Bullying has been identified as the most common form of aggression experienced by school-age youth. However, it is still unclear about the family’s influence on school bullying. Therefore, the current study aimed to explore the associations between sibling bullying and school bullying, sibling victimization and school victimization, and parental acceptance–rejection and school bullying victimization. The study was cross-sectional and conducted on a sample of students aged between 11 and 20 years recruited from middle schools in Algeria. The study used a survey adopted from the scale of Sibling Bullying, Student Survey of Bullying Behavior—Revised 2, and the Survey of parental acceptance–rejection in collecting the data. The model’s results assessing the association between sibling bullying and school bullying demonstrated that the effect of sibling physical and sibling verbal victims on school victimization was statistically significant. Despite the non-significant effect of sibling emotional victims on school victimization, the effect of sibling physical and sibling verbal bullying on school bullying was statistically significant. However, the effect of sibling emotional bullying on school bullying was not statistically significant. The direct effect of parental acceptance on school victimization was not statistically significant, whereas the effect of parental rejection on school victimization was statistically significant. The direct effect of parental acceptance on school bullying was not statistically significant, while the effect of parental rejection on school bullying was statistically significant. Based on the results, this study provides insights into the understanding of how the family and siblings contribute to school bullying. In particular, sibling victimization, sibling bullying, and parental acceptance–rejection are predictive factors of school bullying among adolescents. Future research should take into account factors based on family to explore the risks of school bullying. School violence, a type of violence that happens in school, including different subtypes  to cause physical and psychological harm to students, has attracted attention in the literature ,2,3. AltBullying is the most common form of aggression experienced by school-age youths , and it A cross-sectional and cultural study by Biswas et al.  investigViolence in Algerian society continues to be a severe social evil and a complex reality that has attracted the attention of Algerian academics, researchers, and scholars, necessitating a review of both the country’s family and educational responsibilities and some suggested measures to lessen or end violence in schools . SchoolsBullying can occur in different situations and environments. One potential place where bullying exists is the home environment with family members, specifically among siblings. The current literature shows a growing interest in understanding such sibling bullying (or sibling abuse) and its associated effects ,21. HistSibling bullying refers to any physical or verbal aggressive behavior involving one or both siblings. It includes hitting, pushing, kicking, spitting, biting, throwing objects, fighting, overplay, or name-calling . SimilarIn addition to sibling bullying, children’s interaction and relationship with their parents are important factors for their proper behavior and mental health. According to Rohner , one of In most cases, similar violent behaviors are extended into multiple environments in a child’s life, such as home and school. In contrast, a home bully may be a school bully, which can be explained by personality traits, individual temperaments, family conflicts, and parental bullying . In addiSibling and peer relationships appear prominently in the daily experiences of children and adolescents as essential contexts for individual development. The experiences of children and adolescents in these relationships do not occur in isolation from each other, but rather they create vital links between these two crucial relationships in the process of development . In a stBullying also harms the social and emotional well-being of the child and adolescent, regardless of the perpetrator, and the child’s exposure to bullying by siblings is linked to similar results as school bullying. The study by Coyle et al.  aimed toIndeed, acceptance and rejection by parents play an important role in school bullying and victimization. Mendo-Lázaro et al.  showed aDoes sibling victimization  have an association with school victimization?Does sibling bullying  have an association with school bullying?Does parental acceptance–rejection have an association with school victimization?Does parental acceptance–rejection have an association with school bullying?To the best of the authors’ knowledge, family violence in general, specifically childhood offensive behavior, has received much attention over the past several decades, which professionals recognize as a large and widespread problem with lifelong consequences ,52,53. HA cross-sectional study was conducted among 221 students in middle schools at the Provinces of Chlef and Ouargla, Algeria. The inclusion criteria of the participants were (i) adolescents aged between 11 and 20 years old (ii) having at least a sibling. The participants’ mean age was 14.84 years (SD = 1.90). The majority of the participants, 148 (67%), were females, while 73 (33%) of them were males. The participants who were early adolescence (11 to 14 years) were 39.4% (n = 87); middle adolescence (14 to 18 years) was 58.8% (n = 130); late adolescence (18 to 20 years) represented 1.8% (n = 4). Concerning the number of siblings, the highest percentage  reported was four to six siblings, followed by 32.1% (n = 71) of the participants who had one to three siblings, while 23.1% (n = 51) of them had more than six siblings. Furthermore, the majority of adolescents reported that their parents were still living together , followed by 4.1% (n = 9) who stated they had divorced parents; 6.8% (n = 15) reported a deceased parent  was developed by Aiche Sabah (2021). It consists of 26 items that measure two aspects of bullying: a bully and victim siblings. It measures three types of bullying and victimization, which are physical, emotional, and verbal bullying and victimization. The SBS items were reported using a five-point Likert scale: always = 5, never = 1 . The psyThe Student Survey of Bullying Behavior—Revised 2 (SSBB-2) in the current study used two subscales (victimization and bullying) of the SSBB-2 developed by Varjas et al.  to invesThe psychometric properties of the SSBB-2 from the current study were satisfactory. The three-factor structure of the SSBB-2 victimization subscale was supported by the fit indices in the CFA: chi-square/df = 1.658, SRMR = 0.063, comparative fit index (CFI) = 0.954, and RMSEA = 0.055. The three dimensions  in the SSBB-2 victimization subscale had good internal consistency, with maximal reliability = 0.712, 0.741, and 0.732 and composite reliability = 0.677, 0.712, and 0.702.The three-factor structure of the SSBB-2 bullying subscale was supported by the fit indices in the CFA: chi-square/df = 2.788, SRMR = 0.057, CFI = 0.93, and RMSEA = 0.09. The three dimensions  in the SSBB-2 victimization subscale had good internal consistency, with maximal reliability = 0.819, 0.804, and 0.770 and composite reliability = 0.795, 0.775, and 0.760.The perception of parental acceptance and rejection questionnaire was adopted from Erraji . It consIBM SPSS Statistics, Version 28  was used for descriptive statistics in this study, while AMOS Version 24  was used for structural equation modeling (SEM). The SEM instead of the multiple linear regression model was used in the present study because the SEM has the strengths of simultaneously taking measurement errors into account when assessing the associations. Although regression models can also be used to assess the associations, they do not consider measurement errors . Moreovep = 0.006), whereas sibling emotional victim was not significantly associated with school victimization ; sibling verbal victim was significantly associated with school victimization .p = 0.016), while sibling emotional bullying was not significantly associated with school bullying ; sibling verbal bullying was significantly associated with school bullying .p = 0.228); parental rejection of adolescents was significantly associated with school victimization .p = 0.369); parental rejection of adolescents was significantly associated with school bullying .Using cross-sectional data on adolescent students in the school context of Algeria, this study aimed to determine the contribution of sibling bullying in its two forms: bullies of sibling bullying and victims of sibling bullying in the interpretation of school bullying victimization among peers in a sample of school-age adolescents. Moreover, the study investigated the effect of parental acceptance or rejection on school bullying victimization. The main findings of the present study are (i) sibling bullying was associated with school bullying and school victimization, (ii) sibling bullying and parental acceptance/rejection were associated with school bullying, (iii) sibling emotional bullying and sibling emotional victims were not associated with school bullying or victimization, and (iv) parental rejection was associated with school victimization and school bullying. The findings demonstrated that any experience of sibling bullying (either victim or bully) is associated with school bullying and school victimization. In particular, sibling physical victims and sibling verbal victims appeared to influence school victimization, but the effect of sibling emotional victims on school victimization was not statistically significant. The results showed that sibling physical bullying and sibling verbal bullying had effects on school bullying. As to the effect of sibling emotional bullying on school bullying, it was not statistically significant. These results suggest a high impact of being consistently bullied  by siblings on school bullying.Sibling bullying and parental acceptance/rejection contribute to school bullying. This finding is consistent with previous research in this area ,45,46,48As for sibling emotional bullying and sibling emotional victims, it was found that there were no statistically significant associations with school bullying or victimization. The results of the present study support previous studies. Relevant literature indicates that adolescence sees a decline in emotional involvement and intimacy with siblings ,21. In aThe associations between parental acceptance and school bullying/victimization were not statistically significant. In contrast, parental rejection was significantly associated with both school victimization and school bullying. These results are supported by the Theory of Parental Acceptance–Rejection  as citedIn this study, we have sought to understand bullying from a family to school perspective. We have researched, in particular, the effects of sibling bullying and parental acceptance on school bullying. The findings provide theoretical and practical implications for the field of family psychology and adolescents in general.Our findings help to address the lack of studies in the Arab environment on fraternal bullying and its role in school bullying, as we have noticed that many studies treat school bullying, but such studies ignore its relationship to bullying in the family. Accordingly, the first major practical contribution of the present research is that it provides empirical data about the effect of family factors  on school bullying. This finding is important given the spread of bullying in schools; therefore, it is important to identify its true causes in order to reduce this dangerous phenomenon among adolescents.This study is an important addition to the program/policy implications regarding bullying reduction. Specifically, the present findings in the family and the school are in agreement with the previous literature. Therefore, our findings echoed the importance of taking care of aggressive behaviors and promoting warmth in both the family and school contexts. In other words, programs and policies are needed to take care of bullying reduction to avoid the possibility that children learn bullying behaviors in the family and generalize them to their interactions and social relationship with peers.According to the present study’s findings, future studies may want to design effective programs to reduce school and sibling bullying. Therefore, studies are also needed to evaluate if there are effective programs for bullying reduction. For example, future studies may want to examine if promoting family warmth  is helpful for reducing bullying. In addition, future studies may want to explore if the present study’s findings can be generalized to other cultural contexts , given that bullying is an issue associated with cultures.These findings provide preliminary evidence for the contribution of sibling bullying and parental acceptance to school bullying, but such results cannot be generalized to adolescents around the world, because many considerations restrict such generalizations. The first limitation is that the study sample was selected using a cross-sectional sampling method. Longitudinal studies, therefore, should be conducted in order to provide more reliable results. The second limitation is related to the method of collecting data that relies on psychological scales, which only express the adolescents’ point of view and may be biased, as other data collection tools, such as interviews, may give more accurate results. The third constraint is the sample size, which was far lower than the study population. The study was conducted only on a sample from the state of Chlef in Algeria due to the difficulty of including all Algerian school students in the study.The results of the present study showed a statistically significant effect of sibling bullying/victimization on school bullying/victimization. Moreover, parental rejection was found to affect school bullying/ victimization significantly. These results offer theoretical implications for the literature on how to address bullying among adolescence with families’ and siblings’ contributions to school bullying. Specifically, our study proposes that the family context plays a fundamental role in school bullying. These findings can help researchers, teachers, educators, and parents better understand the important family-related factors that lead to students’ school bullying.


We aim to compare the severity of infections between omicron and delta variants in 609,352 SARS-CoV-2 positive cases using local hospitalization, vaccination, and variants data from the Catalan Health Care System (which covers around 7. 8 million people).We performed a substitution model to establish the increase in transmissibility of omicron using variant screening data from primary care practices (PCP) and hospital admissions. In addition, we used this data from PCP to establish the two periods when delta and omicron were, respectively, dominant (above 95% of cases). After that, we performed a population-based cohort analysis to calculate the rates of hospital and intensive care unit (ICU) admissions for both periods and to estimate reduction in severity. Rate ratios (RR) and 95% confidence intervals (95% CI) were calculated and stratified by age and vaccination status. In a second analysis, the differential substitution model in primary care vs. hospitals allowed us to obtain a population-level average change in severity.We have included 48,874 cases during the delta period and 560,658 during the omicron period. During the delta period, on average, 3.8% of the detected cases required hospitalization for COVID-19. This percentage dropped to 0.9% with omicron [RR of 0.46 (95% CI: 0.43 to 0.49)]. For ICU admissions, it dropped from 0.8 to 0.1% [RR 0.25 (95% CI: 0.21 to 0.28)]. The proportion of cases hospitalized or admitted to ICU was lower in the vaccinated groups, independently of the variant. Omicron was associated with a reduction in risk of admission to hospital and ICU in all age and vaccination status strata. The differential substitution models showed an average RR between 0.19 and 0.50.Both independent methods consistently show an important decrease in severity for omicron relative to delta. The systematic reduction happens regardless of age. The severity is also reduced for non-vaccinated and vaccinated groups, but it remains always higher in the non-vaccinated population. This suggests an overall reduction in severity, which could be intrinsic to the omicron variant. The fact is that the RR in ICU admission is systematically smaller than in hospitalization points in the same direction. On 26 November 2021, the World Health Organization (WHO) declared omicron (Pango lineage B.1.1.529) a SARS-CoV-2 variant of concern (VOC)  and to estimate both hospitalization and ICU ratios for each period. Second, a differential substitution model was fitted jointly to variants data in primary care and hospitals to analyze changes in severity by assessing the differential substitution properties in primary care vs. hospitals, inferring an average decrease in severity.In order to determine the different periods, the percentage of omicron presence was obtained through variants analyses carried out in the clinical microbiology laboratories at Hospital Universitari Vall d'Hebron  and Hospital Universitari Germans Trias i Pujol  using a 20% of SARS-CoV-2-positive specimens from the primary care of their area of influence. From epidemiological weeks 48/2021 (late November) to 04/2022 (late January), screening of presumptive variants with ΔH69-ΔV70 in spike protein was first performed using the TaqPathTM COVID-19 RT-PCR Kit  according to the manufacturer's instructions. ΔH69-ΔV70 viruses are presumably detected with the assay when both ORF1ab and N targets yield positive amplifications with PCR cycles below 30, while the S target provides negative results due to the serendipitous location of its probes, known as S gene target failure (SGTF)  that corresponds to each subset of cases, using an empiric definition .NA and NB, at a given moment, t, would evolve as follows:The number of cases of each variant, A and βB are two exponents related with the transmissibility of each variant in this context and, therefore, to the effective reproduction number. The effective reproduction number, R, of each variant was assessed from these Equations, assuming a fixed mean period τ between infection and maximum infectivity of individuals , the increase in transmissibility can be computed as follows:If the period between new cases is the same (τRA(t), RB(t)], but if the mean period between new cases is not the same, there is a dependency on the effective reproductive number. To compute the increase of transmissibility in this case, we need to estimate the mean effective reproduction number of at least one of the epidemics during a time period  and lateral flow tests (LFT) for SARS-CoV-2 linked to hospital and ICU admissions. Vaccination status was obtained from the Catalan Shared Clinical Records, a database with vaccine data covering the entire Catalan Health System and all its vaccination centers.The study population comprised two cohorts older than 10 years of age and defined based on the period in which each variant caused more than 95% of the analyzed cases, according to the results of the substitution model (see Results Section): (1) the delta cohort with initial SARS-CoV-2 infection identified between 01 November 2021 and 08 December 2021, and (2) the omicron cohort of cases identified between 05 January 2021 and 25 January 2022.The main outcome was hospitalization and ICU admission in the 14-day time window following SARS-CoV-2 infection.For this analysis, we excluded those individuals with a previous SARS-CoV-2 infection before the beginning of the study period.We compared the percentage of cases hospitalized or admitted to ICU in the following 14 days between omicron vs. delta cohorts. Rate ratios (RR) and 95% confidence intervals (95% CI) were calculated and stratified by age and vaccination status: non-vaccinated, partially vaccinated (one dose of a two-dose regimen vaccine), fully vaccinated (the complete vaccination regimen), and boosted (third dose). In addition, Mantel–Haenszel method was used to estimate overall adjusted RRs.H(t) as a function of time and the average RR between hospitalization with omicron and delta α.We checked whether the severity reduction calculated was consistent with the substitution process observed in admissions to hospitals during the transition from the delta period to the omicron period. We used the substitution model adapted to hospital admissions. The model provides an expression for the proportion of omicron cases in hospital admission ρT) between case confirmations and hospital admission, and an omicron admission rate different from that for delta. Generally speaking, we defined r as the average ratio of cases that led to hospitalizations for variant A (HA) (delta), obtaining the number of hospitalizations as a function of time asWe assumed a delay  and variant A (delta) as α to obtainHB could be written as follows:The proportion of variant B cases in hospital admissions ρH, 0 is the initial ratio between hospitalization with omicron and delta variants. This parameter was adjusted from the data. An important relation for our purposes is that α can be written as a combination of the adjusted parameters Δβ, ξo ξH, 0, and T aswhere ξo, and ξH, 0 were obtained from the fit of the substitution process. The delay (T) between detection and hospitalization was obtained using the database of detected cases and admission from the mean value of the difference between diagnosis and hospital admission of the individuals detected between 09 December 2021 and 04 January 2022 . The few cases that were negative or longer than 14 days were omitted to guarantee that there was a causal link between infection, detection, and admission.Parameters Δβ, ξH, 0) to experimental data of the substitution process in hospitals allows to compute α, being o being the initial ratio between cases of omicron and delta, once the delay (T) between detection and hospitalization is obtained using the database of detected cases and admissions.The fit of the parameters of this model , as shown in  were during the omicron period and 48,874 (8%) during the delta period. Cases analyzed during the delta period were 28.4% not vaccinated, 0.9% partially vaccinated, 69.4% fully vaccinated without booster, and 1.2% boosted. Cases detected during the omicron period were 18.0% not vaccinated, 0.7% partially vaccinated, 65.4% fully vaccinated without booster, and 16.0% boosted. The percentage of the detected cases that were admitted to hospitals and ICU is presented in On average, 3.8% of the detected cases required hospitalization for COVID-19 complications during the delta period. This percentage dropped to 0.9% with omicron, equivalent to an RR of 0.46 [95% CI: 0.43 to 0.49], as shown in The proportion of cases hospitalized or admitted to ICU was lower in the vaccinated groups, independently of the variant. Full vaccination without booster did not modify the observed reduction in severity for omicron relative to delta, as shown by stratification by vaccination status in Omicron was associated with a reduction in risk of admission to hospital and ICU in all age and vaccination status strata.T = 4.75  days. Second, a reduction in the proportion of cases requiring admission also affected the delay between the two substitution curves, as discussed in Methodology. The substitution model fitted both substitution processes to obtain the RR for hospitalization. The obtained parameters from the fit values can be observed in The fraction of samples from SARS-CoV-2 suggestive of the omicron variant based on SGTF in primary care and hospitals is shown in Ecological analysis of the percentage of hospitalization and ICU admissions in different subgroups of detected SARS-CoV-2 cases points to a systematic drop in the severity of the disease caused by the omicron variant with respect to the delta variant. The RR of hospitalization and ICUs is lower than 1 for all age cohorts and is also observed independently of vaccination status. For non-vaccinated, fully vaccinated, and boosted groups, there is a reduction in the percentage of detected cases requiring hospitalization or ICU care. Most age groups and vaccination status groups have a reduction in hospitalization of 40–80% and in ICU admission of 60–90%. Such a systematic reduction regardless of age and vaccination status suggests an overall reduction in severity which could be intrinsic to the omicron variant, and not due merely to the high level of immunization of the population. The fact is that the RR in ICU admission is systematically smaller than in hospitalization points in the same direction.Our study found an overall 54% and 75% reduced risk of hospitalization and ICU admission for omicron cases compared to delta, respectively. While our ecological analysis has the known limitation of making direct comparison between subgroups unreliable, the general average results are consistent with those observed in other studies. For instance, in Norway, researchers found that omicron was associated with a 73% reduced risk of hospitalization , while aWe stress here that our analysis does not include reinfections. We only study patients that are first cases in the data system. We do not have information on antibody status for these patients, so we cannot be sure that all patients did have the disease for the first time, since, during the first wave a part of the cases were undetected. After the first wave, contact tracing protocols were set-up and asymptomatic cases typically represented 50% of the cases detected according to our health records. Nevertheless, even if some cases were hidden reinfections, the fact is that the reinfections that were detected  during the period under analysis were very low (below 8%). In this sense, it is highly unlikely that a possible highly asymmetric hidden reinfection with omicron vs. delta can explain a systematic 75% reduction in ICU admissions with constant admission protocols, pointing again toward omicron being an inherently less severe variant than delta.Similarly, as the periods used to analyze the RR in hospitalization and ICU are relatively short, other environmental effects that could lead to a reduction in severity, such as a better immunization system or weather, are highly unlikely. In this sense, we performed a substitution analysis that investigates a global averaged reduction in the RR tracking information in a continuous way. Analysis of the substitution process in primary care settings and hospitalization led to similar increases in transmissibility. In that short period of time, the inferred RR in hospitalization is consistent with those observed ecologically before and after the substitution of delta by omicron. In other words, with an effective RR of around 0.34, the substitution analysis leads to an RR that is similar to those observed in the different subgroups in the ecological analysis.The substitution model has the limitation of considering the same time frame for both variants. Despite this assumption, this model has been successfully applied to the substitution process of alpha and delta variants in the past . It provth of December 2021, and its administration remained very high up until mid-January. The number of individuals aged >10 with two doses increased only from 82%, at the beginning of the study period (01 November 2021), to 85%, at the end (25 January 2022), mainly due to an increase in children coverage. On the contrary, the increase in booster coverage in the Catalan population older than 10 years was 2% at the beginning and 45% at the end of the study period. This leads to a low level of boosted individuals for the delta period (596) that represents a similar percentage (1.2%) of the overall number of cases detected during the delta period. This indicates the necessity to divide the cohorts in different vaccination statuses to check that all of them show a reduction in severity, but it is a limitation in the purely substitution model since the average hospitalization can be affected by the protection of the third dose.An important feature that did change during the period of the study is the number of people with a booster dose in the general population. The booster dose was available only to a reduced number of high-risk groups in September 2021. From November 2021, it was made available for the whole population at different stages depending on age and previous vaccine platform. The actual peak of third-dose administration happened just before Christmas in the Catalan Health System, the 18Regarding whether the decrease in severity compensated for the increase in transmission in terms of the resources needed to face the epidemics, we observed that ICU admissions did not grow as a consequence of the substitution process and were thus compensated for, but did not compensate for general hospital admissions, as they did continue to grow. We must stress that this result is dependent on the particularities of the Catalan situation. First, it depended, necessarily, on the level of vaccination and population immunity since both strongly affect the level of protection against severe disease for a given number of cases –16. In tFinally, an important question arises regarding how useful this information may be in preparing health services for future waves. In this sense, we must stress that the ratios we present here are highly dependent on the particularities of the Catalan Health Care System. In other countries and areas, the ratio of hospitalization and ICU admission could be very different due to different diagnostic abilities , differeOur study has important strengths. The large sample of first detected infections used in the study plus the fact that two very different methodologies provided comparable results regarding the average reduction in severity lends a significant robustness to our main result. Furthermore, the ratios obtained here can be used as general guidelines in the future as long as the omicron variant is dominant. They can also be critically compared and used in other countries. Continuously tracking these ratios and analyzing their deviations from the data presented here could be very useful, and they could be interpreted as warning signs if the ratios were to increase above the general baseline observed in this study.https://analisi.transparenciacatalunya.cat/browse?q=covid&sortBy=relevance and https://dadescovid.cat/descarregues. Hospital lab information on variants is all included in the tables.The datasets regarding cases with its vaccination status, age cohort and sex are publicly available in The studies involving human participants were reviewed and approved by CEIC Hospital Germans Tries i Pujol, Badalona, Spain (Project Code PI-22-131) and the Hospital Universitari Vall d'Hebron Clinical Research Ethics Committee (2022-533), Barcelona, Spain. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.MC: conceptualization, formal analysis, visualization, methodology, and software. EC: data curation, conceptualization, methodology, software, and writing—original draft. SA: conceptualization, formal analysis, methodology, and writing—original draft. CA: methodology, data curation, investigation, and writing—original draft. AA: methodology, data curation, and investigation. IB, AB, and VS: data curation and investigation. P-JC: data curation and validation. FF and MM: data curation, methodology, and formal analysis. EM: methodology and investigation. NM: formal analysis, methodology, and investigation. CP: conceptualization, data curation, formal analysis, supervision, and funding acquisition. DP-A: conceptualization, supervision, and writing—original draft. EA-L: conceptualization, formal analysis, supervision, project administration, and writing—original draft. All authors critically reviewed and edited the draft and approved the final draft.MC received funding from la Caixa Foundation ID 100010434, under agreement LCF/PR/GN17/50300003. MC, CP, and SA received funding from Ministerio de Ciencia, Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00.EA-L, CP, and SA report a relationship with Janssen-Cilag SA that includes consulting or advisory. DP-A reports a relationship with Amgen Inc that includes consulting or advisory, funding grants, and speaking and lecture fees. DP-A reports a relationship with Chesi-Taylor that includes funding grants. DP-A reports a relationship with Novartis AG that includes funding grants. DP-A reports a relationship with UCB Biopharma that includes consulting or advisory, funding grants, and speaking and lecture fees. DP-A reports a relationship with Astellas Pharma Inc that includes consulting or advisory. DP-A reports a relationship with AstraZeneca that includes consulting or advisory. DP-A reports a relationship with Johnson and Johnson SA that includes consulting or advisory. Janssen, on behalf of IMI-funded EHDEN and EMIF consortiums, and Synapse Management Partners have supported training programs organized by co-author DP-A's department and open for external participants. The remaining 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. 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P < 0.05). The abdominal fat yield in dietary paddy rice groups was higher than that of the control group (P < 0.05). There were no effects on the moisture, protein, and fat contents of breast and thigh muscle among the five treatments (P > 0.05). Compared to the control group, the breast muscle of geese fed the paddy rice had a lower L* value and a higher a* value (P < 0.05). Dietary paddy rice decreased the bill score of geese (P < 0.05). Geese in the paddy rice groups exhibited higher total starch digestibility than geese in the control group (P < 0.05). The digestibility of energy, crude protein, crude fat, crude fiber, NDF, and ADF did not differ between groups (P > 0.05). In conclusion, paddy rice is an excellent energy source in geese diets and could improve the growth performance, breast muscle color, and utilization of total starch but increase the abdominal fat yield and decrease the bill color of geese.The aim of this study was to investigate the effects of dietary paddy rice on growth performance, carcass traits, bare skin color, and nutrient digestibility in geese. A total of 300 twenty-eight-day-old male goslings were randomly divided into 5 treatment groups with 6 pens containing 10 goslings each. The geese were raised for 42 d on feed with 0% (control), 13, 26, 39, or 52% dietary paddy rice inclusion. Body weight and feed intake per pen were recorded from the arrival of goslings to the end of the trial. On d 70, two goslings were selected from each pen, one of which was used to measure slaughter performance, meat quality, meat proximate composition, and bare skin color, and one was used to determine nutrient utilization. The results showed that goslings fed a diet containing 26, 39, and 52% paddy rice had a higher final body weight, average daily feed intake, and average daily gain than those in the control group ( Corn is the main energy source in the poultry diet, accounting for approximately 60% of feed ingredients . Currentindica rice is widely planted in southern China, where it is particularly predominant as an early-season crop   . Geese h-glucan) . The uni-glucan) .Therefore, the objective of this study was to investigate the effect of replacing corn with different concentrations of paddy rice on growth performance, carcass traits, bare skin color, and nutrient digestibility in geese.All animal care and experimental procedures in this study were performed in accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals of the People's Republic of China and approved by the animal care and use committee of Yangzhou University .indica rice, the first season paddy rice on the market, was selected as the experimental raw material. The paddy rice harvested in July 2019 was obtained from Shangrao City . Whole grains were crushed and formulated into the diet. The chemical compositions of the paddy rice and corn are shown in Early indica rice inclusion. These experimental diets (mash form) were formulated to be isonitrogenous and isocaloric and meet or exceed the nutrient requirements of geese according to the This experiment was conducted at Yangzhou University Experimental Farm  from October to December 2019. Three-hundred 28-day-old healthy male Jiangnan White goslings were obtained from a commercial hatchery . The goslings were all of similar body weights and were randomized to 5 groups that included 6 replicates per treatment and ten goslings per replicate. The geese were raised for 42 d on feed with 0% (control), 13, 26, 39, or 52% dietary early ADFI), average daily gain (ADG), and feed-to-gain ratio (F/G) were calculated at the end of the experiment. At d 70, one goose in each replicate with the average BW of the replicate was selected and exsanguinated after fasting for 6 h. After bleeding and plucking, the weight was recorded as the carcass weight. The geese were then eviscerated, and the semi-eviscerated carcass, eviscerated carcass, breast muscle , leg muscle (thigh and drumstick), and abdominal fat (fat around the abdomen and gizzard) were weighed. The semi-eviscerated weight was calculated by removing the trachea, esophagus, intestines, spleen, pancreas, gallbladder, reproductive organs, and gizzard contents and corneum from the carcass. The eviscerated weight was calculated by removing the heart, liver, proventriculus, gizzard, lungs, and abdominal fat from the semi-eviscerated carcass. The carcass, semi-eviscerated carcass, eviscerated carcass, breast muscle, thigh muscle, and abdominal fat percentages were calculated relative to the live BW before slaughter. After weighing, the major part of left breast and leg muscles  were immediately divided into 2 pieces along the direction of muscle fibers. One part was stored at 4°C for measuring meat quality, and the other part was frozen at −20°C until analysis of the meat proximate composition. Additionally, the yellowness of the goose bare skin, including the flipper and bill, was scored.The feed intake was measured in replicates on a daily basis, and the BW of goslings was recorded at 28 and 70 d of age. The average daily feed intake  system values of lightness (L*), redness (a*), and yellowness (b*). The pH value was recorded 45 min after slaughter using a portable pH meter . According to the method of The meat color was measured at 45 min postmortem with a chroma meter  and reported according to the Commission Internationale de l'Eclairage , so this was chosen as the scoring standard. The higher the color score is, the more yellow the bare skin color; the lower the score is, the paler the color. Then, the goose flippers and bills were scored by comparison with the color chart.The chemical composition of meat samples was analyzed according to the procedures set forth by the Association of Official Analytical Chemists . Crude mNDF) and acid detergent fiber (ADF) were determined sequentially as described by diet − Excreta output × Nutrientexcrement)/(Feed intake × Nutrientexcrement) × 100%.All chemical analyses  were performed in duplicate. Gross energy was determined using a Parr 6100 oxygen bomb calorimeter  standardized with benzoic acid. The crude protein and crude fat contents in the diets and excrement samples were determined as described in the muscle above. The contents of crude fiber of the samples were determined using SEM). Differences were considered statistically significant at P < 0.05.SPSS version 22.0  was used for data analysis. All data were tested for normal distribution by the Kolmogorov-Smirnov test. The flipper score data were not normally distributed, and they were analyzed by the nonparametric Kruskal-Wallis test. The data of other indicators were normally distributed, and they were subjected to one-way ANOVA. The significant differences between treatments were detected by Duncan's multiple range tests. Each replicate pen served as an experimental unit for all statistical analyses. When Kruskal-Wallis tests were used, the results are expressed as medians (interquartile range) and presented in figures with box plots ; other data are presented as the mean value and standard error of the means (P < 0.05). However, increasing dietary paddy rice did not affect the F/G during the whole experimental period (P > 0.05).The BW, ADFI, ADG, and F/G of geese fed graded concentrations of dietary paddy rice are shown in P < 0.05). There were no effects on carcass yield, semi-eviscerated yield, eviscerated yield, breast muscle yield, or leg muscle yield (P > 0.05).As shown in P > 0.05).The effect of dietary paddy rice on the proximate composition of the breast and thigh muscle of geese at 70 d is shown in P < 0.05). However, the b* value, pH value, cooking loss, and shear force were not affected by dietary paddy rice (P > 0.05). There were no effects on the meat quality of thigh muscle among 5 treatments (P > 0.05).The meat quality of the breast and thigh muscles of the geese is presented in P > 0.05; P < 0.05; P < 0.05); and the 26% dietary paddy rice group had a higher bill score than 39 and 52% dietary paddy rice groups (P < 0.05). The higher the color score is, the more yellow the bare skin color; the lower the score is, the paler the color.A Kruskal-Wallis test showed that dietary paddy rice did not significantly affect the bare skin score of the flipper (P < 0.05). However, the utilization of other nutrients, including energy, crude protein, crude fat, crude fiber, NDF, and ADF, did not differ between groups (P > 0.05).As shown in To alleviate the increasing global demand for corn, many types of grains are being used to replace corn as a source of energy in feed. For poultry, paddy rice is an excellent energy source among many grains. Slaughter performance is an important index to evaluate the meat production capacity of livestock and poultry, which can directly reflect the differences in nutrient deposition in different parts and tissues of animals. In the present study, carcass yield, semi-eviscerated yield, eviscerated yield, breast muscle yield and leg muscle yield of the geese did not change with increasing dietary paddy rice, indicating that deposition of material in these parts was synchronized with the increase in BW. In this study, however, abdominal fat yield in dietary paddy rice groups was higher than that of the control group. The reason may be related to the difference in proportions of starch fractions and starch granule size in the diet. Rice has more rapidly digestible starch and less slowly digestible starch and resistant starch than corn . Moreovelongissimus thoracis muscle of pigs.However, increased abdominal fat was not related to a higher intramuscular fat content . This suMeat quality is closely related to the marketing of meat as well as its processing. For consumers, color and overall appearance are the initial criteria affecting preference when purchasing raw meat products. Higher a* values and lower L* and b* scores mean less pale meat and better quality . In the People in some regions of China prefer to buy live birds and therefore pay more attention to the appearance of the goose, especially the color of the flipper and bill. In this study, the replacement of dietary corn with paddy rice resulted in a lighter yellow coloration of the bill of goslings. Similar results were reported for broken rice by In summary, goslings fed a diet containing 26, 39, and 52% paddy rice had a higher final BW, average daily feed intake, and average daily gain than those in the control group. Paddy rice improved the breast muscle color and the utilization of total starch but increased the abdominal fat yield and decreased the bill color of geese.


Nitrite and nitrate intake through food and water may be an important risk factor for many cancers, including glioma. However, the association of nitrite and nitrate with glioma is unclear.This review aimed to quantitatively assess the effects of nitrite and nitrate on glioma by meta-analysis.A literature search was conducted for available articles published in English using the databases of Embase, Web of Science, PubMed, Medline, and the Cochrane Library up to 24 March 2022. According to heterogeneity, the fixed-effects or random-effects model was selected to obtain the merger’s relative risk (RR). Based on the methods described by Greenland and Longnecker, we explored the dose-response relationship between nitrite/nitrate and the risk of glioma. Subgroup analysis, sensitivity analysis, and publication bias tests were also used.This study reviewed 17 articles, including 812,107 participants and 4,574 cases. For glioma in adults, compared with the lowest intakes, the highest intakes of nitrite significantly increased the risk of glioma :1.09-1.47). For brain tumors in children, compared with the lowest intakes, the highest intakes of nitrate significantly increased the risk of brain tumors . The results of subgroup and sensitivity analyses remained unchanged. In the dose-response relationship, per 1 mg/day increase in nitrite intake increased the risk of glioma by 14% .Our analysis suggests that nitrite increases the risk of glioma in adults, while nitrate increases the risk of brain tumors in children. Therefore, the effects of nitrite and nitrate on glioma cannot be ignored.https://www.crd.york.ac.uk/prospero/, identifier CRD42022320295. Compared with other types of cancer, the incidence of brain tumors is low, with an annual incidence of only 22.6/100,000. But primary brain tumors are one of the leading causes of death from cancer, accounting for about 13,000 deaths each year. And one in 1,300 children under the age of 20 is diagnosed with a brain tumor each year . TherefoBut so far, only ionizing radiation has been considered an established risk factor for glioma , 6. For To quantitatively assess the association of nitrite and nitrate with glioma, we searched all published observational studies on nitrite or nitrate and glioma, using dose-response meta-analyses to quantify the association between nitrite or nitrate intake and the risk of glioma to explore further evidence for the effect of nitrite or nitrate on glioma.3” OR “NO2” OR “nitrosamine” OR “nitrite amine” combined with “glioma” OR “brain cancer” OR “brain tumor”. Other databases also referred to the same retrieval strategy for literature search. Two investigators searched for relevant articles during the retrieval process and independently reviewed all retrieved studies without document type, language, or other applicable restrictions, and unpublished articles were excluded.A literature search was conducted for available articles published in English using the databases of Embase, Web of Science, PubMed, Medline, and the Cochrane Library up to 24 March 2022. The Cochrane Library search terms used for the title, keywords, and abstract were “nitrite” OR “nitrate” OR “N-nitroso compounds” OR “NOFor inclusion, studies had to fulfill the following criteria (1): the exposure of interest was nitrite or nitrate intake. These studies provided daily intake of each food or total intake of a food group through food frequency questionnaires or dietary records, and the dietary survey methods were tested for reliability and validity or had been used in previous studies. The individual exposure was calculated based on the unit content of nitrite or nitrate in each food reported in local government reports or published articles; (2) the outcome of interest was glioma in adults; we also considered childish patients, but because most childish patients in the current study had brain tumors as the outcome, the outcome of interest was considered brain tumors when the subjects were children; (3) the study type was observational; (4) the exposed population was adults; pregnant women were exposed in the childhood brain tumor study. Since there were few studies evaluating nitrite and nitrate exposure in children when evaluating the association of nitrite and nitrate with brain tumors in children, the exposed population should be pregnant women, that was, to assess the association between nitrite and nitrate of pregnant women during pregnancy and the risk of brain tumors in offspring.The exclusion criteria of the meta-analysis were as follows: (1) non-observational study ; (2) effect size or 95%CI could not be obtained; (3) animal experiments and cell experiments; (4) if there were multiple studies used the same population, we excluded studies with smaller sample sizes.Two investigators independently assessed eligibility based on inclusion criteria and data extraction. Disagreements were discussed and resolved by a third investigator. For selected studies, data included study characteristics: the first author, year of publication, country, study population (adults or children), study type (cohort study or case-control study), age, disease (glioma or brain tumor), sample size, number of cases, exposure source (food or water), exposure type (nitrite or nitrate), exposure dose, effect size (OR or RR), and 95%CI extracted from the most adjusted model.The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the quality of the included studies. It was scored independently by two investigators and was discussed by a third investigator in the event of disagreement. Scores ranged from 0 to 9 .2I statistic. In the heterogeneity analysis, P-values less than 0.1or 2I greater than 50% were considered to be statistically significant heterogeneity. Pooled estimates based on random-effects models were reported when considerable heterogeneity was detected. Otherwise, pooled estimates based on fixed-effects models were reported. We used these two effect models to calculate pooled RRs and 95% CIs for the highest and lowest nitrate or nitrite intake categories for analysis. In addition, subgroup analyses were performed according to study population (American population and other populations), study design (case-control study and cohort study), study quality (≤7 and >7), and source of exposure (food and water). We used sensitivity analysis to assess each study’s relative impact on the total effect size by successively omitting one study when determining the effect size. To detect publication bias, Egger’s test and Begg’s test were used.The possible heterogeneity in study results was examined using Cochran Q and quantified by the Subsequently, we also explored the dose-response relationship between nitrite/nitrate and the risk of glioma in adults and the dose-response relationship between nitrite/nitrate during pregnancy and the risk of brain tumor in offspring. This study analyzed the dose-response relationship using a method developed by Greenland and Longnecker . For thiP-values were 2-sided with a significance level of 0.05.All data analyses were carried out by Stata14.0. Characteristics of the 17 included articles are shown in 2 =I0, for heterogeneityP =0.601)    , the cohort study subgroup , and the study quality score >7 subgroup . Nitrate had no statistical significance in each subgroup, which was consistent with the overall combined results. However, in the study type subgroup, its heterogeneity decreased from 9.1% to 0 Table 3.For brain tumors in children, nitrate was statistically significant in the other population , the study quality score ≤7 subgroup , and the water subgroup . And in the subgroup of the study population, the heterogeneity decreased from 39.0% to 0. Nitrite had no statistical significance in each subgroup, which was consistent with the overall combined results Table 3.The effect of individual studies on the overall RR was assessed by repeating the meta-analysis after removing each study in turn Table 4.P-values were >0.1, indicating that the difference was not statistically significant, so the publication bias of this study was not significant . However, the results were not significant for the dose-response relationship between nitrate and brain tumors in children .Due to the limited number of available articles, 7 articles could only analyse dose-response relationships. The dose-response relationship between nitrite intake and the risk of glioma in adults was shown in Based on 17 observational studies on nitrite/nitrate and gliomas published from 1993 to 2021, involving 812,107 participants and 4,574 cases, our meta-analysis results suggested that nitrite could significantly increase the risk of glioma in adults, while nitrate could significantly increase the risk of brain tumors in children. However, nitrate had no significant effect on gliomas in adults, and nitrite had no significant effect on brain tumors in children. For the results of the dose-response relationship, per 1 mg/day increase in nitrite intake was associated with a 14% increased risk of glioma.We performed subgroup analyses based on the study population, study type, study quality, and source of exposure to explore sources of heterogeneity. For gliomas in adults, nitrite heterogeneity was 0, suggesting that pooled results were robust and significant in most subgroups. The heterogeneity of nitrates might be mainly due to differences in study types. Five of the seven studies were case-control studies, and dietary survey methods specifically assessed nitrate intake. These case-control studies used the food frequency questionnaire method was used to conduct dietary surveys, which may cause some heterogeneity due to recall bias. For brain tumors in children, differences in the study population may be a source of heterogeneity in nitrates. In the subgroup of the study population, the heterogeneity decreased from 39.0% to 0. Since most nitrates in the study came from drinking water, it might be due to the different concentrations of nitrate in water in different regions. For nitrite, heterogeneity decreased slightly when Pogoda’s study was excluded, which may be related to the relatively low quality of the study. Sensitivity analysis showed that most of the study results were stable. No publication bias was found in all studies.2 =I0) and nitrate  and glioma was not significant, but the number of this study was small, and only three articles were included. Therefore, this might not contradict our results , whereas nitrate did not have similar results . This was not the same as the results of the previous meta-analysis. In this study, the relationship between nitrite , analysis of the effects of nitrite and nitrate on glioma subtypes was not possible. Secondly, nitrite and nitrate exposure were quantified mainly through dietary surveys, which could not avoid bias caused by recall. Most studies on the determination of nitrite and nitrate content in food and water were based on government testing or literature reports, moreover, most of the studies only evaluated the exposure of a certain pathway, which seemed to be unable to represent the overall exposure level of the population. In the future, the association of biomarkers of nitrate and nitrite exposure The current meta-analysis suggests that nitrite increases the risk of glioma in adults, and nitrate increases the risk of brain tumors in children. Therefore, the effect of nitrite/nitrate on glioma cannot be ignored. In future studies, we should find a method to evaluate nitrite/nitrate exposure accurately and further explore the relationship between nitrite/nitrate and glioma.The original contributions presented in the study are included in the article/WL and WZ contributed to the conception or design of the work. WZ, JJ, and YH contributed to searching the databases. WZ, JJ, and XL contributed to the acquisition, analysis, or interpretation of data for the work. WZ, XL, and SY proofread and modified the language. WL and FC reviewed and edited the manuscript. All authors contributed to the article and approved the submitted version.This study was supported by the Special Research Project of Capital Health Development 2016 (No. 2020-2-2048) and National Science and Technology Major Project of China (No. 2016ZX09101017).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.


Background: The environment of semiconductor facilities and exposure status has undergone changes. To identify changes in the work environment, health status, and risk factors, a qualitative and cross-sectional study was conducted. Methods: For the qualitative study, 38 current and retired workers who worked for at least 10-years were studied; for the cross-sectional study, 306 current workers who worked for at least 5-years based on JEM strata from Samsung Electronics were selected. Participants were asked about occupational history, cancer-relating risk factors during the working period, medical history, dietary habits for the past year, and hematological cancer-relating infection. Results: In the qualitative study, fabrication workers reported bladder cystitis, dermatitis in hands, gastritis/ulcer, and dry eye as frequent symptoms during work environment changes . In the cross-sectional study, there were no abnormal findings for infection biomarkers related to hematological cancer and spontaneous abortion, and their general health status was no different from the general population. Also, questionnaire feasibility was evaluated for the applicability in the prospective cohort. Conclusion: Current semiconductor workers’ health status was good compared to other populations. For lifelong health assessment, a cohort study is needed which considers health worker effects and current environments. In the 1980s, as an occupational disease, the risk of spontaneous abortion among semiconductor workers was first reported ,4,5,6,7.In June 2007, a female worker who was employed at a Samsung Electronics semiconductor facility died of leukemia, and five additional similar cases were reported where workers and their bereaved families initiated work-related lawsuits. They were all people who worked during the 1990s and 2000s. Consequently, the Korea Labor Welfare Corporation, the Ministry of Labor requested an epidemiological investigation for the evaluation of work-relatedness to the Occupational Safety and Health Research Institute (OSHRI) and Korea Occupational Safety and Health Agency (KOSHA). In 2019, an Epidemiological investigation from the OSHRI showed that the hematopoietic cancer of workers was related to semiconductor works but needed to be interpreted carefully due to the detection bias and the low number of rare disease cases . Along wHowever, the current semiconductor work environment may be different now, compared to the past, so it is necessary to understand the environment changes from the past to the present. Thus, a qualitative study was conducted based on the current and retired workers whose employment period was higher than 10 years in a focus group interview. Additionally, we conducted a cross-sectional study to evaluate the health status and possibly related factors in the current semiconductor works. In the cross-sectional study, both questionnaire and the infection status , and Ebstein-Barr virus (EBV) were assessed according to the semiconductor job categories. Finally, in advance of conducting a prospective cohort study on the overall semiconductor workers, this study tried to verify the usefulness of the questionnaire tool.In advance of the focus group interview, participants were asked to fill out a self-reported questionnaire about their occupational histories such as processes, occupational substance use, and common diseases in each group. The main questions were: (1) What was the environment in which workers worked in the past? How is it different from the present? (2) Have you ever been exposed to odors, air quality, or environmental exposure substances in the past and present working environments? (3) How was your shift work? (Please explain if it is different from what is indicated on the questionnaire). Isn’t shift work difficult? (4) If there have been any clusters of symptoms or diseases that have occurred to you and your co-workers from the past to the present, please tell me as much as you can remember. For the interview, each group and interviewer attended the meeting and talked freely for about 30 min to 1 h to answer the main questions. The interview contents were recorded with the consent of the participants, and the recorded contents were organized into scripts. The qualitative study analysis was conducted as terms first and then in phrases. After that, the data were analyzed according to each group. The details of the questions are described in To collect the information, semiconductor workers were asked to visit a separate place for the research. Because of their shift work patterns, research consent with a reported questionnaire was obtained one hour before their work time. All of the workers completed the questionnaire by themselves first, if there was any non-responded questions or they could not understand the question, the research assistant helped with the answer. If some questionnaires needed additional work, it was checked after the shift work. In addition, 15 mL of workers’ blood and urine were collected to assess their infection status along with an assessment of occupational substances. As collection items, the subcontractor workers collected urine only. As a detailed questionnaire item, occupational history including employment period, shift work pattern, fab work status, individual disease history including cancer, drug, medical radiation exposure status, lifestyle factor including smoking, drinking, and physical activity, and their dietary habits. Occupational history was reported by the semiconductor workers themselves, but detailed processes, job duty, and factory district were referred to in the current facilities records at the human resource department. In the case of personal disease history, the workers reported by themselves, but was based on the diagnosis of diseases at the medical center or the health examination center. For their dietary habits, we identified their food consumption by the food frequency questionnaire and their usual eating habits. The individual’s infection status was confirmed by hepatitis B virus (Chemiluminescent Microparticle Immunoassay), hepatitis C virus, HIV-1, H. Pylori , and EBV (Sandwich ELISA) based on the blood samples.p-values for the differences were presented.We classified semiconductor workers into seven groups as follows: (1) Office work (men and women), (2) Assembly work (men and women); (3) Operators (women); (4) LCD workers (men); (5) Engineers working for non-implant semiconductor processes (men); (6) Engineers working for ion-implant (men) (Employed under Samsung Electronics); (7) PM engineers (ion-implant process employed in subcontractor workers). Detailed statistical analysis, overall, and seven groups were described using the mean, median for continuous variables, and proportion for categorical variables. Differences in distribution among the seven groups were tested using analysis of variance for continuous variables and chi-square test for categorical variables, and In the process of the study population selection, both qualitative and cross-sectional studies were considered six basic criteria and constructed a group according to criteria to identify the overall and the eligible number of semiconductor workers. First, (1) semiconductor workers were classified as current, retired, and subcontractor workers. Then (2) identify each worker’s work district, and (3) identify non-fab, fab, LCD, and assembly work in large job categories. Next, (4) their detailed job duty and specific processes would classify and (5) divided the workers according to the gender. Lastly, (6) the group is divided according to their employment period into two  or three groups  .Accordingly, the eligible subjects were extracted by stratified random sampling with unequal probabilities without replacement, then we asked workers if they agreed to participate as subjects in this study. In addition, the study population of the cross-sectional study was selected by considering workers’ shift work, and the ratio was 1:1:1 in each shift work Day (06:00–14:00), Swing (14:00–22:00), Graveyard . However, for the retired and subcontractor workers included in the qualitative study and subcontractor workers in the cross-section study, their overall and eligible subjects could not confirm. In the case of the retired workers, due to the personal information protection act in Korea, we could not get any personal information such as addresses or contact numbers. In the case of subcontractor workers, there was a social issue of companies laying down the law for the workers. Therefore, the semiconductor facility could not ask for detailed information from subcontractor workers directly. Thus, research consent was the primary role of the research participation. After that, only agreed subcontractor factories and their workers could include in the study population. According to the process, there were 4594 eligible subjects in the qualitative study, and 32 workers (0.7%) were randomly selected, and six retired and subcontractor workers were non-randomly included in the study population (38 participants). In the cross-sectional study, there were 8059 eligible subjects, 239 current workers (3% from Samsung Semiconductor Electronics population) were selected, and 67 (11.2% from the subcontractor population) out of 596 subcontractor workers were selected as the study population (306 participants). We described the detailed eligible subjects in each group in There were 26 males and 12 females in the qualitative study aged in their 40s and their dialogues are described in In the case of the cross-sectional study, there were 220 males and 86 females , with a median age of 36 years . As occup < 0.05). Only men workers used e-cigarettes, which was higher in PM workers (18%) than office workers (4%) (p = 0.06). The lifetime drinking prevalence (the fraction of people who drink in the past and present) and the current drinking rate were 84% and 82%, respectively (Current drinking rates); and there was no significant difference in a lifetime and current drinking rates across the groups. Among the drinkers, the proportion of drinking more than 4 times per week was 22%, which was 32% and 27% in the non-implant group and PM engineers group, respectively, which was higher than that of the office workers (23%) (p < 0.05). In the case of physical activities, there was a difference between groups in both high and moderate intensity (p < 0.05), and the LCD and non-implant workers showed the highest rate among the groups.As individual lifestyle factors, we assessed smoking status, alcohol consumption and physical activity . Currentp = 0.07). The co-morbidity of two or more Fab-related diseases was highest among operators (23%), and the co-morbidity of two or more cardiometabolic diseases was highest among office workers (21%). Additionally, we described the detailed diseases list of compensation from Samsung Electronics in p < 0.05) (p < 0.05) (p < 0.05).The diseases consisted of cancers, rare diseases, and reproductive diseases. Similar to qualitative study, the most common diseases were gastritis or gastroduodenal ulcer (16%) and dermatosis  in the cross-sectional study. In men, gastritis or gastroduodenal ulcer (11%) was the most common, and gastritis or gastroduodenal ulcer (20%), cystitis (14%), and dermatosis (14%) were observed in women. We hypothesized that family histories of diseases could be related to compensation and common diseases observed in workers, but no statistically significant difference was observed between groups. Gastroduodenal ulcer, dermatosis , cystitis, and dry eye, could be classified as ‘Fabrication-relating diseases’, hypertension, hyperlipidemia, diabetes, angina pectoris, fatty liver, and liver disease  were classified as cardiometabolic diseases. In the survey on personal medical history, 17% of the total subjects had multi-morbidity for two or more diseases. Across the working group, office workers had the highest multi-morbidity (38%), and the PM engineers and implant workers had the lowest multi-morbidity (7% and 5%), respectively  . Specifi < 0.05) . Additio < 0.05) . In the  < 0.05) . In mediIn this study, semiconductor workers were classified and selected according to the JEM. Also, we assessed changes in the semiconductor working environment from past to present based on a qualitative study. In addition, by the cross-sectional pilot study, long-term employment semiconductor workers were classified by JEM and assessed their occupational, lifestyle , history and comorbidity of individual diseases, carcinogenic infection, and reproductive history. There was no difference between the groups, but some patterns were identified as semiconductor workers’ unique characteristics.From the qualitative study, the health impact of the working environment was evaluated in both current and retired workers. Along with the change of the wafer size from the 1980s (4-inch) to 2000s (12-inch), the work environment had changed significantly due to fully automatic processes from some manual processes. Firstly, workers stated that TCEs were used directly as substances for cleaning or dissolving oil on their hands in the past. Second, due to the no spatial separation between processes, workers could be exposed the hazardous substance even they did not handle the material. However, it is difficult to generalize the situation to all workers, and there is a limit to reconstructing the actual exposure situation.As is known, some diseases are reported mainly in semiconductor workers ,15. FromH. pylori in semiconductor workers were lower than those in Korean general population. The Korea National Health and Nutrition Examination Survey (KNHANES) in 2017 reported that the infection rates of hepatitis B virus (HBV) (measured by HBsAg) and hepatitis C virus (measured by anti-HCV antibody) were near 3% and 0.3–0.6% in people aged 30–49 years, respectively [H. pylori (measured by H. pylori IgG antibody) in Korean health examinees derived from 21 health screening centers were near 51%  [The selected infectious agents are known to be associated with several cancers ,22,23,24ectively . In cont, 48.8%) , but thoWhen we compared lifestyle factors, the current smoking rate in semiconductor workers was 42%, and it is the same rate in the general population (42%). However, the smoking rate among subcontractor workers was 79%, which is more than the general population. Semiconductor workers reported that 22% of workers drink alcohol over 4 times a week. In the general population, 7.1% of those in their 30s and 7.2% of those aged in their 40s reported drinking alcohol over four times a week. In men, 8.8% in their 30s and 11.3% in their 40s and in women, 5.2% in their 30s drink alcohol over 4 times a week. Therefore, it seemed that semiconductor workers consumed higher levels of alcohol than the general population.In the KNHANES, 5.9% of female workers over the age of 19 experienced a spontaneous abortion, and 6.5% of those with shiftwork . HoweverWhen we assessed the specific dietary habits in semiconductor workers, their rate of skipping meals was a little bit higher than that of the general population . In the One of the purposes of this study was to assess the usefulness of the questionnaire and further use it in the cohort study on overall semiconductor workers. First, this questionnaire was constructed specializing in semiconductor workers which referred to the KNHANES and other national cohort studies. Through this, lifestyle status and others can compare to the Korean general population. In the case of individual disease history, questions were organized focusing on diseases that are mainly complained about by the semiconductor workers from previous studies or qualitative studies. Second, we assessed the response rate of the questionnaire. In this study, the non-responder in each question was lower than two participants  and the overall non-response rate was lower than 5%. Third, we compared the concordance between the self-reported answer from the semiconductor workers and the answer when the interviewer asked the semiconductor workers. Thus, all of the answers were correct. Therefore, we concluded that this questionnaire is useful for semiconductor workers. In particular, the healthy worker effect should be considered in occupational epidemiology. First of all, defining the suitable comparison group to semiconductor workers is needed . PreviouAs a limitation, identifying actual past occupational exposures and frequent diseases is limited because of individual opinions and the small number of volunteers in a qualitative study. In addition, factors such as radiation, magnetic exposure, and thermal decomposition products that are difficult to perceive for humans could not be assessed. Occupational or other risk factors were identified in the cross-sectional study, and information on environmental exposure was limited to the current exposure. Due to the selected PM engineers from the subcontractors, the distribution of factors and diseases may be deviated results compared to the total number of PM engineers. Even various strata of JEM were considered to select the study population, the possibility of misclassification could be existed due to the diverse semiconductor process. In addition, to fully assess the exact time of change in the semiconductor environment and cancer incidence considering their latent period, more workers who have long-term employment are needed. Nevertheless, this qualitative study confirmed the possibility that the past occupational exposure situation may be different from the present and the exposure intensity may be higher. It was also possible to list the diseases that are likely to occur in the special environment workers of fabrication. The cross-sectional study confirmed the acceptability of a questionnaire that could be used in future cohorts of semiconductor workers.This study was the results of a qualitative survey based on 38 current and retired workers with at least 10 years of employment period and a cross-sectional pilot study from 306 current workers with at least 5 years of employment period. Diseases mainly reported in qualitative studies were also reported in the cross-sectional study, and through the information, we could identify common diseases under the current semiconductor environment. Compared to the general population, semiconductor workers’ medical, lifestyle, dietary behavior seemed to be similar or better. However, it cannot be generalized as a health effect on the overall semiconductor workers, so careful interpretation is needed. Also, the healthy worker effect should be considered for interpretation due to the fact that current workers comprised the majority of the study population. Additionally, based on the survey response rate, comparison of the response rate between the self-administrated questionnaire and the interviewed questionnaire, and non-concordant response rate, a semiconductor targeted questionnaire could apply in further prospective cohorts. Along with this, a prospective cohort design construction could establish a system that can check the risk signals of semiconductor workers through continuous health and exposure investigation and information construction. In advance of the construction of the cohort study, detailed improvement should be taken in the semiconductor environment such as in cleanroom garments and their specific patterns.


Parkinson's disease (PD) causes movement disorders [called motor symptoms (MS)], and motor dysfunction poses a great barrier to the quality of life. Although pharmacological therapy like levodopa can relieve the symptoms, it can also cause complications, such as psychosis, nausea, and dyskinesia. A therapy with more minor side effects is needed for PD. Therapeutic massages are the most commonly used forms of complementary and alternative medicine (CAM), but no systematic review and meta-analysis have focused on the efficacy of massage on PD.To evaluate the quality of evidence and efficacy of therapeutic massage for improving MS in PD.I2 was used.We independently searched four electronic databases, including Chinese National Knowledge Infrastructure (CNKI), MEDLINE/PubMed, Embase, and Cochrane Library, for randomized controlled trials (RCTs) about therapeutic massage and other available manual therapies improving MS in PD from January 1, 2012, to December 31, 2021 (recent 10 years). The main outcome measures were total effectiveness and the Unified Parkinson's Disease Rating Scale (UPDRS), including UPDRS total, II, and III. For the statistical analysis, the risk ratio, standard mean difference, and 95% confidence interval (CI) were used to calculate effect sizes between groups. To determine heterogeneity, statistical index p = 0.0002]. The UPDRS-III scores showed that massage improves motor function more than the control group . But we found that massage performed no better than the control group in improving daily life activities .A total of 363 PD participants in seven RCTs and one randomized pilot-control study were included in this meta-analysis. The total effectiveness showed that therapeutic massage was more effective than the intervention of the control group for improving MS [ratio risk (RR): 1.33, 95% CI (1.14–1.55), Therapeutic massage was effective in improving MS in PD. It is suggested to be an appropriate form of CAM in treating PD.https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=323182, identifier: CRD42022323182. Parkinson's disease (PD) is a neurodegenerative disorder that progressively damages multiple organ systems in the human body. In Europe, the annual incidence of this disease ranges from 13.5 to 18.8 per 100,000. Therefore, the common opinion is that the prevalence of PD ranges from 1 to 2 per 10,000 . The decNowadays, the mainstream therapy for PD is drugs. As first-line treatments for MS in PD, monoamine oxidase B inhibitors, levodopa, dopamine agonists, and amantadine have definite effectiveness . HoweverTherapeutic massage is a popular form of complementary and alternative medicine (CAM) worldwide , 12. ThaThis systematic review is registered with the PROSPERO database (CRD42022323182). This systematic review and meta-analysis followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement principles, using the population, intervention, control, and outcomes (PICO) model. Two reviewers (ZRK and HX) independently searched the following electronic databases (one Chinese database and three databases in English): Chinese National Knowledge Infrastructure (CNKI), MEDLINE/PubMed, Embase, and Cochrane Library. Searching terms for all the databases are displayed in Selected studies fulfilled the following inclusion criteria: (1) randomized control trials (RCTs) or randomized pilot studies, (2) certainly diagnosed PD participants with MS, (3) the experimental group including the intervention of manipulation therapy alone, (4) the control group that received basic clinical care, rehabilitative therapy, or basic drug therapy while excluding any manual therapy, and (5) assessment mainly including UPDRS-III, then UPDRS total and II.Based on our design, the characteristics and data of our study were assessed and extracted. Two authors (ZRK and QL) independently extracted the following data from selected studies: first author and year, country, study type, patients' characteristics , the protocol of experimental and control groups, and outcome measures.Cochrane Handbook for Systematic Reviews of Interventions (V6.3) for risk of bias (Two authors (ZRK and HX) independently assessed the quality of each selected study using version 2 of the Cochrane risk-of-bias tool (ROB-2) outlined in Chapter 8 of the  of bias . The biap-value < 0.05 represented statistical significance.The analysis was run on the Cochrane Review Manager software v.5.4 (the latest version). UPDRS scores  were considered continuous data. We analyzed continuous data based on the standard mean difference (SMD). The total effectiveness was dichotomous data. For evaluation of dichotomous data, we used risk ratio (RR) and 95% confidence interval (CI). p < 0.1 represented heterogeneity between studies that had statistically significant differences. I2 tests were assessed for all outcomes in our study. We regarded I2 ≥ 75 as significant heterogeneity, I2 ≤ 50 as low heterogeneity, and I2 < 75 but >50 as moderate heterogeneity. When the level of heterogeneity was moderate or low, we used a fixed-effects model. Otherwise, we used a random-effects model. If the heterogeneity was high, we prepared to run sensitivity analysis and explained the potential reasons for heterogeneity. A funnel plot was established to explore possible publication biases if more than ten studies were in the analysis. Egger's test was used to test the asymmetry of the funnel plot . The fixed model was used. The results showed that the differences between therapeutic massage groups and control groups were statistically significant  . We used the fixed model. The results showed that after analyzing post-intervention data, therapeutic massage was significantly more effective than the control in improving MS  ; we used the fixed model. The differences were statistically significant between the therapeutic massage and control groups, implying that therapeutic massage was more effective in improving the overall condition of PD patients  ; we used the fixed model. After analyzing post-intervention data, there were no significant differences in daily living improvement between the therapeutic massage and control groups  . There were six RCTs and one randomized pilot study. The intervention of the experimental group was therapeutic massage, while that of the control group was basic drug therapy, clinical care, and health education. The test of homogeneity and several statistical tests were run in the meta-analysis. In total, 363 people with PD were included.To evaluate the motor function and symptoms in included PD patients, UPDRS-III became the primary outcome measure (POM); we regarded total effectiveness, UPDRS-total, and UPDRS-II as the secondary outcome measures for evaluating the efficacy and other aspects of the effect of therapeutic massage. All seven included studies used the UPDRS-III score to assess motor function , 26, 27.p < 0.05). It is important to mention that the standard of levels division of total effectiveness was based on the POM that the study chose and the calculation between baseline and post-intervention scores. The calculation formula of the standard was The meta-analysis results showed that therapeutic massage had significantly better efficacy than the control group , indicating that therapeutic massage could alleviate MS and improve motor function. The curative mechanism of massage was broadly discussed. During manipulation techniques performed on muscles of different body parts, it was proved that massage had a positive effect on muscle characteristics, including strength, tension, and extensibility, in several massage clinical trials on other diseases . The activities of daily life need the support of the motor function. The complex movement of the body makes up our life behavior. Interestingly, in comparison with the control group, therapeutic massage improved motor function well while hardly improving the quality of daily living. This phenomenon implied that improving motor function by therapeutic massage could not help PD patients perform their daily tasks well, making us view it rationally. After all, massage was a complementary therapy for diseases, and from this aspect, we thought it could not be the sole main therapy for PD. The direction of clinical trials may explore how to apply massage assisting first-line or regular therapy in enhancing motor function and daily life or letting massage mediate the reduction of adverse events of PD drugs.After the UPDRS-II score was meta-analyzed, results showed no significant difference between therapeutic massage and intervention of the control group for improving the daily living of PD patients (I2 = 71%). We conducted a sensitivity analysis by removing one study at a time, but the level of heterogeneity did not change a lot. Restricted to the amount of data, we did not perform a subgroup analysis, but we inferred that the age of patients and severity could be the source of heterogeneity. Chen et al. enrolled patients in the community whose ages were beyond 80 years, while the other studies enrolled PD patients with an average age of 65 years. Older aging patients probably performed worse than younger patients (In summary, therapeutic massage had relatively good efficacy for PD and for improving MS in PD to some extent. However, therapeutic massage did not have a satisfactory effect on the quality of daily life compared with the control group. Additionally, the heterogeneity of UPDRS-III between the two groups was comparatively high (patients , 37. AnoTherapeutic massage improved the overall condition and motor function better than the control intervention in terms of the total effectiveness, UPDRS-III, and UPDRS-total, but not UPDRS-II. More standardized and normalized RCTs are needed to make the meta-analysis more accurate and valuable.The original contributions presented in the study are included in the article/ZK made substantial contributions to the conception or design and data acquisition of the study. HX made a contribution to data analysis and interpretation. ZK and LG drafted the manuscript or revised it critically for important intellectual content. HX, QL, and FM agreed to be accountable for all aspects of the study in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. LG approved the final version to be published. All authors contributed to the article and approved the submitted version.This study was supported by the Key Subject Construction Project of Shanghai Municipal Health Commission, No. shslczdzk04001.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. 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