Profile of Caregiving Activities and Association With Physical Health Among Dementia Spousal Caregivers.

Background and Objectives: This study aims to identify patterns of caregiving intensity and assess associations between caregiving intensity and multidimensional physical health indicators and health behaviors among spousal caregivers of persons with Alzheimer's disease and related dementia. Research Design and Methods: Using data from 152 spousal caregivers aged 65 and older, the intensity of their caregiving experience was measured as the number and frequency of health- and medical-related helping activities for their care recipient. Multidimensional health indicators included self-reported fatigue, sleep disturbance, physical functioning, pain interference, general health, and the number of chronic conditions from the electronic health records. Self-reported health promotion behaviors were assessed as health responsibility, physical activity, nutrition, interpersonal relations, and stress management. Results: Two distinct caregiving intensity patterns, high-intensity (37.5%) and low-intensity (62.5%) caregiving, were identified with cluster analysis. Caregivers in the high-intensity caregiving cluster reported feeling more tired (t = 2.25, p < .05), experiencing more sleep disturbance (t = 3.06, p < .01), and performing less physical activity (t = 2.05, p < .05) compared with caregivers in the low-intensity group. Discussion and Implications: Future studies are needed to develop effective interventions to address caregiving intensity and its consequences on the health of spousal caregivers of persons with dementia.

Pap Smear Cancer Coverage in Brazilian Capitals including the Pandemic Period Caused by the SARS-CoV-2 Virus: Ecological Study.

INTRODUCTION: Cervical cancer develops slowly and may not manifest signs and symptoms at an early stage. It is worth mentioning the factors that can influence the onset of cervical cancer: smoking, early sexual life, multiple sexual partners, use of oral contraceptives, multiparity, low socioeconomic status, among others. An important risk factor for the onset of this disease is HPV infection, a virus associated with most cases of precursor lesions of this type of cancer. It is essential to understand the comprehensiveness of the scope and adherence to the recommended guidelines throughout the national territory. Therefore, health indicators are important management tools that make it possible to evaluate the services offered, measuring the reach of the target population, the supply and access to preventive exams. OBJECTIVE: To analyze the trend of progress in cervical cancer coverage actions in Brazilian capitals from 2016 to 2021. METHOD: This is an ecological study with temporal analysis that used secondary data referring to process indicators for cervical cancer control actions in women aged between 25 and 64 years living in Brazilian capitals between 2016 and 2021. Aspects related to the quality of care in the cervical cancer prevention program were evaluated using databases of the Cancer Information System (SISCAN), available in DATASUS. The indicators used to monitor and evaluate cervical cancer control actions were (i) cervical coverage, (ii) reason for cervical surgery, and (iii) proportion of cervical cancer every 3 years. RESULTS: In 2016, 410,000 tests were performed and notified in the SISCAN system in all Brazilian capitals, with emphasis on Curitiba, with 65,715 tests performed, and Porto Velho, with 174. In 2020, there was a reduction in exams compared to the previous year in all capitals, with the exception of Palmas, which went from 7655 exams to 9604. It was observed that all the capitals studied showed an increase in the annual percentage variation of Pap smear coverage, with the exception of Brasília, Manaus, Porto Alegre and Porto Velho, which did not show a statistically significant increase (APC = 3.01, 2.746, 3.987, 3.69, respectively). When analyzing the performance of oncotic cytology exams in the capitals according to the years 2019 and 2020, it was observed that only Manaus registered an increase in the number of procedures performed, reaching a difference of 56.5% from one year to the next. CONCLUSION: The ecological analysis revealed a worrying drop in the number of tests performed in 2020, reflecting a sharp drop in coverage actions in Brazilian capitals during the pandemic caused by the SARS-CoV-2 virus. The pandemic has exacerbated existing inequalities and highlighted the need for adaptive strategies to maintain essential screening services in times of crisis.

Revealing the Mysteries of Population Mobility Amid the COVID-19 Pandemic in Canada: Comparative Analysis With Internet of Things-Based Thermostat Data and Google Mobility Insights.

BACKGROUND: The COVID-19 pandemic necessitated public health policies to limit human mobility and curb infection spread. Human mobility, which is often underestimated, plays a pivotal role in health outcomes, impacting both infectious and chronic diseases. Collecting precise mobility data is vital for understanding human behavior and informing public health strategies. Google's GPS-based location tracking, which is compiled in Google Mobility Reports, became the gold standard for monitoring outdoor mobility during the pandemic. However, indoor mobility remains underexplored. OBJECTIVE: This study investigates in-home mobility data from ecobee's smart thermostats in Canada (February 2020 to February 2021) and compares it directly with Google's residential mobility data. By assessing the suitability of smart thermostat data, we aim to shed light on indoor mobility patterns, contributing valuable insights to public health research and strategies. METHODS: Motion sensor data were acquired from the ecobee "Donate Your Data" initiative via Google's BigQuery cloud platform. Concurrently, residential mobility data were sourced from the Google Mobility Report. This study centered on 4 Canadian provinces-Ontario, Quebec, Alberta, and British Columbia-during the period from February 15, 2020, to February 14, 2021. Data processing, analysis, and visualization were conducted on the Microsoft Azure platform using Python (Python Software Foundation) and R programming languages (R Foundation for Statistical Computing). Our investigation involved assessing changes in mobility relative to the baseline in both data sets, with the strength of this relationship assessed using Pearson and Spearman correlation coefficients. We scrutinized daily, weekly, and monthly variations in mobility patterns across the data sets and performed anomaly detection for further insights. RESULTS: The results revealed noteworthy week-to-week and month-to-month shifts in population mobility within the chosen provinces, aligning with pandemic-driven policy adjustments. Notably, the ecobee data exhibited a robust correlation with Google's data set. Examination of Google's daily patterns detected more pronounced mobility fluctuations during weekdays, a trend not mirrored in the ecobee data. Anomaly detection successfully identified substantial mobility deviations coinciding with policy modifications and cultural events. CONCLUSIONS: This study's findings illustrate the substantial influence of the Canadian stay-at-home and work-from-home policies on population mobility. This impact was discernible through both Google's out-of-house residential mobility data and ecobee's in-house smart thermostat data. As such, we deduce that smart thermostats represent a valid tool for facilitating intelligent monitoring of population mobility in response to policy-driven shifts.

Dietary microalgal-fabricated selenium nanoparticles improve Nile tilapia biochemical indices, immune-related gene expression, and intestinal immunity.

BACKGROUND: Feed supplements, including essential trace elements are believed to play an important role in augmenting fish immune response. In this context, selenium nanoparticles (SeNPs) in fish diets via a green biosynthesis strategy have attracted considerable interest. In this investigation, selenium nanoparticles (SeNPs, 79.26 nm) synthesized from the green microalga Pediastrum boryanum were incorporated into Nile tilapia diets to explore its beneficial effects on the immune defense and intestinal integrity, in comparison with control basal diets containing inorganic Se source. Nile tilapia (No. 180, 54-57 g) were fed on three formulated diets at concentrations of 0, 0.75, and 1.5 mg/kg of SeNPs for 8 weeks. After the trial completion, tissue bioaccumulation, biochemical indices, antioxidant and pro-inflammatory cytokine-related genes, and intestinal histological examination were analyzed. RESULTS: Our finding revealed that dietary SeNPs significantly decreased (P < 0.05) serum alkaline phosphatase (ALP), lactate dehydrogenase (LDH), and cholesterol, while increasing (P < 0.05) high-density lipoproteins (HDL). The Se concentration in the muscle tissues showed a dose-dependent increase. SeNPs at a dose of 1.5 mg/kg significantly upregulated intestinal interleukin 8 (IL-8) and interleukin 1 beta (IL-1ß) gene transcription compared with the control diet. Glutathione reductase (GSR) and glutathione synthetase (GSS) genes were significantly upregulated in both SeNPs-supplemented groups compared with the control. No apoptotic changes or cell damages were observed as indicated by proliferating cell nuclear antigen (PCNA) and caspase-3 gene expression and evidenced histopathologically. SeNPs supplementation positively affects mucin-producing goblet cells (GCs), particularly at dose of 1.5 mg/kg. CONCLUSION: Therefore, these results suggest that Green synthesized SeNPs supplementation has promising effects on enhancing Nile tilapia immunity and maintaining their intestinal health.

Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility.

Soil health plays a crucial role in crop production, both in terms of quality and quantity, highlighting the importance of effective methods for preserving soil quality to ensure global food security. Soil quality indices (SQIs) have been widely utilized as comprehensive measures of soil function by integrating multiple physical, chemical, and biological soil properties. Traditional SQI analysis involves laborious and costly laboratory analyses, which limits its practicality. To overcome this limitation, our study explores the use of visible near-infrared (vis-NIR) spectroscopy as a rapid and non-destructive alternative for predicting soil properties and SQIs. This study specifically focused on seven soil indicators that contribute to soil fertility, including pH, organic matter (OM), potassium (K), calcium (Ca), magnesium (Mg), available phosphorous (P), and total nitrogen (TN). These properties play key roles in nutrient availability, pH regulation, and soil structure, influencing soil fertility and overall soil health. By utilizing vis-NIR spectroscopy, we were able to accurately predict the soil indicators with good accuracy using the Cubist model (R2 = 0.35-0.93), offering a cost-effective and environmentally friendly alternative to traditional laboratory analyses. Using the seven soil indicators, we looked at three different approaches for calculating and predicting the SQI, including: (1) measured SQI (SQI_m), which is derived from laboratory-measured soil properties; (2) predicted SQI (SQI_p), which is calculated using predicted soil properties from spectral data; and (3) direct prediction of SQI (SQI_dp), The findings demonstrated that SQI_dp exhibited a higher accuracy (R2 = 0.90) in predicting soil quality compared to SQI_p (R2 = 0.23).

The international Family Affluence Scale (FAS): Charting 25 years of indicator development, evidence produced, and policy impact on adolescent health inequalities.

In the absence of suitable indicators of adolescent socioeconomic status, the Family Affluence Scale (FAS) was first developed in Scotland 25 years ago. Since then, it has been adapted for use in the Health Behaviour in School-Aged Children (HBSC) Study to research inequalities in adolescent health in Europe and North America. FAS has also been used as an indicator of adolescent socioeconomic status in research studies outside of HBSC, worldwide. There has been a need for FAS to evolve and change its component items over time in order to take into account social and technological changes influencing the families of adolescents. This paper uniquely charts the development of FAS describing the methodological work carried out to validate the measure internationally and over time. It also presents an overview of the body of evidence on adolescent health inequalities produced over years from the HBSC Study and other research studies. Interviews conducted with policy stakeholders reveal that the evidence from FAS-related HBSC work has influenced their strategic work to raise awareness of inequalities and make the case for action to address these. Finally, the future of FAS is discussed with respect to its continual evolution in the context of technological, environmental and social change.

Psychometrics of psychosocial behavior items under age 6 years: Evidence from Nebraska, USA.

Because healthy psychosocial development in the first years of life is critical to lifelong well-being, governmental, and nongovernmental organizations are increasingly interested in monitoring psychosocial behaviors among populations of children. In response, the World Health Organization is developing the Global Scales of Early Development Psychosocial Form (GSED PF) to facilitate population-level psychosocial monitoring. Once validated, the GSED PF will be an open-access, caregiver-reported measure of children's psychosocial behaviors that is appropriate for infants and young children. This study examines the psychometric validity evidence from 45 items under consideration for inclusion in the GSED PF. Using data from N = 836 Nebraskan (USA) children aged 180 days to 71 months, results indicate that scores from 44 of the 45 (98%) items exhibit positive evidence of validity and reliability. A bifactor model with one general factor and five specific factors best fit the data, exhibited strong reliability, and acceptable model fit. Criterion associations with known predictors of children's psychosocial behaviors were in the expected direction. These findings suggest that measurement of children's psychosocial behaviors may be feasible, at least in the United States. Data from more culturally and linguistically diverse settings is needed to assess these items for global monitoring.

Debido a que el desarrollo sicosocial en los primeros años de vida es crítico para el bienestar de toda la vida, las organizaciones gubernamentales y no gubernamentales están más y más interesadas en observar vigilantemente las conductas sicosociales en la población infantil. Como respuesta, la Organización Mundial de la Salud está desarrollando el Formulario Sicosocial de las Escalas Globales del Temprano Desarrollo (GSED PF) para facilitar la observación sicosocial alerta al nivel del grupo de población. Una vez que se haya convalidado, el GSED PF será una medida de acceso abierto, que reportará el cuidador, sobre las conductas sicosociales de los niños que son apropiadas para infantes y niños pequeñitos. Este estudio examina la evidencia de la validez sicométrica de 45 puntos bajo consideración para ser incluidos en el GSED PF. Usando datos de N = 836 niños de Nebraska (Estados Unidos), de edad entre 180 días y 71 meses, los resultados indican que los puntajes de 44 de los 45 (98%) puntos muestran evidencia positiva de validez y confiabilidad. Un modelo bifactorial con un factor general y cinco factores específicos, que mejor encaja con los datos, mostró una fuerte confiabilidad y un modelo aceptable que encaja. Las asociaciones de criterio con factores de predicción conocidos acerca de las conductas sicosociales de los niños se encontraban en la dirección esperada. Estos resultados sugieren que la medida de las conductas sicosociales de los niños pudiera ser posible, por lo menos en los Estados Unidos. Se necesitan datos de escenarios más diversos cultural y lingüísticamente para evaluar estos puntos para la estar alerta en la observación global.

Trends in caesarean section rates in Europe from 2015 to 2019 using Robson's Ten Group Classification System: A Euro-Peristat study.

OBJECTIVE: To assess changes in caesarean section (CS) rates in Europe from 2015 to 2019 and utilise the Robson Ten Group Classification System (TGCS) to evaluate the contribution of different obstetric populations to overall CS rates and trends. DESIGN: Observational study utilising routine birth registry data. SETTING: A total of 28 European countries. POPULATION: Births at ≥22 weeks of gestation in 2015 and 2019. METHODS: Using a federated model, individual-level data from routine sources in each country were formatted to a common data model and transformed into anonymised, aggregated data. MAIN OUTCOME MEASURES: By country: overall CS rate. For TGCS groups (by country): CS rate, relative size, relative and absolute contribution to overall CS rate. RESULTS: Among the 28 European countries, both the CS rates (2015, 16.0%-55.9%; 2019, 16.0%-52.2%) and the trends varied (from -3.7% to +4.7%, with decreased rates in nine countries, maintained rates in seven countries (≤ ± 0.2) and with increasing rates in 12 countries). Using the TGCS (for 17 countries), in most countries labour induction increased (groups 2a and 4a), whereas multiple pregnancies (group 8) decreased. In countries with decreasing overall CS rates, CS tended to decrease across all TGCS groups, whereas in countries with increasing rates, CS tended to increase in most groups. In countries with the greatest increase in CS rates (>1%), the absolute contributions of groups 1 (nulliparous term cephalic singletons, spontaneous labour), 2a and 4a (induction of labour), 2b and 4b (prelabour CS) and 10 (preterm cephalic singletons) to the overall CS rate tended to increase. CONCLUSIONS: The TGCS shows varying CS trends and rates among countries of Europe. Comparisons between European countries, particularly those with differing trends, could provide insight into strategies to reduce CS without clinical indication.

Indicators to support local public health to reduce the impacts of heat on health.

Heat exposure presents a significant weather-related health risk in England and Wales, and is associated with acute impacts on mortality and adverse effects on a range of clinical conditions, as well as increased healthcare costs. Most heat-related health outcomes are preventable with health protection measures such as behavioural changes, individual cooling actions, and strategies implemented at the landscape level or related to improved urban infrastructure. We review current limitations in reporting systems and propose ten indicators to monitor changes in heat exposures, vulnerabilities, heat-health outcomes, and progress on adaptation actions. These indicators can primarily inform local area decision-making in managing risks across multiple sectors such as public health, adult and social care, housing, urban planning, and education. The indicators can be used alongside information on other vulnerabilities relevant for heat and health such as underlying morbidity or housing characteristics, to prioritise the most effective adaptation actions for those who need it the most.

[WORLD EXPERIENCE: HOW THE DEVELOPMENT OF THE PRINCIPLES OF ACADEMICIAN OF THE ACADEMY OF MEDICAL SCIENCES OF THE USSR N. A. SEMASHKO HELPED ICELAND TO CREATE ONE OF THE MOST EFFECTIVE HEALTHCARE SYSTEMS IN THE WORLD. PART 1. HISTORICAL OVERVIEW].

Annotation. The review article is devoted to the healthcare system of Iceland, which demonstrates some of the best indicators of public health in the world at relatively low costs for a developed European country. The successful experience of Icelandic healthcare is important for Russia, on the one hand, due to the proximity of this country to many Russian regions in terms of climatic and geographical location, demography and territorial development. On the other hand, the success of Iceland's healthcare is closely linked to the development of a model, in many ways similar to the Soviet model of Nikolai Semashko, which Russia has abandoned. The authors believe that Iceland's experience can be used in the modernization of regional healthcare systems in Eastern Siberia, the Far East and the Arctic, as well as Russian healthcare in general.

[WORLD EXPERIENCE: HOW THE DEVELOPMENT OF THE PRINCIPLES OF ACADEMICIAN OF THE ACADEMY OF MEDICAL SCIENCES OF THE USSR N. A. SEMASHKO HELPED ICELAND TO CREATE ONE OF THE MOST EFFECTIVE HEALTHCARE SYSTEMS IN THE WORLD. PART 2. PRINCIPLES FUNCTIONING OF THE ICELANDIC HEALTH SYSTEM].

Annotation. The review article is devoted to the healthcare system of Iceland, which demonstrates some of the best indicators of public health in the world at relatively low costs for a developed European country. The successful experience of Icelandic healthcare is important for Russia, on the one hand, due to the proximity of this country to many Russian regions in terms of climatic and geographical location, demography and territorial development. On the other hand, the success of Iceland's healthcare is closely linked to the development of a model, in many ways similar to the Soviet model of Nikolai Semashko, which Russia has abandoned. The authors believe that Iceland's experience can be used in the modernization of regional healthcare systems in Eastern Siberia, the Far East and the Arctic, as well as Russian healthcare in general.

Key findings from NFHS-5 India report: Observing trends of health indicators between NFHS-4 and NFHS-5.

The National Health Family Survey (NFHS) is one of the largest cross-sectional surveys in the world and plays a very important role in seeing the health sector's growth in India. Its comprehensiveness in data points serves as a baseline for policymakers to amend or continue the health policy at the national and state levels. It is also imperative to look up the survey's major findings and compare the same with the previous survey finding to obtain a trend (positive/negative) of the placed data indicators. In writing this information, we aim to provide a researched paper to undergraduates and postgraduates in medical education to identify the trends or gap pockets in NFHS-4 and NFHS-5. These findings might help them as an educational piece of work and further research evidence in their local community. Also, the present work is the compilation of demographic characteristics and major health indicators.

The H9c2(2-1) cell-based sulforhodamine B assay is a non-animal alternative to evaluate municipal wastewater quality over time.

The present study validates the potential of the in vitro H9c2(2-1) cell-based sulforhodamine B (SRB) assay to evaluate the temporal variability of wastewater quality. The impact of effluent disposal on water quality and the efficiency of the wastewater treatment process were also assessed. To correlate standard analytical method results with in vitro results, a total of 16 physicochemical parameters, such as nutrients, pH, chemical oxygen demand, total suspended solids and metals, were determined in both raw and treated wastewater samples. Results revealed that the H9c2(2-1) cell-based SRB assay has an enormous potential to evaluate municipal wastewater quality over time and to discriminate influent and effluent toxic characteristics, as well as for water quality monitoring and surveillance of the efficacy of treatment processes. Finally, the gathered results alerted to the impact of phosphates in a biological system, leading us to recommend the selection of this parameter as a potential environmental health indicator.

Normal isn't normal: On the medicalization of health.

BACKGROUND: This study investigated the proportion of the U.S. population classified as healthy based on 10 common indicators, examined in two ways: (1) above or below (in the healthy direction) the sample median (termed "normal"), and (2) below diagnostic cut-off points for clinical caseness or high risk (termed "ideal"). METHODS: Data are from the 2017-March 2020 round of the National Health and Nutrition Examination Survey (NHANES). Sample sizes ranged from 3,956 to 8,961 for respective health indicators, with a total of 3,102 respondents for two weighted multi-item measures described below. Measures included the Alameda 5 health behaviors (smoking, drinking exercising, sleeping, and body mass index) and five standard biomarkers (systolic and diastolic blood pressure, resting heart rate, fasting glucose, and total cholesterol). Besides point prevalences for the normal and ideal categories for each indicator, we also calculated the proportion healthy for all 10 indicators, again calculated both ways, termed "meta-normal" and "meta-ideal." RESULTS: The prevalence of meta-normality was 1.05%, suggesting that hardly any adult Americans are completely healthy according to population norms. Findings for meta-ideality showed that while most Americans are not clinical cases for any respective indicator, only 5.55% met the official criteria for being healthy according to all 10 indicators. CONCLUSION: Most Americans appear healthy according to nearly all key health indicators and biomarkers, according to "normal" or "ideal" criteria. However, the proportion healthy according to all measures is extremely small. Relatively few U.S. adults are completely healthy according to clinical criteria (meta-ideal), and even fewer are completely healthy according to population norms (meta-normal). Results are interpreted through sociological writing on medicalization.

Applying Life History Theory to Understand Earlier Onset of Puberty: An Adolescent Brain Cognitive Development Cohort Analysis.

PURPOSE: Life history theory posits that multigenerational exposure to adversity and deprivation influences childhood growth and development, including pubertal maturation. We applied this ecological, evolutionary theory to examine the contributions of distal and proximal adversity on early puberty, a potentially important marker for population health. METHODS: Baseline data from 5,645 girls in the adolescent brain cognitive development study were included. Early puberty was defined as midlate/post pubertal development by age 9-11 years. The contributions of multigenerational Black/Indigenous (Black, Indigenous and People of Color [BIPOC]) or Hispanic identities, intergenerational mental health, economic deprivation, personal trauma exposure and mental health, and proximal biological factors of premature birth and body mass index on early puberty were examined with hierarchical modeling. RESULTS: 1,225 girls (21.7%) had early puberty. BIPOC/Hispanic identity, familial adversity, economic deprivation, personal trauma, depression, and a higher body mass index contributed significantly toward early puberty. The effect of multigenerational adversity remained significant across models, but the likelihood of early puberty decreased sequentially for BIPOC and Hispanic youth as proximal adversities were added (e.g., OR decreased from 2.93 to 2.38 for BIPOC youth), supporting a synergistic effect of layered adversity on early puberty. DISCUSSION: This analysis supports life history theory as a coherent framework to understand early puberty among girls. Findings suggest monitoring pubertal timing as a population health indictor, like birth weight, prematurity, or life expectancy. Addressing early puberty may require policy and social changes to mitigate the negative impact of multiple layers of adversity including racial/ethnic disadvantage, family, and individual mental health and trauma, as well as economic insecurity.

Developing and testing a protocol using a common data model for federated collection and analysis of national perinatal health indicators in Europe.

Context: International comparisons of the health of mothers and babies provide essential benchmarks for guiding health practice and policy, but statistics are not routinely compiled in a comparable way. These data are especially critical during health emergencies, such as the coronavirus disease (COVID-19) pandemic. The Population Health Information Research Infrastructure (PHIRI) project aimed to promote the exchange of population data in Europe and included a Use Case on perinatal health. Objective: To develop and test a protocol for federated analysis of population birth data in Europe. Methods: The Euro-Peristat network with participants from 31 countries developed a Common Data Model (CDM) and R scripts to exchange and analyse aggregated data on perinatal indicators. Building on recommended Euro-Peristat indicators, complemented by a three-round consensus process, the network specified variables for a CDM and common outputs. The protocol was tested using routine birth data for 2015 to 2020; a survey was conducted assessing data provider experiences and opinions. Results: The CDM included 17 core data items for the testing phase and 18 for a future expanded phase. 28 countries and the four UK nations created individual person-level databases and ran R scripts to produce anonymous aggregate tables. Seven had all core items, 17 had 13-16, while eight had ≤12. Limitations were not having all items in the same database, required for this protocol. Infant death and mode of birth were most frequently missing. Countries took from under a day to several weeks to set up the CDM, after which the protocol was easy and quick to use. Conclusion: This open-source protocol enables rapid production and analysis of perinatal indicators and constitutes a roadmap for a sustainable European information system. It also provides minimum standards for improving national data systems and can be used in other countries to facilitate comparison of perinatal indicators.

The Impact of Continuity of Care on Health Indicators in Patients With Type 2 Diabetes Mellitus in Family Medicine Clinics in Riyadh.

BACKGROUND: Diabetes Mellitus Type 2 (DM2) is highly prevalent in Saudi Arabia, with many experiencing complications due to the disease. Family medicine physicians are usually the primary care providers responsible for the medical management of type 2 diabetes mellitus patients. Microvascular and macrovascular complications can occur if type 2 diabetes mellitus is poorly managed. Effective management of health indicators in patients with DM2 relating to glycated hemoglobin (HbA1c), low density lipoprotein cholesterol, blood pressure, and tobacco use is an essential part of medical care to prevent complications. Due to the projected increase in the number of patients with DM2, there is huge concern surrounding the management of this chronic illness that requires review. This study aims to evaluate the impact of continuity of care on health indicators among family medicine patients diagnosed with diabetes mellitus type 2 and to analyze the effect of continuity of care regarding the completion of age-appropriate preventive health screenings. METHODS:  This is a retrospective cohort study. Data collected from electronic medical records of patients 40-75 years of age that received care at the Family Medicine clinics that were diagnosed with type 2 diabetes mellitus with ≥4 clinic visits from January 1, 2017, to June 30, 2020, at King Faisal Specialist Hospital & Research Centre in Riyadh, Saudi Arabia. Data collected included demographic data, body mass index, smoking status, blood pressure, past medical history, preventive health screening completed, and laboratory results, including HbA1c and lipid profile. The continuity of care index and usual provider continuity score indices were calculated for the analysis to measure continuity of care. RESULTS:  Three hundred and fifty-two patients were included in the study. Most of the patients were Saudi (74.15%), female (51.99%), and married (82.67%). In addition, 90.34% accounted for a high usual provider continuity of care score (UPCS), and 64.20% of the patients had a high continuity of care index (COCi). Younger age groups were significantly more prevalent in the high UPCS group (p=0.037). Additionally, patients of non-Saudi nationalities constituted a significantly larger proportion of the high UPCS group. Single patients showed high UPCS. Comorbidities were not different between the groups, except inflammatory joint disease, which was more common in the low COCi group. Preventative screening measures were also not different between the groups; however, the type of colon cancer screening differed, where patients with high COCi more frequently underwent colonoscopies (13.3% vs. 4.4%, p=0.015) instead of fecal occult blood tests. CONCLUSION:  For the first time, we report the implications of the continuity of care for DM2 patients in Saudi Arabia and the Middle East. Continuity of care did not result in the improvement of health indicators or in the completion of preventive health screenings in diabetic patients. Further studies are needed in the region to confirm our findings and assess the association between continuity of care and patient health indicators impact.

Digital health solution for monitoring and surveillance of Amyotrophic Lateral Sclerosis in Brazil.

Amyotrophic Lateral Sclerosis (ALS) is a complex and rare neurodegenerative disease given its heterogeneity. Despite being known for many years, few countries have accurate information about the characteristics of people diagnosed with ALS, such as data regarding diagnosis and clinical features of the disease. In Brazil, the lack of information about ALS limits data for the research progress and public policy development that benefits people affected by this health condition. In this context, this article aims to show a digital health solution development and application for research, intervention, and strengthening of the response to ALS in the Brazilian Health System. The proposed solution is composed of two platforms: the Brazilian National ALS Registry, responsible for the data collection in a structured way from ALS patients all over Brazil; and the Brazilian National ALS Observatory, responsible for processing the data collected in the National Registry and for providing a monitoring room with indicators on people diagnosed with ALS in Brazil. The development of this solution was supported by the Brazilian Ministry of Health (MoH) and was carried out by a multidisciplinary team with expertise in ALS. This solution represents a tool with great potential for strengthening public policies and stands out for being the only public database on the disease, besides containing innovations that allow data collection by health professionals and/or patients. By using both platforms, it is believed that it will be possible to understand the demographic and epidemiological data of ALS in Brazil, since the data will be able to be analyzed by care teams and also by public health managers, both in the individual and collective monitoring of people living with ALS in Brazil.

Leveraging explainable machine learning models to assess forest health: A case study in Hainan, China.

Global forest area has declined over the past few years, forest quality has declined, and ecological and environmental events have increased with climate change and human activity. In the context of ecological civilization, forest health issues have received unprecedented attention. By improving forest health, forests can better perform their ecosystem service functions and promote green development. This study was carried out in the WuZhi Shan area of Hainan Tropical Rainforest National Park. We employed a decision tree algorithm, a machine learning technique, for our modeling due to its high accuracy and interpretability. The objective weighted method using criteria of importance through intercriteria correlation (CRITIC) was used to determine forest health classes based on survey and experimental data from 132 forest samples. The results showed that species diversity is the most important metric to measure forest health. An interpretable decision tree machine learning model was proposed to incorporate forest health indicators, providing up to 90% accuracy in the classification of forest health conditions. The model demonstrated a high degree of effectiveness, achieving an average precision of 90%, a recall of 67%, and an F1 score of 70.2% in predicting forest health. The interpretable decision tree classification results showed that breast height diameter is the most important variable in classifying the health status of both primary and secondary forests. This study highlights the importance of using interpretable machine learning methods for the decision-making process. Our work contributes to the scientific underpinnings of sustainable forest development and effective conservation planning.