BACKGROUND: In Japan, regulations preventing the prescriptions of various types of psychotropic drugs have become stricter in recent years. However, the areas where multi-psychotropic drug prescriptions are common and the geographic factors that contribute to the regional difference, have not been studied. In this study, we used data from all claims in Japan to examine regional differences in the prescription for multi-psychotropic drugs using an ecological study.
METHODS: The National Database of Health Insurance Claims and Specific Health Checkups of Japan Open data in 2019 were used. The outcome was the number of prescriptions for four or more different types of anxiolytics and hypnotics as well as for three or more of the same kind of psychotropic drugs (any one of anxiolytics, hypnotics, antipsychotics, antidepressants) for outpatients in each area. Among the 335 secondary medical areas in Japan, the data on 331 areas were used in the analysis. The standardized claim ratio (SCR), an indicator of the number of this multi-psychotropic drug prescription, correcting for regional differences in distribution of population by age and sex, was calculated for each of the secondary medical areas. The spatial cluster detection technique was used to locate a cluster of high-SCR areas. Furthermore, factors associated with regional differences in the SCRs were examined by a spatial statistics model.
RESULTS: North Japanese regions tend to have high SCRs, and 13 areas in Hokkaido were identified as the most likely cluster (cluster with the highest likelihood ratio) for multi-psychotropic drug prescription. Furthermore, a spatial regression analysis revealed that the proportion of people with lower educational levels, the total number of prescriptions per capita, and the number of physicians working in psychiatric departments per capita were statistically positively associated with the SCR for the prescription of multiple psychotropic drugs.
CONCLUSIONS: It was suggested that socioeconomic and medical characteristics of areas are related to the regional variation in the multi-psychotropic drug prescriptions, however, further research using individual-level data is required to confirm these results.

UNASSIGNED: Cutaneous melanoma (CM) is a significant contributor to skin cancer-related mortality globally and in Canada. Despite the well-established link between ultraviolet (UV) radiation exposure and skin cancer risk, there remains a gap in population-level interventions and persistent misconceptions about sun exposure and impact of environment on individual behavior.
UNASSIGNED: The current study provides an ecological analysis using latest available data (2011-2017) to define geographic/environmental contributors to the CM landscape in Canada.
UNASSIGNED: Utilizing Canadian Cancer Registry and Canadian Urban Environmental Health Research Consortium data, we analyzed 39,605 CM cases occurring in Canada from 2011 to 2017. Environmental data, including UV radiation, greenspace (normalized difference vegetation index), temperature, heat events, and precipitation was used to evaluate the effect of environment on CM incidence rates across Forward Sortation Area postal codes.
UNASSIGNED: Forward Sortation Areas with increased CM incidence were associated with higher annual average temperature, snowfall, heat events, normalized difference vegetation index, and vitamin D-weighted UV exposure. Conversely, factors associated with decreased incidence included an increased annual highest temperature, rain precipitation, and a longer duration of heat events.
UNASSIGNED: This study is subject to ecological bias and findings should be interpreted with caution.
UNASSIGNED: This study further substantiates associations between specific environmental factors and CM incidence.

BACKGROUND: A coordinated care system helps provide timely access to treatment for suspected acute stroke. In Northwestern Ontario (NWO), Canada, communities are widespread with several hospitals offering various diagnostic equipment and services. Thus, resources are limited, and health care providers must often transfer patients with stroke to different hospital locations to ensure the most appropriate care access within recommended time frames. However, health care providers frequently situated temporarily (locum) in NWO or providing care remotely from other areas of Ontario may lack sufficient information and experience in the region to access care for a patient with a time-sensitive condition. Suboptimal decision-making may lead to multiple transfers before definitive stroke care is obtained, resulting in poor outcomes and additional health care system costs.
OBJECTIVE: We aimed to develop a tool to inform and assist NWO health care providers in determining the best transfer options for patients with stroke to provide the most efficient care access. We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities.
METHODS: Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.
RESULTS: In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. Various learning models were analyzed; all learning models perform better than the simple average of all points in predicting output variables. The decision tree model provided more accurate results than the other models. The decision tree model performed remarkably well, with the values from testing, validation, and the model within a close range. This model was used to develop the \"NWO Navigate Stroke\" system. The system provides accurate results and demonstrates that a mobile app can be a significant tool for health care providers navigating stroke care in NWO, potentially impacting patient care and outcomes.
CONCLUSIONS: The NWO Navigate Stroke system uses a data-driven, reliable, accurate prediction model while considering all variations and is simultaneously linked to all required acute stroke management pathways and tools. It was tested using historical data, and the next step will to involve usability testing with end users.

UNASSIGNED: Behavioral differences exist between countries, regions, and religions. With rapid development in recent decades, an increasing number of international immigrants from different regions with different religions have settled in China. The degrees to which sexual behaviors-particularly risky sexual behaviors-differ by religion and geographical areas are not known.
UNASSIGNED: We aim to estimate the associations of religion and geographical areas with sexual behaviors of international immigrants and provide evidence for promoting the sexual health of international immigrants.
UNASSIGNED: A cross-sectional study was conducted via the internet with a snowball sampling method among international immigrants in China. In our study, risky sexual behaviors included having multiple sexual partners and engaging in unprotected sex. Descriptive analysis was used to analyze the basic characteristics of international immigrants as well as their sexual behaviors, religious affiliations, and geographical regions of origin. Multivariate binary logistic regression analyses with multiplicative and additive interactions were used to identify aspects of religion and geography that were associated with risky sexual behaviors among international immigrants.
UNASSIGNED: A total of 1433 international immigrants were included in the study. South Americans and nonreligious immigrants were more likely to engage in risky sexual behaviors, and Asian and Buddhist immigrants were less likely to engage in risky sexual behaviors. The majority of the Muslims had sexually transmitted infection and HIV testing experiences; however, Muslims had a low willingness to do these tests in the future. The multivariate analysis showed that Muslim (adjusted odds ratio [AOR] 0.453, 95% CI 0.228-0.897), Hindu (AOR 0.280, 95% CI 0.082-0.961), and Buddhist (AOR 0.097, 95% CI 0.012-0.811) immigrants were less likely to report engaging in unprotected sexual behaviors. Buddhist immigrants (AOR 0.292, 95% CI 0.086-0.990) were also less likely to have multiple sexual partners. With regard to geography, compared to Asians, South Americans (AOR 2.642, 95% CI 1.034-6.755), Europeans (AOR 2.310, 95% CI 1.022-5.221), and North Africans (AOR 3.524, 95% CI 1.104-11.248) had a higher probability of having multiple sexual partners.
UNASSIGNED: The rates of risky sexual behaviors among international immigrants living in China differed depending on their religions and geographical areas of origin. South Americans and nonreligious immigrants were more likely to engage in risky sexual behaviors. It is necessary to promote measures, including HIV self-testing, pre-exposure prophylaxis implementation, and targeted sexual health education, among international immigrants in China.

OBJECTIVE: Cervicofacial lymphadenitis caused by non-tubercular mycobacterial (NTM) infections has the highest infection rate in children. Our objective was to assess patient demographics, treatment methods, and the impact of weather and geography on the incidence of disease in patients with NTM cervicofacial lymphadenitis.
METHODS: The Pediatric Health Information System (PHIS) database was queried for data on all patients diagnosed with concurrent cervicofacial lymphadenopathy and NTM infection from 2004 to 2022. We assessed the association between weather patterns and NTM cervicofacial lymphadenitis by collecting monthly weather data from the NOAA National Center for Environmental Information. Incidence rates were calculated by dividing the number of cases by the total hospital discharges during the study period.
RESULTS: Among 47 PHIS hospitals, there were 992 diagnoses of NTM cervicofacial lymphadenitis. The average age at diagnosis was 2 [IQR, 2-4], with 59 % female. Drainage of skin abscesses or lesions was performed for 93 (9.4 %) patients, while 15 (1.5 %) had an excisional procedure of the CPT codes assessed. The most common antibiotics utilized were cephalosporins (28 %), macrolides (27 %), and rifampin (12 %). The most common treatment method was surgery with antibiotics (37 %) followed by no treatment at all (35 %), surgery alone (17 %), and antibiotics alone (10 %). Of the 28 states included in the analysis, Washington (IR: 3.5) and Nebraska (IR: 3.3) had the highest incidence rates (IR) of NTM cervical lymphadenitis. The cases were relatively equally distributed across the different weather seasons within each U.S. geographic region. However, the overall average wind speed was weakly associated with increasing the risk of diagnosis when utilizing a mixed effect zero-inflated negative binomial model (Incidence Ratio: 1.07, 95 % CI: (1.01-1.14), p = 0.035).
CONCLUSIONS: Our results indicate that the most common treatment method utilized in patients within our cohort with NTM cervicofacial lymphadenitis was the concurrent use of surgery and antibiotics. Our results also indicate there may be variation in the incidence rate among different states, but additional studies are needed as our cohort only included approximately 50 % of states within the U.S.

The impact of air pollution is a major public health concern. However, there are few studies on the correlation between PM2.5 and respiratory infections. This study aimed to determine a link between PM2.5 and respiratory diseases among the elderly in Thailand. The data source for this study consisted of 43 electronic files from the Khon Kaen Provincial Health Office covering years 2020 and 2021 and surveyed a total of 43,534 people. The generalized linear mixed model (GLMM) was used to determine the adjusted odds ratio (AOR), and 95 % CI. We found that exposure to PM2.5 concentrations (in 10 μg m-3 increments) was associated with respiratory diseases (AOR: 3.98; 95 % CI [1.53-10.31]). Respondents who are male, aged less than 80 years, single, self-employed, or working as contractors, have a body mass index (BMI) not equal to the standard, have NCDs (hypertension, diabetes mellitus, and cardiovascular disease), are smokers, live in sub-districts where more than 5 % of the land is planted to sugarcane, or live in close proximity to a biomass power plant were at significantly higher risk of developing respiratory diseases (p<0.05). Therefore, environmental factors including ambient PM2.5 concentrations, the proportion of sugarcane plantation areas, and biomass power plants impact the occurrence of respiratory diseases among the elderly. Also, demographic factors and NCDs are serious issues. Systematic approaches to reducing PM2.5 levels in industrial and agricultural sectors are necessary for both the general population and vulnerable groups, including the elderly and NCD patients.

It is significant to systematically quantify the propagation thresholds of meteorological drought to different levels of agricultural drought in karst areas, and revealit\'s the propagation driving mechanisms. This can guide early warning and fine management of agricultural drought. In this study,we selected Guizhou Province as an example. The standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSI) were used to characterize meteorological and agricultural drought. The run theory was used to identify, merge and eliminate drought events. The maximum correlation coefficient was used to capture the propagation time of meteorological-agricultural drought. The regression models were used to quantify the propagation intensity threshold from meteorological drought to different levels of agricultural drought. Finally, the propagation threshold driving mechanism was explored using geographical detectors. The results show that: (1) in terms of temporal variations during the past 21 years, regional meteorological drought had a shorter duration and a higher intensity than agricultural drought, Particularly, 2011 was a year of severe drought, and agricultural drought was significantly alleviated after 2014. (2) In terms of spatial variations, the \"long duration area\" of meteorological drought duration showed an \"S\" shaped distribution in the northeast, and the \"short duration area\" showed a point-like distribution. The overall duration of agricultural drought showed a spatial distribution of northeast to \"medium-high in the northeast and low in the southwest. (3) The drought propagation time showed an alternating distribution of \"valley-peak-valley-peak\" from southeast to northwest. In terms of propagation intensity thresholds, light drought showed an overall spatial distribution of high in the east and low in the west. Moderate, severe, and extreme droughts showed a spatial distribution of low in the center north of southern Guizhou) and high in the borders. (4) There was a strong spatial coupling relationship between karst development intensity, altitude and meteorological-agricultural drought propagation thresholds. The interaction of different factors exhibited a two-factor enhancement and nonlinear enhancement on the propagation threshold. This indicates that synergistic effects of different factors on the propagation threshold were larger than single-factor effects.

An aging population is one of the main features of China\'s current population structure, and it is a key area that needs attention to achieve high-quality population development. Because of its unique geographical environment, economic conditions, and sociocultural background, the study of population aging in the karst region of southwest China is particularly important. However, there is a lack of research exploring the regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we chose Anshun City, located in Guizhou Province\'s southwest area, as the case study area. We used the Lorenz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging and introduced multi-scale geographical weighted regression to explore its influencing factors. The results show that Anshun City\'s older people population proportion (OPP) is generally high with more than 7% of the older people there, making it part of an aging society. The OPP appeared high in the east and low in the west in spatial distribution; the older people population density (OPD) revealed a gradually increasing trend from south to north. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics were obvious. OPD and OPP have a positive spatial correlation at the global level, and townships with similar OPP or OPD were spatially adjacent. The spatial distribution characteristics of population aging are the consequence of complex contributions such as natural, social, economic, and karst factors. Further, the spatial distribution pattern of aging is determined by a variety of influencing factors, which have different directions and intensities. Therefore, it is necessary to formulate and implement corresponding policies and strategies to deal with the aging problem in the future.

BACKGROUND: The decline in global child mortality is an important public health achievement, yet child mortality remains disproportionally high in many low-income countries like Guinea-Bissau. The persisting high mortality rates necessitate targeted research to identify vulnerable subgroups of children and formulate effective interventions.
OBJECTIVE: This study aimed to discover subgroups of children at an elevated risk of mortality in the urban setting of Bissau, Guinea-Bissau, West Africa. By identifying these groups, we intend to provide a foundation for developing targeted health interventions and inform public health policy.
METHODS: We used data from the health and demographic surveillance site, Bandim Health Project, covering 2003 to 2019. We identified baseline variables recorded before children reached the age of 6 weeks. The focus was on determining factors consistently linked with increased mortality up to the age of 3 years. Our multifaceted methodological approach incorporated spatial analysis for visualizing geographical variations in mortality risk, causally adjusted regression analysis to single out specific risk factors, and machine learning techniques for identifying clusters of multifactorial risk factors. To ensure robustness and validity, we divided the data set temporally, assessing the persistence of identified subgroups over different periods. The reassessment of mortality risk used the targeted maximum likelihood estimation (TMLE) method to achieve more robust causal modeling.
RESULTS: We analyzed data from 21,005 children. The mortality risk (6 weeks to 3 years of age) was 5.2% (95% CI 4.8%-5.6%) for children born between 2003 and 2011, and 2.9% (95% CI 2.5%-3.3%) for children born between 2012 and 2016. Our findings revealed 3 distinct high-risk subgroups with notably higher mortality rates, children residing in a specific urban area (adjusted mortality risk difference of 3.4%, 95% CI 0.3%-6.5%), children born to mothers with no prenatal consultations (adjusted mortality risk difference of 5.8%, 95% CI 2.6%-8.9%), and children from polygamous families born during the dry season (adjusted mortality risk difference of 1.7%, 95% CI 0.4%-2.9%). These subgroups, though small, showed a consistent pattern of higher mortality risk over time. Common social and economic factors were linked to a larger share of the total child deaths.
CONCLUSIONS: The study\'s results underscore the need for targeted interventions to address the specific risks faced by these identified high-risk subgroups. These interventions should be designed to work to complement broader public health strategies, creating a comprehensive approach to reducing child mortality. We suggest future research that focuses on developing, testing, and comparing targeted intervention strategies unraveling the proposed hypotheses found in this study. The ultimate aim is to optimize health outcomes for all children in high-mortality settings, leveraging a strategic mix of targeted and general health interventions to address the varied needs of different child subgroups.

OBJECTIVE: The purpose of our study was to assess the multiscalar changes in leprosy burden and its associated risk factors over the last three decades.
METHODS: We conducted an in-depth examination of leprosy\'s spatial-temporal trends at multiple geographical scale (global, regional, and national), utilizing information from Global Burden of Disease, Injuries, and Risk Factors Study (GBD 2019).
METHODS: Incidence and the estimated annual percentage change (EAPC) in age-standardized incidence rate (ASIR) of leprosy were determined, with countries categorized based on leprosy incidence changes. We examined socioeconomic and physical geography influences on leprosy incidence via Spearman correlation analysis, using ternary phase diagrams to reveal the synergetic effects on leprosy occurrence.
RESULTS: Globally, incident cases of leprosy decreased by 27.86% from 1990 to 2019, with a reduction in ASIR (EAPC = -2.53), yet trends were not homogeneous across regions. ASIR and EAPC correlated positively with sociodemographic index (SDI), and an ASIR growth appeared in high SDI region (EAPC = 3.07). Leprosy burden was chiefly distributed in Tropical Latin America, Oceania, Central Sub-Saharan Africa, and South Asia. Negative correlations were detected between the incidence of leprosy and factors of SDI, GDP per capita, urban population to total population, and precipitation, whereas the number of refugee population, temperature, and elevation showed opposite positive results.
CONCLUSIONS: Despite a global decline in leprosy over the past three decades, the disparities of disease occurrence at regional and national scales still persisted. Socioeconomic and physical geographic factors posed an obvious influence on the transmission risk of leprosy. The persistence and regional fluctuations of leprosy incidence necessitate the ongoing dynamic and multilayered control strategies worldwide in combating this ancient disease.