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Background: The towering peaks of the Himalayas lie in troves of captivating hill destinations, especially in India. Each destination aims to provide tourists with unique experiences and breath-taking landscapes. Understanding the tapestry of factors that weave the allure of these destinations and draw visitors from diverse backgrounds remains intriguing. Method: This study delves into the socio-demographic tapestry of Himalayan hill destination selection, unraveling the complex interplay of demographic characteristics, social influences, and individual motivations that shape tourists' choices. Results: This study aims to answer why different tourists have different travel choices and what factors are the drivers behind such choices. The results show that destination selection factors are similar irrespective of respondents' socio-demographic variabilities; however, for a few factors, the results are reversed. Conclusion: The study has implications for policymakers and the limitations of the research discussed at the end.

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BACKGROUND: Despite global efforts to reduce and eventually interrupt malaria transmission, the disease remains a pressing public health problem, especially in sub-Saharan Africa. This study presents a detailed spatio-temporal analysis of malaria transmission in Rwanda from 2012 to 2022. The main objective was to gain insights into the evolving patterns of malaria and to inform and tailor effective public health strategies. METHODS: The study used yearly aggregated data of malaria cases from the Rwanda health management information system. We employed a multifaceted analytical approach, including descriptive statistics and spatio-temporal analysis across three demographic groups: children under the age of 5 years, and males and females above 5 years. Bayesian spatially explicit models and spatio scan statistics were utilised to examine geographic and temporal patterns of relative risks and to identify clusters of malaria transmission. RESULTS: We observed a significant increase in malaria cases from 2014 to 2018, peaking in 2016 for males and females aged above 5 years with counts of 98,645 and 116,627, respectively and in 2018 for under 5-year-old children with 84,440 cases with notable geographic disparities. Districts like Kamonyi (Southern Province), Ngoma, Kayonza and Bugesera (Eastern Province) exhibited high burdens, possibly influenced by factors such as climate, vector control practices, and cross-border dynamics. Bayesian spatially explicit modeling revealed elevated relative risks in numerous districts, underscoring the heterogeneity of malaria transmission in these districts, and thus contributing to an overall rising trend in malaria cases until 2018, followed by a subsequent decline. Our findings emphasize that the heterogeneity of malaria transmission is potentially driven by ecologic, socioeconomic, and behavioural factors. CONCLUSIONS: The study underscores the complexity of malaria transmission in Rwanda and calls for climate adaptive, gender-, age- and district-specific strategies in the national malaria control program. The emergence of both artemisinin and pyrethoids resistance and persistent high transmission in some districts necessitates continuous monitoring and innovative, data-driven approaches for effective and sustainable malaria control.

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OBJECTIVES: To analyze the fertility rate trends in the GCC countries and their association with socioeconomic factors so that policymakers may use the study findings for future healthcare plans. METHODS: Total population, crude death rate, life expectancy, literacy rate, human development index (HDI), female employment, unemployment rate, urbanisation, gross domestic product (GDP) per capita and inflation were chosen as possible predictors of TFR trends. The data were collected for the Global Burden of Disease 2021 study and other official databases such as the World Bank, the United Nations Development Program and Our World in Data for the 6 Gulf Cooperation Council (GCC) countries. Mean with standard deviation and percentage change was calculated to assess trends of TFR and all other variables from 1980-2021. RESULTS: The fertility rate declined in all 6 countries in 2021 compared to 1980. The highest decline was found in the United Arab Emirates (75.5%), while the lowest was in Kuwait (60.9%). From 1980-2021, total population, life expectancy, HDI, literacy rate, GDP, urbanisation, and female labor force increased in all GCC countries. The total population, life expectancy, urbanisation, female labor force, GDP and HDI were negatively and significantly correlated with TFR (p<0.01). The literacy rate showed a negative and significant correlation with TFR in Bahrain, Kuwait, Saudi Arabia, and Qatar. CONCLUSION: The TFR is declining in GCC countries. The plausible causes include the inclination towards postponement of marriages and excessive costs of living. These trends and associations need to be evaluated by policymakers so that they identify priority areas for interventions, allocate resources and formulate developmental plans accordingly to ensure strategic progress of the region.

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BACKGROUND: Dengue outbreaks are common in tropical or temperate countries, and climate change can exacerbate the problem by creating conditions conducive to the spread of mosquitoes and prolonging the transmission season. Warmer temperatures can allow mosquitoes to mature faster and increase their ability to spread disease. Additionally, changes in rainfall patterns can create more standing water, providing a breeding ground for mosquitoes. OBJECTIVE: The objective of this study is to investigate the correlation between environmental and demographic factors and the dissemination of dengue fever. The study will use yearly data from 2000 to 2021 from 11 countries highly affected by dengue, considering multiple factors such as dengue cases, temperatures, precipitation, and population to better understand the impact of these variables on dengue transmission. METHODS: In this research, Poisson regression (PR) and negative binomial regression (NBR) models are used to model count data and estimate the effect of different predictor variables on the outcome. Also, histogram plots and pairwise correlation plots are used to provide an initial overview of the distribution and relationship between the variables. Moreover, Goodness-of-fit tests, t-test analysis, diagnostic plots, influence plots, and residual vs. leverage plots are used to check the assumptions and validity of the models and identify any outliers or influential observations that may be affecting the results. RESULTS: The findings indicate that mean temperature and log(Urban) had a positive impact on dengue infection rates, while maximum temperature, log(Precipitation), and population density had a negative impact. However, minimum temperature, log(Rural), and log(Total population) did not demonstrate any significant effects on the incidence of dengue. CONCLUSION: The impact of demographic-environmental factors on dengue outbreaks in 11 Asian countries is illuminated by this study. The results highlight the significance of mean temperature (Tmean), maximum temperature (Tmax), log(Urban), log(Precipitation), and population density in influencing dengue incidence rates. However, further research is needed to gain a better understanding of the role of additional variables, such as immunity levels, awareness, and vector control measures, in the spread of dengue.

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Health equity is a fast emerging priority for most healthcare systems around the world. Factors impacting health equity include education level, geographical location, age, gender, employment status and income. However, research examining the effect of these demographic variables on health service utilisation among mid-aged and older post-stroke adults is limited. Data was obtained from a sub-study of the Sax Institute's 45 and Up Study, which is conducted in Australia. The sub-study survey collected demographic, health service utilisation and health status information from 576 participants who had a previous stroke diagnosis. Poisson regression was used to examine the association between demographic characteristics and number of consultations with a doctor and/or an allied health practitioner over a 12 month period. All demographic measures were significantly associated with the number of consultations with doctors and/or allied health practitioners. The number of doctor consultations increased for those who struggled to live on their available income (IRR = 1.41), but decreased for females (IRR = 0.81), those who reside in an inner regional area (IRR = 0.83), those who were separated, divorced or widowed (IRR = 0.61), and for those who completed a trade, apprenticeship or diploma (IRR = 0.83). The number of allied health practitioner consultations increased for those who completed a trade, apprenticeship or diploma (IRR = 1.27), and for those who struggled to live on their available income (IRR = 1.38), but decreased for increasing age (IRR = 0.87), females (IRR = 0.78), and for those who reside in an outer regional or remote area (IRR = 0.49). We identified several demographic factors associated with a lower frequency and type of health care services used by post-stroke adults. These possible barriers need to be explored further, as reduced use of healthcare services may lead to poorer stroke outcomes in these demographics. Specifically, researching strategies to best support individuals facing these additional challenges is necessary to ensure equitable healthcare for all Australians.

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This cross-sectional study compares the race and ethnicity and gender of images of physicians generated by artificial intelligence (AI) with US physician demographic characteristics.

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Introduction: The under-representativeness of participants in clinical trials limits the generalisability of results. This review evaluates the representative-ness within pharmaceutical randomised controlled trials (RCTs) in Singapore. Method: Four bibliographic databases were searched for papers on pharmaceutical RCTs which included Singapore adults (≥18 years old), published between 2017 and 2022. The demographic characteristics of study participants were compared against the population in the 2020 Singapore census. Recruitment strategies and authors' comments on the generalisa-bility of their findings were reviewed. Results: Thirty-three publications were included (19 Singapore-only studies and 14 multiregional trials which included Singapore). Where data were available, we found that females and Indians were under-represented compared to the census (41.3% versus [vs] 51.1%, P<0.05; 7.3% vs 9.0%, P<0.05). Ethnic diversity varied between individual studies, and almost half (46.2%) of Singapore-only studies achieved census levels. However, more than one-third of the trials provided no data (31.6%) or partial data (5.3%) on ethnicity. Half of the multiregional publications stated the number of participants recruited from Singapore, but only 1 reported any detail beyond Asian participants. Recruitment strategies were mentioned in fewer than half (42.4%), and less than a quarter (24.2%) commented on sample representative-ness or the external validity of the evidence generated. Conclusion: There is room for improvement regarding the recruitment of RCT participants in Singapore, with particular attention to female gender and Indian ethnicity. Demographic data should also be presented in full. RCTs should be designed and reported such that clinicians can ascertain the generalisability to the Singapore population and the potential benefits from the studied interventions in clinical practice.

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The demographical history of France remains largely understudied despite its central role toward understanding modern population structure across Western Europe. Here, by exploring publicly available Europe-wide genotype datasets together with the genomes of 3234 present-day and six newly sequenced medieval individuals from Northern France, we found extensive fine-scale population structure across Brittany and the downstream Loire basin and increased population differentiation between the northern and southern sides of the river Loire, associated with higher proportions of steppe vs. Neolithic-related ancestry. We also found increased allele sharing between individuals from Western Brittany and those associated with the Bell Beaker complex. Our results emphasise the need for investigating local populations to better understand the distribution of rare (putatively deleterious) variants across space and the importance of common genetic legacy in understanding the sharing of disease-related alleles between Brittany and people from western Britain and Ireland.

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BACKGROUND: Infant survival is an important factor in any community's health. Low birth weight affects babies not only during their infancy but also has long-term consequences for their health as adults. Unfortunately, Sub-Saharan Africa as a region is still dealing with the burden of Low birth weight (LBW), and Tanzania as a part of this region is no exception. So this study aimed to determine the Magnitude of Low Birth Weight and Its Associated Maternal Factors among Women of Reproductive Age who gave birth to live babies. METHODS: The study used analytical cross-sectional study design to analyze secondary data from the Tanzania Demographic and Health Survey and Malaria Indicators Survey 2015-2016. A total of 4,644 women of reproductive age who gave birth to live babies within five years preceding the survey were included in the study. Both bivariate and multivariable logistics regression analyses were used to assess maternal factors associated with low birth weight. RESULTS: The prevalence of LBW was 262(6.2%). After adjusting for confounders, the maternal factors associated with LBW were Age group of a pregnant woman [Less than 20 years (aOR = 1.907 CI = 1.134-3.205) in reference to those aged more than 34years], Number of ANC visits made [Inadequate visits (aOR = 1.612 CI = 1.266-2.05)], parity [para 2-4 (aOR = 0.609 CI = 0.453-0.818), para 5+ (aOR = 0.612 CI = 0.397-0.944)] and area of residence [Unguja (aOR = 1.981 CI = 1.367-2.87). CONCLUSION: The prevalence of low birth weight in Tanzania remains high. Women's age, parity, number of Antenatal care visits (ANC), and area of residence were found to be maternal factors associated with LBW. Thus, early prenatal diagnosis of risk factors for low birth weight in high-risk pregnant women may help to reduce the LBW burden in Tanzania and its detrimental effects.

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Alcohol consumption among college students continues to be a significant public health concern for colleges and universities across the country. However, a preponderance of research primarily included White samples from predominantly white institutions. Unsurprisingly, this practice limits what is known regarding alcohol consumption among African American male college students on historically Black campuses. Notably, as a "rite of passages" from childhood to adulthood, early exposure to alcohol consumption has been viewed as a cultural norm in African American families. The negative consequences associated with alcohol abuse, early exposure to alcohol, and the prevalence of problem drinking among college students in general, mandated further research facilitating a better understanding of this public health concern on historically Black campuses. This study examined alcohol use among African American male college students, investigating relationships between demographics and socio-cultural factors as predictors of alcohol consumption among African American male college students who drink. A convenience sample of 94 students was used. A multiple regression was conducted to test whether demographics and socio-cultural factors were predictors of alcohol consumption. Findings from this study will advance social work research and stimulate discussions about substance abuse disparities among African American male college students who consume alcohol. Furthermore, this research highlights the public health issue, prompting the development of prevention and intervention programs aimed at addressing the social problem of alcohol consumption among African American male college students at historically Black universities.

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The incidence of dengue virus disease has increased globally across the past half-century, with highest number of cases ever reported in 2019 and again in 2023. We analyzed climatological, epidemiological, and phylogenomic data to investigate drivers of two decades of dengue in Cambodia, an understudied endemic setting. Using epidemiological models fit to a 19-y dataset, we first demonstrate that climate-driven transmission alone is insufficient to explain three epidemics across the time series. We then use wavelet decomposition to highlight enhanced annual and multiannual synchronicity in dengue cycles between provinces in epidemic years, suggesting a role for climate in homogenizing dynamics across space and time. Assuming reported cases correspond to symptomatic secondary infections, we next use an age-structured catalytic model to estimate a declining force of infection for dengue through time, which elevates the mean age of reported cases in Cambodia. Reported cases in >70-y-old individuals in the 2019 epidemic are best explained when also allowing for waning multitypic immunity and repeat symptomatic infections in older patients. We support this work with phylogenetic analysis of 192 dengue virus (DENV) genomes that we sequenced between 2019 and 2022, which document emergence of DENV-2 Cosmopolitan Genotype-II into Cambodia. This lineage demonstrates phylogenetic homogeneity across wide geographic areas, consistent with invasion behavior and in contrast to high phylogenetic diversity exhibited by endemic DENV-1. Finally, we simulate an age-structured, mechanistic model of dengue dynamics to demonstrate how expansion of an antigenically distinct lineage that evades preexisting multitypic immunity effectively reproduces the older-age infections witnessed in our data.

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This study examines demographic disparities in COVID-19 exposures across older adults age 60-79 and older adults age 80 and over, and explores the factors driving these dynamics in the United States (U.S.) from January 2020 to July 2022. Spatial clusters were identified, and 14 main health determinants were synthesized from 62 pre-existing county-level variables. The study also assessed the correlation between these health determinants and COVID-19 incidence rates for both age groups during the pandemic years. Further examination of incidence rates in relation to health determinants was carried out through statistical and spatial regression models. Results show that individuals aged 80 and over had much higher hospitalization rates, death rates, and case-fatality rates in 2020-2022. Spatial results indicate that the geographical cluster of high incidence rates for both groups shifted from the Midwest at the beginning of the pandemic to the Southwest in 2022. The study revealed marked spatial, temporal, and demographic nonstationary dynamics in COVID-19 exposures, indicating that the health effects of contextual factors vary across age groups. COVID-19 incidence rates in older adults were strongly influenced by race, healthcare access, social capital, environment, household composition, and mobility. Future public health policies and mitigations should further their efforts by considering temporal and demographic nonstationarity as well as local conditions.

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OBJECTIVES: Medical student-run patient navigation (PN) programs enhance healthcare access in underserved communities. This study examines the relationship between patient demographics and PN outcomes in a student-led PN program. METHODS: Patients with moderate or high-risk health concerns were paired with medical students at health fairs. Statistical analysis evaluates program success and demographic influences. RESULTS: Of 444 patients, 66.4% were female, 47.1% Hispanic White, 49.1% spoke English, and 63.7% earned <300% of the federal poverty level. More than half were uninsured and 52.5% achieved navigation goals. Insurance status and risk level significantly predicted PN outcomes, with "other insurance" and high-risk patients being 1.9 and 1.7 times more likely to complete navigation. CONCLUSIONS: The program achieved high completion rates, emphasizing the need for resources such as translators and financial assistance. Risk stratification successfully linked acute cases to resources. Navigation success was consistent, demonstrating the effectiveness of the program across diverse patient groups.

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A secondary data analysis of the 2022 Philippine National Demographic and Health Survey (PNDHS) was conducted to explore the underlying structure of knowledge regarding communicable and noncommunicable diseases using multilevel confirmatory factor analysis (CFA). The PNDHS data consist of two levels: level-1 represents within-household data (household questionnaire), and level-2 represents between-household data (primary sampling unit (PSU)). Therefore, a two-level CFA and two-level variance CFA were performed. Furthermore, a multigroup analysis assessed the structural differences between males/females and urban/rural groups. In the PNDHS survey, 30,372 household interviews were completed. Knowledge levels for cancer, heart disease, diabetes, dengue fever, TB, and COVID-19 were 96.7%, 94.9%, 97.8%, 98.4%, 96.7%, and 92.8%, respectively. The two-level CFA indicated that the coefficient loadings of each item for both levels were statistically significant (Z-test, P < 0.001). Regarding two-level variance CFA, the variance at level-1 was higher than that at level-2 (13 and 6.7, respectively). The multigroup analysis revealed that the model was non-invariant (not equal) across gender and residence (likelihood ratio test; P < 0.001, P < 0.001, respectively). In conclusion, level-1 has greater effect than does level-2 because the variance in level-1 is greater than that in level-2, the knowledge of COVID-19 has the lowest loading compared to other items, and rural/urban areas and females/males exhibit different levels of health knowledge.

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ABSTRACT: We report 1- and 5-year survival after acute myeloid leukemia (AML) diagnosis and early mortality within 30 days of systemic anticancer therapy (SACT) treatments, using national cancer registry data in England. Patients aged 18 to 99 years diagnosed between 2013 and 2020 were included. Overall survival (OS) was calculated using Kaplan-Meier methodology, and adjusted hazard ratios (aHRs; adjusted for intensity of treatment, age at diagnosis, sex, ethnicity, socioeconomic deprivation, comorbidity, and year of diagnosis) using Cox proportional hazards regression. Odds of 30-day mortality (adjusted odds ratios [aORs], adjusted for aforementioned characteristics), along with performance status and body mass index, were calculated using logistic regression. Among 17 107 patients identified, older age and comorbidity were associated with worse survival. Asian and Black patients had better survival than White patients: 5-year OS of 34.6%, 29.7%, and 17.8%, respectively; aHR of 0.86; (95% confidence interval [CI], 0.77-0.96) Asian vs White, and 0.84 (95% CI, 0.73-0.96) Black vs White. Socioeconomic deprivation was associated with worse survival. Overall, 7906 (46.2%) patients were documented as having received SACT. Thirty-day mortality was lower for patients receiving intensive rather than nonintensive SACT. After adjustment for cofactors, the risk was higher in those treated intensively (aOR, 0.74; 95% CI, 0.60-0.92). We show that ethnicity and socioeconomic status affects outcomes in AML. Further work is needed to understand how these effects may differ in different health care settings, and whether this because of effects on disease biology, responsiveness to treatment, or drug toxicity. Selection of intensive vs nonintensive treatment should be based on individual patient factors, balancing improved long-term survival against higher early mortality.

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PURPOSE: To determine whether the professional behaviors of radiologic technologists differ based on demographic variables. METHODS: An invitation was sent to 10 000 radiologic technologists to participate in the study. Participants completed the Haynes Scale of Professionalism for Radiologic Technology and answered demographic questions. Kruskal-Wallis tests and analyses of variance were conducted to identify the relationship between demographic variables and professional behaviors. Post hoc analyses were performed to identify differences between groups. RESULTS: A significant difference was identified for the demographic variable of age and the professionalism subscale of quality patient care (P < .001). The demographic variable of years as a technologist had significant differences with the subscales of quality patient care (P = .007), ethical performance (P = .008), personal and professional development (P = .02), and the total professionalism score (P = .01). A significant difference was found for the highest degree and the subscale of quality patient care (P = .007). DISCUSSION: The demographic variables of age, years as a technologist, and highest degree affected the technologist's professional behavior scores. Technologists who were older or had more years of experience had higher professional behavior scores. CONCLUSION: Certain demographic variables can affect the professional behavior of technologists. These results help to highlight the factors that influence the development of professional behaviors.

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The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R2 values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.

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