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中国膳食质量调查 DQQ 问卷的研发、验证与应用

2022-12-30 11:00

来源:

MDPI开放科学

发布于：湖北省

原标题：中国膳食质量调查 DQQ 问卷的研发、验证与应用

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低膳食质量是非传染性疾病负担的主要危险因素之一，不合理膳食也造成了沉重的死亡负担，2017 年全球有 1100 万死亡归因于不合理膳食。中国食物种类繁多 (3000 余种)，膳食摄入的地区差异性较大，进行大规模、标准化的膳食质量评价较为困难，且现有的膳食质量评价指标均依赖于定量膳食数据和中国食物成分表，对调查者和受访者造成沉重的经济、技术和时间负担，不利于开展大规模的人群膳食调查，与相关慢病关联不强，因此亟需新的、快速简便的、具有全球可比性的膳食质量调查方法。来自北京大学公共卫生学院儿童青少年卫生研究所的邹志勇副研究员及其团队在 Nutrients 期刊发表了系列文章，他们基于全球膳食质量框架，研制出了中国膳食质量调查问卷 (Dietary Quality Questionnaire, DQQ)，并在中国成年人群和儿童青少年群体中进行了验证，同时探究了依托 DQQ 开发的全球膳食推荐 (Global Dietary Recommendations, GDR) 评分与儿童青少年超重肥胖、膳食多样性指数与成人心理压力的关联，为膳食质量调查方法的发展和 DQQ 的广泛应用奠定了基础。

展开全文

2017 年全球 10 大死亡危险因素。

研究过程与结果

作者基于全球膳食质量框架，将中国食物详细分为 29 组，并利用 2011 年中国健康与营养调查数据结合人群访谈，研制出了中国 DQQ，被调查者只需要回顾过去 24 h 内所食用或饮用的食物或饮料，回答“是”或“否”，整个实施过程仅需约 5 分钟。

DQQ 问卷。

DQQ 的有效性通过哨点食物 (食用某种或某几种食物的累计消费人数达到调查总人数的95%及以上) 的消费量占比来评价。在 15 岁以上人群及 7~18 岁儿童青少年群体中，29 组食物里几乎每组食物中的哨点食物摄入人数都占该组食物摄入总人数的 95% 以上，有效性得到了验证，表明 DQQ 是收集中国人群常见食物消费的有效工具。

(上) DQQ 在 15 岁以上人群的验证；(下) DQQ 在 7~18 岁人群中的验证。

根据 DQQ 可构建一系列膳食质量评价指标，其中 GDR 是可以反映慢病风险的新指标。根据 DQQ 中特定的食物组，可以计算 GDR-Health 评分、GDR-Limit 评分、总体 GDR 评分。GDR-Health 评分和总体 GDR 分数越高或 GDR-Limit 评分越低，则表明膳食质量越高。研究结果表明，随着 GDR-Limit 评分的增加，一般性肥胖和中心性肥胖的检出率均呈上升趋势；GDR-Limit 评分与一般性肥胖和中心性肥胖呈正相关，总体 GDR 评分与一般性肥胖呈负相关；分性别、年龄和城乡分析后 GDR-Limit 评分仍与一般性肥胖呈正相关。

GDR-limit 得分与中国 7~18 岁儿童青少年超重肥胖呈正相关。

此外，作者还采用中国健康与营养调查的前瞻性数据分析了基于 DQQ 计算的膳食多样性指数与成人心理压力之间的关联。使用心理压力感知量表 (PSS-14) 测量心理压力，分数越高表明感知压力越大，总压力分数大于 25 分被认为是有害的。膳食多样性指数通过受试者消费的食物组数量进行衡量。采用单因素和多因素分析方法对膳食多样性与心理压力的相关性进行分析，结果表明：与心理压力组相比，低心理压力组的饮食多样性更高，并且女性和男性的心理压力水平均随着日常饮食多样性的增加而降低。在采用多因素 logistic 回归分析控制协变量后，与日常饮食多样性较低的研究对象相比，饮食多样性较高的研究对象经历更高水平心理压力的风险降低。

膳食多样性与压力评分的相关趋势图。

研究总结与展望

该系列文章基于全球膳食质量框架，利用哨点食物法研制出了中国 DQQ，并验证了其在中国人群中的有效性，同时探究了依托 DQQ 开发的 GDR 评分与儿童青少年超重肥胖的关联，介绍了膳食多样性与心理压力水平的相关性，并讨论了其可能的原因和机制。研究发现 DQQ 可用于中国成人及儿童青少年群体的膳食质量评价，基于 DQQ 的全球膳食推荐评分 GDR-Limit 与儿童超重肥胖呈正相关，且高饮食多样性可以降低高水平心理压力的风险，为膳食质量调查新方法的发展和 DQQ 的广泛应用奠定了基础，为儿童青少年超重肥胖、成人心理压力相关疾病的预防提供膳食相关新思路。

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责任编辑：

平台声明：该文观点仅代表作者本人，搜狐号系信息发布平台，搜狐仅提供信息存储空间服务。

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Open AccessArticle

Validation of the Diet Quality Questionnaire in Chinese Children and Adolescents and Relationship with Pediatric Overweight and Obesity

Huan WangHuan Wang

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1,2, Anna W. HerforthAnna W. Herforth

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3,4, Bo XiBo Xi

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2 and Zhiyong ZouZhiyong Zou

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1,*

National Health Commission Key Laboratory of Reproductive Health, Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China

Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China

Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA

Division of Human Nutrition and Health, Wageningen University and Research, P.O. Box 230, 6700 AE Wageningen, The Netherlands

Author to whom correspondence should be addressed.

Nutrients 2022, 14(17), 3551; https://doi.org/10.3390/nu14173551

Submission received: 4 May 2022

Accepted: 27 May 2022

Published: 29 August 2022

(This article belongs to the Special Issue Dietary, Lifestyle and Children Health)

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Abstract:

The low-burden Diet Quality Questionnaire (DQQ) has been developed to rapidly assess diet quality globally. Poor diet is often correlated with body size, and certain dietary risk factors can result in overweight and obesity. We aimed to examine the extent to which the DQQ captured food group consumption among children and adolescents in China, and to understand the association of several new indicators of diet quality scores derived from the DQQ with overweight and obesity, using the 2011 wave of the China Health and Nutrition Survey. The DQQ questions are constructed using sentinel foods—that is, food items that are intended to capture a large proportion of the population consuming the food groups. The overall Global Dietary Recommendations (GDR) score, GDR-Healthy score, and GDR-Limit score are novel indicators of diet quality that reflect dietary risk factors for non-communicable diseases derived from the DQQ questions. Multivariable logistic regression analysis was used to examine the associations of the GDR scores with overweight and obesity in the sample. The DQQ questions captured over 95% of children who consumed the food groups. Additionally, we found that the GDR-Limit score was positively associated with general obesity (odds ratio (OR) = 1.43, 95% confidence interval (CI): 1.17–1.74) and abdominal obesity (OR = 1.22, 95% CI: 1.05–1.43), whereas the overall GDR score was negatively related to general obesity (OR = 0.85, 95% CI: 0.74–0.97). The low-burden DQQ could be a valid tool to assess diet quality for the Chinese pediatric population aged 7–18 years. Poor diet quality, as determined by the GDR-Limit score, is associated with the increased risk of obesity in Chinese children and adolescents.

Keywords: Diet Quality Questionnaire; global dietary recommendations; overweight; obesity; children and adolescents

1. IntroductionDiets have shifted dramatically and rapidly in China in recent decades with socio-economic development and urbanization [1,2]. Between 1991 and 2009, higher daily fat intake, lower daily protein intake, and an increasing percentage of energy from fat mainly characterized the diets of Chinese children and adolescents aged 7–17 years [3], which subsequently contributed to the prevalence of pediatric overweight and obesity [3]. More recently, a nationwide study of more than one million Chinese school-aged children and adolescents showed that the mean prevalence of overweight and obesity increased markedly from 5.3% in 1995 to 20.5% in 2014 with economic development, highlighting an additional focus on healthy diets and physical activity [4]. Childhood obesity could not only track into adulthood [5] but also correlate with non-communicable diseases (NCDs) and mortality in early adulthood [6], making pediatric obesity a pressing concern in the prevention of obesity and obesity-related adverse outcomes later in life.Although increasing work has been conducted on diet quality and obesity, diet quality scores do not always correlate with obesity strongly or in expected directions. The Healthy Eating Index (HEI) was reported to be negatively associated with obesity, whereas diversity-based indices were positively associated with obesity in adults [7]. A systematic review and meta-analysis found no significant associations of dietary diversity score with overweight, obesity, or abdominal obesity in either adults or children [8]. Another systemic review provided convincing evidence on the null association between the HEI and body mass index (BMI) in adults and children [9]. These inconsistent findings might be attributed to the considerable heterogeneity of diet assessment or diverse populations with different demographics and socio-economic contexts. For example, diet quality was mainly assessed from a single 24 h recall, multiple 24 h recalls, or a food frequency questionnaire, and many diet quality indicators were country-specific [7,8,9,10], which complicates diet assessment and limits widespread use. Moreover, some diet quality scores, such as diet diversity scores, are designed to measure specific aspects of diet quality, such as nutrient adequacy, rather than total diet quality or risk factors for obesity or NCDs [11]. When selecting and applying indicators, it is important to use them for the purpose intended. Few indicators have been developed that specifically relate to diet-related NCDs.Measuring diet quality in the pediatric population has additional challenges and is less well studied. Many diet quality indices in the pediatric population have been developed and modified, yet few indices were validated [12,13]. To better monitor healthy diets globally, simple and feasible approaches are highly required to be uniform and standardized, which promotes comparability over time and across countries [14].Recently, a low-burden Diet Quality Questionnaire (DQQ) entirely based on 29 food groups has been developed to collect dietary data, which takes only five minutes to administer using “yes/no” questions about foods or drinks and is easily understood by respondents [11,15,16]. The novel DQQ is designed to rapidly assess diet quality in populations and has been adapted for more than 100 countries. The DQQ has been developed for the general population but so far has been validated and implemented only for adults (aged 15 years and older). The DQQ questions are constructed using sentinel foods—that is, food items which are intended to capture a large proportion of the population consuming the food groups. The DQQ sentinel food items have not yet been validated for use in populations younger than 15 years of age.The DQQ data can be used to construct several diet quality indicators at the population level, such as the Minimum Diet Diversity for Women, Food Group Diversity Score, and Global Dietary Recommendations (GDR) scores [15]. The GDR scores are constructed to reflect dietary risk factors for NCDs [15]. Thus, these scores may be plausibly associated with obesity, because dietary risks for NCDs and for obesity are similar. In particular, we would expect that the GDR-Limit score may be associated with obesity, because it captures the consumption of food groups that are generally energy-dense and high in fat and/or sugar.The present study has two aims, using data from the 2011 wave of the China Health and Nutrition Survey (CHNS). Firstly, we aim to validate the DQQ sentinel foods for Chinese children and adolescents aged 7–18 years. Secondly, we examine the associations of the GDR scores with overweight and obesity. The motivation of these analyses is to understand whether the DQQ could be applied for pediatric use in China, and to understand the relationship of GDR scores (indicators derived from the DQQ) with obesity in children and adolescents. 2. Materials and Methods 2.1. Study PopulationData were obtained from the 2011 wave of the CHNS, which aimed to understand the interplay of socio-economic transition and nutrition and health-related outcomes in China [17]. The CHNS is an international collaborative project between the Carolina Population Center at the University of North Carolina at Chapel Hill and the National Institute for Nutrition and Health at the Chinese Center for Disease Control and Prevention. This study was approved by corresponding institutional review committees and all participants provided written informed consent for inclusion before they participated in the survey [18]. Further information on the survey design and the publicly available datasets can be found in the cohort profile [17] and at the CHNS website [19].There were 15,725 participants in the 2011 wave of the CHNS, and we included all children and adolescents (hereafter referred to as “children”) aged 7–18 years with complete records on diet and anthropometrics (n = 1506). After further exclusion of those with implausible dietary intakes (carbohydrate intake ≥1500 g/day, calcium intake ≥3000 mg/day, or sodium intake ≥30 g/day), a total of 1501 children were included in this cross-sectional study (Figure 1). 2.2. Dietary Data CollectionThe quantitative dietary data were collected using 24 h dietary recall by trained investigators for three consecutive days that were randomly allocated from Monday to Sunday. For children younger than 12 years, someone who prepared the food for the household was asked to recall the children’s dietary intakes. More details on the dietary interview have been described elsewhere [1]. Nutrient intakes were calculated mainly using the 2009 Chinese food composition database [20], complemented by the 2018/2019 Chinese food composition databases [21,22]. 2.3. Dietary AssessmentFood intake of the first day from the consecutive three 24 h dietary recalls was coded into 29 food groups following the DQQ tool. The DQQ has been adapted to represent foods in the Chinese context that could reliably capture the food group consumption for the Chinese population, and the identification of sentinel food items for China has been described elsewhere [16]. The China DQQ and further information are available at the Global Diet Quality Project website [15].The GDR-Healthy score, GDR-Limit score, and overall GDR score were constructed from the dietary intake data: (1) GDR-Healthy score: reflecting five global recommendations on health-protective foods for healthy diets (fruits and vegetables, beans and other legumes, nuts and seeds, whole grains, and dietary fiber); (2) GDR-Limit score: reflecting six global recommendations on dietary components to limit (total fat, saturated fat, dietary sodium, free sugars, processed meat, and unprocessed red meat); (3) overall GDR score: subtracts the GDR-Limit score from the GDR-Healthy score, and reflects all 11 recommendations. The GDR score and its subcomponents were validated against quantitative intakes aligned with each of the recommendations. Specific food groups included for the GDR-Healthy score, GDR-Limit score, and overall GDR score are presented in Table S1. The GDR-Healthy and GDR-Limit scores ranged from 0 to 9 points and the overall GDR score ranged from −9 to 9 points. A lower overall GDR score, lower GDR-Healthy score, and higher GDR-Limit score indicate poorer diet quality [11]. 2.4. Physical ExaminationHeight, weight, and waist circumference (WC) were measured by trained field investigators following standardized procedures, as recommended by the World Health Organization (WHO) [23]. Height (accurate to 0.1 cm) and weight (accurate to 0.1 kg) were measured using calibrated weighing and height scales when participants stood straight in light clothes and without shoes. BMI was calculated as weight (kg) divided by height squared (m2). WC (accurate to 0.1 cm) was measured at the midpoint between the lowest rib and the iliac crest using non-elastic tapes in the standing position after normal expiration. 2.5. Definitions of Overweight and ObesityOverweight and general obesity were defined using the sex- and age-specific BMI cut-offs for screening among children and adolescents aged 2–18 years, released by the National Health and Family Planning Commission of China in 2018 [24]. Abdominal obesity was defined as WC values ≥ the sex- and age-specific 90th percentiles for Chinese children [25]. Additionally, according to the WHO BMI for age z-scores [26] and the international WC cut-offs [27], overweight, general obesity, and abdominal obesity were re-defined to test the robustness of the results. 2.6. Statistical AnalysisThe sentinel food analysis was conducted by ranking all foods in each food group in descending order according to the cumulative frequency of food consumption. Additionally, the percentages of the consumption of sentinel food items compared with all food items in the respective 29 food groups were calculated.Continuous variables were expressed as means ± standard deviations (age, weight, height, BMI, and WC) or medians ± interquartile ranges (dietary intakes and urbanicity index), and categorical variables were shown as numbers (percentages). The independent t-test, Wilcoxon rank test, and Chi-square test were used to compare differences in characteristics between boys and girls.The Cochran–Armitage test was used to examine trends in the prevalence of overweight and obesity across diet quality scores. The multivariable logistic regression analyses were used to evaluate the associations of the GDR scores with overweight and obesity; adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated after adjusting for sex, age, residence, and urbanicity index. Stratified analyses by sex (boys vs. girls), age (7–12 vs. 13–18 years), and residence (rural vs. urban) were conducted. All analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, USA). Two-sided p values < 0.05 were considered statistically significant. 3. Results 3.1. Participant CharacteristicsA total of 1501 children from the 2011 wave of the CHNS with a mean age of 11.7 years were included in this study, 59.9% of whom lived in rural areas. Approximately one tenth of children were overweight (11.0%) or obese (10.0%) and approximately one fifth had abdominal obesity (20.1%). Boys (51.7% of the sample) had significantly higher levels of weight, height, BMI, and WC than girls; boys also consumed more energy, carbohydrates, protein, and fat per day than girls. Boys were more likely to be overweight or obese than girls, whereas there was no significant difference in the prevalence of abdominal obesity between boys and girls (Table 1). 3.2. DQQ Sentinel Food Validation for Children and AdolescentsIn almost every food group, the sentinel food items captured over 95% of children aged 7–18 years who consumed the food groups, suggesting that the DQQ was a valid tool to collect the most common food consumption groups of the Chinese children (Figure 2). For example, people who consumed the sentinel food items (rice, noodles, steamed buns, and bread) accounted for 99.1% of those who consumed grains as a staple food (Table S2). For the vitamin A-rich fruits group, persimmon, mango, papaya, cantaloupe, and hawthorn captured 96.9% of children who consumed this food group; however, the sentinel food items only included the first four foods (capturing 93.8% of children). The specific sentinel food items for each food group are shown in Table S2. 3.3. Associations of Diet Quality Scores with Overweight and ObesityThe prevalence of overweight, general obesity, and abdominal obesity is presented in Figure 3 and Figure 4. Overall, the prevalence of general obesity was higher as the GDR-Limit score increased but was lower as the overall GDR score increased (both p for trend < 0.05). The observed trend in the overall GDR score appears to be driven by the GDR-Limit score. The prevalence of abdominal obesity also gradually increased with an increment in the GDR-Limit score (p for trend < 0.05). Detailed numbers of overweight and obese children who had each GDR score are shown in Table S3.After adjustment for sex, age, residence, and urbanicity index, the continuous GDR-Limit score was positively associated with general obesity (OR = 1.43, 95% CI: 1.17–1.74) and abdominal obesity (OR = 1.22, 95% CI: 1.05–1.43), whereas the continuous overall GDR score was negatively associated with general obesity (OR = 0.85, 95% CI: 0.74–0.97) (Table 2). As the diet quality scores were categorized according to their distribution, compared with children with a zero-point GDR-Limit score, those with a GDR-Limit score ≥2-point had increased odds of general obesity (OR = 2.66, 95% CI: 1.53–4.62) and abdominal obesity (OR = 1.60, 95% CI: 1.07–2.40) (Table 2).Stratified analyses by sex (boys vs. girls), age (7–12 vs. 13–18 years), and residence (rural vs. urban) are shown in Figure 5, and similar positive associations between the GDR-Limit score and obesity were found in the subgroups (Figure 5 and Table S4). In the sensitivity analysis, after redefining overweight and obesity, the GDR-Limit score was also positively associated with obesity (Table S5). 4. DiscussionIn this national cross-sectional analysis of 1501 children and adolescents aged 7–18 years from the 2011 wave of the CHNS, we found that the sentinel foods in the DQQ captured over 95% of children who consumed the food groups, indicating that it is a valid tool for diet quality assessment in this age group. The GDR-Limit score (derived from the DQQ questions) was positively associated with general and abdominal obesity, whereas the overall GDR score was negatively associated with general obesity. The present study suggests that the DQQ tool and new indicators of diet quality are valid for Chinese children and adolescents, and the poor diet quality determined by the GDR-Limit score is associated with the increased risk of obesity.Our finding that the sentinel food items captured over 95% of the food consumption of children suggests that the China-adapted DQQ tool has the potential to assess the diet quality in the Chinese pediatric population, aligned with global diet quality frameworks in the general population. Although there are several diet quality indicators for Chinese children and adolescents, such as the Chinese Children Dietary Index [28], Chinese Healthy Eating Index [29], and Chinese Healthy Eating Index for School-Age Children [30], these indices rely on 24 h diet recalls and food–nutrient conversion tables, which is time-consuming and poses a heavy burden for both investigators and interviewees. Additionally, these indices only reflect adherence to the Dietary Guidelines for Chinese residents, impeding the comparison of diet quality across countries. Given the increasing attention to adolescent nutrition globally [31,32], aligning with the global framework is useful. Although existing global platforms targeting adolescents are scarce, there are potential global indicators for individuals aged 2–19 years, including the GDR scores calculated easily from the DQQ [14]. Therefore, our study results support the application of the DQQ tool in China and accelerate the process of monitoring healthy diets for children and adolescents at national and global levels.In our study, we used the GDR scores from the China-adapted DQQ to assess diet quality, which reflects adherence to the WHO Global Dietary Recommendations [11]. We observed higher odds of obesity with a higher GDR-Limit score, and lower odds with a higher overall GDR score. On the other hand, the GDR-Healthy score was not significantly associated with obesity; thus, our findings support the importance of reducing intakes of unhealthy foods as the most important factor for reducing the risk of obesity. The overall GDR score was aligned with the 11 Global Dietary Recommendations on fruits and vegetables, beans and other legumes, nuts and seeds, whole grains, dietary fiber, total fat, saturated fat, dietary sodium, free sugar, processed meat, and unprocessed red meat [11]. Importantly, WHO proposes these recommendations generally based on evidence related to diet-related NCD risks [33,34,35]; therefore, the GDR scores obtained from the DQQ are promising diet quality indicators related to the risk of obesity and other diet-related NCDs in the Chinese population.This is the first study to validate the DQQ sentinel food items in Chinese children and adolescents. It is also the first study to assess the association between the GDR scores and overweight and obesity in a pediatric population. Several limitations of this study should be noted. First, we only obtained data from the 2011 wave of the CHNS; it is possible that the relationship between diet quality and obesity has changed in the last 10 years. Second, although age, sex, residence, and a comprehensive urbanicity index (proxy of modernization and urbanization) were accounted for in our analyses, residual confounding factors cannot be ruled out, such as physical activity, sedentary behavior, and pubertal development status. Third, although this study finds that the DQQ sentinel foods are valid for children and adolescents, further research is warranted to validate the application of the DQQ in terms of the ability of children and adolescents to reliably report their diet. In general, dietary recall and reporting are challenging for the pediatric age range [36]. 5. ConclusionsThe DQQ sentinel food items could be applied for use in populations aged 7–18 years. The GDR-Limit score is associated with the increased risk of obesity, and the low-burden DQQ could be a valid tool to assess diet quality for Chinese children and adolescents.

Supplementary MaterialsThe following are available online at https://www.mdpi.com/article/10.3390/nu14173551/s1, Table S1: Global Dietary Recommendations scores constructed from the Diet Quality Questionnaire; Table S2: Percentage (%) of the consumption of sentinel food items compared with all food items in respective 29 food groups by sex, age, and residence; Table S3: Number and percentage (%) of the overweight and obesity by the Global Dietary Recommendations (GDR) scores; Table S4: Subgroup analysis of associations between the Global Dietary Recommendations scores and overweight and obesity by sex, age, and residence; Table S5: Sensitivity analysis of associations between the Global Dietary Recommendations scores and overweight and obesity.Author ContributionsConceptualization, A.W.H., Z.Z., B.X. and H.W.; methodology, Z.Z., B.X. and H.W.; software, H.W.; validation, Z.Z.; formal analysis, H.W.; investigation, Z.Z.; resources, Z.Z.; data curation, Z.Z.; writing—original draft preparation, Z.Z. and H.W.; writing—review and editing, H.W., A.W.H., B.X. and Z.Z.; supervision, Z.Z. and A.W.H.; project administration, Z.Z.; funding acquisition, Z.Z. and A.W.H.; All authors have read and agreed to the published version of the manuscript.FundingThe study was funded by the National Natural Science Foundation of China (82073573 to Z.Z.) and the EU and BMZ through GIZ (Knowledge for Nutrition, K4N, to A.W.H.). The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.Institutional Review Board StatementThe study was approved by the Institutional Review Committee of the University of North Carolina at Chapel Hill, and the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention.Informed Consent StatementInformed consent was voluntarily provided by all participants and their legal guardians.Data Availability StatementThe dataset in the present study was open-access and can be freely obtained from the CHNS website: https://www.cpc.unc.edu/projects/china/data/datasets/data_downloads/longitudinal (accessed on 20 November 2021).AcknowledgmentsThis study used data from the China Health and Nutrition Survey (CHNS). We gratefully acknowledge the National Institute of Nutrition and Food Safety, China Centre for Disease Control and Prevention; the Carolina Population Centre, University of North Carolina at Chapel Hill; the National Institutes of Health (NIH; R01-HD30880, DK056350, and R01-HD38700); and the Fogarty International Centre, NIH, for their financial contributions towards the CHNS data collection and analysis files since 1989. We also thank all the participants and the staff of the CHNS involved in this study.Conflicts of InterestThe authors declare no conflict of interest. The funders had no role in the design of the study, data collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.ReferencesZhai, F.Y.; Du, S.F.; Wang, Z.H.; Zhang, J.G.; Du, W.W.; Popkin, B.M. Dynamics of the Chinese diet and the role of urbanicity, 1991–2011. Obes. Rev. 2014, 15 (Suppl. 1), 16–26. [Google Scholar] [CrossRef]Popkin, B.M. 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Figure 1.

Flow chart of the inclusion/exclusion of participants.

Figure 1.

Flow chart of the inclusion/exclusion of participants.

Figure 2.

Percentage (%) of the consumption of sentinel food items compared with all food items in respective 29 food groups by sex, age, and residence. Note: 1: Staple foods made from grains; 2: Whole grains; 3: White root/tubers; 4: Legumes; 5: Vitamin A-rich orange vegetables; 6: Dark green leafy vegetables; 7: Other vegetables; 8: Vitamin A-rich fruits; 9: Citrus; 10: Other fruits; 11: Grain-baked sweets; 12: Other sweets; 13: Eggs; 14: Cheese; 15: Yogurt; 16: Processed meats; 17: Unprocessed red meat (ruminant); 18: Unprocessed red meat (nonruminant); 19: Poultry; 20: Fish and seafood; 21: Nuts and seeds; 22: Packaged ultra-processed salty snacks; 23: Instant noodles; 24: Deep fried foods; 25: Fluid milk; 26: Sweetened tea/coffee/milk drinks; 27: Fruit juice; 28: Sugar-sweetened beverages (sodas); 29: Fast food.

Figure 2.

Figure 3.

Prevalence of overweight and obesity by Global Dietary Recommendations (GDR) scores.

Figure 3.

Prevalence of overweight and obesity by Global Dietary Recommendations (GDR) scores.

Figure 4.

Prevalence of abdominal obesity by Global Dietary Recommendations (GDR) scores.

Figure 4.

Prevalence of abdominal obesity by Global Dietary Recommendations (GDR) scores.

Figure 5.

Associations of the Global Dietary Recommendations scores with overweight and obesity by sex, age, and residence. Note: CI, confidence interval; GDR, global dietary recommendations; OR, odds ratio. Logistic regression analyses were used to calculate the odds ratios and 95% confidence intervals with adjustment for sex, age, residence, and urbanicity index.

Figure 5.

Table 1.

Characteristics of participants by sex.

Table 1.

Characteristics of participants by sex.

CharacteristicsTotal (n = 1501)Boys (n = 776)Girls (n = 725)p Value bAge, years11.72 ± 3.3011.75 ± 3.3111.69 ± 3.280.725Weight, kg41.56 ± 19.7643.13 ± 16.3839.89 ± 22.690.002Height, cm147.13 ± 17.29149.24 ± 18.59144.90 ± 15.50<0.001BMI, kg/m218.42 ± 3.9318.66 ± 3.8818.17 ± 3.960.020WC, cm65.06 ± 14.0166.21 ± 12.6463.85 ± 15.230.002Energy, kcal/day a1525.20 ± 858.451657.62 ± 926.571412.82 ± 781.48<0.001Carbohydrate, g/day a214.04 ± 138.98234.58 ± 142.68193.15 ± 122.90<0.001Protein, g/day a53.73 ± 34.4159.02 ± 35.1549.63 ± 31.45<0.001Fat, g/day a49.65 ± 45.5552.92 ± 46.2045.32 ± 44.05<0.001Urbanicity index a73.84 ± 35.7671.29 ± 35.7976.30 ± 36.060.366Residence, n (%) 0.935Rural899 (59.89)464 (59.79)435 (60.00) Urban602 (40.11)312 (40.21)290 (40.00) BMI categories, n (%) 0.001Non-overweight/obesity1125 (79.06)552 (75.41)573 (82.92) Overweight156 (10.96)100 (13.66)56 (8.10) General obesity142 (9.98)80 (10.93)62 (8.97) WC categories, n (%) 0.651Non-obesity1134 (79.92)586 (80.38)548 (79.42) Abdominal obesity285 (20.08)143 (19.62)142 (20.58)

BMI, body mass index; WC, waist circumference. Continuous variables are expressed as means ± standard deviations, and categorical variables as numbers (percentages). a Continuous variables are expressed as medians ± interquartile ranges. b Differences in characteristics between boys and girls were tested by independent t-test, Wilcoxon rank test, or Chi-square test.

Table 2.

Associations of Global Dietary Recommendations scores with overweight and obesity.

Table 2.

Associations of Global Dietary Recommendations scores with overweight and obesity.

ScoresOverweightGeneral ObesityAbdominal ObesityOR (95% CI)p ValueOR (95% CI)p ValueOR (95% CI)p ValueGDR-Healthy Continuous1.07 (0.92–1.24)0.3930.98 (0.83–1.15)0.8121.03 (0.91–1.16)0.644Categories ≤11.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 21.86 (1.05–3.29)0.0341.01 (0.59–1.73)0.9731.13 (0.76–1.69)0.553≥31.72 (0.99–2.99)0.0561.05 (0.63–1.73)0.8631.17 (0.80–1.71)0.419GDR-Limit Continuous1.03 (0.84–1.27)0.7971.43 (1.17–1.74)<0.0011.22 (1.05–1.43)0.012Categories 01.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 11.69 (1.05–2.70)0.0301.33 (0.78–2.26)0.2961.23 (0.86–1.77)0.262≥21.21 (0.69–2.11)0.5162.66 (1.53–4.62)0.0011.60 (1.07–2.40)0.022Overall GDR Continuous1.04 (0.91–1.18)0.5720.85 (0.74–0.97)0.0160.94 (0.86–1.04)0.244Categories <01.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 00.87 (0.36–2.14)0.7690.89 (0.44–1.80)0.7500.81 (0.46–1.44)0.480≥11.17 (0.59–2.70)0.5540.53 (0.29–0.98)0.0430.63 (0.39–1.04)0.070

CI, confidence interval; GDR, global dietary recommendations; OR, odds ratio; Ref, reference group. Logistic regression analyses were used to calculate the odds ratios and 95% confidence intervals with adjustment for sex, age, residence, and urbanicity index.

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Wang, H.; Herforth, A.W.; Xi, B.; Zou, Z.

Validation of the Diet Quality Questionnaire in Chinese Children and Adolescents and Relationship with Pediatric Overweight and Obesity. Nutrients 2022, 14, 3551.

https://doi.org/10.3390/nu14173551

AMA Style

Wang H, Herforth AW, Xi B, Zou Z.

Validation of the Diet Quality Questionnaire in Chinese Children and Adolescents and Relationship with Pediatric Overweight and Obesity. Nutrients. 2022; 14(17):3551.

https://doi.org/10.3390/nu14173551

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Wang, Huan, Anna W. Herforth, Bo Xi, and Zhiyong Zou.

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https://doi.org/10.3390/nu14173551

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Wang, H.; Herforth, A.W.; Xi, B.; Zou, Z.

Validation of the Diet Quality Questionnaire in Chinese Children and Adolescents and Relationship with Pediatric Overweight and Obesity. Nutrients 2022, 14, 3551.

https://doi.org/10.3390/nu14173551

AMA Style

Wang H, Herforth AW, Xi B, Zou Z.

Validation of the Diet Quality Questionnaire in Chinese Children and Adolescents and Relationship with Pediatric Overweight and Obesity. Nutrients. 2022; 14(17):3551.

https://doi.org/10.3390/nu14173551

Chicago/Turabian Style

Wang, Huan, Anna W. Herforth, Bo Xi, and Zhiyong Zou.

2022. "Validation of the Diet Quality Questionnaire in Chinese Children and Adolescents and Relationship with Pediatric Overweight and Obesity" Nutrients 14, no. 17: 3551.

https://doi.org/10.3390/nu14173551

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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