Developing subscale threshold scores for the nutrition literacy assessment instrument (NLit).

Discover public health Pub Date : 2025-01-01 Epub Date: 2025-05-28 DOI:10.1186/s12982-025-00677-5
Nicholas J Marchello, Juliana T Camargo, Byron J Gajewski, Debra K Sullivan, Heather D Gibbs
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Abstract

Objective: Understanding a patient's nutrition literacy weaknesses may aid in improving the patient's nutrition literacy and diet quality. The Nutrition Literacy Assessment Instrument (NLit) was developed to fill this knowledge gap. Global NLit cutoff scores were previously developed; however, subscale NLit cutoff scores are needed.

Design: In this secondary analysis, individual post hoc linear regressions were calculated for each NLit subscale to determine scoring thresholds for each NLit subscale. Scoring thresholds were determined for both long- and short-form NLit subscales.

Setting: Two University-affiliated general practice clinics and two University-affiliated safety net clinics were used as recruitment sites.

Participants: Patients (n = 402) with self-reported hyperlipidemia, hypertension, diabetes, or obesity were included in primary analysis from which data in this secondary analysis were derived.

Results: Subscale scores were associated with predicted Healthy Eating Index (HEI)-2010 scores linked to increased risk for mortality. Tenth-percentile NLit scores were associated with HEI-2010 scores between 59.33 and 62.27 (by subscale) for the long-form NLit, and between 60.12 and 61.77 for the short-form NLit.

Conclusions: NLit cutoff scores can pinpoint capacity with nutrition information by subscale. Identifying nutrition literacy deficits may allow nutrition professionals to better focus interventions.

Supplementary information: The online version contains supplementary material available at 10.1186/s12982-025-00677-5.

为营养素养评估工具(NLit)开发子量表阈值分数。
目的:了解患者营养素养的不足,有助于提高患者的营养素养和饮食质量。开发营养素养评估工具(NLit)就是为了填补这一知识空白。以前制定了全球NLit截止分数;然而,需要子尺度NLit的截止分数。设计:在这个次要分析中,计算每个NLit子量表的单独事后线性回归,以确定每个NLit子量表的评分阈值。确定了NLit长、短量表的评分阈值。招募地点:两所大学附属全科诊所和两所大学附属安全网诊所。参与者:自我报告患有高脂血症、高血压、糖尿病或肥胖的患者(n = 402)被纳入初级分析,二级分析的数据来源于此。结果:子量表得分与预测健康饮食指数(HEI)-2010得分相关,与死亡风险增加相关。十百分位NLit分数与HEI-2010分数相关,长形式NLit分数在59.33至62.27之间(按子量表),短形式NLit分数在60.12至61.77之间。结论:NLit的分界点分数可以通过分量表确定营养信息能力。确定营养素养缺陷可以使营养专业人员更好地集中干预措施。补充资料:在线版本包含补充资料,下载地址:10.1186/s12982-025-00677-5。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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