Aims: The aim of this study was to determine the optimal allostatic load scoring method.
Design: This is a secondary analysis of data on women of reproductive age from the 2001-2006 National Health and Nutrition Examination Survey.
Methods: We created allostatic load summary scores using five scoring methods including the count-based, Z-Score, logistic regression, factor analysis and grade of membership methods. Then, we examined the predictive performance of each allostatic load summary measure in relation to three outcomes: general health status, diabetes and hypertension.
Results: We found that the allostatic load summary measure by the logistic regression method had the highest predictive validity with respect to the three outcomes. The logistic regression method performed significantly better than the count-based and grade of membership methods for predicting diabetes as well as performed significantly better for predicting hypertension than all of the other methods. But the five scoring methods performed similarly for predicting poor health status.
Conclusion: We recommended the logistic regression method when the outcome information is available, otherwise the frequently used simpler count-based method may be a good alternative.
Impact: The study compared different scoring methods and made recommendations for the optimal scoring approach. We found that allostatic load summary measure by the logistic regression method had the strongest predictive validity with respect to general health status, diabetes and hypertension. The study may provide empirical evidence for future research to use the recommended scoring approach to score allostatic load. The allostatic load index may serve as an 'early warning' indicator for health risk.
目的: 这项研究的目的在于,确定最佳适应负荷评分方法。 设计: 这是对2001年至2006期间全国健康和营养检查调查中育龄妇女数据的二次分析。 方法: 我们使用了五种评分方法(包括基于计数法、Z计分法、逻辑回归法、因子分析法和隶属度方法)来创建了适应负荷汇总分数。然后,我们检查了与三个结果相关的各种适应负荷汇总数值的预测性能:整体健康状态、糖尿病和高血压。 结果: 我们发现,逻辑回归法的适应负荷汇总分数对这三个结果具有最高的预测效度。逻辑回归法在预测糖尿病方面的表现明显优于基于计数法和隶属度方法,在预测高血压方面的表现也明显优于所有其他方法。但这五种评分方法在预测不良健康状态方面的表现相似。 结论: 当结果资料可用时,我们推荐逻辑回归法,在其他方面,常用且更简单的基于计数法可能也是一个不错的选择。 影响: 该研究比较了不同的评分方法,并提出了最佳评分方法的建议。我们发现用逻辑回归法进行的适应负荷汇总分数对整体健康状态、糖尿病和高血压具有最强的预测有效性。该研究可以为今后使用推荐的评分方法对所有适应负荷评分提供实验性证据。适应负荷指数可以作为健康风险的“预警”指标。.
Keywords: allostatic load; nursing; scoring; women of reproductive age.
© 2019 John Wiley & Sons Ltd.