Stimulating food is emerging as an important modifiable factor in the development of gastrointestinal (GI) tract cancers, but the association between chili pepper consumption and the risk of GI cancers is unclear. We aimed to evaluate the direction and magnitude of the association between chili pepper consumption and the risk of GI cancers.A literature search was performed in PubMed, Embase, and Web of Science databases from inception to 22 December 2021. Observational studies reporting the association between chili pepper consumption and the risk of gastric cancer (GC), esophageal cancer (EC), and/or colorectal cancer (CRC) in adults were eligible for inclusion. Data extraction and quality assessment were conducted independently by two reviewers for the included literature. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup analyses were also performed based on the cancer type, study design, region of the study, study quality, and adjustments.A total of 11,421 studies were screened, and 14 case-control studies were included involving 5009 GI cancers among 11,310 participants. The summary OR showed that high consumption of chili pepper was positively related to the risk of GI cancers . A stronger positive relationship was observed between chili pepper consumption and EC risk , but there was no statistically significant association between GC and CRC risk. In analyses stratified by geographical location, a positive association was found between chili pepper consumption and the risk of GI cancers in Asian studies , African studies , and North American studies , but an inverse association was seen in South American studies  and European studies .This meta-analysis suggests that chili pepper is a risk factor for certain GI cancers . Geographical regions influence the risk of GI cancers, especially in Asian, African, and North American populations, which require more attention during dietary guidance.https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022320670].[ Globally, gastrointestinal (GI) tract cancers are a significant cause of morbidity and mortality, of which the most prevalent are colorectal cancer (CRC), gastric cancer (GC), and esophageal cancer (EC), ranking third, fifth, and eighth in incidence, respectively, but second, fourth, and sixth in mortality in both sexes combined according to GLOBOCAN estimates for 2020 . Despitein vitro and vivo experiments  . This reWe searched PubMed, Embase, and Web of Science for studies in humans on the association between chili pepper consumption and the risk of GI cancers from inception until 22 December 2021, using (“spicy” OR “chili” OR “chilli” OR “pepper” OR “capsaicin” OR “paprika”) AND  as search terms. Additionally, references to relevant articles and recent reviews were manually searched to identify other eligible articles.Studies that satisfied the following criteria were included in this meta-analysis: (1) participants were adults; (2) studies were observational ; (3) information was available on the relationship between chili pepper consumption as the exposure of interest and the risk of EC, GC, and/or CRC as the outcome of interest; and (4) studies reported available risk estimates in the form of relative risk (RR), odds ratio (OR), or hazard ratio (HR) with 95% confidence intervals (CIs). When overlapping populations were included in multiple articles, only the most recent or largest population was used to avoid duplications.Non-English articles were excluded. Studies were excluded if they were reviews, letters, posters, meetings, or conference abstracts. We also excluded studies that included patients with precancerous lesions as an outcome of interest, mixed chili pepper with other foods  as the exposure of interest, had a sample size of fewer than 20 cases, and were conducted on children or adolescents. Additionally, studies with insufficient data were excluded. All searches were performed independently by two authors (CC and MZ), and inconsistencies were resolved through discussion.Two investigators (CC and MZ) independently reviewed and performed the data extraction from all the included studies. The extracted characteristics and data were composed of the first author’s last name, publication year, country, study design , number of study populations and cases, mean/median age of participants, male ratio, assessment method of exposure, GI cancer type, risk estimates and corresponding 95% CI, and covariates adjusted in multivariate analysis. For studies reporting several multivariate-adjusted risk estimates, the risk estimates that were maximally adjusted for underlying confounders were the top priority for use. Any discrepancies during the data extraction process were determined through discussion with a third investigator (XZ).The quality of the included studies was evaluated using a modified version of the Newcastle–Ottawa Quality Assessment Scale (NOS)  with a nI-square (I2) statistic , study design , region of the study , study quality , adjustment for alcohol intake (Yes or No), and adjustment for smoking (Yes or No). Statistical analyses were done using Stata 16.0 software . All Our search strategy retrieved 11,421 studies from 3 databases, and 3,227 duplicates were excluded. A further 8,194 studies were screened based on titles and abstracts, of which 8,064 articles were excluded because they did not meet the eligibility criteria. The remaining 130 studies were identified for full-text review, and 116 studies were excluded due to 54 being non-chili exposure, 16 being non-GI cancers, 14 studies being editorial, letter, poster, meeting, and conference abstract, the data of 13 studies being unavailable, 11 studies being review, 7 studies being published in a non-English language, and 1 study reporting the same population , 22–33 wThe detailed quality assessment of the included studies by the modified NOS for case-control studies is shown in 2I = 90.3%; P < 0.001). No evidence of publication bias was found based on Egger’s test (P = 0.651) and symmetrical funnel plot , but not with GC  and CRC risk  . When stThis systematic review and meta-analysis was designed to evaluate the association between chili pepper consumption and the risk of GI cancers. The evaluation of 14 case-control studies involving 11,310 participants found a positive association between chili pepper consumption and the risk of GI cancers. In the subgroup analysis, this correlation between high chili pepper consumption and rising GI cancer risk was applied to EC, but not to GC and CRC. Especially in Asia, Africa, and North America, chili pepper intake showed a significant positive correlation with GI cancer risk.In this study, the intake of chili pepper was positively associated with EC risk. The same finding was also observed for the consumption of chili pepper and GI cancer risk. Given that EC is a part of all GI cancers, the observed increased association with GI cancers appears to be related to EC. Several mechanisms could explain why higher chili pepper consumption was significantly associated with an increased risk of EC, but not with GC and CRC. The different effects could be due to differences in cancer sites. Chili peppers are rich in CAP, which has an intensely pungent flavor, further leading to a sensation of tingling and burning pain by stimulating transient receptor potential vanilloid 1 (TRPV1) –36. The Several meta-analyses have investigated the relationship between the frequency of chili pepper consumption and GI cancer risk, with controversial results. When comparing the highest with lowest categories, most meta-analyses revealed a positive association between chili pepper intake and GC risk –13, whilWhen stratified by the region of the studies, those studies conducted in Asia, North America, and Africa indicated that participants consuming the highest category of chili pepper had a greater risk of GI cancers, whereas three studies conducted in South America and Europe reported a significantly lower risk of GI cancers , 22, 29.In addition, subgroup analysis revealed that studies adjusted for alcohol consumption in the final model examining chili pepper intake and the risk of GI cancers had a positive association. Meanwhile, a seemingly stronger association between chili pepper consumption and the risk of GI cancers was observed in studies with adjustment for smoking than in those without such adjustment. The small number of original studies focusing on adjustment for smoking (n = 8) or alcohol consumption (n = 6) may be a possible reason. Another explanation is that numerous studies have found alcohol consumption or smoking to be related to a higher risk of GI cancers –48. HoweH. pylori) infection status was limited as data on H. pylori infection were only provided in one original study  and IFN-γ (H. pylori infection rate (H. pylori infection may act as a mediator and confound the association between chili pepper consumption and cancer risk.Although a series of prespecified subgroup analyses were conducted, some heterogeneity generally persisted and could not be reduced. There were some other reasons for the heterogeneity among the included studies. First, the types of chili peppers consumed in different regions may have contributed to the heterogeneity among the results. However, few of the included studies reported specific types of chili peppers, except for two studies, in which the types of chili peppers were reported as sweet pepper  and red al study . H. pylond IFN-γ . On the ion rate . Thus, HCertain limitations of this study should be acknowledged. First, given the observational nature of the included studies, it is possible that the associations we found reflected residual confounding. Although a large number of potential confounders, such as cancer type, study design, and region of the study, were adjusted for in most studies, we cannot exclude that some other dietary biologically active components may partly or wholly affect the association. Second, recall bias associated with the assessment methods of chili pepper exposure should be considered because FFQ or frequency-reported questionnaires are subject to measurement errors, which can attenuate or overestimate the observed association . AdditioOur results suggest that chili pepper consumption is associated with an increased risk of certain GI cancers. An increased EC risk was observed when high levels of chili pepper were ingested. However, no significant association was found between chili pepper consumption and the risk of GC and CRC. More prospective cohort studies are necessary to clarify the dose-response effect of chili pepper on the risk of GI cancers.The original contributions presented in this study are included in the article/CC and MZ designed the study, performed the literature search, extracted data, conducted the statistical analysis, and drafted the manuscript. CC, XZ, and HL performed data screening, interpreted the data, and performed the writing review of the manuscript. All authors contributed to the articles and approved the final manuscript.


Identification of modifiable risk factors that may impact chronic disease risk is critical to public health. Our study objective was to conduct a theoretical population attributable risk analysis to estimate the burden of disease from low dairy intake and to estimate the impact of increased dairy intake on United States (US)-based disability adjusted life years (DALYs).We conducted a comprehensive literature review to identify statistically significant summary relative risk estimates (SRREs) from recent meta-analyses of dairy consumption and key chronic disease outcomes. The SRREs were applied to preventive fractions using a range of categories (low to high) for population consumption of dairy products. The preventive fraction estimates were then applied to the number of DALYs for each health outcome in the US based on 2019 WHO estimates. The population attributable risk proportion estimates were calculated using the inverse of the SRRE from each meta-analysis using the same range of categories of consumption. These values were subsequently applied to the DALYs estimates to estimate the theoretical burden of disease attributable to low dairy intake.Statistically significant SRREs were identified in recent meta-analyses of total dairy consumption in relation to breast cancer, colorectal cancer, cardiovascular disease (CVD), type 2 diabetes (T2D), stroke, and hypertension. In this theoretical analysis, nearly 850,000 DALYs  due to CVD and 200,000 DALYs (4.5%) due to T2D may be prevented by increased dairy consumption. Approximately 100,000 DALYs due to breast cancer (7.5%) and approximately 120,000 DALYs (8.5%) due to colorectal cancer may be prevented by high dairy intake. The numbers of DALYs for stroke and hypertension that may be prevented by increased dairy consumption were approximately 210,000 (6.0%) and 74,000 (5.5%), respectively.Consumption of dairy products has been associated with decreased risk of multiple chronic diseases of significant public health importance. The burden of disease that may potentially be prevented by increasing dairy consumption is substantial, and population-wide improvement in meeting recommended daily dairy intake goals could have a notable public health impact. However, this analysis is theoretical, and thus additional studies providing empirical evidence are needed to further clarify potential relationships between dairy intake and various health outcomes.The online version contains supplementary material available at 10.1186/s12889-022-14042-7. With the rising burden of chronic disease on a global scale, the identification of modifiable factors that may impact disease risk is paramount. Several behaviors, such as cigarette smoking, low physical activity, and excess body weight, have been identified as important risk factors for multiple chronic diseases –4. Altho2D3, has been shown to target cellular processes such as apoptosis, cellular adhesion, and cell cycle progression in several lines of cancer cells [Dairy products provide an important source of key nutrients, including whey proteins, casein proteins, calcium, and essential vitamins and minerals. Calcium and magnesium found in dairy products are crucial factors in insulin response and glucose tolerance, and whey proteins can affect glycemic control. Milk proteins have been shown to decrease ghrelin levels and improve satiety and appetite control and prevent weight gain . The viter cells .Despite these findings, some controversy remains regarding the association between dairy products and chronic disease, mainly due to the presence of saturated fatty acids in milk fat. Evidence from experimental studies indicates that consumption of saturated fats increases the amount of plasma total cholesterol, LDL cholesterol, and apolipoprotein B levels, which have been associated with increased risk of heart disease , 16, butThe United States Department of Agriculture (USDA) Dietary Guidelines for Americans 2020 recommends an equivalency of 3 cups of dairy per day for adults . HoweverGiven the beneficial role of dairy intake on chronic disease risk and the fact that most Americans are not meeting recommended intake levels, our objective was to construct theoretical attributable risk models to estimate the potential impact that dairy consumption modification could have on chronic disease in the general US population, using burden of disease data from the World Health Organization (WHO).Global Health Risks: Mortality and Burden of Disease Attributable to Selected Major Risks [Under the health statistics and information systems program of the WHO , the buror Risks  describior Risks  and the or Risks  that repor Risks . One DALor Risks , indicatTherefore, using the concept of attributable risk and burden of disease on a public health scale, we conducted theoretical preventive fraction and population attributable risk analyses of total dairy intake and selected health and disease outcomes. Data from these analyses were applied to US WHO DALYs figures to estimate the impact on burden of disease.In 2012, Doidge et al.  publisheWe implemented a two-phase literature search and study inclusion protocol. In the first phase, we conducted a series of comprehensive literature searches in May 2021 to identify studies that reported risk estimates (regardless of direction of effect) for dairy intake and chronic disease outcomes  , total milk, and low-fat or high-fat dairy products from the articles identified in the first phase. Analyses of other specific dairy products  were not included as the data were more limited and variable across studies. Our objective was to calculate preventive fraction and population attributable risk percentages; the informativeness of such estimates is based upon established or causal relationships. We did not conduct systematic causation analyses nor are we specifically implying that causal relationships exist. Rather, the purpose of this assessment is to provide a theoretical framework for population-based attributable risk analyses for a dietary intake variable  that has been consistently associated with decreased chronic disease risk across numerous analytical epidemiologic investigations. Thus, as a conservative approach, we selected only topic areas for which statistically significant meta-analysis findings between dairy intake and chronic disease were reported. In addition, studies with reported statistically significant summary associations for total milk intake were included in our assessment. No meta-analyses were identified that observed consistently statistically significant increased risks of disease based on dairy consumption.From each meta-analysis, we extracted summary relative risks for the highest vs. lowest intake strata of total dairy or total milk consumption and the outcomes of interest. These risk estimates were then used to calculate preventive fractions and population-attributable risk proportions (PARPs).Pr (1 – RR), where Pr = prevalence of exposure and RR = relative risk for disease associated with exposure. In nutritional epidemiology studies, intake categories often vary considerably between studies, and distinctions made between intake strata may be arbitrary and may not represent thresholds in either the distribution of consumption or the relationship to disease risk [Pr of 15%, 25%, 35%, and 50%) to represent the proportion of the general population who consume high levels of dairy. Importantly, the designation of ‘high’ dairy is based on the highest intake strata across the studies and does not differ appreciably from the USDA recommended daily intake levels for dairy. The highest intake categories across the nutritional epidemiology studies typically range between three and four servings per day. Therefore, our estimates are based on “high” categories of dairy intake in the epidemiology studies which are also in line with USDA recommendations. As the current proportion of Americans that meet the USDA recommendations for dairy intake is approximately 11.65% [For exposures that decrease disease risk, a preventive fraction (or proportion) can be calculated to estimate the proportion of disease in the population that may be prevented if the population was exposed or achieved a certain level of exposure to a factor . The forase risk . Therefoy 11.65% , the preFor exposures that increase disease risk, a PARP can be calculated to estimate the proportion of disease that may be attributed to the exposure. Since all summary estimates for dairy were in the inverse direction , we used the inverse of the summary RRs from the selected meta-analyses to estimate disease risk based on low dairy consumption (vs. the high intake strata) and the proportion of disease therefore attributable to low dairy intake. The same four prevalence proportions were used to represent dairy intake levels in the general population. The following formula was used to calculate the PARP estimates:Pr = prevalence of exposure andwhere RR1 = the inverse of the meta-analysis summary risk estimates.The preventive fraction and PARP estimates for each dairy-outcome were applied to WHO global burden of disease data. Specifically, the disability-adjusted life year (DALY) estimates for the United States by cause were selected from the WHO Global Health Estimate Database for 2019 . In its c, age a, sex and year t.c, age a, sex s and year t is the following:The formula for years of life lost (YLL) for a given cause N is the number of deaths due to the cause c for the given age a and sex s in year t,where L is a standard loss function specifying years of life lost for a death at age a for sex s using highest projected life expectancies for 2050.The formula for years lived with disability (YLD) is adjusted for comorbidity and calculated using the following formula:I is the number of incident cases for cause c, age a and sex s,where DW is the disability weight for cause c, age a and sex s on a scale from 0  to 1 (dead) and,L is the average duration of the case until remission or death.To estimate the number of DALYs in the US theoretically prevented by high consumption of total dairy or milk, we multiplied the preventive fractions for each outcome and prevalence exposure by the US 2019 DALY estimate for that specific factor provided by the WHO. To estimate the number of DALYs in the US attributable to low consumption of total dairy or milk, we multiplied the PARP estimates for each outcome and prevalence exposure by the US 2019 DALY estimate for that specific factor.Our review of the literature yielded six chronic diseases with at least one published meta-analysis demonstrating a significant association with total dairy consumption: breast cancer , colorecPr 15%, T2D) and 8.5%  of DALYs due to these chronic diseases may be attributable to low population total dairy consumption.The results of the analyses of preventive fraction estimates and population attributable risk proportion estimates for the range of total dairy prevalence exposures are presented in Table The numbers of DALYs that could potentially be prevented by higher population consumption of total dairy and attributable to low population consumption of total dairy are presented in Table Two of the identified meta-analyses provided a statistically significant summary relative risk estimate for total milk consumption and risk of chronic disease  the outcome of interest. As indicated earlier, we did not perform a systematic causal assessment pertaining to dairy consumption and the selected outcomes. Rather, we assumed that increased dairy intake was associated with decreased risk of the selected outcomes based on the reported findings across the published meta-analyses which were peer reviewed publications derived from publicly funded research. Second, the meta-analyses used as the basis for this analysis quantitatively summarize data from observational studies. Thus, the prevailing methodological considerations  when interpreting findings from nutritional epidemiology studies are relevant. A related limitation is that this analysis utilized DALYs for the US but the summary estimates from meta-analyses were based on multiple observational studies, some of which were conducted outside the US. Finally, our methodology does not take into account other risk factors for the outcomes of interest or interactions between such risk factors, and thus our results may be over-stated if the individual population attributable risks for all risk factors exceeds 100%. With these assumptions and limitations noted, our analyses were conducted to provide a methodological and analytical framework to estimate the theoretical impact of low or high dairy consumption on the burden of selected diseases in the general US population. We chose to use dairy consumption in this analysis because it is a modifiable behavior, a high proportion of the general population consumes dairy products, and there is a robust volume of published prospective cohort studies and meta-analyses of dairy consumption and chronic disease outcomes.Our analysis was based on an exposure that has been associated with decreased risks of several chronic disease outcomes of public health interest. Furthermore, our reliance upon statistically significant findings from comprehensive meta-analyses is a conservative approach in that we only examined outcomes with consistent associations in numerous analytical epidemiologic investigations. This selection of outcomes with robust and consistent findings, despite presence of heterogeneity in some studies, adds confidence to the interpretation of patterns of results observed in our analyses. The range of prevalence exposure estimates are based on categories of dairy intake as defined by the epidemiology studies in the meta-analyses, which generally coincide with USDA dairy recommendations. Thus, the DALYs estimates based on our analyses may be considered conservative and do not represent the most extreme values of dairy intake in the population.The concept of this analysis was based upon a publication by Doidge et al. , who conThough multiple meta-analyses were identified evaluating the association between dairy consumption and prostate cancer, we elected not to perform analyses for this outcome due to a lack of consistent and significant results observed in the epidemiologic literature. A meta-analysis published by Aune et al. presented an SSRE for total dairy and total prostate cancer of 1.07 (95% CI: 1.02–1.12) . HuncharA large volume of epidemiologic studies and reviews have been published evaluating the relationship between dairy consumption and breast cancer, colorectal cancer, CVD, and T2D. Several risk factors, protective factors and mechanisms have been postulated for the relationship between dairy consumption and the aforementioned health outcomes. Components of dairy products including calcium, vitamin D, and conjugated linoleic acid have been proposed to reduce breast cancer risk due to anti-carcinogenic properties , 50–53. This analysis represents a theoretical model to estimate the impact on disease burden of a widely prevalent modifiable dietary factor. Specifically, we observed that higher dairy consumption in the US population may have a pronounced impact on reducing the number of DALYs due to breast cancer, colorectal cancer, CVD, T2D, stroke, and hypertension, and that a substantial proportion of these diseases may be attributable to low population consumption of dairy. However, these findings are based on an analytical framework of theoretical modelling and are dependent upon the reported statistical associations across published observational studies. As such, the results from our analyses are not intended to imply a causal relationship between low dairy intake and increased risk of certain chronic disease outcomes. Rather, our analyses emphasize the importance of meeting dietary guidelines as they provide a population-based extension of the findings from meta-analyses of prospective studies that indicate decreased risk of several chronic diseases of public health importance in relation to increased dairy consumption.Additional file 1:Supplementary Table 1. Search strings utilized to identify meta-analyses for dairy and health outcomes.Additional file 2:Supplementary Table 2. Considered meta-analyses for the six chronic disease outcomes.


There are 150 million women worldwide using combined or progestogen-only hormonal contraceptive methods who may be at risk of sexually transmitted infections (STIs). Previous systematic reviews that have sought to establish whether there is an aetiological association between hormonal contraceptive methods/use and STIs have been limited in their methods and have mixed findings. We sought to update these reviews using appropriate control groups. We undertook a systematic review following the PRISMA guidelines and meta-analysis to examine the association between the use of all hormonal contraceptive methods and the acquisition of STIs  and/or bacterial vaginosis in literature published between 2005 and 2020. We analysed the effect of hormonal contraceptive methods/use separately on the prevalence, incidence and recurrence of STIs. A total of 37 studies were included in this review that reported 61 associations, in which 27 prevalence, eight incidence and two recurrence studies provided 43, 16, and two associations, respectively. We observed a positive association between hormonal contraceptive methods/use and the risk of chlamydia and herpes but a negative association for trichomoniasis and vaginosis. A negative but statistically insignificant association was observed between hormonal contraceptive methods/use and gonorrhoea. Hormonal contraceptive methods/use influences a woman's risk of STIs/ bacterial vaginosis, but the risk may differ depending on the type of STI. These findings should be contextualized carefully, particularly when formulating practice guidelines and policy, as the effects of hormonal contraceptive methods/use on the risk of STIs varied in direction when analysed separately by STI. Specifically, there are approximately 131 million cases of chlamydia trachomatis (CT), 78 million cases of Neisseria gonorrhoeae (NG), 143 million cases of trichomonas vaginalis (TV) and 5.6 million cases of syphilis/Treponema pallidum (ST)1. The prevalence of viral STIs is also high. Approximately 500 million cases of herpes simplex virus (HSV) are recorded each year and there are 290 million cases of women with human papillomavirus (HPV)1. The high incidence of STIs has an adverse effect on sexual and reproductive health. STIs may significantly increase the risk of human immunodeficiency virus (HIV) acquisition, cause cervical cancer and lead to pelvic inflammatory disease (PID), infertility, ectopic pregnancy, miscarriage, fetal death, stillbirth, neonatal death, and congenital infections1.Globally the acquisition of new sexually transmitted infections (STIs) is very high—around 357 million per year2. HC that includes combined oestrogen-progesterone contraception , progestin-only injectables (e.g. depo-medroxyprogesterone acetate), and hormone-containing technologies  reduce unwanted pregnancy and maternal morbidity and mortality. However, previous systematic reviews have reported that HC may increase the risk of HIV acquisition, CT and HSV type 27. In contrast, some reviews have found an inconclusive effect of HC on the incidence of NG and TV, while other reviews have observed that HC can reduce the risk of TV and bacterial vaginosis (BV)10.Hormonal contraceptives (HC) are used worldwide by more than 150 million women and therefore, an investigation into whether there is an aetiological association between STIs and HC is an important question for public health6 and Morrison et al.7 include studies up to 2008. On the other hand, reviews by Vodstrcil et al.9 and Van de Wijgert et al.8 were limited to specific STIs and/or considered control groups that also included users of HC. Furthermore, reviews by McCarthy et al.5, Deese et al.10, Van de Wijgert et al.8, Mohllajee et al.6 and Morrison et al.7 did not include a meta-analysis. A clear understanding of the association between hormonal contraceptive use (HC-use) and the risk of STIs requires a meta-analysis to draw accurate conclusions based on studies that used appropriate control groups.Previous reviews examining the association between HC and the risk of STIs are outdated and/or did not include a meta-analysis of data, or used comparisons of groups that included HC users. For example, reviews by Mohllajee et al.12. Specifically, such a study may also contribute to ending the preventable deaths of newborns and children under five years (SDG3 target 2), combating the epidemics of AIDS and other communicable diseases (SDG3 target 3) and ensuring universal access to sexual and reproductive health care (SDG3 target 7)12. Therefore, this systematic review and meta-analysis aimed to examine the association between the use of HC and the acquisition of STIs based on the literature published between 2005 and 2020.An updated review of the association of HC-use with the risk of STIs may help to provide insights to improve infection control and consequently achieve the health-related targets of the Sustainable Development Goal 3 (SDG3)13 and is registered with PROSPERO, CRD42021272742.The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was used to conduct this systematic review and meta-analysis14, was formed to lead this review. Thus, this review considered women of reproductive age (15–49 years) as participants. Specifically, we focused on studies involving HC-use by women of reproductive age and tested for prevalence (a measure of a condition in a population at a given point/period), incidence (number of new occurrences of a condition in a population over a period), or recurrence (return of a condition after a remission) of STIs using standard diagnostic methods. This review considered all HC methods as interventions/exposures and included combined oestrogen-progesterone contraception , progesterone-only contraception , as well as the use of unspecified HC. The comparator/control group was the non-users of HC . The outcome of interest was the following STIs: Neisserria gonorrhoeae, Syphilis/Treponema pallidum, Chlamydia Trachomatis, Herpes Simplex Virus, and Trichomonas Vaginalis. We also considered Bacterial Vaginosis and Pelvic Inflammatory Disease as our outcome of interest. HIV and HPV were not included as there is already an updated review in relation to HIV15 and HPV is beyond the scope of our study. Randomised trials , observational and descriptive studies were eligible for inclusion in this review.A Population, Interventions, Comparators, Outcomes, Study design (PICOS) question, as suggested in the Centre for Reviews and Dissemination (CRD) CRD9 we excluded studies reporting either less than 20 STIs cases or less than 10% of participants exposed to HC.This investigation excluded review articles, and studies that did not use standard methods to diagnose STIs, had no comparison groups and did not investigate the association of hormonal contraception with STIs. Following Vodstrcil et al.17. The Medline MeSH subject headings employed in this review were: hormonal contraceptive OR contraceptive OR contraception OR Combined oral Contraceptive OR Oral Contraceptive OR oestrogen OR Progesterone-releasing vaginal ring OR Progering OR progesterone OR progestin OR Intrauterine device OR depot medroxyprogesterone acetate OR DMPA OR Emergency contraceptive OR Levonorgestrel AND Sexually Transmitted Diseases OR Sexually Transmitted Infection OR STI OR Gonorrhoea OR Chlamydia Trachomatis OR Herpesvirus 1, Human OR Herpesvirus 2, Human OR Trichomonas Vaginitis OR Trichomonas Vaginalis OR Bacterial Vaginosis OR Bacterial Vaginitis OR Pelvic Inflammatory Disease OR Syphilis.We focused on studies on HC and STIs and searched PubMed and EMBASE databases for relevant peer-reviewed articles published between 2005 and 2020 and written in English. Following the other reviews, we selected a 15-year period to ensure an analysis of the most contemporary researchWe initially retrieved 1,405 articles and screened these articles as per the PICOS question ; analysis country; study design; sample size; the participants' characteristics; outcomes (the type of STIs/BV/PID); STI/BV/PID outcome measure ; the number of participants with STIs; the diagnostic method employed; the exposures ; the comparison group ; the type of statistical analysis performed; the control variables used in the adjusted analysis ; the size of the estimate, and the significance level.20. The risks of bias in studies were assessed regarding the selection of participants, study design, confounders and analyses. Other potential risks of bias included whether the study had reported a standard method of STIs assessment and clearly defined the HC-use.Following the previous literature, existing quality assessment tools—MOOSE, STROBE and QATSO—were used to evaluate the quality of the selected studies before the initiation of data synthesis2 test for heterogeneity as described in Vodstrcil et al.9. A meta-analysis based on a fixed-effect model was conducted if the I2 statistic was < 25% and used a random-effect model if the I2 statistic was between 25 and 75%, otherwise, the studies were not analysed. We preferred adjusted over unadjusted results, in case both were available for any study, as the former netted out the effect of confounders.The primary objective of this study was to examine the association between HC-use and STIs/BV/PID. We directly copied both the estimates and the 95% confidence intervals from the selected studies. In the case of their unavailability, we calculated those numbers using raw data from those studies. Then, we undertook a meta-analysis using either fixed or random effects models depending on the I9, we attempted to convert the odds ratios (ORs) to risk ratios (RRs) in studies where data was available. Then, we analysed the effect of HC-use separately on prevalence, incidence and recurrence of STIs. All of these analyses were stratified by types of STIs/BV/PID, as described earlier.The analysis initially investigated the effect of HC-use on composite STIs outcome measures . In that analysis, following Vodstrcil et al.Stata version 15 was used for all the analyses.9, we conducted several sensitivity checks where we excluded some specific sub-groups to check the robustness of our results. The large sample size allowed us to conduct the analysis by omitting studies in which all women were sex workers or studies including HIV-positive participants since these groups are more vulnerable to develop/spread STIs; or studies in which comparison group contained women not using any contraception; or studies in which women were selected based on RCT design.Following the previous research9. Asymmetry was statistically evaluated using the Egger's correlation tests by regressing the log of the estimate (unadjusted/adjusted OR or RR) on the log of the standard error (SE) of the estimate. The SEs were estimated based on the width of the reported confidence interval using the formula (ln[upper limit of CI]-ln[OR or RR])/1.96.We used funnel plots to assess the potential presence of publication bias in studies reporting the prevalence and incidence of STIs, as suggested in Vodstrcil et al.All 37 studies in this review are summarized in Table We observed that the majority of the studies under this review adequately discussed the selection criteria of participants and clearly described the study design. In terms of the study recruitment venue, 24 studies were conducted at sexual or reproductive health service setting, three at general community healthcare service setting and six at sex worker service setting, while four were population-based Table . The inc26  and UHC , respectively.Six studies evaluated the association between HC-use and the risk of incidence or prevalence of NG26 Table . Among tThe overall estimates of meta-analysis demonstrated that HC-use did not significantly reduce the risk of NG in comparison with no HC-use or no contraceptive use  with the heterogeneity between the studies were 59% Fig. . We then29  with the heterogeneity between the studies were 57% Fig. . In the 26  Fig. . Interes35 was the only study that evaluated the association between POC use and PID and found a reduced risk of association   Table .37. Two studies observed that POC users were around two times more likely to develop the risk of HSV237, and the third one observed that the risk of developing HSV2 was 70% for UHC users36.Three studies examined the association between HC-use and HSV2 Table  and a siThe overall estimate from the meta-analysis also showed a significant increase in the risk of HSV2 due to the use of HC  with the heterogeneity of 44%  with the heterogeneity between the studies were 33% Fig. . The strSeveral sensitivity analyses were carried out to check the influence of certain studies and populations on the overall estimates . Users of oral contraceptives, a popular HC, often suffer from cervical ectopy, which may enhance susceptibility to CT23. The significant association we found between HC use and CT prevalence but not between HC use and CT incidence may be the result of a small sample size. However, this could also be linked to challenges relating to treating chlamydia infections, as some antibiotic resistant strains may prolong treatment and thus lead to an increase in the prevalence.The estimates of our meta-analysis indicated that HC-users experienced a significantly increased risk of CT compared to the control group. Two previous reviews59 were found to have a significantly lower risk of chlamydia compared with the levonorgestrel implant and copper IUD groups. This may be partially explained by research that demonstrates that the initiation of the copper IUD is associated with an increased prevalence of BV and BV is associated with increased rates of CT and NG60. Our finding showing that HC-use can significantly increase the risk of CT alongside a significantly reduced risk of BV compared to the control group is not consistent with this research58. There may be two explanations for the relationship between DMPA and risk of BV. The prolonged effect of the hormones in DMPA and the absence of a cyclical change in hormonal levels may affect the milieu of the vaginal epithelium, which would make it less favourable for BV to thrive. The other explanation may be due to the constant pH due to the contraceptive effect, which may make it more favourable for less BV.However, in contrast to our findings, DMPA users in a study by Deese et al.61. Research has examined the relationship between DMPA and Norethisterone enanthate use and the impact of immune cell responsiveness to identify whether using these POC may increase susceptibility to infections. However, in a study by Matubu et al.62 the exposure of CD4 + and CD8 + T cells to typical pharmacologic concentrations of DMPA was not found to cause immunosuppressive effects. Despite this, the depletion of cytokine-producing T cells may occur after prolonged DMPA use. Length of use may therefore be a factor in exposure to STI risk and could also contribute to the significantly increased risk of CT compared to the control group we identified in our meta-analysis.Several studies have investigated the effects of HC use on immune responses in the female genital tract5, specifically DMPA and OCP. Mohllajee et al.6 and Morrison et al.7 could not conclude about the effect of HC-use on TV. As mentioned earlier, both of those studies were dated and their selection criteria were different from ours. A potential reason for this association is that TV requires both oestrogen and androgen receptors. The progesterone receptor is highly expressed in DMPA users or that high MPA concentrations in DMPA users may prevent TV binding to the androgen receptor by competing for receptor binding63.The reduction in the risk of TV associated with HC-use, observed in our study, was also evident in McCarthy et al.5 and Deese et al.10 also documented a similar association in their review in relation to DMPA use. It is worth mentioning that the control group selection criteria were different in the latter study. A possible biological mechanism was investigated in a recent study on mice64. The study demonstrated that DMPA and levonorgestrel, another type of progestin, increase mucosal epithelial permeability by acting on epithelial cell junction proteins, enhancing access to inflammatory and infectious viral molecules to the genital tissue64.We observed a significant increase in the risk of HSV2 due to the use of HC in the meta-analysis, although the estimation was based on a small number of studies. McCarthy et al.9 and Van de Widjert et al.8. Examining the association of HC-use in our analysis, separately for the prevalence and the incidence of BV, also showed a negative association. These findings were also consistent with a previous review, Vodstrcil et al.9. Menses destabilize the vaginal flora resulting in high concentrations of non-lactobacillus species that favour BV. HC users can experience reduced menses due to use of progestin, reducing BV rates65. For oestrogen-containing contraceptive users, there is another plausible explanation for experiencing a reduced risk of BV. Such contraceptives increase the glycogen-content of epithelial cells that is metabolised to lactic acid, a suspected primary vaginal acidifier and a known inhibitor of BV67.Our review concluded that HC-use can significantly reduce the risk of BV that was similar to two previous systematic reviews, Vodstrcil et al.7. However a study by Deese et al. found lower prevalence rates of NG in DMPA users compared with copper intrauterine device59. Progesterone-based HC may induce thickening of cervical mucus, limiting STD acquisition, including NG23. The reduced incidence of NG can also be due to the reduction in menstrual blood flow for combined HC-users. This is because HC regulation may result in a lighter menstrual flow, which by reducing iron sources, can inhibit the growth of NG since Gonococcal growth is augmented in iron-rich menstrual blood69.Our study observed that HC-use did not significantly reduce the risk of NG. Many other reviews also documented an inconclusive association on the acquisition of NG with HC-use59.This study has some potential limitations. Firstly, a smaller number of studies did not allow a meta-analysis to be conducted that was stratified by the type of HC. Such analyses are important to better understand the differential effects of COCs and POCs in developing STIs and are more useful for planning public health policies and programmes. Despite this, differences have been found between the effects of types of HCs and STIs in research as noted above for DMPA and CT, TV and NG9, we included studies in which women self-reported HC use was selected. As noted by Pyra et al.70, a significant proportion of women self-reporting HC use often had no hormones detected. Though, the sensitivity analysis did not observe any impact on the findings of this research due to the removal of those studies; consequently, it may not be an issue for our research. Finally, we did not perform the adjusted analyses despite the presence of several confounding factors in the current study . However, the use of adjusted estimates of the selected studies in the meta-analyses reduces the chance of confounding effect on the estimates.A limited number of studies also did not allow us to draw a conclusion concerning ST and PID. Secondly, selected studies may suffer from a publication bias because most published studies only report significant results. However, this may not be an issue in our case, as we observed a very low level of publication bias indicated by funnel plots and Egger’s bias tests. Thirdly, the majority of the selected studies in this review provided a prevalence estimate that may indicate only an association between HC and STIs/BV. However, identifying causal effects is more useful for health care decision-making. Fourthly, the control groups were not the same in all studies. Again, this may not be an issue in our case, as sensitivity analyses indicated the robustness of our results. Fifthly, following the previous reviewThis systematic review and meta-analysis provide evidence that HC-use influences a woman's risk of STIs/BV, but the risk may differ depending on the type of STIs. We observed a positive association between HC-use and the risk of CT and HSV2 but a negative association for TV and BV. A negative but statistically insignificant association was observed between HC-use and NG. The differences in HC-use and the risk profiles of various types of STIs has clinical implications. Counselling and care for both contraception and infectious disease protection must be provided to all sexually active individuals.We conclude that there is a need for more studies to investigate the association between different categories of HC and types of STIs. Research is needed to address the lack of knowledge concerning the exact mechanisms of CT, NG and BV infections and HC in the presence of different types of HC, biological and behavioural factors, length of HC use and clinical testing and care. This will reveal further evidence of the complex factors that render individuals more susceptible to STIs according to HC type. Longitudinal cross-sectional or population-based case–control studies are required to estimate causal effects to ensure robust clinical practice and policy formulation. However, rigorously designed studies are needed to enable confounders to be adequately addressed and accounted for. Clinically significant meta-analyses need to be performed to inform guidelines that demonstrate the effect different contraceptives have different effects on STI acquisition. Future research should examine different types of STIs in diverse settings and populations, as a large proportion of previous studies have focused on sex workers and the acquisition of HIV in African contexts.Supplementary Figure 1.Supplementary Figure 2.Supplementary Information 1.


P < 0.001), total cholesterol , low-density lipoprotein WMD = −9.63 mg/dl; 95%CI, −13.87, −5.39; P < 0.001), fasting blood glucose (FBG) , insulin , HbA1c , HOMA-IR , systolic blood pressure , weight , body mass index , while increased high-density lipoprotein (HDL) . The optimal dose of BBR was 1 g/day for TG, TC, and weight, 1.8 g/day for insulin and HOMA-IR, and 5 g/day for HDL. FBG's most efficient time frame was 40 weeks from the beginning of supplementation, whereas DBP and waist circumference was 50 weeks. In conclusion, the lipid profile, FBG balance, obesity parameters, and SBP were improved with BBR supplementation.Cardiovascular disease (CVD) is a major concern today. Herbal medicine is one helping way to control CVD risks. One conclusive of herbal medicine is Berberine (BBR) and converse about it still exists, to clarify this issue, this meta-analysis was performed. PubMed/Medline, Scopus, and Web of Science were searched for RCTs in adults on the effect of BBR supplementation on CVD risk factors up to July 2022. The pooled results showed BBR significantly reduced triglyceride (WMD = −23.70 mg/dl; 95%CI −30.16, −17.25; CRD42022347004. Cardiovascular disease (CVD), a general term for heart and blood vessel disorders, is still the first-ranked cause of death despite recent advances in its management . World Hin vitro) studies demonstrate that BBR has positive effects on lowering blood lipids, blood glucose, and controlling weight and blood pressure , a plant alkaloid with known pharmacological properties extracted from Chinese traditional herbs , has beepressure , 11. Prepressure –16. In apressure , 17, 18.pressure , 17, shopressure , 14, 19,pressure , 14.Therefore, because the existing literature still lacks an appropriate comprehensive answer to whether BBR is effective on CVD risk factors or not, with finding the optimal dose and duration, we aimed to perform a novel comprehensive dose-response meta-analysis on the effect of BBR on all CVD risk factors in adults.The current study was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) . The proWe conducted a systematic literature search in the following databases without any time, length of study, or language restrictions: PubMed/Medline, Scopus, Web of Science, EMBASE, the Cochrane databases, and Google Scholar . The framework that we used for our search was the PICO  strategy, which is recommended by Cochrane: (1) participants; (2) intervention group (which was treated by BBR); (3) comparison/Control group (non-BBR supplementation), and (4) outcome . The full search strategy and the terms used to search in each database could be found in detail in in-vitro studies; (2) studies on children and adolescents; (3) grey literature, reviews, conference abstracts, editorials, and books; (4) RCTs that did not have control/placebo groups.To include clinical studies, we considered the following criteria: (1) Only randomized clinical trials . (2) The intervention duration ≥1 week; (3) Studies with adult human subjects (≥18 years); (5) Studies that reported mean ± standard deviation (SD) or other effect sizes from which the calculation of mean and SD was possible; (6) Studies that examined the effect of BBR supplementation on triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL), fasting blood glucose, hemoglobin A1c (HbA1c), serum insulin, homeostasis model assessment-insulin resistance (HOMA-IR), systolic blood pressure (SBP), diastolic blood pressure (DBP), C-reactive protein (CRP), interleukin-6, (IL-6), weight, waist circumference (WC), body mass index (BMI), aspartate transaminase (AST) and alanine transaminase (ALT). The exclusion criteria were as follows: (1) studies on animal subjects and MZ and OA independently screened the titles and abstracts of studies and discussed them with each other in case of any disagreement. Then, after re-assessment, MZ and OA extracted the following information from the included studies: first author's name, year of publication, country, type of clinical trial, participant characteristics , duration of intervention, randomization, blinding, adverse effects sample size, the number of participants in the intervention and control groups, form and dosage of supplemented BBR, the health status of participants , and outcome values. To solve any inconsistency in dosage, all of the BBR supplementation doses were converted to g/day.Table 2). Then, three groups of high , moderate , and low  risk of bias were defined. Two reviewers (MZ and OA) independently assessed the quality of the work, and any conflicting opinions were settled by discussion.Included studies were screened for any source of bias, including random sequence generation, allocation concealment, participant and staff blindness, outcome assessor blinding, incomplete outcome data, selective reporting, and other biases using the Cochrane Collaboration tool  (Table 2Table 4)  approach was used to assess and summarize the certainty of evidence among the included studies, as described previously (Table 4) .P-values < 0.05 considered statistically significant. The pooled weighted mean difference (WMD) was calculated using a random-effects model (2+ (SD at the end of study)2 –(2 r × SD at baseline × SD at the end of study)] ] formula to calculate SD (2) statistic (P = 0.05 and I2 > 40%) (2), overweight (25–29.9 kg/m2) and obese (>30 kg/m2)], and category of risk of bias in studies . Studies examining the impact of BBR supplementation on CVD risk variables used the Begg's and Eager tests according to the number of studies for every outcome and the funnel plot test to evaluate publication bias . All tests were two-tailed with ts model . Mean di study)] . In eachulate SD . A correulate SD . After vulate SD , heterog2 > 40%) . Subgrou2 > 40%) , 30. Subion bias , 32. Usiion bias . The posion bias , 35.n = 2,153), ISI Web of Science (n = 867), and Scopus . A total of 1,266 duplicated studies were excluded, and 3,418 studies were screened based on title and abstract. After screening, 3,348 irrelevant studies were excluded, and 70 full-text studies were considered. In the end, 21 studies were excluded due to reporting non-desired outcomes. As a result, 49 studies were included in the systematic and meta-analysis review (The selection process of the included studies is presented in s review –84.2), WC (cm), ALT (U/L), AST (U/L), and their changes are presented in n = 22) (n = 19) (n = 2) (n = 2) (n = 2) (n = 1) (n = 1) , ALT n = 1 084 , AST n = 880 , body weight n = 1,706 , BMI n = 1,990 , WC n = 1,083 , FBG n = 2,713 , insulin n = 1,138 , HbA1c n = 1,566 , HOMA-IR n = 1,119 , CRP n = 662 , IL-6, n = 358 , TG n = 3,004 , TC n = 2,804 , LDL n = 2,824 , HDL n = 2,784 .The characteristics of included studies are presented in  n = 22) , 71–80, (n = 19) –83, 85,  (n = 2) , 84, Mex (n = 2) , 62, Ind (n = 2) , 66, USA (n = 1) , and Pak (n = 1) . The stu (n = 1) –83 and o females , 60, 72  females  and the  females –78, 83,  females , 79, 80, females , metabol females , 82, pol females , 60, 72, females , non-alc females , 74, 75, females , women w females , rheumat females , 51, sch females , hyperte females , and hea females , 84. SamThe adverse effect was reported in studies including Asemani et al. , Sharma Based on the Cochrane Risk of Bias Assessment tool, a total of 38 studies were considered with a high risk of bias , 82, 83,P < 0.001). The subgroup analysis showed that the effect of BBR on TG was significant in studies conducted on the baseline TG < 150 mg/dl  and ≥150 mg/dl , trial duration ≤ 8 weeks  and trial duration >8 weeks , intervention dose ≤ 1 g/d  and >1 g/d , overweight (25–29.9 kg/m2)  and obese (>30 kg/m2) , type 2 diabetes , metabolic syndrome , non-alcoholic fatty liver diseases , and category of trails risk of bias, high risk of bias , moderate risk of bias  (2 = 96.6%). The heterogeneity disappeared when subgroup analysis was performed on baseline TG (<150) , and dyslipidemia , low risk of bias   . Between= 0.668) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on TC was significant in studies conducted on the baseline TC < 200 mg/dl , ≥200 mg/dl , trial duration ≤ 8 weeks  and >8 weeks , intervention dose ≤ 1 g/d  and > 1 g/d , overweight (25–29.9 kg/m2) , obese (>30 kg/m2) , dyslipidemia , type 2 diabetes , metabolic syndrome , non-alcoholic fatty liver diseases , other health status , and category of risk of bias of trails, high risk of bias , moderate risk of bias  (2 = 85.4%). The heterogeneity diminished when subgroup analysis was conducted on health status (metabolic syndrome)   . Between= 0.807) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on LDL was significant in studies conducted on the baseline LDL ≥ 100 mg/dl , trial duration ≤ 8 weeks , trial duration > 8 weeks , intervention dose ≤ 1 g/d , and >1 g/d , overweight (25–29.9 kg/m2) , dyslipidemia , metabolic syndrome , non-alcoholic fatty liver disease , other health status , and category of risk of bias of trails, high risk of bias , moderate risk of bias , low risk of bias trials  (2 = 96.1%). The heterogeneity disappeared when subgroup analysis was conducted on baseline LDL (< 100) , health status including dyslipidemia , metabolic syndrome , and non-alcoholic fatty liver disease  and low risk of bias trials   . Between= 0.187) .P = 0.005). The subgroup analysis showed that the effect of BBR supplementation on HDL was significant in studies conducted on the baseline HDL < 40 mg/dl , trial duration ≤ 8 weeks , intervention dose >1 g/d , obese (>30 kg/m2) , type 2 diabetes , and metabolic syndrome , and category of risk of bias of trails, high risk of bias , low risk of bias trials  (2 = 92.7%). The heterogeneity diminished when subgroup analysis was performed on health status including dyslipidemia , metabolic syndrome , and non-alcoholic fatty liver disease   . Between= 0.988) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on FBG was significant in studies conducted baseline FBG ≥ 100 mg/dl , trial duration >8 weeks , intervention dose ≤ 1 g/d  and >1 g/d , normal (18.5–24.9 kg/m2) , overweight (25–29.9 kg/m2) , type 2 diabetes , and non-alcoholic fatty liver diseases , and category of risk of bias of trails, high risk of bias , moderate risk of bias  (2 = 97.0%). The heterogeneity diminished when the subgroup analysis was performed on BMI categories including normal BMI , and obesity   . Between= 0.322) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on insulin was significant in studies conducted with trial duration ≤ 8 weeks  and >8 weeks , intervention dose ≤ 1 g/d  and >1 g/d , overweight (25–29.9 kg/m2) , obese (>30 kg/m2) , type 2 diabetes , and others , and category of risk of bias of trails, high risk of bias , moderate risk of bias . Between study heterogeneity was found for insulin (I2 = 95.3%). The heterogeneity diminished when the subgroup analysis was performed on the risk of bias, moderate risk of bias   .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on HbA1c was significant in studies conducted trial duration > 8 weeks , intervention dose >1 g/d , normal (18.5–24.9 kg/m2) , overweight (25–29.9 kg/m2) , obese (>30 kg/m2) , type 2 diabetes , non-alcoholic fatty liver disease , and category of risk of bias of trails, high risk of bias  (2 = 92.5%). The heterogeneity disappeared when subgroup analysis was performed on BMI categories including normal BMI , overweight , health status  , moderate   . Between= 0.082) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on HOMA-IR was significant in studies conducted trial duration > 8 weeks , intervention dose ≤ 1 g/d  and >1 g/d , normal (18.5–24.9 kg/m2) , overweight (25–29.9 kg/m2) , obese (>30 kg/m2) , type 2 diabetes  others , and category of risk of bias of trails, high risk of bias , moderate  (2 = 99.1%). The heterogeneity diminished when subgroup analysis was performed on BMI categories  , and health status  , low risk of bias   . Between= 0.498) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on SBP was significant in studies conducted baseline SBP < 120 mmHg , and ≥120 mmHg , trial duration ≤ 8 weeks  and > 8 weeks , intervention dose ≤ 1 g/d  and >1 g/d , overweight (25–29.9 kg/m2) , obese (>30 kg/m2) , type 2 diabetes , metabolic syndrome , others , and high risk of bias , moderate  (2 = 86.3%). The heterogeneity diminished when subgroup analysis was conducted on baseline SBP , BMI categories , and health status including dyslipidemia , metabolic syndrome , other health status , and moderate risk of bias   . Between= 0.667) .P = 0.063). The subgroup analysis showed that the effect of BBR supplementation on DBP was significant in studies conducted on trial duration ≤ 8 , and intervention dose >1 , metabolic syndrome  (2 = 94.9%). The heterogeneity diminished when subgroup analysis was conducted on BMI categories , health status including dyslipidemia , metabolic syndrome , and moderate   . Between= 0.734) .P = 0.887). The subgroup analysis showed that the effect of BBR supplementation on CRP was significant in studies conducted on intervention dose ≤ 1 g/d , BMI categories  (2 = 97.4%)  . Between= 97.4%) .P = 0.073). The subgroup analysis showed that the effect of BBR supplementation on IL-6 was significant in studies conducted on trial duration ≤ 8 weeks , intervention dose ≤ 1 g/d , and BMI categories  (2 = 94.7%). The heterogeneity diminished when subgroup analysis was conducted on intervention dose ≤ 1 g/d   . Between= 0.766) .P < 0.001). The subgroup analysis showed that the effect of BBR supplementation on weight was significant in studies conducted trial duration >8 weeks , intervention dose >1 g/d , overweight , type 2 diabetes  and non-alcoholic fatty liver disease , high risk of bias . Between study heterogeneity was found for the weight (I2 = 21.2%)  .2; 95%CI, −0.46 to −0.04; P = 0.020). The subgroup analysis showed that the effect of BBR supplementation on BMI was significant in studies conducted on overweight (25–29.9 kg/m2)  (2 = 44.7%). The heterogeneity diminished when subgroup analysis was conducted on trial duration , intervention dose , BMI categories , and health status including dyslipidemia , metabolic syndrome , and non-alcoholic fatty liver disease , and moderate risk of bias   . Between= 0.449) .2; 95%CI, −3.55 to 0.01; P = 0.005). The subgroup analysis showed that the effect of BBR supplementation on WC was significant in studies conducted on overweight (25–29.9 kg/m2) , >1 g/d dose  (2 = 92.9%). The heterogeneity diminished when subgroup analysis was conducted on >1 g/d dose , moderate risk of bias   . Between= 0.612) .P = 0.068) (2 = 92.3%) The heterogeneity diminished when subgroup analysis was conducted on trial duration ≤ 8 weeks , intervention dose >1 g/d , overweight (25–29.9 kg/m2) , obese (>30 kg/m2) , type 2 diabetes , and other health status   . Between= 0.069) .P = 0.316). The subgroup analysis showed that the effect of BBR supplementation on AST was significant in studies conducted on other health statuses  (2 = 95.8%) The heterogeneity diminished when subgroup analysis was conducted on trial duration ≤ 8 weeks , intervention dose >1 g/d , BMI categories , and type 2 diabetes   . Between= 0.992) .While the visual inspection of funnel plots showed slight asymmetries in funnel plots for all outcomes, no significant bias was detected based on Begg's for TG, TC, LDL, HDL, FBG, insulin, HbA1c, HOMA-IR, SBP, DBP, weight, BMI, WC, ALT and Egger's tests for CRP, IL-6, and AST .Plinearity = 0.019) (Plinearity = 0.006)   and WC (= 0.006)  was obsePnon − linearity = 0.007). The effect was more prominent at a dose of 1 g/d (Pnon − linearity = 0.013), while the association was more effective at a dose of 1 g/d (Pnon − linearity = 0.012), while the effect was more prominent at the dose of 5 g/d (Pnon − linearity < 0.001), and the effective dose of BBR was more optimum at the dose of 1.8 g/d (Pnon − linearity < 0.001), while the association was more effective at a dose of 1.8 g/d (Pnon − linearity = 0.043), while the association was more prominent at the dose of 1.8g/d , and the association was more effective at week 40 (Pnon − linearity < 0.001) while the effect was more prominent at 50 (Pnon − linearity = 0.005) and the association was more effective at week 50  of BBR use and serum concentration of FBG . Furthermore, regarding WC, León-Martínez et al.  was ineffective for changing TG, TC, LDL, HDL, insulin, SBP, weight, BMI, and WC. The significant effects of BBR on HDL and WC were only seen in doses of more than 1 g/day, on FBG and HOMA-IR in the durations of more than 8 weeks, and on HbA1c and weight in both mentioned higher subgroups of dose (>1 g/d) and duration (>8 weeks). Moreover, BBR was significantly effective in alleviating cardiovascular risk factors, mainly in subgroups with impaired metabolic health such as NAFLD, type 2 diabetes, and metabolic syndrome. In addition, BBR was effective for the improvement of LDL, HDL, and FBG only in subgroups with abnormal ranges . In the non-linear dose-response analysis, the optimum dose for BBR was 1 g/day for TG, TC, and weight, 1.8 g/day for insulin and HOMA-IR, and 5 g/day for HDL. The most effective duration was 40 weeks for FBG and 50 weeks from beginning of BBR supplementation for DBP and WC.BBR, a plant isoquinoline alkaloid with a long history of medical use , reducedn = 2).According to the subgroup analysis, it seems that BBR needs a supplementation duration of more than 8 weeks to reduce FBG, HbA1c, and HOMA-IR, and a dose of more than 1 gram per day to reduce HbA1c. This can be owing to the low bioavailability (< 1%) of this substance . Higher This meta-analysis showed a significant effect of BBR on TG, TC, LDL, and HDL. In line with this study, all the previous meta-analyses in different years have shown beneficial effects of BBR on lipid profile improvement , 98–100.n = 5).In subgroup analysis, the reduction in TG and TC was significant only in participants with overweight (BMI: 25–29.9) and obesity (BMI ≥ 30), the significant reduction in LDL was only in the overweight subgroup, and the significant increase in HDL was only in the obese group. Moreover, the subgroups with unhealthy metabolic status and with abnormal LDL (≥100 mg/dl) and HDL (< 40 mg/dl) responded significantly to this supplementation. All these conditions are linked to the secretion of inflammatory mediators and may benefit from anti-inflammatory substances –104. As The present study demonstrated a significant effect of BBR on weight, BMI, and WC. Two meta-analyses by Asbaghi et al. and Xiong et al., similar to this study, revealed the significant influence of BBR supplementation on the reduction of BMI and WC , 14. TheAccording to the subgroup analysis, the only BMI category in which the reduction in weight, WC, and BMI was significant was the overweight (BMI: 25–29.9). The number of trials included in this category was more than 3-folds that of the obese (BMI 30) and normal weight (BMI: 18.5–24.9) categories combined. We may see significant results in other BMI subgroups if the sample size was more. Doses of more than 1 g/day were effective for WC and BMI reduction and a duration of more than 8 weeks was effective for weight loss, which can be attributed the aforementioned low bioavailability of BBR . In a riThe present study reports a significant reduction in SBP but a non-significant change in DBP following BBR supplementation. Regarding the previous studies on the effect of BBR on BP, a systematic review done in 2021 by Suadoni et al. reported that the evidence was not enough, of good quality, and suitable duration to report any significant effects , and a mRegarding the subgroup analysis, SBP was significantly reduced in all subgroups despite normal BMI, dyslipidemia, and NAFLD, in which the included trials were only 1 or 2 studies. DBP did not change in the majority of subgroups, despite being significantly lower in the intervention dose of >1. This finding highlights the need for more well-designed RCTs in the future with higher intervention doses. In risk of bias subgroup analysis has shown that in high and moderate risk of bias trials, the decreasing effect is constant for SBP.This meta-analysis could not see any significant changes in two main inflammatory markers, CRP and IL-6, following the supplementation with BBR that was not expected regarding the anti-inflammatory properties of BBR. This result is in contrast with the meta-analysis of 12 RCTs by Asbaghi et al.  that fouSimilar to two previous meta-analyses, one from 12 RCTs by Asbaghi et al. , and anoIn the non-linear dose-response analyses, we found that the approximate optimum dose for BBR supplementation for the reduction of TG, TC, and weight is 1 g/day. This dose is 1.8 g/day for insulin and HOMA-IR, and 5 g/day for HDL improvement. The most effective duration for BBR intake was 40 weeks for FBG and 50 weeks for DBP and WC from beginning of supplementation. Although the plasma concentration of BBR tends to be low owing to its poor oral absorption and bioavailability, its concentration in different tissues usually remains high . The pha(GLUT4) translocation (via recovering depressed I (to) and I (Ca) currents (BBR has attracted many scientists' attention owing to its ameliorative effects on CVD risk factors , 16, 77.location . It is plocation . Therefolocation , 93, andlocation . Moreovelocation . BBR canlocation , CREB (1location , GATA-2,location . It is alocation . The othlocation . This aglocation . The othlocation , and itslocation . BBR attcurrents .This meta-analysis has various strengths and limitations. one of the most important strengths of this study can be considered the most comprehensive meta-analysis to date regarding the relationship between BBR and all different cardiovascular risk factors with a dose-response analysis with the larger sample size compared to the previous similar meta-analysis , 91, 99.This systematic review and dose-response meta-analysis found a significant improvement in lipid profiles, insulin resistance, and anthropometric measures associated with BBR supplementation. However, no significant changes have been observed in liver enzymes or inflammatory markers. Therefore, BBR may be an effective supplement for the improvement of metabolic syndrome and cardiovascular risk. To comprehend how BBR affects these outcomes in people, mechanistic research, homogeneous RCTs, and future investigations are required.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.MZam designed the study. MZam and OA developed the search strategy and assessed the risk of bias in the meta-analyses. MZam, MN-S, and OA extracted the data and conducted the analyses. SH and MZar drafted the manuscript. FS, OA, and MN-S interpreted the results. FS and OA revised the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The relationship between abnormal lipid levels and atherosclerotic cardiovascular diseases is well established, but the association between remnant cholesterol (RC) and coronary heart disease (CHD) remains uncertain. The aim of this meta-analysis is to systematically evaluate the prognostic value of RC concentration in patients with CHD.PubMed, EMBASE, Cochrane, and Web of Science databases were reviewed to identify relevant observational cohort studies published in English up to December 2021. Random-effects meta-analysis compared the highest and lowest RC concentration. The primary outcome was a composite of major adverse cardiovascular events (MACEs) and all-cause mortality in patients with CHD.P = 0.44). Subgroup analysis showed consistent results.A total of 10 studies recruiting 30,605 patients with CHD were selected to be included in this meta-analysis. Patients with CHD with elevated RC concentration had an increased risk of the composite endpoint events  and MACEs , but the risk of all-cause mortality was not statistically significant (RR = 1.16, 95% CI: 0.79–1.69, Our results suggest that elevated concentration RC may independently predict MACEs in patients with CHD. Determination of RC concentration may improve risk stratification of prognosis in patients with CHD. However, more high-quality studies are necessary to confirm this association. Coronary heart disease (CHD) is the most common type of organ disease caused by atherosclerosis, which is seriously threatening people’s life and health , 2. The In recent years, remnant cholesterol (RC) has been reported to have a critical role in atherosclerosis and CHD, which might indicate it may also be a critical component of the residual risk of patients with CHD , 4. RC iTherefore, our study aims to systematically review and compile meta-analyses of the evidence on the relationship between RC concentration and CHD outcome, by identifying the potential confounders and investigating the prognostic value, which may provide a novel perspective for risk assessment and treatment in patients with CHD.Our meta-analysis was performed according to the recommendation of the meta-analysis of Observational Studies in Epidemiology (MOOSE)  and the We comprehensively searched four medical databases, including PubMed, EMBASE, Cochrane, and Web of Science, to identify cohort studies assessing the relationship between RC concentration and cardiovascular outcomes published in English from inception up to 25 December 2021. The query syntax was set using Medical Subject Headings (MeSH) and thesaurus search terms, including (“remnant cholesterol” OR “remnant-like particle cholesterol” OR “triglyceride-rich lipoprotein cholesterol”) AND (“coronary heart disease” OR “coronary disease” OR “coronary artery disease”). The detailed search strategy was presented in the The inclusion criteria for this study were presented as follows: (1) cohort studies; (2) an inception cohort involving adults with CHD; CHD included stable or unstable angina, and myocardial infarction (MI); (3) the exposure factor was RC concentration; (4) the endpoint was major adverse cardiovascular events (MACEs) and all-cause mortality. MACEs included cardiac death, MI, ischemic stroke, myocardial ischemia, heart failure, unstable angina requiring readmission, and coronary revascularization; and (5) the highest and lowest RC concentration groups of multivariate-adjusted relative risks (RRs), odds ratios (ORs), or hazard ratios (HRs) and their 95% confidence intervals (95% CI) or the above indicators could be calculated with the complete data .Exclusion criteria included (1) case reports, commentary, and conference abstracts; (2) animal, cross-sectional studies, or randomized clinical trials; (3) studies carried out among pregnant women or children; and (4) examined non-relevant outcomes.YT did the screening of the titles and abstracts of the identified articles, and pertinent articles were independently reviewed in full text by two investigators (YT and WW). Thus, disagreement was resolved through consensus.Data extraction was in a standardized style. Two investigators (YT and LQ) independently extracted the following data: the first author, publication year, population, study design, type of CHD, sample size, percentage of women, age, exposure assessment method, fasting status, follow-up duration, outcome assessment, categorical or continuous, adjusted risk estimates, and adjustment for variables.The quality of observational cohort studies was assessed using the Newcastle–Ottawa Scale (NOS) , which wI2 statistics and chi-square Cochran’s Q-test were used to assess the heterogeneity across studies. If P ≥ 0.05 and I2 < 50%, suggesting that no significant heterogeneity could be found, a fixed-effect model was also applied. In addition, if P < 0.05 and I2 ≥ 50%, a random-effect model was cautiously applied, and then subgroup analysis was used to explore the source of heterogeneity  and Stata 16.0  were employed for statistical analysis. The ogeneity . The eliogeneity –24. The n = 11) (n = 5) (n = 5) (n = 7)  , 25–34,  (n = 5) –39, thos (n = 5) –42, and  (n = 7) –49. Fina (n = 7) , 50–54 cThe main characteristics of the included studies are summarized in P < 0.0001) in a random-effect model , and sensitivity analysis indicated that the total combined effect size did not change significantly in each step, demonstrating that the meta-analysis results were relatively stable. However, if the study conducted by Martin et al. .The results demonstrated that elevated RC concentration was related to an increased risk of composite endpoint events   without significant heterogeneity  in a fixed-effect model. However, the risk of all-cause mortality was not statistically significant , with significant heterogeneity  in a random effect model. In addition, sensitivity analysis showed that after removing the study of Martin et al. .In addition, as shown in n et al. , the hetP < 0.0001) for those with the diagnosis of MI  and with older age (≥65 years old) . In addition, this constant association continued in selected studies for those publications with sample size <1,000 cases , those that used the immunoseparation method  and fasting status test  for RC assessment, and studies with a long follow-up time (≥3 years)   .P < 0.05).As shown in In the present study, the relationship between RC concentration and the prognosis of the patients with CHD was evaluated by meta-analysis for the first time. The results illustrated that elevated RC concentration was significantly correlated with an increased risk of the composite endpoint events and MACEs in patients with CHD, but the risk of all-cause mortality was not statistically significant. In addition, the prognostic significance of higher RC concentration on CHD risks was also confirmed in the subgroup analysis. This meta-analysis contributes to the increasing evidence that higher RC concentration may be an independent predictor of poor cardiovascular outcomes in patients with CHD.Remnant cholesterol, also known as triglyceride-rich lipoprotein cholesterol, is the cholesterol content of all non-LDL and non-HDL. In the fasting state, RC is composed of liver-derived very low-density lipoprotein (VLDL) and intermediate-density lipoprotein (IDL) in the fasting state, as well as intestinal-derived chylomicron remnants (CM) . RecentlThe previous clinical studies demonstrated similar conclusions between RC concentration and prognosis in the general population but not in patients with CHD. The latest study by Wadstrom et al.  revealedIn addition, genetic evidence has also been found that RC was the risk factor for atherosclerosis. Varbo et al.  performe3-C and IDL-C was used to calculate RC and fasting state was unknown. At present, no uniform method to measure RC concentration has been provided, and accurate measurement is still challenging, which might be the main reason for conflict in the findings (In our study, sensitivity analysis found that the source of heterogeneity might be the research conducted by Martin et al. . In thisfindings –16. Thisfindings . Currentfindings ; that isfindings , 52–54. findings , 50, 51,findings , and nucfindings . In our This study also had potential limitations. First, the studies included in this study were all published in English, which might have a language bias. Second, the differences in the types of CHD and RC measurement approaches in each study may lead to clinical heterogeneity. Third, the included studies adjusted some confounders, but other unadjusted risk factors may exist. Some traditional CHD factors cannot be extracted adequately from the included studies, which might also lead to bias. Thus, further studies of stratified analysis for the risk factors of CHD outcome are necessary. Fourth, there were insufficient relevant data to compare the prognostic effect between LDL-C and RC from the included studies. Then, it is worth answering this valuable question in future studies. Finally, there was a significant publication bias in our study, suggesting the possible presence of negative results that were not published. Therefore, future studies are needed before a firm conclusion can be drawn concerning the association between RC concentration and CHD outcome.This meta-analysis of 10 cohort studies showed that CHD patients with elevated RC concentrations had a higher risk of adverse cardiovascular outcomes. Measurement of RC concentration has the potential to improve risk classification in patients with CHD. However, future larger sample sizes and higher quality studies are still required to confirm the findings.The original contributions presented in this study are included in this article/YT, WW, and LQ performed the literature search, data extraction, and quality assessment. YT performed data analysis and drafted the manuscript. XY and LC critically revised the study. HW and ZZ designed the study, interpreted the data, and revised the manuscript. All authors contributed intellectually to this manuscript and have approved this final version.


Some studies suggest that a higher phytochemical index (PI) is associated with a lower risk of overweight/obesity. This meta-analysis is performed to summarize published studies on the relationship of PI and the risk of overweight/obesity. We searched on PubMed, Cochrane Library and Web of Science from the inception dates to February 2022. The random-effect model was used based on heterogeneity. Meta-regression was used to explore potential sources of between-study heterogeneity. Publication bias was evaluated using Begg’s and Egger’s tests. The dose–response relationship was assessed using a restricted cubic spline model. Nine studies were included in the meta-analysis, with a total of 100,753 participants. The meta-analysis showed that the phytochemical index was associated with a decreased risk of overweight/obesity. The pooled OR (95% CI) was 0.81 (0.74–0.90). The findings from dose–response analysis showed a nonlinear association between the phytochemical index and the risk of overweight/obesity. The results of the meta-regression showed that gender and area were significant covariates influencing the heterogeneity between studies. There was no publication bias in the meta-analysis of this study. In conclusion, although this meta-analysis indicates that a high phytochemical index is associated with a reduced risk of overweight/obesity, all the studies included in this meta-analysis were cross-sectional studies with high heterogeneity. As such, more data from randomized controlled trials are required to confirm the efficacy of PI in evaluating the risk of overweight/obesity. Overweight and obesity are characterized by abnormal or excessive fat accumulation that can damage health . Recent Several epidemiological and cross-sectional studies have shown that vegetarian diets can reduce body weight and body mass index (BMI) ,7,8,9. ISome studies have suggested that a higher phytochemical index (PI) is associated with a lower risk of overweight/obesity ,18,19,20We searched PubMed, the Cochrane Library and Web of Science from the inception dates to February 2022. The following keywords were used to identify published literature which examined the relationship between PI and the incidence of overweight or obesity: phytochemicals, dietary phytochemicals, plant bioactive compounds, plant biologically active compounds, plant-derived chemicals, phytonutrients, non-nutrient bioactive substances, bioactive food components, index, overweight, and obesity.The included articles needed to meet the following five inclusion conditions: (1) The exposure variable was PI/DPI; (2) the outcome variables were overweight/obesity or centripetal obesity; (3) the literature needed to provide an odds ratio/relative risk/hazard ratio (OR/RR/HR) and a 95% confidence interval (CI) between PI and overweight/obesity; (4) the literature used for dose–response analysis must provide the dose, number of cases, number of person-years in each group, or the data can be obtained by the conversion of missing values; and (5) the language of the original article was English. The following two exclusion criteria were applied: (1) the study subjects were not humans and (2) review.Data were independently extracted and cross-checked by two researchers according to uniform standards, and experts could be consulted in case of disagreement. The main contents of data extraction included: first author, publication year, area, dose, cases per year and OR/RR/HR in each exposure–dose range.The quality of the included literature was assessed using the 11-item checklist recommended by the Healthcare Research and Quality Authority (AHRQ). Article quality was assessed as follows: low quality = 0–3; moderate quality = 4–7; and high quality = 8–11 .2 < 50% [2 ≥ 50% [Stata12.0 software was used for statistical analysis, the Q test was used to test the heterogeneity of the included studies, I2 was used to evaluate the heterogeneity, and the test level was α = 0.05. If I2 < 50% , there w[2 ≥ 50% , the ran[2 ≥ 50% ,25 were [2 ≥ 50% .The literature-screening process is shown in 2 = 61.3%; p < 0.001).2 = 64.3%, p < 0.001); however, there was no statistically significant relationship between the highest PI and overweight/obesity in children or adolescents . In addition, a total of three studies [2 = 34.1%, p = 0.167), but not in men . The subgroup analysis of diagnostic criteria of overweight/obesity showed that PI was related to the prevalence of overweight/obesity when waist circumference/waist-to-hip ratio/waist-to-height ratio (WC/WHR/WHtR) was used to determine obesity , but this was not found when BMI was used . A subgroup analysis of area showed that the highest PI was associated with overweight/obesity in both West Asia  and East Asia . studies ,19,20 in2 = 38.4%) after the first article [The included studies were removed one by one, and the remaining studies were meta-analyzed. The results showed that the combined effect value changed greatly and heterogeneity decreased  as covariates . The resp for Begg’s test = 0.955; p for Egger’s test = 0.059).A funnel plot , Begg’s p = 0.0447).We included four articles including 13 sets of data to study the dose–response relationship . The resA growing number of studies have investigated the effects of the phytochemical index on chronic diseases such as metabolic syndrome ,19, diabFrom the results of the subgroup analysis, there are several factors worth considering. First, the results varied according to the age of the participants in the original study. A subgroup analysis of age showed that a higher PI was a protective factor in adults. However, the results were not statistically significant in children or adolescents, which may be due to the lack of corresponding literature. To date, only a few studies have assessed the link between PI and obesity, and most of the research was conducted on adults.Subgroup analysis by gender found that women with a higher PI had a lower risk of obesity, but no association between PI and obesity prevalence was observed in men. In fact, a study of adults in Korea found that a higher intake of total flavones was associated with a lower risk of obesity; however, this association was not found in men . In addiA subgroup analysis using diagnostic criteria of overweight/obesity found that when obesity was defined by WC/WHR/WHtR, the incidence of overweight/obesity was lower in people with a high PI. A cross-sectional survey of 54 adults showed a negative correlation between DPI and WC. Phytochemicals may inhibit preadipocyte proliferation through partial polyphenols, reduce adipogenesis and promote lipid decomposition to maintain WC normality ,41. A suIn addition, the dose–response relationship showed a decreased risk of overweight/obesity with increased PI. Diets with more phytochemicals are generally lower in calories, so they are more likely to reduce obesity risk. Some studies have shown that a diet rich in phytochemicals can improve obesity by reducing oxidative stress, inducing the production of pro-inflammatory cytokines, promoting thermogenesis, inhibiting adipocyte differentiation and reducing adipogenesis ,43.Inter-study heterogeneity is a key issue in meta-analysis, which directly affects the interpretation of meta-analysis results. Therefore, it is an important aspect of this study to explore the potential sources of heterogeneity between studies. The results of our meta-regression showed that gender and area were the significant covariables affecting inter-study heterogeneity. The sensitivity analysis results showed that after removing Bahadoran Z’s study , the hetOur meta-analysis showed that PI was inversely associated with the risk of overweight/obesity. With the increase in PI, the prevalence of overweight/obesity decreased gradually. However, these findings were limited because the studies included in this meta-analysis were all cross-sectional studies. Therefore, no definite conclusions can be drawn at present. Due to the high heterogeneity of cross-sectional studies, this evidence needs further validation.