Previous studies have suggested that ambient temperature is associated with the morbidity and mortality of stroke although results among these investigations remained unclear. Therefore, the purpose of present meta‐analysis was to summarize the evidence of the relationship between ambient temperature and stroke morbidity and mortality.A systematic search of the PubMed, Embase, and Web of Science databases was from inception to April 13, 2022. The pooled estimates for heat ambient temperature and cold ambient temperature, which were defined as comparison between extreme hot or cold conditions and the reference or threshold temperature, were calculated utilizing a random‐effects model. A total of 20 studies were included in the meta‐analysis.RR], 1.10; 95% confidence interval [95%CI]: 1.02–1.18) and 9%  increase in the risk of stroke morbidity and mortality, respectively. In addition, the pooled estimated show that the cold ambient temperature was significant associated with 33%  and 18%  increase in the risk of stroke morbidity and mortality, respectively.The pooled estimated show that the heat ambient temperature was significant associated with 10%  and 9% , respectively.For cold ambient temperature effect, the risk of stroke morbidity and mortality increased 33%  and 18% , respectively. Animal‐based studies, intervention studies, toxicological studies, qualitative evaluations, letters, reviews, commentaries, or studies that only reported cardiovascular disease events but did not specifically access stroke or cerebrovascular disorders were excluded. Detailed inclusion criteria are shown in Tables  populati exposure2.3We screened and identified the studies which met the eligibility criteria in a step‐by‐step manner. First, we screened the title and abstract based on predefined eligibility criteria. Second, two authors (J.W. and Y.L.) independently assessed the full text before performing the meta‐analysis, the reference lists of relevant original articles and relevant review articles were also scrupulously checked to avoid missing possible original articles. Additionally, discrepancies were resolved by discussion with the third author (J.M.).2.4RR, or odds ratios [OR] with 95% confidence interval [CI]), and controlled variables . Any differences in data extraction were resolved and confirmed by discussion with third authors (J.M.).Eligible articles were extracted independently in duplicate, and all reconciled by two authors (J.W. and Y.L.). Data were extracted on the following study characteristics: the last name of the first author, publication year, study period, country, study design, sample size, exposure, temperature range, outcome, model, lag days, population, effect indicator  was used to evaluate the quality of time‐series and case‐crossover studies, respectively. The scale score was calculated based on the three sections including study group selection (4 points), comparability of groups (2 points), and the exposures or outcomes (3 points)  was >25%; or otherwise, the fixed‐effects model was applied  was deemed statistically significance.All statistical analyses were conducted using Stata 16.0 , and 33.1According to the systematic search, a total of 9847 articles were identified, of which 3326 were removed because of duplication. Of those, 6459 were removed after review of the title and abstract, because they were animal studies, clinical trials, letters, commentaries, reviews, biomechanics, or not relevant studies. Then, a total of 62 articles were excluded after a full‐text screening because exposure was not heat/cold effect, the outcomes were not stroke, or information were not useful. Finally, 20 articles were leaved on meta‐analysis , and the pooled RR of stroke mortality was 1.09 . For cold ambient temperature effect, the pooled RR of stroke morbidity was 1.33 , and the pooled RR of stroke mortality was 1.18 .In the categorical meta‐analysis, the pooled estimates of heat ambient temperature effect on stroke morbidity and mortality and cold ambient temperature effect on stroke morbidity and mortality were shown separately Figures , 3, 4, 53.4RR = 1.16, 95%CI: 1.00–1.34; RR = 1.14, 95%CI: .97–1.33) from heat ambient effect were higher in developed countries compared to developing countries . Interestingly, the cold ambient effect was quite different, with stroke mortality and morbidity risks being lower in developed countries  than in developing countries . Of note, we found that the heterogeneity of the association between the heat ambient temperature effect and stroke mortality was 35.5% in studies that controlled for air pollution and 81.8% in studies that did not. In terms of cold ambient temperature effect and stroke mortality, the heterogeneity was 7.5% in studies that controlled for air pollution and 72.7% in studies that did not. Additionally, subgroup on the heat or cold ambient temperature effect of stroke mortality showed that the source of heterogeneity could also be whether the long‐term and seasonal trend was controlled. The heterogeneity was mainly from studies controlled for long‐term and seasonal trend: I2 = 84.7% for heat ambient temperature effect and I2 = 87.4% for cold ambient temperature effect. The heterogeneity was 0.0% and 10.0% for heat and cold ambient temperature effect that did not control the long‐term and seasonal trend, respectively. The result of the subgroup analysis is in Table Aim to evaluate the stability of the primary pooled estimates results and identify the possible resources of heterogeneity, subgroup analyses were conducted according to study design, socioeconomic status, latitude, and controlling for relative humidity, air pollution, day of week, holiday, long‐term, and seasonal trend, respectively. In general, the results were similar across the subgroups in that heat or cold ambient temperature increased the risk of stroke. When stratified by socioeconomic status, we found that stroke morbidity and mortality (3.5RR ranged from 1.08 (1.01–1.15) to 1.11 (1.06–1.16) in stroke mortality. For cold ambient temperature effect, the pooled RR ranged from 1.28 (1.14–1.44) to 1.41 (1.20–1.66) and from 1.14 (1.04–1.26) to 1.21 (1.06–1.37) in stroke morbidity and mortality, respectively. Although sensitivity analysis suggested very subtle modifies in the assessments of heat ambient temperature effect on stroke morbidity, the pooled RR ranged from 1.07 (95%CI: 1.00–1.14) to 1.12 (95%CI: 1.03–1.20). The study performed by Chen would modify the pooled heat ambient temperature effect of stroke morbidity.Sensitivity analyses suggested that neither the study was likely to have a significant impact on the result for heat ambient temperature effect on stroke mortality, nor cold ambient temperature effect on stroke morbidity and mortality Figure . For hea3.6pEgger's = .048, pBegg's = .858 in stroke morbidity; pEgger's = .021, pBegg's = .764 in stroke mortality). For cold ambient temperature effect on stroke morbidity and mortality, both the Egger test and Begg test indicated evidence of publication bias .For heat ambient temperature effect on stroke morbidity and mortality, the Egger test indicated evidence of publication bias, but the Begg test did not  and 1.04 (95%CI: .97–1.10), respectively. The corrected RR of cold ambient temperature effect on morbidity and mortality was 1.11 (95%CI: .97–1.27) and 1.03 (95%CI: .94–1.14), respectively. Funnel plots and trim‐and‐fill figures are in Figures The pooled effects on stroke morbidity were corrected using the trim‐and‐fill method owing to publication bias. The corrected 4This meta‐analysis supplies an updated examination of the effects of various ambient temperature conditions. To the best of our knowledge, this is the first study to assess not only the association between heat and cold ambient temperature effects and stroke morbidity, but also stroke mortality, which fill the gaps in previous studies. More specifically, present meta‐analysis found that the risk of stroke morbidity and mortality significantly increased in relation to heat and cold ambient temperature effect. Our findings have important implications for developing the policy of public health and reducing the burden of stroke.RR: .98, 95%CI: .94–1.02). The inconsistent results may be due to the fact that this meta‐analysis study reported the relationship between maximum temperature and ischemic stroke occurrence, which temperature as a continuous variable, but in our study ambient temperature as a categorical variable, heat ambient temperature was compared to reference or threshold temperature. Moreover, there were only two original studies with greater chance in previous meta‐analysis (Wang et al., The combined estimate of heat exposure on elevated risk of stroke morbidity and mortality, which is accordant with the previous meta‐analysis in which each 1°C increase was associated with 1.1% increase in occurrence and mortality of stroke (Lian et al., The increased risk of stroke morbidity and mortality with heat ambient temperature effect may be explained by some potential mechanisms. One possible explanation is that in heat conditions the body needs to increase heat diffusion through sweating, which may lead to dehydration and a reduction in central blood volume. This further leads to increased blood viscosity, altered serum osmolality, and altered BUN/cr, which may increase the risk of microvascular thrombosis and subsequent ischemic stroke (Bahouth et al., In our meta‐analysis, the combined estimate of cold ambient temperature exposure on elevated risk of stroke morbidity and mortality was significant. Our assessment of the relationship between cold ambient temperature effect and stroke was in‐line with similar previous meta‐analyses (Lian et al., Several physiological mechanisms by which cold ambient temperature effect might act as a trigger for stroke have been suggested to explain this phenomenon. Exposure to cold ambient temperatures may lead to activation of the sympathetic nervous system and the renin‐angiotensin system and an increase in blood pressure, which may lead to plaque rupture and thus an increased risk of ischemic stroke (Barnett et al., As substantial heterogeneity was found among the included studies, we conducted subgroup analyses by study design, socioeconomic status, latitude, and controlling for relative humidity, air pollution, day of week, holiday, long‐term and seasonal trend. In subgroup analyses, we found whether air pollution and long‐term and seasonal trends were controlled may be sources of heterogeneity. Besides, we found that heterogeneity remained substantial which may be related to numerous factors. First, exposure measurement of studies was from different sources with varied definitions. For example, some studies use apparent temperature, including daily average air temperature, relative humidity, wind speed, and vapor pressure, which is different from ambient temperature (Roye et al., Aim to access the robustness of our result, we conducted a publication bias assessment and a sensitivity analysis. Publication bias among studies which accessed the association between heat and cold ambient temperature effect and stroke morbidity and mortality were found in our study. Therefore, we used the trim‐and‐fill method to assess publication bias. We found that the trim‐and‐fill method could change our results, probably due to the small number of original studies. According to the principle of symmetry, multiple non‐existing small sample size studies were supplemented, and the combined effect size was calculated on this basis, resulting in the appearance of overcorrection (Egger & Smith, The review highlighted the need for research to identify and study interventions in public health to reduce the problem of increased stroke morbidity and mortality due to extreme ambient temperatures, particularly in vulnerable populations. First of all, all countries are advised to take environment‐related actions, such as reducing greenhouse gas emissions. Developed countries in particular should pay more attention to the public health issues arising from greenhouse gas emissions. The subgroup analysis showed that the risk of increased stroke morbidity and mortality associated with heat effect is higher in developed countries than in developing countries, which may be related to the higher greenhouse gas emissions in developed countries. Second, the health care system should also take action to deal with the health problems caused by extreme temperatures. For example, an early warning system for extreme temperatures should be set up, with extreme temperature warnings issued through television, radio, and the internet, so that the public, especially vulnerable people, can receive timely weather information and take measures to protect themselves. In addition, special adaptation measures and health promotion methods can also be developed for the characteristics of different vulnerable groups, which can lead to more effective results. For example, when extreme temperature warnings are issued, health care system such as community hospitals can take the initiative to give health guidance and medication advice to elderly people with chronic illnesses, especially those living alone and suffering from neurological disorders or a history of stroke, using telephone visits or home visits to ensure that they stay in air‐conditioned environments as much as possible during extreme temperature and seek prompt medical attention if they have any health problems. During a COVID‐19 pandemic, the health care system can take measures for smart care, such as telemedicine and smart homes, to reduce the health risks associated with COVID‐19‐related isolation.There are several highlights in our study. First, we provided updates on the associations of ambient temperature with the risk of stroke, including more than one times as many studies as for a meta‐analysis of pooled effect sizes than previous meta‐analysis. Moreover, the selection of studies was based on strict criteria for eligibility and exclusion, which helped provide more reliable evidence. Second, in contrast to previous study, this is the first studies covered four outcomes, allowing comparisons among these outcomes and a more comprehensive assessment of ambient temperature changes effect on stroke morbidity and mortality separately. Third, despite heterogeneity among the included studies, consistent results from sensitivity analyses and various subgroup analyses suggest that our findings are reliable and robust.However, in our studies there were some limitations should be of concern. First, we included both time‐series studies and case‐crossover studies. Although we used NOS for assessing the quality of included studies, which is considered the most effective standard. There are some limitations in proving causation of disease, which may influence the validity of our results (Mendoza & Yeh, 5The inspiration of our meta‐analysis clearly suggests that heat or cold ambient temperature are associated with an increased risk of stroke morbidity and mortality. This study provides a potential mechanism for the association of ambient temperature changes on stroke, and an understanding of the broader effects of extreme ambient temperature on stroke has the potential to suggest enhancements to public messaging efforts. As well as authorities should be aware of the seriousness and provide interventions that might mitigate the adverse effects of extreme ambient temperature, which everyone can benefit from these.Jing Wen, Li Zou, and Jing Mao: Conceptualization. Jing Wen and Ziwen Jiang: Methodology. Jing Wen and Yufeng Li: Software. Jing Wen, Yufeng Li, and Li Zou: Validation. Ziwen Jiang, Wenning Fu, and Jiaxin Tao: Formal analysis. Ziwen Jiang, Wenning Fu, and Yufeng Li: Investigation. Ziwen Jiang, Wenning Fu, and Xue Bai: Resources. Xue Bai and Jiaxin Tao: Data curation. Jing Wen and Li Zou: Writing—original draft preparation. Yufeng Li and Li Zou: Writing—review and editing. Jing Mao: Visualization. Jing Mao: Supervision. Jing Mao: Project administration. Li Zou and Wenning Fu: Funding acquisitionThe authors have no relevant financial or nonfinancial interests to disclose.https://publons.com/publon/10.1002/brb3.3078.The peer review history for this article is available at Figure S1 Sensitivity analysis plot of stroke morbidity and mortality for ambient temperature.Click here for additional data file.Figure S2 Funnel plot of stroke morbidity and mortality for ambient temperature.Click here for additional data file.Figure S3 Filled funnel plot of stroke morbidity and mortality for ambient temperature.Click here for additional data file.Table S1 Search strategies for electronic academic databases.Click here for additional data file.Table S2 Subgroup analyses of stroke morbidity and mortality for ambient temperature.Click here for additional data file.


Soy is rich in plant protein, isoflavones, and polyunsaturated fatty acids. To clarify the associations between soy intake and type 2 diabetes (T2D) and cardiovascular diseases (CVDs) events, we performed a meta-analysis and review. A total of 1963 studies met the inclusion criteria, and 29 articles with 16,521 T2D and 54,213 CVDs events were identified by the eligibility criteria. During a follow-up of 2.5–24 years, the risk of T2D, CVDs, coronary heart disease, and stroke in participants with the highest soy consumption decreased by 17%  = 0.83, 95% CI: 0.74–0.93), 13% , 21% , and 12% , respectively, compared to the lowest sot consumption. A daily intake of 26.7 g of tofu reduced CVDs risk by 18%  and 11.1 g of natto lowered the risk of CVDs by 17% , especially stroke. This meta-analysis demonstrated that soy consumption was negatively associated with the risks of T2D and CVDs and a specific quantity of soy products was the most beneficial for the prevention of T2D and CVDs. This study has been registered on PROSPERO (registration number: CRD42022360504). Soy is a major source of plant protein, dietary fiber, polyunsaturated fatty acids, lecithin, stigmasterol and isoflavones. Soy protein is the only plant-derived complete protein and it accounts for 35–40% of soy, containing all the essential amino acids in animal proteins . Its amiCardiovascular diseases (CVDs) remain a major cause of mortality and disability worldwide, accounting for one-third of global deaths . CVDs moAn increasing number of observational studies and meta-analyses have been focusing on the relationship between increased soy consumption and the risk of T2D and CVDs, but the conclusions were inconsistent ,24 To reThis systematic review and meta-analysis was reported based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline . We alsoThree reviewers conducted a systematic search of all articles published up to 14 October 2022, of online databases, including Medline, PubMed, Web of Science core collection, and Embase. The research was restricted to human studies. Detailed search strategies can be found in Studies were included in this meta-analysis according to the following criteria: (1) the study design was a case–control or nested case–control or cohort, (2) the exposure factor was soybean, soy food, or soy protein consumption, (3) the outcome of interest was population aged more than 18 years with T2D or CVDs events, including coronary heart disease (CHD) and stroke, and those who reported odds ratio (OR), relative risk (RR), or hazard ratio (HR) associated with 95% confidence interval (95% CI) between the interested exposure and outcome. Exclusion criteria were as follows: (1) Case reports, editorials, letters to editors, comments, conference abstracts, short communications, reviews, cross-sectional, and animal studies were not considered. (2) If study participants were reported more than once, we selected the greatest number of cases or the result with a longer follow-up time. Three independent reviewers first selected relevant studies by screening the titles and then, reviewed the full texts according to the inclusion/exclusion criteria to decide the final relevant references to be included in the review. Any discrepancy between the three co-authors was resolved with a fourth author.Three investigators used a predefined form to extract information, including first author, publication year, database used, country, study design, sample size, duration of follow-up in cohort studies, type of Food Frequency Questionnaire (FFQ), exposure assessment, ascertainment of outcomes , comparison, adjustment for confounding covariates, and the Newcastle–Ottawa Scale (NOS)  score. WThe methodological quality of each study was independently evaluated by three reviewers using NOS . This scI2, the Q-test was used to estimate the heterogeneity between studies. A p value less than 0.10 or an I2 value greater than 50% indicated statistical heterogeneity. Meta-regression and subgroup analyses were used to analyze sources of heterogeneity. Sensitivity analyses were performed by excluding each study to assess the stability of the study. Egger’s test and Begg’s test were designed to assess publication bias.Review Manager, version 5.3  and Stata, Version 14.0  were used to perform all statistical analyses. A random-effects model was used to calculate total relative risk (TRR) and 95% CI for the highest category compared to the lowest category analysis of each study in this meta-analysis. Forest plot was created to visually assess the pooled result for each study and overall estimate. Based on the statistical test of p values were considered significant at the level < 0.05.Methods described by Greenland  and OrsiThis study included 45 articles by screening the titles and abstracts and sixteen articles were further excluded based on the inclusion and exclusion criteria . FinallyThe main characteristics of the included studies were given in A meta-analysis for fifteen studies from nine articles about T2D events demonstrated a significant negative association between soy consumption and the incidence rate of T2D . However, dried and other soy foods were significantly and negatively associated with T2D events . In cardiovascular events, only tofu  and natto  were negatively associated with CVDs, whereas soy milk  and miso soup  were not. Further analyses found that only tofu was associated negatively with CHD events , and only natto was associated negatively with stroke events .To investigate the association of specific soy products with T2D and CVDs, we performed a subgroup analysis. All subgroup analyses of soy foods were shown in Pnonlinearity = 0.003, Pnonlinearity < 0.001, Pnonlinearity < 0.001, Plinearity = 0.72, Pnonlinearity = 0.13; Plinearity = 0.91, Pnonlinearity = 0.70; Plinearity = 0.62, Pnonlinearity = 0.19; Through a dose–response analysis, the non-linear significant relationships were found between tofu and CVDs  was demonstrated, but neither was found in men  nor in both included together . The daily intake of 26.7 g of tofu reduced CVDs risk by 18%. A daily intake of 11.1 g of natto lowered the risk of CVDs by 17%, especially stroke. Our findings may support a specific intake of tofu and natto for preventing CVDs and providing greater longevity. More prospective and multi-center studies should be performed to find the protective association between dose-analysis of soy foods and T2D and CVDs.


Previous studies have found the potential role of gout or hyperuricemia in subsequent development of Alzheimer's disease (AD) but reported inconsistent results. We conducted the current meta‐analysis to evaluate whether an association exists between gout/ hyperuricemia and AD.We systematically searched PubMed and EMBASE for the published cohort studies that measured the risk of AD in subject with gout/ hyperuricemia up to May 20, 2023. Data extraction was employed by two authors independently. Rev Man 5.3 and Stata 15.0 software were used to calculate the relative ratio (RR) or hazard ratio (HR) for including studies. Subgroup analysis was performed to assess the sources of heterogeneity. A random‐effects model was adopted when heterogeneity was present. The funnel plot, Begg's test, and and Egger's test were used to assess publication bias.After rigorous screening, seven eligible studies were included in the final analyses. Pooled results indicated that gout or hyperuricemia decreases the risk of AD , with a high heterogeneity of 93%. Subgroup analyses showed that regional distribution was the source of heterogeneity. Egger's and Begg's tests as well as visual inspection of funnel plot suggested no publication bias in the studies.The findings suggested that gout or hyperuricemia might have a protective effect against AD. This negative correlation should be verified by more cohort studies due to the existence of substantial heterogeneity. In the current meta‐analysis, we comprehensively evaluated the association between gout/hyperuricemia and AD based on evidence from high‐quality cohort studies. Interestingly, the results showed a 31% AD risk reduction for gout or hyperuricemia. This indicated that gout or hyperuricemia might be a protective factor approach to prevent AD formation.  Existing epidemiological surveys indicated that approximately 50 million people worldwide were living with dementia, projected to triple in 2050  crystals in the synovial fluid of articular and peri‐articular tissues, resulting in gouty arthropathy, tophi formation and organ damage Lee, . Gout isBecause of the inconsistencies among studies, we conducted an up‐to‐date cohort based meta‐analysis to quantify the correlation of gout or hyperuricemia with AD.2These systematic review and meta‐analysis were conducted in accordance with the preferred reporting items for systematic reviews and meta‐analysis (PRISMA) guidelines  independently searched the PubMed and EMBASE for papers published from their inceptions to May 20, 2023. Medical Subject Headings (MESH) terms set in the search were (“gout” OR “arthrolithiasis” OR “podagra” OR “dominus merborum” OR “hyperuricaemia”) AND (“Dementia” OR “Alzheimer's disease” OR “Mixed Dementia” OR “Cognitive decline” OR “Cognitive impairment”) NOT .2.2Articles were included if they fulfilled the following inclusion criteria: (1) prospective or retrospective cohort studies; (2) the exposed group consisted of gout or hyperuricemia patients, while controlled group consisted of AD patients; (3) report of risk estimates [hazard ratios (HR) or rate ratios (RR)] with 95% confidence intervals (CIs) as the outcome; (4) studies without restrictions by language of publication. Additionally, reviews, case‐control or cross‐sectional studies, and publications without adequate data were excluded.2.3The following data were extracted independently by two authors (ZT and F‐YW): first author, publication year, geographic location (country), study design, sample size, male ratio, mean or range of age among patients, diagnostic criteria of gout/ hyperuricemia and dementia, duration of follow‐up, outcome, adjustment, and study quality . The Newcastle‐Ottawa Scale (NOS) Stang,  was appl2.4Q and I2 statistic; I2 <50%, 50%∼75%, and > 75% indicated low, medium, and high homogeneity, respectively  from each study to evaluate the relationship between LOE and risk of dementia. Heterogeneity of HR or RR across articles was assessed using the Cochrane's 33.1As shown in Figure 3.2The details of the included studies were shown in Table 3.3I2 = 93%, p < .001).Pooled results showed that individuals presenting with gout or hyperuricemia had a high probability of reducing AD . Neither subgroup analysis by study design nor sample size could explain the origin of the higher heterogeneity. However, when using regional distribution as subgroup, the Asia studies showed lower heterogeneity  and Egger's test  did not reveal potential publication bias.On visual inspection, the funnel plot seemed to be asymmetrical Figure . However4In the current meta‐analysis, we comprehensively evaluated the association between gout/hyperuricemia and AD based on evidence from high‐quality cohort studies. Interestingly, the results showed a 31% AD risk reduction for gout or hyperuricemia. This indicated that gout or hyperuricemia might be a protective factor approach to prevent AD formation. Additionally, these relationships remained consistent across subgroup and sensitivity analyses.Although a previous meta‐analysis investigated the association between gout/hyperuricemia and dementia, the results suggested no statistically significant risk of all‐cause dementia in patients with gout or hyperuricemia  may be more helpful in exposing the cognitive effects of high uric acid (Euser et al., For the subgroup analysis, the source of heterogeneity may be related to regional distribution. Therefore, more studies from different regions are needed to clarify the connection of gout or hyperuricemia with risk of AD.Some limitations should be addressed. First, as mentioned above, there are the limited studies that examine the effect of gout or hyperuricemia on AD, thereby reducing the accuracy of the pooled estimates. Additionally, it is not possible to distinguish the different effects of gout on various types of dementia. Second, inconsistencies in the clinical diagnostic criteria for gout, hyperuricemia and AD across studies may affect the stability of outcomes. Third, previous studies have shown that the use of antigout preparations, with particular reference to benzbromarone, was negatively correlated with dementia (Taipale et al., In summary, our meta‐analysis suggested negative relationship of gout or hyperuricemia with risk of AD. This finding supports the protective effect of gout or hyperuricemia on cognitive function. More basic and clinical evidence from future studies needs to be clarified the cause‐and‐effect association between gout and AD.J‐CW were responsible for study design, overall planning, and project administration. LW and ZT contributed to the data curation. ZT, F‐YW, and W‐PW performed investigation, methodology, resources, and validation. LW and ZT drafted the original manuscript. ZT contributed to statistical analysis and interpreted the results. All authors have read and approved the submission.The authors declare no conflict of interest in this paper.https://publons.com/publon/10.1002/brb3.3207.The peer review history for this article is available at


In Hispanics, the pooled RR was 0.66 . In Asian Americans, the pooled RR was 0.55 . In American Indians, the pooled RR was 0.80 . Subgroup analysis by sex in Black people revealed the strength of association was greater in men  than in women . Our findings suggest that people of other races and ethnic groups have a lower fracture risk than white people.This systematic review and meta-analysis examined the association between race and ethnicity and fracture risk in the United States. We identified relevant studies by searching PubMed and EMBASE for studies published from the databases’ inception date to December 23, 2022. Only observational studies conducted in the US population that reported the effect size of racial-ethnic minority groups versus white people were included. Two investigators independently conducted literature searches, study selection, risk of bias assessment, and data abstraction; discrepancies were resolved by consensus or consultation of a third investigator. Twenty-five studies met the inclusion criteria, and the random-effects model was used to calculate the pooled effect size due to heterogeneity between the studies. Using white people as the reference group, we found that people of other races and ethnic groups had a significantly lower fracture risk. In Black people, the pooled relative risk (RR) was 0.46 , 0.43–0.48,  By 2025, the annual economic burden of osteoporotic fractures is expected to exceed $25 billion, and its annual aggregate incidence is expected to surpass 3 million2. In recent years, the prevalence of osteoporosis among US adults aged 50 and over was 12.6%, and the prevalence of osteopenia, which can often progress to osteoporosis, was 43.1%3. These affected populations, which constitute a major proportion of the US population, are especially vulnerable to osteoporotic fractures. Patients discharged after suffering such fractures are still at an increased risk of subsequent fractures, morbidity, and mortality6.As the population in the United States ages, osteoporotic fractures are becoming an increasing public health concern8. In white men and women, the incidence of hip fractures has decreased since 200010. However, a similar decrease was not observed in Black people, Asian Americans, Hispanics, and American Indians10. Such difference could be due to health disparities existing across these groups with regard to osteoporosis awareness, in addition to disparities in osteoporosis screening, diagnosis, and treatment13. Given the current trends in demographic changes, populations from racial-ethnic minority groups are expected to compose a majority of the population growth in the following decades14. Understanding the association between race and ethnicity and fracture risk is vital in preventing fracture and decreasing the burden on racial and ethnic minorities and the healthcare system.These fracture rates and related mortality vary by race and ethnicity17. Often, these adjustments tend to underestimate the needs of minority patients, which may delay necessary interventions and further exacerbate racial disparities in medical care17. In the setting of osteoporosis, extensive research into the relationship between race and ethnicity and fracture risk has been scarce. Previous literature reviews addressing the issue have demonstrated that race and ethnicity do play a role in the risk of fracture in minority groups19. However, such reviews did not provide quantitative evidence about the association between race and ethnicity and the risk of fractures. These reviews were published over a decade ago and were not able to include recent reports24. To our knowledge, there have not been any systematic reviews or meta-analyses conducted on this subject. In light of these considerations, this study aimed to quantitatively assess all available studies to investigate the association between race and ethnicity and the risk of fractures, which is vital to promoting race-based methodologies for effective osteoporosis prevention and treatment.Recent literature has questioned the use of race and ethnicity in medicine, especially in the context of clinical algorithms, whose outputs are adjusted based on a patient’s race or ethnicity43. However, two studies were conducted by the same research team and used the same data source but reported different outcomes34. These two studies were combined, and a final twenty-four studies were included in our meta-analysis. At this second stage, the inter-rater agreement was substantial (κ = 0.70).From the initial literature search, we identified 6971 articles, as well as an additional 5 through searching references of potentially relevant articles . The relative risk of fracture was 0.66  in Hispanics, 0.55  in Asian Americans, and 0.80  in American Indians.The RRs of fracture risk in different races and ethnic groups are presented in Fig p-values > 0.05.When different exclusion criteria were applied to the studies, with the exception of American Indians, the association between race and fracture risk changed slightly but remained significant. After applying various criteria, the RR ranged from 0.44 to 0.46 in Black people Table . In studp < 0.0001) had a higher risk of fracture than women  when compared with their white counterparts. The risk of fracture was greater in studies that reported vertebral fractures , were cohort in design , were published before 2011 , and were adjusted for BMD . However, these subgroup differences were not statistically significant due to overlapping confidence intervals within their own subgroups (Table 2 = 75%) was observed between the twenty-two studies. A sensitivity analysis was conducted by omitting one study in each analysis so as to determine its impact on heterogeneity. The study by Amir et al. was the single greatest contributor to the heterogeneity23. By removing this study, heterogeneity was reduced by 11% (I2 = 64%). The study methodology did not differ much compared to the other included studies, although it did contain the second-largest study population of all studies involving all races and ethnicities, and its population was composed strictly of individuals aged ≥ 65 in nursing homes. Regarding the pooled effect sizes, there were no major changes when each study was omitted one at a time.In Black people, subgroup analyses by sex showed men , studies published before 2011 , and studies that adjusted for BMD . However, these subgroup differences were not statistically significant due to overlapping confidence intervals within their own subgroups (Table p < 0.0001) and risks of hip fractures  did not statistically differ from the original association of Hispanic ethnicity with fractures . There was considerable heterogeneity (I2 = 99%) observed between the studies included in the analysis. Another “one-study removed” sensitivity analysis revealed that the removal of Sullivan et al. moderately reduced heterogeneity (I2 = 66%)10. The study’s methodology did not differ significantly from the other included studies. However, it was the only included study whose entire study population resides in California. The study only controlled for age, while the majority of the other studies controlled for additional variables. The omission of Sullivan et al. changed the pooled effect size because its removal resulted in the relative fracture risk in Hispanics increasing to 0.73 10.In Hispanics, subgroup analyses revealed the risk of fracture was greater in cross-sectional studies  and in studies published before 2011 . Nonetheless, these subgroup differences were not statistically significant due to overlapping 95% CIs within their own subgroups (Table p < 0.0001), were cohort studies , and were not adjusted for BMD  did not statistically differ from the original association of Asian race with fractures . A similar considerable heterogeneity (I2 = 99%) was observed in the pooled effect sizes analysis. A sensitivity analysis demonstrated that the removal of Sullivan et al. minimally reduced heterogeneity (I2 = 83%)10. The study’s omission increased the relative risk of fracture in Asian Americans to 0.61 . Similar to studies included in the Hispanics analysis, Sullivan et al. was the only study that reported populations limited to California and that only adjusted the effect sizes for age10.In Asian Americans, subgroup analyses showed the risk of fracture was higher in women . In the pooled effect size analysis, there was also considerable heterogeneity (I2 = 99%). As in the previous groups, a sensitivity analysis was performed and determined the removal of Sullivan et al. completely removed heterogeneity (I2 = 0%)10. By omitting the study, fracture risk increased to 1.05 . Differences in study methodology between Sullivan et al. and the other included studies are similar to those observed in the other analyses10.In American Indians, there were insufficient studies to properly conduct subgroup analyses by sex, anatomical site of the fracture, study design, year of publication, and adjustment for BMD Table . In addip = 0.42); however, publication bias was detected in Hispanics (p = 0.036).Funnel plots and the Egger tests were performed to assess publication bias for Black people and Hispanics. We could not examine publication bias for Asian Americans and American Indians due to an insufficient number of studies (< 10). The funnel plots Fig.  and EggeOur comprehensive meta-analysis of available observational studies examined the association between race and ethnicity and fracture risk. That analysis showed that people of racial-ethnic minority groups were at a lower fracture risk than white people. Compared with white people, the relative fracture risk decreased by 54% in Black people, 34% in Hispanics, 45% in Asian Americans, and 20% in American Indians.19. However, there have not yet been any published systematic reviews or meta-analyses, and thus no quantitative data on the association between race and ethnicity and the risk of fractures. In the present study, we performed meta-analyses for each race group and included subgroup analyses and sensitivity analyses to further examine the robustness of our findings. In addition, while previous reviews explored data from countries outside the US, we focused strictly on studies conducted in the US population. Moreover, the previous reviews were published nearly a decade ago and could not integrate findings from recently published extensive studies24.Our study findings are consistent with previous literature reviews regarding the risk of fractures in different races and ethnicities17. However, the current study cements the idea of race and ethnicity as a clinical risk factor for fractures, similar to any other risk factors. While this supports the use of race adjustments in FRAX USA, it is important to consider patient demographics and other clinical risk factors when discussing predictions of fractures. Together, these factors can help properly identify individuals at high risk of fractures, guide clinicians to treat the appropriate patients, and help close the osteoporosis treatment gap44. Although the underlying difference in risk factors between separate race groups is not yet fully understood, several risk factors have been heavily implicated in the risk of osteoporosis and fractures. While risk factors such as smoking, alcohol consumption, and Type 1 diabetes have been shown to increase the risk of fractures, low BMD continues to be one of the strongest predictors of future fractures47. In Black people, subgroup analysis by studies that controlled for BMD revealed the association between race and fracture risk continued to be significant even after adjusting for BMD. However, a similar conclusion cannot be made for the other races and ethnicities due to statistically insignificant results or a limited number of studies that adjusted for BMD. A fact is that for every standard deviation decrease in femur neck BMD (FNBMD), the risk of hip fractures increases by 294% in men and 288% in women at the age of 6548. Previous studies have continuously reported higher BMD in Black people in comparison with the other races and ethnicities24. Black people also exhibit a decreased age-adjusted annual decline in BMD49. The overall higher BMD at all sites and lower BMD loss as Black people age may help explain their significantly lower risk of fractures. Another explanation that may influence the measured difference between the risk of fractures in Black and white people is the difference in life expectancy at birth between the two races. In the US, Black people have a life expectancy at birth of 72 years, whereas white people have a life expectancy of 78 years50. As osteoporosis and resulting fractures are most common in the elderly population, with higher age groups at increasing risk, differences in life expectancy can influence the availability of Black participants in observational studies, thus, underestimating the rates and risks of fractures. Examining data from other countries with diverse but distinct racial and ethnic groups revealed similarities in the risks and rates of fractures between white and Black populations. For example, in South Africa, the African population was observed to possess the lowest incidence rates of fractures. The white population had the highest incidence rates, while the other races and ethnic groups were between white people and Africans51. These observed differences show similarity to the situation in the US. Consequently, the latest version of FRAX incorporated a South African-specific model in which race adjustments are performed in the tool’s output.The role that race plays in clinical decisions has been an increasing point of discussion in recent years. In the context of osteoporotic fractures, a recent study by Vyas et al. has questioned the use of race in FRAX USA’s calculation of the 10-year probability of fractures52. MrOS demonstrated FNBMD was 2% higher in Hispanic men than in white men53. Interestingly, several large studies have shown lumbar spine BMD (LSBMD) in Hispanics to be lower than in white people56. Unfortunately, we were unable to explore how this translates into vertebral fracture risks due to the limited number of studies reporting vertebral fractures in Hispanics. In American Indians, data regarding BMD measurements have been scarce. While our meta-analysis showed American Indians were at a decreased risk of fractures compared to white people, the wide confidence interval suggests no statistically significant difference in fracture risk between the two races. Data from the WHI study and the National Osteoporosis Risk Assessment study showed American Indian women possess similar BMD at various sites in comparison to white women57. In contrast to the relation between BMD and fracture risk observed in the other races, Asian Americans possess lower BMD than white people, yet are at a decreased risk of fractures. There have been various attempts to address this paradox. One explanation contributes to the lower risk of fractures in Asian Americans to their skeletal geometry, whereby Asian Americans tend to have a shorter hip axis length59. Since longer hip axis length has been associated with an increased risk of fractures, the shorter hip axis length in Asian Americans may confer protection against hip fractures61. Another explanation proposes studies that reported areal BMD (aBMD) did not adjust for weight, height, and other important covariates. An example of this was seen in the Study of Women’s Health Across the Nation. Compared with Black and white women, Asian American women seemed to possess the lowest unadjusted lumbar vertebrae and femoral neck aBMD62. However, after adjusting for weight and other covariates, aBMD was greater in Asian American women than in white women. Similarly, a study on men from four countries found that the aBMD gap between white people and Asians was significantly reduced after adjusting for height and weight54.In Hispanics, FNBMD measurements are higher than in white people but lower than in Black people. In NHANES 2005–2006, FNBMD was 6.6% greater in Mexican American women than in white women, while FNBMD in Black women was 10% greater than in white women35. Furthermore, other well-established risk factors for fractures known to differ between races and ethnicities, such as volumetric BMD (vBMD) or failure load, have not been included as a confounder in the included studies’ analyses64. There are also socio-demographic and socioeconomic determinants of fracture risks, such as education and income. For example, an inverse relationship between fracture risk and income was observed in Medicare beneficiaries65. In our included studies, only 4 of 22 studies adjusted for education, and only one adjusted for family income37. These clinical, socio-demographic, and socioeconomic factors all play an important role in the risks of fractures. They should be considered when discussing the fracture risks between races and ethnicities. Future studies should explore these factors further in-depth to help explain the observed variations in risks and rates of fracture among different races and ethnicities.Although these factors could help explain the racial and ethnic differences in fracture risks, it must be noted that many of these factors, such as aBMD, were not adjusted in the analyses of the included studies. As seen from the subgroup analyses, most included studies did not adjust for BMD. Only 3 of 21 studies in Black people and 2 of 11 studies in Hispanics adjusted for BMD, while no studies in Asian Americans and American Indians adjusted for BMD14. Thus, the significance of proper bone health should not be neglected for all population groups. Healthcare disparities exist in all stages of care, from screening to post-fracture outcomes. In studies of Black women, they were less likely than their white counterparts to be referred for dual-energy x-ray absorptiometry (DXA) screening, to know their DXA results, and to be properly prescribed osteoporosis medication67. In a large study of Medicare patients with hip fractures, Black and Hispanic women were 48% and 34%, respectively, less likely than white women to have undergone bone testing prior to their fractures68. However, data regarding screening rates in races and ethnicities other than Black have been scarce and mixed, making it harder to draw conclusions69, which demonstrates the need for more research on the disparities in the screening and treatment of minority groups. With regards to post-fracture care, outcomes similarly differ by race and ethnicity. After suffering common osteoporotic fractures, such as hip or vertebral fractures, the risk of mortality is not the same in every race. In a study of US Medicare data from 2010 to 2016, Black women suffered greater rates of mortality, frailty, and poverty after a fracture when compared to white women70. In another large study of three cohorts, white people were 1.74 more likely to survive six months post-fracture than other races and ethnic groups, including Black people and Hispanics7. The reasons for these discrepancies are not yet fully understood. The current research adds to the pool of knowledge that physicians and other healthcare providers can use when assessing fracture risk in patients of different races. Our research is, to our knowledge, the first study that provides quantitative evidence regarding the association between race and ethnicity and the risk of fractures. However, as evidenced by the discrepancy in the number of studies that reported results for Black people and other races and ethnicities, there is an obvious need for more research into Hispanics, Asian Americans, and American Indians. In addition to including more participants of these races and ethnicities, future research should also attempt to adjust for both age and BMD, as these are important risk factors for developing osteoporosis and subsequent fractures. Lastly, there is an urgent need for more research into sociological factors influencing socioeconomic and socio-demographic characteristics of different racial and ethnic minority groups and how these interplay with the risk of osteoporosis and osteoporotic fractures, which is essential in reducing the observed healthcare disparities across different racial and ethnic groups.While our findings suggest that a focus should be placed on white people and perhaps American Indians, it is crucial to understand that the number of fractures and associated costs is expected to balloon over the coming years due to shifting demographics in the US. While this can be attributed to an overall aging population, we must also consider that population growth in minority races exceeds that of white peopleI2. When the number of studies pooled together is small, there is a tendency for I2 to introduce significant bias71, which may partially explain the heterogeneity observed in the Hispanic, Asian American, and American Indian analyses (I2 = 99%). Another explanation of heterogeneity may be pooling cross-sectional studies with other study designs. Although cross-sectional studies are less expensive and more convenient to perform than case-control or cohort studies, they are often more susceptible to bias, such as non-response and recall bias72. Subgroup analyses by study design were performed to ensure the pooling of different study designs did not significantly influence our findings. In the subgroup analyses by study design for Black people and Hispanics, no significant differences in effect sizes were observed when comparing cross-sectional and cohort studies. In Asian Americans and American Indians, subgroup analyses were not performed due to the limited studies available. Another explanation could be due to the inherent nature of pooling observational studies. Oftentimes in such meta-analyses, it is difficult to control for the baseline characteristics of participants across the included studies, especially given the number of variables that can influence the risk of osteoporotic fractures. Second, our meta-analyses pooled several measures of effect sizes together . As previously mentioned, OR is often interpreted as broadly equivalent to RR due to the rare nature of fractures24. In contrast, HR differs from RR because it considers the timing of the outcome. Nonetheless, HR has been deemed broadly equivalent to RR, and pooling the two is common in meta-analysis research76. To ensure the addition of HR did not affect our results, we performed a sensitivity analysis by including only studies that reported effect sizes using HR. In analyses where sufficient studies were available, the exclusion of RR/OR did not considerably affect our findings, which remained significant. Third, it is important to consider socio-demographic, socioeconomic, and other clinical risk factors when discussing fracture risks in different races and ethnicities. In our meta-analysis, most included studies did not account for many of these established confounders known to influence fracture risks. Finally, our research focused on race and ethnic groups within the US only and thus may not be generalizable to other countries. Furthermore, it should also be taken into consideration that race and ethnic groups in the US are comprised of individuals with ancestry from different countries with varying fracture rates. This may translate into differing risks of fractures for individuals within the same race and ethnic group and is why patient demographics and other clinical risk factors, along with race and ethnicity should be considered when identifying patients at high risk of fractures.Our study has several limitations. First, there was substantial to considerable heterogeneity in all of the analyses. In three of four analyses, it may be possible to attribute this to the nature of Our study showed that people of other races and ethnicities in the US are at a lower risk of fracture than white people. This decrease in risk was most significant in Black people and least significant in American Indians; a moderate decrease in risk was observed in Hispanics and Asian Americans. Our findings add to the tools available for healthcare providers who screen, diagnose, and treat men and women at risk of fractures. The work we have done provides quantitative data regarding fracture risk across different racial and ethnic groups, which along with patients’ clinical information, helps identify those who would benefit most from the initiation of osteoporosis treatment and help close the osteoporosis treatment gap. Our work also demonstrates the need for further research into fracture risks and their contributors. There are substantial gaps in osteoporosis research, especially in Hispanic, Asian American, and American Indian populations, and the currently available research clearly demonstrates the presence of healthcare disparities in minority populations.78. The protocol of this review was prospectively registered on PROSPERO (CRD42021239943).This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelinesA comprehensive search of PubMed and EMBASE electronic databases was performed to include studies from the databases’ date of inception to October 20, 2021. An updated literature search was conducted on December 23, 2022. The search strategy for each database is reported in Supplemental Table The following search terms were used to identify studies: “fractures,” “blacks,” “African American,” “whites,” “Caucasian,” “Hispanic,” “Latino,” “Asian,” “Native American,” “American Indian,” “Alaska Native,” “Pacific Islander,” “Native Hawaiian.”In the initial study selection stage, investigators Y.B. and Z.L. independently screened each article’s title and abstract from the electronic literature search for studies that investigated the association between race and ethnicity and the risk of fractures. The following criteria were used to screen for relevance: (1) the study population was limited to the US, (2) the study reported the effect size of racial-ethnic minority groups using white people as the reference group, and (3) the study reported fractures as the outcome. We defined fractures as those occurring in any site. However, fractures attributed to major trauma were excluded. Citations deemed irrelevant by both investigators were excluded, and articles with disagreements at the screening were included for a full review in the second study selection stage. There are no clinical trial studies that meet the inclusion criteria.In the second study selection stage, the full text of each article obtained during the initial study selection stage was reviewed and evaluated for inclusion. Studies had to be cohort, cross-sectional, or case-control in design, had to report outcomes using odds ratio (OR), relative risk (RR), or hazard ratio (HR), and had to include the corresponding 95% confidence intervals (CI). Studies were also included if the effect sizes were calculable from the provided data. Disagreements between investigators were resolved through discussion, and if necessary, a third investigator (Y.X.) was consulted. Agreement between investigators was evaluated using the κ statistic, a robust measure of inter-rater reliability.79. For cross-sectional studies, a modified NOS was used. In accordance with MOOSE guidelines, quality scores were not used as weights in the analyses. Instead, they were used in the sensitivity analysis, where studies with low scores were excluded. A study was considered high-quality if it scored ≥ 7 on the NOS, while a low-quality study scored < 7.Investigators Y.B. and Z.L. performed data extraction independently. The following information was extracted from each study: study characteristics , participants’ characteristics , outcomes and ascertainment of outcomes, and risk estimates . For cases of missing or unclear data, study authors were contacted for clarification and/or additional data. In our systematic review and meta-analysis, we refer to the biological sex when referring to men and women. Race and ethnicity are in accordance with the United States Census Bureau, whereby white people, Black people, Asian Americans, and American Indians are race categories and Hispanic ethnicity. The methodological quality of both the case-control and cohort studies was assessed using the Newcastle-Ottawa Scale (NOS)80. When determining the weights of the studies, the inverse-variance method was used.In our meta-analysis, RR was used to measure the association between race and ethnicity and the risk of fracture. We calculated the pooled effect size using OR, RR, and HR and the 95% CIs reported by the included studies. Due to the occurrence of fractures being rare, we approximated ORs as RRsI2 index, which measures how much of the variability in the effects is due to heterogeneity instead of chance alone81. We interpreted I2 < 40% as minimal heterogeneity, 30–60% as moderate heterogeneity, 50–90% as substantial heterogeneity, and > 75% as considerable heterogeneity83. In light of the heterogeneity, the DerSimonian and Laird random-effects model was used to pool the overall effect sizes84.Between-study heterogeneity was measured using the Higgins Sensitivity analyses were performed to assess the robustness of our findings. We examined the influence of race and ethnicity by fracture definition, adjustment for age and other fracture risk factors, stratification by age (age ≥ 65 vs. < 65), methodological quality score, and type of effect size. Pre-specific subgroup analyses were also conducted to determine if study demographics influenced the effects of race and ethnicity on the risk of fractures. The subgroup analysis variables were sex (men vs. women), anatomical site of fracture (hip vs. vertebrae), study design , year of publication (pre-2011 vs. post-2011), and adjustment for BMD.85. The Egger’s test was also conducted to help assess the presence of publication bias in the funnel plots86. For races and ethnicities with less than ten studies, a funnel plot was not performed because its ability to detect publication bias through asymmetry is too unreliable88.Potential publication bias was examined by constructing a funnel plot that plotted RRs against their standard errorsp-value of 0.05 or less was considered to be statistically significant.All data analyses were conducted using the R statistical software . A Supplementary Information.


There are many studies on the association of tea and its extracts with colorectal adenomas, but the results have varied. The study aims to investigate the effect of tea and its extracts on colorectal adenomas using meta analysis and systematic review.2I statistics and Q test. The effect measures were odds ratio (OR) and 95% confidence interval (95% CI). Stata17.0 software was used for data processing.Literature was obtained through PubMed, Cochrane Library, Embase and Chinese BioMedical Literature Service System since the establishment of the database until April 31, 2023. Search terms include adenomas, polyps, colorectal, rectal, rectum, tea, epigallocatechin, drinking and beverages. Meta-regression analysis was used to infer the source of heterogeneity. Heterogeneity was assessed using t = 0.78, P = 0.454), types of tea intake , occurrences , regions  and grades of adenomas  were statistical homogeneity. Tea and its extracts were negatively correlated with the risk of colorectal adenomas . No publication bias was found in this study  and the results are robust.The findings indicated that study design (This study suggests that tea and its extracts have a certain protective effect on colorectal adenomas, which provides scientific evidence for preventive strategies for colorectal adenomas. As for the causal relationship between tea and its extracts on colorectal adenomas, further prospective studies are needed. AccordiSome studies have found that the development of CRC mostly follows the evolutionary pathway of “adenoma-cancer,” that is, normal mucosa first appears with epithelial hyperplasia-like changes, then can gradually transform into an adenoma, and later can develop into carcinoma in situ and invasive carcinoma, and it generally takes 5–10 years to progress from precancerous lesions to cancer, this provides an important time window for early diagnosis and clinical intervention . TherefoTea is rich in polyphenolic compounds, with catechins as the main component. Studies have shown that catechins have a variety of pharmacological properties, including antioxidant, anti-inflammatory, anti-cancer effects, and so on . In the There are few studies investigating the relationship between tea and the risk of colorectal adenomas. Some studies have found that tea has a negative correlation with the risk of colorectal adenomas and helps reduce the incidence of CRC , 15. How2.2.1.The systematic review and meta-analysis were performed according to the Cochrane Handbook for Systematic Reviews of Interventions  and the Research terms (adenomas OR polyps) AND  AND  were used. The details of research strategy were provided in 2.2.Inclusion criteria were as follows: (1) literature investigating the relationship between tea and its extracts with colorectal adenomas, (2) cohort studies, case–control studies, cross-sectional studies, or randomized controlled trials (RCTs), (3) studies reporting the definition of colorectal adenomas and the methods of diagnosis, and (4) literature reporting the sample size of the study, or which could be derived from the original data.Reports as follows were excluded: (1) literature with repeated reports on the same population, (2) case reports, reviews, letters or comments, (3) animal or cell trials, and (4) literature with incomplete data or where sample sizes for each study result could not be derived from the literature.2.3.Two authors screened the literature independently, extracted information using a uniform data extraction form and cross-checked. In case of disagreement, it was discussed or referred to a third-party evaluation for resolution. Potentially eligible studies were selected by abstracting the title or abstract. If the title or the abstract was inadequate to reach a final decision, the full paper was obtained. Data extraction included: the first author’s name, published year, country, study design, sex ratio, age, cases, sample size, odds ratio (OR) and its 95% confidence interval (95% CI) after adjusting for the most covariates, and adjusted confounders. The Newcastle-Ottawa scale was used to assess the quality and risk of bias of observational studies , and stu2.4.Q test and the 2I statistic  with corresponding 95% CI to test the association between tea and its extracts on the risk of colorectal adenomas. Heterogeneity between studies was assessed using Cochran’s tatistic , 26. Hetr’s test . SensitiP-value ≤0.05 with the two-sided test.All statistical analyzes were performed by STATA software . The differences were considered to be statistically significant at 3.3.1.The literature screening process was shown in The basic characteristics of the included studies were shown in 3.2.2I = 60.3%, P = 0.003), so a random-effect model was used for the analysis. The results indicated that tea and its extracts could reduce the risk of colorectal adenomas .The results of the overall meta-analysis were presented in 3.3.Meta-regression analysis was conducted according to two study design types, observational studies and clinical trials, two types of tea intake, green and black tea, two occurrences, incidence and recurrence, three regions, East Asia, North America, and Europe, and two grades of adenomas, low and high. The results were presented in The results of the subgroup analysis were presented in 3.4.t = −0.22, P = 0.828). The results of sensitivity analysis showed no impact of excluding any single study on the overall estimate of the effect of tea and its extracts on the risk of colorectal adenomas, indicating that the analysis was robust , with a larger proportion of RCT studies and cohort studies, and a higher level of confidence in the results of the analysis. Besides, we performed relatively comprehensive analyzes including meta-regression analysis, subgroup analysis, publication bias detection, and sensitivity analysis to explore potential sources of heterogeneity and bias.The strength of this study is that we enrolled all relevant studies (However, our study still has several limitations. Firstly, the number of enrolled studies was limited, so the number of literature on the subgroup analysis groups was fewer, and their results may be unstable. Secondly, there is the issue of measurement error, which may result in bias in the calculation of estimated effects and the judgment of confounding factors due to different methods of measuring the dosage of tea and its extracts included in the study. Finally, because tea is mainly prevalent in Asia, the relatively large sample size of Asians in this study leads to a potential selection bias, caution should be exercised when extrapolating the results of this study to other countries. More studies are needed to confirm the preventive effect of tea on the risk of colorectal adenomas, especially for populations of different genders in different regions.5.The result from the meta-analysis of 12 studies indicates that tea and its extract supplements have a protective effect against colorectal adenomas. Subgroup analyzes show that the protective effects of tea and its extracts against colorectal adenomas are more pronounced in green tea, East Asian populations, and low-risk adenomas, but the number of literature on the subgroup analysis groups was fewer, which needs to be determined by more evidence. The findings may provide a theoretical basis for the development of nutrition guidelines. As for the causal relationship between tea and its extracts on colorectal adenomas, further prospective studies are needed.XL, DX, and XG conceived and designed the meta-analysis. XG, NL, ZZ, and YX searched the literature. XG, NL, and ZZ extracted the data. XG analyzed the data. ZZ contributed analysis tools. XG and NL wrote the manuscript. XL revised the manuscript. All authors contributed to the article and approved the submitted version.


Emerging evidence have suggested a potential relationship between hysterectomy and risk of kidney cancer with inconsistent results. We aimed to investigate the association of hysterectomy with kidney cancer risk based on a meta-analysis of all available cohort studies.A comprehensive literature search was performed in the PubMed and Embase database, covering all the papers published by September 2022. The pooled relative risks (RRs) and 95% confidence intervals (CIs) were estimated using a DerSimonian and Laird random effects model.P = 0.206 for heterogeneity; I2 = 25.9%).Overall, our meta-analysis included 10 cohorts from 9 studies with approximately 240 million participants. The pooled RR with its 95% CI showed a significantly positive association between hysterectomy and risk of kidney cancer . No obvious heterogeneity was observed across the studies (Findings from this meta-analysis of cohort studies indicated that hysterectomy was positively associated with subsequent kidney cancer risk. Further large prospective studies with long-term follow-up are warranted to verify these findings. Kidney cancer develops from the renal parenchyma, which ranks seventh among the most frequently diagnosed cancers in men and ninth in women . AccordiEstablished risk factors for kidney cancer include tobacco smoking, body size, history of hypertension and chronic kidney disease , 8. The We conducted a comprehensive literature search in the PubMed and Embase database, covering all the papers published from their inception to September 2022. The search strategy was used as follows: (hysterectomy or reproductive factors) and  and (cancer or carcinoma) and (cohort or prospective). We also examined the cited references from retrieved articles and reviews to identify additional relevant studies. This systematic review and meta-analysis was planned, performed, and reported according to the PRISMA guidelines of quality for reporting meta-analyses , 17.Studies included in this meta-analysis met all of the following criteria: (a) one of the exposures of interest was hysterectomy history; (b) one of the outcomes of interest was kidney cancer incidence; (c) they had a cohort or prospective design; and (d) studies provided the rate ratios (RRs) or hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs) or data to calculate them. Exclusion criteria: review or editorial paper; non-human studies; studies based on same population; cancer mortality as the outcome; and the exposure not including hysterectomy.Two authors (YL and LY) independently extracted the data using a predefined extraction form with disagreements resolved by consensus. The following characteristics were collected from each study: the first author’s name, year of publication, the country in which the study was performed, cohort name, cohort size, kidney cancer cases, average participants’ age, follow-up time, methods of ascertainment of hysterectomy and kidney cancer, risk estimates with their 95% CIs, and adjusted covariates in the data analysis. For each study, we extracted the most-fully adjusted risk estimate.The same two authors (YL and LY) independently completed the quality assessment using the Newcastle-Ottawa Scale (NOS) , which wQ statistic and the I2 score . Galbraith plot analysis was further used to detect potential sources of heterogeneity. A number of stratified analyses were performed according to publishing year (before 2010 versus 2010 and thereafter), geographical region (Europe vs. United States), number of cases (> 500 vs. ≤ 500), number of participants , and duration of follow-up (> 15 years vs. ≤ 15 years). A sensitivity analysis was performed by repeating the meta-analysis after ruling out of each included study in turn. Potential publication bias was assessed by Begg’s test , Europe (n = 3), and Australia (n = 1). A total of approximately 240 million participants with 4752 cases were included in these studies. These cohort studies were published between 1997 and 2022, of which three large cohorts , 27, 28 P = 0.206 for heterogeneity; I2 = 25.9%).The overall RR with its 95% CI showed a statistically significant positive association between hysterectomy and kidney cancer risk (P for interaction > 0.05).A significant association between hysterectomy and risk of kidney cancer was observed in most subgroups based on geographical region, publication year, duration of follow-up, number of participants and number of cases, except for studies published before 2010 Table 2.2 of from 25.9% (P = 0.206) to 0.0% (P = 0.636), while the association maintained significant . There was some degree of publication bias with Egger’s test (P = 0.017), whereas no evidence of publication bias was identified from Begg’s test (P = 0.152, We performed two types of sensitivity analyses. First, the impact of each study on the summary RR was evaluated by repeating the meta-analysis after omitting one study at a time. The exclusion of any single study did not substantially alter the pooled RR Figure 3The findings from this meta-analysis of cohort studies indicated that hysterectomy was significantly associated with a 30% higher risk of kidney cancer, and the result was robust with no obvious heterogeneity observed across the included studies. Sensitivity analyses also showed similar results.The results of our study were consistent with a previous meta-analysis published in 2014 , which aPrevious studies which reported a positive association between hysterectomy and kidney cancer risk have been criticized for the issue of detection bias. Detection bias may partially explain the positive results since women with a history of hysterectomy may seek medical care and exanimation more actively than those without, and thus had a higher chance to be detected with kidney cancer. However, detection bias may contribute to a higher short-term cancer incidence relative to the surgical procedure, but this may not still come into play decades after the surgery. In fact, this association did not change substantially in studies which performed subgroup analyses according to the time since hysterectomy or age at hysterectomy , 27.It remains unclear what biological mechanisms would mediate the association between hysterectomy and kidney cancer risk. Hysterectomy may cause renal damage or pelvic anatomy changes. A high incidence of post-renal obstruction following hysterectomy has been reported in previous studies. Hydronephrosis could appear after hysterectomy even without any obvious intraoperative ureteral injury , 30, 31.This study had several limitations. First, the confounding bias that was inherent in the included studies cannot be excluded. Inadequate control or adjustment for confounders may bias the results in either direction, leading to underestimation or overestimation of the risk estimates . Second,Nevertheless, this study had some strengths. First, a total of approximately 240 million participants were included in this meta-analysis, which provided sufficient statistical power to evaluate the impact, if any, of hysterectomy on kidney cancer risk. Second, only cohort studies were included in this meta-analysis, which, to some extent, avoided the selection and recall bias typically existing in case-control studies. Lastly, no significant heterogeneity was found across the included studies, which indicated our findings were relatively robust.In summary, findings from this meta-analysis of cohort studies indicated that hysterectomy was positively associated with the risk of kidney cancer. Future large prospective studies with long term follow-ups are warranted to verify these findings, and the potential underlying molecular mechanism that links hysterectomy and kidney cancer incidence needs further exploration.The original contributions presented in the study are included in the article/LY: project development, data collection and analysis, manuscript writing and editing. PY: data collection and analysis, manuscript writing. YL: project development, manuscript editing, and project supervising.


There is very little epidemiological evidence on the effects of ambient air pollution on brain tumor risk. The purpose of this study was to determine the relationship between exposure to air pollution and the incidence of brain tumors.A comprehensive literature search in five international databases, including PubMed/Medline, ProQuest, Scopus, Embase, and ISI/WOS on April 15, 2019, was conducted. The methodology of the present study was based on the PRISMA  statement. The Newcastle-Ottawa Quality Assessment Form was used to evaluate the quality of the selected papers.2.5 absorbance, and proximity to traffic (Trafnear) were reviewed. The results showed that the pooled relative risk (RR) for incidence of brain tumor and long term exposure to Trafnear, PM2.5, PM2.5 absorbance, O3 and NOx were RR = 1.07, (95% CI 0.99–1.16), P = 0.079, for Trafnear; RR = 0.90, (95% CI 0.80–1.00), P = 0.064 for PM2.5; RR = 1.63, (95% CI 1.04–2.55), P = 0.031 for PM2.5 absorbance; RR = 1.3, (95% CI 1.03–1.6), P = 0.023 for O3; and RR = 1.16, (95% CI 0.93–1.45), P = 0.173 for NOx. Exposure to other air pollutants had no statistically significant association with brain tumor incidence.Five studies that measured adult brain tumors as well as their long-term exposure to at least one of the pollutants criteria for air pollution, PM3 and PM2.5 absorbance, had the highest correlation with brain tumor incidence. They also showed an absence of correlation between exposure to certain pollutants  and brain tumor incidence.The results showed that exposure to air pollutants, such as O Nervous system cancers account for about 3% of all cancers in the world and are more common among men than women 23. In ge2n cities . The prin cities 89.Nowadays, air pollution is a severe difficulty in numerous parts of the world and is acknowledged as one of the most hazardous environmental concerns 11. Expos12131416183 can reach the brain through inhalation or directly through the nose and the olfactory nerve, causing inflammation and destruction of nerve tissue [Outdoor air pollution caused more than 3.2 million premature deaths globally . Combust16e tissue . While se tissue . The leve tissue .Inflammation has been suggested to be very important in the pathogenesis of brain cancer. Also, genetic damage was observed in mice exposed to airborne particles that led to brain cancer . StudiesIn this study, we aimed to examine the effects of air pollution criteria exposure in urban regions on the incidence of the central nervous system (CNS) cancer utilizing scientific proof, by reviewing prior studies through a systematic review and meta-analysis.The present study is a systematic review and meta-analysis of the relationship between exposure to air pollution and the incidence of brain tumors. This study was designed in 2019, and it is consistent with the PRISMA  checklist .2.5, PM10 Coarse particles, Ozone (O3), Sulfur Dioxide (SO2) Nitrogen dioxide (NO2), Carbon Monoxide (CO), NOx, Trafnear and Brain Neoplasms were searched by researchers on April 15, 2019. All searches were entered into EndNote X7 software, and duplicate articles were automatically deleted. Two researchers examined the papers individually. There was no time period limit in the quest for studies.Five international databases including Medline/PubMed, ProQuest, Scopus, Embase, ISI/WOS with combinations of keyword including PM10), less than 2.5 µm (PM2.5), or between 2.5 and 10 microns (PM2.5–10), nitrogen oxides (NOx) or nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), Trafnear and carbon monoxide (CO2); 2) the examined population included adults with brain cancer; and, 3) all studies were written in english. It is necessary to clarify that the references of the articles were also reviewed in order to add relevant studies.The studies that were considered, were as follows: 1) all cohort or longitudinal studies that address all or one of the benchmark pollutants including particles less than 10 µm in diameter (PMExclusion criteria included: (1) studies examining the exposure of these pollutants to animals; (2) studies that have examined exposure to tobacco smoke such as cigarette smoke; (3) occupational exposure studies; (4) studies for which there was no access to the full text even after the researchers’ follow-up (contacting authors by email).The Newcastle-Ottawa Quality Assessment Form was used to evaluate the quality of the selected papers. This tool has three different parts including selection (four questions), comparability (one question) and outcome (three questions); and based on the final scores divided into three categories, good , fair  and poor   The resuThe initial search was conducted by two researchers (SH and HAN). Screening studies, extraction of results, and evaluation of the quality control of articles were performed individually (AB and HAN).In case of any disagreement, the team leader (SH) would make a final comment on the article.2 statistics (with a significance level greater than 50%). In the case of heterogeneity, the random-effect model was used with the inverse variance method, and in cases without heterogeneity, the fixed-effect model was employed. Because of the different indices published in the studies, the converted indices obtained by CMA software were used. The index used in this study was the risk ratio (RR). If the RR is 1 (or close to 1), it implies no difference or little difference in risk . RR greater than one suggests an increased risk of the outcome in the exposed group. RR lesser than one suggests a reduced risk in the exposed group. Sub group analysis was conducted based on years of follow up (less than 10 years versus more than 10 years). Due to the high heterogeneity in the results of meta-analysis, power analysis was used to estimate the power of effect sizes. All analyzes were performed using CMA statistical software version 2.The heterogeneity amongst the included studies was assessed by the cochran test (with a significance level of less than 0.1) and its combination using IAfter searching the databases, 313 articles were found. After eliminating duplicates, 273 articles entered the title and abstract review phase. The titles and abstracts of the studies were reviewed, and 17 articles were entered into the next phase, in which the full text of the articles was reviewed, and five articles were entered into the final analysis. During the screening stage of the studies, studies could have been excluded for multiple reasons, including unrelated subject matter  and an uThe articles in our analysis included 3.779 million people from 7 countries around the world, including Sweden, Norway, Netherland, Austria, Denmark, the USA, and Italy. The results of the fourteen cohorts were used in this meta-analysis. The characteristics of the included studies are listed in The results of the quality evaluation of the articles are shown in appendix I. According to our review using relevant checklists, all of the five studies were of good quality.Egger test and funnel plots were used to investigate the publication bias in the results. The results of the publication bias of the study indicated the absence of bias in the examined results (p = 0.461) According to the results, there was no high heterogeneity in most selected studies. Random effect model was used with the inverse variance method for our results.2 = 59.69 %, P = 0.008).The results of the meta-analysis are shown based on the type of air pollution index. Five studies for use were identified in our meta-analysis. All studies were of good quality, as assessed by our modified quality assessment checklist. The sample size in the analyzed articles was 3.779 million people from 14 cohorts study. As observed in 2 = 0.0 %, P = 0.748).According to 3 index and brain tumor incidence .The results displayed in 2.5 Absorbance index and the incidence of brain tumors .The results displayed in 2 index and brain tumor incidence .Based on the results displayed in supplementary 1, there was no significant relationship between SO2 = 87.71 %, P = 0.004).According to the results, displayed in supplementary 2, no significant relationship was found between CO index and brain tumor incidence .As observed in supplementary 3, no significant relationship was found between NO10 index and brain tumor incidence .According to the results supplementary 4, no significant relationship was observed between PM2.5 index and brain tumor incidence. .Results, displayed in supplementary 5, showed no significant relationship between the PMThe result of sub-group analysis based on years of follow up (less than 10 years versus more than 10 years) show that in According to the results of power analysis, due to the large sample size among included studies, the values of power (1-β error probability) are close to one in all air pollution types. The results of power analysis presented in 2, CO, NO2, PM10, O3, and PM2.5 Absorbance, NOx, Trafnear, and PM2.5) and brain tumors were reviewed. The results revealed that there was a relationship between exposure to NOx index  and brain tumor incidence (supplementary 1–5).In this study, the relationship between short and long term exposure to standard pollutants  and tumor necrosis factor (TNF-ɑ), that can cross the blood-brain barrier may lead to activation of microglia [3 has been associated with cumulative rodent brain injury, and its inhalation appears to disrupt dopamine neurons in mice [The results of our meta-analysis clarified that there was a statistically significant correlation between exposure to Oorbance,  and 5, aolecules 36. Inhalicroglia . These a in mice 38.2.5 absorbance indicates black carbon aerosol due to incomplete combustion of fossil fuels in motor vehicles, especially in areas near traffic, and usually refers to elemental carbon in particulate matter PM2.5 [23PMer PM2.5 39.These er PM2.5 . There aer PM2.5 2341. The PM2.5 23.2.5 can cause brain-blood barrier disturbance by causing oxidative stress and neuritis. In a study reporting long-term exposure to PM2.5 and its association with stroke, the results manifested that increased exposure to this pollutant heightened the risk of stroke , and mortality caused by stroke  [2.5 and its impact on the risks of stroke and observed that short and long term exposure was associated with increased risk and mortality from stroke [According to the results of previous studies, PM01–1.51) . Additiom stroke .Experiments on animals have revealed that inhaled particles penetrate the olfactory bulb and reach the brain through the nasal cavity and specific pathways. NOx can damage neurons through the bulb or the olfactory bulb, the nasal epithelium, and the lungs by propagating, trapping, and transporting red blood cells throughout the cerebral-blood barrier pathway. NOx and cytokines released by pulmonary inflammation activate microglia, thereby provoking neuronal nitric oxide synthesis 45.The McKean-Cowdin et al. cohort study showed that there was no association between increased risk of brain cancer mortality and exposure to conventional air pollutants. However, with increased exposure to sulfur dioxide, nitrogen dioxide, and carbon monoxide, there was an unforeseen risk reduction for the group. Relative risks (RR) were obtained by increasing ten ppb concentrations of sulfur dioxide or nitrogen dioxide or by increasing one ppb concentration of carbon monoxide .10, PM2.5) have not been chemically and biologically studied.In the present work, the design of the studies was mainly cohort. This, of course, adds to the richness of this study, but there are weaknesses, such as the limited number of studies, which are mostly related to developed and developing countries. In these articles, the most significant people with exposure to standard pollutants have been studied, but the structure and constituents of airborne particulate matter (PM2.5 absorbance, proximity to traffic and NOx incidence index had the most relevant impact. The effects of ozone and PM2.5 absorbance were similarly statistically significant. However, no association was detected between other air pollutants and brain tumor incidence.The results of this systematic review and meta-analysis, which is based on long-term exposure to ambient air pollution in adults and the incidence of a brain tumor, explicated that exposure to ozone, PMThe additional files for this article can be found as follows:10.5334/aogh.3889.s1Supplementary File 1.Appendix 1- Quality Assessment of included studies.10.5334/aogh.3889.s2Supplementary File 2.Supplementary figures 1 to 5.


Alzheimer's disease (AD) is an irreversible, progressive brain disorder that impairs memory, thinking, language, and, eventually, the ability to carry out the simplest of tasks. Tau protein, the major component of neurofibrillary tangles, is considered a key mediator of AD pathogenesis. The association between obstructive sleep apnea (OSA) and circulating tau remains unclear. The aim of the present meta‐analysis was to evaluate the relationship between OSA and circulating tau via quantitative analysis.A systematic search of Pubmed, Embase, and Web of Science were performed. The mean values of circulating total tau (T‐tau) and phosphorylated tau (P‐tau) in OSA and control groups were extracted. Standardized mean difference (SMD) with 95% confidence interval (CI) was calculated by using a random‐effect model or fixed‐effect model.z = 3.56, p < .001). OSA patients also had significantly higher circulating P‐tau level than control group .A total of seven studies comprising 233 controls and 306 OSA patients were included in this study. The meta‐analysis showed that the circulating T‐tau level was significantly higher in OSA patients than those in the control group (SMD = 1.319, 95% CI = 0.594 to 2.044, The present meta‐analysis demonstrated that both circulating T‐tau and P‐tau levels were significantly increased in OSA subjects when compared with non‐OSA subjects. Larger sample‐size studies on the association between OSA and circulating tau are still required to further validate our results. The present meta‐analysis demonstrated that circulating tau level was significantly increased in OSA subjects when compared with non‐OSA subjects. These episodes are associated with intermittent hypoxia and sleep fragmentation, both of which can raise systematic inflammation, oxidative stress, and sympathetic activity. The prevalence of OSA increases with age and ranges 30%–80% in elderly subjects  guidelines  All participants included in the study were adults with age ≥ 18 years; (2) the diagnosis of OSA was according to polysomnography with apnea‐hypopnea index (AHI) ≥ 5; (3) OSA subjects were newly diagnosed and did not receive any form of treatment; (4) circulating tau levels were reported both in OSA and control group. Exclusion criteria were: case reports, reviews, letters, editorials, conference articles, animal studies, duplicate publications, and those with insufficient data. If the essential data were not reported in the study, the authors were contacted via email. If there was no response following two communication attempts, the article was ruled out. When a disagreement about the inclusion of a study occurred, a third reviewer engaged.2.3The following data were extracted using a standardized form by two authors independently: first author, publication year, region of study, study design, sample size, OSA diagnosis method, time of blood sampling, population characteristics, sample type, and the mean value of total tau (T‐tau) and phosphorylated tau (P‐tau). The study quality was evaluated using the Newcastle–Ottawa Scale  and 95% confidence interval (CI) were used to evaluate the differences in circulating tau levels between OSA and control groups. The heterogeneity of the included studies was assessed by the chi‐squared test and I33.1A PRISMA flow diagram of the study selection process is presented in Figure 3.2A total of seven studies comprising 233 controls and 306 OSA patients were included in the meta‐analysis ; thus, a random‐effect model was conducted to pool analysis. As shown in Figure z = 3.56, p < .001).As a high heterogeneity existed between studies  was observed among studies and a fixed‐effect model was applied. The pooled analysis revealed that OSA patients had significantly higher circulating P‐tau level than the control group  suggested evidence of publication bias, while Begg's tests (p = .072) showed no evidence to support publication bias  and Begg's (p = 1.000) proved no evidence of publication bias in our study (Figure For circulating T‐tau, Egger's tests (s Figure . For ciry Figure .4The results of this meta‐analysis demonstrated that OSA was significantly and positively correlated with circulating T‐tau and P‐tau in a cognitively normal population. Both circulating T‐tau and P‐tau of the OSA group were significantly higher than that of the control group.There is increasing literature to suggest that OSA is not only highly prevalent among AD patients but also increases the risk of developing AD and even dementia (Bubu et al., Some studies evaluated the effect of OSA treatment on AD/dementia (Ancoli‐Israel et al., The role of circulating tau proteins as dementia biomarkers has been validated by accumulating evidence (Chiu et al., Our study suggested that OSA was significantly and positively correlated with circulating T‐tau and P‐tau levels in a group of cognitively normal patients. The finding has some clinical implications. First, OSA confers an increased risk of developing AD and dementia. Intermittent hypoxia, sleep fragmentation, reduced slow‐wave sleep, and intrathoracic pressure swings are suggested to be possible mechanisms by which OSA induces neurodegenerative changes (Bubu et al., Several limitations must be addressed when interpreting these results. First, although a significant relationship between OSA and elevated circulating T‐tau and P‐tau levels was identified, the strength of evidence might be weak because of the limited sample size. Second, subgroup analysis based on some confounding variables cannot be performed because of the limited number of included studies. Third, as the severity of OSA was not grouped in most studies, the dose–response relationship between OSA and elevated circulating tau levels cannot be evaluated in this study. Fourth, the circulating T‐tau level varies significantly in different studies. The variability could be explained by several factors: differences of blood sampling time, sample type, measure assay, and patient characteristics. The SMD was applied to estimate the pooled results. Finally, all studies were cross‐sectional in design, so we cannot explore a causal relationship.In conclusion, the present meta‐analysis demonstrated that both circulating T‐tau and P‐tau levels were significantly increased in OSA subjects when compared with non‐OSA subjects. The results of our study support the potential role of circulating tau in linking OSA with increased risk of AD and even dementia. However, larger sample‐size studies on the association between OSA and circulating tau are still required to further validate our results.The authors have disclosed no conflicts of interest.https://publons.com/publon/10.1002/brb3.2972.The peer review history for this article is available at TABLE S1 Quality assessment of case‐control studies with the Newcastle–Ottawa Scale.Click here for additional data file.