School of Nursing, Inner Mongolia Minzu University, 028000, Tongliao, China.
Micron Intelligent Manufacturing Systems Science and Technology (Beijing) Co., Ltd, 100086, Beijing, China.
BMC Public Health. 2022 Nov 5;22(1):2027. doi: 10.1186/s12889-022-14392-2.
It is difficult to accurately assess the health literacy(HL) level of Mongolians by using Chinese conventional HL questionnaire, due to their particularity in language, culture and living environment. Therefore, it is very important to design an exclusive HL questionnaire for them. In addition, the existing statistical models cannot meet the requirement of HL assessment with high precision, so it is necessary to study a new HL assessment model.
A HL questionnaire with 68 questions is designed by combing the HLS-EU-Q47and the characteristics of Mongolians in China. 742 Mongolians aged 18 to 87 in Inner Mongolia of China answered the questionnaire. A data set with 742 samples is constructed, where each sample has 68 features and 1 target. Based on it, the XGB and LGBM regression models are respectively constructed to assess the HL levels of respondents, and their evaluation effects are compared. The impact of each question on the HL level is quantitatively analyzed by using the feature-importance function in LGBM model to verify the effectiveness of the questionnaire and to find the key factors for affecting HL.
The HL questionnaire has the high reliability, which is reflected by the high internal consistency (Cronbach's coefficient=0.807) and test-retest reliability (Mutual Information Score= 0.803). The validity of the HL questionnaire is obtained by solving KMO and Bartlett Spherical Test Chi-square Value, which are 0.765 and 2486 ([Formula: see text]), respectively. [Formula: see text] index and the absolute error obtained by using the HL assessment model based on LGBM are 0.98347 and 11, which are better than ones by applying the model based-XGB, respectively. The quantitative analysis results show that all 68 questions have influence on HL level, but their degree are different. The first three factors are age, salary level, the judgment ability for the HL information in media, respectively. The HL level distribution of the respondents was 66.71[Formula: see text] excellent, 25.74[Formula: see text] good and 7.54[Formula: see text] poor, respectively.
The presented HL questionnaire with 68 questions and LGBM regression model can obtain the HL level assessment results with high precision for Mongolians in China. The impact of each question in the questionnaire on the final assessment results can be quantified by using the feature-importance function in LGBM model, which is better than the existing qualitative analysis methods.
由于语言、文化和生活环境的特殊性，使用中文常规健康素养问卷难以准确评估蒙古族的健康素养水平。因此，为他们设计专门的健康素养问卷非常重要。此外，现有的统计模型无法满足高精度的健康素养评估要求，因此有必要研究新的健康素养评估模型。
通过结合中国汉族人群的 HLS-EU-Q47 和蒙古族特点，设计了一个包含 68 个问题的健康素养问卷。在中国内蒙古，742 名 18 至 87 岁的蒙古族回答了该问卷。构建了一个包含 742 个样本的数据集，每个样本具有 68 个特征和 1 个目标。在此基础上，分别构建了 XGB 和 LGBM 回归模型来评估受访者的健康素养水平，并比较了它们的评估效果。通过 LGBM 模型中的特征重要性函数对每个问题对健康素养水平的影响进行定量分析，验证问卷的有效性，并找出影响健康素养的关键因素。
健康素养问卷具有较高的可靠性，内部一致性（克朗巴赫系数=0.807）和重测信度（互信息得分=0.803）较高。通过求解 KMO 和 Bartlett 球形检验 Chi-square 值，获得了健康素养问卷的有效性，分别为 0.765 和 2486（[公式：见文本]）。通过基于 LGBM 的健康素养评估模型获得的[公式：见文本]指数和绝对误差分别为 0.98347 和 11，优于基于 XGB 的模型。定量分析结果表明，68 个问题都对健康素养水平有影响，但影响程度不同。前三个因素分别是年龄、工资水平、对媒体中健康素养信息的判断能力。受访者的健康素养水平分布为 66.71%[公式：见文本]优秀、25.74%[公式：见文本]良好和 7.54%[公式：见文本]较差。
本研究提出的包含 68 个问题的健康素养问卷和 LGBM 回归模型，可以为中国蒙古族人群提供高精度的健康素养水平评估结果。通过 LGBM 模型中的特征重要性函数，可以对问卷中每个问题对最终评估结果的影响进行量化，优于现有的定性分析方法。
