The impact of credit accessibility and information communication technology on the income of small-scale sugarcane farmers in Ndwedwe Local Municipality, KwaZulu-Natal Province, South Africa.

Introduction: Access to credit and information and communication technology (ICT) plays a pivotal role in enhancing the practices of small-scale sugarcane farmers, impacting their financial, social, and economic wellbeing. However, many small-scale farmers need help accessing these resources, thereby affecting their ability to generate sustainable income. This study aimed to assess the factors influencing the adoption of ICT and access to credit and their subsequent impact on small-scale farmers' income. Methods: Employing a multistage sampling technique, 300 small-scale farmers were selected as participants in the study. The recursive bivariate probit regression model was used to assess the factors affecting adoption ICT and a selectivity-corrected ordinary least square regression model was utilized to estimate the synergistic effect of ICT adoption and access to credit on the income of small-scale sugarcane farmers. Results and discussion: The findings revealed that approximately 77% of small-scale farmers had access to credit, while more than 80% had adopted ICT. The results derived from the recursive bivariate probit (RBP) regression model indicated that access to credit, education, and extension support positively and significantly influenced the adoption of ICT. Conversely, marital status and non-farm income exhibited a negative and significant influence on the adoption of ICT. Gender and marital status were positively and significantly associated with access to credit, whereas age, education, and non-farm income showed a negative and significant relationship on access to credit. Subsequently, a selectivity-corrected ordinary least square regression model analysis revealed that factors such as gender, marital status, extension, government support, and transportation costs positively and significantly influenced farmer's income. In contrast, education, employment status, and non-farm income exhibited a negative and significant influence on income. Conclusion and recommendations: The study concludes that socio-demographic factors, such as gender, marital status, extension support, government support, and transportation costs, positively contribute to farmers' income. Small-scale sugarcane farmer involvement in other non-farm activities is associated with reduced farm income. This implies that farmers' livelihoods options are reduced as they can only focus on sugarcane development as a source of income. There is a pressing need to educate small-scale farmers on ICT and provide them with access to agricultural credit. Additionally, extension workers should offer advisory support to small-scale farmers requiring assistance in accessing agricultural credit. There is a need to train sugarcane farmers on different agricultural income generating activities to reduce their over-reliance on sugarcane development. By addressing the identified socio-demographic factors and implementing targeted policy interventions, stakeholders can foster an enabling environment for small-scale farmers to thrive, ultimately contributing to the sustainable development of the sugarcane sector and the broader agricultural landscape in South Africa.

Bayesian inference for multivariate probit model with latent envelope.

The response envelope model proposed by Cook et al. (2010) is an efficient method to estimate the regression coefficient under the context of the multivariate linear regression model. It improves estimation efficiency by identifying material and immaterial parts of responses and removing the immaterial variation. The response envelope model has been investigated only for continuous response variables. In this paper, we propose the multivariate probit model with latent envelope, in short, the probit envelope model, as a response envelope model for multivariate binary response variables. The probit envelope model takes into account relations between Gaussian latent variables of the multivariate probit model by using the idea of the response envelope model. We address the identifiability of the probit envelope model by employing the essential identifiability concept and suggest a Bayesian method for the parameter estimation. We illustrate the probit envelope model via simulation studies and real-data analysis. The simulation studies show that the probit envelope model has the potential to gain efficiency in estimation compared to the multivariate probit model. The real data analysis shows that the probit envelope model is useful for multi-label classification.

Gen Z's Willingness to Adopt Plant-Based Diets: Empirical Evidence from Greece, India, and the UK.

Comprising the largest population cohort on this planet, Gen Z presents a future-oriented consumer segment driven by climate change and food. This study sought to investigate Gen Z's perceptions toward plant-based foods and diets and explore the relationship that attitude components, meal preparation involvement, personal and lifestyle factors, and perceived barriers in adopting a plant-based diet have with willingness to adopt green-eating practices. Using cross-sectional data from university students in Greece, India, and the UK, various tools were employed to determine the factors influencing youths' consumer behavior toward animal-protein substitutes. PCA indicated the underlying dimensions of students' viewpoints on plant-based foods, whereas hierarchical and k-means clustering provided the cluster structure. An ordered probit model was estimated to delineate Gen Z's willingness to adopt plant-based diets and distinguish among mostly unwilling, somewhat willing, and mostly willing youths. Our findings identified two consumer segments, namely proponents and opponents of plant-based foods and diets, with statistically significant differences in the perceived health benefits of plant-based diets, attachment to animal-based proteins, perceived exclusion of animal-based foods, dissatisfaction with plant-based foods' attributes, and demand for ensuring adequate protein intake. The ordered probit model estimates showed that there is a "homogeneity" in the factors influencing youths' intention to adopt plant-based diets, with attitude components, meal preparation indicators, perceived barriers to eating "green", and personal factors, such as self-assessed knowledge of healthy eating and physical activity, being strongly associated with students' willingness to switch to plant-based diets in all three countries. Mapping potential obstacles and enablers in terms of shifting to more green-eating behaviors, our findings could add information to better understand the factors affecting food choice and youths' transition to a more sustainable lifestyle.

Assessing the impact of three biosphere reserves on the conservation of coastal ecosystems.

Biosphere Reserves (BR) manage large territories with diverse natural covers and land uses to preserve biodiversity, promote local development and preserve ecosystems. This study evaluated how their zoning (buffer and core) and policy timeframes (decree period, management plan period, and land planning period) influence four landscape management outcomes: deforestation, natural cover recovery, and anthropic and natural permanence. For three Mexican BR case studies, land use and cover transitions were calculated and compared to contrafactual sites. Observed rates of land cover change were marginal within all three BR zoning and across their policy timeframe (<0.02 % change rate), suggesting that BR effectively promote the permanence of both natural and anthropic covers. Nevertheless, the predicted probability of uncommon deforestation and recovery outcomes at local levels showed that the effect of a BR over its regulated landscape is not spatiotemporally static, contrasting the effect of individual allocation vs a group or network. Poverty, land tenure, agriculture aptitude and distance to markets adds to this dynamic and is modelled and discussed. This study shows that BR zoning schemes and its regulatory sequence influence the rates of land cover change and the predicted probability of landscape management outcomes across space and time.

Preferences for index-based crop insurance in South Africa.

The main reason cited for the low participation rate in indexed insurance in Africa is the lack of farmers' involvement in the initial conception. The main aim of this article was, therefore, to design an improved participatory methodology that would help farmers in South Africa gather information on the value they place in new crop insurance initiatives based on weather indices. The main objective of this study was to determine their willingness to pay (WTP) crop insurance in the Eastern Cape. The study adopted a cross-sectional design, and the respondents were selected by using a probability sampling procedure. A sample of 150 respondents was selected. The results from descriptive statistics showed that 62% of the smallholder irrigation scheme farmers were between 52 and above years of age, male and female: 87% and 13%, respectively. The results from the probit model revealed that out of nine variables included in the model, only four namely, logAge square, gender, marital status and age were significantly influencing the WTP index-based crop insurance at 1%, 5% and 10%, respectively. However, age was found to reduce the chances of participating in crop-based insurance. A large proportion of those who were willing to pay insurance had not previously experienced losses because of natural hazards. Therefore, it recommended that the government should use existing extension officers to educate the farmers and promote the importance and benefits of insurance products. Contribution: The results are expected to contribute to the local government to improve disaster resilience through strengthening regional financial funding.

Assessment of radiosensitivity and enhancing key steviol glycosides in Stevia rebaudiana Bertoni through gamma radiation.

PURPOSE: Stevia rebaudiana Bertoni is a perennial herb, widely used as a natural sweetener around the globe. The key compounds responsible for its sweetness includes stevioside and rebaudioside-A. In order to improve these steviol glycosides, the present study was initiated to study the effect of induced mutagenesis on growth parameters, steviol glycosides and nuclear DNA content in Stevia rebaudiana Bertoni using ten doses of gamma-rays (5-100 kR). MATERIALS AND METHODS: Healthy seeds of 'Madhuguna' variety of Stevia rebaudiana Bertoni developed and maintained at stevia breeding farm, Agrotechnology division, CSIR-Institute of Himalayan Bioresource Technology, Palampur (HP), India were irradiated with ten doses of gamma rays (600 seeds each/dose) ranging from 5 kR to 100 kR (i.e., 5, 10, 15, 20, 30, 40, 50, 60, 80 and 100 kR) using Co60 gamma irradiation chamber at CCS Haryana Agricultural University, Hisar, (Haryana), India. RESULTS: Significant variations were recorded for all the seedling traits studied while major impact was noticed on the seedling after reaching the cotyledonary stage and doses above 40 kR showed absolute mortality of the seedlings. Based on probit analysis, the optimum LD50 dose lies in the range of 20-23 kR. Glycosidic profiling of 296 mutants using high-performance liquid chromatography showed decreased total steviol glycoside content with increased radiation dose. Doses 5 kR and 10 kR, were found to be effective in increasing the overall glycosidic content. A total of 72 promising mutants were also screened for increased rebaudioside-A stevioside ratio. Comparison of nuclear DNA content using flow cytometry revealed a similar decrease in the total nuclear DNA content with increase in dosage of gamma rays. The average genome size at 5, 10, 15, 20 and 30 kR treatments were 2.72, 2.69, 2.68, 2.70 and 2.66 pg as compared to 2.72 pg in control. CONCLUSIONS: Mild dose of gamma rays (5 and 10 kR) in stevia were found to be effective in improving the mean steviol glycoside content and may be used in future stevia mutation programmes.

A joint normal-ordinal (probit) model for ordinal and continuous longitudinal data.

In biomedical studies, continuous and ordinal longitudinal variables are frequently encountered. In many of these studies it is of interest to estimate the effect of one of these longitudinal variables on the other. Time-dependent covariates have, however, several limitations; they can, for example, not be included when the data is not collected at fixed intervals. The issues can be circumvented by implementing joint models, where two or more longitudinal variables are treated as a response and modeled with a correlated random effect. Next, by conditioning on these response(s), we can study the effect of one or more longitudinal variables on another. We propose a normal-ordinal(probit) joint model. First, we derive closed-form formulas to estimate the model-based correlations between the responses on their original scale. In addition, we derive the marginal model, where the interpretation is no longer conditional on the random effects. As a consequence, we can make predictions for a subvector of one response conditional on the other response and potentially a subvector of the history of the response. Next, we extend the approach to a high-dimensional case with more than two ordinal and/or continuous longitudinal variables. The methodology is applied to a case study where, among others, a longitudinal ordinal response is predicted with a longitudinal continuous variable.

Probability and severity of climate change threats to natural world heritage sites vary across site specifics and over time.

This study contributes a first comparison of current and potential threats to Natural World Heritage Sites from climate change, as assessed by experts, when site and location characteristics (size, year of inscription to the World Heritage list, continent, climate zone and kind of site) are controlled for. The probability of a threat as well as its intensity is analysed. Another novelty lies in the use of data from the IUCN Conservation Outlook Assessment, covering all 245 Natural and Mixed World Heritage Sites across the world for three points in time: 2014, 2017 and 2020. The threat of climate change is broadly defined and includes temperature extremes, rising temperatures, disappearing glaciers, coral bleaching, droughts, desertification, and rising sea levels. Results based on a simultaneous Probit model with random effects show that the probability of actual and potential climate change threats increases over time, but with differences for size, kind of site and location. The probability that a threat is identified is highest for marine and coastal sites, and for those in Latin America, while it is significantly lower for sites on the African continent. Larger sites have a higher probability of being assessed as at risk and the severity of threats is found to be lower for recently inscribed sites. The rate at which the likelihood of a threat assessment increases is consistent for both current and future situations, while the probability of the most severe threat is larger for the current than the future period. A serious threat from climate change is assessed as highest for locations in the tropical monsoon (current period) or the tropical savannah climate (future period). Estimations also show that pure descriptive statistics or bivariate correlations may not correctly identify the risk or the dignity of a threat.

Characterization of workers or population percentage affected by low-back pain (LPB), sciatica and herniated disc due to whole-body vibrations (WBV).

Whole-body vibrations have several harmful effects on the population's health. The most suitable way to characterize the vibrations is to use the daily vibration exposure A (8) and Vibration Dose Value as specified in Directive 2002/44/EC. Therefore, based on the existing literature, we propose Probit equations that allow us to relate the population percentage affected by the vibration effects (low-back pain, sciatica, and herniated disc) with the A (8) and the Vibration Dose Value. It is worth noting that there is a good correlation between the experimental data and the expressions obtained, especially for low-back pain and herniated discs. Once the expressions have been validated, we analyze the limit values given in the aforementioned legislation, showing that the percentage of the affected population is significant for them. Therefore, this study also proposes new limits based on their own definitions, which are more in line with the results shown in the bibliography.

Adoption of digital payment platforms and trade credit activities among informal firms in Ghana.

This study investigates the relationship between the utilisation of digital payment platforms and the decision of informal firms to engage in the demand for or supply of trade credit. Recognizing the pivotal role of trade credit in alleviating financial constraints for informal enterprises, our research employs a recursive bivariate probit model to assess the impact of digital payment platform usage on both the demand for and supply of trade credit among informal firms in Ghana. Leveraging data from the World Bank Enterprise Survey, we find that 13.83 % of informal firms receive trade credit from suppliers, while 26.89 % extend trade credit to customers. Additionally, 49.6 % of firms use digital payment platforms for their business transactions. The study finds that digital payment platforms increase the probability of firms engaging in the demand and supply of trade credit. It argues that digital payments enhance transaction efficiency, convenience, and security, potentially reducing associated transaction costs and facilitating business interactions across distant locations. Various factors, including firm age, maintenance of accounting records, sales volume, owner experience, credit facilities, internet use for social media marketing, and operating hours, significantly influence the decision to engage in trade credit activities. The robustness of our results is confirmed through alternative estimation techniques. Recommendations include policy interventions aimed at promoting the digitalization of informal firms, supported by government investments in digital infrastructure. It is recommended that firms and their suppliers and customers should adopt these digital payment platforms in order to facilitate their use of trade credit in business transactions. A regulatory environment fostering business trust and responsible use of digital payment platforms is crucial, necessitating measures to ensure data protection, security, and ethical conduct within the digital payments' ecosystem.

Factors Shaping Public Support for More Carbon Capture and Storage Projects in the United States.

This study contributes to the literature examining public acceptance of carbon capture and storage (CCS) projects in the US. The examination of factors that shape public support for CCS projects provides policymakers with insights to address public concerns, balance CCS development with public sentiments, and make informed decisions about optimal locations and timing. Based on a nationally representative survey on 1850 respondents, the study finds that in the US, there is very low familiarity (6.4%) regarding CCS technology and some limited opposition (11.5%) to increased CCS development. Regression results suggest that support for increased CCS projects in the US is influenced by perceptions of technical and social risks (leakage and community danger, respectively) but not cost of living risks, perceptions of environmental and economic benefits, familiarity with the technology, confidence in government regulations, and a desire for the US to lead in CCS. We fail to find the 'Not-in-My-Backyard' effect, and individuals supporting the development of more CCS in their states also support it at a national level. Understanding these factors helps policymakers anticipate challenges in implementing CCS initiatives and allows for the development of strategies to address concerns.

Innovation and entrepreneurship of Chinese returning migrant workers in their home region.

This study aims to investigate the influence of pre-entrepreneurial career mobility frequency and job changes among returning migrant workers (RMWs) on the innovation level of enterprises, with a particular focus on the mediating role of urban social capital accumulated by RMWs. Using data from the "current entrepreneurial status of RMWs", we applied an ordered probit model to validate our hypotheses. To address endogeneity, a recursive bivariate probit model was used, and stepwise regression combined with bootstrap methods was employed to ascertain the mediating influence of urban social capital. Our results demonstrate a significant positive correlation (P < 0.01) between pre-entrepreneurial career mobility frequency and the innovation level of enterprises among RMWs. However, there's a notable negative correlation (P < 0.01) between experiences as elementary workers and enterprise innovation level, while technical and marketing roles correlate positively (P < 0.01) with enterprise innovation level. Urban social capital mediates the relationship between career mobility and enterprise innovation level, suggesting that career mobility enhance urban social capital accumulation, influencing RMWs' enterprise innovation levels. This empirical evidence holds even after robustness tests. We further observed that RMWs with fewer than three career moves lean towards low level of enterprise innovation, while those with three or more gravitate towards high level of enterprise innovation. This study advances the theory of career mobility and enriches the understanding of enterprise innovation levels. Additionally, it provides critical theoretical insights for prospective RMWs entrepreneurs in strategizing their career mobility and job changes. Policy implications suggest that, in addition to providing entrepreneurial support, the government should facilitate pre-entrepreneurial career mobility channels for migrant workers and consider the transition from rural to urban employment as a socialized ritual for RMWs engaging in entrepreneurship.

Supervised and unsupervised techniques to analyze risk factors associated with motorcycle crash.

PURPOSE: Motorcycles are one of the highly used modes of transport in Barcelona, Spain, in particular, and in many different regions, in general. This situation is compromising safety on the road and may be attributed to a potential increase in traffic crashes. Therefore, this study examines several risk factors and their consequential impacts on the level of injury that is resulted in case of a traffic crash. METHODS: Two approaches are employed to analyze the risk factors, including a supervised learning technique which is a binary probit model, and an unsupervised technique which is the Kohonen clustering. RESULTS: The results for both models show that alcoholism and road in poor condition can indeed increase the probability of having different levels of injuries as reasons for the crash. Elderly users are less likely to be involved in motorcycle crash injuries compared to other age categories, especially the age group that ranges from 25 to 40 years old which has the highest odds. For both techniques, the performance in analyzing the utilized data shows that both approaches can be successfully utilized for this type of dataset. CONCLUSION: This study highlights the considerable danger faced by motorcyclists due to various risk factors. It stresses the critical importance of maintaining roads in optimal condition not just for efficient travel but also to enhance motorcyclists' safety. Additionally, the research underscores the significant threat posed by speeding, particularly exceeding speed limits, to motorcyclists' safety, emphasizing the urgent need for more 30 km/h speed limit zones and stricter enforcement of speed regulations. As a result, the research has identified several risk factors that increase the likelihood of severe or fatal injuries among motorcyclists in Barcelona and has suggested certain recommendations to mitigate their impact.

Analysis of incidence, intensity, and gender perspective of multidimensional urban poverty in Kenya.

Poverty continues to be one of the biggest challenges facing many economies worldwide, and its incidences and intensities are very high in developing economies. This paper utilized the Alkire-Foster (AF) method to compute the multidimensional poverty index (MPI) and analyze the incidence and intensity of multidimensional poverty among urban households in Kenya. The findings indicated that 8.7 % of urban households are multidimensionally deprived in 33.3 % of the selected dimensional indicators. Also, the results showed that over 50 % of urban households are deprived of drinking water and sanitation services. In addition, the findings revealed that higher poverty incidence, intensity, and urban multidimensional poverty exist among female-headed households, old household headships, and households residing in peri-urban regions. The Probit regression analysis indicated that large household size, number of children under five years, household head age, gender, marital status, urban food insecurity, health status, and residing in Malaria endemic zone are significant positive predictors of urban multidimensional poverty. On the other hand, an increase in the number of educated women, owners of insurance coverage, agricultural land, and wealthy and home-owning households is linked to a decline in urban multidimensional poverty. The paper professes that policymakers should cautiously consider household socioeconomic differences while designing poverty alleviation policies.

Comparative Responses of Two Major Cucurbit Pests, Zeugodacus cucurbitae and Zeugodacus tau to Phenylbutanoid Male Lures.

Zeugodacus cucurbitae and Z. tau are two major fruit fly pests of cucurbitaceous plants in the tropical and subtropical regions. The former species has a broader host range and wider world distribution than the latter. With global climate change, Z. tau shows great potential for geographical expansion with several invasion records in recent years. Males of both species are attracted to cue lure (CL) (and raspberry ketone (RK), a deacetyl derivative of CL), a common male lure used in fruit fly population detection, monitoring and control programs. Males of both species are also known to respond to zingerone (ZN), which are produced by some rainforest orchids. Previous studies have shown that fruit fly-male lure interactions are unique to species and lure types, and significantly impact the success of a lure-based fruit fly control program. We seek to compare the attraction of Z. cucurbitae and Z. tau males to CL, RK and ZN via Probit behavioral assays. Our results showed that CL is more attractive to Z. cucurbitae and Z. tau males than RK, while ZN is a poor lure for both species. Attraction Z. tau to CL is slightly lower than Z. cucurbitae, but the former is at least 1.71 times less attractive to RK than the latter. Together with published information on species' sexual development, our current study indicates a lure-based control program via male annihilation technique for Z. tau will be more challenging than Z. cucurbitae and should incorporate other integrated pest management strategies for a desirable outcome.

Bivariate ordered probit modelling of motorcycle riders and pillion passengers' injury severities relationship and associated risk factors.

This study simultaneously modelled the injury severity of motorcycle riders and their pillion passengers and determine the associated risk factors. The analysis is based on motorcycle crashes data in Ashanti region of Ghana spanning from 2017 to 2019. The study implemented bivariate ordered probit model to identify the possible risk factors under the premise that the injury severity of pillion passenger is endogenously related to that of the rider in the event of crash. The model provides more efficient estimates by considered the common unobserved factors shared between rider and pillion passenger. The result shows a significant positive relationship between the two injury severities with a correlation coefficient of 0.63. Thus, the unobservable factors that increase the probability of the rider to sustain more severe injury in the event of crash also increase that of their corresponding pillion passenger. The rider and their pillion passenger injury severities have different propensity to some of the risk factors including passengers' gender, day of week, road width and light condition. In addition, the study found that time of day, weather condition, collision type, and number of vehicles involved in the crash jointly influence the injury severity of both rider and pillion passenger significantly.

A threat to the natural World Heritage site rarely happens alone.

This study contributes an empirical investigation of the likelihood that different external threats to a UNESCO Natural World Heritage Site occur in combination with each other when site characteristics and location are controlled for. For the purpose of the analysis, the World Heritage database and the UNESCO State of Conservation Reports are used and the nine most frequently appearing external threats are identified. These databases include 6852 site-year observations and 3316 threats over the period 1979-2023. The most commonly identified external threats are illegal activities, with eleven percent of all observations and mining with six percent. Transport infrastructure, tourism and visitor pressure are also common threats. Estimation results based on the multivariate Probit (equation system) model demonstrate that there are strong positive correlations between many pairs of the nine external threats. Most apparent are the links between illegal activities and loss of identity, social cohesion, changes in local population and community, water infrastructure (dams) and farming, as well as illegal activities and land conversion. There are also clear links between tourism and infrastructure. This emphasises that the various threats seldom appear in isolation from each other. Results also highlight that the threats have different drivers. Among the determinants, site characteristics and location are the most important ones. The likelihood of threats is highest for Natural Heritage Sites covered by forests or those in marine and coastal areas, Africa as well as the Arab region. It is also possible to identify a general increase in threats over time, although with a diminishing rate of growth towards the period 2015-2019. Contrary to this development and the general downturn in threats during the Covid-19 pandemic period of 2020-2023, pressure from tourism continues to grow. Methodologically, the results emphasize the need for multivariate Probit models when research goes beyond analyses of descriptive statistics and single equation approaches.

Interdependence of rural household welfare measurement in the context of climate variability in Ethiopia.

The Ethiopian government and various stakeholders have made significant efforts to improve household consumption, poverty, and food security. However, the results have not met expectations. To ensure that programs are effective, it is critical to have a robust measure of well-being that considers social, economic, institutional and environmental challenges. Previous studies on welfare have focused on a single measurement, but it is important to recognize the interdependence between various well-being indicators to formulate comprehensive interventions and initiatives for rural households in the context of climate change and variability. This paper examines the dynamic link between unidimensional poverty, multidimensional poverty, and food security using panel data from Ethiopia. The interdependency of welfare measurements was estimated using a seemingly unrelated multivariate probit model with a conditional mixed process estimator with full information, a simulated maximum likelihood approach, and the presumption that different metrics can have various policy implications. The chances of interdependence wellbeing status were low for households that were simultaneously food insecure and poor or nonpoor. Multidimensional poverty has a higher success rate than food insecurity or consumption poverty. Unlike unidimensional poverty and food insecurity, multidimensional poverty has a higher chance of to be deprived. Policymakers must consider the synergies and trade-offs of different types of welfare and the dynamic linkage between climate-induced shocks and other covariates with household welfare to minimize households' vulnerability to climate-induced shocks for effective intervention for rural households to obtain a whole picture of wellbeing.

Too Young to Gamble: Long-term Risks from Underage Gambling.

The increasing availability of gambling opportunities worldwide has the potential to impact youth gambling behavior and the prevalence of gambling-related harm. This paper studies whether starting gambling at an early age (i.e., below the minimum legal gambling age) increases an individual's likelihood of suffering some kind of gambling-related harm in the future. Data taken from the Study on the Prevalence, Behavior and Characteristics of Gamblers in Spain provide information on respondents' gambling starting age and assess gambling risk based on criteria established by the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates from an ordered probit model suggest that starting to gamble while under the minimum legal age is associated with a higher likelihood of problem gambling.

Characterization of the effects of vitamin D synthesis and sunburn in the population due to solar radiation exposure using PROBIT methodology.

The main objective of this work is to present a set of equations that relates exposure time to solar radiation, the ultraviolet index (UVI), and its effects, both positive (vitamin D synthesis) and negative (sunburns), including the influence of repeated doses and the incorporation of protective factors. To do so, expressions are proposed for both effects and a time range is specified where repeated doses can be applied. Moreover, we propose expressions (PROBIT equations) that relate the percentage of a population that would reach the recommended daily amount of vitamin D and the repeated dosage to which the population is exposed for skin types I to IV. For all the cases studied, protective factors, such as the use of clothes or sunscreens, were taken into account. Additionally, comparisons were made based on skin types between the generation of daily vitamin D and the onset of sunburn, being able to establish a percentage of those who would suffer from first-degree sunburns when this population reached the recommended daily amount of vitamin D. Thus, it can be noted that when a large percentage of a population wants to obtain the recommended daily allowance of vitamin D of 2000 IU or more, and by exposing a small portion of skin to solar radiation, a considerable percentage of that population would suffer from first-degree sunburn as vitamin D generation is related to the area of exposed skin. Therefore, by increasing the area of skin that is exposed to solar radiation, vitamin D needs can be safely met even with higher daily amounts.