Urban Quality and Biochemical, Hematological, and Nutritional Markers in Older Adults: Cross-Sectional Geospatial Study
Bibliographic record
Abstract
Background: The urban environment is an important determinant of frailty, primarily through factors such as infrastructure that supports physical activity, availability of social and medical support, and access to nutritious food. Given the increasing aging population, understanding the link between urban quality, frailty, and metabolic health is crucial for effective public health and urban planning interventions. Objective: This study aims to quantify the impact of distinct urban domains (built-environment characteristics, accessibility to essential services, availability of green and recreational spaces, and neighborhood socioeconomic context) on frailty status, nutritional profile, and hematological or biochemical biomarkers in community-dwelling older adults by integrating geospatial analysis. Methods: A cohort of 251 older adults (aged older than 65 years) was studied. Frailty was assessed using the Frailty Trait Scale 5, and nutritional status was determined using the Controlling Nutritional Status score. Hematological and biochemical parameters were evaluated in a subset of 70 participants by MINDRAY automatic equipment. A spatial analysis of frailty was conducted by incorporating Geographic Information System layers that mapped the distribution of urban facilities, including fruit and vegetable shops, senior centers, pharmacies, emergency health centers, parks and squares, community centers, and exercise facilities. Statistical analyses included t tests, Mann-Whitney U test, ANOVA, and correlation analyses. Results: The prevalence of frailty was 17.5%. Frail individuals exhibited significantly higher BMI (mean 31.5, SD 4.4 vs mean 28.5, SD 4.5 kg/m²; P=.0001). When comparing the upper (Q4) and lower (Q1) quartiles of urban quality, Q4 participants had higher Frailty Trait Scale 5 scores (mean 15.2, SD 7.4 vs mean 11.8, SD 6.4; P=.0334) and lower handgrip strength (mean 19.1, SD 4.4 vs mean 22.8, SD 7.3 kg; P=.006). Frail individuals resided significantly closer to emergency health centers (P=.0010), family health centers (P=.0412), and exercise facilities (P=.0322). In addition, bilirubin (Spearman ρ=0.33; P=.0049), serum iron (Spearman ρ=0.27; P=.0272), transferrin saturation (Spearman ρ=0.24; P=.0386), red blood cell count (Spearman ρ=0.26; P=.0303), and red blood cell distribution width (Spearman ρ=0.23; P=.0462) were positively correlated with urban quality. Frail participants also had higher Controlling Nutritional Status scores (P=.0323), which were positively correlated with urban quality (Spearman ρ=0.25; P=.0359). Conclusions: Urban quality was significantly associated with hematological parameters, nutritional status, and frailty. Frail individuals in areas with better urban quality exhibit lower handgrip strength, higher frailty scores, and greater proximity to emergency rooms, community health centers, and exercise facilities. This spatial distribution may reflect higher accessibility to health care and recreational resources among frail participants. Urban planning and public health strategies should focus on creating age-friendly environments to prevent frailty and improve health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".