To the Editor—In light of the recent pandemic, it is normal for the health practitioners, researchers, and policy makers to concentrate primarily on the pathogen and biological threats to understand the pathophysiology involved and recommend steps for the prevention and containment of the disease. The media and public health generally focus on the biological and physical ramifications of pandemics. Under circumstances that threaten to one’s existence, mental health issues secondary to the primary challenge are often avoided. However, stable mental health is one of the keys to fighting this ongoing pandemic and to restoring a post-pandemic society.2 This phenomenon has been especially true for COVID-19. In a study conducted in China during the initial outbreak of COVID-19, 53.8% of the participants graded the psychological effects secondary to the outbreak as moderate to severe.3 This scenario raises many questions regarding the factors adversely affecting mental health and potential ways to approach this problem. To better understand the mental implications of a pandemic, it is mandatory to recognize and address the feelings attached to it such as fear, anxiety, and anger.The outbreak of coronavirus disease (COVID-19) was deemed a public health emergency of global significance by the World Health Organization on January 30, 2020. The ubiquity of fear and angst, resulting in irrationality among people amid infectious outbreaks, is not uncommon. Past tragedies have proven that mental health effects can persist longer and can have a much higher prevalence than the disease itself. In a pandemic, although uncertainty raises stress and anxiety levels in healthy individuals, it also aggravates the symptoms in those with preexisting mental disorders.4 mobility restriction associated with it is a major concern. A recent article by Brooks et al5 elucidates the psychological impact of lack of liberty among those quarantined. The uncertainty of the future causes distress to the affected individuals. When coupled with the restriction of social interaction, diminishing financial capital, and the continuous need for attention and treatment, this suffering can make life a living nightmare. Given the significance of mobility issues and financial crisis amid the COVID-19 outbreak, governments, as well as the private sectors, should deal with these issues efficiently by providing necessities to the commoners in the state of quarantine. It is essential that the general population does not succumb to this outbreak but stays organized and restricts circulation as much as possible and always to the fewest number of individuals.Although isolation, quarantine, and proactive social distancing are essential components for successful management of the current pandemic,6Internationally, stigma and resentment aimed at affected populations by other nations due to fear of infection deter cross-border trade have stirred further unrest. In the ongoing COVID-19 pandemic, many instances of xenophobic attitudes against people of Asian origin have been publicized. These range from refraining from sitting next to Asians on public transport to physical and verbal abuse. Such emotions can be exacerbated by pre-existing mental disorders, leading to an intensified rumination of illness contraction. Thus, combined efforts of the state, leaders, and health agencies are vital for fostering social cohesion that is essential to the prevention of prejudice associated with an outbreak.7 It is unfortunate and deeply disturbing to lose a life over the financial burden. This leads to another major concern regarding the economic impact associated with the epidemic and current quarantine. With the closure of industries and community services, many people face unemployment and financial distress, further fueling the negative emotions endured by many individuals.8 For example, the economic impact of the current epidemic in Japan has been drastic.2 Thus, people who have lower incomes and are rendered unemployed during quarantine might need extra support in such times of need. Governments can reduce the financial effects of isolation by halting tax payments or even by providing financial reimbursements.Regarding financial issues, the finance minister of Hesse state in Germany, Thomas Schaefer, committed suicide due to the falling economy during a prolonged countrywide lockdown.9 A lack of certainty about becoming infected and infecting others, as well as uncertainty about death, can aggravate a dysphoric mental condition.2 Thus, it is important to ensure that those affected by the outbreak have a clear understanding of the situation and the disease. It is up to the media to provide authentic information and regular updates regarding COVID-19 and professionals in infectious disease to alleviate the doubts. Last but not least, special attention should be given to the mental health of our healthcare workers at the frontline of the pandemic fight.10Another issue that warrants immediate attention concerns the spread of dubious information regarding the factors facilitating virus transmission, the number of people infected, and the mortality rate, which has led to fear and confusion among people. Easy access to communication devices such as mobile phones and various social media sites has proven to be a major contributing factor to the spread of inaccurate information. In turn, such misinformation has led to fear, confusion, and aggression among people.All of the aforementioned stressors deeply affect mental health and cause fear anxiety, stress, and paranoia; they also create global hysteria that must be dealt with proficiently. The psychological impact of quarantine is wide-ranging and is likely to prevail for an extended period. Although quarantine is essential during this pandemic, authorities should carefully control this situation and should provide people with necessities such as food, water, and medical supplies, as well as clear communications containing timely accurate updates regarding COVID-19 and constant reassurance. Currently, no such organization is working to enhance the psychological health of individuals during this outbreak. Governments and other authorities should assemble a task force consisting of psychiatrists, psychologists, and other mental healthcare workers to provide psychological first aid to the people, to advise the government in matters of psychiatric health issues, and to create policies to intervene in such situations. If such measures are not given priority, then at the end of this pandemic, nations will be dealing with massive psychological suffering.


M = 51.38, SD = 2.84) compared to those with correct estimates . Agreement between greenness scores at home but not at university was obtained, and mental health was related to the perception of greenness at university. We conclude that reliable and corresponding methods for greenness scores need to be developed.Research has reported the associations between objective or subjective neighborhood greenness and health, with low agreement between the greenness scores. College students are prone to poor health, and data are lacking on home and university environments. We studied the agreement between greenness parameters and the associations of objective greenness with health in different locations. Three hundred and seventy-seven college students were recruited, with a mean age of 24 years, in the city of Graz, Austria. Objective and perceived greenness was assessed at home and at university. Health measures included the WHO-5 questionnaire for mental health, the IPAQ questionnaire (short) for physical activity and sedentariness, and body mass index. Per location, quintile pairs of objective and perceived greenness were classified into underestimates, correct estimates or overestimates. Interrater reliability and correlation analyses revealed agreement between greenness scores at home but not at university. ANOVA models only showed poorer mental health for students underestimating greenness at university ( The biophilia hypothesis states that humans have developed and maintained an affinity for nature throughout their evolution ,2. AlthoThe assumption, the mere existence of nature around people’s residences influences health, does not incorporate human information processing. A second dimension therefore needs to be addressed, namely, how the real (objective) environment is subjectively perceived. The idea that the degree of perceived nature in a resident’s immediate neighborhood is equally important for certain health parameters arises from studies incorporating both objective and subjective measures of greenness in their designs ,17,18,19Most previous studies have assessed the effects of greenness in the neighborhood of residents’ homes or unspecified locations ,22, althThis study aims to gain new insights into the agreement between the objective and perceived neighborhood greenness for college students at home and at university. As a second aim, we want to explore the association of objective neighborhood greenness in both locations with mental health, physical activity, sedentariness and BMI in students.This study is part of a larger research project, which collected data via an online survey between October and December 2017. For the current paper, we investigated the agreement between objective and subjective greenness measures as well as their importance for different health parameters.2. The neighboring campuses of the three major universities  form this university district. There is only little distance between the respective campus areas, which is why quite some students travel frequently between the facilities due to the range of interdisciplinary and interuniversity study programs. In Graz, students do not live on the campus area; they have their homes elsewhere in the city or surrounding areas. Due to these characteristics, Graz was considered a good place for representative student data in (mid-)Europe. This research project has been approved by the ethics committee of the University of Graz (GZ 39/58/63 ex 2016/17).All study participants had their homes and study environments in and around the city of Graz . Graz is predominantly known for its university area, has approximately 300,000 residents and spans 128 kmHow data was acquired has been described in two previous papers ,29. In sFrom a spatial science perspective, the attempt to quantify greenness measures—with as little subjective bias as possible—is based on the recording of land-cover/land-use features’ spatial distributions, which are interpreted as relevant for greenness in the context of this study  . SpecialIn the online survey, participants were asked to allocate and mark their approximate home and study environments on an interactive map. They were instructed to place the map pin somewhere near each location (at least in front of the relevant building). They were not asked to indicate their exact address, since this might have decreased compliance due to data security concerns. In order to derive a reasonable buffer zone within which they were expected to be active around each location, they were asked how often they used different modes of transport. As was to be expected given the composition of the sample, the participants primarily used bicycles and public transport. Based on this finding, a zone of activity-buffer was chosen to define the area used for a realistic determination of the objective green value. This allowed both bicycles and public transport to be considered as means of transport. The research project did not collect data about the daily bicycle routes of the participants, and since the possible entry points into the road network system in Graz are ubiquitously distributed, the parameterization of the buffer width was primarily oriented towards the public transport stops. Based on the maximum values for both the nearest stops for each individual’s home  and university , a buffer zone of 300 m for both locations was defined. This range is in line with the recommendation of the European Commission that open public spaces should be within a distance of 300 m around residences . Single For the implementation of the spatial analysis concept in a GIS, geo data of different origins—official as well as semi-official—had to be used to enable all the analyses required. This procedure necessitated a data homogenization step preceding the core analyses to ensure the quality of the results. The base map data were accessed via OpenStreetMap Sources over the internet . In ordePerceived greenness measures were previously described in detail . MeasureAccess to parks or nature?Access to walking or bicycle paths?The presence of greenness?The presence of trees/tree density or canopies along footpaths?The presence of other natural features?Overall, how would you describe the quality of the green/blue space at your location?How would you describe:Means of all the answers per location were calculated and then transformed into percentages, which led to a measure for perceived greenness at home and at university. In order to make a comparison with objective greenness, a variable “perceived presence of greenness” was created from the means of the three items focusing on the presence of greenness, trees/tree density or canopies and other natural features per location.The objective and perceived greenness measures differed from each other in their characteristics, i.e., the responses to questions about the subjective accessibility, quality and presence of greenness vs. the objective presence of greenness. Although the perceived presence of greenness was added as a parameter more similar to objective greenness, there are still differences in how these variables were measured. Therefore, objective and perceived greenness measures were divided into quintiles, resulting in five almost equally sized groups for each variable (from the first quintile with low greenness to the fifth quintile with high greenness), as shown in Mental health was assessed with the German version of the WHO (Five) Well-Being Index, which focuses on the last two weeks of wellbeing ,36.Physical activity was assessed with the German version of the short-form of the IPAQ questionnaire . The act2).Participants were asked about their height and body weight to obtain the BMI score of each individual  was analyzed using univariate two-way ANOVA models. Two-way multivariate mixed-ANOVA models were used to adjust the objective and perceived greenness scores for gender and marital status. Post hoc comparisons were accomplished via Bonferroni corrections. Linear regression models were used to assess the associations between objective greenness scores and the relevant outcomes.SD = 7) years. Additional characteristics of the sample can be found in The study sample consisted of 377 college students, 281 (75%) of whom were female, with a mean age of 24 . Tolerance statistics and variance inflation factors indicated that collinearity was not of concern.The collinearity checks are summarized in M = 79.49%, SD = 16.40%) and the university environment  as well as the scores of the perceived presence of greenness at home  and at university  were high, in general, compared to objective greenness at home  and at university . Pearson correlations yielded a significant but small-to-moderate correlation between objective and perceived greenness at home . However, no correlation between objective and perceived greenness at university was found . The perceived presence of greenness at home correlated significantly with objective greenness at home , but there was no correlation between those measures at university . Significant correlations were obtained for the perceived greenness at home and perceived presence of greenness at home  as well as for the perceived greenness at university and perceived presence of greenness at university .The perceived greenness scores for both the home environment . No agreement was found for the estimates of objective greenness at university and perceived greenness at university . κ = 0.15, p < 0.001), but there was also no agreement for the presence of greenness at work .Similarly, there was significant agreement between the estimates of objective greenness at home (based on quintiles) and perceived greenness at home  compared to those that correctly estimated greenness at university  = 4.06, p = 0.014). No differences were observed between people who correctly estimated or overestimated greenness at university, nor between those who underestimated or overestimated. No differences were found between groups for the estimation of greenness at home. The results of the ANOVA models can be found in the Supplementary Material , sedentariness (hours spent sitting per day) or BMI between people who underestimated, correctly estimated, or overestimated greenness at home and at university. The results did not change when the ANOVA models included gender, age, income, education and marital status as covariates (data not shown).Two-way multivariate mixed ANOVA models with objective and perceived greenness as dependent measures showed no significant differences according to gender or marital status .No significant associations between objective greenness and mental health, physical activity, sedentariness or BMI were found. The results can be found in In this study, we aimed to analyze the agreement between objective and perceived greenness measures at home and at university and to compare the mental health, BMI and physical activity of people who underestimated, correctly estimated or overestimated greenness in those distinct places.In line with our expectations, we found a small-to-moderate correlation and agreement between objective and perceived greenness at home. However, no correlation or agreement was found between objective and perceived greenness at university. This last finding corresponds with previous research reporting a lack of agreement between objective and subjective greenness scores ,20. A poPeople who underestimated, correctly estimated, or overestimated the greenness at home or at university were not different with regards to their physical activity level or BMI. However, people with poorer mental health were more likely to underestimate greenness at university but not at home.Most of the prevailing literature on green space does incorporate greenness in distinct locations ,22. ThisOur results might have been influenced by the difference in the greenness measures taken, since perceived greenness scores included the accessibility, quality and presence of greenness, and the objective measurements could only reflect the presence of greenness. However, analyses with the variable “perceived presence of greenness” did not change the results. High correlations between the perceived greenness and perceived presence of greenness show that a large part of the variance is shared between those variables.The authors of another study that focused on both objective and subjective greenness argued that the lack of agreement between those values is to do with how measures are assessed . ObjectiPeople who underestimated greenness at university had poorer mental health compared to people who correctly estimated this. Previously, we reported an association of the perceived greenness of both the home and university environments with mental health . HoweverHighly green environments in cities, which are more favorable residential environments, are rather chosen by people who can afford to live there . In lineThe method used for measuring objective greenness has its shortcomings, which are primarily due to the available data material and the resulting weaknesses. If one accepts the basic concept of quantifying greenness by means of the greenness component in relation to the (recognizable) overall environment, two main problems remain to be solved. First, the question of which characteristics that can be depicted in spatial databases make an evaluation in the sense of the present study possible at all needs to be answered; in other words, a consensus has to be created regarding the attributes of greenness, whereby these have to be collected and entered into the spatial databases. The second problem deals with spatial perception; apart from the generally inadequate consideration of the third dimension (height), as mentioned earlier, aspects essential for the study have not been considered at all so far—the limitation of the area able to be seen/recognized by the human field of vision and the effective range of our vision. Finally, the different cognitive abilities of the individual participants should also be taken into account.This study did not collect data on indoor environments. However, positive health outcomes can be expected from green indoor environments, such as reduced air pollution, which is partially mediated by the greenness of the outdoor environment . SimilarBased on the results of the current study, future research could entail a more detailed look at the association between both objective and perceived greenness in the context of different environments, such as at home, places of study or workplaces. Further research is needed to explore the implications of this approach. In line with this, more valid and reliable methods are needed to uncover the “true” relationships between objective and subjective greenness. This means that study designs including objective measurements need to take into consideration how study participants perceive and describe their environments at eye level . For insIn addition, questionnaires and other methods for assessing perceived natural features also have to be refined and adjusted in a direction that is in line with what is currently technically possible for obtaining objective values.In order to develop effective public health strategies, the drivers of the association between greenness and health should be of major interest. Therefore, it is important to assess whether the subjective perception of greenness, instead of objective greenness, is the most important factor in this association. If so, we need to better understand which features of objective greenness have the greatest impact on peoples’ perception of nature, in order to improve their health outcomes.This study found positive associations and agreement in the ratings between objective and perceived greenness for home but not for university environments. Students underestimating greenness levels at university showed poorer mental health scores compared to those who correctly estimated greenness at university. The results indicate that more attention should be paid to developing validated, reliable and corresponding methods for assessing both objective and perceived greenness scores. Future studies are needed in more diverse populations and in other geographic locations.


Cultural heritage capitalization in rural areas redefines the local development model. Thus, heritage tourism has become the engine of economic activities diversification. This study aims to identify a decision-making-model substantiating algorithm in order to support the local heritage capitalization , based on three types of qualitative researches, and the improved Analytical Hierarchy Process (AHP) method. In case of lesser known heritage, trademark potential and international cultural tourism route for heritage capitalization are smart choices for the innovative local hub development. The developed AHP version allows for a broader investigation of the characteristics that can lead to a trademark associated development based on integrated and innovative tourism products. To substantiate our approach and validate the model, we conducted a pilot study on a geographic area , slightly exploited from the perspective of heritage potential, and characterized by a combination of heritage assets. The study’s results can be used by local authorities as a foundation for sound and strategic development of the area with economic potential from tangible and intangible heritage (re)interpretation. Heritage has a complex meaning, which includes tangible and intangible elements defining time and space that can be associated with culture and nature. Through tourism, cultural heritage can be transformed into an important resource for local economic development . With thA trademark is used to distinguish one entity’s goods or services , 5. It iCultural tourism development is conditioned by regional strategic planning and resource allocation from public bodies and the entrepreneurs’ level of involvement , which mDigitalization and social media have promoted higher basic cultural heritage knowledge. It is proven that the presence in social media of heritage tourism positively affects tourism entrepreneurship . TherefoTourism has been recognized for stimulating economic development, increasing exchange, smallholder investment, and local employment . HoweverIn the past decades, Southern Transylvania–Romania, has developed an increased interest of various categories of niche tourism consumers–who wish to experience daily life "returning to the wild natural ecosystems" and authentic cultural consumption, based on local heritage. Transylvania is recognized for several world heritage like Sighisoara town—a small scale fortified living citadel built in the 12th century , Alba IuThis study aims to: a)identify a decision-making model algorithm applied at local level to support rural development through cultural heritage capitalization , based on the improved AHP method; b) to identify the most valuable alternative from a set of strategic alternatives for rural development identified at the regional level. Using a collaborative-approach, our study evaluates the potential of rural development starting from a set of criteria, considered to be important by local stakeholders. Several late researches identified the multiple potential of the decision- making process’s method in different industries , 24 or dThe present work’s contribution is also theoretically–the development of the AHP model, applicable in the area of heritage capitalization, can contribute to an appropriate decision-making algorithm development. To substantiate our theoretical approach, we conducted a pilot study for less known rural areas located in Sothern Transylvania, based on cultural potential and characterized by a combination of built heritage and natural assets with a rich local intangible heritage .Based on the extension of the decision tree, this study also provides a developed version of the AHP method by including particular aspects of local interest and/or relevance. The developed version allows for broader investigation of the defining characteristics that can lead to the development of a trademark associated with the ongoing demand model for cultural heritage capitalization in the context of integrated innovative tourism products in Southern Transylvania. The added value of promoting local authenticity and developing branding on the visibility, attractiveness and economic efficiency of tourism services associated with cultural consumption was investigated using the experts’ opinion on the developed AHP model.Furthermore, we intended to examine whether the existence of notorious exploitation models of the built heritage  in the vicinity increase the potential for rural tourism and economic and social development of the areas included in this study.th century contributed to the reintroduction of the rural tourism concept, using the long-distance railways network as a link between the main cities of the continents. Following the Second World War, the concept of rural tourism has expanded, throughout the world [The 19he world . Develophe world . Touristhe world –33.Several dimensions of culture are associated with tourism, each of which contributes to the economic development of the community . Since tth century during the reign of Carol I of Romania, Prince of Hohenzollern-Sigmaringen, belonging to the Royal Family of Romania), was included in almost all tour packages in Romania [Transylvania has a rich cultural heritage, which contributes nationally to the development of tourism , 65. Pro Romania . Althoug Romania . One of  Romania . It is kOver the years, researchers have concentrated their work on theories that prioritize the conservation, restoration, and rehabilitation of cultural heritage sites by using different methods of multi-criteria decisional analysis –74. Morehttp://portcultural.usv.ro –, in order to define additional instruments for supporting strategic planning in rural areas with heritage trademark potential.Data field collection was carried out in 2019, during which working visits were made within the multidisciplinary PORT Cultural project - The theoretical model of decision analysis development has been tested in rural areas located in Southern Transylvania. In the first stage of our investigation, we identified more than 100 potential heritage-built assets that can be capitalized and for which trademarks can be developed hence analyzing, from a monographic perspective, the potential of the associated areas—the rural localities/villages. The selection also considered the (co)existence of intangible heritage elements, that could power the cultural and tourist consumption attractiveness of a wider variety of consumers / tourists, without depriving the local authenticity. Demographic, economic and social factors were selected for monograph development. The 100 built heritage identified in rural areas were documented using photographs and were located in space, and the owners were interviewed, after which they completed a questionnaire consisting of several sections . The local heritage components that define each area were selected, while considering: the European history intrinsic value, the state of cultural heritage conservation assets, specific cultural diversity, local traditions and crafts, natural landscape and other intangible heritage elements.In the second stage of the field research, in order to evaluate the potential of exploiting existing heritage through tourism, the following aspects were considered: access to road, rail and sanitary infrastructure, number of tourists in the area, possible available accommodation facilities, recognized tourist attractions, the specific cultural activities of the area, etc. Based on the international visibility of the new patrimony objectives and the development/completion of the cultural and thematic routes, we also analyzed the existence in area or in the near vicinity of the recognized heritage brands or trademarks .As the research focused on the heritage assets in rural areas, the natural potential was identified hence its status has been evaluated—the level of human intervention/alteration of the habitats, the air quality reported in the area, the presence or proximity with natural parks/reserves and the existence of natural elements of uniqueness . In this study we excluded the rural areas already presenting innovative entrepreneurship models and those developed from a tourist, economic and social perspective . However, these represented reference points and models of good practices in the subsequent research in defining the model/profile of entrepreneurial development and designing the integrated local strategy.Data on the number of tourists and the accommodation capacity of the analyzed areas were selected from the official statistical database (NIS on-line database). The annual reports of the National Environmental Guard provided data on air quality. The specific cultural activities and hospitality infrastructure  were extracted using TripAdvisor™ and Booking™ sites. Specific data were also obtained with the support of the local public authorities.Additional criteria for the inclusion/exclusion of the researched areas namely the level of entrepreneurial development in rural areas , the level of accessibility and the existence of other recognized forms of tourism or rural tourism development potential  were considered. Using the AHP method, many researchers applied similar criteria on cultural heritage/ cultural tourism assessment –84.Following the collection of these data, we established several areas of interest for our multi-criteria decision-making analysis, both geographically and socio-economically similar. Rural areas with similar characteristics and with close geographical proximity have been grouped into clusters. These clusters form the 16 alternatives included in our research and are briefly described in All the 16 selected alternatives contain rural areas that are characterized by a complex and multicultural landscape that incorporates cultural heritage elements (tangible and intangible) with an increased potential in trademark creation. The alternatives were chosen by the experts from the project research team, based on the analysis of the data described in recognized brands, the level of accessibility, the classification of the areas in the natural landscape, the existence of cultural heritage as well as the facilities offered by the selected alternatives. The criteria’s description can be identified in In our approach to identify and prioritize the alternatives for strategic rural development through innovative heritage entrepreneurship, several criteria were chosen with the help of the data collection process. During the working meetings and with specialists, we conducted several brainstorming sessions, for the selection of the main criteria needed to apply the multi-criteria decision analysis, based on the developed AHP method. These main criteria refer to the area’s AHP has multiple applications in optimal allocation of resources. It has been shown particularly useful in urban or rural valorization process and development process, as a tool of mediation among multiple and sometimes divergent interests and it is able to create a shared platform among decision makers and stakeholders directly affected by the final decision. AHP deals both with the problems of efficiency and equity of choices. In this sense, AHP is a flexible instrument to compare values and qualitative aspects of decisions considering all various aspects of a problem. It integrates knowledge of different fields of expertise, considering the complexity of the context and the consequences of every alternative option.Using the AHP multi-criteria decision-making method, we identified the most suitable area for rural development through innovative entrepreneurship by highlighting the cultural heritage in the rural area, with potential for a trademark design. In summary, the research was structured in the following steps:Step 1: Defining the main purpose  of the research and selecting the outcomes.Step 2: Conducting field study visits and developing monographs for each of the initial selected areas, organizing qualitative research based on focus groups and in-depth interviews, brainstorming sessions with the project research team and literature review in the field. Based on the results obtained in these activities, the evaluation criteria and their importance were established from trademark creation and strategic rural development perspectives.Step 3: For accurate research results, we collaborated with experts in the reconditioning cultural heritage, the landscape and natural sciences, the rural entrepreneurial development, the behavioral theory of the consumer and tourism economics. The experts were selected based on the discussions within the focus groups, their independence and activeness in the business environment. The selected experts independently analyzed and evaluated the specific established criterion having the freedom to assign and assess sub-criteria where appropriate, based on professional experience and reasoning.Trademark criterion–is the Brand manager in a national based company, specialized in branding strategy or brand story design, identifying the main target group of the brand and the company's core values, building the brand positioning and communication strategy for the market. Using professional skills and rationing, expert 1 established 5 sub-criteria for the Trademark criterion and weighted an importance for each sub-criterion. For example, expert 1 considers that the trademark for local tourism development is perceived differently depending on the profile of visitors, the presence and promotion in the online environment of recognized tourist objectives, the authenticity of experiences given by visiting trademarked places. Therefore, these are some of the sub-criteria assigned by the expert to the trademark criterion.Expert 1 –selected for the evaluation of Accessibility criterion analysis–is an independent expert, self-employed specialist in the economic impact and counterfactual analysis, spatial development, rural entrepreneurship and sustainable growth of the small areas. Expert 2 considers that an objective can become of tourist interest if it is located in an area with high accessibility, for example close to main roads, railways or airport. However, from the professional experience, the expert considers that, on the contrary, a certain type of tourists visits areas that are not easily accessible, out of the desire to disconnect from work and their normal life. Therefore, two sub-criteria were considered relevant by the expert, namely: easy access and remote. These two sub-criteria for the Accessibility criterion and weighted an importance to each one.Expert 2 –selected for the Landscape criterion–is an architect specialized in landscape, urbanism and spatial planning, sustainable development, urban and rural revitalization, mobility, capitalization of natural and built heritage and energy efficiency of new and old buildings, being a member of a specialized NGO in Built Environment, active in Southern Transylvania, with multiple projects to enhance the natural environment and its integration in cultural and leisure routes. In the context of the potential for tourism development, given the potential profile of tourists, expert 3 considers that a rural area can be developed for tourism if the area is recognized for good air quality, natural beauty (eg nature reserves) or other attractions. travel. Therefore, expert 3 established 3 sub-criteria for the Landscape criterion and weighted an importance to each one.Expert 3 –chosen for the evaluation of the Cultural Heritage criterion–is an economic expert in cultural heritage capitalization. They were a national expert for the Ministry of Culture from Romania and the National project manager for INE, in THE JOP BLACK SEA CBC ALECTOR Collaborative PROJECT Multilevel networks of Actors, to advance Quality Standards for Heritage Tourism at Cross Border Level. Expert 4 was also the National Project Manager for Launching local level entrepreneurship heritage: strategies and tools to safeguard the United forces, like cultural values, mobilize, and deliver the experience (SAGITTARIUS). SEE schedule, with Certified EQF 06, expert in heritage interpretation. Expert 4 did not consider it necessary to assign sub-criteria for the Cultural Heritage criterion, considering however, that this main criterion must be highly important for the analysis performed using the multi criteria analysis method.Expert 4 –selected for the Facilities criterion–is a specialist in tourism economics and innovative hubs development Agency and is the promoting international tourism marketing manager for integrated hospitality, specialized in the incoming activities for the tourist’s International member EVANEOS. The expert considers that already existing accommodation facilities, restaurants and tourist activities in one area can contribute to rural development. Thus, expert 5 assigned 3 sub-criteria for the Facilities criterion and weighted an importance to each one.Expert 5 –selected for the Step 4: Application of the AHP method according to the methodology developed by Saaty [by Saaty , and theThe criteria selection method, which was based on both quantitative and qualitative approaches, started from statistical evidence and evaluating identified heritage potential in each area, as described in Section 2.Simkova  describeAfter the development of the monographs in the research area, we identified and selected the localities/villages with the highest potential for rural heritage trademark creation and capitalization. In addition to the components mentioned by Simkova in , we seleThree qualitative methods were used to identify the analysis criteria and to substantiate their choice i.e. a qualitative survey based on defined questionnaire applied to the owners of the 100 built heritage assets identified in the area and eight focus groups with local stakeholders, including public authorities Existing facilities in the area were discussed to be important for their investment decisions. In addition to the attractiveness of the area, most said that infrastructure is also important, both road, air or rail, and health. Others believed that there is a need for a quiet, authentic area with little impact on the environment, which has not undergone significant changes due to technological developments to develop rural cultural tourism. All participants were of the opinion that cultural tourism is frequented by a certain category of people, being considered a form of niche tourism. Participants also stated that they are willing to invest in rural cultural tourism by creating innovative and sustainable business models. One of the participants stated:"If I knew exactly where I should place my tourism business, I would implement a locally innovative idea to create a successful sustainable business model that would bring fame to the area and stimulate the local economy." Based on the preliminary results of the on-site meetings with local entrepreneurs, we built an AHP model using the selected criteria: trademark potential, accessibility, landscape, existent cultural heritage capitalization potential and facilities. Each criterion was assigned to a collaborating expert for further analysis. The experts created sub-criteria where they considered and established the importance  of eachgoal, criteria, sub-criteria, and alternatives selection. We developed the AHP model version, with three levels as shown in The pairwise comparison method was first introduced into research by Fechner . Thurstoalternatives are the different options being weighted in the decision. Criteria and sub-criteria are the factors used to evaluate the alternatives regarding the main goal , testing the consistency of comparison matrices becomes extremely important for establishing viable final results. However, Saaty has introduced indicators for calculating the consistency of a matrix, called consistency index (CI) and consistency ratio (CR), which allow the consistency of the matrices developed in the decision-making process to be checked, given the human errors that may occur. He considered the CR level at a maximum of 0.10 to be acceptable, which means that the comparison matrix must be at least 90% consistent. In order to determine CR, first we had to determine CI  and Random Index (RI). We used the values of RI for our analysis as they were calculated by [A matrix lated by .CR<0.10), we normalized the values in order to homogenize the data obtained through initial evaluation. The general normalized matrix If the pairwise comparison matrices were consistent  with those obtained by each alternative. The final results  are represented by the sum of the scores obtained by multiplication of each line . For an easier interpretation of the results, we ordered the alternatives depending on the score obtained. Thus, the alternative with the highest score obtained ranks 1king see .To determine the best alternative for investing in the development of cultural tourism in rural areas, we used five criteria that local stakeholders (present at meetings held in the first stage of research) mentioned as basic for investing in business models in the field of tourism. Therefore, our analysis responds to the needs of entrepreneurs involved in tourism industry of Southern Transylvania rural areas. Criteria and sub-criteria priorities, as well as their rank are found in Trademark criterion obtained the highest score, with an importance of over 30%. It is followed by the Facilities criterion, Cultural Heritage, Landscape, and Accessibility, respectively. The sub-criteria rank was established by comparing each sub-criteria pair established by the independent experts (see The erts see .Facilities criterion), followed by the two sub-criteria given by the Trademark criterion . The capacity and type of accommodation, as well as the existence of restaurants in the area are also crucial sub-criteria. The criteria and sub-criteria matrix’s consistency ratio is below the acceptable value of 0.10  of the other areas in the immediate vicinity. Thus, directing resources to the area with the greatest potential will maximize the effects of development resource allocations and it creates a high drive effect for the adjacent area. Therefore, with the help of the AHP method, we aimed to determine the best alternative for rural development in the area of Southern Transylvania.The obtained results can be used as a starting point in the development of rural development strategies applicable in Southern Transylvania. The analysis performed using the AHP method allowed the ranking of alternatives according to some criteria established following concrete discussions with local stakeholders. The most important findings can be further chosen for an in-depth analysis, in which the alternatives with the highest overall priorities can be analyzed based on an economic approach, thus extending the research.A14. The tourism development potential of A14 is proven by the scores obtained by applying the AHP method. Investments in this area will lead, in turn, to the development of neighboring areas, following the same assumed principle, that the existing trademark in the area contributes to the growth of tourism in neighboring areas. Our results can contribute to the enhance of regional and national strategies for rural development and resource allocation that may support heritage rural tourism and stimulate economic growth improving the quality of life in many of the less developed areas of Southern Transylvania.Based on the results obtained in this study, we propose that stakeholders consider the investment decision for the development of a heritage business model in the area indicated by A14) is located near the national and European interests’ cultural heritage elements. The consistency ratios of the matrices  confirm the accuracy of our results. The cultural tourism models developed in this area are innovative and integrate the area into the European cultural landscape.The results outweigh the investment potential in rural areas with partially/remotely capitalized cultural heritage. The research also highlights the importance of existing TCEs for increasing competitiveness among cultural and/or natural heritage and tourism markets. Our research allows the recognition, ranking and selection of entrepreneurial development opportunities in rural areas with cultural heritage potential, with a positive impact on local economic and social sustainable development. Therefore, this study’s results show that cultural heritage, trademark, as well as the facilities offered by the analyzed areas, significantly contribute to choosing the best alternative for entrepreneurial development. Moreover, the criteria’s evaluation performed by the experts strengthened these results. Therefore, the level of accessibility of a place is not necessarily important for the investment decision. However, the history of the place, transposed in elements of cultural heritage, both tangible and intangible, is important. The best investment decision’s alternative  in rural areas. The study’s results can be used by public authorities as foundation for a sound strategic development of the area with economic potential from tangible and intangible heritage (re)interpretation for the benefits of everybody, according to Agenda 2030 goals implementation in rural areas.A14, which provides a generous area in which stakeholders can elaborate various heritage-based business models. Moreover, the examples of successful entrepreneurship models already existing in certain areas of Southern Transylvania can provide support in starting the investment process. Furthermore, with the help of the AHP method, taking into account the criteria established together with the local entrepreneurial environment, we narrowed the area of interest for the potential for tourism and entrepreneurial development in the area of Southern Transylvania. Thus, we propose that in the future the alternatives with the highest overall priorities should be subjected to in-depth economic analyzes.In addition to the theoretical implications of this study, some practical implications are underlined. The results of our research highlight the tourism development potential of MCDM, in general, is an analytical method that involves subjective decision makers. Even though we measured the consistency of the comparison matrices during the entire process of evaluation, the experts’ opinion in assessing weights and priorities may indicate subjectivity issues. Thus, we considered this a limitation to our research.For further research, the following directions were identified: the extension of the monographic analysis and application of the AHP method for the second area selected in the ongoing Port Cultural project, for Bucovina in the Nord-East of Romania; the extension of the study by adding other two criteria that will allow on the one hand the transition to the development of smart villages that use digital technology to promote the local cultural heritage digitization the tourism product to capitalize the cultural heritage objective and promoting multisensory experiences in-situ  and on tS1 Text(DOCX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S3 Appendix(DOCX)Click here for additional data file.S4 Appendix(XLSX)Click here for additional data file.


Background: Tobacco growing has been considered a mainstay of Mozambique’s economy, but there is a dearth of analysis of the tobacco policy landscape in the country. Methods: Review of government and non-government documents and academic papers addressing Mozambique’s tobacco-growing history, the changes in the political economy of tobacco, and health policies addressing tobacco use and prevention of noncommunicable diseases. Results: Despite its tobacco growing and exporting history, the contribution of tobacco to the economy has been in steady decline in the past two decades, including in the areas dedicated to growing. At the same time there has been an increase in multinational control of the tobacco economy. In parallel, Mozambique’s commitment to addressing the growing burden of noncommunicable disease and accession to the Framework Convention on Tobacco Control indicate a potential for internal government tensions to balance immediate economic interests with long term health goals. Conclusions: With the decline in tobacco share of the overall economy, Mozambique may be well-positioned to explore alternative, sustainable livelihoods for farmers that grow tobacco, but it must overcome inter-sectoral barriers and advocate for a whole of government approach to address the health and economic impact of tobacco. Tobacco control requires action at different levels and across different sectors. The slate of policies required to reduce demand are well known and supported by decades of evidence of effectiveness . TaxatioTobacco was first introduced in Mozambique in colonial times by Portuguese traders and was traditionally grown by African peasants for domestic consumption. At the beginning of the 20th-century, tobacco became a commodity in Mozambique that could be exchanged for clothing and other consumer goods on the market as well as a source of income to pay mussoco, the colonial tax. The districts of Malema and Ribàué in the province of Nampula, today is known as two of the most agriculturally productive districts in the country, became the center of tobacco production in settlers’ farms, a production that reached an average of approximately 3000 tons per annum at that time. Without agricultural assistance or access to credit, the relative success of tobacco production was largely dependent on the mobilization of forced labor for Portuguese farms. Navohola  calculatPrior to obtaining independence from the Portuguese regime in 1975, tobacco farms flourished in central Mozambique due to the inexpensive forced labor and expropriated land . TobaccoMeticais annually in tax revenue to the state [The Republic of Mozambique is located in South-East Africa and is utilized by neighboring landlocked countries to access external markets. Mozambique has a population of 28.9 million, of which 84.9% are active in the formal economy. Smallholder farmers (SHFs) account for 86.2% of the rural population. Mozambique’s arable land accounts for about 36 million acres, and agriculture accounts for up to 80% of the nation’s economic workforce, though it only accounts for 25% of the nation’s GDP . In thishe state .With roughly 98% of tobacco being produced by SHFs . The comBetween 72,000 and 124,000 households grow tobacco out of 3.9 million farming households total nationwide, with higher concentrations of tobacco farmers in the Tete and Niassa provinces, which together in 2017 accounted for approximately 78% of the total number of growers. The total number of farmers varies considerably annually, however, and data from national agricultural surveys conducted by MADER show a consistent decline in Zambézia where alternative livelihoods have been promoted. The export data presented in According to data from the Ministry of Agriculture , which aIn addition to job creation opportunities and high demand from a diverse market, the incentives of tobacco production, specifically for rural smallholder household welfare and farming systems, have been plentiful. Data by the national agricultural sample survey (TIA) in 2002 revealed that at the time, the incomes of tobacco growers were much higher than those who did not produce tobacco ,22. The Tobacco production in Mozambique is regulated by the Tobacco Promotion, Production and Marketing Regulation   and by tThe first of these elements, the interconnection between the input and production markets, served as a solution to the lack of credible sources for agricultural producers ,28. The In 2005, there were about 129,000 agricultural producers with tobacco production contracts. Of these, there were 34,813 producers in Niassa and 43,464 in Tete. MLT was the main buyer and had concessions in Tete and Manica. According to the 2001 Tobacco Regulation, under article 2, there are four classes of economic operators in the tobacco production space , started operating in Mozambique in the mid-1990s, joining companies such as JFS and SONIL, which have worked in Mozambique since the colonial period but were new to the tobacco trade. Stancom was present in Manica, and as a subcontractor for SONIL and Mosagrius, in both Niassa and Cabo Delgado province. Dimon worked in Tete, Manica and Sofala. The other major player, JFS, was a Portuguese Mozambican business group with tobacco and cotton contracts in Nampula, Niassa and Cabo Delgado province . AlthougThe mid-2000s marked a turning point in the trajectory of the tobacco market in Mozambique. There were three developments that determined, from then on, the evolution of the sector: technological developments such as the creation of a processing factory in Tete province, which ended the need to send raw tobacco to Malawi for processing; the withdrawal of the Chifunde concession, which led to the departure of Dimon Inc. from Mozambique; and the failure of tobacco production in the province of Manica. In the early 2000s, tobacco from Mozambique had a consolidated presence in the international market, but it had to be exported to Malawi or Zimbabwe, to be processed, and reexported through the port of Beira city in Sofala province since there were no processing facilities in Mozambique. This resulted in additional transport costs and loss of revenue. An internal proposal was studied at the MADER to introduce an export tax of 20% on the value of raw tobacco to force commercial companies to invest in a leaf-cutting infrastructure in Mozambique .An internal document from 2004, prepared by the National Directorate of Agrarian Services of MADER was quoted by Benfica and colleagues  and arguIn 2019, a media source published that China was due to import approximately 60,000 tons of tobacco from Mozambique until February 2020, making them the second-largest tobacco importer. Mozambique’s current President, Filipe Nyusi, stated that the sale of these products would improve the livelihood of local farmers . To confAs stated in earlier sections, the general consensus for producing tobacco is to improve farmer livelihoods. Although cotton and tobacco have a long history as cash crops in Mozambique, there are other cash crops that have recently been introduced to farmers. Soybeans are one example of a crop grown as an alternative to tobacco. The percentage of growers of tobacco at the national level declined slightly  as farmeThe project invested heavily in extension services, machinery, post-harvesting technologies, and a seed factory. In 2002 about 3.5% of farmers in Zambezia cultivated tobacco, and no one grew soybeans. By 2017 the percentage of tobacco growers in Zambezia had declined to 0.8%, and there was a shift to soybean production  attributed to the guaranteed market for soybean seeds, which, unlike tobacco, sells at a premium price at the factory, and due to demand for soybean that is sold to the poultry industry both locally and in neighboring Malawi. As previously stated, the tobacco contribution to farmer livelihoods in Mozambique is unknown. From both a public health and economic perspective, the cash crops outlined in The Ministry of Health, under the mental health department, has outlined tobacco control strategies in both national decrees and strategic documents. Under the decree for Consumption and Commercialization of Tobacco (Decree 11/2007), there are various limitations relating to the commercialization, consumption, as well as demand and supply reduction for tobacco, including the banning of partnerships/cooperation between tobacco companies and public health campaigns of any kind (Article 13). Relevant articles limiting the supply and sales of tobacco under Decree 11/2007 include Article 10, which explicitly prohibits the sale and publicity of tobacco in various establishments, including, but not limited to, health, education and public administration institutions; and Article 12, which prohibits the sale of tobacco products to minors (anyone under the age of 18). Relevant articles to decrease tobacco demand include the following: Article 3 provides for a modest increase in tobacco taxes; Articles 7 and 8, which outlaw general tobacco advertising as well as false marketing that outline false benefits related to tobacco; and lastly, Article 9, which highlights demand reduction measures related to tobacco dependence and cessation as the focus.A common government interest that has been consistent in the decree and later translated in relevant national strategic documents concerning tobacco is the importance of awareness-raising of the negative impacts of tobacco use to the general public. Key policy documents including the Strategic Plan for the Health Sector (2014–2019) , NationaThe concessionaire that dominates the growing and processing of tobacco in Mozambique, MLT, has various social corporate responsibility programs. However, most are related to discouraging child labor practices, enhancing good agricultural labor practices, financial literacy, and increasing access to clean water. The program most related to tobacco control policy in Mozambique is an HIV program , due to According to the government officials responsible for leading the multi-sectoral tobacco control working group under the Ministry of Health, and the mandate of the National Inspection of Economic Activities , INAE ensures that all economic activities are completed in compliance with the law in order to create a good business environment in the country. INAE has been granted authority to work together with the Ministry of Health, through inspections, in order to ensure that the in-country tobacco control regulations are followed. It is also relevant to highlight that there is not much information about economic sectors taking up tobacco control from the health perspective, nor are there regular inspections by the Health Ministry or in collaboration with INAE to ensure consistent implementation of tobacco control regulations in economic sectors. Therefore, further stakeholder consultations with the private sector are advised to gather more data. In-depth interviews with decision-makers are also needed to explore this dynamic.Under the auspices of the Ministry of Health, the aforementioned multi-sectorial working group for tobacco control was created to regulate the consumption and commercialization of tobacco in Mozambique. The working group which was mostly responsible for the creation of Decree 11/2007, which aimed to follow the FCTC framework, consists of focal points from all government ministries, civil society, UN  and customs, was formed, and later became functional in 2005 after Mozambique signed the FCTC in 2003. Although Mozambique was indeed a signatory to the convention, it would be years to come until the government officially ratified the FCTC. Being one of the few tobacco-producing countries that had an existing tobacco control instrument prior to the ratification of the convention, the multi-sectoral working group continued to work with decree 11/2007 as a base for tobacco control advocacy, which led to the eventual accession to the FCTC on 2 November 2017. Granted that the ratification of the FCTC was a success, a high-level government official we spoke with emphasized that although the tobacco leaf MLT purchases are intended for exportation, it still returns Mozambique as manufactured cigarettes making them readily available for consumption . It is aThis paper outlines the tobacco policy landscape across time with an added emphasis on the private enterprise operating to facilitate tobacco production. Not surprisingly, we find two parallel and conflicting approaches to tobacco. On one hand, the government continues to approach tobacco as an important economic commodity. This approach stems in part from a historical legacy of tobacco production that has increased since the 1950s onwards. However, what we find is that tobacco is not a dominant cash crop and is mainly situated in two regions. The findings suggest that shifts are currently taking place to scale-up other cash crops like soybean, which has demonstrated a slow, but consistent increase in production. What we also see in this analysis is a theme that emerges consistently from other tobacco-growing countries that are considering alternatives. The supply chain of tobacco tends to be robust and incentivizes production by establishing contractual relationships for the provision of inputs, transportation to market and a guaranteed market for leaf sales . We findIn the end, the tobacco control community approaches tobacco supply from a unique perspective. This perspective starts from the premise that tobacco should be phased out both as a consumer product and as an agricultural commodity. This perspective is not often one that is taken in the economic and agribusiness sectors ,9,45. Th


Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consider this time frame. This study investigates a broad decision tree multifactorial approach for the prediction of dementia, considering 75 variables regarding demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and health instruments. Previous work on dementia prognoses with machine learning did not consider a broad range of factors in a large time frame. The proposed approach investigated predictive factors for dementia and possible prognostic subgroups. This study used data from the ongoing multipurpose Swedish National Study on Aging and Care, consisting of 726 subjects (91 presented dementia diagnosis in 10 years). The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Most of the variables selected by the tree are related to modifiable risk factors; physical strength was important across all ages. Also, there was a lack of variables related to health instruments routinely used for the dementia diagnosis. Dementia refers to a set of complex neurodegenerative disorders that are characterized by progressive cognitive deterioration and increasing disabilities that affect the individual’s independence, social and professional functioning ,2. It afIt is worth noting that dementia disorder has several subtypes, with the most common being Alzheimer’s disease, Vascular dementia, dementia with Lewy Bodies and Frontotemporal dementia . HoweverPrevention and risk reduction have been identified by the World Health Organization as key elements to focus on to decrease the worldwide impact of the dementia epidemic ,6. In thHowever, any research investigating a disorder as complex as dementia is difficult, especially with regard to traditional trials, as they suffer from major obstacles. For instance, certain health conditions that have high prevalence among older persons  cannot be left untreated in a control group; blinding is a challenge in trials related to lifestyle interventions; and since dementia is a multifactorial disorder, the assumption of one-dimensionality may hinder the results ,9. AnothMachine learning is a field of the artificial intelligence discipline which aims to design algorithms that are able to learn from data. The reasons for employing such algorithms are related to the limited human capacity to deal with large amounts of data, multiple variables and changing environments, i.e., settings which would hinder, if not impede, manual coding or analysis . These iWhen applied to a prognostic setting, machine learning algorithms are able to analyze the health trajectories of a large number of individuals to identify patterns of progression that lead to specific health outcomes of interest . Being aOne of the most significant initiatives in this direction is the Alzheimer’s Disease Neuroimaging Initiative (ADNI), which aims to identify biomarkers to be used in treatment trials and pharmaceutical research . ResearcOnly one study identified in the systematic literature review considered both modifiable and nonmodifiable risk factors. However, the study sample consisted of already cognitive impaired subjects, and hence, individuals who were already at major risk of developing Alzheimer’s Disease, and the prediction was given in a short interval, i.e., 5 years . The machine learning technique that was employed in this study was decision trees. The decision trees technique creates a model for representing knowledge in the form of IF-THEN rules that are intuitive and highly interpretable, which is the reason why it is widely used in medical research for identifying prognostic subgroups . For theIn summary, dementia research faces challenges regarding traditional research and would benefit from data centered machine learning approaches, which are able to provide predictions that consider various factors, in a time frame large enough for the application of interventions that could possibly delay or prevent the onset of the disease. What is evidenced in the literature regarding machine learning for dementia prediction is studies that make their predictions over smaller time frames , and which are based almost exclusively on neuroimaging. In the present study, a multifactorial approach for the 10-year prediction of dementia is proposed. It is important to note that, while a 15-year prediction would be a better time frame for a multifactorial prediction tool, due to limitations in the data, it was not possible to approach the problem in this way. The 10-year time frame was considered in the present study as being a long-term prediction, which could allow interventions to be implemented for the prevention or delay of the onset of dementia. This could be considered a differential to the present study, since the aforementioned studies in the literature which approach the problem over smaller time frames (3 and 5 years) explicitly consider subjects already at the prodromal stage of dementia disorder (MCI), whereas in the approach proposed herein, there is a higher chance of studying the prediction of dementia in its preclinical stages. This is important, since the approach constitutes a prognostic and not a diagnostic model.A longitudinal approach that investigates the prediction of dementia in a cohort of older individuals who did not present a diagnosis of dementia at baseline (2000 to 2003) and their development (or not) of dementia at the 10-year mark of the study (2010 to 2013). This could provide a time frame large enough for the application of interventions for delaying or preventing the onset of dementia.A broad multifactorial approach that considers 75 variables related to modifiable and nonmodifiable risk factors in the following categories: demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and multiple health instruments relevant to the dementia evaluation. This approach considers modifiable and nonmodifiable factors which cover many domains in which interventions could be investigated.An interpretable approach, which employs decision trees, in order to identify possible risk factors and prognostic subgroups of interest. The decision tree approach not only identifies factors which are important for the prediction process, but examines how they interact with each other, which could lead to possible prognostic subgroups.Given the complexities and current status of dementia research, this study proposes a machine learning approach, based on decision trees, aiming at the prediction of dementia in 10 years. The proposed approach addresses research gaps in the following ways:https://www.snac-k.se/for-researchers) with data regarding physical examination, psychological assessment, social factors, lifestyle factors, medical history, etc. The SNAC project started in 2000 and is ongoing. The SNAC cohort contains a subset of the aging population in Sweden that collects data of individuals aged 60 years or more into defined age groups  .,52.51,52For the specific decision tree algorithm implementation in R (version 3.4.1) used in this study, we refer to the book by Kuhn and Johnson . The R pThe main metric that drove the evaluation of the models was the Area Under the Curve (AUC), due to it being undisturbed by skewed class distributions . Other mThe performance metrics obtained in each of the outer cross-validation test sets of the nested stratified cross-validation procedure are shown in General lower values for the Precision metric were a consequence of the class weighting approach employed to deal with the significant class imbalance of the used sample. This makes the misclassification of the positive class costlier than the inverse, minimizing the gravest error. In a diagnostic tool, this would be a poor scenario, but in the present study, the aim is to conduct a prognostic analysis on the factors that could influence the development of dementia 10 years later, so this type of error has a reduced importance.The median model, which presents the median AUC, was model 2 with an AUC of 0.735, Accuracy of 0.745, Recall of 0.722 and Precision of 0.289. The decision tree that visually represents this model is shown in Age was chosen by the algorithm as the decision tree root node see , at a thThe most striking factor of the branch of subjects 75 years and older is the presence of two variables related to smoking, which not only relate to whether an individual is a present smoker at baseline, but also if they smoked in the past. Smoking is a known risk factor for dementia, and literature findings point out that smoking in midlife and late-life increases the risk of developing dementia (compared with nonsmokers) , and mayThe variable associated with the number of medications taken regularly by the subjects is related to that of past heavy smokers, and could be interpreted as an indicator of comorbidities (possibly connected to the heavy smoking itself). The presence of comorbidities may be associated with an accelerated decline in function in demented individuals . HoweverThe inclusion of the hand strength (grip test) and single-leg balancing exams testify to the fact that physical strength is protective against dementia. A poor value on these variables could be related to frailty or sedentary life, which is known to be a risk factor of dementia .The last variable on the branch related to subjects 75 years and older is alcohol consumption frequency. Evidence about the protective benefits of alcohol consumption are not very consolidated in the literature, as no randomized clinical trials have been performed on the subject, but observational studies suggest that moderate consumption seems to be protective against cardiovascular disease (a known risk factor of dementia ), while The variables in the branch related to the subjects younger than 75 years are somewhat similar to those of older subjects in relation to hand strength (grip test), single-leg balancing and alcohol consumption frequency.Another important variable in this branch is the subject’s medical history with regard to diabetes Type 2. The risk of dementia in individuals with this condition is reported to be higher than in individuals without it , and the2 was also selected as a split in the tree, which is commonly referred to as the threshold for being considered overweight. The relationship between BMI and dementia, and it being a risk factor or not, is not consolidated in the literature, and findings thereof are conflicting; trials on the older adult population showed that higher BMI values are both protective and a risk factor [A BMI threshold of 32 kg/mk factor ,62. In tThe only health instrument that was selected as a predictive factor of dementia was the Backwards Digit Span test. This is a neuropsychological instrument that is used to assess the working memory . Since mThis study proposed a decision tree approach for the 10-year prediction of dementia, which achieved an AUC of 0.745 and Recall of 0.722. The proposed approach investigated multiple domains in order to derive prognostic estimates, assessing 75 variables related to demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and diverse health instruments relevant to the dementia disorder. The approach investigated herein not only identified predictive factors (and thresholds for these factors) related to the long-term prediction of dementia, but also possible interactions between these, which is enabled by the structure provided by the decision tree model. These interactions could be further investigated in clinical trials as being potential prognostic subgroups of importance for dementia.The main findings of our assessment are the following: (i) even though both modifiable and nonmodifiable factors were considered for the prediction, the majority of the variables selected by the decision tree were related to modifiable factors; (ii) poor physical strength was an important predictive factor of dementia across all ages of the study sample; and (iii) the decision tree selected almost no variables related to health instruments that are used nowadays in the assessment of dementia  every three months for the subjects in the intervention group. The decision tree model identified the modifiable factors for dementia: a medical history of diabetes Type 2 at least 10 years’ prior the dementia diagnosis; past smoking habit (cigarettes/day) and present smoking frequency, which indicates both the present and past habit of smoking; alcohol consumption, which takes into account alcohol consumption habits and BMI, which could be an indicator of obesity. All of these factors are related to metabolic and vascular risks.Cognitive training: The FINGER RCT proposed a computer-based intervention that addressed episodic memory, executive function, mental speed and working memory. The decision tree model of the present study identified the Backwards Digit Span Test score, which assesses the working memory of individuals.Randomized clinical trials on multidomain interventions related to modifiable risks to investigate the benefits to cognition or dementia incidence in the older population were conducted, the most notable being the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER). The FINGER trial aimed at investigating the effects on cognition of a 2-year lifestyle multidomain intervention that encompassed nutritional guidance, exercise, cognitive training, social activity, and the management of metabolic and vascular risk factors . The popBeing a 2-year intervention, the FINGER trial brought positive results with regard to the cognition of the participants, with many factors comparable to the present study, which proposed a 10-year prediction tool for dementia. This strengthens the evidence of the merits of the results presented herein and suggests that the identified factors could be strong indicators to be studied in longer trials for the prevention or delay of the onset of dementia.Another important aspect to be discussed is that among the sub-branches of the tree that leads to dementia in 10 years from the baseline, in all of them but one, there was the presence of a node indicating poor physical strength. Exercise brings a series of health benefits which might act in favor of dementia prevention, e.g., by helping to maintain a healthy weight, reducing diabetes risk, improving cardiovascular function, decreasing glutamine and enhancing hippocampal neurogenesis . Such beAdditionally, the lack of variables related to health instruments that are routinely used for assessments of dementia indicates that these instruments may not be sensitive enough for long-term predictions, and may also be insensitive to mild cases that are possibly at the beginning of their development. We can argue that such instruments were conceived for diagnosis and not prognosis, i.e., they are sensitive to early signs that indicate cognitive decline, but are not suited to making long-term predictions. The only health instrument identified by the decision tree was the Backwards Digit Span test, which assesses the working memory of an individual and may have potential for use in detecting early memory loss, one of the early symptoms of dementia. This is important, as most cases of dementia are diagnosed when the disorder is at an already advanced stage .Lastly, considering the results, especially in relation to the modifiable factors, they are all already recommended in some form to prevent chronic illnesses and to maintain a healthy lifestyle. This could also refer to theories that state that dementia is not an unavoidable consequence of aging, and measures to delay and prevent its onset should be investigated .The low value for the precision metric, which was a direct consequence of employing the cost-sensitive learning technique, could be seen as a limitation of the proposed method. This feature would be undesirable if our objective were to propose a diagnostic tool; however, the main goal of the proposed approach was to identify factors for the long-term prediction of dementia, minimizing the misclassification of demented cases, which are the most important class to be classified. This was achieved with reasonable success.It is important to note that commonly used dementia research biochemical laboratory tests related to glucose, urinalysis, cerobrospinal fluid, thyroid, amyloid beta-tau and oxidative stress factors were not available in the SNAC Blekinge database; this could be seen as a study limitation. However, the present study employs a broad range of factors and selected variables which are able to relate to these.Internal validity threats related to selection threats were mitigated, as the data from the SNAC study consisted of a randomized sample of the aged population in Sweden. With regard to the external validity, it could be argued that the number of subjects was too low to be generalizable. However, the stratified, nested cross-validation method was employed to avoid the selection of an overfitted or overoptimistic model. Also, it is important to note that the results presented herein relate to a Swedish urban sample, and may not be generalizable to other populations with different overall socioeconomic statuses; therefore, further investigation is needed in order to establish the effect of this factor on the results presented herein. Construct validity threats in the present study relate to the question of whether the considered measures represent what the study intended to investigate. The SNAC data used in this study were collected by trained physicians, nurses and psychologists who followed the Good Clinical Practice standards for clinical studies (GDP). Nonetheless, a possible construct threat could arise from the use of 8 variables which had not previously been validated in studies . Our broad, multifactorial approach investigated social, lifestyle, medical history, blood examination, physical and psychological factors, and diverse health instruments that are currently in use for the assessment of dementia. The model achieved an AUC of 0.745 and Recall of 0.722, and identified diverse modifiable factors that could potentially give rise to interventions attempting a delay or prevent the onset of dementia. Future work efforts should be directed towards the investigation of gender-specific prognoses of dementia, especially with the imbalance shown in the incidence between male and female subjects at the 10-year mark. In addition, as this study is based on a single site of the SNAC study (Blekinge), further studies should be undertaken to validate the findings of this study in the other SNAC sites.