Association between nutrition literacy and physical activity among adults in Bengbu,China
蚌埠市成年人营养素养与身体活动的关系
Abstract
抽象
Background: Physical activity(PA) and rational dietary intake are crucial behavioral factors in chronic disease prevention. Nutrition literacy (NL) serves as a significant determinant of dietary behaviors. This study aims to explore the relationship between NL and PA.
背景: 体力活动 (PA) 和合理饮食摄入是预防慢性病的关键行为因素。营养素养 (NL) 是饮食行为的重要决定因素。本研究旨在探讨 NL 和 PA 之间的关系。
Methods: This cross-sectional study was conducted in Bengbu, China, from May to July 2023. Data were collected through self-reported questionnaires, including demographic information, the International Physical Activity Questionnaire, and the Short-Form Nutrition Literacy Scale. An ordinal logistic regression model was employed to analyze the association between NL and PA, with subgroup analyses also performed.
方法: 这项横断面研究于 2023 年 5 月至 7 月在中国蚌埠进行。数据是通过自我报告的问卷收集的,包括人口统计信息、国际身体活动问卷和简式营养素养量表。采用顺序 logistic 回归模型分析 NL 和 PA 之间的关联,并进行亚组分析。
Results: Participants with higher NL levels showed a significant association with higher PA (OR: 1.63, 95% CI: 1.24-2.14). This association was particularly observed across four dimensions: nutritional knowledge, nutritional understanding, interactive skills, and critical skills. Subgroup analyses revealed that age, residence location, education level, and monthly income significantly influenced the positive correlation between NL and PA.
结果:NL 水平较高的参与者与较高的 PA 呈显著相关性 (OR: 1.63,95% CI: 1.24-2.14)。这种关联在四个维度上特别观察到:营养知识、营养理解、互动技能和关键技能。亚组分析显示,年龄、居住地、教育水平和月收入显著影响 NL 和 PA 之间的正相关。
Conclusion: NL demonstrated a positive correlation with PA, especially in the aspects of nutritional knowledge, nutritional understanding, interactive skills, and critical skills. The correlation between NL and physical activity was influenced by age, residence location, education level, and monthly income. Our findings underscore that NL contributes to enhancing PA levels. To promote human health and prevent diseases, public health practitioners should implement targeted interventions for NL based on specific demographic profiles.
结论:NL 与 PA 呈正相关,尤其是在营养知识、营养理解、互动技能和关键技能方面。NL 与身体活动之间的相关性受年龄、居住地、教育水平和月收入的影响。我们的研究结果强调 NL 有助于提高 PA 水平。为了促进人类健康和预防疾病,公共卫生从业者应根据特定的人口统计特征对 NL 实施有针对性的干预措施。
Introduction
介绍
Chronic diseases pose a serious threat to the health of Chinese residents and have become a major public health issue affecting national economic and social development[1]. Physical inactivity and unhealthy diets are two key risk factors contributing to chronic disease mortality[2]. Improving nutritional literacy and physical activity levels among the population constitutes crucial behavioral factors for chronic disease prevention[3].
慢性病对中国居民的健康构成严重威胁,已成为影响国民经济和社会发展的重大公共卫生问题[1]。缺乏身体活动和不健康的饮食是导致慢性病死亡的两个关键风险因素[2]。提高人群的营养素养和身体活动水平是预防慢性病的关键行为因素[3]。
Physical activity(PA) is defined by the World Health Organization as any bodily movement produced by skeletal muscles that requires energy expenditure[4]. Physical inactivity is one of the leading risk factors for mortality worldwide and a major risk factor for chronic diseases such as cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes[4]. Adequate and regular PA is one of the key strategies for promoting health in adults[5]. Among adults and older adults, PA can reduce the risk of cancer and chronic diseases. It also improves bone health and cognitive development in children and adolescents. For physically inactive individuals, even small increases in PA provide health benefits[6]. Additionally, it helps reduce obesity risk, promotes physical and mental well-being, and alleviates symptoms of depression and anxiety[7]. However, despite the numerous benefits of regular PA for adults, most people fail to engage in it regularly and adequately[8]. The 2020 WHO guidelines recommend that adults should perform 150-300 minutes of moderate-intensity PA per week, or 75-150 minutes of vigorous-intensity PA[9]. A recent study indicates that nearly one-third (31%) of the global adult population (1.8 billion adults) are physically inactive[10].Adult PA levels are influenced by various socio-demographic characteristics and health conditions, such as educational level, age, employment status, and chronic diseases[11]. Another significant factor affecting PA levels is health literacy (HL)[12,13,14].
世界卫生组织将体能活动 (PA) 定义为骨骼肌产生的任何需要消耗能量的身体运动 [4]。 缺乏身体活动是全球死亡的主要风险因素之一,也是心血管疾病、癌症、慢性呼吸系统疾病和糖尿病等慢性疾病的主要风险因素 [4]。 充足和定期的 PA 是促进成人健康的关键策略之一 [5]。 在成人和老年人中,PA 可以降低患癌症和慢性病的风险。它还可以改善儿童和青少年的骨骼健康和认知发展。对于缺乏身体活动的个体,即使 PA 的小幅增加也能对健康有益 [6]。 此外,它还有助于降低肥胖风险,促进身心健康,并缓解抑郁和焦虑症状 [7]。 然而,尽管常规 PA 对成人有很多好处,但大多数人未能定期和充分地参与其中 [8]。2020 年 WHO 指南建议,成人应每周进行 150-300 分钟的中等强度 PA,或 75-150 分钟的高强度 PA[9]。 最近的一项研究表明,全球近三分之一 (31%) 的成年人口(18 亿成年人)缺乏身体活动 [10]。 成人 PA 水平受各种社会人口学特征和健康状况的影响,例如教育水平、年龄、就业状况和慢性病 [11]。 影响 PA 水平的另一个重要因素是健康素养 (HL)[12,13,14]。
Nutrition literacy (NL), a specialized form of HL[15], is defined as the ability to acquire, comprehend, analyze, and apply relevant nutritional information to make informed dietary decisions[16]. Nutrition and health are closely interrelated, with healthy eating habits contributing to disease prevention[17]. Some research findings indicate a significant positive correlation between high HL and high levels of PA[12]. However, to date, no studies have reported the association between NL and PA. Therefore, investigating the relationship between NL and PA status among adults may facilitate the development of effective strategies to promote nutritional health in adult populations.
营养素养 (NL) 是 HL 的一种特殊形式 [15],被定义为获取、理解、分析和应用相关营养信息以做出明智饮食决策的能力 [16]。 营养和健康密切相关,健康的饮食习惯有助于预防疾病 [17]。 一些研究结果表明,高 HL 与高水平 PA 之间存在显著的正相关 [12]。 然而,迄今为止,还没有研究报告 NL 和 PA 之间的关联。因此,调查成人 NL 和 PA 状态之间的关系可能有助于制定促进成人营养健康的有效策略。
2.Methods
2.方法
2.1 Study Design and Participants
2.1 研究设计和参与者
This cross-sectional investigation was conducted from May to July 2023 in Bengbu, Anhui Province, China, with the objective of examining the relationship between NL and PA.The survey employed a multistage random sampling strategy, stratified by urban-rural location, to select participants. In the initial stage of the sampling procedure, two urban areas and two rural counties within Bengbu City were selected using a random sampling method. In the subsequent stage, two streets and two townships/villages within the two selected urban areas and rural counties were randomly selected as specific sampling sites. In the third stage, 110 households were randomly selected from these streets and townships/villages, and all eligible members of these households were included in the study.The inclusion criteria for study participants were as follows: (1) a minimum age of 18 years, (2) the capacity for normal communication without verbal communication barriers, and (3) a lack of prior training in nutrition or food knowledge.All participants voluntarily engaged in the study and provided written informed consent. Investigators were uniformly trained and conducted face-to-face interviews to obtain survey data according to standardized procedures. The study was approved by the Ethics Committee of Bengbu Medical University.A total of 2,279 samples were collected in this study, 177 participants were excluded due to incomplete data on NL, age, BMI, and PA, and the final 2,102 samples were included in the study with an efficiency rate of 92.23%.
这项横断面调查于 2023 年 5 月至 7 月在中国安徽省蚌埠市进行,目的是研究 NL 和 PA 之间的关系。该调查采用多阶段随机抽样策略,按城乡位置分层,以选择参与者。在抽样程序的初始阶段,使用随机抽样方法选择了蚌埠市内的两个城市地区和两个农村县。在后续阶段,随机选取两个选定城区和农村县内的 2 个街道和 2 个乡/村作为具体采样点。在第三阶段,从这些街道和乡镇/村庄中随机选择 110 户,这些家庭中所有符合条件的成员都被纳入研究。研究参与者的纳入标准如下:(1) 最低年龄为 18 岁,(2) 没有口头交流障碍的正常沟通能力,以及 (3) 缺乏营养或食品知识方面的先前培训。所有参与者都自愿参与研究并提供书面知情同意书。调查人员接受统一培训,并根据标准化程序进行面对面访谈以获取调查数据。本研究共收集 2,279 份样本,因 NL、年龄、BMI 和 PA 数据不完整而被排除在 177 名参与者之外,最终 2,102 份样本被纳入研究,有效率为 92.23%。
2.2 Assessment of NL
2.2 无限注
The 12-item Short-Form Nutritional Literacy Scale (NL-SF12) was utilized in this study to assess participants' levels of NL. The scale was developed based on an original 43-item scale used to assess NL in adults and validated in a previous study.The NL-SF12 scale is composed of two primary domains and six dimensions: two domains of Nutritional Cognition (4 items) and Nutritional Skills (8 items), and six domains of Knowledge, Understanding, Obtaining Skills, Apply Skills, Interactive Skills, and Critical Skills, with a total of 12 items.Each item was evaluated using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The total score was determined by summing the scores for each domain and the total scores, with higher scores indicating higher levels of NL.In this study, NL levels were categorized into four quartiles: Q1 (low level), Q2 (low-moderate level), Q3 (high-moderate level), and Q4 (high level).The NL-SF12 scale demonstrated high internal consistency (Cronbach's a value of 0.881) in this study, suggesting that its items effectively encompass all dimensions of NL.
本研究使用 12 项短式营养素养量表 (NL-SF12) 来评估参与者的 NL 水平。该量表是根据用于评估成人 NL 的原始 43 项量表开发的,并在之前的研究中得到验证。NL-SF12 量表由两个主要领域和六个维度组成:营养认知(4 项)和营养技能(8 项)两个领域,以及知识、理解、获得技能、应用技能、互动技能和关键技能六个领域,共 12 个项目。每个项目都使用 5 点李克特量表进行评估,范围从 1(非常不同意)到 5(非常同意)。总分是通过将每个领域的分数和总分相加来确定的,分数越高表示水平越高 NL.In 本研究将 NL 水平分为四个四分位数:Q1(低水平)、Q2(中低水平)、Q3(中高水平)和 Q4(高水平)。NL-SF12 量表在本研究中表现出高度的内部一致性 (Cronbach 的值为 0.881),表明其项目有效地涵盖了 NL 的所有维度。
2.3 Assessment of PA
2.3 PA 的 A session
This study employed the Chinese version of the International Physical Activity Questionnaire Short Form (IPAQ-SF) to assess participants' PA levels, which has been validated with a test-retest reliability coefficient ranging from 0.71 to 0.93[18,19].Participants were asked to report their physical activity levels over the past 7 days. The first six questions of the IPAQ-SF inquired about three specific types of activities:walking, moderate-intensity, and vigorous-intensity over the past 7 days, as well as the specific number of days and time (in minutes) spent on these activities. The last question inquired about the time spent sitting. According to the criteria and data processing principles provided in the IPAQ scoring protocol[20]. If an individual reports more than 960 minutes of PA across three intensity levels, they will be excluded from the analysis. For any intensity level where the cumulative daily activity time is less than 10 minutes, both the time and corresponding weekly frequency should be recoded as "0". Additionally, if the daily duration of a specific intensity physical activity exceeds 3 hours, it should be recoded as 180 minutes. In the IPAQ-SF, metabolic equivalents (METs) are used to measure the intensity of PA, with one MET defined as the oxygen consumption at rest. walking is set at 3.3 METs, moderate-intensity PA at 4 METs, and vigorous-intensity PA at 8 METs. The weekly level of an individual engaged in PA of a certain intensity is calculated as the corresponding MET value of the PA × daily time (min/d) × weekly frequency (d/w).
本研究采用中文版国际体力活动问卷简表 (IPAQ-SF) 来评估参与者的 PA 水平,该水平已通过 0.71 至 0.93 的重测信度系数验证 [18,19]。 参与者被要求报告他们在过去 7 天内的身体活动水平。IPAQ-SF 的前六个问题询问了过去 7 天内三种特定类型的活动 : 步行、中等强度和高强度 , 以及在这些活动上花费的具体天数和时间(以分钟为单位)。最后一个问题是关于坐着的时间。根据 IPAQ 评分协议中提供的标准和数据处理原则 [20]。 如果一个人报告在三个强度水平上超过 960 分钟的 PA,他们将被排除在分析之外。 对于每日累计活动时间少于 10 分钟的任何强度级别,时间和相应的每周频率都应重新编码为“0”。 此外,如果特定强度的体能活动的每日持续时间超过 3 小时,则应重新编码为 180 分钟。 在 IPAQ-SF 中,代谢当量 (MET) 用于测量 PA 的强度 ,其中 1 MET 定义为静息时的耗氧量。步行设置为 3.3 MET,中等强度 PA 为 4 MET,高强度 PA 为 8 MET。 从事一定强度的 PA 的个人的每周水平计算为 PA ×每日时间 (min/d) ×每周频率 (d/w) 的相应 MET 值。
The weekly MET value is calculated using the following formula:
每周 MET 值使用以下公式计算:
Walking PA = 3.3METs×min×days,
步行 PA = 3.3METs×min×days,
Moderate PA = 4METs×min×days, and
中度 PA = 4METs×min×days,并且
Vigorous PA = 8METs×min× days.
强劲的 PA = 8METs×min× 天。
Overall, based on participants' weekly PA frequency, intensity, and metabolic syndrome, they were categorized into three PA levels .
总体而言,根据参与者每周的 PA 频率、强度和代谢综合征,他们被分为三个 PA 级别。
High-level PA (HPA) requires meeting any one of the following two criteria:
高级别 PA (HPA) 需要满足以下两个标准中的任何一个:
the sum of three intensity levels of physical activity is greater than or equal to 7 days, with a total weekly PA of greater than or equal to 3,000 MET-min/w. HPA totals more than 3 days, with an overall weekly PA level of greater than or equal to 1,500 MET-min/w.
身体活动的三个强度水平之和大于或等于 7 天,每周总 PA 大于或等于 3,000 MET-min/w。HPA 总计超过 3 天,每周总体 PA 水平大于或等于 1,500 MET-min/w。
Moderate-level PA (MPA) requires meeting any one of the following three criteria:
中度 PA (MPA) 需要满足以下三个标准中的任何一个:
At least 20 minutes of high-intensity PA per day, totaling 3 or more days; at least 30 minutes of moderate-intensity PA and/or walking per day, totaling 5 or more days; a combination of three intensities of PA totaling 5 or more days, with a total weekly PA level of 600 MET-min/w or more.
每天至少 20 分钟的高强度 PA,共 3 天或更长时间;每天至少 30 分钟的中等强度 PA 和/或步行,共 5 天或更长时间;三种强度的 PA 的组合,总计 5 天或更长时间,每周总 PA 水平为 600 MET-min/w 或更高。
Low-level PA (LPA):
低水平 PA (LPA):
Participants who do not meet the above two levels (HPA or MPA) are included in this group.
未达到上述两个级别(HPA 或 MPA)的参与者被纳入该组。
2.4 Other variables
2.4 其他变量
To ensure the reliability of the results and to maximally control for the influence of confounding factors, the statistical model was adjusted for factors such as demographic characteristics, lifestyle, and health status. Demographic characteristics include: age (18-44, 45-64, or 65+), sex (male or female), residence types (urban or rural), marital status (married and others (unmarried,divorced or widowed), educational level (primary school or below, junior high school or above), occupation (farmer, separated/retired staff and others), monthly income (<1000RMB, 1000-3000RMB and >3000RMB), smoking status (never smoker, former smoker, and current smoker), drinking status (never drinker, former drinker and current drinker), BMI(underweight (<18.5kg/m²), normal (18.5-23.9kg/m²), overweight (24-27.9kg/m²), or obese (≥28kg/m²)) and chronic disease status (yes (suffering from any one or more of hypertension, diabetes, cardiovascular disease, osteoporosis, dyslipidaemia, arthritis, rheumatism, lumbar spine disease, cancer, etc.) or no).
为了确保结果的可靠性并最大限度地控制混杂因素的影响,统计模型根据人口统计学特征、生活方式和健康状况等因素进行了调整。人口特征包括:年龄(18-44 岁、45-64 岁或 65 岁+)、 性别 (男性或女性)、 居住类型 (城市或农村)、婚姻状况(已婚及其他 ( 未婚 、离婚或丧偶 )、教育程度(小学及以下、初中或以上)、职业(农民、离职/退休人员等)、 月收入 (x3C1000RMB、1000-3000 元和 x3E3000 元)、 吸烟状况(从不吸烟 、 以前吸烟 、 现在吸烟)、饮酒状况(从不吸烟 、 以前饮酒和现在饮酒)、BMI(体重不足(x3C18.5kg/m²)、正常(18.5-23.9kg/m²)、超重(24-27.9kg/m²)或肥胖(≥28kg/m²)) 和慢性疾病状态(是(患有高血压、糖尿病、心血管疾病、骨质疏松症、血脂异常 A 血症、关节炎、风湿病、腰椎疾病、癌症等)或否)。
2.5 Statistical analysis
2.5 统计分析
Descriptive statistics were expressed as frequencies and percentages for categorical variables. The chi-square test was performed to compare the correlation between NL levels and physical activity levels in each subgroup based on demographic characteristics. Multinomial logistic regression models were used to access the correlation between NL and physical activity by calculating the odds ratios (OR) and 95% confidence intervals (CI). The variations in the associations of overall NL with physical activity were determined by subgroup analyses by age, BMI, sex, residence types, education levels, occupation types, marital status, chronic disease status, monthly incomes, smoking status, and drinking status. Data were analyzed using SPSS 27.0 and a P value of <0.05 was considered statistically significant.
描述性统计表示为分类变量的频率和百分比。 进行卡方检验,根据人口统计学特征比较每个亚组 NL 水平与体力活动水平之间的相关性。使用多项式 logistic 回归模型通过 计算比值比 (OR) 和 95% 置信区间 (CI) 来了解 NL 与身体活动之间的相关性。 总体 NL 与身体活动关联的变化是通过年龄、BMI、 性别 、居住类型 、教育水平 s、职业类型 s、婚姻状况、慢性病状况、月收入 s、吸烟状况和饮酒状况的亚组分析确定的。 使用 SPSS 27.0 分析数据,% 3C0.05 的 P 值被认为具有统计学意义。
3.Results
3.结果
3.1Participant characteristics
3.1参与者特征
Table 1 presents the fundamental characteristics of the study population. A total of 2,102 participants were included in this study, with the proportions of low LPA, MPA, HPA being 20.6%, 42.6%, and 36.8%, respectively.Participants aged >65 constituted 51.8% of the sample, while females represented 60.7%. Urban residents accounted for 47.7%, 77.8% were married, 29.0% were farmers and obese individuals constituted 17.4%. Furthermore, more than half of the participants had received junior high school education or above (53.2%).Approximately one-third had a monthly income > 3,000 RMB (30.8%).Over half were never smoker (72.1%) or never drinker (63.4%), and a significant majority suffered from chronic diseases (70.8%).
表 1 显示了研究人群的基本特征。本研究共纳入 2,102 名参与者,低 LPA、MPA、HPA 的比例分别为 20.6%、42.6% 和 36.8%。%3E65 岁的参与者占样本 的 51.8%, 而女性占 60.7%。城市居民占 47.7%, 已婚占 77.8%,农民占 29.0%, 肥胖者占 17.4%。 此外,超过一半的参与者接受过初中或以上教育 (53.2%)。大约三分之一的受访者月收入 > 3,000 元人民币 (30.8%)。超过一半的人从不吸烟 (72.1%) 或从不饮酒 (63.4%),绝大多数人患有慢性疾病 (70.8%)。
3.2Associations between NL levels and physical activity
3.2NL 水平与身体活动之间的关联
Table 2 illustrates the correlation between NL and PA,The highest proportion of individuals exhibiting HPA is found among those in the highest quartile of NL levels.This correlation is consistent across two NL domains and six NL dimensions.
表 2 说明了 NL 和 PA 之间的相关性,在 NL 水平最高四分位数的个体中,表现出 HPA 的个体比例最高。这种相关性在 2 个 NL 域和 6 个 NL 维度中是一致的。
Table 3 presents the logistic regression results of the correlation between NL and PA. After adjusting for all covariates revealed that participants with total NL levels in the highest quartile had higher odds of engaging in HPA (OR: 1.63, 95% CI: 1.24-2.14). Furthermore, this correlation was applicable in nutrition skills (OR: 1.59, 95% CI: 1.21-2.08) and nutrition cognition (OR: 1.40, 95% CI: 1.08-1.82), including interactive skills (OR: 1.52, 95% CI: 1.19-1.92), critical skills (OR: 1.65, 95% CI: 1.27-2.14), knowledge (OR: 1.49, 95% CI: 1.16-1.91), and understanding (OR: 1.41, 95% CI: 1.01-1.97). However, no differences were found in the dimensions of obtaining skills and applying skills.
表 3 显示了 NL 和 PA 之间相关性的 logistic 回归结果。在调整所有协变量后,发现总 NL 水平在最高四分位数的参与者参与 HPA 的几率更高 (OR: 1.63, 95% CI: 1.24-2.14)。此外,这种相关性适用于营养技能(OR:1.59,95% CI:1.21-2.08)和营养认知(OR:1.40,95% CI:1.08-1.82),包括互动技能(OR:1.52,95% CI:1.19-1.92)、关键技能(OR:1.65,95% CI:1.27-2.14)、知识(OR:1.49,95% CI:1.16-1.91)和理解(OR:1.41,95% CI:1.01-1.97)。然而,在获得技能和应用技能的维度上没有发现差异。
3.3Subgroup analysis
3.3亚组分析
Table 4 illustrates the association between NL and PA levels in the subgroups. The upper quartile of NL were significantly associated with HPA in participants aged 65+ (OR:1.72,95%CI:1.18-2.52), urban areas (OR: 1.72, 95% CI: 1.12-2.62), with junior high school education or above (OR: 1.83, 95% CI: 1.19-2.84), with a monthly income < 1000RMB (OR: 1.81, 95% CI: 1.09-3.00). But not in under 65 years of age, rural areas, primary school education or less and monthly income >1000 RMB.
表 4 说明了子组中 NL 和 PA 水平之间的关联。65+ (OR: 1.72,95% CI:1.18-2.52)、城市地区 (OR: 1.72,95% CI: 1.12-2.62)、初中及以上学历 (OR: 1.83, 95% CI: 1.19-2.84)、月收入 < 1000RMB (OR: 1.81, 95% CI: 1.09-3.00) 的参与者,NL 的上四分位数与 HPA 显著相关。但年龄不满 65 周岁、农村地区、小学以上文化程度及以下且月收入>1000 元。
Table 1 Characteristics of the study population.
表 1 研究人群的特征。
Variable | N (%) | LPA(%) | MPA(%) | HPA(%) | 2 | P-value |
Total | 2102(100.0) | 433(20.6) | 896(42.6) | 773(36.8) | ||
Age | 48.652 | <0.001 | ||||
18-44 45-64 65+ | 360(17.1) 654(31.1) 1088(51.8) | 97(22.4) 102(23.6) 234(54.0) | 160(17.9) 246(27.5) 490(54.7) | 103(13.3) 306(39.6) 364(47.1) | ||
Sex Male Female | 826(39.3) 1276(60.7) | 134(30.9) 299(69.1) | 356(39.7) 540(60.3) | 336(43.5) 437(56.5) | 18.362 | <0.001 |
Residence | 49.761 | <0.001 | ||||
Urban | 1002(47.7) | 155(35.8) | 499(55.7) | 348(45.0) | ||
Rural | 1100(52.3) | 278(64.2) | 397(44.3) | 425(55.0) | ||
Marital status | 25.609 | <0.001 | ||||
Married | 1636(77.8) | 330(76.2) | 659(73.5) | 647(83.7) | ||
Other | 466(22.2) | 103(23.8) | 237(26.5) | 126(16.3) | ||
Education | 27.103 | <0.001 | ||||
Primary school and below | 984(46.8) | 249(57.5) | 380(42.4) | 355(45.9) | ||
Junior high school and above | 1118(53.2) | 184(42.5) | 516(57.6) | 418(54.1) | ||
Type of occupation | 54.251 | <0.001 | ||||
Farmers | 610(29.0) | 149(34.4) | 196(21.9) | 265(34.3) | ||
Separated/retired staff | 710(33.8) | 105(24.2) | 356(39.7) | 249(32.2) | ||
Other | 782(37.2) | 179(41.3) | 344(38.4) | 259(33.5) | ||
Monthly income | 39.530 | <0.001 | ||||
<1000 RMB | 804(38.2) | 207(47.8) | 330(36.8) | 267(34.5) | ||
1000-3000 RMB | 651(31.0) | 104(24.0) | 257(28.7) | 290(37.5) | ||
>3000 RMB | 647(30.8) | 122(28.2) | 309(34.5) | 216(27.9) | ||
Smoking status | 11.433 | 0.022 | ||||
Never smoker | 1515(72.1) | 334(77.1) | 640(71.4) | 541(70.0) | ||
Former smoker | 195(9.3) | 37(8.5) | 92(10.3) | 66(8.5) | ||
Current smoker | 392(18.6) | 62(14.3) | 164(18.3) | 166(21.5) | ||
Drinking status | 6.244 | 0.182 | ||||
Never drinker | 1333(63.4) | 294(67.9) | 568(63.4) | 471(60.9) | ||
Former drinker | 241(11.5) | 47(10.9) | 101(11.3) | 93(12.0) | ||
Current drinker | 528(25.1) | 92(21.2) | 227(25.3) | 209(27.0) | ||
BMI | 9.177 | 0.164 | ||||
<18.5 kg/m2 | 57(2.7) | 12(2.8) | 30(3.3) | 15(1.9) | ||
18.5-23.9 kg/m2 | 845(40.2) | 188(43.4) | 356(39.7) | 301(38.9) | ||
24-27.9 kg/m2 | 834(39.7) | 152(35.1) | 353(39.4) | 329(42.6) | ||
≥28 kg/m2 | 366(17.4) | 81(18.7) | 157(17.5) | 128(16.6) | ||
Chronic diseases status | 2.610 | 0.271 | ||||
Yes | 1489(70.8) | 317(73.2) | 639(71.3) | 533(69.0) | ||
No | 613(29.2) | 116(26.8) | 257(28.7) | 240(31.0) |
Table 2 Correlation between nutrition literacy and physical activity
表 2 营养素养与身体活动之间的相关性.
variable | N(%) | LPA(%) | MPA(%) | HPA(%) | 2 | P-value |
Nutrition literacy | 32.391 | <0.001 | ||||
Q1 | 501(23.8) | 130(30.0) | 191(21.3) | 180(23.3) | ||
Q2 | 523(24.9) | 124(28.6) | 228(25.4) | 171(22.1) | ||
Q3 | 530(25.2) | 104(24.0) | 235(26.2) | 191(24.7) | ||
Q4 | 548(26.1) | 75(17.3) | 242(27.0) | 231(29.9) | ||
Nutrition cognition | 17.799 | 0.007 | ||||
Q1 | 438(20.8) | 118(27.3) | 170(19.0) | 150(19.4) | ||
Q2 | 479(22.8) | 103(23.8) | 209(23.3) | 167(21.6) | ||
Q3 | 436(20.7) | 83(19.2) | 191(21.3) | 162(21.0) | ||
Q4 | 749(35.6) | 129(29.8) | 326(36.4) | 294(38.0) | ||
Nutrition skills | 46.431 | <0.001 | ||||
Q1 | 490(23.3) | 124(28.6) | 182(20.3) | 184(23.3) | ||
Q2 | 525(25.0) | 125(28.9) | 227(25.3) | 173(22.4) | ||
Q3 | 551(26.2) | 119(27.5) | 255(28.5) | 177(22.9) | ||
Q4 | 536(25.5) | 65(15.0) | 232(25.9) | 239(30.9) | ||
Knowledge | 21.687 | <0.001 | ||||
Q1 | 397(18.9) | 107(24.7) | 150(16.7) | 140(18.1) | ||
Q2 | 269(12.8) | 58(13.4) | 120(13.4) | 91(11.8) | ||
Q3 | 766(36.4) | 162(37.4) | 332(37.1) | 272(35.2) | ||
Q4 | 670(31.9) | 106(24.5) | 294(33.8) | 270(34.9) | ||
Understanding | 20.545 | 0.002 | ||||
Q1 | 208(9.9) | 62(14.3) | 75(8.4) | 71(9.2) | ||
Q2 | 576(27.4) | 130(30.0) | 248(27.7) | 198(25.6) | ||
Q3 | 601(28.6) | 112(25.9) | 274(30.6) | 215(27.8) | ||
Q4 | 717(34.1) | 129(29.8) | 299(33.4) | 289(37.4) | ||
Obtaining skills | 23.231 | <0.001 | ||||
Q1 | 331(15.7) | 78(18.0) | 125(14.0) | 128(16.6) | ||
Q2 | 703(33.4) | 171(39.5) | 297(33.1) | 235(30.4) | ||
Q3 | 356(16.9) | 73(16.9) | 161(18.0) | 122(15.8) | ||
Q4 | 712(33.9) | 111(25.6) | 313(34.9) | 288(37.3) | ||
Applying skills | 17.214 | 0.009 | ||||
Q1 | 366(17.4) | 85(19.9) | 130(14.5) | 151(19.5) | ||
Q2 | 490(23.3) | 118(27.3) | 205(22.9) | 167(21.6) | ||
Q3 | 326(15.5) | 67(15.5) | 145(16.2) | 114(14.7) | ||
Q4 | 920(43.8) | 163(37.6) | 416(46.4) | 341(44.1) | ||
Interactive skills | 25.278 | <0.001 | ||||
Q1 | 387(18.4) | 107(24.7) | 153(17.1) | 127(16.4) | ||
Q2 | 487(23.2) | 108(24.9) | 210(23.4) | 169(21.9) | ||
Q3 | 370(17.6) | 81(18.7) | 156(17.4) | 133(17.2) | ||
Q4 | 858(40.8) | 137(31.6) | 377(42.1) | 344(44.5) | ||
Critical skills | 33.448 | <0.001 | ||||
Q1 | 429(20.4) | 116(26.8) | 166(18.5) | 147(19.0) | ||
Q2 | 203(9.7) | 41(9.5) | 95(10.6) | 67(8.7) | ||
Q3 | 927(44.1) | 201(46.4) | 404(45.1) | 322(41.7) | ||
Q4 | 543(25.8) | 75(17.3) | 231(25.8) | 237(30.7) |
Table 3 Logistic regression modelling for nutrition literacy and physical activity (Regression coefficient with their standard errors; odds ratios and 95 % confidence intervals)
Table 3 营养素养和身体活动的 Logistic 回归模型 (回归系数及其标准误差;比值比和 95 % 置信区间)
Variable | Physical activity | ||||
B | SE | OR | 95%CI | P-value | |
Nutrition literacy (Q1) | |||||
Q2 | -0.06 | 0.12 | 0.94 | 0.75,1.19 | 0.63 |
Q3 | 0.08 | 0.13 | 1.08 | 0.84,1.40 | 0.55 |
Q4 | 0.49 | 0.14 | 1.63 | 1.24,2.14 | <0.001 |
Nutrition cognition (Q1) | |||||
Q2 | 0.07 | 0.13 | 1.07 | 0.83,1.37 | 0.61 |
Q3 | 0.14 | 0.14 | 1.15 | 0.88,1.50 | 0.30 |
Q4 | 0.34 | 0.13 | 1.40 | 1.08,1.82 | 0.02 |
Nutrition skills (Q1) | |||||
Q2 | -0.12 | 0.12 | 0.89 | 0.70,1.13 | 0.34 |
Q3 | -0.15 | 0.13 | 0.86 | 0.67,1.11 | 0.24 |
Q4 | 0.46 | 0.14 | 1.59 | 1.21,2.08 | <0.001 |
Knowledge (Q1) | |||||
Q2 | 0.07 | 0.15 | 1.07 | 0.80,1.44 | 0.65 |
Q3 | 0.12 | 0.12 | 1.13 | 0.89,1.43 | 0.33 |
Q4 | 0.40 | 0.13 | 1.49 | 1.16,1.91 | 0.002 |
Understanding (Q1) | |||||
Q2 | 0.05 | 0.16 | 1.05 | 0.77,1.43 | 0.74 |
Q3 | 0.15 | 0.16 | 1.16 | 0.84,1.59 | 0.38 |
Q4 | 0.34 | 0.17 | 1.41 | 1.01,1.97 | 0.04 |
Obtaining skills (Q1) | |||||
Q2 | -0.23 | 0.13 | 0.80 | 0.62,1.03 | 0.08 |
Q3 | -0.15 | 0.15 | 0.86 | 0.64,1.17 | 0.34 |
Q4 | 0.13 | 0.14 | 1.14 | 0.86,1.51 | 0.36 |
Applying skills (Q1) | |||||
Q2 | -0.26 | 0.13 | 0.77 | 0.60,1.00 | 0.05 |
Q3 | -0.19 | 0.15 | 0.83 | 0.62,1.11 | 0.20 |
Q4 | -0.10 | 0.13 | 0.91 | 0.71,1.17 | 0.45 |
Interactive skills (Q1) | |||||
Q2 | 0.14 | 0.13 | 1.15 | 0.89,1.48 | 0.28 |
Q3 | 0.16 | 0.14 | 1.18 | 0.89,1.55 | 0.25 |
Q4 | 0.42 | 0.12 | 1.52 | 1.19,1.92 | <0.001 |
Critical skills (Q1) | |||||
Q2 | 0.05 | 0.16 | 1.05 | 0.77,1.44 | 0.76 |
Q3 | 0.06 | 0.12 | 1.06 | 0.85,1.33 | 0.60 |
Q4 | 0.50 | 0.13 | 1.65 | 1.27,2.14 | <0.001 |
B: regression coefficient. The results are adjusted for age, sex, residential location type, marital status, education level, occupation, monthly income, smoking status, drinking status, BMI and chronic diseases
B:回归系数。结果根据年龄、性别、居住地类型、婚姻状况、教育水平、职业、月收入、吸烟状况、饮酒状况、BMI 和慢性疾病进行调整.
Table 4 Results of subgroup analyses for the correlation of nutrition literacy with physical activity.
表 4 营养素养与身体活动相关性的亚组分析结果。
subgroups | Variables | OR(95%CI) | P-value |
Age | |||
18-44 | Nutrition literacy(Q1) | ||
Q2 | 1.15(0.32-4.07) | 0.83 | |
Q3 | 1.05(0.30-3.66) | 0.94 | |
Q4 | 1.90(0.55-6.50) | 0.31 | |
45-64 | Nutrition literacy(Q1) | ||
Q2 | 0.73(0.46-1.15) | 0.17 | |
Q3 | 1.22(0.77-1.95) | 0.40 | |
Q4 | 1.44(0.87-2.37) | 0.15 | |
65+ | Nutrition literacy(Q1) | ||
Q2 | 1.03(0.77-1.38) | 0.85 | |
Q3 | 0.99(0.70-1.39) | 0.94 | |
Q4 | 1.72(1.18-2.52) | 0.005 | |
Q3 | 1.12(0.80-1.57) | 0.51 | |
Q4 | 1.69(1.18-2.41) | 0.004 | |
Residence | |||
Urban | Nutrition literacy(Q1) | ||
Q2 | 0.87(0.56-1.34) | 0.53 | |
Q3 | 1.00(0.66-1.51) | 0.98 | |
Q4 | 1.72(1.12-2.62) | 0.01 | |
Rural | Nutrition literacy(Q1) | ||
Q2 | 0.94(0.71-1.25) | 0.67 | |
Q3 | 1.08(0.77-1.52) | 0.65 | |
Q4 | 1.46(0.98-2.16) | 0.06 | |
Education | |||
Primary school and below | Nutrition literacy(Q1) | ||
Q2 | 0.86(0.65-1.13) | 0.27 | |
Q3 | 1.29(0.90-1.84) | 0.17 | |
Q4 | 1.46(0.94-2.27) | 0.10 | |
Junior high school and above | Nutrition literacy(Q1) | ||
Q2 | 1.16(0.73-1.85) | 0.53 | |
Q3 | 1.00(0.65-1.54) | 1.00 | |
Q4 | 1.83(1.19-2.84) | 0.006 | |
Monthly income | |||
<1000 RMB | Nutrition literacy(Q1) | ||
Q2 | 0.93(0.69-1.27) | 0.66 | |
Q3 | 1.27(0.85-1.90) | 0.24 | |
Q4 | 1.81(1.09-3.00) | 0.02 | |
1000-3000 RMB | Nutrition literacy(Q1) | ||
Q2 | 1.32(0.81-2.13) | 0.26 | |
Q3 | 0.91(0.57-1.45) | 0.68 | |
Q4 | 1.63(1.00-2.69) | 0.06 | |
>3000 RMB | Nutrition literacy(Q1) | ||
Q2 | 0.63(0.34-1.18) | 0.15 | |
Q3 | 0.97(0.54-1.75) | 0.92 | |
Q4 | 1.38(0.77-2.49) | 0.28 |
4 Discussion
4 讨论
This study is the first to investigate the associations between NL and PA among adults in Bengbu, China. The results revealed that adults with higher NL levels had greater odds of engaging in HPA. In recent years, NL has become a research hotspot in academia. However, to our knowledge, no studies have reported the association between NL and PA. This finding suggests that improving NL may help enhance PA levels and promote human health.
这项研究首次调查了中国蚌埠市成年人 NL 和 PA 之间的关联 。结果显示,NL 水平较高的成年人参与 HPA 的几率更大 。近年来,NL 已成为学术界的研究热点。然而,据我们所知,没有研究报告 NL 和 PA 之间的关联 。这一发现表明,改善 NL 可能有助于提高 PA 水平并促进人类健康。
In this study, we identified a positive correlation between adult NL and PA. This finding is supported by other research, indicating that participants with adequate NL levels are more likely to engage in PA compared to those with lower NL levels[21]. Adults with higher NL levels tend to exhibit healthier dietary behaviors and lifestyles, characterized by factors such as increased protein intake and regular PA[22,23]. Several prior studies have reported a positive association between protein consumption and PA levels [24,25,26], with high-protein diets providing the metabolic foundation for HPA[27]. Furthermore, although current research directly examining the correlation between adults' NL and PA remains limited, it is noteworthy that NL represents a specialized form of HL. The relationship between HL and PA has been extensively studied, with numerous empirical studies demonstrating a significant positive correlation between higher HL levels and HPA among healthy adults[12,13]. This provides indirect evidence supporting the association investigated in this study. Improving NL levels may potentially encourage adults to engage in HPA.
在这项研究中,我们确定了成人 NL 和 PA 之间的正相关 。这一发现得到了其他研究的支持,表明与 NL 水平较低的参与者相比,具有足够 NL 水平的参与者更有可能参与 PA[21]。NL 水平较高的成年人往往表现出更健康的饮食行为和生活方式,其特征是蛋白质摄入量增加和定期 PA 等因素 [22,23]。 先前的几项研究报道了蛋白质消耗与 PA 水平之间呈正相关 [2, 4,2, 5,2, 6],高蛋白饮食为 HPA 提供了代谢基础 [27]。 此外,尽管目前直接检查成人 NL 和 PA 之间相关性的研究 仍然有限,但值得注意的是,NL 代表了 HL 的一种特殊形式 。HL 和 PA 之间的关系已被广泛研究,大量实证研究表明 , 在健康成人中 ,较高的 HL 水平与 HPA 之间存在显著的正相关 [12,13]。 这提供了间接证据支持本研究中调查的关联。提高 NL 水平可能会鼓励成年人参与 HPA。
This study further explored the relationship between the two domains and six dimensions of NL and PA in individuals,The results indicated that both the cognitive and skill domains exhibit significant positive correlations with PA. At specific dimensional levels, such associations were also observed in knowledge, understanding, interactive skills and critical skills. Previous research has noted an association between higher nutritional knowledge and higher time spent in PA[28,29]. However, this study observed that high levels of obtaining skills and applying skills were not associated with PA. This may stem from the fact that mere information acquisition capability cannot directly translate into actual participation in PA, and nutritional knowledge alone is insufficient to alter individuals' dietary preferences[30]. In real life, numerous factors influence an individual's ability to apply nutritional knowledge to PA, which is not solely determined by applying skills. Achieving behavioral change requires fundamental behavioral competencies, environmental support, collaborative actions, and partnerships across different levels of influence[31]. Overall, the findings of this study further enrich the understanding of the relationship between NL and PA. Public health practitioners should enhance adults' NL levels through nutrition education, encourage them to acquire nutrition-related knowledge and skills, and ultimately improve population-wide PA levels.
本研究进一步探讨了个体 NL 和 PA 的两个领域和 6 个维度之间的关系 ,结果表明 d 认知和技能领域都与 PA 表现出显著的正相关 。 在特定维度水平上,在知识、 理解 、互动技能和关键技能中也观察到这种关联。先前的研究指出,较高的营养知识与较高的 PA 时间之间存在关联 [28,29]。 然而 , 他的研究观察到,高水平的获得技能和应用技能与 PA 无关 。 这可能源于这样一个事实,即单纯的信息获取能力不能直接转化为实际参与 PA, 仅靠营养知识不足以改变个体的饮食偏好 [30]。 在现实生活中,许多因素会影响个人将营养知识应用于 PA 的能力 ,这不仅仅取决于应用技能。实现行为改变需要基本的行为能力、环境支持、协作行动以及不同影响力级别的伙伴关系 [31]。 总体而言,本研究的结果进一步丰富了对 NL 和 PA 之间关系的理解 。 公共卫生从业者应通过营养教育提高成人的 NL 水平,鼓励他们获得营养相关知识和技能,并最终提高全人群的 PA 水平。
In this study, subgroup analysis revealed potential confounding factors influencing the association between NL and PA: residence location, age, education level, and monthly income level. In the urban-rural stratification, rural residents no longer need to engage in PA due to increased availability and use of modernized and automated agricultural machinery[32]. Additionally, rural areas face barriers to PA participation, such as insufficient fitness facilities and long distances to such facilities[33]. The promotion effect of NL on PA may be limited in rural areas due to economic constraints and lagging health awareness, indicating the need to strengthen nutrition education and sports infrastructure construction in rural regions. We also observed that high NL was significantly positively correlated with HPA only in the elderly population aged 65 and above, while no significant association was found in the young and middle-aged groups. These findings are consistent with previous studies indicating that PA levels in older adults are not necessarily lower than those in younger individuals[34], and that PA in the elderly increases with age [35, 36, 37]. These results suggest that younger individuals may spend more time on work and less time on PA. Furthermore, the prevalence of sarcopenia and chronic diseases among Chinese elderly is gradually increasing. Trujillo et al noted that older adults are becoming increasingly concerned about their health outcomes[38]. PA can reduce the risk of sarcopenia in the elderly[39], and HPA are associated with lower odds of chronic diseases[40]. Therefore, age may influence the correlation between NL and physical activity.
在这项研究中,亚组分析揭示了影响 NL 和 PA 之间关联的潜在混杂因素 :居住地、年龄、教育水平和月收入水平。在城乡分层中, 由于现代化和自动化农业机械的可用性和使用增加 ,农村居民不再需要参与 PA [32]。 此外,农村地区在参与 PA 方面面临障碍 ,例如健身设施不足和距离此类设施距离遥远 [33]。 由于经济限制和健康意识滞后,NL 对 PA 的促进作用在农村地区可能有限,这表明需要加强农村地区的营养教育和体育基础设施建设。我们还观察到,仅在 65 岁及以上的老年人群中,高 NL 与 HPA 呈显著正相关 ,而在中青年群体中未发现显著关联。这些发现与以前的研究一致,表明老年人的 PA 水平不一定低于年轻人 [34],并且老年人的 PA 随着年龄的增长而增加 [35, 3, 6, 37]。这些结果表明,年轻人可能花更多的时间在工作上,而花在 PA 上的时间更少。此外,中国老年人肌肉减少症和慢性病的患病率正在逐渐增加。 Trujillo 等人指出,老年人越来越关注他们的健康结果[38]。 PA 可以降低老年人患肌肉减少症的风险[39],而 HPA 与慢性病的几率较低有关[40]。因此,年龄可能会影响 NL 与身体活动之间的相关性。
Educational level and average monthly income are key factors influencing PA[41]. Wang J et al found that high-income populations exhibit lower LPA[42], while Celis-Morales et al discovered that adults with higher education demonstrate a greater prevalence of PA[43]. In summary, the positive correlation between NL and PA is influenced by residential location, age, educational level, and monthly income. These findings suggest that improving NL can promote PA engagement. Therefore, public health practitioners should develop targeted interventions incorporating demographic and lifestyle factors to enhance PA levels.
教育水平和平均月收入是影响 PA 的关键因素 [41]。Wang J 等人发现高收入人群的 LPA 较低 [42],而 Celis-Morales 等人发现受过高等教育的成年人表现出更高的 PA 患病率 [43]。综上所述,NL 和 PA 之间的正相关 受居住位置、年龄、教育水平和月收入的影响。这些发现表明,改善 NL 可以促进 PA 参与度。因此,公共卫生从业者应制定有针对性的干预措施,结合人口和生活方式因素,以提高 PA 水平。
This study has several strengths, being the first to investigate the relationship between NL and PA in adults. Additionally, the sample size collected from various districts of Bengbu City is relatively large. However, there are also some limitations to this study. First, the cross-sectional design limits the ability to establish causal relationships. It is impossible to determine whether NL levels are the cause or the result of PA based on a single cross-sectional study. Future research should employ longitudinal studies. Second, although we conducted uniform survey and measurement training to control survey quality, there may still be some recall bias in the self-reported information on covariates and PA. Third, the sample was limited to one city in Anhui Province. Therefore, caution should be exercised when generalizing the findings to other ethnic populations.
这项研究有几个优点,是第一个调查成人 NL 和 PA 之间关系的研究 。此外,从蚌埠市各区收集的样本量相对较大。然而,这项研究也存在一些局限性。首先,横截面设计限制了建立因果关系的能力。无法根据单一横断面研究确定 NL 水平是 PA 的原因还是结果 。未来的研究应采用纵向研究。其次,尽管我们进行了统一的调查和测量培训以控制调查质量,但在关于协变量和 PA 的自我报告信息中可能仍然存在一些回忆偏差 。第三,样本仅限于安徽省的一个城市。因此,在将研究结果推广到其他种族人群时应谨慎。
4 Conclusions
4 结论
High NL is strongly associated with HPA. Our results suggest that improving NL may be an effective approach to enhance PA. However, the relationship between NL and PA varies by residence location, age, educational level and monthly income level. Our findings indicate that interventions aimed at increasing PA should prioritize greater educational efforts targeting rural residents, middle-aged and young adults, as well as individuals with higher incomes and lower education levels.
高 NL 与 HPA 密切相关 。我们的结果表明,改善 NL 可能是增强 PA 的有效方法 。但是,NL 和 PA 之间的关系因居住地、年龄、教育水平和月收入水平而异。我们的研究结果表明,旨在提高 PA 的干预措施 应优先考虑针对农村居民、中年和年轻人以及收入较高但教育水平较低的个人的更大教育工作。
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