Role of Gender and Physical Activity Level on Cardiovascular Risk Factors and Biomarkers of Oxidative Stress in the Elderly
Bibliographic record
Abstract
Background . Cardiovascular diseases remain as the leading cause of morbidity and mortality in industrialized countries. Ageing and gender strongly modulate the risk to develop cardiovascular diseases but very few studies have investigated the impact of gender on cardiovascular diseases in the elderly, which represents a growing population. The purpose of this study was to test the impact of gender and physical activity level on several biochemical and clinical markers of cardiovascular risk in elderly individuals. Methods . Elderly individuals (318 women (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mn>75.8</mml:mn><mml:mo>±</mml:mo><mml:mn>1.2</mml:mn></mml:math> years-old) and 227 men (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mn>75.8</mml:mn><mml:mo>±</mml:mo><mml:mn>1.1</mml:mn></mml:math> years-old)) were recruited. Physical activity was measured by a questionnaire. Metabolic syndrome was defined using the National Cholesterol Education Program Expert Panel’s definition. Polysomnography and digital tonometry were used to detect obstructive sleep apnea and assess vascular reactivity, respectively. Blood was sampled to measure several oxidative stress markers and adhesion molecules. Results . The frequency of cardiovascular diseases was significantly higher in men (16.4%) than in women (6.1%) (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn>0.001</mml:mn></mml:math>). Body mass index (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mn>25.0</mml:mn><mml:mo>±</mml:mo><mml:mn>4.3</mml:mn></mml:math> vs. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mn>25.8</mml:mn><mml:mo>±</mml:mo><mml:mn>3.13</mml:mn><mml:mtext> </mml:mtext><mml:mtext>kg</mml:mtext><mml:mo>.</mml:mo><mml:msup><mml:mrow><mml:mtext>m</mml:mtext></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math>) and glycaemia (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M6"><mml:mn>94.9</mml:mn><mml:mo>±</mml:mo><mml:mn>16.5</mml:mn></mml:math> vs. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M7"><mml:mn>101.5</mml:mn><mml:mo>±</mml:mo><mml:mn>22.6</mml:mn><mml:mtext> </mml:mtext><mml:mtext>mg</mml:mtext><mml:mo>.</mml:mo><mml:mtext>d</mml:mtext><mml:msup><mml:mrow><mml:mtext>L</mml:mtext></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>) were lower, and High Density Lipoprotein (HDL) (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M8"><mml:mn>74.6</mml:mn><mml:mo>±</mml:mo><mml:mn>17.8</mml:mn></mml:math> vs. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M9"><mml:mn>65.0</mml:mn><mml:mo>±</mml:mo><mml:mn>17.2</mml:mn><mml:mtext> </mml:mtext><mml:mtext>mg</mml:mtext><mml:mo>.</mml:mo><mml:mtext>d</mml:mtext><mml:msup><mml:mrow><mml:mtext>L</mml:mtext></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>) was higher in women compared to men (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M10"><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn>0.05</mml:mn></mml:math>). Oxidative stress was lower in women than in men (uric acid: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M11"><mml:mn>52.05</mml:mn><mml:mo>±</mml:mo><mml:mn>13.78</mml:mn></mml:math> vs. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M12"><mml:mn>59.84</mml:mn><mml:mo>±</mml:mo><mml:mn>13.58</mml:mn></mml:math>, advanced oxidation protein products: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M13"><mml:mn>223</mml:mn><mml:mo>±</mml:mo><mml:mn>94</mml:mn></mml:math> vs. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M14"><mml:mn>246</mml:mn><mml:mo>±</mml:mo><mml:mn>101</mml:mn><mml:mtext> </mml:mtext><mml:mi>μ</mml:mi><mml:mtext>mol</mml:mtext><mml:mo>.</mml:mo><mml:msup><mml:mrow><mml:mtext>L</mml:mtext></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>, malondialdehyde: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M15"><mml:mn>22.44</mml:mn><mml:mo>±</mml:mo><mml:mn>6.81</mml:mn></mml:math> vs. <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M16"><mml:mn>23.88</mml:mn><mml:mo>±</mml:mo><mml:mn>9.74</mml:mn><mml:mtext> </mml:mtext><mml:mtext>nmol</mml:mtext><mml:mo>.</mml:mo><mml:msup><mml:mrow><mml:mtext>L</mml:mtext></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math>). Physical activity was not associated with lower cardiovascular risk factors in both genders. Multivariate analyses showed an independent effect of gender on acid uric (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M17"><mml:mi>β</mml:mi><mml:mo>=</mml:mo><mml:mn>0.182</mml:mn></mml:math>; <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M18"><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn>0.020</mml:mn></mml:math>), advanced oxidation protein products (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M19"><mml:mi>β</mml:mi><mml:mo>=</mml:mo><mml:mn>0.257</mml:mn></mml:math>; <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M20"><mml:mi>p</mml:mi><mml:mo><</mml:mo><mml:mn>0.001</mml:mn></mml:math>), and HDL concentration (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M21"><mml:mi>β</mml:mi><mml:mo>=</mml:mo><mml:mo>−</mml:mo><mml:mn>0.182</mml:mn></mml:math>; <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M22"><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn>0.026</mml:mn></mml:math>). Conclusion . These findings suggest that biochemical cardiovascular risk factors are lower in women than men which could explain the lower cardiovascular disease proportion observed in women in the elderly.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".