N = 654), we find that individuals’ estimates of the pandemic’s social  impact are associated with an unwillingness to curtail social interaction and follow other Centers for Disease Control guidelines as the pandemic spreads. First, these associations are present in self-report data of participants’ own behaviors and behavior across hypothetical scenarios; second, participants’ estimates of the pandemic’s impact on social life in their location of residence are associated with movement data collected unobtrusively from mobile phones in those locations. We suggest that perceptions of social impact could be a potential mechanism underlying, and therefore potential intervention target for addressing, disease-preventing behavior during a pandemic.People regularly make decisions about how often and with whom to interact. During an epidemic of communicable disease, these decisions gain new weight, as individual choices exert more direct influence on collective health and wellbeing. While much attention has been paid to how people’s concerns about the health impact of the COVID-19 pandemic affect their engagement in behaviors that could curb (or accelerate) the spread of the disease, less is understood about how people’s concerns about the pandemic’s impact on their social lives affect these outcomes. Across three studies (total  People often face tradeoffs between their own immediate interests and the collective interests of a group. In March 2020, the World Health Organization declared a global pandemic as a result of the worldwide spread of a new coronavirus (SARS-CoV-2), which causes the respiratory disease COVID-19. The declaration of a pandemic brought with it a collection of guidelines aimed at curtailing the spread of the disease and that imposed limitations on people’s activities in daily life. These guidelines were met with widely varying levels of compliance across individuals , in turnperceptions of the potential impact of the pandemic on various aspects of human life are potentially more malleable. Additionally, perceptions may change over time as the overall picture of the pandemic continues to evolve .These figures point to the importance of understanding the factors that give rise to compliance with guidelines aimed at mitigating disease spread. In particular, although individual differences in demographics . Here, we investigate the possibility that individual differences in the perceived consequences of the pandemic for specific aspects of human life are associated with disease-preventing behaviors in specific ways. In particular, we test the possibility that the anticipated impact of the pandemic on social life, over and above its anticipated health consequences, relates to people’s (un)willingness to curtail social behavior in the interest of mitigating disease spread.Behavioral interventions have proven effective for containment of COVID-19 and have a robust potential to prevent illness and death . As a reWhile perceptions related to the health impact of the pandemic have been associated with engagement in preventative behaviors , there aHere, we assessed perceptions of the health and social impacts of the pandemic in separate samples across two time points: 3 weeks after the pandemic declaration (April 2020) and 13 weeks after the pandemic declaration (June 2020). Between April and June 2020, much changed in terms of pandemic, including the cumulative number of cases and deaths, the current number of cases, and the knowledge available regarding transmission, effective preventative measures, and the course of the virus . AdditioIn Study 1, we first examined whether there are differences in the perceived severity of the pandemic’s impact on health and social domains and whether the perceived severity of the pandemic’s impact on health and social domains was different in April and June. Next, we tested to what extent people’s perceptions of impact are associated with their likelihood of engaging in disease-preventing behaviors. We were particularly interested in whether perceived social impacts would be associated with more or less engagement with disease-preventing behaviors, including social distancing. Finally, we examined the relationship between ratings of perceived impact and changes in the extent of people’s physical movement through space, as indexed by state-level movement change using Google movement data. We included the Google movement data as an out-of-sample behavioral measure of the extent to which individuals followed social distancing recommendations. State-level movement provides a proximal and objective measure of social activity.In Study 2, we assessed whether people’s perceptions of the impact of the pandemic, and behavioral intentions, could be influenced by explicit messages about the pandemic’s social or health impacts. In Study 2, we also asked participants to estimate rates of disease prevalence that would influence their movement to the specific locations indexed by the Google movement data in order to tie the state-level movement outcomes to individual-level movement predictions. Across both Study 1 and Study 2, we predicted that perceptions of social impact of the pandemic would be associated with behavior over and above perceived health impacts. In doing so, we aimed to identify a potential mechanism for understanding whether, and why, individuals might continue to engage with others when doing so poses a health risk. Finally, in Study 3, we explored reasons for an association between perceptions of the social impact of the pandemic and behavior. Specifically, we asked to what extent behaviors associated with curbing social interactions  were rated as more difficult, less controllable, or less effective than other disease-mitigating actions . Better understanding such factors may help guide public health communication and recommendations.Study 1 sought to characterize the anticipated impact of the pandemic on health and social domains across time and to investigate how these expectations relate to people’s disease-mitigating behaviors. In order to assess whether perceived social impacts could relate to behavior over and above health influences, we first needed to compare perceptions of health and social impacts to each other and across time. Therefore, we examined ratings of perceived health impacts in two samples, one collected 3 weeks after the pandemic declaration and one collected 13 weeks after the pandemic declaration. Then, we examined whether the perceived social impact of the pandemic was associated with behavior, and whether the direction of association was consistent with disease-mitigating behaviors. Finally, we examined these associations using out-of-sample data to better understand how individual ratings relate to larger patterns of population movement.https://osf.io/48yxk/For all studies, we report how we determined our sample size, all data exclusions, and all manipulations. Because the studies reported here were part of a larger data collection effort related to the COVID-19 pandemic, measures were collected outside the scope of the current hypotheses. All measures collected in the full study are reported and available on: n = 188) recruited via Amazon’s Mechanical Turk approximately 3 weeks or approximately 13 weeks after the World Health Organization declared the COVID-19 outbreak a global pandemic. Ninety-seven participants completed the study on April 3, 2020  and an independent set of 91 participants completed the study on June 15, 2020 . We restricted participation to MTurk workers with HIT acceptance rates > 97% who were located in the United States. Sixty-four additional participants were excluded because of bot-like responses , using a restricted number of response options, or currently residing outside of the United States. Participants provided informed consent and received $1.25 for completing the task. The study was approved by the Institutional Review Board.Participants were two groups of adults  within the next week (both sets of participants) and in the following month (April participants only) on a 5-point scale from 1 = not at all likely to 5 = extremely likely. Finally, participants provided demographic information, including the state in which they were currently residing and the number of COVID-19 cases in their city. We report findings investigating relationships moderated by local prevalence of cases in To identify core dimensions underlying the 26 behaviors, we conducted an exploratory factor analysis. The parallel analysis and scree plot recommended three factors. The three-factor solution using a varimax rotation accounted for 51% of the variance see . The fir1. The Google Mobility Report measures change in movement  from a baseline to a specific date. The baseline is the median movement measurement during a 5-week span before the COVID-19 pandemic, from January 3, 2020 to February 6, 2020. The places of interest included retail and recreation locations, grocery stores and pharmacies, parks, transit stations, workplaces, and residential locations. To match our individual impact perception data with state-level measurements of movement, we used the Google Mobility data for the state in which our study participants lived and on the date on which our study participants completed the questionnaire.To investigate the generalizability of the relationship between perceived social and health impact and disease-relevant behaviors, we asked whether the observed perceptions were associated with behavior out-of-sample by using large-scale data from the Google Mobility Reporthttps://osf.io/48yxk/. Because this investigation was exploratory, we used a predefined sample size of collecting at least 100 participants at each time point. Sample size was determined before any data analysis. A sensitivity analysis using G*Power . Analyses were conducted in R  was rated as more severe than the anticipated social impact  = 28.222, p < 0.001, 95% CI ). There was also a main effect of time, such that anticipated impact was rated as more severe for the next 3 months (M = 4.95) than 1 year in the future  = 38.377, p < 0.001, 95% CI ). The main effect of month of survey completion was not significant  = 0.081, p = 0.776, 95% CI ).We first examined participants’ overall expectations about the severity of the perceived health and social impact of the COVID-19 pandemic across time. In a linear mixed effects model, we regressed participants’ rating of perceived impact on domain , time frame , and month of survey completion  with a by-participant random intercept and by-participant random slopes for domain and time frame. There was a main effect of domain, such that the anticipated health impact  = 8.327, p = 0.004, 95% CI ). Second, there was an interaction between domain and time frame  = 4.028, p = 0.045, 95% CI ); participants perceived a greater difference between the severity of health and social impacts within 3 months as compared to 1 year in the future. Finally, there was an interaction between domain and month of survey completion  = 10.207, p = 0.001, 95% CI ; b = 0.444, SE = 0.216, X2(1) = 4.215, p = 0.040, 95% CI ); ratings of anticipated health impact did not decrease  = 1.415, p = 0.234, 95% CI ). The three-way interaction between domain, time frame, and month of survey completion was not significant  = 0.418, p = 0.518, 95% CI ). Therefore, perceived impacts of the pandemic on the social domain appear to have increased over time and become more similar in magnitude to perceived health impacts (which did not change over time).The main effects were qualified by three interactions, reflecting the interplay between perceptions across domains and time. First, there was an interaction between the time frame and the month of survey completion such that participants expected a greater difference in severity of impact between the next 3 months and 1 year in April as compared to June  = 4.943, p < 0.001, 95% CI ), but not intentional social interactions  = 0.662, p = 0.509, 95% CI ). Ratings of perceived social impact were positively correlated with social interactions  = 4.431, p < 0.001, 95% CI ; marginally correlated with following guidelines, r = 0.126, t(184) = 1.718, p = 0.088, 95% CI ). Therefore, perceived health impacts primarily related to following  guidelines, whereas perceived social impacts related to continued interaction with others.We examined whether perceived social and health impacts were associated with the intentional social interactions and following guidelines factor scores. Perceived health impact was positively associated with following guidelines . Therefore, we next calculated a difference score between ratings of social and health impact . The difference score allows us to capture relationships with behavior given the extent to which people view the social or health impacts as larger. The social-health difference score was positively associated with intentional social interactions and negatively associated with following guidelines  = 3.209, p = 0.002, 95% CI ; follow guidelines: r = –0.194, t(184) = –2.682, p = 0.008, 95% CI ). The more highly participants rated the anticipated social, relative to health, impact, the more likely they were to report that they would interact with others and the less likely they were to report that they would follow recommended guidelines. We further confirmed that the social-health difference score was differently related to following guidelines vs. interacting with others by examining the interaction. We regressed the factor score ratings on the social-health difference score and type of behavior  with a by-participant random intercept. The interaction was significant  = 17.827, p < 0.001, 95% CI ; b = 0.013, SE = 0.028, X2(1) = 0.213, p = 0.645, 95% CI , behavior: b = 0.144, SE = 0.101, X2(1) = 2.045, p = 0.153, 95% CI ), providing additional evidence that perceiving the social impact of the pandemic as relatively higher in severity is associated with less likelihood of following guidelines and greater likelihood of interacting with others.We observed considerable variability in severity of perceived impact, and a person’s behavior may track best with the b = 0.223, X2(1) = 4.799, p = 0.028, 95% CI = ), such that men provided higher ratings of impact overall. This was qualified by an interaction between gender and the factor score type , such that gender differences were larger for interacting with others (with men reporting they were more likely to interact with others) than for following guidelines  = 8.511, p = 0.004, 95% CI = ). Additionally, the association between the social-health difference score and intentional social interactions was steeper for men than for women  = 6.146, p = 0.013, 95% CI = ). That is, increases in perceived social  impact were associated with greater likelihood of continued social interactions for men than for women.Because men and women may have responded differently to the pandemic , we sougwhere individuals tended to go. Existing research has documented state-level differences in health-related behaviors, e.g., mask-wearing  = –1.095, p = 0.275, 95% CI ). However, here was a significant correlation between overall movement change and perceived social impact. Specifically, in locations where our participants had reported anticipating higher social impact, there was less change  in people’s mobility as reported by Google  = 2.822, p = 0.006, 95% CI ). In other words, those who resided in locations where people expected more social impact from the pandemic were less likely to curtail their social behavior. There was also a correlation with the social-health difference score, such that higher ratings of social vs. health impacts were associated with smaller changes in mobility  = 3.640, p < 0.001, 95% CI ).There was no relationship between overall movement change and perceived health impact  = –2.818, p = 0.006, 95% CI ). The associations with the social-health difference score corroborated these effects, with positive correlations with movement in all areas except residential locations, which had a negative correlation , ratings of health impact were not correlated with movement change in any area. However, social impact was significantly positively related with movement in retail and recreation locations, grocery stores and pharmacies, parks, transit stations, and workplaces  = 3.431, p < 0.001, 95% CI ). The relationship held for each of the location areas, and was again in the opposite direction for movement change in residential areas  was measured at the state level five days later  whether there were differences across individuals and time in perceptions of the extent to which the pandemic would impact the health and social domains, (2) whether perceptions of impact were associated with likelihood of engaging in disease-preventing behaviors, and (3) whether ratings of impact generalized to a relationship with state-level movement change. We found that perceptions of the social impact of the pandemic increased between April and June . As a result, there was a smaller distinction in the anticipated severity of health vs. social impact at the second timepoint. Consistent with effects seen on social wellbeing , by 13 mFinally, we observed an association between the perceptions of participants in our sample and the degree of movement change in their states. There were notable limitations with this approach, including that we only sampled a relatively small number of individuals across the United States and we did not measure additional demographic factors  that may interact with this effect. However, this finding points to the possible importance of local governance in promoting particular messages regarding the impact of the pandemic. We explored the possible influence of messages individuals might receive regarding the pandemic in Study 2.In the first set of studies, we found evidence to support the idea that perceptions of the social and health impacts of the pandemic have different associations with the extent to which individuals are likely to follow disease-preventing recommendations. In a second study, we follow up on these findings with the aim of testing whether brief manipulations change individual perceptions of the social and health impacts of the pandemic. Health communication has been a key focus during the pandemic, particularly in light of evolving knowledge and information  and has age range = 20–79 years, Mage = 38.65, SDage = 11.73). All participants were living in the United States. For consistency with Study 1, we aimed to recruit 100 participants per group, however, forty-one additional participants were excluded for failing an attention check question that was repeated twice during the survey (participants were asked to write a specific phrase in a free response block to check that they were reading the instructions). Participants provided informed consent and received $0.75 for completing the task. The study was approved by the Institutional Review Board.Participants were a sample of 362 adults recruited via Amazon’s Mechanical Turk between July 2, 2020 and July 6, 2020 . In each of these conditions, participants saw a brief description of potential impacts of the pandemic. The impacts highlighted were taken from those that consistently loaded on the health and social factors in our survey  and severity of impact  creating four between-subjects conditions . Therefore, it appeared that the brief manipulation was not sufficient to change perceptions.In order to examine whether brief descriptions influenced ratings of perceived impact, we regressed perceived impact on our manipulated degree of severity , order , and their interaction for those in the social condition. There was no effect of impact, order, or the interaction  = 30.52, p < 0.001, 95% CI ; p = 0.397).Because participants’ perceptions of health and social impact were robust to the descriptions provided, we collapsed across conditions to examine the effects of perceived social impact on behavior in imagined social scenarios. We ran a linear mixed effects model, regressing the interaction rating for each scenario on ratings of perceived social impact (mean-centered), and ratings of perceived health impact (mean-centered). We included random intercepts for participant, amount of cases, and the scenario rated. The main effect of social impact was significant  = 28.96, p < 0.001, 95% CI ; p = 0.98). The main effect of social impact held for work, grocery, parks, retail, transit, and residential locations  at which they would feel comfortable visiting the same places that were assessed in the Google Mobility Report. The findings of Study 2 supported our conclusions from Study 1: individuals who perceived a greater social impact of the pandemic reported that they would continue visiting public spaces, at a higher rate of case increase. These results may help us to understand, and potentially predict, how social interactions might change (or not) as cases climb. In conjunction with Study 1, we gain further confidence in the unique association between perceived social impact and engaging in social behaviors.why perceived social impact might be associated with social interactions. First, we focused on understanding the particular aspects of social life in which expected impact might relate to behavior. For example, people might be especially unwilling to reduce social interactions if they are concerned about the pandemic’s impact on their relationships or on their daily social interactions. Second, we investigated whether and how disease-mitigating social behaviors  are seen as different from disease-mitigating physical behaviors . One possibility is that it is more difficult to curtail social behaviors  than it is to follow other guidelines, such as washing one’s hands more frequently. Another possibility is that one has less control over social behaviors than non-social behaviors. Alternatively, individuals may see social behaviors as overall less effective at reducing the spread of the disease.Given the consistency with which perceived health and social impacts were differentially associated with behavior, we were interested in the potential reasons age range = 19–72 years, Mage = 40.13, SDage = 13.07). All participants were living in the United States. For consistency with Study 1, we aimed to recruit 100 participants, but oversampled by 25 participants in order to account for potential exclusions. Twenty-one additional participants were excluded for using a limited number of response options, completing the survey in less than 5 min, and/or living outside of the United States. Participants provided informed consent and received $1.25 for completing the task. The study was approved by the Institutional Review Board.Participants were 104 adults recruited via Amazon’s Mechanical Turk on May 7, 2020  within the next month on a 5-point scale from 1 = not at all likely to 5 = extremely likely.To assess whether social and physical behaviors were considered differently from each other, participants then rated how difficult it has been to do each of six behaviors in the last 30 days from 1 = very difficult to 5 = very easy . The behaviors were: adjust the frequency of going to the store, practice recommended hand-washing practices, wear a mask in public, practice social distancing, stay away from close family and friends (with whom you don’t live), and avoid public spaces . Participants rated the level of control they have in their ability to engage in these behaviors from 1 = almost none to 5 = a lot. Finally, they rated the behaviors in terms of effectiveness. Participants provided a numerical rating from 0 to 10  on the effectiveness of each of these behaviors for reducing the risk of COVID-19. They provided two effectiveness ratings: (i) effectiveness if they were to engage in the practices consistently themselves and (ii) effectiveness if their community in general were to engage in the practices consistently . Because individuals vary in their own risk of becoming seriously ill, we also included these ratings separately for the effectiveness in reducing the risk of COVID-19 for their self, close family and friends, people in their city, people in their state, and people across the globe. Finally, participants provided single-item ratings on how easy, controllable, and effective social practices (as a whole) and physical practices (as a whole) were, respectively, on a scale from 1 = not at all to 5 = very. Additional measures were collected that are outside the scope of this paper; these are provided in the survey available online.Because participants only rated expected impact for areas of social life , we tested whether these social variables would cluster in meaningful ways. The parallel analysis and scree plot recommended a three-factor solution, which accounted for 38% of the variance in people’s impact ratings. The first factor (15% of variance) captured impact on social contact between others , the second factor (13% of variance) captured impact on social relationships , and the third factor (10% of variance) captured global social issues . Again, for people’s likelihood of engaging in various behaviors, a three-factor solution was recommended (44% of variance), with the first factor representing social interactions (20%), the second factor representing following guidelines (15%), and the third factor containing a more heterogeneous group of variables  = 2.96, p = 0.004, 95% CI ). However, engagement in social interactions was negatively associated with perceived impact on social contact and social interactions  = –2.45, p = 0.016, 95% CI ), suggesting that the perceived impact of the pandemic on social relationships, as opposed to its effect on social contact more generally, best explained the likelihood of continuing to interact with others. The association between the global social issues factor score and social interactions was not significant  = –0.234, p = 0.815, 95% CI ).We examined whether perceptions of each of the three domains of social impact were associated with people’s likelihood of engaging in social interactions. Engagement in social interactions was positively associated with perceived impact on social relationships, consistent with the overall patterns observed in Studies 1 and 2  = 0.447, p = 0.504, 95% CI ). The effect of behavior type on the single-item measures asking how difficult it is to follow each physical guideline and social guideline was also not significant (t(193.99) = –1.102, p = 0.272, 95% CI ). That is, participants did not perceive adjustments to social behavior to be more difficult than following other guidelines. See We regressed difficulty ratings on type of behavior  with by-participant and by-activity random intercepts and a by-participant random slope. The effect of type of behavior was not significant  = 0.210, p = 0.647, 95% CI ) or for the single item measure (t(198.57) = 0.539, p = 0.590, 95% CI ). None of the pairwise contrasts were significant  = 0.263, p = 0.608, 95% CI ). The single-item comparison of effectiveness was also not significant (t(196.01) = –0.650, p = 0.517, 95% CI ). See Finally, we looked at ratings for effectiveness, first examining ratings of effectiveness if the participant engaged in each behavior consistently. To test for differences in effectiveness, we regressed ratings of effectiveness on type of behavior  with a random slope for type of behavior and random intercepts for participant, specific activity , and target . The effect of type of behavior was not significant  = 0.505, p = 0.477, 95% CI ). See Next, we ran the same model examining ratings of the effectiveness participants expected these behaviors to have if people in the community were to engage in them consistently. There was no effect of type of behavior on expected effectiveness . In Study 3, we also examined whether social behaviors were simply more difficult to enact or control or perceived as less effective than other physical-health promoting behaviors. Our results suggest that individuals do not view the social behaviors that could reduce disease spread as more difficult, less controllable, or less effective than their less social counterparts.Across three studies, we provide evidence that how individuals perceive the social impact of the pandemic is associated with the degree of continued interaction with others and engagement in disease-preventing behaviors. We provide support for these associations using participants’ self-reports of their own behavior, self-reports of behavioral intentions, and extrapolations to aggregated measures of movement occurring at the state level. Each of these approaches serves to help us understand these associations by probing individual self-reflection and intentions (via self-reported behaviors), reducing individual-level variability by having each participant consider a specific hypothetical situation (via imagined scenarios), and observing large-scale patterns in the real world (via state-level movement). Our third study highlights the pandemic’s impact on our social relationships as a potentially potent factor that influences individuals’ behaviors and decision making. These results expand upon previous research that implicates consideration of health effects  and indirelative expectations of social vs. health impact, on the one hand, and their absolute expectations of social impact, on the other. Further understanding the relationship between expected health and social impacts could also highlight areas for intervention. Although Study 2 leaves open the question of exactly what type of intervention is needed to change individual perceptions about the pandemic, perceptions during the pandemic have changed ; however, it is worth noting that the interpretation of these findings is limited somewhat by their correlational nature. Although our findings are consistent with the possibility that expectations about how the pandemic will impact their social lives lead them to take measures to minimize those impacts , it may be also be the case that individuals who engage in more social interactions seek to justify that behavior by reporting elevated perceptions of social impact. On their own, the current studies cannot adjudicate between these possibilities .Although partly mitigated by the use of Google Mobility data, the conclusions that can be drawn from the present studies are additionally constrained by the reliance on self-report data. Responding in a questionnaire format may lessen some of the weight that people experience when making these decisions in real life. For example, it might be relatively easy to say that you would stay away from family and friends when completing the survey, but your choice may be different when faced with your own and others’ desire for social connection in the moment. Another notable limitation is that study measurement occurred amid the changing landscape of the pandemic. Across time when the studies were conducted, much changed (and continues to change) with regard to the number of cases, observed severity of impact on health and social consequences, and information provided to the public. Additionally, there is extensive variability in the extent to which individuals are impacted by the pandemic e.g., , and theThe research presented here provides a first investigation of the role of perceptions of the impact of a pandemic on social life in influencing the extent to which individuals participate in disease-preventing behaviors, particularly with regard to social interactions. Expectations that the COVID-19 pandemic will more severely impact social life, and especially social relationships, are associated with greater engagement with others as the pandemic unfolds, which may hamper societal attempts to “flatten the curve” and accordingly prolong a pandemic. In this way, concerns that a pandemic will impact social life may eventually contribute to the very outcome people wish to prevent. These findings paint a more complete picture of how individuals weigh various aspects of a pandemic’s influence in their daily lives and provide some insights into the psychological mechanisms underlying, and therefore possible intervention targets for, behaviors that slow (or accelerate) the spread of communicable disease.https://osf.io/48yxk/.The datasets presented in this study can be found on Open Science Framework: The studies involving human participants were reviewed and approved by University of Pennsylvania Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.RP collected the data and drafted the manuscript. AJ provided critical revisions. Both authors were involved with data analysis and conceptualized the research questions and contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The elderly is a vulnerable group susceptible to toxic environmental factors; however, the association between unsafe water and osteoarthritis (OA) incident among this population is poorly investigated. This study aimed to examine the effects of drinking water sources on OA risk in the Chinese elderly population.Data were obtained from the China Longitudinal Healthy Longevity Survey to perform a 16-year longitudinal study. All participants aged ≥65 years at baseline were potentially eligible. Information on drinking water sources was recorded via a structured questionnaire. The water source was classified as well, surface, spring, or tap. OA was selected as the health outcome. Cox proportional hazard models, adjusted socio-demographics, lifestyle, and chronic disease were used to estimate the hazard ratio (HR) for OA. Subgroup analyses were performed to assess the potential interactive effect.p for interaction <0.05). After multiple imputations for missing data and excluding deaths in the first year of follow-up and participants with a history of the disease and using the Shared-frailty Cox model, sensitivity analysis indicated a robust association between the drinking water source and OA incidence.A total of 12,543 participants were included. With restriction to the longest follow-up time, the mean survival time of follow-up was 14.56 years. Among the cohort members, 1,585 members suffered from OA. In the full model, drinking from well water and spring water was associated with a higher risk of OA compared with drinking from tap water . Except for age, the effects of modifications from socioeconomic status, lifestyles, and health conditions were non-significant (Drinking tap water was associated with a low risk of OA among older adults in China. The use of clean water sources as a marker of decreased OA and arthritis risks must be revisited in low- and middle-income countries. Osteoarthritis (OA) is a chronic pathological joint disease characterized by changes in cartilages and hyperplasia around bones . PatientOsteoarthritis pathogenesis is unclear and linked with age, obesity, inflammation, trauma, and genetic and environmental factors. Consumable water in China contains a dangerous concentration of arsenic, fluorine, and sulfates , and an The global elderly population is at an increased risk of OA , and thiConsidering that OA might be affected by different water sources, this study evaluated the long-term effects of drinking water sources on OA risk among the Chinese elderly population.The Chinese Longitudinal Healthy Longevity Survey (CLHLS) is a dynamic longitudinal study of follow-up surveys conducted every 2–4 years that covers 85% of the elderly in 22 provinces in China. From 1998 to 2000, CLHLS recruited participants aged 80 years and above and performed multistage, stratified cluster sampling. Participants aged 65–79 years were additionally recruited since 2002. All the participants were interviewed on determinants of healthy longevity for the elderly, such as socioeconomic characteristics, lifestyle, social interaction, residential environment, cognitive function, and physical/mental condition. This study was approved by the Research Ethics Committee of Peking University (IRB00001052-13074), and written consent was obtained from all participants or their legal representatives.To date, six waves of surveys have been performed. Individuals still living were followed up in each wave. If a participant has already died when being surveyed, then his/her relatives and/or family members were interviewed for the cause of his/her death, health condition, and utilization of health service before death. The questionnaires were divided into two sections, namely, the “survivors questionnaire”  and the “deceased questionnaire” for the relatives/family members . The curIn the first wave (2002), 16,064 individuals were selected. Among which, 12,543 participants with complete information on drinking water sources and OA history at baseline and follow-up surveys were eligible. A total of 599 participants with missing data or ambiguous answers, 2,710 participants with OA at baseline, and 212 participants leaving the place of residence were excluded. A fixed cohort was employed in this study.During the succeeding surveys in the cohort, OA diagnosis was self-reported (“Have you suffered from osteoarthritis?”). The outcome was defined as OA that occurred in the follow-up period for participants without a history of OA at baseline. All interviewees were followed up from baseline until arthritis incidence, dropout, or latest interview.Water sources were identified by one item: “What source of water source did you mainly drink from at present ?”Several potential confounders were adjusted in the analyses. Sociodemographic data included age, sex, residential place , and education level (illiterate/primary school/high school or above). Lifestyle factors comprised smoking status (never/previously/currently), drinking status (never/previously/currently), dietary diversity scores (low/medium/high), and social activity (yes/no). Health status was composed of body weight (kg), chronic diseases , cognitive function [as measured by Mini-Mental State Examination (MMSE) score], and depression status (measured by five items). Detailed definitions of covariates are described in the Appendix methods in Continuous variables were described as mean ± SD and analyzed by Chi-square test, and categorical variables were described as frequency and proportion (%) and tested by ANOVA or Kruskal–Wallis test. Multivariable Cox regression was used to assess the association between water sources and OA incidence. Drinking well water was set as the reference group. A set of Cox regression models were built: Model 1—adjusting age and gender; Model 2—further adjusting residence, education, income, region, and weight; Model 3—further adjusting social activity and physical activity based on model 2; Model 4—further adjusting drinking alcohol, smoking, and dietary scores; and Model 5—further adjusting chronic disease, depressive symptoms, and cognitive impairment.Subgroup analyses were conducted to test multiplicative interactions between water sources and covariates by adding a cross-product term in the full multivariable Cox regression model, namely, sex, age, residence, chronic disease, drinking, smoking, or exercise.Three sensitivity analyses were performed to address the potential influence of dropout. First, deaths in 2005 (second wave) were excluded to ensure that the participants were pre-mortality. Second, individuals with chronic diseases  were excluded to minimize the hysteretic effects of chronic diseases on the outcome. Third, multiple imputations based on five replications and Monte Carlo simulations were performed to account for missing data because the covariates were disproportional and randomly missing. The Cox model with shared frailty was used to treat the cluster, and participants with equal value were assumed to have shared frailty across different groups in controlled provinces. The effect within the province group was estimated separately to identify the significance of regional heterogeneity.p was <0.05 (two-sided).All analyses were performed using Stata 16.1 . Statistical significance was considered when the two-side This study included 12,543 eligible participants at baseline. The regional sample distribution is displayed in As shown in p < 0.001) was also observed. In terms of drinking mainly from well, a significantly large effect size was observed among female participants, those aged below 80 years, living in rural areas, had no chronic disease, never smoked and drunk, and had no physical activity. In terms of drinking main from spring water, a significantly large effect size was observed among women, those living in rural areas, had chronic diseases or smoking/drinking habits, and participated in physical activity.A series of subgroup analyses was conducted by using pre-defined factors . Although the individuals who died before the second wave (2005) were excluded, the fitted model was comparable with the models imputing missing values. In addition, the participants drinking from well had a high risk but no significance was observed for those drinking spring water . After participants with chronic diseases were excluded, drinking well and spring water was linked with a high risk of OA . Finally, the Cox model with shared frailty showed that drinking well water was positively associated with OA risk, though the cluster effect within provinces was controlled  and protein expression of p16, p53, and p21 . In a raammation –32, oxidammation , 34, andammation . In partThis study shows several strengths. First, this work is the first attempt to analyze the effect of drinking water sources on the OA incidence of the Chinese elderly. The findings provide novel evidence for improving the availability of water, sanitation, and hygiene and the prevention of OA in the elderly. Second, this study was based on CLHLS, a large-scale population-based cohort study. Sufficient statistical power was obtained to infer the casual associations of drinking water sources with OA incidence. Finally, three sensitive analyses were conducted to verify the accuracy and credibility of the association, and the results were consistent with those from the analysis of the overall sample.This study has several limitations. First, sufficient and valid information on the diagnosed OA cases was not available from the dataset. Recall bias could be generated due to retrospective longitudinal design and self-report data. Second, detailed food data were not accessible, and the proxy variable of the dietary pattern cannot be adopted in the baseline questionnaire. Therefore, the association between dietary patterns and drinking water sources cannot be explored. Third, the proportion of participants drinking spring water and surface water was relatively small. A large sample size should be employed to improve the power of statistical inference. Finally, the dose-response relationship of chemical substances and OA  cannot be assessed. Further evidence from environmental medicine perspective must be obtained to clarify the underlying mechanism between drinking water sources and OA. The conclusion of this research was proposed carefully.Drinking well and spring water was associated with a high risk of OA among the population of age >65 years old in China. Therefore, the association between unprocessed drinking water with a multilevel exposure and OA incidence must be re-examined in low- and middle-income countries. Further longitudinal studies are also needed to confirm the relationship as causal. This work paves the way for an evidence-based intervention for the policymakers to ease the burden of OA related to water pollution for the elderly in such a globally aging population.https://sites.duke.edu/centerforaging/programs/chinese-longitudinal-healthy-longevity-survey-clhls/.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The studies involving human particpants were reviewed and approved by the Institutional Review Board, Duke University (Pro00062871), and the Biomedical Ethics Committee, Peking University (IRB00001052-13074). The patients/participants provided their written informed consent to participate in this study.YZ and TW contributed to the conception, analysis, interpretation of data, drafted the report, and received the final version for publication. YL, YX, SS, JY, XC, XW, and XL contributed to analyzing and interpreting the data, commented on the report, revised the manuscript, and approved the final version for submission. All authors have read and agreed to the published version of the manuscript.This work was supported by the Natural Science Foundation General Project of Chongqing Science and Technology Bureau (Grant No. cstc2020jcyj-msxmX0279) and the Science and Technology Research Project of Chongqing Education Commission (Grant No. KJQN202100432).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To investigate the influence of quality of life (QOL) on unhealthy emotions as well as relevant factors among patients with endometriosis for supporting relevant clinical care.P < 0.05, there was statistical significance.A convenience sampling method was used to administer questionnaires to 139 patients with endometriosis, using the Hamilton Anxiety Inventory (HAMA), the Depression Anxiety Scale (SDS), and the SF-12 Health Survey Short Form, and the results were analyzed. The SPSS20.0 software was used for statistical analysis on relevant data. If OR = 0.912, 95% CI: 0.877–0.949; OR = 0.899, 95% CI: 0.866–0.933). PCS score was a factor influencing anxiety degree; the higher the PCS score, the lower the anxiety degree .Twelve-Item Short Form (SF-12) for health survey covered two comprehensive indexes, i.e., physical component summary (PCS) and mental component summary (MCS) scores. MCS score was the main factor influencing anxiety and depression in patients with endometriosis; the higher the MCS score, the lower the anxiety and depression degrees in patients with endometriosis (The QOL of patients with endometriosis is negatively correlated with anxiety and depression. Therefore, improvement in QOL may help relevant patients to relieve their unhealthy emotions. The aim of our study is to investigate the influence of quality of life (QOL) on unhealthy emotions as well as relevant factors among patients with endometriosis. Endometriosis is defined as growth of endometrial gland and/or stroma growing in a site outside the uterine cavity . It is eThis is a research study that includes in-patients diagnosed with endometriosis at the First Affiliated Hospital of Sun Yat-sen University between July 2020 and April 2021. Inclusion criteria for the study were: no previous mental illness or history of psychiatric diagnosis, no neurological disease, no other chronic diseases, patients with stable conditions who can complete the questionnaire independently and voluntarily, and patients must be histologically diagnosed as having endometriosis. These patients underwent surgery after being clinically diagnosed with endometriosis based on symptoms and ultrasound results. Exclusion criteria of the study were: patients with serious audiovisual impairment that may influence the understanding and response to the questionnaire, patients who suffer from serious mental illness, and patients who cannot cooperate or refuse to cooperate.The self-designed scale for general information survey, 12-item Short-Form (SF-12), Hamilton Anxiety Scale (HAMA), and Self-rating Depression Scale (SDS) were used to investigate patients with endometriosis. General information on the patients included age, education level, family concern level, obstetrical history, dysmenorrhea, dyspareunia, use of painkiller, and efficacy of painkiller. HAMA was assessed by surveyors who were professionally trained and qualified. Other questionnaires were completed by the subjects independently after explanation by the investigators. The investigators then checked all the questionnaires, so as to ensure the authenticity and validity of the survey results.Twelve-Item Short Form (SF-12) is a short form for health survey that includes 12 items covering 8 dimensions: general health (GH), physiological function (PF), role-physical (RP), bodily pain (BP), mental health (MH), vitality (VT), social function (SF), and role-emotional (RE). The SF-12 was summarized as two comprehensive indexes, namely, physical component summary (PCS) and mental component summary (MCS) scores. A scoring algorithm ranging from 0 to 100 was used to calculate body functional component score and mental functional component score. The higher the scores, the better the self-perceived QOL; the lower the scores, the poorer the outcomes . The phyHamilton Anxiety Scale (HAMA)  covered P < 0.05, there was statistical significance. The SPSS 20.0 software was used for statistical analysis.For quantitative indexes, analysis of variance was performed, while for qualitative indexes, Kruskal-Wallis H test was adopted. Ordered logistic regression was utilized for a multifactor model. If This study has been approved by the Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University, with approval number: Lun Shen [2021] No. 237. Each patient signed an informed consent form.OR = 0.942, 95% CI: 0.97–0.977), and the higher the MCS score, the lower the anxiety level . The MCS score was the only factor influencing depression level. The higher the MCS score, the lower the depression level   see , 3.3 see , 3For patients with endometriosis, the higher the QOL, the lower the anxiety and depression levels. Physical component summary (PCS) and mental component summary (MCS) scores are two comprehensive indexes of SF-12: the higher the PCS and MCS scores, the lower the anxiety and depression levels. At present, there is no report concerning the correlation between QOL and unhealthy emotion worldwide. For patients with endometriosis, the PCS score (x ±s) was 42 ± 8.99, and the MCS score (x ±s) was 44. ± 11.91. The PCS score was obtained by a calculation based on general health (GH), physiological function (PF), role-physical (RP), and bodily pain (BP) scores, and MCS score was obtained by a calculation based on mental health (MH), vitality (VT), social function (SF), and role-emotional (RE) scores .Worldwide, most studies on the QOL of patients with endometriosis have focused only on its relevant factors and neglected the role of emotions. This study is the first attempt to investigate the correlation between unhealthy emotion and QOL among patients with endometriosis, aiming to improve psychological care in nursing, as well as the QOL of patients with endometriosis in the future.In our study, about 84.9% of the patients with endometriosis had dysmenorrhea see , which wP < 0.05). Relative to incidence and mortality of cervical cancer and ovarian cancer as gynecological diseases, endometriosis failed to attract public attention, and there are only few studies on family support and social support for patients with endometriosis. For patients with endometriosis, dysmenorrhea is often the first symptom for treatment, and, usually, as they come to hospital for this, the pain can no longer be relieved by oral painkillers. Many families even think that women’s dysmenorrhea is normal, and a painkiller is enough for it. Therefore, they cannot comfort patients as they need, which makes patients feel helpless. At the same time, for patients with endometriosis, relevant diagnosis and treatment are time-consuming. Duration may be a few years, or even 30 years, which may make patients’ families become accustomed to the condition. Thus, the loneliness of patients may become more serious because of lack of family care. As a common cause of infertility, endometriosis may lead to infertility in approximately 20–40% of relevant patients . In this study, 40.3% of the patients were accompanied with dyspareunia, and a prospective study of The univariate analysis found that for the influence of dyspareunia on anxiety of patients, there was statistical significance  adopted in this study is a self-rating scale; thus, the results may be greatly influenced by the subjectivity of the subjects. In the future, other rating scales may be used for further evaluation, thus increasing the reliability of relevant appraisal. 2. This study merely included patients with endometriosis treated at the First Affiliated Hospital of Sun Yat-sen University; therefore, relevant conclusions need to be further verified by multi-center studies.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.GH and JC: conceptualization, methodology, investigation, formal analysis, and writing—original draft. ZP: data curation and writing—original draft. KF: data curation and investigation. CL and XZ: conceptualization, resources, supervision, and writing—review and editing. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Primary Sjögren's syndrome (pSS) is a disease associated with the overexpression of proinflammatory cytokines, and oxidative stress is one of the factors responsible for its etiopathogenesis. This study aimed to investigate the thiol/disulphide homeostasis in pSS patients.The study included 68 pSS patients and 69 healthy controls. Thiol/disulphide homeostasis  was measured using the automatic spectrophotometric method developed by Erel and Neselioglu, and the results of the 2 groups were compared.P = 0.988 and P = 0.065). Total thiol and native thiol levels were lower in the pSS group than in the control group . There were no differences in disulphide levels between groups .The gender and age distributions of the pSS and control groups were similar (It was concluded that the thiol/disulphide balance shifted towards disulphide in patients with pSS. Sjögren's syndrome (SS) is a systemic chronic inflammatory disease characterized by the lymphocytic infiltration of exocrine organs Oxidative damage in the body is prevented by enzymatic or non-enzymatic antioxidant mechanisms To the best of our knowledge, there are no studies that have investigated oxidative status via the measurement of native thiol, total thiol, and disulphide levels in patients with pSS. Therefore, it was aimed herein to evaluate the oxidative status via these parameters in patients with pSS.Sixty-eight patients with pSS and 69 healthy individuals were included in the study. Patients with cardiovascular diseases, cerebrovascular diseases, kidney failure, liver failure, infections, malignancies, and individuals that used antioxidants, multivitamins, cigarettes, or alcohol were excluded from the study. SS was diagnosed according to the criteria defined by the 2016 American College of Rheumatology/European League Against Rheumatism The demographic and clinical characteristics  and laboratory results  of the patients were recorded. The study was approved by the ethical board of the institution, and informed consent was obtained from all participants .Biochemical parameters  were measured using standard laboratory methods . The hemogram was evaluated on Sysmex XN-1000  analyzer, and serological parameters were studied using the nephelometric method (Siemens BN-11).For the assessment of the thiol/disulphide homeostasis, blood samples were centrifuged at 1500 rpm for 10 min and stored at -80°C until assessment. After all of the samples had been collected, they were simultaneously evaluated for oxidative stress parameters by the same laboratory technician using the same device. Native thiol, total thiol, and disulphide levels were assessed using the novel and fully automated assay developed by Erel and Neselioglu, which is based on the reduction of dynamic disulphide bonds to free thiol groups by sodium borohydride (NaBH4) Next, the native thiol content was subtracted from the total thiol content, and 50% of this difference revealed the quantity of the disulphide bond. An automated clinical chemistry analyser (Cobas 501) was used to measure the amount of native thiol and disulphide. The serum thiol and disulphide values were presented as µmol/L.P < 0.05 was considered statistically significant.All statistical analyses were performed with IBM SPSS Statistics 21.0  software. The Shapiro-Wilk test was used to evaluate compliance with the normal distribution. Descriptive analyses were presented as the mean ± standard deviation (SD) for normally distributed variables and median and range (min-max) for non-normally distributed variables. Categorical variables were presented as numbers and percentages. The 2 groups were compared using the Student t-test and 1-way ANOVA for parametric variables, and the Kruskal-Wallis test for non-parametric variables. P = 0.988). The mean ages of the patient and control groups were 53.71±8.17 and 51.04±8.57 years, respectively (P = 0.065). Of the pSS patients, 64.7% had Raynaud's phenomenon, 57.4% were anti-SSA-positive, and 69.1% were anti-SSB-positive. The Schirmer's test result was 2 mm in 30.9% of the patients. According to the Chisholm-Mason classification Of the pSS patients, 66 were female, and 2 were male, and of the controls, 67 were female, and 2 were male . The total thiol and native thiol levels were statistically lower in the pSS patients when compared to the controls . Although the disulphide levels were higher in the pSS group when compared to the control group, this difference was not statistically significant  . The total thiol, native thiol, and disulphide levels were not significantly associated with the Schirmer's test or minor salivary gland biopsy results . Moreover, the thiol/disulphide parameters of the anti-SSA- and anti-SSB-positive patients were similar to those of the anti-SSA- and anti-SSB-negative patients   .Although oxidative stress is involved in the pathophysiology of several chronic conditions, there have been a limited number of studies evaluating the relationship between SS and oxidative stress. To the best of our knowledge, the current study was the first to investigate thiol/disulphide homeostasis in pSS. In this study, it was observed that the total thiol and native thiol levels were reduced in the pSS patients when compared to the healthy controls, there was a statistically insignificant increase in the disulphide levels, and the dynamic thiol/disulphide balance shifted towards disulphide.There is an association between proinflammatory states and oxidative stress. Moreover, studies have suggested that oxidative stress is involved in the pathogenesis of SS. A study by Kurimoto et al. Thiols are crucial organic compounds that contain sulfhydryl groups, which play an important role in the oxidant/antioxidant mechanism The thiol/disulphide balance is impaired in many diseases, such as myocardial infarction, preeclampsia, polycystic kidney disease, diabetes mellitus (DM), and cancer. Disulphide levels increase in degenerative diseases, such as DM, obesity, pneumonia, and familial Mediterranean fever, and the balance shifts towards thiol in proliferative diseases, such as multiple myeloma, bladder cancer, colon cancer, and kidney cancer -2), and reactive oxygen particles In the current study, the total thiol and native thiol levels in the pSS patients were significantly lower than in the control group, as was the case in patients with RA. This suggested that antioxidation had decreased in patients with pSS, indirectly increasing oxidation. The fact that disulphide levels did not increase as expected, despite the fact that native thiols decreased, may have been because these molecules could not be measured due to being converted into advanced oxidation products. It should be noted that the subjects herein with pSS were on a variety of drugs, including immunosuppressives and corticosteroids. Methotrexate is known to reduce oxidative stress by reducing free radicals, such as superoxide  received no financial support for the research, authorship, and/or publication of this article.All the authors declare that they have no conflict of interest in this work.


Background: A considerable amount of evidence has shown that acute cardiovascular diseases exhibit specific temporal patterns in their onset.Aim: This study was performed to determine if takotsubo syndrome (TTS) shows chronobiological variations with short and long-term impacts on adverse events.Design: Our institutional database constituted a collective of 114 consecutive TTS patients between 2003 and 2015.Methods: Patients were divided into groups defined by the onset of TTS as per time of the day, day of the week, month and quarter of year.Results: TTS events were most common afternoon and least common in the night, indicating a wave-like pattern (p = 0.001) of manifestation. The occurrence of TTS events was similar among days of the week and weeks of the month. TTS patients diagnosed in the month of November and subsequently in the fourth quarter showed a significantly longer QTc interval. These patients also revealed a significantly lower event-free-survival over a 1-year follow-up. In a multivariate Cox regression analysis, TTS events occurring in the fourth quarter of year  proved to be an independent predictor of lower event-free-survival.Conclusions: TTS seems to exhibit temporal preference in its onset, but nevertheless this possibly coincidental result needs to be analyzed in a large multicenter registry. The exact pathophysiological mechanism for selective wall motion abnormality in the absence of significant coronary artery stenosis remains unknown in Takotsubo syndrome (TTS). TTS patients may suffer from complications e.g., acute heart failure, ventricular tachyarrhythmias, thromboembolic events and significant mitral valve regurgitation similar to acute coronary syndrome (ACS). Patients often complain about chest pain and/or dyspnea –5. TTS hChronobiology is the biomedical science aimed at the study of biological rhythms. Defined by the cycle length, biological rhythms may be divided into three main types: ultradian , circadian , infradian . The natural predilection of the cardiovascular system is oriented to function in an oscillatory circadian order, both in conditions of health or disease. The occurrence of cardiovascular events is not evenly distributed in time but shows peculiar temporal patterns that vary with time of the day, day of the week, and month of the year , 7.There have been reports suggesting a chronobiological difference and circadian variation to the occurrence of TTS , 9. HoweThe primary hypothesis of the present study is that circadian variant may have a different impact on the outcome of TTS patients.We retrospectively studied a collective of 114 consecutive patients diagnosed with TTS between January 2003 and September 2015 at our institution, the Medical Faculty of Mannheim. Patients were diagnosed as per the Mayo Clinic Criteria , which oThis study was conducted in compliance with the Declaration of Helsinki concerning investigations in human subjects and the study protocol was approved by the Ethics Committee of the Medical Faculty Mannheim, University of Heidelberg. The need for informed consent was not required by the ethics committee. All methods were performed in accordance with the relevant guidelines and regulations.Screening for TTS was done prospectively at the TTS event. The assessment of complications associated with TTS was conducted at index-event and at the subsequent follow-up after 1 year. The clinical outcome of patients was assessed by chart review and/or telephone review. If medical records, treating physicians or relatives were unable to substantiate information identifying the circumstances of death, it was defined as death due to an unknown cause.All patients included in this study were grouped in a standardized fashion as per the timing of their initial 12-lead ECG recordings on admission to the emergency department reflecting the event onset and diagnosis of TTS. This was used to determine if the occurrence of this syndrome was consistent with circadian dependence. The day was spitted into 6-h blocks beginning at 06:00 a.m. The week was divided into 7 days and the year into 12 months. The year was divided into 3-month blocks: spring including March to May, summer including June to August, autumn including September to November, and finally winter including December to February.The end-point of our study was a composite of thromboembolic events, life-threatening arrhythmias, all-cause mortality, re-hospitalization due to heart failure, stroke, myocardial infarction, and recurrence of TTS as assessed by chart review and/or telephone review over a mean follow-up for 1 year. The selection of endpoint components was based on previous results which have described these complications to influence the prognosis of TTS patients . The folt-test and the Mann–Whitney U-test were used to compare continuous variables with normal and non-normal distributions. The chi-squared-test and Fisher's exact test were used to compare categorical variables. Additionally, with the use of the chi-squared “Goodness of Fit” test, observed vs. expected numbers were compared to evaluate whether TTS events are evenly distributed across the day, months, or quarter of year. The log-rank test was used to compare the survival curves between groups. Factors with p < 0.10 in univariate analysis were subjected to the Cox multivariate regression analysis to define independent risk factors for the adverse outcome. Data was analyzed in an exploratory manner to generate new hypotheses and therefore we did not adjust the p-values with the number of all performed analyses. The IBM SPSS 23.0 or GraphPad InStat were used for statistical calculations. In all analyses, p < 0.05 (two-tailed) was taken to indicate statistical significance, 0.05 > p ≤ 0.10 was taken to indicate significance by tendency.Our data are presented as means ± SD for continuous variables with a normal distribution, median (interquartile range) for continuous variables with a non-normal distribution, and as frequency (%) for categorical variables. Student's n = 82) of patients, whereas the non-apical ballooning form could be diagnosed in 28% (n = 32). The most frequent complications associated with TTS were life-threatening arrhythmias (11.4%), pulmonary congestion with need for invasive respiratory support (20%), thromboembolic events (12.2%), cardiogenic shock (19.2%) and in-hospital death (7.9%).The mean age of patients presenting with TTS was 67 ± 11 years, with our data skewing toward a female preponderance (83%), n = 44, 38.5%) and least common between 12 midnight and 6 a.m. , respectively, depicting a wave-like pattern of occurrence. This distribution was significantly different from the expected equal distribution of n = 28.5 TTS cases per 6 h unit (114/4), p = 0.001 (Chi-Squared Goodness of Fit Test), The role of diurnal variations influencing the onset of TTS was evaluated by dividing the day into four periods: 6 a.m. to 12 noon, 12 noon to 6 p.m., 6 p.m. to 12 midnight, 12 midnight to 6 a.m. TTS events were most common between 12 noon and 6 p.m. (n = 16.3 TTS cases per day (p = 0.25), n = 25, 21.9%) and least on Friday .Although the onset of TTS events over a week-long period was statistically insignificant with an expected equal distribution of n = 16, 14%) and the least in March and December . However, this distribution was not significantly different from the expected equal distribution with n = 9.5 TTS cases per month (p = 0.67), A monthly distribution of TTS events revealed that most cases took place in October , however, this distribution was also not significantly different from the expected equal distribution with n = 28.5 TTS cases per quarter of year (p = 0.70), TTS events, grouped quarterly, increased continuously in number with a maximum number of cases diagnosed at the last quarter of the year , p = 0.04), TTS events taking place during the four 6 h units of the day were not significantly different in their association with the composite endpoint after 1 year, log-rank Baseline characteristics of patients diagnosed with TTS in the last quarter were compared to TTS patients from other groups, due to the increased incidence of adverse outcomes in the former.p = 0.05), The values of blood pressure as well as heart rate were not significantly different. ECG-changes like ST-segment elevation and inverted T-waves were present in both groups, without significant difference. However, it was noticed that the QTc interval was significantly longer in TTS patients admitted in the fourth quarter as compared to those patients diagnosed in other months and other quarters , right ventricular involvement  and glomerular filtration rate <60 ml/min  were associated with lower event-free survival rate with the composite endpoint. A multivariate Cox regression analysis was performed with adjustment for the known risk factors, to highlight an independent association with a lower-event free survival rate. This analysis revealed that TTS taking place only in the fourth quarter  was an independent predictor of lower event-free survival rate, In a Cox univariate analysis of TTS events in the fourth quarter of year  The occurrence of TTS exhibits a circadian rhythm; (ii) the event-free survival rate is significantly lower in TTS patients admitted in the fourth quarter of year; (iii) TTS patients presenting with TTS in fourth quarter of the year show a significant QTc prolongation in comparison to the general TTS population.Mechanisms dictated by the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic adreno-medullary system maintain biological homeostasis and protect living organisms from internal and external stresses during environmental and physiological challenges. The HPA axis is activated by corticotropin-releasing hormone (CRH) from the paraventricular nucleus of the hypothalamus, stimulating production of glucocorticosteroids . The cenACS seems to exhibit some temporal preference in its onset, and is characterized by diurnal variations, variations as per day of the week as well as monthly variations, albeit with analogies and differences. Each of these temporal frames has been discussed in detail , 13–19.A meta-analysis extrapolating data from 30 studies on ACS and 19 studies on sudden cardiac death estimated that nearly 27.7% of morning cases of ACS and 22.5% of sudden cardiac deaths were attributable to an increased risk at that time of day. Recent studies give credence to the hypothesis that there exists a Monday preference for the occurrence of ACS . In caseA Monday preference for TTS events has been suggested in studies from Italy and Korea, although our data did show a possible Wednesday preference for occurrence of TTS (increasing from Monday to Wednesday but not reaching significance), more like data reported from studies conducted in the USA , 22, 23.Increases in plasma catecholamines and cortisol, heart rate, blood pressure, coronary vasomotor tone and platelet aggregation predispose to coronary artery occlusion and this has been correlated to the early morning circadian peak characteristic of ischemic heart disease–related events –26. In cIt has been suggested that diurnal variations may have an impact on the clinical outcome of ACS patients, because several fatal cases were diagnosed in the morning, independent of patient age and infarction site or extension . A correOur data offers a detailed analysis of the chronobiological association of TTS events in a German population for the first time, and additionally, detail its influence on the reported adverse outcomes.This study had a few limitations; firstly, this was a single-center retrospective case series study including patients admitted over the period of 13 years without a comparative control group and therefore there is a need to evaluate results in large multicenter registries. Secondly, data was analyzed in an exploratory manner to generate new hypotheses concerning time-dependency of TTS events and associated adverse events. Therefore, we cannot rule-out random or accidental findings. The timing of onset of TTS may vary because some patients who had a symptom at night might come to the hospital on the next day.TTS seems to exhibit temporal preference in its onset. The chrono-biological distribution of TTS may influence the outcome of patients. These novel findings may help to identify high risk TTS patients with a need of subsequent follow-ups.ibrahim.el-battrawy@medma.uni-heidelberg.d.The data analyzed in this study is subject to the following licenses/restrictions: original data are available under request according to the ethical committee. Requests to access these datasets should be directed to The studies involving human participants were reviewed and approved by MA 2018/KA. The patients/participants provided their written informed consent to participate in this study.IE-B, AA, SL, XZ, UA, MB, and IA designed the research and wrote the paper. IE-B, IA, and TG performed the clinical research. IE-B, SL, AM, XZ, NU, TG, and IA analyzed data. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Objective: Patients with well-developed coronary collateral circulation (CC) usually have low mortality, improved cardiac function, and reduced infarct size. Currently, there is conflicting evidence on the association between traditional cardiovascular risk factors  and CC.Design: We performed a meta-analysis of case-control studies to better understand such associations.Data Sources: We searched the MEDINE, EMBASE, and Science Citation Index databases to identify relevant studies.Eligibility Criteria for Selecting Studies: Case control studies reporting data on risk factors  in comparing cases between poor CC and well-developed CC groups. Well-developed CC was the primary outcome of this meta-analysisData Extraction and Synthesis: Relevant data were extracted by two independent investigators. We derived pooled odds ratios (ORs) with random effects models. We performed quality assessments, publication bias, and sensitivity analysis to ensure the reliability of our results.Results: In total, 18 studies that had 4,746 enrolled patients were analyzed. Our results showed that hypertension and smoking habit did not , and diabetes did  affect the development of CC.Conclusion: Unlike hypertension and smoking habit, diabetes was associated with poor CC formation.Trial Registration Number:https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=87821, identifier: CRD42018087821. These risk factors are predictors of poor clinical outcomes in patients with myocardial infarction, stroke, and peripheral artery diseases –3. CollaThis meta-analysis is presented in accordance with the Preferred Reporting Items for System Reviews and Meta-Analyses (PRISMA) Statement and has been registered with the International Prospective Register of Systematic Reviews (CRD42018087821) . The proWe searched the MEDLINE, EMBASE, and Web of Science databases to identify relevant studies published from inception of those databases to January 1, 2021. We used the “coronary collaterals” as the key words, “collateral circulation” as the MeSH terms to identify relevant studies.p-values of the data of interest without any numerical values in each group; (2) they were not published in English peer-reviewed journals; and/or (3) they presented data that were previously published.Studies were included in our analyses if (1) they reported the extent of coronary CC, describing it as well-developed or poorly developed; (2) they reported data on risk factors  in comparing cases between poor CC and well-developed CC groups; (3) they were case-control studies; and (4) they contained sufficient information . Studies were excluded if (1) they reported only the Traditional coronary risk factors  were defined as exposure factors. We used the Rentrop scoring system to grade CC . A RentrData selection was conducted independently (JY Pei and XP Wang).Disagreements were resolved through discussion with all authors or by consulting a third author (ZH Xing). We selected the following data from the included articles: study characteristics , the characteristics of included participants , the definition of coronary CC, and the risk factors of coronary CC. We used the Review manager and Stata to organize included articles and data.If quantitative analysis was not appropriate, we performed a narrative, qualitative summary. Results are presented both in the text and in tables.We assessed the methodological quality of the included studies by the Newcastle-Ottawa Scale. A maximum of two stars could be given for comparability measurements. A star system of the scale  was used in the current study.P-values < 0.05 were considered statistically significant. Heterogeneity was assessed by the Cochran Q-test, and statistical heterogeneity was summarized by the I2, which quantifies the percent of variation in study results that is because of heterogeneity rather than to chance. When I2 was <25%, the heterogeneity was small, and a fixed-effect model will be used. When I2 ≥ 25%, the included studies were considered to have moderate heterogeneity, the I2 ≥ 50%, there is a significant heterogeneity  and CC in patients with chronic coronary occlusion was expressed in terms of the odds ratio (OR) and its 95% confidence interval (CI). An OR >1 indicated that the studied factors were positively correlated with the formation of CC, while an OR <1 indicated that the studied factors were negatively correlated with the formation of CC. ogeneity . When thAn outline of the screening process is shown in A total of 4,746 CTO patients were enrolled in the selected studies, including 2,928 (61.7%) patients with hypertension, 1907 (40.2%) patients with diabetes, and 2,146 (45.2%) patients with a history of smoking. Most of these studies were cross-sectional studies that study the relationship between blood biochemical indicators and coronary collateral circulation. These biochemical indicators have been shown to be related to the severity of cardiovascular disease in previous studies. In most studies, male patients accounted for the majority. This might be because the formation of coronary collateral circulation was related to the severity of coronary atherosclerosis, and male patients usually have more severe symptoms than female patients . The basThe Newcastle-Ottawa Scale was used to evaluate the quality of the included studies. Each of the included studies had a score above seven points, and thus, all these studies were included in our analyses.I2 score was 65.8% (p = 0.0001), indicating that the included literature was heterogeneous, thus requiring a random-effects model  indicated that the included literature was heterogeneous; thus, requiring a random-effects model  diabetic patients. I2 = 40.4% (p = 0.06) indicated that the included literature showed significant heterogeneity. Therefore, a random-effects model was used  patients with a history of smoking. p = 0.0001, The use of a fixed-effect model showed that the statistical methods did not influence the observed results , diabetes , and smoking habit .The Begg and Egger methods were used to test publication bias. No publication bias was observed for hypertension , leading to an increase in nitric oxide (NO) synthesis . HoweverDiabetes is a relatively important risk factor for coronary heart disease, and it can lead to poor short-term and long-term cardiovascular outcomes . Abaci eRevascularization of patients with chronic complete coronary occlusion can significantly improve the patient's left ventricular function and reduce the risk of cardiovascular events  and currMoreover, tobacco consumption may both promote and inhibit the formation of CC. Heeschen et al. found that nicotine promoted the adhesion of monocytes to endothelial cells and thus, may promote the development of CC . HoweverThe current study has a few limitations. First, this is a meta-analysis of observational studies, and thus, it was not possible to consider all confounding factors between groups with and without good CC formation, which may affect the evaluation of our results. There are many factors that can affect the formation of coronary collateral circulation, such as age, weight, ethnicity, body mass index or cholesterol level. The data obtained from the original study can only show the average age or average weight of all patients. As far as we know, we cannot adjust in statistical methods based on these data, so we did not adjust age and weight in the statistical process. As for race, because most of the included studies are single-center case-control studies, the original article did not provide exact race data, these may have some influence on the results. Additionally, along with real operators/equipment, the definition/identification of the presence or absence of coronary collaterals can vary between different studies, and therefore, such differences can affect the quality assessment of CC. And we used the Rentrop scores to evaluate the quality of CC, not the CFI, because Rentrop scores was used in most studies. We were unable to obtain relevant data from these original studies, so we did not perform the inter and intra-observer variability analyses. The OR value of hypertension and smoking habit was 0.92 and 1.01, respectively. The effect values and 95% CI of these two variables were very close to 1. However, the effect values and 95% CI for diabetes was close to 0.5. Even if there were confounding factors that may have affected the outcome measures, they are unlikely to overturn the observed results of this study since our meta-analysis incorporated a large population base, and subgroup/sensitivity analyses were used to verify the reliability of our conclusions. Since the included studies were all case-control studies, data of patient's hypertension stage cannot be collected from the original article, so we cannot perform the analysis of the impact of hypertension stage and collateralization. As well for diabetes, data of patient's hypertension stage cannot be collected from the original article, we cannot perform the analysis of the HbA1c and collateralization status in diabetics either. Second, despite a detailed search of different databases, some studies could have been missed during the initial search. Finally, the bulk of the studies included in our meta-analysis was performed in China and Turkey, which may limit the generalizability of our results in other  populations.This meta-analysis found that hypertension and smoking habit were not associated with CC formation. However, diabetes was associated with poor CC formation.The original contributions presented in the study are included in the article/ZX designed the study and provided methodological expertise. JP and XW data selection was conducted independently and relevant studies were searched by 2 independent investigators. JP and ZX drafted the manuscript. All authors have read, provided critical feedback on, and approved the final manuscript.This work was supported in part by National Science Foundation of China Project No. 82000298 and Natural Science Foundation of Hunan Province 2021JJ40883 to ZX.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.