Search Results (275)

Background/Objectives: Healthy food incentive programs (HFIP), such as fruit and vegetable voucher incentives, can supplement other nutrition assistance programs to support food and nutrition security. However, little is known about the prevalence of HFIP, particularly at the municipal level. This study examines the prevalence of HFIP in a nationally representative sample of U.S. municipalities and the association between the availability of HFIP and municipal characteristics. Methods: Using data from the CDC’s 2021 National Survey of Community-Based Policy and Environmental Supports for Healthy and Active Living (n = 1982 municipalities), a weighted bivariate analysis and multivariable logistic regression analysis were conducted to estimate the prevalence of HFIP overall and by municipal characteristics, and to assess the relationship between municipal characteristics and HFIP. Results: Only 7.8% of municipalities reported offering HFIP in 2021. The odds of having an HFIP were higher in municipalities with a food policy council (aOR 2.8; 95%CI: 1.9, 3.9) compared to those without. Larger communities (size ≥ 50,000 reported 24.6%) and those with a higher prevalence of residents living in poverty were also more likely to offer HFIP. Conclusions: Few municipalities reported offering HFIP. Results suggested that engaging institutions and individuals (e.g., via food access coalitions) may be strategies that could support municipalities initiating and implementing HFIP to improve diet quality and reduce chronic disease risk. Full article

Localization and navigation techniques have become fundamental for modern lives, while achieving accurate results indoors still remains a significant challenge. The widespread adoption of smart devices, and especially smartphones, has increased the need for accurate and robust pedestrian dead reckoning systems that operate in infrastructure-less environments. Pedestrian dead reckoning’s primary challenge is maintaining accuracy despite varying smartphone placements (attitudes) and the noisy, low-cost inertial measurements units. In this work, a comprehensive pedestrian dead reckoning framework is presented that integrates advanced step counting and heading estimation techniques. For step detection and counting, we propose a robust step counting algorithm that utilizes the optimum fusion of the raw IMU readings, i.e., accelerometer, linear accelerometer, gyroscope, and magnetometer readings, each broken down into three degrees of freedom for different body placements and walking speeds. Furthermore, to address the critical issue of heading estimation, we propose the heading estimation axis mapping (HEAT-MAP) algorithm, which dynamically adjusts the sensor axes in response to the smartphone’s orientation, ensuring a consistent coordinate frame and reducing heading drift. Moreover, to eliminate cumulative pedestrian dead reckoning errors, the system incorporates an adaptive weighted fusion mechanism with Wi-Fi fingerprinting. Experimental results demonstrate that this integrated system significantly improves the overall trajectory accuracy, providing a high-precision, attitude-unconstrained solution for real-time indoor pedestrian navigation. Full article

Background/Objectives: Stroke is a leading cause of mortality and disability in Saudi Arabia; however, national estimates of stroke-related rehabilitation needs remain limited. This study quantified temporal trends in stroke incidence, prevalence, premature mortality, and disability from 1990 to 2021. It also examined disparities in stroke-related disability by subtype, sex, and age in 2021 and projected rehabilitation demand to 2030 to inform health system planning under Vision 2030. Methods: We conducted a secondary analysis of Global Burden of Disease (GBD) 2021 estimates for Saudi Arabia. Age-standardized rates for incidence, prevalence, years of life lost (YLLs), and years lived with disability (YLDs) were extracted for overall stroke and three subtypes: ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). Temporal trends were evaluated using log-linear regression to estimate the average annual percentage change (AAPC). YLDs were mapped to severity levels and four rehabilitation modalities, physiotherapy (PT), occupational therapy (OT), speech–language therapy (SLT), and multidisciplinary comprehensive rehabilitation (MCR), using utilization probabilities informed by the literature. Projections to 2030 incorporated national population forecasts and included 95% prediction intervals and sensitivity analyses. Results: From 1990 to 2021, age-standardized stroke incidence declined from 166.3 to 130.7 per 100,000 (−21.4%; AAPC, −0.86%, p = 0.004), prevalence from 982.4 to 965.2 per 100,000 (−1.8%; AAPC, −0.10%, p = 0.056), and YLL rates from 3209.0 to 1893.4 per 100,000 (−41.0%; AAPC, −1.76%, p < 0.001). In contrast, YLD rates declined modestly from 133.5 to 129.9 per 100,000 (−2.7%; AAPC, −0.13%; p = 0.032). Despite these reductions in age-standardized rates, absolute stroke-related YLDs more than tripled, increasing from approximately 10,900 (95% UI: 8100–13,900) in 1990 to 36,245 (95% UI: 26,600–46,100) in 2021, largely driven by population growth and aging. In 2021, ischemic stroke accounted for 71.1% of total YLDs, followed by ICH (20.3%) and SAH (8.5%). Among adults aged 15–49 years, females had higher hemorrhagic YLD rates than males, with particularly pronounced differences for SAH (female-to-male ratio, 1.5–1.7). By 2030, the projected YLD-equivalent workload, a standardized proxy measure of relative service demand rather than a direct headcount of required therapists, is expected to increase to 29,758 for PT, 21,809 for OT, 14,879 for SLT, and 15,083 for MCR. Sensitivity analyses showed that rehabilitation demand estimates were sensitive to assumptions regarding severity distribution, with a hemorrhagic-weighted scenario increasing projected MCR demand by 6.8%. Conclusions: The increasing absolute burden of stroke-related disability in Saudi Arabia, despite declining age-standardized rates and substantial reductions in premature mortality, highlights the necessity to expand rehabilitation capacity. Scaling community-based, outpatient, and telerehabilitation services in alignment with the Health Sector Transformation Program and integrating disability-informed planning into Vision 2030 should be prioritized. Full article

The ongoing development of the economy and society has increasingly intensified the imbalance between the supply and demand of land resources. Achieving coordinated development between socio-economic growth and the “Production-Living-Ecological” functions of land-use is therefore a key foundation for high-quality regional development. In light of this, this study focuses on Henan Province at the county level. Building on a theoretical framework that examines the relationship between socio-economic development and the “Production-Living-Ecological” functions of land-use, we employed methods including the entropy method, linear weighting method, mechanical equilibrium model, and curve estimation model. These were used to explore the evolution characteristics and interactive relationship between socio-economic development and the “Production-Living-Ecological” functions at the county level in Henan Province. The findings reveal that: (1) The socio-economic development level of counties in Henan showed an overall upward trend during the study period, with the average value rising from 0.2320 in 2010 to 0.2702 in 2023. High-level areas were mainly concentrated in the central region around Zhengzhou. (2) The overall level of the “Production-Living-Ecological” functions of land-use in Henan’s counties followed a gradually increasing trend, with a relatively stable evolution process. The functional levels in northern, central, and eastern Henan were notably higher than those in the western and southern regions. (3) There is a significant positive correlation between the socio-economic development level of counties in Henan and the comprehensive level of the “Production-Living-Ecological” functions of land-use. Moreover, socio-economic development exerts a one-way influence on the functional level of “Production-Living-Ecological” in land-use. Identifying the interactive relationship between socio-economic factors and these land-use functions can provide quantitative references and a decision-making basis for rationally adjusting the “Production-Living-Ecological” functions across different stages of development. Full article

Atrial septal defect (ASD) affects 1:11.3 children in some US states; however, the antecedents of these trends are yet to be identified. A total of 1882 ASD rates (ASDRs) for 2003–2020 were sourced from the National Birth Defects Prevention Network reports. A total of 406,893 ASDs are reported. Substance (cigarettes, binge alcohol, cannabis, cannabinoids, analgesics, cocaine) exposure data were taken from the National Survey of Drug Use and Health. Income and ethnicity data were derived from the US Census. Adjustment was performed by mixed effects, survey and generalized additive regression. Causal analysis was by inverse probability weighting and E-values. Data were analyzed in RStudio. The highest ASDR of 884/10,000 live births was amongst Non-Hispanic Asians and Pacific Islanders in Nevada in 2016–2020. The 2005–2018 median ASDR rose >12-fold in Nevada and New Mexico, >6-fold in New York, and 4.2-fold nationally 1989–2020; it doubled in NY from 2012–2016 to 2016–2020. The average state ASDR rose supra-exponentially (p = 0.0075) and was associated with higher cannabis use states (p = Zero, Cohen’s D = 1.24), apparently driven by cannabis legalization (p = Zero). Estimated exposures to Δ9THC, cannabidiol and cannabigerol were implicated (from p = 2.67 × 10^–68). Cannabis-legal states were compared with others (mean ASDR (C.I.) 178.15 (131.68, 224.62) vs. 74.28 (70.60, 77.96), p = Zero; O.R. 1.82 (1.81, 1.84), E-values 3.04 (lower C.I. 3.02), Cohen’s D 1.29 (0.96, 1.62)). Overall, 29/39 (74.4%) E-value estimates were >4; 39/39 (100%) were >1.25. Cannabis, cannabinoids and cannabis legalization are strong candidates for driving the US ASDR supra-exponentially. Estimates of many cannabinoids, including cannabidiol, Δ9THC, and cannabigerol, are implicated. The results are consistent with other large epidemiological studies. The importance of the results is magnified by the increasing legalization and penetration of cannabinoids into the US population. Since therapeutic abortion is not practiced for ASD, it may be used as a bellwether index of heritable transgenerational cannabinoid genotoxicity and epigenotoxicity associated with cannabinoid exposure. Full article

Multi-wavelength lensless microscopy enables high-speed, wide-field, and high-throughput imaging, making it highly attractive for modern biomedical applications. However, its practical performance is often limited by unreliable autofocusing and wavelength-dependent phase inconsistencies, which together degrade reconstruction fidelity in complex environments. To explicitly address these two limitations, we present a fully scanning-free computational microscopy framework using a static four-wavelength Light-Emitting Diode (LED) illumination module that sequentially switches between wavelengths to provide strong spectral constraints. For robust geometric parameter estimation, we develop an Adaptive-Weighted Multi-wavelength Autofocus (A-WMAF) scheme that exploits the differential defocus sensitivities of multiple wavelengths to yield a single, sharply peaked autofocus curve and thereby reliably determines the sample–sensor distance. To mitigate chromatic phase inconsistencies, we further introduce an iterative optical-path-difference (OPD)–domain adaptive fusion strategy that fuses multi-wavelength phase estimates in a physically consistent OPD space, suppressing wavelength-dependent artifacts and reconstruction noise. With only four raw holograms acquired within seconds, the proposed method achieves high-fidelity quantitative phase reconstruction with a Phase Structural Similarity Index Measure (SSIM) of 0.9942 and a quantitative OPD accuracy of 95.0%, as well as a measured lateral resolution of 1.23 µm, surpassing the Nyquist–Shannon sampling limit. Experimental demonstrations on fixed biological samples and long-term live-cell monitoring validate that the proposed framework simultaneously achieves reliable autofocusing and chromaticity-robust phase fusion, highlighting its potential for high-throughput biomedical imaging and clinical diagnostics. Full article

Siberian sturgeon (Acipenser baerii Brandt, 1869), characterized by its rapid mass accumulation and high survival rate under industrial breeding conditions, is one of the most promising aquacultural species. This research aimed to study the growth and development of farmed Siberian sturgeon (Acipenser baerii Brandt, 1869) to improve breeding programs. This research was conducted at the Federal Research Center for Animal Husbandry named after Academy Member L.K. Ernst and focused on the Lena population broodstock of Siberian sturgeon of the April 2022 generation (n = 98), grown in a recirculating aquaculture system (RAS). The experiment took into account body weight (W, g) and eleven morphological measurements: L—absolute length (cm); LR—fish body length increase (cm/day); l—commercial length (cm); L2—fork length (cm); HL—head length (cm); PV—pectoventral distance (cm); VA—ventroanal distance (cm); pl1—peduncle length (cm); H—body height (cm); h—peduncle height (cm); SC—body thickness (cm); GC—body circumference (cm); and Cc—peduncle circumference (cm). These measurements were taken from the same sample of fish at five different time points, all belonging to the same generation and approximately the same age. Measurements were taken every 3 to 9 months: 1 y (group G1), 1 y. 5 m. (group G2), 2 y. 2 m. (group G3), 2 y. 5 m. (group G4), 3 y. 2 m. (group G5), and 3 y. 5 m. (group G6). To evaluate the rate of growth and development, relative speed of growth (SGR) and relative speed of lengthening (SLR) during the observation period were determined. To characterize the fish’s exterior, we evaluated Fulton’s condition factor (KF) and the leanness index (Q). With increasing age, there was a significant (p < 0.01) decline in both SGR (from 0.454 to 0.065 g%/day) and SLR (from 0.132 to 0.028 cm%/day), which reflects changes in the fish’s physiological processes tied to the transition from the growth phase to the puberty phase. Relatively large variability was observed in body weight (C_v = 19.7–30.4%) compared to morphological measurements (C_v = 5.7–14.9%). Correlations between morphological measurements and the body weight of the fish varied from low to high (r = 0.22–0.97). Equations that allow for very precise (coefficient of determination R² = 0.800–0.933) estimation of the fish’s body weight based on morphological measurements were developed. The most preferable predictors were measurements of H (R² = 0.931), SC (R² = 0.933), and L2 (R² = 0.930). These morphological measurements are promising candidates for future development of contactless live weight detection using computer vision and machine learning algorithms. The study of live weight conjugacy at different ages showed that the best time to use this measurement to select fish for reproduction is at the age of 2 y. 2 m. or older. Acquired data can be used for the development and improvement of programs for the selection and breeding of Siberian sturgeon grown in a recirculating aquaculture system. Full article

Background/Objectives: Keeping physical activity (PA) at an optimal level is important for protecting independence and keeping quality of life at the highest level while adopting healthy aging. This study aimed to estimate the PA levels of the older population living in Northern Cyprus and to examine the relationship between barrier and facilitator factors and PA levels. This is a cross-sectional population-based study. Methods: Detailed sociodemographic information was recorded and the PA level of the participants was evaluated using the Physical Activity Scale for the Elderly (PASE). Facilitators and barriers to participation in PA were assessed by questionnaire. Results: A total of 387 older individuals (224 women and 163 men; mean age: 74.3 ± 3.12) were grouped as youngest-old (68.31 ± 3.05) and old (80.29 ± 3.21). PA frequency and PASE scores were low in the overall study population and they were higher in the youngest-old group (p < 0.001). Conclusions: Low PA levels were estimated in older adults living in Northern Cyprus and they were significantly higher in the youngest-old group compared with the old group. There is a relationship between PA level and barriers such as fear of falling, fear of injury, comorbidities, shortness of breath, heart palpitations, incontinence, not knowing the benefits of PA, financial problems, not driving, and doing PA alone. Facilitators such as weight loss; living in a walkable area; friendship with groups; and being active, energetic, happy, and safe are related to PA level. This study highlights the importance of increasing PA levels by increasing awareness of the importance of PA in the older adult population, removing the barriers and using facilitators. Full article

Background: Family planning remains a cornerstone of reproductive health strategies to reduce maternal and child mortality by preventing unintended and high-risk pregnancies. Despite the implementation of the FP2020 initiative, empirical evidence on its population-level impact in the Democratic Republic of the Congo (DRC) remains scarce. This study examined the association between modern contraceptive use as a proxy for exposure to the FP2020 era expansion of family planning services and high-risk pregnancies and under-five mortality during the FP2020 in the DRC era. Methods: A quasi-experimental Difference-in-Differences (DiD) design was applied using Demographic and Health Survey (DHS) data from 2013 (pre-intervention) and 2023 (post-intervention). Women aged 15–49 years with at least one live birth were included for maternal outcomes, while all live-born children within five years preceding each survey were analyzed for child outcomes. Weighted analyses employed Linear Probability Models (LPMs), adjusting by potential confounder variables. Results: The prevalence of high-risk pregnancies among modern contraceptive users declined from 58.6% in 2013 to 54.5% in 2023, while under-five mortality decreased from 10.4% to 5.9% over the same period. DiD estimates revealed a significant reduction in high-risk pregnancies among users in urban areas (β = −0.067) (95% CI: −0.133 to −0.003), and a substantial decline in under-five mortality in rural areas (β = −0.031) (95% CI: −0.059 to −0.002). Results remained robust across model specifications, and a parallel trends test confirmed model validity (p > 0.5). Conclusions: Findings demonstrate that the FP2020 initiative and increased modern contraceptive use contributed to measurable reductions in maternal and child health risks in the DRC. Expanding access to family planning within universal health coverage (UHC) frameworks could further reduce health inequalities and accelerate progress toward the Sustainable Development Goals (SDGs). Full article

Accurately quantifying the amount of corn straw returned to the field is crucial for evaluating conservation tillage measures and phaeozem protection. This study proposes a framework for quantitatively estimating the amount of corn straw returned to the field based on UAV multispectral imaging, integrating a standardized spectral correction strategy, a novel straw index (SI), and an improved deep learning model (convolutional neural network-straw, CNN-Straw). By combining multispectral images acquired by UAVs with ground-measured straw weight data, regression datasets covering autumn and spring conditions were constructed. The proposed straw index aims to enhance the spectral differences between non-photosynthetic straw residues and living vegetation. Furthermore, the CNN-Straw model, combining frequency domain convolution and local spatial attention mechanisms, has an improved ability to represent the complex texture of straw features. Experimental results show that CNN-Straw outperforms traditional machine learning models, including random forest (RF), support vector regression (SVR), and XGBoost, achieving a high coefficient of determination (R²) of 0.82 on different seasonal datasets and effectively reducing the root mean square error (RMSE) and mean absolute error (MAE). Cross-seasonal experiments further demonstrate the stable performance of the framework under different environmental conditions. The proposed method provides an efficient and scalable solution for the quantitative assessment of straw return to the field, supporting precision agricultural management and phaeozem conservation practices. Full article

Live weight is widely used as a reference indicator for growth performance and for evaluating the accuracy of weight measurement technologies in pig production. However, live weight is not a fixed physiological quantity, and finishing pigs naturally experience substantial short-term mass fluctuations due to normal behaviors such as drinking, feeding, urination, and defecation. In this study, we integrated published physiological and behavioral parameters into a stochastic simulation model to quantify within-day live-weight dynamics in finishing pigs weighing approximately 100 kg. The simulation was conducted with 1-min temporal resolution over a 24-h period. The model demonstrated that short-term weight fluctuations of approximately ±3–5 kg can occur within a single day, even when measurement error is minimal. Across 1000 simulated pigs, the mean daily fluctuation range was 4.2 kg, confirming that kilogram-scale variation is physiologically expected under normal conditions. These results provide a plausible physiological basis for understanding the frequently reported discrepancies between camera-based weight estimates and instantaneous floor-scale measurements. Camera systems primarily reflect body mass derived from external morphology, whereas floor scales measure instantaneous total mass that includes transient contributions from gastrointestinal contents, ingested water, and retained waste. Consequently, direct comparisons based on instantaneous scale readings can be misleading when used as ground truth. Our findings indicate that commonly cited accuracy claims of ±2–3 kg for camera weighing systems should be interpreted with caution, as normal physiological weight variation often exceeds this range. Recognizing live weight as a dynamic physiological variable is essential for developing biologically meaningful evaluation frameworks and for the appropriate interpretation and comparison of weight measurement technologies in precision livestock farming. Full article

This study explores the feasibility of estimating tibiofemoral joint contact forces using deep learning models trained on in vivo biomechanical data. Leveraging the comprehensive CAMS-Knee datasets, we developed and evaluated two machine learning network architectures, a bidirectional Long Short-Term-Memory Network with a Multilayer Perceptron (biLSTM-MLP) and a Temporal Convolutional Network (TCN) model, to predict medial and lateral knee contact forces (KCFs) across various activities of daily living. Using a leave-one-subject-out validation approach, the biLSTM-MLP model achieved root mean square errors (RMSEs) as low as 0.16 body weight (BW) and Pearson correlation coefficients up to 0.98 for the total KCF (${\mathrm{F}}_{\mathrm{tot}}$) during walking. Although the prediction of individual force components showed slightly lower accuracy, the model consistently demonstrated high predictive accuracy and strong temporal coherence. In contrast to the biLSTM-MLP model, the TCN model showed more variable performance across force components and activities. Leave-one-feature-out analyses underscored the dominant role of lower-limb kinematics and ground reaction forces in driving model accuracy, while EMG features contributed only marginally to the overall predictive performance. Collectively, these findings highlight deep learning as a scalable and reliable alternative to traditional musculoskeletal simulations for personalized knee load estimation, establishing a foundation for future research on larger and more heterogeneous populations. Full article

Background: Neonatal mortality remains a significant public health challenge in Ethiopia. Despite efforts to implement key evidence-based interventions, their coverage and utilization remain low. The Saving Little Lives (SLL) program aims to scale-up a Minimum Care Package (MCP) of synergistic, life-saving interventions for all liveborn neonates, with a focus on preterm and low birth weight (LBW) infants, across 290 hospitals in Ethiopia (206 primary, 69 general, and 15 referral hospitals), representing 82% of all hospitals in the country at the time of the study, and evaluate the impact on neonatal mortality. Methods: A non-randomized stepped-wedge trial will be conducted to evaluate the impact of implementing the SLL MCP interventions. Quantitative evaluation data will be collected from 36 primary hospitals, selected from 206 primary hospitals across four regions, receiving the interventions. An independent evaluation research assistant will be deployed in each of the hospitals to collect data using Open Data Kit (ODK) through interviewing mothers before discharge, on the 29th day of life if discharged, and reviewing medical records. A mixed-method, cross-sectional formative assessment will be conducted prior to implementation, employing quantitative facility assessment and qualitative interviews with mothers, healthcare providers, and facility managers. This will be followed by continuous program learning assessment once implementation begins. Descriptive data will be presented using numbers, percentages, tables, and graphs. Regression modeling and generalized estimating equations (GEEs) will be used to estimate the impact of the SLL MCP interventions. Qualitative data will be gathered through in-depth interviews, digitally recorded, transcribed, and thematically analyzed using ATLAS.ti Version 7.5 software to assess facility readiness, barriers, and enablers of implementing the SLL MCP interventions. Expected Outcome: We hypothesize that achieving 80% coverage of the SLL MCP interventions among eligible neonates will result in a 35% reduction in neonatal mortality at implementation facilities. Full article

Biofouling communities are usually managed as pests in aquaculture, yet their natural proliferation in fish farms makes them also promising IMTA extractive components. The growth and biomass production of four dominant macrofoulers, Mytilus galloprovincialis (mussels), Sabella spallanzanii (polychaete worms), Phallusia mammillata and Styela plicata (ascidians), were evaluated under a novel IMTA system in the Ionian Sea (southern Italy). Coconut-fiber ropes (10 m) were deployed around fish cages in October 2022 and monitored over a 1-year cycle. Monthly density, length-frequency and cohort analyses combined with species-specific length-weight relationships were used to estimate target species’ growth and biomass. Mytilus and Sabella showed single-cohort dynamics, with densities steadily declining over time, whereas ascidians displayed continuous recruitment allowing for additional rope-deployment windows. Specific growth rates in length were significantly higher in Phallusia and Sabella (≈25% month⁻¹) than in Mytilus and Styela (≈17 and 22% month⁻¹). Total macrofouling biomass (live weight) increased from ≈350 kg in May to a peak of ≈2500 kg in August, remaining as high in October. Mytilus and Sabella accounted for 60–80% of total biomass while ascidians contributed 20–40%. Beyond environmental restoration, this multispecies biomass offers several potential commercial opportunities and could be further valorized through biorefinery-based cascading extraction, including final conversion into bioenergy. Overall, IMTA could leverage traditionally undesired fouling organisms as multifunctional crops, enhancing bioremediation while supporting circular blue-bioeconomy principles. Future research should focus on optimizing rope deployment timing, harvesting strategies, and biomass valorization pathways to fully exploit the emerging potential of integrating multispecies fouling biomass within IMTA systems. Full article

Background: Dementia and mild cognitive impairment (MCI) are major public health concerns in rapidly aging societies. However, evidence from non-Western populations with self- or proxy-reported physician-diagnosed cognitive outcomes remains limited. Methods: This study investigated the four-year (2018–2022) incidence of self- or proxy-reported dementia and MCI, and their multidomain risk markers in a nationally representative sample of 3432 Korean adults aged ≥ 65 years from the Korean Longitudinal Study of Aging. Weighted descriptive analyses and multinomial logistic regression accounting for the complex survey design (sampling weights, strata, and clusters) were used to identify demographic, functional, mental health, and social factors associated with the incidence of cognitive impairment. Adjusted predicted probabilities were estimated for age, depressive symptoms, and instrumental activities of daily living (IADL). Results: Over the four-year follow-up period, among 3432 initially cognitively normal community-dwelling older adults, 34 participants developed MCI and 70 developed dementia. Older age, increased IADL impairment, depressive symptoms, and multimorbidity were significantly associated with a higher likelihood of incident cognitive impairment, while living with family was associated with a lower likelihood. Frequent social interaction showed a protective association against dementia. Predicted probabilities demonstrated overall increasing trends across age, depressive symptoms, and IADL, reflecting general risk patterns. Conclusions: These findings emphasize the importance of multidomain assessments for early detection and community-based prevention strategies. By identifying key clinical and social markers, this study provides culturally relevant evidence to support dementia risk management in rapidly aging populations, highlighting the protective roles of family co-residence and frequent social interaction among Korean older adults. Full article