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Mycotoxins, as prevalent contaminants in the food chain, exhibit diverse toxicological effects on both animals and humans. Chronic dietary exposure to mycotoxin-contaminated foods may result in the bioaccumulation of these toxins, posing substantial public health risks. This review systematically examines the contamination patterns of mycotoxins across major food categories, including cereals and related products, animal-derived foods, fruits, and medical food materials. Furthermore, we critically evaluated two methodological frameworks for assessing mycotoxin exposure risks: (1) dietary exposure models integrating contamination levels and consumption data and (2) human biomonitoring approaches quantifying mycotoxin biomarkers in biological samples. A key contribution lies in the stratified analysis of exposure disparities among population subgroups (adults, teenagers, children, and infants). Additionally, we summarize current research on the relationship between human mycotoxin biomonitoring and associated health impacts, with a particular emphasis on vulnerable groups such as pregnant women and infants. By elucidating the challenges inherent in existing studies, this synthesis provides a roadmap for advancing risk characterization and evidence-based food safety interventions.

The paper studies seasonality of conceptions among five distinct population subgroups of mainland Greece for the period 1951-2002. The populations explored include those residing in Metsovo, Dion, Organi, Kehros, as well as a “General” Sample consisting of persons located in various areas of continental Greece. The populations under investigation present diverse characteristics regarding religion, cultural background, socio-economic status etc. Records of births were derived from the Vital Registration System of the respective municipalities and communities of the populations under research were constructed. The date of child conception was estimated as the recorded date of birth minus 260 days. The analysis focuses, among others, on the construction of seasonal indices, applying a variant ratio to moving averages method which reveal, in relative terms, the seasonality of the phenomenon. Subsequently, these ratios are considered as the dependent variable in regression models while months, expressed in terms of dummy variables, are introduced as predictors. Four main sub-periods are considered; 1951-64, 1965-80, 1981-92 and 1992-2002. The findings show that the extent of seasonality differs between periods as well as between the five population subgroups though the phenomenon becomes less prominent over time in all cases. There is a tendency of an increased number of conceptions among mountainous populations during summer, irrespective of religion or socio-economic status, possibly partly due to environmental factors (i.e. seasonal workload, domestic organisation of extended families, etc). Nevertheless, the mountainous populations differ regarding the intensity and duration of this phenomenon. By contrast, in Dion, a lowland Christian Orthodox population, conceptions increase after Easter and remain elevated until June.

CYP2C9 and CYP2C19 are major CYP450 enzymes that heavily influence the hepatic metabolism and bioactivation of many medications, including over-the-counter and narrow therapeutic index drugs. Compared to the wild-type alleles, genetic variants in either gene could potentially alter the pharmacokinetics of widely used medications, affect the desired therapeutic outcomes of a drug therapy, or increase the risk of undesired adverse events. The frequency of genetic polymorphisms associated with CYP450 enzymes can widely differ across and between racial and ethnic groups. This narrative review highlights the differences in CYP2C9 and CYP2C19 allele frequencies among European and Asian population subgroups, using published literature. Identifying the substantial differences across European and Asian populations, as well as within Asian subgroups, indicates the need to further scrutinize general population data. Clinical scientists and healthcare providers should advocate for more inclusive clinical pharmacogenomic data and racially and ethnically diverse pharmacogenomic databases. Clinical trials of limited racial and geographical diversity may not necessarily have strong external generalizability for all populations. Furthermore, clinical trials that designate an all-inclusive Asian population consisting of multiple ethnicities may not be adequate due to the perceived genetic differences among Asian subgroups. Gravitating towards a more comprehensive approach to utilizing pharmacogenomic data necessitates granular population-level genetic information which can be leveraged to improve how drug therapies are prescribed, achieve health equity, and advance the future of precision medicine.

Background: In India, HIV prevalence varies by region and high-risk groups. General population rates have decreased in high prevalence states through HIV Sentinel Surveillance among pregnant women, while low-moderate prevalence states show variable trends. Gujarat, in western India, has mixed HIV prevalence according to 2017 Sentinel Surveillance data. Objectives: To study the level and trend of HIV positivity among pregnant women and high-risk groups (HRGs) across different districts of the state of Gujarat from year 2012-13 to 2016-17. To review the possible determinants of the HIV epidemic across the selected districts in the state of Gujarat. Materials and Methods: Data from the National AIDS Control Organization (NACO) spanning 2012-17 was analyzed for HIV trends in Gujarat. This included combined HIV testing data from pregnant women at Integrated and Counseling Testing Centers, blood unit testing data from selected districts, and HIV testing among high-risk populations through Targeted Intervention sites. Results: HIV cases in Kheda district declined post-2013-14 among pregnant women (0.38% to 0.21% in 2016-17), and in general ICTC clients (5.53% to 0.264% in 2017-18). MSM seropositivity dropped from 1.15% (2014-15) to 0.74% (2016-17), FSWs from 0.7% (2014-15) to 0.29% (2015-16). Contrastingly, blood donors exhibited an increasing trend, rising from 0.15% (2012-13) to 0.24% (2016-17). In Mehsana, ANC mother seropositivity rose to 0.6% (2013-14), fell to 0.32% (2015-16), and rose again to 0.48% (2016-17). General ICTC clients declined from 1.2% (2012-13) to 0.53% (2016-17). FSWs had 0.25% seropositivity (2015-16), while MSM saw a drop from 0.44% (2014-15) to 0.23% (2016-17). Blood donors' trend was inconsistent. Sabarkantha's pregnant women seropositivity dipped from 0.59% (2012-13) to 0.20% (2014-15), rising to 0.25% (2017-18). General ICTC client seropositivity decreased from 5.34% (2012-13) to 1.17% (2017-18). Conclusion: While declines in HIV prevalence are evident among certain groups such as pregnant women and general ICTC clients, there are fluctuations in seropositivity among high-risk populations like MSM, FSWs, and blood donors. These insights emphasize the need for targeted interventions and ongoing monitoring to effectively address the evolving HIV landscape in these districts.

Suburbanization is one of the key phenomena of spatial population change in many countries in transition. Yet we know surprisingly little about the population carrying out the post-socialist suburbanization process. The objective of this article is to improve on this situation by studying the Tallinn metropolis in Estonia. Our analysis, which covers the inter-censal period 1989 to 2000, focuses on the differences between population subgroups with respect to their probabilities to move to the suburbs. As such, it also clarifies choices of destination by dwelling and municipality type. For the analysis, we use individual anonymous 2000 census data and logistic regression. The results indicate that suburbanization was a socially polarizing process during this period. People with low social status had the highest probability to sub-urbanize, and mainly occupied the pre-existing housing stock. Conversely, people with high social status were less likely to move into suburban areas, yet when they did they moved to the most attractive destinations in the suburbs (new single-family houses, coastal municipalities and municipalities closer to the city).

A companion to the bestseller, The Impact of Economic Policies on Poverty and Income Distribution, this title deals with theoretical challenges and cutting-edge macro-micro linkage models. The authors compare the predictive and analytical power of various macro-micro linkage techniques using the traditional RHG approach as a benchmark to evaluate standard policies, such as, a typical stabilization package and a typical structural reform policy.

The objective of this study was to identify factors associated with HIV infection among specific population subgroups and complement the HIV surveillance system in Cameroon. Five subgroups (truck drivers, female-sex-workers, university students, health service providers, and residents along Chad-Cameroon petroleum pipeline) were targeted in 2004. Potential participants were approached at their geographically diverse areas and consented to participate in the study. Anonymous blood samples were collected. 4,011 participants were surveyed (35% students, 25% sex-workers, 20% pipeline residents, 12.5% health service providers, 7.5% truck drivers). HIV prevalence was highest among sex-workers [26.4%, (95% CI, 23.6–29.2)], pipeline residents [19.9% (95% CI, 17.1–22.7)] and truck drivers [16.3% (95% CI, 12.3–20.9))] and lowest among health service providers [5.2% (95% CI, 3.4–7.5)] and university students [3.8% (95% CI, 2.9–5.0)]. Risky sexual behaviours were practiced in all subpopulations. Multivariable analysis shows in female-sex-workers that; older age, residing in the grassland region (Northwest and West Provinces) and inconstant condom use were significantly associated with HIV infection. Despite a moderate HIV prevalence in the general Cameroonian population, some subgroups are at much higher risk for HIV transmission and practicing risky sexual behaviours. There is need for expanded prevention and care programs with emphasis on truck drivers, sex-workers and pipeline residents.

This report tries to put boundaries around the abstraction that is \"social inclusion\". It is intended for policy makers, academics, activists and development partners – indeed anyone who is curious about how to address inclusion in a world that is witness to intense demographic, spatial, economic and technological transitions. Placing the discussion of social inclusion within such global transitions and transformations, it argues that social inclusion is an evolving agenda. While it does not purport to provide definitive answers as to how to achieve social inclusion in any given context, the report offers an easy-to-use definition and a framework to assist practitioners in asking, outlining and developing some of the right questions that can help advance the agenda of inclusion in different contexts. There are seven main messages in this report: 1. Excluded groups exist in all countries. 2. Excluded groups are consistently denied opportunities. 3. Intense global transitions are leading to social transformations that create new opportunities for inclusion as well as exacerbating existing forms of exclusion. 4. People take part in society through markets, services, and spaces. 5. Social and economic transformations affect the attitudes and perceptions of people. As people act on the basis of how they feel, it is important to pay attention to their attitudes and perceptions. 6. Exclusion is not immutable. Abundant evidence demonstrates that social inclusion can be planned and achieved. 7. Moving ahead will require a broader and deeper knowledge of exclusion and its impacts as well as taking concerted action.

In this paper, we present and develop the argument that if the survival functions for two population subgroups converge in later life, a mortality crossover must precede the occurrence of this convergence. Specifically, two survival curves, S₁(x) and S₂ (x), associated with two distinct population subgroups, G₁ and G₂, tend to converge before all members die out, as often observed and anticipated. This convergence leads to an increased mortality acceleration for the \"advantaged\" group, and eventually fosters the occurrence of a mortality crossover. We present a mathematical proof for this relationship and offer several explanations for the mechanisms involved in the process of survival convergence and the preceding mortality crossover. This new presentation demonstrates that mortality crossover is a highly observable demographic event given the trend of survival convergence in later life.

This chapter contains sections titled: Introduction Elements of Survey Design Application to Compositional Data Discussion References