also showed a considerable asymmetry distribution amongst the included studies  was observed after adjustment. The sensitivity analysis indicated that the effect sizes of removing any single study did not deviate from the overall effect.Amongst five genetic models, the methods of Begg’s rank correlation and Egger’s weighted regression detected significant publication selection bias in this meta-analysis. For instance, under the recessive model, both of methods suggested significant publication bias consistently . Under codominant (RK vs. KK genotype) and over dominant (RK vs. RR + KK genotypes) models, a weak correlation between R219K and LDLC level was also detected . However, no significant correlation was observed under these three genetic models  including 39,323 participants. Under six genetic models, the relationship between R219K and individual’s LDLC level was estimated using the meta-analysis. Under the dominant model, R allele carriers (i.e. with RR + RK genotypes) showed a significantly lower LDLC level than the KK genotype group , no significant modulation on the effect of R219K was found using hierarchical and meta-regression analyses. The Begg’s rank correlation and Egger’s weighted regression tests showed no consistent publication bias in all genetic models.n = 35,885). The meta-analysis showed no significant difference in the TC levels of the RR genotype population and K allele carriers in the random model and a significant heterogeneity amongst all studies. After removing the five outliers  were collected in this study to explore the relationship between the R219K polymorphism and individual TG levels. Under the recessive model, the RR genotype population had significantly higher TG level than K allele carriers , and I2 = 96.38%  for the heterogeneity test. After removing six outliers , dominant  and recessive  models.A total of 76 eligible studies . Only a weak effect was observed within the Caucasian population  in all three subgroups. No significant effect was detected under three genetic models , and an inconsistent result was observed under the dominant model . The significant influence of NOS score on relationship between R219K and TG level under recessive model , R219K had a significant effect on the TG levels , and the risk of common human diseases  has been extensively investigated. Thus, this polymorphism has been observed as a promising prognostic and predictive biomarker of these diseases for susceptible individuals23. However, such relationship between this polymorphism and lipid levels still presents some controversies. Here, we conducted four updated meta-analyses based on current studies and observed the consistent significant effect of R219K on the level of HDLC under codominant, dominant and recessive genetic models. At the same time, the weak correlation of R219K with LDLC and TG levels was detected.Given the importance of ABCA1 in the formation of nascent HDLC75. On the basis of the data of more than 80 studies, this study confirmed the significant effect of R219K on the level of HDLC under the codominant, dominant and recessive genetic models  even after the removal of outliers and the correction of permutation test with 1000 iterations. This finding was consistent with previous reports29. However, the effect of R219K on the levels of TG and LDLC seemed somewhat unclear. For the TG level, R219K showed a consistent effect only in the recessive model . For the LDLC level, some studies78 and meta-analyses28 reported the association between R219K and LDLC level, which disappeared when studies with the outliers were removed. Such results demonstrated the value of R219K in the clinical application of the above mentioned diseases’ diagnosis, monitoring and strategic therapeutic approach design75, but other potential elements, such as the influence of outliers, race, gender, and age, should be treated with caution.HDLC is the well-behaved “good cholesterol” because it removes harmful “bad cholesterol” from the body, and increasing evidence showed that the K allele of R219K is positively associated with elevated HDLC level and lower risks of common human diseases Q = 0.07, df = 2, P = 0.03; Supplementary Table 80 mentioned, racial/ethnic difference was observed. Compared with those of Caucasian populations, the effect of R219K on the HDLC and TG levels of Asian populations showed more significance and consistency. For the TG level, the effect of R219K was observed under three genetic models  should be considered in this study. Firstly, populations with different conditions  had significantly different effects of R219K. For instance, significantly different effects of R219K were observed on the HDLC level in groups with different health status . (ii) The metafor package was used for the detection and removal of outliers from total studies to minimise their influence, which usually had a decreased quality and extreme effect size, and obtain a robust pooled effect. The obvious influence of the study’s quality (i.e. NOS score) on the findings  It used a robust, systematic and transparent approach in accordance with the Cochrane Handbook and the PRISMA statement. Compared with previous meta-analyses, this study explored the heterogeneity sources by using larger and more comprehensive samples , which may result in different risks of human diseases. The influences of ethnicity and health status on pooled effects must be considered when interpreting current findings and/or accepting the recommendation for R219K clinical applications in the future.The present meta-analyses confirmed the effect of R219K in the Supplementary Information.


Overall, petroleum industry work was associated with an increased risk of mesothelioma , skin melanoma , and cancers of the prostate  and urinary bladder  and a decreased risk of cancers of the esophagus, stomach, colon, rectum, and pancreas. Offshore petroleum work was associated with an increased risk of lung cancer  and leukemia  in stratified analysis. Residential proximity to petroleum facilities was associated with childhood leukemia . Very few studies examined specific exposures among petroleum industry workers or residents living in oil producing communities. The present review warrants further studies on specific exposure levels and pathways among petroleum-exposed workers and residents living near petroleum facilities.Petroleum extraction and refining are major sources of various occupational exposures and of air pollution and may therefore contribute to the global cancer burden. This systematic review and meta-analysis is aimed at evaluating the cancer risk in petroleum-exposed workers and in residents living near petroleum facilities. Relevant studies were identified and retrieved through PubMed and Web of Science databases. Summary effect size (ES) and 95% confidence intervals (CI) were analysed using random effect models, and heterogeneity across studies was assessed (I The petroleum industry has been, and still is, an important pillar in many countries′ economy . PetroleA recent systematic review and meta-analysis including studies published up to 2012 was based on data from 36 cohort studies assessed the meta-relative risk of 11 cancers among petroleum refinery workers . Their rThe aim of this present systematic review was to evaluate the epidemiological studies on cancer risks among petroleum workers and residents living near petroleum facilities through articles published between 1990 and 2019. Our review adds to the previous review  with fouOur systematic review was conducted in accordance with the Preferred Reporting Items for Systemic Reviews and Meta-Analysis (PRISMA) check list of 2009 . The preScientific papers were identified and retrieved through PubMed and Web of Science (WOS) databases, imported and automatically screened for duplicates in EndNote version X8.2, and later screened manually. The search strategies included a list of key words and Mesh terms . AdditioEligibility screening of title and abstract were carried out independently by the first and second authors, and disagreements were resolved by the last author through discussions in line with the Cochrane handbook for systematic reviews . Followi®, version 14.0.  “metan” command in order to (1) compute pooled effect size (ES) for mortality studies and incidence studies with 95% confidence intervals (CI) and (2) explore heterogeneity between studies, expressed as a percentage (I2) [2 was 0%, “probably unimportant” when I2 was 1% to 35%, “moderate” when I2 was 36% to 55%, “substantial” when I2 was 56% to 70% and “considerable” when I2 was 71% to 100% [p-value [Random effects meta-analyses were conducted using the Stataage (I2) . Heterog to 100% . Mortali[p-value ,18. We a®) was used to determine the impact of specific variables ) on the study ES. For heterogeneity and Egger’s regression tests a p-value less than 0.05 were considered statistically significant.Meta regression  and without a single study from Africa. In terms of publication year, most articles (n = 31) were published in the 2000s. Out of the 57 studies, 43 estimated cancer risk among workers, while 14 estimated cancer risk among residents.The methodological quality of studies evaluated on petroleum workers resulted in an average score of 74% (Cohort studies) and 84% (Case control studies). The average score of papers on residents living near petroleum facilities was 41% (Cohort studies), 61%  and 70% (case-control studies). We did not exclude papers on residents based on their methodological quality due to very few papers being eligible for the final analysis in this group. The risk of bias or quality assessment grading for the different components of each study is shown in In this section we describe 36 papers with results from cohort studies among petroleum workers  . The funnel plot did not demonstrate significant asymmetry and Egger’s regression test did not show evidence of publication bias   . The met = 0.99) .2 = 72, p ≤ 0.01). However, the heterogeneity decreased I2 = 55.7% and the ES increased to 2.24  when the “distribution workers” in Sorahan’s study was dropped. In the same vein, four incidence studies [2 = 61, p = 0.69) in ES which was not associated with decade  or country . Combining the incidence and mortality studies resulted in an asymmetric funnel plot but did not show evidence of publication bias  see There were nine mortality studies ,39,40,50 studies ,32,33 wh2 = 59, p = 0.02). The symmetric funnel plots and Egger’s test suggest no publication bias .The pooled ES from 13 mortality studies ,49,50,52A meta-analysis of eight studies ,37,50,51n = 6) [p = 0.50 and 0.34 for mortality and incidence studies)  ,33,42,48studies) .p = 0.18 and 0.08).Combining 14 mortality studies ,50,51,52n = 7) [Effect size of 0.97  was observed for prostate cancer mortality based on 13 mortality studies ,49,50,51n = 7) ,32,42,48The pooled ES was 0.66  based on a study  from Ausp = 0.75)  .p-value  [n = 10) [p = 0.30) with funnel plot did not show evidence of publication bias for estimates of digestive cancer studies  ,50,51,52[n = 10) ,49,50,52 studies .2 = 22.2%, p-value = 0.23. Pancreatic cancer mortality was reported in 12 studies [p = 0.98)  .p = 0.63)  .Thirteen studies ,50,51,52p = 0.53)  .p= 0.16).Nine mortality studies ,37,44,502 = 36.7 %, p = 0.03 (p = 0.59) and its subtypes (p = 0.59).A combined  nine acute myeloid leukemia (AML) studies ,37,44,50p = 0.03 . The leuAmong the five categories of petroleum industries evaluated, there was no substantial effect on the summary ES results of the main meta-analysis . ExceptiHerein, we describe five papers including results from cohort studies among residents living near petroleum plants by cancer site .Lung cancer was reported in three studies ,63,66, oSkin melanoma incidence risks in two studies ,63 had aBrain cancer was investigated in two studies ,63 from 2 = 91, p ≤ 0.01). The study conducted in Ecuador showed a decreased risk of multiple myeloma mortality  whereas the study conducted in Baglan Bay, UK, reported excess mortality risks in relation to distance to petroleum facilities as SMR 2.15  for residents living 3.0 km away and SMR 1.49  for 7.5 km [Multiple myeloma was reported in two studies ,66 showiHodgkin’s lymphoma (HL) mortality was examined in one study  The auth2 = 85, p ≤ 0.01)  .2 = 91, p ≤ 0.01). On the basis of funnel plots and Egger’s tests, we observed no indication of publication bias (p = 0.76)  .Hereunder we describe 10 case-control studies among workers and residents living near petroleum facilities by cancer site . The pooled ES in relation to maximum intensity was 2.17  with “probably unimportant” heterogeneity   .For chronic myeloid leukemia (CML) Glass et al.  reportedKidney cancer in relation to cumulative benzene exposure was analysed in two nested case-control studies ,60 with Finkelstein  conductep = 1.00. Weng et al. conducted a case-control study including 405 childhood leukemia deaths showing an elevated risk of 1.90  for children living in the municipalities characterized by the highest proportion of the population employed in the petrochemical industry, when compared to the municipality with the lowest proportion. McKenzie et al. [p-value = 0.035). No association was found for younger ALL cases or NHL cases.The two studies ,74 yieldLyons et al.  comparedMicheli et al.  investig2 hosting four petrochemical industrial complexes in Kaohsiung, China/Taiwan [2 = 90.6%, p ≤ 0.01)Yu et al.  assesseda/Taiwan . The resa/Taiwan , which iTsai et al. conducted a death certificate-based case-control study on bladder cancer in China/Taiwan from 1995 through 2005, including 821 cases. The results showed that subjects who lived in petrochemical polluted environment had an increased risk of bladder cancer with an OR of 1.65 .Choi et al.  conducteOur systematic review and meta-analyses included 43 publications on cancer risks among petroleum workers and 14 among residents living near petroleum industry sites. Among petroleum workers, six cancer types were associated with elevated risks, namely mesothelioma in both incidence and mortality studies, as well as multiple myeloma, skin melanoma, prostate cancer and urinary bladder cancer in incidence  studies. In stratified analysis, lung cancer and leukemia were associated with an elevated risk among offshore workers. Cancers of the liver, esophagus, colon, pancreas, stomach, and rectum showed inverse associations among petroleum workers, which were stronger in the mortality studies than in the incidence studies. We found significant elevated risks of childhood leukemia for residents living near petroleum facilities.The meta-analysis of the nested case-control studies of hematopoietic cancer among petroleum workers in relation to benzene exposure showed some non-significant elevated risk estimates for AML, CLL and leukemia overall but no conclusive exposure–response relationship. Although the present meta-analysis for cohort studies did not suggest elevated risk for kidney cancer, a non-significant increased risk of kidney cancer was observed in the meta-analysis for case-control studies. Among residents living near petroleum facilities there were non-significant elevated results for brain cancer in adults in both cohort  and case control studies, one positive study of urinary bladder cancer, and one positive study of prostate cancer.The increased risks of mesothelioma, skin melanoma, and multiple myeloma observed among petroleum workers in our review confirm the findings of a previous review . The vasSkin melanoma is also associated with multiple risk factors which workers can be exposed to including occupational chemical exposures   and ultrHowever, the increased risk of prostate cancer we observed among petroleum workers was not observed in the review by Wong and Raabe , but hasThe increased risk of incident urinary bladder cancer we observed among petroleum workers was not examined in the review of Schnatter et al. . InsteadIn our review, skin melanoma, prostate cancer and urinary bladder cancer did not show any association in the mortality-based studies. All three cancers have a good prognosis especially in earlier stages and may be detected early through regular medical check-ups; this may explain why we observe an increased incidence of these cancers but not an increased risk of mortality ,87,88.The association in childhood leukemia we observed is in agreement with previous reviews ,90. ChilThe present meta-analysis showed that mortality was reduced for cancers of the lung, esophagus, stomach, colon, rectum, and pancreas, which are known to be associated with life-style factors such as tobacco, alcohol, and diet ,92. ThisStrengths of this review include that many of the studies had long term follow up in cohort studies, and that both mortality and incidence studies among petroleum workers were clearly separated in the main analyses of our review when compared to previous reviews. Other strengths include stratified analysis by sub-sites of the petroleum industry based on the extracted information. Weaknesses include crude exposure assessment in some studies, e.g., ever employment in this industry, while the exposure variability may be considerable between jobs/tasks and thereby dilute any potential risk for highly exposed workers. Another caveat is the lack of analyses by duration or level of exposure in some of the studies. Insufficient exposure contrasts may have caused bias among petroleum workers, due to non-stratified classes of workers in some of the studies. Furthermore, the cohort studies reported results on multiple cancer sites, for which some analyses were severely under-powered for the detection of any potential risk. Finally, it is relatively common to see lower mortality in occupational cohorts because unhealthy people are usually excluded from employment, which makes the overall death rates lower than those of the general population .The above mentioned limitations could be reduced by improving the exposure assessment, especially in areas with substantial occupational or residential exposures like low and middle income countries (LMICs) with high crude oil production capacity and artisanal refining activities. Unfortunately, there were no studies conducted on petroleum workers and residents living in oil producing communities in Africa. Meanwhile Angola and Nigeria are among the world’s top oil producers. There have been frequent oil spills contaminating landscape and polluting soil and ground water, as well as constant emission of hydrocarbons and other toxic chemicals in the Niger Delta region of Nigeria. In the same region houses are built around petroleum oil wells with pipelines running across the various communities and crude oil is sometimes used for dermal care and ingested for childhood convulsion treatments among other illnesses . The UniIn conclusion, living close to petroleum facilities was associated with increased risk of childhood leukemia, while petroleum industry work was associated with an increased risk of mesothelioma, skin melanoma, multiple myeloma, and cancers of the prostate, urinary bladder, and a decreased risk of cancers of the esophagus, stomach, colon, rectum, and pancreas. Offshore petroleum work was associated with an increased risk of lung cancer and leukemia in stratified analysis. Many of the associations, however, appear to be due to factors other than those directly emerging from petroleum production. This applies to asbestos for mesothelioma, which is a rare cancer, so that the number of cases attributable to this risk were small compared to the working population. This also applies to ultraviolet radiation from outdoor work for skin melanoma, or from healthier lifestyles in petroleum workers for cancers of the colon, rectum, esophagus, stomach and pancreas. Prostate cancer incidence studies may have been affected by medical surveillance. For urinary bladder cancer, studies showed inconsistent results, which may not be surprising given that bladder cancer is positively associated with several workplace chemicals (some occurring in the petroleum industry) but also with smoking (apparently reduced in petroleum workers given the reduced risks of other smoking-related cancers), and therefore inclusion criteria of individual studies and their possibilities to adjust for confounders may have had a significant impact on the study results.The overall evidence remains weak, particularly for the residential studies. Improved exposure assessment is needed in further studies to describe exposure pathways of petroleum and its closest derivatives, e.g., benzene, in order to identify the drivers of the observed cancer risks or identify association which may have been missed using the crude industry-based exposure approach. In particular, there is a need for targeted studies in under-researched areas of high petroleum production with presumably higher exposures. An international consortium guiding new generation studies in Africa, the Middle East and Asia, to harmonize study protocols and exposure assessments, may be the most promising way forward.


NKX2-5 is a key transcription factor that plays an essential role in normal cardiac development. Although some recent studies have studied the role of polymorphisms in the NKX2-5 gene in congenital heart diseases (CHDs), the results were not consistent and remained uncertain. Therefore, we conduct a review of literature and investigate the association of genetic polymorphisms with CHDs.The gene NKX2-5 gene rs2277923 polymorphism with CHDs. Overall, in all the tested genetic models, the 63A > G polymorphism was not significantly associated with increased congenital heart defects risk. We used pooled odds ratios (OR) to calculate the association of CHDs with rs2277923 including allelic model: OR 1.00, 95% CI 0.82–1.21; homozygote model: OR 0.95, 95%CI 0.68–1.33, recessive model: OR 0.89 CI 0.70–1.13, heterozygote model: OR: 1.09, 95%CI 0.87–1.37, dominant model: OR 1.08 CI 0.82–1.42 and overdominant model: OR 1.17 CI 1.01–1.35. In addition, our analysis suggests that no publication bias exists in this meta-analysis.We selected seventeen studies regarding the association of NKX2-5 gene was not significantly associated with congenital heart defects. However, in the future, more studies with increased sample size are required that may provide us more definite conclusions.Our findings suggested that 63A > G polymorphism in the The online version contains supplementary material available at 10.1186/s43044-021-00199-w. TBX), NKX2-5, and the GATA can cause perturbance in normal cardiac development [NKX2-5 gene is a key player in almost all phases of cardiac development including septation, regulation of cardiac progenitors cell numbers, valve formation, and conduction system development [NKX2-5 contains two exons and situated on chromosome 5q34 that encodes the 324 amino acid protein. The gene belongs to the family of homeodomain-containing transcription factors which interacts with DNA through its helix-turn-helix DNA-binding motif. Thus, a single-nucleotide polymorphism (SNP) can disrupt the gene function resulting in abnormal cardiac morphogenesis [Congenital heart diseases (CHDs) or congenital heart defects are defects in great vessels or the heart that arise during cardiac development in the embryo , 2. CHDselopment . The NKXelopment . The NKXogenesis . The rs2ogenesis .NKX2-5 gene, including Iranian [There are many inconsistencies in the published study results regarding the role of rs2277923 in the  Iranian  Asian [1 Iranian  Moroccan Iranian , and Cau Iranian ; hence, NKX2 -5 gene with congenital heart defects.The purpose of the present study was to determine the association of rs2277923 polymorphism in the This study was done according to the standard Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 guidelines, and it is also registered with PROSPERO (PROSPERO registration number CRD42020207952). A PRISMA checklist is also given as a Additional file Electronic databases of Ovid, PubMed, Web of Science, Cochrane Library, Medline, and EMBASE were searched till March 30, 2021, by using the following keywords and MeSH terms: ‘CHD,’ ‘NKX2-5,’ ‘worldwide,’ ‘congenital heart disease,’ ‘gene polymorphism,’ ‘variant,’ ‘genotype,’ and ‘mutation.’ Further identification of each potentially eligible article was conducted based on a manual search of the individual article reference list. In the final analysis, all the duplicate research articles were not included.NKX2-5 gene polymorphism (rs2277923) with congenital heart diseases (2) The retrospective case–control studies (3) Adequate data were available for the genetic statistical analysis. The review articles either narrative or systematic, meta-analysis, doctoral thesis, not published in the English language, not designed as a case–control study, or research articles that not provided enough data for the statistical analysis were excluded from the present study.For the selection of studies, the following criteria were used (1) The full-length published research studies that investigated the relationship of A predesigned data extraction table was used to minimize the selection bias. All three authors individually assessed and extracted the required detailed information from each included study. The following details were abstracted from each selected article: author names, country, publication year, the sample size of both case and control subjects, baseline characteristics, genotypic method, distribution of alleles and genotypes, and evidence confirming the Hardy–Weinberg equilibrium (HWE). Each study’s detailed characteristics are also summarized in Tables Each author evaluated the quality of published studies, and any discrepancies were solved by discussion to achieve a consensus. According to the Newcastle–Ottawa Scale (NOS), the quality of each original study was evaluated. The Newcastle–Ottawa Scale ranges from Worst (0) to Best (9).NKX2-5 polymorphism (rs2277923) in the pathogenesis of congenital heart disease was checked by calculating the pooled odds ratio (ORs) and 95% confidence interval (CI). The chi-squared test and I2 statistic were used to calculate the heterogeneity between each included study. In the presence of significant heterogeneity, we used a random-effects model (DerSimonian–Laird). While in the absence of heterogeneity, a fixed-effect model (Mantel–Haenszel) was used. The genetic models used for rs2277923 were allelic model, heterozygote and homozygote model, overdominant, dominant, and recessive model. To check the stability of the results, we performed the sensitivity test. Publication bias was assessed with the funnel plot. We performed the Begg’s and Egger’s test to evaluate the publication bias, and publication bias was considered present when p ≤ 0.05. The MetaGenyo tool was used for performing the meta-analysis.The role of Initially, 334 published studies were selected, of which 217 articles were not included as they did not study the rs2277923 association with congenital heart diseases, thus 60 articles were selected for further evaluation. Among these, 17 original articles met our inclusion criteria; therefore, these were selected further for final analysis. The complete screening method for the literature search is given in Fig. NKX2-5 gene show a non-significant association with CHDs. We selected the random-effects models to combine all information. Overall, the rs2277923 SNP not increased the risk of congenital heart diseases in each tested genetic model . The meta-analysis of these four models is shown in Fig. The pooled results of rs2277923 in the After sequentially excluding each study, the overall changes in OR with a 95% confidence interval were not statistically significant, suggesting the reliability and stability of current meta-analysis results.p value for each genetic model was given as: allelic: 0.19, overdominant: 0.96, dominant: 0.82, recessive: 0.32, homozygote: 0.66 and heterozygote: 0.89.In the current study, funnel plot analysis does not explain any apparent asymmetry in each tested genetic model as illustrated in Fig. NKX2-5 gene is the vital gene that interacts with other transcriptional factors, including the T-box transcription factor (TBX5) and GATA4; thus, it plays a crucial role in cardiac development. Hence, a single-nucleotide polymorphism can alter the gene function that ultimately affects the growth and heart structural morphogenesis [To date, few systematic reviews and meta-analyses have been done to find the association of rs2277923 association with congenital heart defects , 32, butogenesis .In the current study, we analyzed all the available literature on rs2277923 polymorphism and congenital heart defects, and the pooled results suggest a non-significant relationship between congenital heart diseases and the selected polymorphism. Our analysis showed that in different ethnic groups, minor allele was not associated with CHDs.p = 0.009 [p = 0.39, OR = 1.10, 95% CI = 0.88–1.38) [p = 0.73 for the allelic model [Our results are in accordance with those performed by the Kalayinia et al. as they showed the overall percentage of the mutant and wild allele was 2.5%, and 65.8%, respectively , but in  = 0.009 . Xie et 88–1.38) . Similaric model . Similaric model . Wang etic model . We did ic model . We founAlthough the cumulative results of this study are quite comprehensive, however, certain limitations also exist in this meta-analysis. First, we only chose one single-nucleotide polymorphism of the selected gene that may be influenced by gene–environment and gene–gene interactions. Second, we cannot exclude the possibility of publication bias because, in this study, we selected only English language published literature.NKX2-5 rs2277923 single-nucleotide polymorphism was not significantly associated with congenital heart defects. It is suggested that there is a need for further meta-analysis with a larger cohort size in various subgroups that may provide us the more definite conclusions. Moreover, in the future, more genetic variants should be included in the analysis that may help us in better understanding the genetic mechanism involved in the pathogenesis of CHDs.We concluded that Additional file 1. PRISMA 2009 Checklist.


APOB) gene and gallstone disease (GD) risk through a comparison of the allele and genotype distribution frequencies at this site using meta-analysis.Our aim was to investigate the association between XbaI gene polymorphisms in the apolipoprotein B  and 95 % confidence intervals (CIs) were used to assess the strength of associations.After a comprehensive search, 14 different articles that met the inclusion criteria were selected, with 1583 cases and 1794 controls. Individuals carrying the A-allele or AA genotype of the rs693 polymorphism were determined to possibly have an increased risk of GD. For example, there was a significant relationship between the rs693 polymorphism and increased GD risk in the whole group , the Asian population , and the hospital-based source of the control .APOB rs693 polymorphism is potentially associated with GD susceptibility, which might offer a detection marker for use in future large scale clinic research.This study suggests that the  Gallbladder disease (GD) is a highly prevalent condition affecting up to 15 % of the population with a significant health care burden in the United States . ApproxiBesides race, there are many other factors for GD development, such as advanced age, sex, and a hypercaloric diet rich in carbohydrates and poor in fiber. Additionally, obesity is one of the most important predisposing factor for GD. Other factors that affect the hepatic production of cholesterol, stasis/inflammation, bile acid production, or intestinal absorption of cholesterol and bile acids also contribute to GD development. Increasing evidence also points to genetic factors as being important for GD development , 7.APOB) gene, presumably affecting the lipid composition and lipid metabolism . In addition, Baez et al. enrolled 110 patients with GD and 70 healthy controls and showed that the rs693 variant is involved in gallstone formation and GD risk[15]. It is necessary to combine all previous studies and increase the sample size, and our aim was to obtain a comprehensive and convincing conclusion about the association between the rs693 polymorphism and GD susceptibility.To date, multiple genes have been shown to be associated with increased GD risk, such as ATP binding cassette subfamily G member 8, mucin-like protocadherin, and apolipoprotein E –45. In aThus, it was necessary to analyze the association between the rs693 polymorphism and GD risk using a meta-analysis method. After searching through the main database, 14 different case-control studies were identified, including 1583 cases of GD and 1794 controls. The main result of the current study is that the rs693 polymorphism is a risk factor for GD for all patients, especially in the Asian population (Chinese), which might offer a reference for early detection, prevention, and treatment. Because the incidence for GD between males and females is different, we tried to analyze whether the rs693 polymorphism differed between the two sexes; however, the analysis did not produce any positive results, which might be due to the samples.We found publication bias in the A-allele vs. G-allele model, which might affect the strength and credibility of our conclusion. Here, we have discussed some possible reasons for this. According to the composition of the GD, it can be categorized as follows: cholesterol stones, pigment stones, and mixed stones, of which cholesterol stones are the most common; and based on the site of occurrence, GD can be divided into extrahepatic bile duct stones and hepatolithiasis, of which gallstones account for approximately 50 % of all stones. In the studies included presently, only one study indicated cholesterol stone; meta-regression was applied and showed heterogeneity. Moreover, publication bias might originate from ethnicity, because most studies were from Asian populations, especially from China, and only two studies were from Europe.APOB based on the online String server. The 10 most probable genes are shown in the network around the APOB gene. Among them, six are of the apolipoprotein family (subtypes), and the first related genes are APOA1 and APOA2. Dixit et al. confirmed that the APOA1 75G/A polymorphism is associated with GD and showed sex-specific differences. However, the APOC3 Sstl polymorphism was not found to be a factor for GD susceptibility [APOE E4 polymorphism and GD risk [PCSK9 genetic variant is associated with LDL-C level and influences the formation of GD [APOB gene, as well as gene–gene interactions, in the development of GD in future studies. In addition, we tried to review the variants that are in linkage with the rs693 variant and identify probable exonic and functional variants as rs693 is a synonymous variant. Just only one paper reported by Xiao et al. was found about ischemic stroke not GD disease. They found that two blocks in APOB constructed by Block 1  and Block 2  in chromosome 2 with linkage disequilibrium [It is well known that the development of GD is complex and multi-factorial. Focusing on only one gene or one polymorphism might create a bias. Thus, we attempted to detect some related genes associated with tibility . Sarac etibility . Li et a GD risk . Castro  GD risk . Stenderon of GD . In summilibrium .APOB rs693 polymorphism and GD, including age, sex, diet, diabetes, smoking, familial history, surgical history, and hypertension. Third, whether patients with GD have other complications, such as liver dysfunction, dyslipidemia, and a history of GI obstruction was not reported in the included studies. Further comprehensive studies should include such information. Fourth, the type of stone composition was not distinguished, which should be analyzed separately and can result in more accurate assessments for prediction and treatment.There are some other limitations that should be addressed as well. First, further studies should focus on mixed and African populations, which were not represented in the current analysis. Second, because GD is a multi-factorial disease, gene–gene and gene–environment interactions should be considered and assessed. It is possible that specific environmental and lifestyle factors influence the associations between the APOB rs693 polymorphism might be a powerful predictor of GD risk, which can serve as a detection method in clinics to provide early identification and caution patients with GD.Our present meta-analysis suggests that the


Omega 3 fatty acids supplementation may have an attenuative effect on exercise‐induced muscle damage (EIMD) through the cell membrane stabilization. The purpose of the present meta‐analysis was to evaluate the effects of omega 3 fatty acids supplementation, on indirect blood markers of muscle damage following EIMD in trained and untrained individuals.2 statistic.Scopus, Medline, and Google scholar systematically searched up to January 2021. The Cochrane Collaboration tool was used for the quality of studies. Random‐effects model, weighted mean difference (WMD), and 95% confidence interval (CI) were applied for the overall effect estimating. The heterogeneity between studies was evaluated applying the chi‐squared and IThe outcomes showed a significant effect of omega 3 supplementation on reducing creatine kinase (CK), lactate dehydrogenase (LDH), and myoglobin (Mb) concentrations. In addition, a subgroup analysis indicated a significant reduction in CK, LDH, and Mb concentrations, based on follow‐ups after exercise, studies duration, time of supplementation, and training status.The current meta‐analysis indicated an efficacy of omega 3 in reducing CK, LDH, and Mb serum concentration among healthy individuals, overall and in subgroups analysis. Thus, omega 3 should be considered as a priority EIMD recovery agent in interventions. The current meta‐analysis indicated an efficacy of omega 3 in reducing CK, LDH, and Mb serum concentration among healthy individuals, overall, and in subgroups analysis, based on follow‐ups after exercise, omega 3 doses, studies duration, time of supplementation, exercise type, and training status.  Exclusion criteria were as follows: (1) consuming omega 3 mixture in supplementation group only, not including a placebo group; (2) animal studies; (3) trials without control groups, nonrandomized, or semi‐experimental trials; (4) case reports, editorial articles, or letters to the editor; and (5) duplicate articles with same participant.All RCTs were included in the current meta‐analysis if met our inclusion criteria: (1) original researches in RCT study design; (2) participants received oral omega 3 supplementation, as a nutritional strategy; (3) presented at least one muscle damage indices  measurement; and (4) reporting interest data as mean and standard deviation . According to search strategy, titles and abstracts of papers were screened. Papers were assessed independently by two authors and selected based on the inclusion criteria. Papers including eligibility criteria in the title and abstract checking were selected to be evaluated by full text. If our inclusion criteria were met, all of RCTs were included in current meta‐analysis. We applied a pre‐design form to select papers eligible for inclusion in the review, according to the data within the full text. Contradictions between the reviewer authors were dissolved by the third researcher or consensus.2.4SD of interest data . Any presented standard errors (SE) of mean were changed to SDs via this formula: (SD = SEM × √n (n is the subjects’ number in intervention and placebo groups). Finally, in papers that depicted data in figures, extraction of data was carried out applying Graph Digitizer 2.24 software  including first author's name, country and year of publication, design of research, sample size, age and gender of participants, duration of intervention, and dose of omega 3. In addition, authors extracted baseline and after the intervention mean and Fedorov, .2.5As regards, it has been indicated that inclusion of high risk of bias RCTs may distort the results of a meta‐analysis study  − ]  test and quantified by the I2 statistic, which reports the percentage of the total variation across trials that are attributable to heterogeneity rather than to chance. p‐value of <.05 was defined as significant heterogeneity.Mean differences and For estimating the overall effect, the weighted mean differences (WMDs) with 95% confidence intervals (CIs) were calculated using the random‐effects model. To evaluate whether the outcomes could have been influenced by a single study distinctly, a sensitivity analysis was carried out Tobias, . Also, s33.1n = 10) . We concentrated on results presented immediately after exercise and subsequent hours . Five effect sizes in five articles had immediately after exercise . Significant heterogeneity observed among the articles  . Also, significant heterogeneity observed among the articles  . Also, significant heterogeneity among the articles was observed  . Also, the Egger's test outcomes did not determine any publication bias evidence in articles that evaluate the effect of omega 3 supplementation on LDH and Mb concentration .Any of the studies removal from the meta‐analysis creates no alteration in the outcomes of the meta‐analysis on serum CK concentration based on sensitivity analysis, whereas the results on LDH and Mb concentration were sensitive to omitting Tartibian et al. study  had no significant effect on CK concentrations. The relationship between the duration of omega 3 supplementation and recovery from muscle damage is complex and controversial. The balance between beneficial and damaging effects of the duration of omega 3 supplementation may depend on magnitude of the inflammatory stimulus , the duration of the elevation of the inflammatory factors, and the subject population . This meta‐analysis may provide baseline data and can guide other researchers to design new studies.The high heterogeneity stated is the major limitation in this meta‐analysis. Many factors can affect this heterogeneity. Sex had a significant influence in other articles in serum CK activity (Stupka et al., 5Briefly, the outcomes within the current meta‐analysis indicate that omega 3 supplementation is effective for alleviating EIMD that happens after exercise muscle damage. Further studies with diverse dosages of omega 3 and different exercise protocols are required to assess the best dosage and repetition per day for optimized recovery. In addition, in the present meta‐analysis, we focused on indirect blood markers including CK, LDH, and Mb levels, which associated with EIMD. Other items related to EIMD, such as inflammation markers, strength, and muscular function, have been prove to decrease after exercise. Other studies may be required to assess these outcomes after different exercise protocols and different dosages of EPA and DHA.Authors have no conflict of interest to declare.


The impact of smokeless tobacco (SLT) use on the risk of oral cavity cancer (OCC) has been confirmed; however, the sex-based difference in this association remains inconclusive. Therefore, this study aimed to estimate the association between SLT use and OCC risk in women and compared it to that in men.PubMed, Embase, and Cochrane Library databases were systematically searched for eligible studies from their inception up to August 2020. Studies reporting the effect estimates of SLT use on OCC risk in men and women, were eligible for inclusion. The relative risk ratio (RRR) was applied to calculate the sex-based difference in the relationship between SLT use and OCC risk, and pooled analysis was conducted using a random-effects model with inverse variance weighting.P < 0.001) and women . Moreover, the SLT-use-related risk of OCC was higher in women than that in men . The risk of OCC related to SLT use in women was still significantly higher than that in men  after excluding indirect comparison results. Finally, a subgroup analysis suggested significant sex-based differences only in individuals who received chewed smokeless products, regardless of the control definition. Pooled analysis of studies with high design quality confirmed the notably higher risk of OCC in women than in men.Nineteen studies reporting a total of 6593 OCC cases were included in the final meta-analysis. The pooled relative risk (RR) suggested that SLT use was associated with an increased risk of OCC in both men (RR, 2.94; 95% confidence interval [CI], 2.05–4.20; This study found that SLT use was associated with a higher risk of OCC in women than in men. Further large-scale prospective cohort studies should be conducted to verify sex-based differences in the association between use of specific smokeless products and OCC risk. Oral cavity cancer (OCC) is the subtype of head and neck cancer and defined as any cancerous tissue growth in the oral cavity. It is the sixth most common cancer and accounts for nearly 4–5% of all cancer cases . A totalSmokeless tobacco (SLT) is marketed for oral  or nasal use and contains different amounts of nicotine and nitrosamines . SLT proTobacco chewing appears to be a major risk factor for oral and pharyngeal cancer in Asia ; howeverThis systematic review and meta-analysis was performed and reported following the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) protocol . The eleTwo reviewers independently conducted the literature search and study selection following a standardized protocol. Discrepancies were settled by group discussion until a consensus was reached. The details regarding study inclusion criteria were as follows: (1) Participants: general population for cohort design, and OCC cases and non-cases for case-control design; (2) Exposure: SLT use; (3) Outcome: the prevalence of OCC and sex-specific effects of the relationship between SLT use and OCC risk; and (4) Study design: cohort, case-control, or case-reference studies.OCC was defined by International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) codes to distinguish the anatomic grouping and etiology of the disease. The studies that were included reported on cancers according with the following ICD-10 codes: C00-C06 and C09-C10, which included cancers of the lip, tongue, gum, floor of mouth, palate, cheek, vestibule of mouth, retromolar area, tonsil or oropharynx .The following details of the included studies were independently extracted by two reviewers: first author, publication year, region , study design, sample size (case/non-case), age and sex of participants, case definition, control definition, type of SLT product, confounders adjusted, matching of control, and reported sex-specific effect estimate. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of observational studies, and this assessment was performed by two reviewers independently . A studyI2 and Q statistics, and I2 > 50.0% or P < 0.10 was considered to indicate significant heterogeneity [The association between SLT use and OCC risk was assessed using a sex-specific effect estimates with a 95% confidence interval (CI). Given the low incidence of OCC, the odds ratio (OR) was approximately equal to the relative risk (RR). A random-effects model was applied to calculate pooled RRs and 95%CIs for the relationship between SLT use and OCC risk in men and women. The female-to-male ratio of RRs (RRRs) and 95%CIs were calculated using studies that reported the direct comparisons between men and women in terms of SLT use and OCC risk. The RRRs for indirect comparisons were calculated using the studies that only reported the relationship between SLT use and OCC risk in men or women. The pooled RRRs and 95%CIs for sex-based difference in the association between SLT use and OCC risk were calculated using a random-effects model . Heterogogeneity .P values for the pooled results were two-sided, and the inspection level was 0.05. All statistical analyses were conducted using software the STATA software .Sensitivity analysis was conducted to assess the stability and reliability of the meta-analysis by excluding indirect comparison results . Subgroun = 19), other exposures were investigated (n = 17), or insufficient data (n = 11). Finally, 19 studies were selected for the meta-analysis [The electronic search yielded 6132 records, and 4895 articles were retained after duplicate removal. A total of 4831 articles were excluded after reviewing the title and abstract. The remaining 64 studies were retrieved for full-text evaluations, and 2 studies were obtained by manually searching the reference lists of the 64 studies. Thereafter, 47 studies were excluded for the following reasons: effect estimates were only provided for men and women combined  and women  and women had a much higher risk than did men  and women .Sixteen studies in men and 11 studies in women reported the association between SLT use and OCC risk. We noted that SLT use was associated with an increased risk of OCC in both men . A significant difference was also found in the pooled RRR of indirect comparisons . After excluding indirect comparison results, the conclusion was stable and not altered  or Begg test (P = 0.488).Potential publication bias for sex-based difference in the association between SLT use and OCC risk was observed by reviewing a funnel plot Fig. . HoweverOur study provided both direct and indirect comparisons between SLT use and OCC risk for the first time. We found that SLT use was a strong and independent risk factor for OCC in both men and women. SLT use in women was associated with an increased risk of OCC compared to that in men, irrespective of whether the whole cohort was considered, or only direct comparison results were considered. Subgroup analysis indicated that the sex-based differences were more evident in populations receiving chewed SLT products and in studies with high-quality designs.pan and tobacco (chewed), while no significant sex-based difference was detected in those who use areca nut/lime and tobacco (chewed). Moreover, Balaram et al. [pan with tobacco (chewed). This could be explained by the differences in behavior and methodological issues, including the levels of background smoking and drinking, smaller sample size and lower event rates in women. Most studies had adjusted for confounding variables including age, alcohol, smoking, religion, education, and residential area and matched the controls with cases. However, the possible impact of these confounders was difficult to determine in the present analysis. Therefore, the reliable of pooled results needs further verification by fully adjusting for potential confounders in large-scale populations with long-term follow-up.The pooled result of this study found that the OCC risk related to SLT use in women was significantly higher than that in men based on direct or indirect comparison results. However, among the studies included in the direct comparison, no significant differences were found between men and women, and only 2 studies , 41 obsem et al.  found thSubgroup analysis suggested that significant sex-based differences in SLT-associated OCC risk were found only in individuals receiving chewed smokeless products, regardless of the control definition used in the studies. This finding could probably be attributed to the chewing of SLT product containing betel nut, which was associated with a high risk of OCC , and theNumerous studies –14 have The strengths of this study should be highlighted: (1) this study is the first to estimate the sex-based difference in the relationship between SLT use and OCC risk based on whole cohort and direct comparison results; (2) the pooled result of this study was based on a large number of individuals and would be more robust than those of any individual study; and (3) the results of the subgroup analysis based on the study or participants’ characteristics could help screen the SLT users at high risk for OCC.However, the limitations of this study should be acknowledged as well: (1) this meta-analysis was based on both prospective and retrospective observational studies, which caused inevitable selection and recall bias; (2) several included studies only provided crude effect estimates, which could bias the pooled effect estimate; (3) subgroup analysis stratified by specific SLT products was not conducted owing to the small number of included studies; and (4) potential publication bias was inevitable because of the unavailability of unpublished data.This study found that SLT use was associated with a higher risk of OCC in women than in men. Further large-scale prospective cohort studies should be conducted to verify sex-based difference in specific smokeless products.


The relationship between uncoupling protein (UCP) 1-3 polymorphisms and susceptibility to type 2 diabetes mellitus (T2DM) has been extensively studied, while conclusions remain contradictory. Thus, we performed this meta-analysis to elucidate whether the UCP1-3826A/G, UCP2-866G/A, Ala55Val, and UCP3-55C/T polymorphisms are associated with T2DM.  Eligible studies were searched from PubMed, Cochrane Library, and Web of Science database before 12 July 2020. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated to evaluate the strength of the association. Heterogeneity analysis, subgroup analysis, sensitivity analysis, and publication bias were also performed. P < 0.01; homozygous model: OR = 1.33, 95% CI 1.03-1.72, P = 0.029, respectively). In subgroup analysis stratified by ethnicity, T2DM risk was increased with the UCP2 Ala55Val polymorphism , while decreased with the UCP2-866G/A polymorphism in Asians .  A total of 38 case-control studies were included in this meta-analysis. The overall results revealed significant association between T2DM and the UCP2 Ala55Val polymorphism (recessive model: OR = 1.25, 95% CI 1.12-1.40,  Our results demonstrate that the UCP2-866G/A polymorphism is protective against T2DM, while the UCP2 Ala55Val polymorphism is susceptible to T2DM in Asians. Diabetes is a serious public health problem characterized by chronic hyperglycemia. The International Diabetes Federation (IDF) estimates that there were approximately 463 million adults (aged 20-79 years) diagnosed with diabetes in 2019, and this number is expected to reach 700 million by 2045 across the world [β cells and cells of the immune system, skeletal muscle, spleen, liver, lung, and macrophages; UCP3 is primarily expressed in skeletal muscle, but it is also found in BAT and heart tissue; UCP4 and UCP5 are recently discovered mainly in the central nervous system [Uncoupling proteins (UCPs) are a family of mitochondrial anion transporters located in the mitochondrial inner membrane which plays crucial roles in regulating the flux of protons through the ATP synthase . There as system –9. Moreos system –14. For s system , 16.Human UCP1 gene is located on chromosome 4q28-q31 and 8.9 kb in length, while both UCP2 and UCP3 genes map to chromosome 11q13 and spans 8.2 and 8.7 kb, respectively . Over thThis meta-analysis was performed in accordance to the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines (File S1).We systematically searched electronic databases of PubMed, Cochrane Library, and Web of Science for all relevant articles published before 12 July 2020. The search terms were applied as follows: (“diabetes” or “T2D” or “T2DM”) and (“uncoupling protein” or “UCP”) and (“polymorphism” or “mutation” or “variant”). To obtain more qualified studies, the references cited in the original research and review articles were also manually searched. The papers were restricted to humans and written in English.Studies were considered eligible when meeting the following inclusion criteria: (1) case-control study design; (2) evaluating the association between the UCP1-3826A/G, UCP2-866G/A and Ala55Val, and UCP3-55C/T polymorphisms and T2DM susceptibility; and (3) providing sufficient genotype data to calculate odds ratios (ORs) and 95% confidence intervals (CIs). The exclusion criteria were (1) editorials, case reports, letters, comments, reviews, or meta-analyses and (2) studies without detailed genotyping data. Furthermore, if there were duplicate publications based on the same data, only the latest or most complete study was included in our meta-analysis.Two reviewers (Huang R and Cai TT) independently extracted the following data from the enrolled studies: first author, publication year, ethnicity, genotyping method, total number of cases and controls, genotype and allele distributions of cases and controls, and controls with Hardy-Weinberg equilibrium (HWE) or not. All possible efforts were made to contact the corresponding authors if essential data were needed. Any discrepancy in data extraction was resolved by a third reviewer (Zhou YT).Two investigators (Wang YM and Wang HY) separately performed the quality assessment of each included study using the Newcastle-Ottawa quality assessment scale (NOS). The NOS comprises the following three aspects: selection of study subjects (4 points), comparability of study subjects (2 points), and exposure or outcomes (3 points) . The totχ2 test. Pooled ORs with corresponding 95% CIs were used to measure the strength of the association between UCP1-3826A/G, UCP2-866G/A and Ala55Val, and UCP3-55C/T polymorphisms and T2DM susceptibility under the following models: allele model, dominant model, recessive model, homozygous model, and heterozygous model. Subgroup analysis was performed according to the ethnicity of included populations. The heterogeneity across studies was estimated via Q test and I2 statistics. I2 > 50% or PQ ≤ 0.1 was considered to indicate significant heterogeneity. If significant heterogeneity existed, random effects model (REM) was used; otherwise, fixed effects model (FEM) was applied. Galbraith plot was conducted to explore the outlier and main contributor to heterogeneity. To assess the stability of the results, sensitivity analysis was carried out by omitting each study in sequence. Additionally, potential publication bias was evaluated with Begg's funnel plot and Egger's test. All statistical analyses were performed using STATA Version 11.0 , and a two-sided P value < 0.05 was considered statistically significant.HWE of the genotype distribution in the control subjects was assessed by As described in the flow chart, a total of 583 studies were retrieved through searching the electronic database . After eP < 0.01; homozygous model: OR = 1.33, 95% CI 1.03-1.72, P = 0.029, respectively), but no associations between T2DM and UCP1-3826A/G, UCP2-866G/A or UCP3-55C/T polymorphisms in the overall population. Further in the subgroup analyses stratified by ethnicity, T2DM risk was increased with UCP2 Ala55Val polymorphism , while decreased with UCP2-866G/A polymorphism in Asians   .As shown in P = 0.039; OR = 1.15, 95% CI 1.02-1.29, P = 0.024; OR = 1.21, 95% CI 0.99-1.47, P = 0.064; OR = 1.25, 95% CI 0.96-1.64, P = 0.102, respectively)  .P values obtained from Egger's test were >0.05, which interpreted that there is no publication bias for any of the UCP polymorphisms analyzed  to valine  . AlthougThe UCP3 -55C/T promoter variant is of interest because of its position at 4 bp downstream of a peroxisome proliferator-activated receptor (PPAR) responsive region, which could modify PPAR-dependent responsiveness . Thus, mAlthough some previous meta-analyses reported the role of UCP polymorphisms in the risk for T2DM, our meta-analysis included the most recent publications and conducted a series of analyses, including subgroup analysis, heterogeneity analysis, sensitivity analysis, and publication bias, to achieve more accurate results. Certainly, some limitations should be acknowledged in the present study for better interpreting the results . FirstlyIn conclusion, our results demonstrated that the -866G/A polymorphism is protective against T2DM, while the Ala55Val polymorphism of UCP2 gene is susceptible to T2DM in Asians. Nevertheless, given the presence of between-study heterogeneity and confounding factors in this meta-analysis, further well-designed and large-scale studies, particularly, studies that take the effects of gene-gene and gene-environment interactions into consideration, should be conducted to verify the current findings.


Hyperhomocysteinemia has been defined as an elevated serum concentration of homocysteine exceeding 15 μmol/L and has been proven to play an important role in the pathogenesis of cerebrovascular disease. The prevalence of hyperhomocysteinemia in China has been outlined in a previous meta-analysis. Considering the key role of homocysteine in the process of vascular injury, more studies have been conducted to prevent hyperhomocysteinemia by nutritional supplements such as folic acid or other treatments. Additionally, studies have shown that the prevalence of hyperhomocysteinemia increases over time; therefore, it was necessary to provide an update from the previous meta-analysis on homocysteine status in China. This was needed to understand the prevalence, the trend in changes over time, and its determinants. The results highlight that the prevalence of hyperhomocysteinemia is increasing in China, especially among the elderly, men, and residents in the north, inland areas, and rural areas of China.2 = 99.8%, p for heterogeneity < 0.001). The trend of HHcy prevalence was gradually upward over time, with increases during 2015–2016 , but steady between 2015–2016 and 2017–2018. Subgroup analysis showed that the prevalence was higher in the elderly over 55 years old, males, and residents in the north, inland, and rural China . Meta-regression analysis revealed that age and area of study contributed to 42.3% of the heterogeneity between studies. The current meta-analysis provides strong evidence that the prevalence of HHcy is increasing in China, and varies substantially across different ages, genders, and geographic distribution. Accordingly, high-risk population groups should be focused on, and public health policies and strategies should be carried out to prevent and control HHcy in China.We conducted a meta-analysis to systematically assess the prevalence of hyperhomocysteinemia (HHcy) in China, its change over time, and its determinants. Literature searches were conducted using English databases  and Chinese databases . The time ranges were from Jan 2014 to Mar 2021 in China. We adopted the random effects model to estimate the pooled positive rates of HHcy and corresponding 95% confidence intervals (95% CI). To find the sources of heterogeneity, we performed subgroup analysis and meta-regression. A total of 29 related articles were identified involving 338,660 participants with 128,147 HHcy cases. The estimated prevalence of HHcy in China was 37.2% (95% CI: 32.6–41.8%, I Hyperhomocysteinemia (HHcy) has been defined as elevated serum concentrations of homocysteine (Hcy) exceeding 15 μmol/L , which hThe prevalence of HHcy in China has been determined and was presented in a previously published meta-analysis . In summTherefore, our study proposes to update the estimates of the prevalence of HHcy in China, to determine the trend of change, and to explore additional data to determine the potential impact factors for HHcy. The current study would provide evidence for the early prevention and reduction of HHcy in China.We manually searched for literature regarding population-based observational studies on the prevalence of HHcy published from January 2014 to March 2021 in China using the English databases PubMed, Embase, Web of Science, and the Chinese CNKI , CBM , VIP, and Wanfang electronic databases. The keywords used for the search were (“homocysteine” OR “homocysteinemia” OR “hyperhomocysteinemia”) AND (“China” OR “Chinese”) AND  AND . To find additional relevant studies, the reference lists of the identified studies were also checked thoroughly.Two reviewers independently completed identifying, screening, and including studies, as shown in Two reviewers independently completed data extraction and the risk of bias evaluation, and any difference in these processes was discussed and determined with a third reviewer. The extracted information was: name of the first author, year of publication, year of data collection , mean age, population source , sample size, number of HHcy cases, prevalence of HHcy , region or province , area (inland or coast), and setting .In this meta-analysis, the potential bias of the included studies was assessed by using the Agency for Healthcare Research and Quality (AHRQ) . The biap values less than 0.05 were considered statistically significant, unless otherwise stated. The I2 test was used to assess heterogeneity [p for comparison <0.05 was considered statistically significant. In meta-regression analysis, independent variables included mean age, sex ratio , study area , study location , study setting , sample size, data collection year, publication year, population source , and research topic (main outcome and secondary outcome). Among these variables, mean age, sex ratio , sample size, data collection year, and publication year are continuous variables. First, we performed univariate meta-regression analysis for all variables. Second, we selected those variables with p < 0.1 in univariate meta-regression analysis for further multivariate analysis to explore the source of heterogeneity [The statistical analysis was performed using a Stata software package version 11.0 program  and SPSS Statistics version 19.0 for Windows . All statistical analysis carried out in this study used the two-tailed method, and ogeneity . Accordiogeneity . Subgrouogeneity ,27 to anogeneity . Egg’s togeneity  and sensThe current meta-analysis finally comprised 29 studies (9 from English and 20 from Chinese databases), involving 338,660 participants aged 20–74 years, among whom 128,147 had positive cases of HHcy. Prevalence data collected from 2002–2018, covering 13 provinces and 3 municipalities of China . A basic description of these studies is provided in 2 = 99.8%, p for heterogeneity < 0.001), as shown in p for comparison < 0.001), males , north China , inland area , rural , sample size ≥ 2000 , community based , and HHcy is the secondary outcome .The pooled prevalence of HHcy in China was 37.2%  but remained steady between 2015–2015 and 2017–2018.According to the trend of changes in the prevalence of HHcy in China over time, years of data collection of the included studies were synthesized and divided into four groups . As the current meta-analysis was a follow-up to a previous study (1990–2012), the years of 2013–2018 were a particular focus. The results showed that the trend of prevalence of HHcy increased over time and increased during 2015–2016  and men (53.0%). Age was proven to affect the prevalence of HHcy in the study by Xu et al., which found that the concentration of Hcy in people aged 30–50 years was the lowest, increasing over the age of 50 . The eldAnother interesting finding was that the geographical distribution difference between the studies also affected the prevalence of HHcy among Chinese populations. HHcy was more common in north China 45.7%), inland area 41.6%), and rural residents 42.3%), and is consistent with other studies ,37. The .6%, and .3%, and .7%, inlaAccurate estimate and temporal evolution of the prevalence of HHcy was crucial for the planning, monitoring, and management of public health interventions on HHcy-related health problems. On the basis of ensuring consistency of results with the previous meta-analysis, the strengths of this study were: (1) to update the Hcy status in recent years, and we observed a slightly increasing trend of HHcy prevalence in China; (2) to include more studies investigating the prevalence of HHcy in south China; (3) to perform meta-regression analysis on age and area (inland/coast) to determine the source, which could explain 42.3% of the between-study heterogeneity. There were some limitations in our study. According to Additionally, the sample size of some included studies varied , and studies with low samples were less representative. Therefore, future studies are needed to better understand HHcy in the following areas: (1) to develop a set of unified HHcy diagnostic criteria suitable for China, which could accurately reflect the prevalence of HHcy in China; (2) all regions should pay attention to the prevalence of HHcy and perform a high-quality epidemiological investigation, providing reliable scientific evidence for the prevention, treatment, and control of HHcy in China.The current meta-analysis provided strong evidence that the prevalence of HHcy has increased in China, especially among the elderly, men, residents in the north, inland areas, and rural parts of China. Therefore, high-risk populations should be the focus of public health policies, and preventive strategies should be performed and implemented to prevent and control the increase in HHcy in China.


Current evidence from randomized controlled trials on statins for primary prevention of cardiovascular disease (CVD) in older people, especially those aged > 75 years, is still lacking. We conducted a systematic review and meta-analysis of observational studies to extend the current evidence about the association of statin use in older people primary prevention group with risk of CVD and mortality.PubMed, Scopus, and Embase were searched from inception until March 18, 2021. We included observational studies (cohort or nested case-control) that compared statin use vs non-use for primary prevention of CVD in older people aged ≥ 65 years; provided that each of them reported the risk estimate on at least one of the following primary outcomes: all cause-mortality, CVD death, myocardial infarction (MI), and stroke. Risk estimates of each relevant outcome were pooled as a hazard ratio (HR) with a 95% confidence interval (CI) using the random-effects meta-analysis model. The quality of the evidence was rated using the GRADE approach.n = 815,667) fulfilled our criteria. The overall combined estimate suggested that statin therapy was associated with a significantly lower risk of all-cause mortality (HR: 0.86 [95% CI 0.79 to 0.93]), CVD death (HR: 0.80 [95% CI 0.78 to 0.81]), and stroke (HR: 0.85 [95% CI 0.76 to 0.94]) and a non-significant association with risk of MI (HR 0.74 [95% CI 0.53 to 1.02]). The beneficial association of statins with the risk of all-cause mortality remained significant even at higher ages  and in both men (HR: 0.75 [95% CI: 0.74 to 0.76]) and women (HR 0.85 [95% CI 0.72 to 0.99]). However, this association with the risk of all-cause mortality remained significant only in those with diabetes mellitus (DM) (HR 0.82 [95% CI 0.68 to 0.98]) but not in those without DM. The level of evidence of all the primary outcomes was rated as “very low.”Ten observational studies  without CVD was associated with a 14%, 20%, and 15% lower risk of all-cause mortality, CVD death, and stroke, respectively. The beneficial association with the risk of all-cause mortality remained significant even at higher ages (> 75 years old), in both men and women, and in individuals with DM, but not in those without DM. These observational findings support the need for trials to test the benefits of statins in those above 75 years of age.The online version contains supplementary material available at 10.1186/s12916-021-02009-1. Cardiovascular disease (CVD) is the major cause of mortality worldwide –3. More The consideration of statins for primary CVD prevention in older people represents a dilemma in clinical practice unlike the secondary prevention, which is well-established and supported by a level (A) evidence, according to the most recent European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guidelines , 8. CurrOne important limitation in the previous results is reporting only the treatment effect on a composite outcome  without reporting the results of its component outcomes  that greatly varies in their individual clinical importance . TherefoOther limitations of the current evidence from RCTs include: (Ι) underrepresentation of the older people; most of the available data are from subgroup analyses, and (ΙΙ) relatively short follow-up durations; especially when evaluating the treatment effect on mortality and the potential development of some side effects such as cancer incidence and new onset diabetes mellitus (NODM) that may require longer durations for adequate assessment. Consequently, observational studies on statins for primary prevention in older people may extend the current limited evidence through their larger populations, longer durations of follow-up, and better clinical practice generalizability than the RCTs. To our knowledge, no former meta-analysis assessed such outcomes from observational studies.To address this issue, we conducted a systematic review and meta-analysis of the observational studies to provide better evidence about the association of statin use in older people primary prevention group  with the risk of CVD and mortality.We designed this study according to the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines  terms reported in Supplementary Table After removing the duplicates by Endnote X7 , two independent authors (MM and MZ) performed a two-step screening of the remaining articles. Firstly, title/abstract screening then, full-text screening according to the predefined inclusion/exclusion criteria. Disagreement was resolved by the opinion of a third author (KA).Original studies were included if they met the following criteria: (1) being an observational study (cohort or nested case-control), (2) compared using a statin  with no statins, (3) being restricted to or included a subgroup of older people aged ≥ 65 years and without established CVD , and (4) reported the risk estimate as a hazard ratio (HR), odds ratio (OR) with its 95% CI on at least one of the following outcomes: all cause-mortality, CVD death, MI, and stroke.Exclusion criteria included any of the following: (1) RCTs, experimental studies, reviews, theses, and book chapters, (2) studies whose full-texts were not available or with non-English content, (3) studies that contained made-up data or were retracted by the journal, or (4) studies that missed any of the inclusion criteria.Using preformatted tables, two independent authors  reviewed the included articles and extracted the following data: (1) first author’s name, (2) year of publication, (3) study location, (4) study design, (5) follow-up duration, (6) study population characteristics, and (7) data regarding the relevant outcomes . Disagreements were resolved upon the opinion of another author (KA).Primary outcomes were risk estimates of all cause-mortality, CVD death, MI, and stroke. Secondary outcomes included risk estimates on NODM and cancer incidence.If a study reported its data on the older people as multiple age cohorts, in which participants of the first age cohort who survived to the next target age could have been a part of multiple age cohorts, we only extracted data of the age cohort with the largest sample size to avoid overlapped data.Two reviewers (KA and MZ) independently used The Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool for the risk of bias assessment of the included studies . This toThe level of evidence of each primary outcome was rated as very low, low, moderate, or high quality using the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach . This raOdds ratios from nested case-control studies may be considered to be equivalent to HRs from cohort studies obtained by the Cox regression analysis , 21. The2 and Chi2 tests. Interpretation of these tests was done in accordance with the “Cochrane handbook for systematic reviews of interventions,” in which an alpha level (for Chi2 test) < 0.1 is considered as significant heterogeneity and the I2 test is read as follows: 0–40%, might not be important; 30–60%, may represent moderate heterogeneity; and 50–90%, may represent substantial heterogeneity [Between-study heterogeneity was measured by Iogeneity .To investigate the risk estimate across different older ages and to address the heterogeneity, a subgroup analysis (based on the availability of relevant data for the intended subgroups in the included studies) was conducted according to the age of the participants as follows: 65 to 75 years, ≥ 75 years, ≥ 80 years, and ≥ 85 years. Other subgroup analyses according to sex, presence of DM and risk of bias level were also conducted. Subgroups focused only on all-cause mortality outcome, which was sufficiently reported in most of the included studies.To assess the impact of each study on the overall combined risk estimate , we conducted “leave-one-out sensitivity analysis,” by omitting one study each time and repeating the analysis.www.epigear.com) and Comprehensive Meta-Analysis version 3 .Potential publication bias was assessed by visual inspection of Begg’s funnel plot asymmetry and confirmed by Egger’s regression test . Funnel The literature search yielded 9727 records. After removing the duplicates and the two-step screening, ten observational studies –34 with n = 4), North America , and Asia . The covariates that were used for analysis adjustment in the included studies are shown in Supplementary Table Characteristics and baseline parameters of the included studies are shown in Table According to the ROBINS-I tool, the risk of bias was rated as moderate in four included studies and as serious in six studies. One important source of the serious risk of bias in six included studies was including prevalent statin users  instead of statins new users . The risk of bias assessment is summarized in Supplementary Table n = 9; Fig. n = 4; Fig. n = 8; Fig. n = 5; Fig. 2 = 90%, P value < 0.0001), stroke , and MI . No heterogeneity was observed in the case of CVD death . According to the GRADE approach, the level of evidence of all the primary outcomes was rated as “very low.” The quality of evidence assessment is summarized in Supplementary Table Overall pooled analysis suggested that statin use was significantly associated with a lower risk of all-cause mortality .There was a non-significant association between statin use and the risk of T2DM . There was still a significant heterogeneity in the other age subgroups .Subgroup analysis suggested that statin use was significantly associated with a lower risk of all-cause mortality, compared with statin non-use, in all age subgroups as follows: 65 to 75 years .In the subgroup analysis according to sex, statin use was significantly associated with a lower risk of all-cause mortality, compared with statin non-use, in both men .As for subgroups according to DM, a significant association was found between statin use and the risk of all-cause mortality only in older people with DM .In the subgroup analysis according to risk of bias level within the included studies, statin use was significantly associated with a lower risk of all-cause mortality, compared with statin non-use, only in case of serious risk of bias , stroke , and new-onset cancer  and excluded the presence of publication bias for the rest of the outcomes  revealed that high levels of IL-6 were associated with a higher risk of all-cause mortality in older people [These results are of interest especially in the context of the involved mechanism(s). Several epidemiological studies revealed no association or even an inverse association between low total cholesterol (TC), specifically LDL-C, and all-cause mortality in older people . Howeverr people . In liner people .2 = 43.7%, studies n = 5) compared with placebo in older participants without CVD. Our finding on stroke is in line with this meta-analysis. In contrast, a recent meta-analysis including nine RCTs conducted by Ponce et al. [2 = 58.1%, studies n = 6), compared with placebo, in older participants without CVD. However, the result of this meta-analysis [In a meta-analysis that included eight RCTs, Savarese et al.  found the et al.  suggesteanalysis , unlike analysis , was notIn contradistinction to the aforementioned meta-analyses of RCTs , 14, ourp = 0.03). In line with our study, statin use for primary prevention was also associated with a lower risk of all-cause mortality  compared with statin non-use in a retrospective cohort included 1370 older Korean adults (aged ≥ 75 years); this observed association was more evident  in case of statin use for more than 5 years [Unlike the above-mentioned meta-analyses of RCTs , 14, our 5 years . However 5 years , 53. Eve 5 years , 54. Onl 5 years . In this 5 years  observedIn the present study, the observed beneficial association of statins with the risk of all-cause mortality remained significant even at higher ages. This finding is in line with the previously mentioned result from Mendelian randomization studies about the preserved risk role of elevated LDL-C in the oldest old people (> 90 years) . HoweverThe beneficial association with statins in terms of all-cause mortality was still evident in the subgroup that included studies with serious risk of bias but not in that with moderate risk of bias studies. Inclusion of prevalent statin users instead of statin new users in all the studies with serious risk of bias, denoting the long-term effect of statins, may explain this observed result , 60. HowThe older population has a higher risk of drugs adverse effects because of multiple comorbidities, polypharmacy, and altered pharmacokinetics and pharmacodynamics –66. StatNone of the included studies reported data on other statin safety concerns in older people, including statin-associated muscle symptoms (SAMS) or cognitive impairment except one study by Zhou et al.  that repOlder people are heterogenous in many aspects  . They weThis meta-analysis has several limitations. First, it is based only on observational studies. One critical source of bias in six included studies was including prevalent statin users instead of statins new users. Thus, the present results might have been influenced by residual confounding. Second, unresolved heterogeneity was reported in terms of all-cause mortality, stroke, and MI. Clinical diversity  and methodological diversity  among the included studies are possible causes of this observed heterogeneity. However, we addressed this heterogeneity by applying the random-effects model in the analysis and conducting subgroup analyses. Third, potential publication bias was observed in all relevant outcomes. Fourth, data on relevant outcomes  were not sufficient for further subgroup analyses. Fifth, none of the included studies reported data on any of the relevant outcomes stratified by the participants’ baseline CVD risk score except the study by Gitsels et al. ; they grFuture studies should employ a randomized design with long-term follow-up periods. A consensus set of standardized outcomes should be provided to and followed by future trialists. The development and validation of a risk score for older people to predict the risk of cardiovascular events can inform the clinical applicability of statin use in this population. In addition, safety outcomes should be a culprit in future studies in this high-risk population, and outcomes that relate to cost-effectiveness and quality of life should also be considered.In conclusion, statin therapy appears to be associated with a significantly lower risk of all-cause mortality, CVD death, and stroke  in older people aged ≥ 65 years and without CVD. The beneficial association of statins with the risk of all-cause mortality remained significant even at different higher ages. It also was significant in both men and women. However, the association with all-cause mortality remained significant only in older people with DM but not in those without DM. There was no association between statin use and the risk of MI, incident T2DM, or new-onset cancer. These findings suggest statins may offer benefits in the older people in primary prevention setting especially those at the higher risk of CVD . As such, these findings support the need for ongoing trials of statins in older adults.Additional file 1: Supplementary Figure 1. Forest plot displaying the results of the meta-analysis of observational studies that compared statin use with non-use in older people aged ≥65 years and without cardiovascular disease – A: in terms of type 2 diabetes mellitus and B: in terms of new-onset cancer. HR, hazard ratio; CI, confidence interval; T2DM, type 2 diabetes mellitus.Additional file 2: Supplementary Figure 2. The corrected funnel plots displaying publication bias in the observational studies that compared statin using with non-using in older people aged ≥65 years and without cardiovascular disease – A: in terms of all-cause mortality; B: in terms of cardiovascular death; C: in terms of myocardial infarction; D: in terms of stroke; E: in terms of type 2 diabetes mellitus and F: in terms of new-onset cancer.Additional file 3: Supplementary Table 1. MOOSE Checklist for Meta-analyses of Observational Studies.Additional file 4: Supplementary Table 2. Literature search strategy for each relevant database.Additional file 5: Supplementary Table 3. List of excluded studies and reasons for exclusion.Additional file 6: Supplementary Table 4. Covariates adjustment in the included studies.Additional file 7: Supplementary Table 5. Risk of bias of included studies using Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) Tool.Additional file 8: Supplementary Table 6. GRADE assessment of quality of evidence.Additional file 9: Supplementary Table 7. Results of publication bias assessment using funnel plot asymmetry, trim and fill method, and Egger’s test