The Transfer Payment Policy of National Key Ecological Functional Areas (TPEFAP), a well-known ecological compensation (eco-compensation) scheme in China, has been proposed by the government to alleviate ecological poverty and protect the environment. In literature, the effectiveness of the TPEFAP on environmental conservation has been widely examined, while few pay attention to the effect of the TPEFAP on poverty alleviation, especially with the consideration of its spatial spillovers as well. In this paper, we utilize panel data covering the key ecological functional areas of China during the period 2011–2018 to evaluate the impact of the TPEFAP on poverty alleviation and also its spatial spillovers by employing the synthetic control method (SCM) and the dynamic spatial Durbin model, respectively. Specifically, we apply the entropy weight method (EWM) to calculate the multidimensional poverty index (MPI) and measure pro-poor effect in terms of MPI change. The results show that: (1) TPEFAP has stable positive effects on MPI in Hubei, Yunnan, Jilin, Gansu, and Ningxia, while the impact on Qinghai fluctuates. (2) MPI presents a significant spatial correlation. Furthermore, both the direct and indirect effects of TPEFAP on MPI are significant and stable positive, for both short- or long-term. (3) For potential channels, rural non-farm employment, rural labor mobility, and agricultural productivity are the key pathways through which the TPEFAP can alleviate poverty both in local and adjacent provinces. However, it is difficult to find significant positive spatial spillovers for the TPEFAP if only the natural resources scale is considered. This study indicates that the government should pay attention to the policy expectations of ecological poverty alleviation and, in future eco-compensation, must further increase the coverage of subsidies and diversify the forms of subsidies. In 2015, the United Nations identified green development and poverty reduction as the key objectives of “the 2030 Agenda for Sustainable Development” . ConsequThe Chinese government claimed to achieve the goals of poverty alleviation in 2020, which is 10 years ahead of schedule outlined in “the 2030 Agenda for Sustainable Development”. However, only absolute poverty can be addressed in that time. Multidimensional and relative poverty still exist and will become greater problems. Furthermore, despite the alleviation of poverty, severe poverty regions face a high risk of reverting to poverty. This is why the Chinese government is currently working on how to consolidate an early-stage poverty eradication effort and prevent relapse into poverty, and address multidimensional and relative poverty in the future. Therefore, the following questions arise: Can ecological compensation, as a national policy combining poverty alleviation and environmental development in China, solve poverty in rural areas? Simultaneously, owing to disparities in regional factor endowments and actual consequences of policy execution, does ecological compensation have a general poverty alleviation effect? Are there differences in poverty reduction effects between local and neighboring areas? What are the channels through which the policy works towards poverty alleviation goals? And so forth.To address these issues, we employ China’s Transfer Payment Policy of National Key Ecological Functional Areas (TPEFAP) as a quasi-natural experiment to investigate the effects of eco-compensation on poverty alleviation and spillover effects. The TPEFAP is one of the largest ecological compensation schemes in China in term of payment, scale, and duration. Initiated in 2008, the TPEFAP originally aimed to alleviate environmental pressure and enhance local ecological quality by relocating local residents and reforesting. However, TPEFAP was opposed by local farmers who face poverty and difficulties in finding alternative livelihoods during implementation. Policy makers began to realize the importance of farmer livelihood issues for the TPEFAP and opened a new round of compensation programs in 2011 See . The govThe TPEFAP has now been implemented for fourteen years and has made significant achievements towards its ecological conservation goal . HoweverThe closest study to us is by Wu et al.  who empl(1)Most studies consider only the spillover effects of other poverty alleviation policies, and few pay attention to the spatial spillovers of eco-compensation.(2)Most of the existing literature focuses on the environmental improvement effects of ecological compensation and neglects their relationship with poverty, not to mention that there would be studies evaluating the impact of ecological compensation on poverty from different dimensions.(3)Ecological poverty alleviation assessments in the study areas are mainly confined to valuation in a specific area or individual area, with a lack of studies for a continuous area.(4)The DID model is always used by studies to assess the relationship between eco-compensation and rural poverty. However, these studies do not consider the potential endogeneity of the DID, conversely, the SCM not only overcomes the endogenous problem, but also visualizes the net effects of policy implementation.We try to contribute to existing research in the following ways:The structure of this paper is as follows: The multidimensional poverty serves as the explanatory variable in this paper, as well as the preliminary basis for accurately assessing the poverty reduction effect of TPEFAP based on its reasonable construction. Considering the specific situation of the areas receiving TPEFAP subsidies, therefore the reasonable construction of MPI is closely related to the selection of study area. In this paper, we take the number of counties receiving TPEFAP compensation in a province as a benchmark, and if it is greater than 1/3, then it becomes the target province of this study, and if not, then it is excluded.  TPEFAP implementation is based on the smallest unit of counties, and our study starts at the inter-provincial level. Therefore the number of subsidized counties in the target provinces must be of a certain size, and rural areas are concentrated in these counties, and 1/3 is precisely in line with the actual ratio of one poor county for every three counties in China’s underdeveloped provinces; (2) from the data we obtained on TPEFAP subsidized counties, we estimate that there are over 1/3 subsidized counties in the six provinces we chose, while the other subsidized counties are spread out throughout the provinces, so 1/3 allows for a more realistic cut-off point that excludes more provinces). After careful deliberation, we chose six provinces with the longest implementation period and the largest coverage, namely Jilin, Hubei, Yunnan, Ningxia, Qinghai, and Gansu See , which athe Outline for Development-Oriented Poverty Alleviation for China’s Rural Areas (2011–2020)” [Finally, in light of “1–2020)” , and conBased on In Equation (1), The SCM proposed and refined by Abadie and Gardeazabal  is suitaIt is supposed that there are provinces l result :(2)Y0it=In Equation (2), It is assumed that Suppose that there is a Equation (4) has been proved that when l, 2003) :(5)Y01t−Therefore, when Equation (6) can be considered as the estimator of Labor), rural labor mobility (Urban), agricultural productivity (ATFP), natural resource scale , rural financial expenditure (Gov), economic development (Pgdp), and rural investment level (Invest). For the setting of the spatial weight matrix, existing studies often adopt the adjacency weight matrix, distance weight matrix, economic weight matrix, etc. to reflect the spatial interaction relationship between regions [The above studies suggest that ignoring TPEFAP’s policy spillovers may result in biased assessment results; therefore, we utilized the spatial panel Durbin model for empirical analysis. By incorporating the TPEFAP dummy variable , rural labor mobility (Urban), agricultural productivity (ATFP), and natural resource scale  in turn (see Equation (11)).Channel represents Labor, Urban, ATFP and Natural potential mechanisms, We explore this potential channel by inputting the interaction terms of the policy dummy variable (MPI) is selected as the outcome variable to represent the poverty improvement of each province. The dummy variable . In one respect, after being affected by TPEFAP, some areas will choose to close mountains for afforestation and return farmland to forests for ecological governance, so that those farmers in ecological function areas will either be out of work or will use subsidies for self-employment activities as the result of a reduction in agricultural land and the lower demand for agricultural labor. In another, the government also provided some eco-care positions  to increase employment opportunities for local people. (2) rural labor mobility (Urban). The key ecological function areas are generally built in ecologically fragile areas, and local farmers will then move to areas with a good ecological environment as a result of the policy, i.e., ecological migrants ; the ecological migration work for the Sanjiangyuan area , etc.). The situation will encourage the urbanization of areas benefiting from the TPEFAP subsidies, and urbanization will lead to better education levels and medical facilities, alleviating medical poverty and education poverty. Furthermore, the agglomeration effect caused by labor mobility will further affect the poverty situation in the surrounding areas. (3) Agricultural total factor productivity (ATFP). In the process of changing land from agriculture to other uses, the transformation of agricultural productivity to production service productivity may occur, and may benefit from eco-compensation [Natural). The relationship between livelihood systems, ecosystems, human well-being, and ecological services is particularly important in the context of eco-compensation [TPEFAP’s analytical model of the driving mechanism in multidimensional poverty includes core explanatory variables as well as control variables to alleviate estimation bias. We selected four core explanatory variables from different dimensions to explore the impact of TPEFAP on multidimensional poverty: (1) rural non-farm employment , government expenditure (Gov), and rural investment level (Invest). In particular, the last three variables are logarithmic in the empirical research , Hubei = 185,900, Jilin = 187,400, Gansu = 453,700, Yunnan = 394,100, Ningxia = 66,400), it is difficult for TPEFAP dividends to truly benefit the whole province. Furthermore, Qinghai has more poverty agglomerations and a slower industrialization process so it is hard to develop rural employment and industries overnight by injecting TPEFAP subsides, which may explain why there is an intersection of two curves in the province after policy intervention.After the vertical solid line, the positive effect of TPEFAP on six provinces’ MPI present upward movement of varying degrees . Specifically, the poverty alleviation effects are most significant in Hubei, Yunnan, and Gansu, while the policy effects are relatively weak in Qinghai. This may be because. (1) As the only pilot in central China, Hubei province had a broad-based policy approach and was in the early stages of eradicating poverty, thus the TPEFAP effect on Hubei is immediate; (2) Due to its geographical location in the southwest border of China, where poor mountainous areas crisscross all regions, the Chinese government has focused on Yunnan province by giving more subsides to TPEFAP, which makes the MPI of Yunnan kept increasing year by year. (3) similarly, Gansu is located in northwest China, where a scarcity of resources leads to a serious exodus of labor, resulting in deep poverty, but as mentioned in a theoretical framework, the opening of TPEFAP may alleviate this situation by improving the development of environment and related industries, and eventually attracting some of the labor force back. (4) While Qinghai has the largest land area among six provinces  each year, indicating that the application of the spatial econometric model to analyze the data is necessary see . AdditioAs shown in Urban) channel, the coefficients of Urban and (2) From the rural labor mobility ((3) The effects of ATFP on MPI in both local and adjacent areas are significantly positive, which is consistent with the previous analysis that improving agricultural productivity would lead to the efficiency of farmers’ production activities, and technology spillover would benefit farmers in adjacent areas. Nevertheless, the coefficients of (4) In Model 6 to Model 9, MPI is significantly impacted by the expansion of local natural resources, while the expansion of natural resources in surrounding areas has a negative spatial spillover on MPI locally. The coefficients of The empirical results of synthetic control method reveal that TPEFAP has a positive effect on MPI in Ningxia, Jilin, Hubei, Yunnan, and Gansu, while MPI improvement effect fluctuates in Qinghai. Robustness test results indicate that MPI development in treated provinces is greater than that of donor pools.The empirical results of the spatial effect analysis illustrate that TPEFAP not only increases the MPI of local areas but also has positive spillovers on neighboring areas. In addition, TPEFAP significantly improves short-term MPI, and the direct effect on MPI in local areas (0.02067) is almost the same as that in neighboring areas (0.02699). Hence, it indicates that neighboring areas also benefit from the policy at the beginning of the program. In the long term, TPEFAP improves MPI gradually, and the direct effect (0.06046) is gradually weaker than indirect impact (0.09048) on neighboring areas.The empirical results of the impact mechanism analysis show that rural labor structure, rural labor mobility, agricultural productivity, and natural resource scale are indeed potential paths of TPEFAP poverty reduction. Conversely, rural labor structure and labor mobility are currently the most critical paths for TPEFAP to achieve alleviation of ecological poverty. From the spatial lag term coefficients of the interaction between TPEFAP and the mechanism variables, the optimization of labor structure can suppress MPI increases in neighboring areas, while TPEFAP can cause a positive spatial spillover on MPI in neighboring provinces through labor mobility accelerates, agricultural productivity improvement, and natural resource scale expansion.In this study, we develop an MPI to represent the rural poverty and employ SCM to evaluate the impact of TPEFAP on poverty alleviation to a panel data covering key ecological functional areas of China in 2011–2018 and then utilize the dynamic spatial Durbin model to explore its spatial spillovers and mechanisms. The conclusions are summarized as follows:Understanding the importance of TPEFAP for poverty alleviation. The government should promote construction of ecological function areas nationwide and perfect the details of TPEFAP policy and eco-compensation since TPEFAP is effective in improving poverty. The government can then strengthen poverty identification mechanisms at the macro- and micro-levels in the post-poverty alleviation era. Specifically, at the micro level, local governments should make a solid and detailed record of the poor, prioritize eco-logical poverty reduction, and provide targeted support to farmers struggling with multidimensional poverty. Conversely, at the macro level, governments should clarify the main contradictions causing poverty in the region, fully consider local industrial development and economic development patterns, allocate resources rationally, formulate ecological poverty reduction development, and implementation plans in sub-regions, while concentrating on a win–win situation of poverty reduction and environmental sustainability.Refining the framework for poverty reduction spillovers. The Chinese government should incorporate the spatial aggregation effect of poverty reduction into the future framework of TPEFAP. For national key ecological function areas with diffusion effects, they should adopt more effective regional synergistic policies for mutual assistance and promote the coordinated development of multidimensional poverty improvement among regions, thus creating positive spatial economic benefits.Reinforcing TPEFAP’s channels for poverty reduction. On the one hand, the channel of the scale of natural resources has a little overall effect. Therefore, in the future, the government should make use of the natural resource advantage possessed by poor areas to vigorously develop eco-industries and strengthen its policy effectiveness. Specifically, from the actual situation of different regions, the development mode of ecological agriculture and breeding industry for each region is formulated based on the principle of “forestry as appropriate, fishing as appropriate”. On the other hand, to further optimize the structure of rural labor and increase the proportion of “farmers to workers”, the government should create special agricultural labor training institutions, strengthen labor skills training for farmers, and coordinate use of ecological jobs such as “ecological ranger” jobs to transform the proportion of “farmers to workers” actively. Additionally, the government also should promote ecological migration for farmers located in resource-poor functional areas, which will create jobs and accelerate urbanization of functional areas.Three following policy implications are put forward in accordance with the results above:There are still some shortcomings in this study.Urban. In fact, it makes more sense to use the number of rural to urban migrants to calculate rural labor mobility. Secondly, although we have explored several impact paths that can have effects on multidimensional poverty, there are many channels through which the ecological compensation system affects poverty, and we cannot exhaust each of them due to limited space. These shortcomings will be studied in the future.Firstly, our selection of certain variable measures is not optimal due to data availability. For example, the urbanization rate to measure the variable


The World Health Organization estimates that at least 2.2 billion people suffer from visual impairment globally.Herein we provide a broad overview of historic successes in the quest to improve the accessibility and quality of eye care globally (“the past”), opportunities for integrating recent technological advances such as AI , and “a path forward” to successfully develop and implement these innovations in a responsible and impactful manner.The global eye care community has a rich history of innovating care delivery models to address unmet needs in vision health. For example, despite effective treatment, cataract remains the leading cause of preventable blindness worldwide. Efforts to reduce the cost of performing cataract surgery resulted in the development of a novel surgical approach, manual small incision cataract surgery, which achieves comparable outcomes to state-of-the-art phacoemulsification cataract surgery at a fraction of the cost.Another major barrier to accessible care is the physical distance between patients and care providers possessing the skills, knowledge, capacity, and infrastructure to provide needed eye care. Several approaches have been employed to close this distance gap. Surgical outreach camps can bring providers and supplies to populations in need, while educating and supplying local providers may provide a more sustainable alternative to reduce regional accessibility gaps. For example, organizations like ORBIS and Seva have successfully trained and equipped 10s of 1000s of eye care professionals globally.Teleophthalmology bridges the distance gap by virtually connecting patients and providers and has been shown to improve accessibility to eye care, particularly in low-income and middle-income countries.The successes of the global ophthalmology community to date emphasize that overcoming the barriers to accessible, high-quality eye care for all can be achieved using a framework that adapts existing approaches  with an emphasis on scalability, sustainability, cultural competency, and stimulating patients’ individual agency and sense of empowerment.While many of the above interventions have been remarkably impactful, recent technological advances have resulted in significant enthusiasm for potential novel approaches to address global vision issues.Nowhere is the potential impact of advancing technology on global vision health more apparent than in the concept of large-scale automated image-based screening for eye diseases. The burden of many major global causes of blindness far exceeds the capacity of traditional telemedicine approaches with remote expert interpretation for secondary prevention. The application of artificial intelligence extends the concept of telemedicine beyond connecting patients to care providers, allowing the potential for massive scalability through assistive diagnosis or autonomous screening. There are now 2 FDA-approved devices for automated detection of diabetic retinopathy, and similar success may be achievable for other major global causes of preventable or treatable blindness, including glaucoma, macular degeneration, and retinopathy of prematurity.Artificial intelligence (AI) and clinical informatics may also provide benefits for tertiary prevention purposes. For example, clinical decision support systems have long been leveraged to reduce prescribing errors.Finally, artificial intelligence may also be utilized to address language barriers between the provider and the patient. Automated interpretation of speech and language has demonstrated remarkable progress in recent years, with some models capable of accurate interpretation between 100s of languages . This may provide a similar scalability benefit compared with traditional in-person or remote human interpretation between the provider and patient, although the accurate interpretation of medical speech remains a challenge for modern AI models.Technology, in addition, provides opportunities to gain insight into disease characteristics, including epidemiology, genetic factors, clinical presentation, and response to treatment, which can inform the revision of what is considered “state-of-the-art” eye care. Structured data in clinical registries such as the IRIS registry, analyzed using tools and best practices within the framework of clinical informatics and big data analytics, provide opportunities to gain knowledge of diseases that would not be feasible with traditional epidemiologic methods.While the pace of innovation in this field is exciting, several significant barriers remain before tangible benefits can be obtained from many of these applications of artificial intelligence and information technology to global eye health. Most modern deep learning models require large amounts of accurately labeled training data to achieve high performance, but “FAIR” , machine-learning-ready medical data are scarce.Even after sufficient data has been accumulated and an AI model has been successfully trained and evaluated, there remain significant barriers to implementing such models in the health care setting and achieving benefits to patients. There is a striking discordance between a large number of AI publications in ophthalmology journals and the relatively low number of systems in deployment.The potential exists for recent technological advances to transform the way ophthalmic care is delivered around the world and reduce preventable blindness. To bring these technologies to patients, we need to: (1) Learn from prior successes in global ophthalmology by focusing on community engagement, building sustainable infrastructure, and optimizing care delivery models; (2) Fund research to support the development of FAIR datasets that accurately represent diverse populations and reduce the machine learning implementation gap; and (3) Foster active collaboration among all stakeholders, including patients, clinicians, public health experts, machine learning engineers, informaticists, data scientists, and implementation scientists.The low-hanging fruit in blindness prevention has always been the implementation of existing knowledge. Although there are many high-tech innovations in ophthalmic imaging, constantly evolving surgical techniques, and new drugs, the most impactful interventions in the next few decades may be in the realm of implementation science, solving barriers such as data infrastructure, adapting care models to local contexts, and creating scalable and sustainable revenue models for technological innovations.


Citizens who contribute as volunteers and peer mentors within a community are important assets that can be mobilised to improve health and wellbeing. In order to optimise the contribution of peer-volunteers to active ageing initiatives, we need to understand their experiences and identify ways to support them in preparing for the role and overcoming potential challenges.Aim: This study synthesises the perspectives of a range of stakeholders involved in peer volunteering active ageing initiatives implemented in UK and provides an in-depth account of how such initiatives can effectively mobilise individuals as community assets. It draws on the experience of all actors involved in such initiatives, ranging from volunteers, recipients of volunteering actions, volunteer managers and volunteering service providers.This evidence synthesis used qualitative data from (a) three studies focusing on the development (phase 1), feasibility trial evaluation (phase 2) and community roll-out (phase 3) of ACE , a peer volunteering active ageing intervention, alongside (b) the experiences of third sector organisations in providing peer volunteering programmes. Ten managers, 22 volunteers and 20 ACE participants were interviewed. Interviews were audio-recorded, transcribed verbatim and analysed using framework analysis.Seven main themes including 33 higher and 22 lower order themes were identified: Motives; Benefits; Characteristics of peer volunteers; Challenges; Training needs; Recruitment; Successful strategies for maintenance. Altruism, changes in life circumstances, opportunities to reconnect with the community and personal fulfilment were the main reasons for volunteering. Volunteering was described as being personally rewarding, an avenue to acquire new skills and knowledge, and increased social connections and physical activity. Effective volunteers are committed, reliable, have a good sense of humour, good interpersonal skills and are able to relate to the participants. When pairing volunteers with participants, clarity of role, level of time commitment, shared interests and geographical proximity are worth considering.Successful implementation of peer-volunteering initiatives requires the use of appropriate recruitment routes, easy joining procedures, provision of ongoing support, good communication across all stakeholders, feedback and recognition of effort and a dedicated team to build resilience and provide volunteers with administrative support.


The Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) cohort was established to (1) investigate how exposures before conception and in previous generations influence health and disease, particularly allergies and respiratory health, (2) identify susceptible time windows and (3) explore underlying mechanisms. The ultimate aim is to facilitate efficient intervention strategies targeting multiple generations.RHINESSA includes study participants of multiple generations from ten study centres in Norway (1), Denmark (1), Sweden (3), Iceland (1), Estonia (1), Spain (2) and Australia (1). The RHINESSA core cohort, adult offspring generation 3 (G3), was first investigated in 2014–17 in a questionnaire study  and a clinical study . Their G2 parents participated in the population-based cohorts, European Community Respiratory Heath Survey and Respiratory Health In Northern Europe, followed since the early 1990s when they were 20–44 years old, at 8–10 years intervals. Study protocols are harmonised across generations.Collected data include spirometry, skin prick tests, exhaled nitric oxide, anthropometrics, bioimpedance, blood pressure; questionnaire/interview data on respiratory/general/reproductive health, indoor/outdoor environment, smoking, occupation, general characteristics and lifestyle; biobanked blood, urine, gingival fluid, skin swabs; measured specific and total IgE, DNA methylation, sex hormones and oral microbiome. Research results suggest that parental environment years before conception, in particular, father’s exposures such as smoking and overweight, may be of key importance for asthma and lung function, and that there is an important susceptibility window in male prepuberty. Statistical analyses developed to approach causal inference suggest that these associations may be causal. DNA methylation studies suggest a mechanism for transfer of father’s exposures to offspring health and disease through impact on offspring DNA methylation.Follow-up is planned at 5–8 years intervals, first in 2021–2023. Linkage with health registries contributes to follow-up of the cohort. The main strength of the Respiratory Health in Northern Europe, Spain and Australia (RHINESSA) cohort is the availability of rich preconception exposure information for a large number of young adolescent and adult study participants, from both the paternal and maternal line, taking advantage of extensive information collected from mothers/fathers over 20 years of childbearing age.Excellent health and population registries in the Northern European study centres contribute to unbiased identification of study participants and enrichment of data, and, for some study centres, provide additional information on multiple generations covering cohorts born over the last century.The multigeneration design and harmonisation of study protocols across generations provide a valuable opportunity to validate next of kin information, thereby improving the validity of retrospectively collected data on family members.The Spanish and Australian study centres contribute to generalisability beyond Northern Europe which has the majority of study participants, however, generalisation to low-income countries must be done with care.Weaknesses of RHINESSA further include relatively low response rates, partly mitigated by the opportunity to analyse selection bias based on parental data for responders and non-responders; further, extensive exposure data is only available from one parent in most study centres, while information on the other parent is available from next of kin data reported by the offspring, and from registry data in the Nordic study centres.While it is generally acknowledged that intrauterine life and early childhood is essential to health and disease throughout life, emerging evidence supports that there may be important susceptibility windows before conception.Knowledge on the early life origins of health and disease led to a paradigm shift in public health strategies, and is today implemented in public health programmes targeting mother and child across the globe. The concept of preconception origins of health and disease, of susceptible time windows before conception, opens a new perspective on public health: Are there opportunities for preventive measures that may result in improved health, not only for the individual but also for their future offspring and generations?There is a need to establish human generation cohorts that are tailored to investigate the preconception origins of health and disease. Most available literature is based on animal studies. There are human cohort studies with preconception data, such as for example, the Isle of Wight Studies, the Avon Longitudinal Study of Parents and Children study, the Lifelines NEXT generation study, and the Tasmanian Longitudinal Health Study. However, birth cohort studies often have not collected data from the fathers, or from the childhood/adolescence of any of the parents. Since the human reproductive cycle spans decades, investigating exposure effects from before conception and across generations represents a great challenge.The RHINESSA study is designed to address this by investigating the offspring of persons who have already been extensively characterised during 20 years of their reproductive life. RHINESSA is an international multigeneration multicentre study established to research the preconception origins of health and disease, in particular allergies and respiratory health. The aims of RHINESSA are to investigate the influence of exposures before conception including in previous generations for health and disease, to identify potentially susceptible time windows for such influences, and to explore mechanisms for exposure effects. RHINESSA’s primary focus is allergies and chronic respiratory disorders, namely asthma, rhinoconjunctivitis, allergic sensitisation, eczema, chronic obstructive pulmonary disease, lung function and sleep disorders. The cohort resource and research methodologies of RHINESSA also have the capacity for multigeneration research in other areas, such as obesity, women’s health and oral health. The ultimate aim of RHINESSA is to improve health at large by generating a knowledge base for efficient strategies that may improve health over several generations.This cohort profile describes the RHINESSA adult offspring cohort (generation 3 (G3) of ≥18 years of age) and their G2 parents investigated as part of the European Community Respiratory Health Survey (ECRHS) and Respiratory Health in Northern Europe (RHINE) studies . Online 10.1136/bmjopen-2021-059434.supp1Supplementary datawww.ecrhs.org) established in the early 1990’swww.rhine.nu).RHINESSA builds on the large longitudinal studies of respiratory health in adults, the ECRHS, www.rhinessa.net), interview guides and procedures for translations/back translations contribute to secure harmonisation of data across study centres and generations.The RHINESSA adult offspring study invited offspring age ≥18 years (G3) of RHINE and ECRHS participants (G2) from ten study centres: Bergen, Norway; Aarhus, Denmark; Uppsala, Göteborg and Umeå, Sweden; Reykjavik, Iceland; Tartu, Estonia; Melbourne, Australia; Huelva and Albacete, Spain . In the 10.1136/bmjopen-2021-059434.supp2Supplementary dataThe study centres in Bergen, Aarhus, Tartu and Melbourne also investigated younger G3 offspring <18 years . Bergen www.ecrhs.org).In the early 1990’s the ECRHS conducted a population-based survey among random samples of young adults aged 20–44 years in several European and non-European countries (www.rhine.nu) developed protocols to follow-up responders to the initial ECRHS postal survey in seven Northern European centres: Bergen, Norway; Göteborg, Umeå and Uppsala, Sweden; Aarhus, Denmark; Reykjavik, Iceland and Tartu, Estonia. In 2000–2002, 16 106 persons answered extensive postal questionnaires .The RHINE study .et al found that grandfather’s cardiometabolic disease (CMD) was directly associated with grand offspring asthma, while accounting for indirect effects transmitted through parental CMD or asthma, consistently in the RHINE, ECRHS and RHINESSA cohorts (not yet published).In a study of sleep disturbances, Lindberg et al found moderate to good agreement between self-reported asthma and asthma reported by family members, both regarding offspring asthma reported by parents and vice versa.et al found that adults reported quite accurately their parents’ smoking during their childhood and their mother’ smoking when pregnant with them, when compared with the parents’ own report.et al found that the accuracy in reporting parental place of upbringing was dependent on own place of upbringing, but this did not bias the associations of place of upbringing with asthma.et al validated mothers’ information about births and pregnancies against data from the Medical Birth Registry of Norway. The analysis found high validity for mother’s report of important birth and pregnancy parameters, and that risk-associations were similar when using maternal versus registry-based information.Information about family members is often sought from study participants, as this is cost-effective and may be the only feasible way to obtain the information. The RHINESSA/RHINE/ECRHS cohorts provide an important opportunity for validation of such next of kin information. Kuiper et al found that current body silhouettes were highly correlated with body mass index (BMI) calculated from measured or self-reported weight and height.et al found that retrospective body silhouettes from adult ages correlated well with BMI calculated from measured height and weight at the corresponding ages in the past, and allowed for differentiation of obesity and non-obesity.Life course data on obesity is rarely available for multiple generations. The RHINESSA/RHINE/ECRHS studies have included a tool with pictorial drawings of body silhouettes in childhood, voice break/menarche and adult ages. Dratva The main strength of the RHINESSA study is the large number of offspring-parent pairs with rich and similar information from both generations, collected using similar protocols, and with very little missing data on key variables. Both fathers and mothers have been extensively characterised over twenty years of childbearing age, and the availability of such parental exposure information for adolescent and adult offspring is quite unique. The prospectively and retrospectively collected data on family members in this multigeneration study allow validation of information provided about family members,A weakness of the RHINESSA study is that detailed parental data are mostly available for one parent of the offspring, the parent (mother or the father) participating in the ECRHS and RHINE studies. To meet this challenge, a subcohort of the ‘other’ parents has been studied in Bergen RHINESSA, validation studies have been performed to improve the usefulness of information reported by offspring on both parents, and there are registry data available for both parents in North European study centres. Another weakness is the relatively low response rates. Fortunately, exposure information in terms of parental information is available for responders and non-responders. While selection bias cannot be ruled out, it is reassuring that So, what lessons have we learnt from the cohort’s creation that could be useful for other researchers? One most useful contribution from RHINESSA to other researchers, is the possibility to validate information provided by family members. In general, we find that strong, longstanding collaboration and friendship has been key for creating a complex set of cohorts in a longitudinal multicentre setting. Thus, building on existing cohorts with well-functioning researcher networks appears to be important for future multigeneration epidemiological studies.


Behçet’s disease (BD), a chronic vascular inflammatory disease, is characterized by the symptoms of ocular lesions, recurrent genital and oral ulcers, skin symptoms and arthritis in addition to neurological, intestinal and vascular involvement. The pathogenesis of BD is poorly understood, and there are no effective laboratory markers for the diagnosis of BD. In addition, BD is presently incurable. Chemokines, a family of small secreted chemotactic cytokines, interact with chemokine receptors and mediate the migration, localization and cellular interactions of inflammatory cells. Several studies have suggested that chemokines and their receptors play an important role in the occurrence and development of BD and that these chemokines along with their receptors can be utilized as biomarkers and therapeutic targets. In the present review, chemokines and chemokine receptors involved in BD and their potential application in diagnosis and therapy have been discussed. The patin China , 4. Thesin China . BD is uin China . Common in China . Howeverin China .Chemokines are a superfamily of small, secreted proteins that facilitate the migration of immune cells into inflammatory sites by interacting with their receptors. This process plays a central role in the occurrence and development of several autoimmune diseases, including rheumatoid arthritis, systemic sclerosis and systemic lupus erythematosus . For insAccumulating evidence has shown that certain chemokine and chemokine receptor genes can increase or decrease the risk of developing BD through gene susceptibility and that the genetic background of BD varies among different gender, regions and ethnicities. A Turkish study reported that CXCL8 gene polymorphisms possibly affect susceptibility to BD in people from the Denizli Province . The stu. As the critical cellular participants in the pathogenesis of BD, overactivated neutrophils release abundant reactive oxygen species via nicotinamide adenine dinucleotide phosphate hydrogen oxidase and neutrophil extracellular traps (NETs), inducing thrombo-inflammation , maraviroc (a CCR5 antagonist) and mogamulizumab (a CCR4 antagonist), respectively, for the mobilization of haematopoietic stem cells, inhibition of the human immunodeficiency virus and treatment of patients with relapsed or refractory adult T-cell leukaemia–lymphoma, mycosis fungoides and Sezary syndrome . As chem+ cells after colchicine and pentoxifylline treatment improved the symptoms of BD mice (Poor understanding of chemokines and chemokine receptors in the pathogenesis of BD may have led to their neglect in therapeutic strategies. Thus, the progression of new treatment strategies in BD has been slow. Th1 interstitial migration is highly dependent on chemokine–chemokine receptor interaction and sensitive to the inhibition of G protein -coupled receptor signalling ; these p BD mice . Surpris BD mice . SubsequChemokines and chemokine receptors are important mediators in the development of BD as they regulate gene susceptibility and mediate cellular infiltration, activation and cascade amplification of inflammatory responses, suggesting their significant potential as laboratory biomarkers and therapeutic targets in the management of BD. However, a poor understanding of their roles in the pathogenesis of BD led to a lack of appreciation for their possible role in laboratory biomarkers and therapeutic strategies. Therapeutic strategies based on certain chemokines and their receptors, including anti-CXCL8, anti-CCL3, anti-CCR5 and anti-CXCR3, could become novel alternatives in BD treatment. Further investigations regarding the roles of chemokines and their receptors in BD and strategies that target the chemokine–chemokine receptor system are necessary.ZL and LC wrote the manuscript based on discussions with HZ and prepared the Table and Figure. YL revised and examined the manuscript. All authors contributed to the article and approved the submitted version.


Disgust is a basic emotion characterized by the feeling of revulsion and evoked by unpleasant stimuli such as contaminated food, poor hygiene and contact with sick or dead organisms. Disgust is a contributing factor to the development of several mental disorders including anxiety disorders (AD). Several studies have tried to explore the relationship between disgust and eating disorders (ED), with heterogeneous findings. Subjects with ED showed a heightened level of disgust sensitivity (DS) when compared with healthy controls (HC).Our study aims to evaluate levels of disgust and anxiety in ED, AD and HC in order to assess associations between these two emotions.We enrolled 74 patients admitted to Psychiatric Unit of Careggi, 41 with diagnosis of Eating Disorder, 33 with Anxiety Disorders, and 40 healthy controls. We administered to all groups: Zung Anxiety Scale (ZSAS) and Disgust Propensity and Sensitivity Scale-revised (DPSS-r).Anxiety and disgust are typical emotions of anxiety disorders and eating disorders. However, they are increased both in anxiety and eating disorders and they are associated in healthy controls. The nature of this association needs to be deeply investigated.No significant relationships.


In Wales almost a quarter of adults and 1 in 8 reception age children are obese. Linked data is a key tool to understanding the role of the built environment on obesity rates and is an important part of developing strategies to combat the obesity epidemic in Wales.We set out to develop an analytical platform for generating evidence on key aspects of the built environment which impact child and adult obesity including; walkability, fast food availability, green space size and qualities, active transport routes and school environments. Utilising the Secure Anonymised Information Linkage (SAIL) Databank We linked multi-sectoral data including routine health data, cohort data, administrative data and linked Geographic Information Systems generated metrics at household and school level. The platform will inform policy makers with and facilitate a better understanding of associations between a range of social, health and built environment factors.We have created a range of built environment variables including temporally and age varying walkability indices, viewable greenspace, garden and house size, access to services and parks for 1.5 million households. In the first instance, as part of the BEACHES project, this data has been linked to several health datasets including the Child Measurement Programme  where initial results have shown that associations between garden size and Body Mass Index in children displays a non-linear negative correlation. We have also created follow-up measures for the CMP using routinely collected general practice data which further enables linking 28,389 height and weight measurements. However, potential bias in these follow-up measures is poorly understood with further work being undertaken to assess usability.The integrated multi-sectoral data platform approach to linking environmental, administrative, health and cohort data aims to develop insights on a range of public health issues. We are working with a range of stakeholders to develop evidence-based policy initiatives to reduce obesity in Wales.


Physical, emotional, and social changes, including exposure to poverty, abuse, or violence, increases youth vulnerability to mental illness. These factors interfere with development, limit opportunities, and hamper achievement of a fulfilling life as adults. Addressing these issues can lead to improved outcomes at the population level and better cost-effectiveness for health services. Cash transfer programs have been a promising way to address social drivers for poor mental health. However, it is still unclear which pathways and mechanisms explain the association between socioeconomic support and lower mental illness among youth. Therefore, we will evaluate the effect of social drivers on youth mental health-related hospitalizations and suicide, test mechanisms and pathways of a countrywide socioeconomic intervention, and examine the timing of the intervention during the life course.We will combine individual-level data from youth national hospitalization, mental health disorders and attempted suicide, suicide registries and notifications of violence, with large-scale databases, including “The 100 Million Brazilian Cohort”, over an 18-year period (2001–2018). Several approaches will be used for the retrospective quasi-experimental impact evaluations, such as Regression Discontinuity Designs, Propensity Score Matching and difference-in-differences, combined with multivariable regressions for cohort analyses. We will run multivariate regressions based on hierarchical analysis approach to evaluate the association between important social drivers  on mental health-related hospitalizations and suicide among youth. Furthermore, we will perform microsimulations to generate projections regarding how mental health-related hospitalizations and suicide trends will be in the future based on the current state, and how BFP implementation scenarios will affect these trends.The results of this project will be of vital importance to guide policies and programs to improve mental health and reduce mental health-related hospitalizations and suicide in youth. It will provide information to improve the effectiveness of these programs worldwide. If cash transfers can decrease mental health problems among youth and reduce suicide. Mental disorders are both common in young people and persistent. Previous study estimates that the global prevalence of mental illness among children and adolescents ranges between 13–20% [https://sdgs.un.org/goals). Since mental health problems affect a large proportion of youth, have profound effects on a range of social outcomes such as education and employment, and can persist into adulthood, addressing mental health problems in youth is a priority for the global health agenda and for realizing the SDGs. However, there is evidence that access to mental health services in Brazil is limited, as only 19% of children with mental illness from schools in São Paulo and Porto Alegre were reported to have had prior treatment [A range of social adversities and deprivations are drivers of mental illness which affect children and adolescents. Youth in low middle income countries (LMICs) are particularly vulnerable due to the higher prevalence of adversities, for example, poverty, and relatively fewer available social protections in place. There is increasing recognition of the relevance of mental health to global development strategies, in particular to the achievement of the Sustainable Development Goals (SDGs), including improving youth mental health and eradicating poverty  recommends that suicide prevention should be prioritized on the global public health agenda . HoweverThe Brazilian government introduced the Bolsa Familia Programme (BFP) in 2003  to promoTo use large national datasets to evaluate the effect of a broad range of social drivers and of a social-economic intervention on youth mental health,To test four mechanisms and pathways  of the social-economic intervention on reducing mental illness among youth,To evaluate whether equity is a moderator of the effectiveness of the cash transfer program, e.g., whether the Brazilian cash transfer program improves the lives of the most vulnerable subgroups  compared to less vulnerable groups, thereby reducing mental health disparities, andInvestigate early life exposures, intergenerational aspects, and to forecast the impact of socioeconomic changes and cash transfers mitigation effects in Brazil until 2030 using microsimulation models, also modelling the impact of the current COVID-19 related economic recession.Our data of over half of the Brazilian population will help understand both  the association of multiple factors on both mental illness and suicide, and the impact of interventions targeting some of these factors. Within each broad analysis, we will explore pathways, mechanisms and interactions/moderators. This is especially important in LMICs, such as Brazil, where implementing preventative measures may be more challenging as a result of cultural and socioeconomic factors, limited resources, as also in large continental countries because of size and distribution of the population . This stThe Brazilian Cash Transfer Program, “Bolsa Família Program” (BFP), is one of the largest conditional cash transfer programs worldwide, which appears to have had an important public health impact. Studies indicate that BFP has promoted social inclusion and strengthened human capital among the poorest, reducing poverty and inequalities, besides increasing school attendance among youth and reduced violence, factors that are associated with mental health , 10, 16.First, this study provides a unique opportunity to use the largest existing longitudinal dataset (The 100 Million Brazilian Cohort) in any LMIC of linked socioeconomic and health individual-level data to assess the effects of socioeconomic conditions and BFP on mental illness and suicide among young people.Second, the longitudinal aspect of the cohort, with a long follow-up period of 18 years of socioeconomic and health data, will allow us to explore and assess in-depth dynamics, lagged and long-term effects of changes in living conditions, parents’ mental illness and in exposures to BFP. The long-term impact of BFP on a diverse population once such a program has been scaled up and sustained for over a decade is completely unknown.Third, with this project, we will be able to identify risk factors for mental health-related hospitalizations and suicide  and investigate pathways and mechanisms using a linkage of massive datasets covering half of the country for sociodemographic information and the full country for hospitalization and mortality information.Fourth, the uniquely large number of individuals of our dataset provides sufficient statistical power to assess the effects and test mechanisms of BFP on a high number of subpopulations, in terms of demographic, geographic, social, and economic conditions, thereby taking advantage of Brazil’s extreme social inequalities. To date, knowledge about the potential of Cash Transfer Programs (CCTs) on mental illness and suicide has been limited to small trials where, in general, the CCT program was not part of a national poverty alleviation strategy, and evaluations have been focused on poor populations of a few lower-income countries. This study provides the exceptional occasion to assess potential effect modification disparities, evaluating whether the Brazilian cash transfer program improved the lives of most vulnerable subgroups  compared to less vulnerable groups, therefore, reducing inequalities.Fifth, this study contributes to translational science with the systematic integration of the large dataset and results from retrospective impact evaluations with prospective mathematical models, developing more reliable forecast scenarios than models which use parameters from other studies or populations. The 18 year-100 million individual retrospective cohort will be used to generate projections, using microsimulation models, of an integrated synthetic cohort up to 2030, maintaining the correlation structure between variables and area/individual-specific trends in all demographic and socioeconomic variables. In creating these forecast cohorts, several alternative scenarios–including maintenance of the current poverty and inequality increase vs their gradual decrease—will be simulated, and resulting effects on mental health-related hospitalizations and suicide (as well as the policy response to it) will be evaluated.This project provides an innovative approach to assess the effects of a large and successfully scaled program on youth mental illness and suicide. Use of a longitudinal big dataset and a pioneer integration between retrospective and forecasting evaluations, together with innovative hybrid microsimulation models, will advance our understanding of mental illness, suicide, and control measures among youth in one of the biggest countries in the world. The implications are vast, as it will help answer questions about mechanisms through which socioeconomic programs can prevent mental illness in early life. These findings will be important to other LMICs struggling to address the mental health burden and to other countries, that also faces high-income inequality, high violence rates and its continental size, which brings challenges to implementing governmental programs.There is a strong association between poverty and poor mental health in young people , 18. PsyEconomic hardship can affect mental health, increase stress, and decrease self-esteem . EconomiSeveral drivers and mechanisms have been hypothesized to underlie the process of the association between cash transfer and better mental health outcomes, and there is also a bidirectional and intergenerational component. Haushofer and Shapiro (2016) have shown that the receipt of a fixed monthly income resulted in a short-term increase in self-reported welfare among beneficiaries in Kenya . A revieWe hypothesize that a socioeconomic intervention, Bolsa Família Program (BFP), could be associated with better mental health outcomes among youth, by mitigating some social drivers for poor mental health, such as exposure to violence . SimilarTherefore, the main potential mechanisms this project will test, through which BFP may be associated with better mental health outcomes are: (i) by reducing parental mental illnesses and family separations; (ii) by improving school retention ; (iii) by reducing exposure to violence; and finally, (iv) by decreasing impulsivity .This protocol offers a unique opportunity to test these mechanisms in a countrywide dataset, and allows subgroup analyses. Considering that the impact of those factors may happen differently among more vulnerable groups, such as black youth, women, youth with lower income and living in deprived areas, after examining the impact of cash transfers on interrupting the pathways between poverty and poor mental health through one or more mechanisms previously mentioned . We will then evaluate the differential impact of BFP across race and gender, and how this might be explained by the mechanisms. If the effect of the cash transfer is stronger among minorities, decreasing inequalities, it can also be one of the mechanisms through which this program may improve youth mental health.Datasets, variables, and sample sizes.100 Million Brazilian Cohort. We will analyze a cohort of subjects registered in Unified Registry for Social Programs (CadÚnico). The CadÚnico is a data collection and storage system that contains individual records with demographic and socioeconomic information on the poorer half of the Brazilian population . Anyone who meets the eligibility criteria can be registered by visiting one of the Centers for Social Assistance (CRAS) or be registered at home, as social workers visit households periodically to identify and register eligible individuals. The criteria to be eligible for CadÚnico registration are: having a monthly family income per capita of half the minimum salary in Brazil  or less; or having a total family income (monthly) of up to three minimum salaries. The CadÚnico contains information about housing conditions, income and demographic characteristics of all the members of a registered family [d family .Bolsa Familia Program (BFP). The Brazilian Cash Transfer Program (BFP) is the largest poverty alleviation program in the world, with about 46 million people having received the benefit up to 2015. It has three aims: income supplement guarantee for immediate relief of extreme poverty  [ capita) ; access  capita) .In 2014, the eligibility criteria for participation in the program (which is more stringent than the conditions for eligibility to register in CadÚnico) was having an income of less than 77 reals (14 USD) monthly per person or less than 154 reals in cases where there is a child, adolescent or pregnant woman in the family. The benefits were: “basic benefit”, 77 reals monthly, regardless of family composition; an extra 35 reals to families with a child or adolescent between 0–15 years, or a pregnant or nursing woman; and an extra 42 reals per adolescent from 16–17 years, in 2014. Families living in extreme poverty can accumulate all these “basic benefits” to a maximum of 1,332 reals per month (235 USD).All BFP beneficiaries are registered in an electronic register called CadÚnico . Since we have both datasets available, we hold information from people who are beneficiaries in the programs and also from people who are not see  & Fig 2 Besides information from BFP, from the CadÚnico, we will also access information from the Hospitalization Information System to identify hospitalizations from: (A) mood disorders ; (B) anxiety; (C) psychosis ; (D) prescribed or illicit drug abuse and dependence; (E) alcohol abuse and dependence; (F) alcohol-related liver, problem/chronic liver disease; (G) physical injuries ; (H) attempted suicide ; and (I) suicide , from 2001–2018. As well as violence notifications from the Brazilian Notification System for Health Surveillance and all cause-specific mortality data, collected from the Brazilian Mortality Information System. All hospitalization, notification, and mortality information data were obtained from the DATASUS held by the Brazilian Ministry of Health and transferred to CIDACS  for reseTo test the pathways and mechanisms of a cash transfer program on youth mental health, we will integrate the five large individual datasets, previously mentioned, with aggregate data, analyzing the variables previously described. We have previously precisely linked the BFP data to the 100 Million Brazilian Cohort, using a social identification number (NIS). Individuals who have died by suicide, hospitalized by suicide attempt or mental disorders, or were a victim of violence , were identified by linking Brazilian Mortality Information System (SIM), Hospitalization Information System (SIH), Notifiable Diseases Information System (SINAN) data, respectively with the 100 Million Brazilian Cohort. The 100 Million Brazilian Cohort and Health databases were linked by the Center for Data and Knowledge Integration for Health (CIDACS) , 28, 31.The linkage algorithm used five variables to identify matching records from the two databases (SIM and CadÚnico), each of which was recorded in all the datasets being linked: the beneficiary’s name, mother’s name, sex, municipality of residence code, and date of birth. The Record Linkage software performed two main steps: The record that corresponded to the data of each 100 Million Brazilian Cohort individual (the larger dataset) was indexed in the Lucene Apache library, which has a method of indexing files and performed a search of data in these files. Then for each information in the health dataset, the algorithm searched the indexed database of the 100 Million Brazilian Cohort for a potential match. A similarity calculation was performed for these records, generating a score indicating the similarities between the two linked records. The similarity calculation was performed and generated a “weighted average” which is the value of the similarity score. Finally, if the score was equal to or greater than 0.95, the link was accepted (as a correct link). In order to check the entire linked dataset, robust accuracy tests were performed, to assess the overall linkage quality. Analysis of linkage accuracy included manual verification and assessing the Receiver Operating Characteristic (ROC) curve. Details were reported elsewhere .Aim 1: To use large national datasets to evaluate the effect of a broad range of social drivers and of a social-economic intervention on youth mental health.In this step we will evaluate: first the effect of the BFP and social drivers such as family income, poverty, early marriage, housing characteristics, family income, parents’ divorce, family composition, and parents’ substance misuse on youth hospitalization from: (A) mood disorders; (B) anxiety; (C) psychosis; (D) prescribed or illicit drug abuse and dependence; (E) alcohol abuse and dependence; (F) alcohol-related liver, problem/chronic liver disease; (G) physical injuries; and (H) attempted suicide and (I) suicide. We will also evaluate if a family history of violence, suicide and psychiatric disorders will be associated with an increased risk of been hospitalized from a mental illness or been a suicide victim among youth. Also, if the BFP reduced the recurrence of mental health-related hospitalizations.We will run regressions to evaluate the association between important social drivers listed above on mental health-related hospitalizations and suicide among youth in Brazil from 2001 to 2018. Multivariate regression models based on a hierarchical analysis approach will be adjusted for mental health care access, income, location of residence , household living conditions including household density, water supply, sewage and garbage collection, residency type and building material, and stratified by age groups, sex and race. The hierarchical models will be ordered according to the level that they act on the dependent variables . It is argued that mental health is conditioned by a series of proximal and intermediate factors, conditioned by socioeconomic situation, among which level of education, marital status, race, home conditions, region, and place of urban/rural residence, all considered social drivers.To evaluate the impact of the countrywide cash transfer program on those outcomes, we will run Regression Discontinuity Design (RDD), Propensity Score Matching (PSM), and difference-in-differences, which are robust methods of impact evaluation in public health. This should help to identify the best statistical techniques to evaluate the impact of BFP on mental health-related hospitalization and suicide. Different evaluation methods make different assumptions. For instance, PSM assumes that after matching for the observed characteristics, there is no unmeasured confounding for the association between the intervention and the outcome. RDD instead assumes that people just below and just above the threshold of a continuous variable used as eligibility criteria for the intervention are “similar” in all relevant respects. Therefore, the difference in the outcome between the intervention groups is practically random near the threshold. PSM is a method that has been used in large electronic health records , 32. It Aim 2: To test four mechanisms and pathways of the social-economic intervention on reducing mental illness among youth; and Aim 3: To evaluate whether equity was a moderator of the effectiveness of the cash transfer program, e.g., whether the Brazilian cash transfer program improved the lives of most vulnerable subgroups  compared to less vulnerable groups reducing mental health disparities.We will evaluate whether BFP program affects youth mental health through improving social drivers by running Regression Discontinuity Design (RDD) and Propensity Score Matching (PSM), and Structural Equation Modelling (SEM) for each of them and the outcomes. Such strategies allow us to examine the pathways by testing the impact of the intervention on variables that might be on the pathway of the relation between BFP and mental health outcomes. We hypothesize that BFP has an effect on reducing mental health-related hospitalizations and suicide among youth because it also affects their social drivers. Stratified analyses by municipality size, regions, states, and levels of Human Development Index (HDI) will also be performed.We will include a set of covariates recognized as social drivers of mental illness for youth at the individual level such as income, income instability, unemployment, isolation and at the contextual level, variables from the municipalities where the youth live, such as population, fertility, mortality, migration, housing characteristics, characteristics of the neighbourhood, municipal income, labour, economic inequality (Gini index), Human Development Index (HDI), proportion of poor people and municipal coverage of the community mental health center and number of mental health professionals in the same municipality. We will also evaluate whether equity was a moderator of the effectiveness of the cash transfer program, e.g., whether the Brazilian cash transfer program improved the lives of most vulnerable subgroups compared to less vulnerable groups, thereby reducing mental health disparities. Therefore, we will repeat the analysis stratifying by subgroups with diverse ranges of income level, black compared with the white population, and female compared to male.We will apply methods from the SEM group, to specify and test the paths laid out in Aim 4: Investigate early life exposures, intergenerational aspects, and to forecast scenarios in Brazil until 2030 using microsimulation models.Finally, to match this aim we will examine: timing of the intervention in the life course, e.g., if cash transfer delivered earlier in life  will be associated with lower mental health-related hospitalizations and lower suicide rates 10 years later (when the same adolescent will be 24 years old); and whether mental health-related problems such as suicidality, post-traumatic stress disorder (PTSD), violent behavior passes over to second generations; and, furthermore to forecast scenarios of mental health-related hospitalizations and suicide rates using microsimulation models. This will leverage the results from previous objectives and compare the impact of different BFP implementations on mental health-related hospitalizations and suicide in Brazil until 2030.To answer the above sub-objectives, we propose the use of modeling for longitudinal data, since the events are observed over time. For sub-objective firstly we will apply extended Cox model , known aThe third stage of modelling will integrate the datasets and analyses above with Microsimulation Models (MS). Microsimulation is increasingly used in epidemiology and is useful to evaluate both overall and subgroup impacts of public policies  This is Step 1. The creation of a synthetic cohort for 2019–2030 using the demographic, socioeconomic and exposure variables as an extension of the big retrospective cohort of 2001–2018 analysis from the previous objectives. For each individual, we will simulate changes in socioeconomic variables over time based on transition probabilities and consistent with different economic scenarios. We will simulate socioeconomic changes as a result of the current economic crisis related to the COVID-19, modelling increases in poverty rates at different pace, intensity and length, together with other relevant social drivers of mental illnesses. Several BFP coverage responses will be tested through three main scenarios to reflect different economic conditions: a) a fiscal austerity scenario assuming a reduction of BFP coverage; b) a stable scenario assuming BFP coverage level is maintained at the pre-economic crisis level; and c) an enhanced coverage scenario, in which BFP is increased to protect all the newly poor individuals from the economic recession. Targeting social determinants, using cash transfer programs, could be important tools to limit hospitalizations from mental illness and suicide among youth, predicted to rise in the aftermath of economic recession consequent to the COVID-19 pandemic.Step 2. The estimation of hospitalizations incidence and mortality for 2019–2030 using the individual-level values of each variable of the synthetic cohort and their effects estimates from the previous retrospective analyses. The microsimulation modelling will follow ISPOR guidelines [idelines  for eachidelines –40. ScenThis study will be conducted in accordance with Resolution N° 466/2012 of the National Health Council (CNS) and also complies with the international (Helsinki) research regulations. It was approved by two Ethics Committees of the: (i) Federal University of Bahia (application number: 1023107) and (ii) London School of Hygiene & Tropical Medicine (application number: 11581). The linkage of the databases will be carried out in a secure and protected environment, following a strict internal procedure to make sure data privacy and confidentiality . A non-iThe study will use quasi-experimental approaches to assess the effect of social drivers on youth mental health-related hospitalizations and suicide, test mechanisms and pathways of a countrywide socioeconomic intervention, and examine the timing of the intervention during the life course, in a large sample of poor and impoverished Brazilian households. The BFP might result in positive impacts in all conditions related to difficulties in accessing health, education, social assistance, employment, and income, thus, improving youth mental health , 19, 41.Suicide can be underreported due to stigma and therefore be misclassified when a family registers them. However, the process used to report violent deaths in Brazil reduces the chances of underreporting or misclassification. Suicide  were collected from the Brazilian Ministry of Health’s Mortality Information System (SIM) and the quality of this data has been previously recognized for having high-quality standards . All deaSome limitations must be considered. The use of proxy in one of the four mechanisms proposed, physical injuries for impulsivity, can be a possible limitation in the analysis of mechanisms. However, assessment of impulsiveness and aggression in studies of risk factors for suicidal behavior, often depend on information from proxy informants, have been evaluated as robust . Since bThe large-scale data set will allow us to investigate comprehensively and in subpopulations the effects of BFP on youth mental health, as well test mechanisms of this effect. The use of these databases will allow exploring mental health outcomes with a high level of statistical power. The databases used in this study have national coverage, low under-registration, and some have already documented reliability. Therefore, this study will provide a comprehensive and representative analysis of the poor and extremely poor Brazilian population and reinforce the adequacy of these bases for epidemiological investigations. Results from this innovative project are expected to inform national efforts to prevent mental illnesses among youth from low-income communities in Brazil through the scale-up of economic interventions; our findings may also be relevant to other comparable middle income countries experiencing challenges, such as those resulting from the economic consequences of the COVID-19 pandemic, to address the burden of mental health problems among youth and reducing mental health disparities.


Major technological advances in genomics have made it possible to identify critical genetic alterations in cancer, rendering oncology well along the path to personalised cancer medicine . Thanks The aim of this Special Issue entitled “Present and Future of Personalised Medicine for Endocrine Cancers” was to offer an overview of exciting new research in the area of endocrine tumours that may set the stage for an innovative personalised management and future precision medicine modalities for individualised care. This issue encompasses nine publications on basic, translational and clinical research in different types of endocrine malignancies, including thyroid cancer ,9,10,11,Looking across diseases, some themes are recurrent, such as the efforts to identify effective biomarkers useful to improve differential diagnosis and/or prognostication of endocrine cancers ,12,14,15Considering adrenocortical tumours, the role of several immunohistochemical markers for the distinction of carcinomas (ACC) from adenomas (ACA) and for prognostic stratification of malignant tumours have been investigated by Angelousi and colleagues, demonstrating that altered reticulin pattern and p53/Ki-67 expression are useful markers for the differential diagnosis of adrenocortical tumours . AnotherRegarding phaeochromocytoma and paraganglioma, which rare neuroendocrine tumours with uncertain malignant potential, Winzeler et al. extensively reviewed the relevant impact of molecular profiling for the understanding of the pathogenic mechanisms and for the prognostic classification, providing current and future opportunities for precision oncology .From a different point of view, Koot and team underlined the importance of considering patients’ needs, preferences and values in enabling us to improve doctor–patient communication and to develop decision support tools in DTC . Basile In general, there is agreement that further studies aimed at evaluating diagnostic, prognostic and predictive markers for therapeutic response are needed for tailoring patient management and allowing more appropriate treatment choices. We hope that future investigations, integrating modern molecular methodologies across cell and tissue models, computational approaches and prospective clinical trials, will continue to drive progress towards improved personalised management of endocrine cancers.


Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making. Accurate monitoring and forecasting of the quality of inland waters, defined here as lakes, reservoirs, estuaries, and coastal marine waters, is fundamental for developing sustainable water resource management strategies and ensuring the health of communities, ecosystems, and economies . Yet, ouhttps://www.geoaquawatch.org/, accessed on July 2021). Integration of inland and coastal water quality data products are required for the successful implementation of the United Nations 2030 Sustainable Development Goals (SDG) and the Sendai Framework for Disaster Risk Reduction. Water quality monitoring is relevant toward SDG 6.3 to improve water quality by reducing pollution, eliminating dumping and minimizing release of hazardous chemicals and materials; SDG 6.6 to protect and restore water-related ecosystems; SDG 14.1 to prevent and significantly reduce marine pollution of all kinds; and for disaster risk reduction water quality monitoring and forecasting is critical for the development and assessment of safe water and sanitation systems. Here, we provide a conceptual approach developed through GEO AquaWatch for integrating data products to create water quality nowcasts (very short time forecast) and forecasts. Some of the main challenges in water quality data integration are discussed in The Group on Earth Observations (GEO) AquaWatch is a community of practice that aims to develop and build the global capacity and utility of water quality data, products, and information to support water resources management and decision making. GEO AquaWatch targets a wide range of stakeholders, from economists to scientists, to industry representatives, resource managers, nongovernmental groups, and policy makers at the local, regional and national levels  or the Fiducial Reference Measurements for Satellite Ocean Colour (FRM4SOC)  across E3.2.Continuous sampling helps overcome the limitations of discrete sampling by providing high frequency measurements over time ,30. Suchwww.gleon.org, accessed on July 2021) has evolved to encompass nearly 100 of similarly purposed buoys across the globe. In addition to the data provided, continuous sampling also benefits the validation of remote sensing products. The dynamic changes that can occur in water quality variables throughout the day are shown in https://lexplore.info/, accessed on July 2021), which is an experimental platform deployed in 2019 on Lake Geneva and equipped with instruments that measure coupled biogeochemical and physical processes at fine temporal and spatial resolution. The platform aims to provide a wide range of open access in situ data  to foster interdisciplinary research, inform stakeholders on the lake status, and communicate science to the public. The temporal resolution and the variety of data measured at such platforms make them effective for validating remote sensing measurements and model simulations.Fixed platforms provide a different type of continuous sampling through a wide variety of techniques typically used with buoys or on hard-mounted platforms. The AERONET-OC network provides continuous and automatic measurements of the remote sensing reflectance in coastal waters . GLEON , addressing the gaps of lack of dedicated missions and high costs for vessels, is also a promising new technology for the monitoring of water quality with a revisit time of 3 to 5 days. Complementing these systems are a number of geostationary ocean color sensors (e.g. GOCI—Geostationary Ocean Color Imager) and meteorological sensors that demonstrated potentiality to observe turbidity dynamics (e.g. SEVIRI—Spinning Enhanced Visible and InfraRed Imager), and have the advantage of obtainaing hourly to daily data allowing the investigation of ocean properties variations over a day  https://wow.metoffice.gov.uk/, accessed on July 2021). Volunteer monitoring is also an effective approach for engaging the public in science and environmental monitoring, empowering individuals and communities to understand and manage the quality of their local environment [Volunteer monitoring often referred to as citizen science, is the collection of scientific samples and data by members of the general public . It is oironment . Volunteironment , althougironment .https://scistarter.org/, accessed on July 2021), and the development of mobile phone apps to gather geo-located data  electronically makes integration with satellite data relatively easy. Some relevant examples of citizen science projects focused on water quality are listed in The number of citizen science projects relevant to water quality monitoring is growing globally  models have the advantage of being computationally inexpensive and can provide good estimates of the seasonal dynamics . They arEcosystem models often focus on plankton communities, food-web structures, and population dynamics. The combination of such coupled hydrodynamic-biological models with in situ observations and associated data analysis has been widely demonstrated –117. A rThere is also reduced availability of data to characterize lake or coastal ecosystems using only a few sampling points, often only a single site per lake, which might not be representative for the entire system ,128. Mod4.GEO AquaWatch, long-recognized as the Global Water Quality Initiative with an extensive global network, coordinates an integrated approach to community stakeholder involvement, and its Knowledge Hub is recognized as a trusted global water quality data and information center. Ongoing efforts by GEO AquaWatch working groups and short-term, cross-cutting focus group activities have yeilded metadata compilations, best practices for data providers, aquatic analysis ready data recommendations, and expanded community-wide information-sharing. Transformational water quality knowledge is delivered to GEO AquaWatch stakeholders via our website and social media accounts, a successful and sustaining webinar series, topical workshops, and Initiative meetings. Printed and electronic work products, such as whitepapers, publications, and data products, services, and tools compiled by our diverse subject matter experts, are easy-access, community-wide resources serving the gamut of water quality users. Leveraging GEO AquaWatch’s association with other national and international water quality organizations amplifies best-practice messaging and enables broader user input.Stakeholder engagement in the delivery of fit-for-purpose, open source products, meeting user needs, is foundational to GEO AquaWatch’s portfolio of projects. A highlight is it’s namesake Google Earth Engine project for inland and coastal waters whichcompiles a reference database of biogeochemical, inherent, and apparent optical properties that is essential for calibration and validation of satellite products. AquaWatch features a self-guided user interface with a nimble API that delivers chunk-sized data streams to the Google Earth Engine Servers.To effectively achieve integrated inland coastal water quality management, users ideally inform their decision-making through combination of evaluating acute conditions and general trends in satellite-derived and in situ data, and utilizing iterative models; but we recognize many users lack one or more of these “three pillars” of data assimiliation and must otherwise rely upon the best available information. The complexity of environmental systems, and the need for meaningful information to be provided to stakeholders, requires the integration of data collected from different and heterogeneous sources. GEO AquaWatch’s Real Earth Portal, expected to debut in 2022, synthesizes multi-platform water quality data from disparate sources and over broad temporal-spatial scales accessible through the GEO AquaWatch website. Many hydrodynamic and ecological models have evolved as relevant predictive tools, and it is essential to accurately calibrate and validate them with available observations to validly represent the reality. Data fusion (DF) techniques have been used to maximally extract consistent spatial and temporal description of variables within hydrodynamic-biological models, cohesively and systematically, to produce more robust and informative datasets. DF algorithms include the wavelength-based method , the Joihttps://www.ars.usda.gov/research/software/download/?softwareid=432, accessed on July 2021), designed for the fusion of Landsat and MODIS images, is available for direct implementation of fusion techniques at the pixel level [NASA-promoted STAR-FM software  techniques have been used . DA enabhttp://pdaf.awi.de/trac/wiki, accessed on July 2021), the Data Assimilation Research Testbed , and the OpenDA , which was used successfully for the automatic calibration of a water level forecasting model [To promote and facilitate the use of DA methodologies, pre-fabricated algorithms and toolkits have been developed and made available from several working groups. These toolkits include the Parallel Data Assimilation Framework   . The ODYhttp://hiseaproject.com, accessed on July 2021) that delivers high resolution information obtained through the integration of in situ, remote sensing, and modeled data and the downscaling of Copernicus and NOAA products. Copernicus provides information at a regional scale that cannot be used to properly describe the system dynamics at the local scale. This is even more true for estuaries, coastal lagoons, and inland waters. HiSea aims to remove the barriers by making information easily accessible to a broader public through access to a single platform.The integrated framework described here for global and regional scale is also implemented by other platforms at local scales. An example is the HiSea platform ; EAWAG’s Swiss lake information portal ; the UK Lakes Portal  the HAB Satellite Analysis tool from San Francisco Estuary Institute ; Datalakes online platform for Swiss lakes ; CoBIOS: Coastal Biomass Observatory Services, the high biomass blooms in Europe’s coastal waters models; and MoS2 project for southern North Sea [A growing list of integrated data to information systems specific to water quality management includes NOAA’s tides and currents ; harmfulorth Sea . All theIn this paper, the framework for integrating data products, derived from multiple observations and modeling, through data assimilation techniques for regional and local water quality nowcasts and forecasts, is conceptualized. It is assumed that all models, satellite algorithms, and data products are already at a satisfactory level for stakeholder needs available as interpretation ready data. Prior requirements, such as calibration, validation, and data quality control and assurance, were outside the scope of consideration here. The sustainability of various observing systems remains a major concern. However, through improved communication between scientists and stakeholders, there is an improved likelihood that scientifically sound information can be transferred and understood by stakeholders for management decisions. Stakeholder obstacles include correct and easily accessible interpretation of data into information, particularly when programming skills may be required to derive additional information, and expert knowledge is required to understand technology limitations and capabilities.The GEO AquaWatch Initiative will continue to improve the transfer of data to information for water-quality-related decisions through integrated efforts, as conceptualized here. Moving forward, GEO AquaWatch recognizes the involvement of stakeholders at the start-up phase of any project and recommends defining integration needs based on stakeholder requirements, in addition to scientific requirements, to adequately address hypotheses. The value of information to stakeholders will be enhanced through the integration of data products in a standard approach using a common platform. This effort will enable users open access to readily available water quality data through data sharing and capacity building.