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Diet quality indices and their associations with health-related outcomes in children and adolescents: an updated systematic review

Abstract

Background

To describe a-priori diet quality indices used in children and adolescents, appraise the validity and reliability of these indices, and synthesise evidence on the relationship between diet quality and physical and mental health, and growth-related outcomes.

Methods

Five electronic databases were searched until January 2019. An a-priori diet quality index was included if it applied a scoring structure to rate child or adolescent (aged 0–18-years) dietary intakes relative to dietary or nutrient guidelines. Diagnostic accuracy studies and prospective cohort studies reporting health outcomes were appraised using the Academy of Nutrition and Dietetics Quality Criteria Checklist.

Results

From 15,577 records screened, 128 unique paediatric diet quality indices were identified from 33 countries. Half of the indices’ scores rated both food and nutrient intakes (n = 65 indices). Some indices were age specific: infant (< 24-months; n = 8 indices), child (2–12-years; n = 16), adolescent (13–18 years; n = 8), and child/adolescent (n = 14). Thirty-seven indices evaluated for validity and/or reliability. Eleven of the 15 indices which investigated associations with prospective health outcomes reported significant results, such as improved IQ, quality of life, blood pressure, body composition, and prevalence of metabolic syndrome.

Conclusions

Research utilising diet quality indices in paediatric populations is rapidly expanding internationally. However, few indices have been evaluated for validity, reliability, or association with health outcomes. Further research is needed to determine the validity, reliability, and association with health of frequently utilised diet quality indices to ensure data generated by an index is useful, applicable, and relevant.

Registration

PROSPERO number: CRD42018107630.

Peer Review reports

Background

The prevalence of non-communicable diseases (NCDs) including type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD), and chronic respiratory disease experienced by children and adolescents aged 0 to 18-years is increasing [1, 2]. Four hundred new cases of T2DM are diagnosed annually in Australians aged 10–24-years [3]. Hypertension, a risk factor of CVD, is present in 6–7% of children and adolescents in Australia, the United Kingdom, and the United States of America (USA) [4,5,6]. Of concern, NCDs adversely affect growth, development, and maturation in childhood and adolescence [7], leading to compromised adult health and reduced life expectancy [8]. Hence, the prevention of NCDs in childhood is a global priority, requiring a multi-pronged approach to address major NCD risk factors [9]. These risk factors include diet quality, healthcare access, and substance abuse, which affect physical growth and mental development [10], with poor diet quality identified as one of the largest contributors to the global burden of NCDs [11].

Diet quality is broadly defined as a dietary pattern or an indicator of variety across key food groups relative to those recommended in dietary guidelines [12]. High diet quality thereby reflects achieving more optimal nutrient intake profiles and a lower risk of diet-related NCDs [13]. Diet quality can be influenced by confounding factors, including cultural and food environment, socio-economic status, child and family food preferences, and nutrition recommendations relevant to age, sex, country, and/or culture of the individual [14]. Diet Quality Indices (DQIs) are assessment tools that can be used to quantify the overall quality of an individual’s dietary intake by scoring food and/or nutrient intakes, and sometimes lifestyle factors, according to how closely they align with dietary guidelines [12]. There are a variety of DQIs which utilise a range of scoring matrices. Some use frequency of food or food group consumption, others use nutrient intakes which require estimation prior to scoring, and some include both.

Due to the link between dietary intake in childhood and NCDs in both childhood and adulthood, the accurate measurement of paediatric diet quality is essential both to understand current intakes as well as evaluate the effect of interventions [15, 16]. Reflecting this need, the use of DQIs is increasing not only in research and epidemiology, but also in community health and clinical settings where DQIs may form part of dietary education and self-monitoring interventions [14, 17,18,19,20]. A systematic review of paediatric DQIs which included papers published up until October 2013 identified 80 individual DQIs used in paediatric population samples, some of which identified cross-sectional associations with growth and health outcomes such as body weight, early onset puberty, and blood pressure [14].

Given the increasing number of DQIs identified in the previous review used or created for research, the diversity in the tools, and the different settings, age groups, and countries they are used amongst, there is a need to update the previous systematic review to identify valid DQIs and their associations with health outcomes [14]. Therefore, the aims of this systematic review update are to; 1) summarise a-priori DQIs used in child and adolescents; 2) appraise the validity and reliability of paediatric diet quality indices; and 3) synthesise the evidence on the relationship between diet quality and physical health, mental health, and growth-related outcomes among paediatric samples.

Methods

Study design

A systematic literature review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [21] and registered prospectively with the International Prospective Register of Systematic Reviews (PROSPERO number: CRD42018107630).

Search strategy

The search was designed as an update of the 2014 systematic review [14]. Medline (PubMed) and CINAHL were searched from 31 October 2013 to 11 January 2019. To broaden the search, the current review also searched Embase, Web of Science, and CENTRAL from database inception to 11 January 2019. The strategy used both controlled-vocabulary and keywords, and was designed for PubMed and translated for use in other databases using Polyglot Search Translator [22]. The translated search strategies were checked for accuracy by a librarian, and two authors (PD and SM), then further adapted for each database after examination of sensitivity and specificity by using a target of one eligible study per 100 records retrieved, with an estimated 150 eligible studies (Appendix). To support the systematic search update, snowball searching of reference lists of identified papers was conducted and the previous review [14] was examined to include any eligible studies the current search strategy didn’t identify.

Eligibility criteria

Table 1 describes the eligibility criteria used to identify studies to answer the research questions; a study was included if it addressed one or more of the research questions. Studies published in English and Mandarin (translated to English by colleagues) were included. Studies published in other languages were included if they could be translated using Google translate [23]. For this review, a DQI was defined as any assessment tool which applied a quantitative score to food (i.e., frequency of consumption) or nutrient intake, where the scoring system reflected pre-defined national dietary or nutrient guideline/s (i.e., the DQI scoring system was developed a-priori). Diversity and variety indices that score or count the variety of foods consumed without regards to a dietary standard were excluded. Excluded lifestyle indices were any scoring system which had ≥2 scoring components on behaviours such as exercise, sedentary activities, or smoking.

Table 1 Eligibility criteria of original studies included in this review according to the population, indicator, comparator, outcomes, and study design (PICOS) format.

Study selection and data extraction

Identified records were de-duplicated using Systematic Review Assistant-Deduplication [24] followed by a manual search in Endnote [25]. Titles and abstracts of papers were screened independently to assess their potential eligibility by two researchers (PD and SM) using Covidence [26], which further removed duplicates. The full texts of potentially eligible records were acquired and screened for eligibility by two researchers independently (PD and SM), with disagreements managed by consensus. Data were extracted from included papers by one researcher (PD) into three standardised tables; with random quality checks by a second researcher SM). For studies which measured prospective health-related outcomes, data were reported in their standard international units at baseline and follow-up, as well as mean change over time where possible.

Health-related outcomes

Any prospective outcome related to physical health, mental health, or growth was included if the variable was reported relative to DQI score or categories. Health-related outcomes used to describe the sample, but not linked to a DQI score were not considered. Health-related outcomes in adults were considered if they were related to a DQI assessment when the sample was aged < 18 years. In order to assess the ability of the DQI to predict health-related outcomes, outcomes were considered from 1-week after the DQI assessment with no further restriction on timeframe of follow-up. Health-related outcomes reported as the result of an intervention study were not considered as outcomes are likely to reflect the intervention rather than baseline diet quality.

Study quality

Any study which reported on the validity of a paediatric DQI or health-related outcomes was critically appraised using The Academy of Nutrition and Dietetics Quality Criteria Checklist (QCC) [27], independently by two authors (PD, SM, TB, or CC). Studies which reported the use of a DQI but didn’t report validity, reliability, or health-related outcomes were not critically appraised as study quality was not relevant to research question 1. Any disagreements in study quality were settled by consensus. The Academy QCC is a critical appraisal tool suitable to evaluate the risk of bias for any study design, including diagnostic, intervention, or observational. The QCC rates the quality of the study as positive, negative, or neutral reflecting risk of bias in participant selection, generalisability, data collection, and analysis [27]. Studies found to have negative study quality were not excluded.

Results

Of 15,577 records identified in the search, 4896 were duplicates. After title and abstract screening, 312 full texts were assessed against the eligibility criteria, with 132 papers included, including 22 identified through snowball searching (Fig. 1). The main reasons for exclusion were use of a non-a-priori diversity or variety index (n = 127), study design (n = 48), or study outcomes (n = 48). From the 132 included studies, 81 diet quality indices were identified by the current search strategy in addition to those identified in the original systematic review [14]. Of the 80 indices described in the original review [14], 47 were eligible in the current review update and were primarily identified from the current search strategy but was supported by the snowball search (Fig. 1), leading to a combined total of 128 unique indices designed for and/or used among children and adolescents. Of these, 39 included papers had evaluated the validity and/or reliability of 37 DQIs, while 12 evaluated the association of 12 DQIs with prospective health outcomes.

Fig. 1
figure1

PRISMA flow diagram demonstrating selection of studies.

Characteristics of diet quality indices developed for or used in paediatric samples

The 128 DQIs were developed across 33 countries, with most being designed for the USA (n = 23), Australia (n = 16), Germany (n = 11), and Brazil (n = 8) (Table 2). There were 23 DQIs created outside of the USA such as Australia, Belgium, Canada, and Gaza with scoring methods based on the Dietary Guidelines for Americans (Table 2). Very few indices were identified in developing countries (n = 7) [262]. Those identified were from India, Indonesia, and Guatemala [134, 138, 141] and were typically brief tools more appropriate for field work, assessing frequency of consumption or dietary patterns and used dietary guidelines from other countries such as the USA to assess diet quality [134, 138, 141]. Thirteen (10%) DQIs were adaptations of the Diet Quality Index (DQI) [250], and 22 (17%) were adaptations of the Health Eating Index (HEI) [227]. These adaptions reflected changes to the scoring system to be more applicable to different countries or age groups. Four identified DQIs were designed for adults and subsequently used among children and adolescents without being adapted [89, 106, 127, 250].

Table 2 Description and purpose of diet quality indices which have been designed for use or used in paediatric populations presented alphabetically by country (n = 128 indices)

Most indices were scored by considering both food and nutrient intakes (n = 64 DQIs), while 34% (n = 44 DQIs) scored by considering food intake alone, and 6% (n = 7 DQIs [111, 114, 115, 117, 146, 148, 189]) scored using nutrient intake data alone (Table 2). In addition, 10% (n = 13 DQIs [46, 73, 75, 80, 121, 128, 165, 195, 214, 224, 235, 248, 258]) assessed a single behaviour (e.g. physical activity levels) as well as food and/or nutrient intake. The most common methods of collecting dietary data in studies which reported the development of DQIs were 24-h dietary recalls (n = 44) and food frequency questionnaires (FFQ) (n = 43); while some studies used both methods (n = 18), others used alternative methods such as study specific questionnaires or multiple day food diaries or records (n = 23) (Table 2).

A number of studies utilised information from the same datasets, such as data from the National Health and Nutrition Examination Survey (NHANES) prospective population surveillance in the USA, or the Healthy Lifestyle by Nutrition in Adolescence (HELENA) in Europe [263, 264].

The quality and strength of papers identified

Of the 39 papers assessing validity and/or reliability of 37 DQIs, 22 papers had positive study quality, while 17 papers had neutral study quality (Table 3). Of the papers assessing the relationship with health-related outcomes, 10 papers had positive study quality and two papers had neutral study quality (Table 4). None of papers evaluated had a negative study quality. The most prevalent reasons for papers to be downgraded to neutral study quality was due to authors not reporting the eligibility criteria of participants, sampling method, or reasons for attrition.

Table 3 Studies evaluating the validity and/or reliability of paediatric a-priori diet quality indices (n = 37).
Table 4 Association of diet quality indices with prospective health-related outcomes in paediatric populations (n = 12).

The validation of diet quality indices

Only 28% (n = 37) of the DQIs identified were evaluated for validity (n = 35) and/or reliability (n = 11) (Table 3). Validity was assessed by construct validity (n = 21), concurrent or convergent validity (n = 8), relative validity (n = 8), content validity (n = 4), predictive validity (n = 4), or comparative validity (n = 1), and eight DQIs were assessed for more than one type of validity [46, 107, 152, 177, 192, 240, 268, 272]. Reference standards used to evaluate the validity of indices were other validated tools, serum biomarkers (n = 9) [45, 50, 74, 80, 88, 130, 194, 265, 266], food intake (n = 18) [19, 33, 45, 69, 73, 74, 80, 87, 88, 107, 121, 130, 152, 172, 175, 177, 178, 265, 266], nutrient intake (n = 30) [19, 33, 43, 45, 46, 53, 69, 73, 74, 80, 87, 88, 104, 107, 121, 130, 151, 152, 172, 175, 177, 178, 189, 192, 194, 240, 265, 266, 270,271,272] and energy intake (n = 9) [43, 69, 73, 104, 107, 172, 194, 200, 240, 272]. Cross-sectional health markers including blood pressure (n = 1) [80], weight (n = 3) [45, 87, 122], BMI (n = 11) [33, 45, 73, 80, 87, 121, 122, 200, 240, 270, 271], and waist circumference (n = 1) [271], percent body fat (n = 2) [122, 270] were used to evaluate validity (Table 3). Although assessed, the Modified revised children’s diet quality index (M-RCDQI) [151] and the Revised Brazilian Healthy Eating Index (BHEI-R) [266] were found to require further research to test the validity and reliability of these tools before they could be considered valid or reliable.

Health-related outcomes

Only 12 DQIs were evaluated for association with prospective health outcomes (n = 12 studies). Measured outcomes from these 12 studies included nutrient biomarkers (n = 7) [74, 88, 269, 273], IQ scores (n = 1) [269], blood pressure (n = 2) [269, 273], plasma cholesterol (n = 2) [269, 273], risk of metabolic syndrome (n = 1) [149], mental health (n = 1) [275], pre and post-menopausal breast cancer (n = 1) [244], and timing of puberty (n = 1) [117] (Table 4). Anthropometric values examined included BMI (n = 7) [38, 74, 85, 88, 252, 254, 269], changes in BMI or fat mass (n = 2) [117, 252], changes in weight (n = 1) [74], and body composition at onset of puberty (n = 1) [117].

Significant associations were found between high diet quality and serum vitamin D (β = 0.005, 95% CI = 0·002, 0·008, p < 0.0001), holo-transcobalamin (an indicator of B12) (β = 1·005, 95% CI = 1·002, 1·007, p = 0.0002), n-3 FS status (β = 0·376, 95% CI = 0·105, 0·646, p < 0·007) [88], and serum vitamin A (r = 0.128, p = 0.004) [74]. In adjusted models there were significant positive associations between CFUI score and total IQ (β = 1.92 [1.38, 2.47], p < 0.001), verbal IQ (β = 1.92 [1.37, 2.48], p < 0.001), and performance IQ (β = 1.33 [0.74, 1.92], p < 0.001) [269].

In adjusted models, significant inverse associations were found between diet quality and waist circumference (β = −0.15 [−0.31, − 0.002], p = 0.046), diastolic blood pressure (β = − 0.15 [− 0.31, − 0.002], p < 0.001) [269] and incidence of metabolic syndrome (OR: 0.35, 95%CI = 0.13,0.98, p < 0.05) [149] (Table 4). Significant inverse associations were found between diet quality and HbA1c levels in youth with type 1 diabetes (β = − 0.2, SE = 0.07, p = 0.0063). There was no association between diet quality and HbA1c in youth type 2 diabetes; however, there was a significant association for improved systolic blood pressure (β = −2.02, SE = 0.97, p = 0.0406) [273, 274].

Diet quality was positively associated with mental health-related quality of life [275] (Table 4). Female children and adolescents with the top three quintiles of diet quality and followed into adulthood had decreased risk of premenopausal breast cancer (HR: 0.78, 95%CI = 0.63,0.97; HR 0.86, 95%CI = 0.69,1.07; and HR 0.84, 95%CI = 0.67,1.04 respectively); but no association was found between AHEI score and pre- or postmenopausal breast cancer (Table 4) [244].

In addition to the above; three studies used prospective health outcomes to evaluate the predictive validity of DQIs (Table 3). The CFUI was associated with improved BMI, waist circumference, and blood pressure [269]; the E-KINDEX was associated with improved BMI, total body fat, and waist circumference [271]; and the Diet Quality Score for Preschool Children was associated with improved fat-free mass and fat mass [177].

Discussion

This review summarises 128 unique a-priori DQIs used in children and adolescents internationally; however, only 30% were assessed for validity and reliability, from which two were found to require refinement [151, 266] to achieve suitable accuracy and reliability. Additionally, only 15 DQIs were tested for association with prospective health outcomes; finding associations between high diet quality and improved nutrient status, IQ, body composition, risk of metabolic syndrome, blood pressure, HbA1c, mental-health related quality of life, and premenopausal breast cancer.

This systematic review update identified 81 novel paediatric a-priori DQIs (from 157 publication), a 172% increase over 7 years from the 47 identified in the original systematic review [14]. This steep increase in the development and use of DQIs demonstrates that this approach to assessing diet quality is well-utilised within research in children and adolescents internationally. The USA, Australia, Germany, and Brazil appear to be leading the development of paediatric DQIs, together producing 45% of all paediatric DQIs. Beyond these four countries, the vast majority of other DQIs were from other developed countries, possibly reflecting this review’s eligibility criteria. Dietary assessment in developing countries are often focused on assessing growth in an environment characterised by a high prevalence of undernutrition, and and is assessed using non-a-priori diet diversity indices (DDIs), diet diversity scores (DDSs), and food variety scores (FVSs) [14, 138, 167, 224] of which there were 127 excluded from this review (Fig. 1).

There were significant variations in DQIs methods. Simpler scoring methods awarded and summed points for foods which were or were not consumed over a specific frequency. This simple food-based scoring method reduces burden on both researchers, clinicians, and individual users as they can be easily applied to clinical practice. Food-based DQIs included the KIDMED, DGI-CA and ACARFS [33, 35, 214]. More complex DQI scoring methods involved quantification of nutrient intakes from reported food intakes which then undergoes a further step of calculating nutrient intakes relative to age-specific dietary guidelines or energy intake, which make such scores less applicable to the clinical setting or for individual use [141]. DQIs with complex nutrient-based scoring approaches included the NIS [114] and the NQI [115], with DQIs which used a combination of food and nutrient-based scoring methods being more common, such as the ARFS-P [19] and the DGI [36], which embody the same limitations as nutrient-only scoring methods.

Of concern, only 29% of the 128 unique DQIs identified were evaluated for validity and/or reliability, and only 12% evaluated associations with prospective health outcomes. Of the 35 DQIs which were evaluated for validity, 34 were stated to be validated tools by authors; however, due to inconsistent methodological approaches the validity of the DQIs could not be consistently evaluated. Only five DQIs (5%; DQI-A [88], diet quality score for preschool children [177], CFUI [269], E-KINDEX [75] and HNSP [74]) were both evaluated for validity and found to be positively associated with prospective nutrient biomarkers, blood pressure, IQ, and body composition. This suggests these DQIs are the most rigorous in terms of accuracy, reliability, and relevance to health. While the use of DQIs to measure the diet quality of children and adolescents is a highly utilised assessment method, further research is required to address the current paucity of evaluation studies of currently available tools.

Further, the large number of new yet non-validated paediatric a-priori DQIs suggests new DQIs are developed prior to evaluating existing DQIs, and therefore may have been unnecessary. The use of DQIs which have not been rigorously developed and evaluated may compromise the research in which they were used and lead to inaccurate and/or unreliable results. This is particularly the case for DQIs which were developed specifically to evaluate outcomes of a particular study, where the development of the tool was minimally described and not intended for re-use or replication; therefore, limiting confidence in the study results.

Approximately half of the identified DQIs were modified forms of the DQI or HEI [227, 250]. However, only 16 of these modified DQIs were validated in the new population (e.g. age, culture, country) group, where the remaining studies assumed validity based upon the tool being valid in the original population. Non-validated tools, even if adapted from a valid tool, should be used with caution as the modified DQI may not accurately assess diet quality or be appropriately extrapolated to the diet and cultural context of the new population sample. This is particularly the case for modified DQIs in which the scoring system was still based on national dietary guidelines of the original country (e.g. The USA), and not the new population (e.g. Brazil, Canada) [50, 59, 70]. Similar cautions should apply for DQIs such as the Healthy Diet Indicator and the Alternative Healthy Eating Index used in paediatric populations that were designed for adults as these indices may not accurately assess children and adolescent’s diet quality [89, 245].

A factor that varied between papers was the method of dietary data collection, with some DQIs able to be calculated using a variety of dietary assessment methods such as the Diet Quality Index – International [252]. This variety is a strength as it allows flexibility in the application of DQIs in future research and clinical practice. A 24-h recall was the most frequently used dietary assessment tool; however, it is unclear if the 24-h recalls were repeated over several days to improve its accuracy in reporting usual intake. Although most remaining DQIs used FFQs, a substantial number of papers did not use validated methods to collect dietary data [39]. There should also be a caution for the use of single 24-h recalls in studies with small sample sizes or in clinical practice as this one-off measure does not accurately represent usual dietary intake. Although a DQI may be valid, the method of dietary intake assessment must also be accurate and relevant if results are to be interpreted with confidence.

Limitations and future directions

The present review may be limited by publication bias, particularly in the fields of a null or negative result relating to the validity of DQIs and their association with health-related outcomes; however, publication bias was unable to be assessed as funnel plots were not able to be generated. Although this review reported validity, reliability, and associations with health-related outcomes; it did not evaluate other aspects of assessment tool utility such as sensitivity to change and participant burden nor did it evaluate the validity and reliability of dietary intake assessment methods.

Limitations in the existing literature highlight the need for future research to validate existing paediatric a-priori DQIs and to test their associations with prospective health-related outcomes. This will allow determination of the effect of diet quality during childhood and adolescence on physical health, mental health, and growth which is of increasing importance as the prevalence of diet-related NCDs continues to rise. The application of any DQI should appropriately assess dietary intake using validated methodology and researchers developing new DQIs should ensure that tools reflect indicators of alignment with an appropriate national dietary guideline or nutrient target specific to the culture, country, and age-group of the intended population, and rigorously describe the tools development, scoring method, and validation procedures. Researchers should consider applying existing valid DQIs to their data and undertaking reliability and validity studies in their population groups. For research reporting associations with health-related outcomes, researchers should fully describe the demographic and medical characteristics of the sample, information about dataset used, and transparently detail the results.

Implications for practice

DQIs present an important opportunity to measure the quality of the total diet of individuals and groups. The current review can be used as a resource to assist health professionals in identifying relevant and valid DQIs for their clinical setting. When selecting a DQI, health professionals should consider: i) whether the DQI demonstrated validity and/or reliability, ii) does the DQI reflect a nutritional reference standard which is relevant to the population in which it will be applied, iii) can the DQI be easily calculated in the clinical setting, and finally iv) can the DQI be calculated by a dietary assessment method which can be performed efficiently in the clinical setting? Although it would be ideal to select a DQI which is associated with prospective health outcomes; due to the paucity of research in this area, this is not yet a feasible consideration.

Conclusion

Research examining diet quality among children and adolescents is of increasing interest globally. However, few indices have been evaluated for validity or reliability or examined for a relationship with prospective health outcomes. Rigorously developed DQIs which have been evaluated have shown good validity, reliability, and association with a range of physical and mental health outcomes. Longitudinal studies are needed to determine the ability of diet quality indices to predict optimal growth and diet-related health-related outcomes among children and adolescents.

Availability of data and materials

Not applicable.

Abbreviations

CVD:

Cardiovascular disease

DDIs:

Diet diversity indices

DDSs:

Diet diversity scores

DQIs:

Diet quality indices

DQI:

The diet quality index (a version of diet quality indices)

EDNP:

Energy-dense, nutrient-poor foods

FFQ:

Food frequency questionnaire

FVSs:

Food variety scores

HEI:

Healthy eating index

IQ:

Intelligence quotient

NCD:

Non-communicable diseases

QCC:

Quality criteria checklist

T2DM:

Type 2 diabetes mellitus

References

  1. 1.

    Torpy JM, Campbell A, Glass RM. Chronic diseases of children. JAMA. 2010;303(7):682.

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Australian Institute of Health and Welfare. Selected Chronic Diseases Among Australia’s Children. AIHW cat no AUS 62. Canberra: AIHW; 2005; Bulletin no. 29.

    Google Scholar 

  3. 3.

    Diabetes Australia. Type 2 diabetes in younger people: small but significant 2015. Available from: https://www.diabetesaustralia.com.au/news/14153?type=articles.

    Google Scholar 

  4. 4.

    Larkins NG, Teixeira-Pinto A, Craig JC. The prevalence and predictors of hypertension in a National Survey of Australian Children. Blood Pressure. 2018;27(1):41–7.

    PubMed  Article  Google Scholar 

  5. 5.

    Riley M, Bluhm B. High blood pressure in children and adolescents. Am Fam Phys. 2012;85(7):693–700.

    Google Scholar 

  6. 6.

    Falkner B. Hypertension in children and adolescents: epidemiology and natural history. Pediatr Nephrol. 2010;25(7):1219–24.

    PubMed  Article  Google Scholar 

  7. 7.

    Michaud PA, Suris JC, Viner R. The Adolescent with a Chronic Condition: Epidemiology, developmental issues and health care provision. Geneva: World Health Organisation; 2007.

  8. 8.

    World Health Organisation. New global estimates of child and adolescent obesity released on World Obesity Day 2017. Available from: http://www.who.int/end-childhood-obesity/news/new-estimate-child-adolescent-obesity/en/.

    Google Scholar 

  9. 9.

    NCD Child. Understanding NCDs 2018. Available from: http://www.ncdchild.org/understanding-ncds/.

    Google Scholar 

  10. 10.

    The NCD Alliance. A Focus on Children and Non-Communicable Diseases (NCDs). 2011.

    Google Scholar 

  11. 11.

    Green R, Sutherland J, Dangour AD, Shankar B, Webb P. Global dietary quality, undernutrition and non-communicable disease: a longitudinal modelling study. BMJ Open. 2016;6(1):e009331.

    PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Wirt A, Collins CE. Diet quality – what is it and does it matter? Public Health Nutr. 2009;12(12):2473–92.

    PubMed  Article  Google Scholar 

  13. 13.

    National Health and Medical Research Council. What are Nutrient Reference Values? 2017. Available from: https://www.nrv.gov.au/introduction.

    Google Scholar 

  14. 14.

    Marshall S, Burrows T, Collins C. Systematic review of diet quality indices and their associations with health-related outcomes in children and adolescents. J Hum Nutr Diet. 2014;27(6):577–98.

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Australian Bureau of Statistics. Children’s risk factors 2017. Available from: http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by%20Subject/4364.0.55.001~2014–15~Main%20F.

    Google Scholar 

  16. 16.

    Al-Khudairy L, Loveman E, Colquitt J, Mead E, Johnson R, Fraser H, et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years. Cochrane Database Syst Rev. 2017;(6) Available from. https://doi.org/10.1002/14651858.CD012691.

  17. 17.

    Morgan PJ, Collins CE, Plotnikoff RC, McElduff P, Burrows T, Warren JM, et al. The SHED-IT community trial study protocol: a randomised controlled trial of weight loss programs for overweight and obese men. BMC Public Health. 2010;10(1):701.

    PubMed  PubMed Central  Article  Google Scholar 

  18. 18.

    Duncanson K, Lee YQ, Burrows T, Collins C. Utility of a brief index to measure diet quality of Australian preschoolers in the Feeding Healthy Food to Kids Randomised Controlled Trial. Nutr Diet. 2017;74(2):158–66.

    PubMed  Article  Google Scholar 

  19. 19.

    Burrows TL, Collins K, Watson J, Guest M, Boggess MM, Neve M, et al. Validity of the Australian Recommended Food Score as a diet quality index for Pre-schoolers. Nutrit J. 2014;13:87.

    Google Scholar 

  20. 20.

    Robinson LN, Rollo ME, Watson J, Burrows TL, Collins CE. Relationships between dietary intakes of children and their parents: a cross-sectional, secondary analysis of families participating in the Family Diet Quality Study. J Hum Nutr Diet. 2015;28(5):443–51.

    CAS  PubMed  Article  Google Scholar 

  21. 21.

    Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Int J Surg. 2010;8(5):336–41.

    PubMed  Article  Google Scholar 

  22. 22.

    Centre for Research in Evidence Based Practice. Polyglot search 2017. Available from: http://crebp-sra.com/#/polyglot.

    Google Scholar 

  23. 23.

    Google Translate. Google Translate 2017. Available from: https://translate.google.com/?sl=sr.

    Google Scholar 

  24. 24.

    Rathbone J, Carter M, Hoffmann T, Glasziou P. Better duplicate detection for systematic reviewers: evaluation of Systematic Review Assistant-Deduplication Module. Systematic reviews. 2015;4:6.

    PubMed  PubMed Central  Article  Google Scholar 

  25. 25.

    Clarivate Analytics. Endnote. Boston: Clarivate Analytics; 2018.

    Google Scholar 

  26. 26.

    Covidence. Covidence. Melbourne: Veritas Health Innovation. Accessed Sept 2018.

  27. 27.

    American Dietetic Association. Evidence analysis manual: steps in the ada evidence analysis process. Chicago: Academy of Nutrition & Dietetics; 2010. Contract No.: ISBN: 978–0–88091-429-1.

  28. 28.

    Tonkin E, Kennedy D, Golley R, Byrne R, Rohit A, Kearns T, et al. The Relative Validity of the Menzies Remote Short-Item Dietary Assessment Tool (MRSDAT) in Aboriginal Australian Children Aged 6–36 Months. Nutrients. 2018;10(5):590.

    PubMed Central  Article  PubMed  Google Scholar 

  29. 29.

    Australian Government. Australian Dietary Guidelines. Canberra: NHMRC; 2013.

    Google Scholar 

  30. 30.

    Rohit A, Brimblecombe J, O’ Dea K, Tonkin E, Maypilama Ḻ, Maple-Brown L. Development of a short-item diet quality questionnaire for Indigenous mothers and their young children: The Menzies remote short-item dietary assessment tool. Aust J Rural Health. 2018;26(3):220–4.

    PubMed  Article  Google Scholar 

  31. 31.

    Bell LK, Golley RK, Magarey AM. A short food-group-based dietary questionnaire is reliable and valid for assessing toddlers’ dietary risk in relatively advantaged samples – Corrigendum. 2014;112(9):1587-.

  32. 32.

    Russell CG, Worsley A. Do children’s food preferences align with dietary recommendations? Public Health Nutr. 2007;10(11):1223–33.

    CAS  PubMed  Article  Google Scholar 

  33. 33.

    Marshall S, Watson J, Burrows T, Guest M, Collins CE. The development and evaluation of the Australian child and adolescent recommended food score: a cross-sectional study. Nutr J. 2012;11(1):96.

    PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Gasser CE, Kerr JA, Mensah FK, Wake M. Stability and change in dietary scores and patterns across six waves of the Longitudinal Study of Australian Children. Br J Nutr. 2017;117(8):1137–50.

    CAS  PubMed  Article  Google Scholar 

  35. 35.

    Golley R, Hendrie G, McNaughton S. The Dietary Guidelines Index for Children and Adolescents (DGI-CA); 2011.

    Google Scholar 

  36. 36.

    Lioret S, McNaughton SA, Cameron AJ, Crawford D, Campbell KJ, Cleland VJ, et al. Three-year change in diet quality and associated changes in BMI among schoolchildren living in socio-economically disadvantaged neighbourhoods. Br J Nutr. 2014;112(2):260–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. 37.

    Jacka F, Kremer P, Leslie E, Berk M, Patton G, Toumbourou JW, et al. Associations between diet quality and depressed mood in adolescents: results from the Australian Healthy Neighbourhoods Study. Aust N Z J Psych. 2010;44(5):435–42.

    Article  Google Scholar 

  38. 38.

    Meyerkort CE, Oddy WH, O'Sullivan TA, Henderson J, Pennell CE. Early diet quality in a longitudinal study of Australian children: associations with nutrition and body mass index later in childhood and adolescence. J Devel Orig Health Dis. 2012;3(1):21–31.

    CAS  Article  Google Scholar 

  39. 39.

    Nyaradi A, Oddy WH, Hickling S, Li J, Foster JK. The relationship between nutrition in infancy and cognitive performance during adolescence. Front Nutr. 2015;2:2.

    PubMed  PubMed Central  Article  Google Scholar 

  40. 40.

    Li J, O'Sullivan T, Johnson S, Stanley F, Oddy W. Maternal work hours in early to middle childhood link to later adolescent diet quality. Public Health Nutr. 2012;15(10):1861–70.

    PubMed  Article  PubMed Central  Google Scholar 

  41. 41.

    National Health and Medical Resarch Council. Nutrient Reference Values for Australia and New Zealand Including Recommended Dietary Intakes. Canberra: National Health and Medical Resarch Council; 2005.

    Google Scholar 

  42. 42.

    Scott JA, Chih TY, Oddy WH. Food variety at 2 years of age is related to duration of breastfeeding. Nutrients. 2012;4(10):1464–74.

    PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    Spence AC, McNaughton SA, Lioret S, Hesketh KD, Crawford DA, Campbell KJ. A health promotion intervention can affect diet quality in early childhood. J Nutr. 2013;143(10):1672–8.

    CAS  PubMed  Article  Google Scholar 

  44. 44.

    Dietary Guidelines for Americans 2015–2020 Eigth Edition. In: Services UDoHaH, editor. dietaryguidelines.gov: USDA; 2015.

  45. 45.

    Kunaratnam K, Halaki M, Wen LM, Baur LA, Flood VM. Reliability and comparative validity of a Diet Quality Index for assessing dietary patterns of preschool-aged children in Sydney, Australia. Eur J Clin Nutr. 2018;72(3):464.

    PubMed  Article  Google Scholar 

  46. 46.

    Huybrechts I, Vereecken C, De Bacquer D, Vandevijvere S, Van Oyen H, Maes L, et al. Reproducibility and validity of a diet quality index for children assessed using a FFQ. Br J Nutr. 2010;104(1):135–44.

    CAS  PubMed  Article  Google Scholar 

  47. 47.

    Vlaams Instituut voor Gezondheidspromotie (VIG). voedingsdriehoek: een Praktische Voedingsgids: VIG; 2004.

    Google Scholar 

  48. 48.

    Sabbe D, De Bourdeaudhuij I, Legiest E, Maes L. A cluster-analytical approach towards physical activity and eating habits among 10-year-old children. Health Educ Res. 2008;23(5):753–62.

    PubMed  Article  Google Scholar 

  49. 49.

    Dietary Guideline Advisory Committee. Report of the Dietary Guidelines Advisory Committee for Americans, 2000. To the Secretary of Health and Human Services and Secretary of Agriculture. ARS. 2000.

    Google Scholar 

  50. 50.

    Rauber F, da Costa Louzada ML, Vitolo MR. Healthy eating index measures diet quality of Brazilian children of low socioeconomic status. J Am College Nutr. 2014;33(1):26–31.

    Article  Google Scholar 

  51. 51.

    Vítolo MR. Dez passos para uma alimentaçào saudável. Guia alimentar para crianças menores de 2 anos: um guia para o profissional da saúde na atençào básica. Dez passos para uma alimentaçào saudável Guia alimentar para crianças menores de 2 anos: um guia para o profissional da saúde na atençào básica; 2002. p. 45.

    Google Scholar 

  52. 52.

    Molina Mdel C, Lopez PM, Faria CP, Cade NV, Zandonade E. Socioeconomic predictors of child diet quality. Revista de saude Publica. 2010;44(5):785–32.

    PubMed  Article  Google Scholar 

  53. 53.

    Conceição SIOD, Oliveira BR, Rizzin M, Silva AAMD. Healthy Eating Index: adaptation for children aged 1 to 2 years. Ciencia Saude Coletiva. 2018;23(12):4095.

    PubMed  Article  Google Scholar 

  54. 54.

    Fisberg RM, Slater B, Barros RR, De Lima FD, Cesar CLG, Carandina L, et al. Índice de Qualidade da Dieta: Avaliação da adaptação e aplicabilidade. Healthy Eating Index Eval Adapted Version Appl. 2004;17(3):301–8.

    Google Scholar 

  55. 55.

    Philippi ST, Latterza AR, Cruz ATR, Ribeiro LC. Pirâmide alimentar adaptada: guia para escolha dos alimentos. Revista de nutrição. 1999;12(1):65–80.

    Article  Google Scholar 

  56. 56.

    Previdelli AN, Andrade SC, Pires MM, Ferreira SRG, Fisberg RM, Marchioni DM. A revised version of the Healthy Eating Index for the Brazilian population. Revista de saude Publica. 2011;45(4):794.

    PubMed  Article  Google Scholar 

  57. 57.

    Paulo Rogério Melo R, Gomes de S RA, Mara Lima De C, Luana Silva M, Camila Pinheiro C, Alessandra Page B, et al. Dietary quality varies according to data collection instrument: a comparison between a food frequency questionnaire and 24-hour recall. Cad Saúde Pública. 2016;32(2):e00047215.

    Google Scholar 

  58. 58.

    Simone C, Semíramis Martins Álvares D. Diet quality index for healthy food choices. Rev Nutrição. 2013;26(6):693–9.

    Article  Google Scholar 

  59. 59.

    Juliana Garcia B, Andréa Polo G, Aline De Piano G. Impact of actions of food and nutrition education program in a population of adolescents. Revista de Nutrição. 2016;29(1):65–75.

    Article  Google Scholar 

  60. 60.

    Wendpap LL, Ferreira MG, Rodrigues PRM, Pereira RA, Loureiro ADS, Gonçalves-Silva RMV. Adolescents’ diet quality and associated factors. Cad Saude Publica. 2014;30(1):97.

    PubMed  Article  Google Scholar 

  61. 61.

    Jessri M, Ng A, L’Abbé M. Adapting the Healthy Eating Index 2010 for the Canadian Population: Evidence from the Canadian Community Health Survey. Nutrients. 2017;9(8):910.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  62. 62.

    Nshimyumukiza L, Lieffers JR, Ekwaru JP, Ohinmaa A, Veugelers PJ. Temporal changes in diet quality and the associated economic burden in Canada. PloS one. 2018;13(11):e0206877.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  63. 63.

    Bush MA, Martineau C, Pronk JA, Brulé D. Eating well with Canada's food guide:“A tool for the times”. Can J Diet Pract Res. 2007;68(2):92–6.

    PubMed  Article  Google Scholar 

  64. 64.

    Glanville NT, Mcintyre L. Diet quality of Atlantic families headed by single mothers. Can J Diet Pract Res. 2006;67(1):28–35.

    PubMed  Article  Google Scholar 

  65. 65.

    Health and Welfare Canada and Ontario Ministry of Health. Canada’s Food Guide to Healthy Eating. Toronto: Queen’s Printer for Ontario; 1993.

    Google Scholar 

  66. 66.

    Woodruff SJ, Hanning RM. Development and implications of a revised Canadian Healthy Eating Index (HEIC-2009). Public Health Nutr. 2010;13(6):820–5.

    PubMed  Article  Google Scholar 

  67. 67.

    Wang JW, Shang L, Light K, O'Loughlin J, Paradis G, Gray-Donald K. Associations between added sugar (solid vs. liquid) intakes, diet quality, and adiposity indicators in Canadian children. Appl Physiol Nutr Metab. 2015;40(8):835–41.

    CAS  PubMed  Article  Google Scholar 

  68. 68.

    Tugault-Lafleur CN, Black JL, Barr SI. Examining school-day dietary intakes among Canadian children. Appl Physiol Nutr Metabol. 2017;42(10):1064.

    CAS  Article  Google Scholar 

  69. 69.

    Absolon JS, Wearring GA, Behme MT. Dietary quality and eating patterns of adolescent girls in southwestern ontario. J Nutr Educ Behav. 1988;20(2):77–81.

    Article  Google Scholar 

  70. 70.

    Protudjer JLP, Sevenhuysen GP, Ramsey CD, Kozyrskyj AL, Becker AB. Low vegetable intake is associated with allergic asthma and moderate-to-severe airway hyperresponsiveness. Pediatr Pulmonol. 2012;47(12):1159–69.

    PubMed  Article  Google Scholar 

  71. 71.

    Ya-Qun Y, Fan L, Rui-Hua D, Jing-Si C, Geng-Sheng H, Shu-Guang L, et al. The Development of a Chinese Healthy Eating Index and Its Application in the General Population. Nutrients. 2017;9(9):977.

    Article  CAS  Google Scholar 

  72. 72.

    Ge K. The transition of Chinese dietary guidelines and the food guide pagoda. Asia Pac J Clin Nutr. 2011;20(3):439.

    PubMed  Google Scholar 

  73. 73.

    Cheng G, Duan R, Kranz S, Libuda L, Zhang L. Development of a dietary index to assess overall diet quality for chinese school-aged children: the chinese children dietary index. J Acad Nutr Diet. 2016;116(4):608–17.

    PubMed  Article  Google Scholar 

  74. 74.

    Peng R, Wei XP, Liang XH, Yang T, Xu JP, Liu YX, et al. Study on dietary screening model for preschool children with vitamin A deficiency in Ba'nan District of Chongqing. J Shanghai Jiaotong Univ (Medical Science). 2015;35(5):753–7.

    Google Scholar 

  75. 75.

    Lazarou C, Panagiotakos DB, Matalas AL. Foods E-KINDEX: a dietary index associated with reduced blood pressure levels among young children: the CYKIDS study. J Am Diet Assoc. 2009;109(6):1070–5.

    PubMed  Article  Google Scholar 

  76. 76.

    Willett WC, Sacks F, Trichopoulou A, Drescher G, Ferro-Luzzi A, Helsing E, et al. Mediterranean diet pyramid: a cultural model for healthy eating. Am J Clin Nutr. 1995;61(6):1402S–6S.

    CAS  PubMed  Article  Google Scholar 

  77. 77.

    Knudsen V, Fagt S, Trolle E, Matthiessen J, Groth M, Biltoft-Jensen A, et al. Evaluation of dietary intake in Danish adults by means of an index based on food-based dietary guidelines. Food Nutr Res. 2012;56(1):17129.

    CAS  Article  Google Scholar 

  78. 78.

    Rohde JF, Larsen SC, Ängquist L, Olsen NJ, Stougaard M, Mortensen EL, et al. Effects of the Healthy Start randomized intervention on dietary intake among obesity-prone normal-weight children. Public Health Nutr. 2017;20(16):2988–97.

    PubMed  Article  Google Scholar 

  79. 79.

    Astrup A, Andersen NL, Stender S, Trolle E. Kostrådene 2005; 2005.

    Google Scholar 

  80. 80.

    Golley RK, Smithers LG, Mittinty MN, Brazionis L, Emmett P, Northstone K, et al. An index measuring adherence to complementary feeding guidelines has convergent validity as a measure of infant diet quality. J Nutr. 2012;142(5):901.

    CAS  PubMed  Article  Google Scholar 

  81. 81.

    National Health and Medical Research Council. Infant Feeding Guidelines Canberra. 2012. Available from: https://www.eatforhealth.gov.au/sites/default/files/files/the_guidelines/n56_infant_feeding_guidelines.pdf.

    Google Scholar 

  82. 82.

    Ministry of Health. Food and Nutrition Guidelines for Healthy Infants and Toddlers (Aged 0–2): A background paper Wellington. 2008. Available from: https://www.health.govt.nz/system/files/documents/publications/food-and-nutrition-guidelines-healthy-infants-and-toddlers-revised-dec12.pdf.

    Google Scholar 

  83. 83.

    Centers for disease control and prevention. Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion. Foods and Drinks for 6 to 24 Month Olds: U.S. Department of Health & Human Services; 2018. Available from: https://www.cdc.gov/nutrition/infantandtoddlernutrition/foods-and-drinks/index.html.

  84. 84.

    Scientific Advisory Committee on Nutrition. Feeding in the first year of life 2018. Cited 2020 5 September. Available from: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/725530/SACN_report_on_Feeding_in_the_First_Year_of_Life.pdf.

    Google Scholar 

  85. 85.

    Okubo H, Crozier SR, Harvey NC, Godfrey KM, Inskip HM, Cooper C, et al. Diet quality across early childhood and adiposity at 6 years: the Southampton Women's Survey. Int J Obes (2005). 2015;39(10):1456.

    CAS  PubMed Central  Article  PubMed  Google Scholar 

  86. 86.

    Ministry of Health LaW. Japanese food guide spinning top. 2005.

    Google Scholar 

  87. 87.

    Rice N, Gibbons H, McNulty BA, Walton J, Flynn A, Gibney MJ, et al. Development and validation testing of a short nutrition questionnaire to identify dietary risk factors in preschoolers aged 12–36 months. Food & nutrition research. 2015;59(1):27912.

    Article  Google Scholar 

  88. 88.

    Vyncke KE, Huybrechts I, Dallongeville J, Mouratidou T, Van Winckel MA, Cuenca-García M, et al. Intake and serum profile of fatty acids are weakly correlated with global dietary quality in European adolescents. Nutrition. 2013;29(2):411–9.e3.

    CAS  PubMed  Article  Google Scholar 

  89. 89.

    Huijbregts P, Feskens E, Räsänen L, Fidanza NF, Nissinen A, Menotti A, et al. Dietary pattern and 20 year mortality in elderly men in Finland, Italy, and The Netherlands: longitudinal cohort study. BMJ. 1997;315(7099):13.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  90. 90.

    World Health Organization. World Health Organisation. Diet, nutrition and prevention of chronic diseases. Report of a WHO Study Group Geneva 1990. Available from: https://www.who.int/nutrition/publications/obesity/WHO_TRS_797/en/.

    Google Scholar 

  91. 91.

    Arvidsson L, Eiben G, Hunsberger M, De Bourdeaudhuij I, Molnar D, Jilani H, et al. Bidirectional associations between psychosocial well-being and adherence to healthy dietary guidelines in European children : prospective findings from the IDEFICS study. BMC Public Health. 2017;17(1):926.

    PubMed  PubMed Central  Article  Google Scholar 

  92. 92.

    Ahrens W, Bammann K, Siani A, Buchecker K, De Henauw S, Iacoviello L, et al. The IDEFICS cohort: design, characteristics and participation in the baseline survey. Int J Obes (2005). 2011;35(S1):S3–S15.

    Article  Google Scholar 

  93. 93.

    Oliveira A, Jones L, de Lauzon-Guillain B, Emmett P, Moreira P, Charles MA, et al. Early problematic eating behaviours are associated with lower fruit and vegetable intake and less dietary variety at 4–5 years of age. A prospective analysis of three European birth cohorts. Br J Nutr. 2015;114(5):763.

    CAS  PubMed  Article  Google Scholar 

  94. 94.

    Jones L, Moschonis G, Oliveira A, de Lauzon-Guillain B, Manios Y, Xepapadaki P, et al. The influence of early feeding practices on healthy diet variety score among pre-school children in four European birth cohorts. Public Health Nutr. 2015;18(10):1774–84.

    PubMed  Article  Google Scholar 

  95. 95.

    De Vriendt T, Clays E, Huybrechts I, De Bourdeaudhuij I, Moreno LA, Patterson E, et al. European adolescents’ level of perceived stress is inversely related to their diet quality: the Healthy Lifestyle in Europe by Nutrition in Adolescence study. Br J Nutr. 2012;108(2):371–80.

    PubMed  Article  CAS  Google Scholar 

  96. 96.

    Vlaams Instituur voor Gezondheidspromotie (Flemish Institute for Health Promotion and Disease Prevention; VIGeZ) De actieve voedingsdriehoek: een praktische voedings- en beweeggids (The Active Food Guide Pyramid: Stress and diet quality in adolescents 379 British Journal of Nutrition 2008. Available from: https://www.cambridge.org/core.

  97. 97.

    Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel L, Van Horn L, et al. Defining and Setting National Goals for Cardiovascular Health Promotion and Disease Reduction The American Heart Association's Strategic Impact Goal Through 2020 and Beyond. Circulation. 2010;121(4):586–613.

    PubMed  Article  Google Scholar 

  98. 98.

    Henriksson P, Cuenca-García M, Labayen I, Esteban-Cornejo I, Henriksson H, Kersting M, et al. Diet quality and attention capacity in European adolescents: the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study. Br J Nutr. 2017;117(11):1587–95.

    CAS  PubMed  Article  Google Scholar 

  99. 99.

    Kavey R-EW, Daniels SR, Lauer RM, Atkins DL, Hayman LL, Taubert K. American heart association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. J Pediatr. 2003;142(4):368–72.

    PubMed  Article  Google Scholar 

  100. 100.

    Röytiö H, Jaakkola J, Hoppu U, Poussa T, Laitinen K. Development and evaluation of a stand-alone index for the assessment of small children’s diet quality. Public Health Nutr. 2015;18(11):1941–9.

    PubMed  Article  Google Scholar 

  101. 101.

    Nordic Nutrition recommendations. In: Ministers NCo, editor. Copenhagen: Nord; 2004.

  102. 102.

    Kanerva N, Kaartinen NE, Schwab U, Lahti-Koski M, Männistö S. The Baltic Sea Diet Score: a tool for assessing healthy eating in Nordic countries. Public Health Nutr. 2014;17(8):1697–705.

    PubMed  Article  Google Scholar 

  103. 103.

    Haapala E, Eloranta A, Venalainen T, Jalkanen H, Poikkeus A, Ahonen T, et al. Diet quality and academic achievement: a prospective study among primary school children. Eur J Nutr. 2017;56(7):2299–308.

    CAS  PubMed  Article  Google Scholar 

  104. 104.

    Kyttälä P, Erkkola M, Lehtinen-Jacks S, Ovaskainen M-L, Uusitalo L, Veijola R, et al. Finnish Children Healthy Eating Index (FCHEI) and its associations with family and child characteristics in pre-school children. Public Health Nutr. 2014;17(11):2519–27.

    PubMed  Article  Google Scholar 

  105. 105.

    Guthrie HA, Scheer JC. Validity of a dietary score for assessing nutrient adequacy. J Am Diet Assoc. 1981;78:240–5.

    CAS  PubMed  Google Scholar 

  106. 106.

    Shatenstein B, Abu-Shaaban D, Pascual ML, Kark JD. Dietary adequacy among urban and semi-rural schoolchildren in Gaza. Ecol Food Nutr. 1996;35(2):135–48.

    Article  Google Scholar 

  107. 107.

    Verger EO, Eussen S, Holmes BA. Evaluation of a nutrient-based diet quality index in UK young children and investigation into the diet quality of consumers of formula and infant foods. Public Health Nutr. 2016;19(10):1785–94.

    PubMed  Article  Google Scholar 

  108. 108.

    Choices N. The Eatwell Guide; 2016.

    Google Scholar 

  109. 109.

    Schoen S, Jergens S, Barbaresko J, Nöthlings U, Kersting M, Remer T, et al. Diet quality during infancy and early childhood in children with and without risk of type 1 diabetes: A DEDIPAC study. Nutrients. 2017;9(1):48.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  110. 110.

    Department of Health Dietary Reference Values for Food Energy and Nutrients for the United Kingdom. London; 1991.

  111. 111.

    Alexy U, Kersting M, Schultze-Pawlitschko V. Two approaches to derive a proposal for added sugars intake for German children and adolescents. Public Health Nutr. 2003;6(7):697–702.

    PubMed  Article  Google Scholar 

  112. 112.

    Kersting M, Alexy U, Clausen K. Using the concept of food based dietary guidelines to develop an optimized mixed diet (OMD) for German children and adolescents. J Pediatr Gastroenterol Nutr. 2005;40(3):301–8.

    PubMed  Article  Google Scholar 

  113. 113.

    Kleiser C, Mensink GBM, Scheidt-Nave C, Kurth BM. HuSKY: A healthy nutrition score based on food intake of children and adolescents in Germany. Br J Nutr. 2009;102(4):610–8.

    CAS  PubMed  Article  Google Scholar 

  114. 114.

    Alexy U, Sichert-Hellert W, Kersting M, Lausen B, Schoch G. Development of scores to measure the effects of nutrition counselling on the overall diet: A pilot study in children and adolescents. Eur J Nutr. 1999;38(4):196–200.

    CAS  PubMed  Article  Google Scholar 

  115. 115.

    Gedrich K, Karg G. Dietary habits of German vs Non-German residents in Germany. Culinary Arts and Sciences III - Global and National Perspectives; 2001. p. 419–28.

    Google Scholar 

  116. 116.

    Deutsche Gesellschaft für Ernährung (DGE). Österreichische Gesellschaft für Ernährung (ÖGE), Schweizerische Vereinigung für Ernährung (SGE): Referenzwerte fur die Nahrstoffzufuhr. Umschau Braus: Frankfurt; 2000.

    Google Scholar 

  117. 117.

    Cheng G, Gerlach S, Libuda L, Kranz S, Günther ALB, Karaolis-Danckert N, et al. Diet quality in childhood is prospectively associated with the timing of puberty but not with body composition at puberty onset. J Nutr. 2010;140(1):95.

    CAS  PubMed  Article  Google Scholar 

  118. 118.

    Gedrich K, Karg G. Dietary habits of German vs. non-German residents in Germany; 2001. p. 419–28.

    Google Scholar 

  119. 119.

    German Nutrition Society ANS, Swiss Society for Nutrition Research. Reference values for nutrient intake. Frankfurt. Main: Swiss Nutrition Association; 2002.

    Google Scholar 

  120. 120.

    Kohlboeck G, Sausenthaler S, Standl M, Koletzko S, Bauer CP, von Berg A, et al. Food intake, diet quality and behavioral problems in children: results from the GINI-plus/LISA-plus studies. Ann Nutr Metabol. 2012;60(4):247–56.

    Article  CAS  Google Scholar 

  121. 121.

    Manios Y, Kourlaba G, Grammatikaki E, Androutsos O, Moschonis G, Roma-Giannikou E. Development of a diet–lifestyle quality index for young children and its relation to obesity: the Preschoolers Diet–Lifestyle Index. Public Health Nutr. 2010;13(12):2000–9.

    PubMed  Article  Google Scholar 

  122. 122.

    Magriplis E, Farajian P, Risvas G, Panagiotakos D, Zampelas A. Newly derived children-based food index. An index that may detect childhood overweight and obesity. Int J Food Sci Nutr. 2015;66(6):623–32.

    CAS  PubMed  Article  Google Scholar 

  123. 123.

    U.S. Department of Agriculture. USDA national nutrient database for standard reference. In: Service. AR, editor. 2010.

    Google Scholar 

  124. 124.

    Yannakoulia M, Karayiannis D, Terzidou M, Kokkevi A, Sidossis LS. Nutrition-related habits of Greek adolescents. Eur J Clin Nutr. 2004;58(4):580–6.

    CAS  PubMed  Article  Google Scholar 

  125. 125.

    Supreme Scientific Health Council (SSHC) MoHaW. Dietary Guidelines for Adults in Greece. 1999.

    Google Scholar 

  126. 126.

    U.S. Department of Agriculture (USDA). Report of the Dietary Guidelines Advisory. Washington, DC: Committee on the Dietary Guidelines for Americans; 2000.

    Google Scholar 

  127. 127.

    Trichopoulou A, Kouris-Blazos A, Wahlqvist ML, Gnardellis C, Lagiou P, Polychronopoulos E, et al. Diet and overall survival in elderly people. Bmj. 1995;311(7018):1457–60.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  128. 128.

    Lazarou C, Panagiotakos D, Matalas A-L. E-KINDEX, a novel dietary index that is associated with obesity status in children. Int J Obes. 2008;32.

  129. 129.

    Lazarou C, Panagiotakos DB, Panayiotou G, Matalas AL. Overweight and obesity in preadolescent children and their parents in Cyprus: prevalence and associated socio-demographic factors – the CYKIDS study. Obes Rev. 2008;9(3):185–93.

    CAS  PubMed  Article  Google Scholar 

  130. 130.

    Manios Y, Kourlaba G, Grammatikaki E, Koubitski A, Siatitsa P, Vandorou A, et al. Development of a lifestyle–diet quality index for primary schoolchildren and its relation to insulin resistance: the Healthy Lifestyle–Diet Index. Eur J Clin Nutr. 2010;64(12):1399.

    CAS  PubMed  Article  Google Scholar 

  131. 131.

    Bach A, Serra-Majem L, Carrasco JL, Roman B, Ngo J, Bertomeu I, et al. The use of indexes evaluating the adherence to the Mediterranean diet in epidemiological studies: a review. Public Health Nutr. 2006;9(1a):132–46.

    PubMed  Article  Google Scholar 

  132. 132.

    Manios Y, Moschonis G, Papandreou C, Politidou E, Naoumi A, Peppas D, et al. Revised Healthy Lifestyle-Diet Index and associations with obesity and iron deficiency in schoolchildren: The Healthy Growth Study. J Hum Nutr. 2015;28 Suppl 2(s2):50.

    CAS  Article  Google Scholar 

  133. 133.

    U.S Department of Agriculture. USDA Choose My Plate n.d. Available from: https://www.choosemyplate.gov/.

  134. 134.

    Enneman A, Hernandez L, Campos R, Vossenaar M, Solomons NW. Dietary characteristics of complementary foods offered to Guatemalan infants vary between urban and rural settings. Nutr Res. 2009;29(7):470–9.

    CAS  PubMed  Article  Google Scholar 

  135. 135.

    Dewey K, Cohen RJ, Arimond M, Ruel MT. Developing and validating simple indicators of complementary food intake and nutrient density for breastfed children in developing countries. Washington, DC: Academy for Educational Development (AED); 2006.

    Google Scholar 

  136. 136.

    Institute of Nutrition of Central America and Panama. Guías alimentarias para Guatemala: los siete pasos para una alimentación sana. n.d.

  137. 137.

    Bermudez OI, Hernandez L, Mazariegos M, Solomons NW. Secular trends in food patterns of Guatemalan consumers: new foods for old. Food Nutr Bull. 2008;29(4):278–87.

    PubMed  Article  Google Scholar 

  138. 138.

    Chiplonkar SA, Tupe R. Development of a diet quality index with special reference to micronutrient adequacy for adolescent girls consuming a lacto-vegetarian diet. J Am Diet Assoc. 2010;110(6):926–31.

    CAS  PubMed  Article  Google Scholar 

  139. 139.

    Indian Council of Medical Research. Dietary Guidelines for Indians—A Manual. Hyderabad: National Institute of Nutrition; 2005. p. 8, 9, 13, 41, 6, 65, 6, 73.

    Google Scholar 

  140. 140.

    Department of Health and Human Services. Dietary Guidelines for Americans. In: Department of Health and Human Services and U.S. Department of Agriculture, editor; 2005.

    Google Scholar 

  141. 141.

    Prasetyo TJ, Hardinsyah, Sinaga T. Food and Nutrients Intake and Desirable Dietary Pattern Score of Indonesian Children Aged 2–6 Years. Jurnal Gizi Dan Pangan. 2013;8(3):159–66.

    Article  Google Scholar 

  142. 142.

    Food and Liverstock department of west Java Province. Hope Dietary Pattern Java, Indonesia. n.d. Available from: http://dkpp.jabarprov.go.id/page/Pola-Pangan-Harapan.

  143. 143.

    Fung T, Chiuve S, McCullough M, Rexrode K, Logroscino G, Hu F. Adherence to a DASH-Style diet and risk of coronary heart disease and stroke in women. Arch Intern Med. 2008;168(7):713–20.

    PubMed  Article  Google Scholar 

  144. 144.

    Asghari G, Yuzbashian E, Mirmiran P, Hooshmand F, Najafi R, Azizi F. Dietary Approaches to Stop Hypertension (DASH) Dietary Pattern Is Associated with Reduced Incidence of Metabolic Syndrome in Children and Adolescents. J Pediatr. 2016;174:178–84.e1.

    PubMed  Article  Google Scholar 

  145. 145.

    National Heart Lung aBI. Your Guide to Lowering Your Blood Pressure With DASH. In: United States Department of Health and Human Services NIoH, editor; 2006.

    Google Scholar 

  146. 146.

    Mohammad Hossein R, Maryam M, Nasrin O, Ahmad E, Leila A. Fast Food Consumption, Quality of Diet, and Obesity among Isfahanian Adolescent Girls. J Obes. 2012;2012(2012):597924.

    Google Scholar 

  147. 147.

    Thurlow J. Krause's Food and Nutrition Therapy, 12th Edition; 2008. p. 1861.

    Google Scholar 

  148. 148.

    Azadbakht L, Akbari F, Esmaillzadeh A. Diet quality among Iranian adolescents needs improvement. Public Health Nutr. 2015;18(4):615–21.

    PubMed  Article  Google Scholar 

  149. 149.

    Hooshmand F, Asghari G, Yuzbashian E, Mahdavi M, Mirmiran P, Azizi F. Modified Healthy Eating Index and Incidence of Metabolic Syndrome in Children and Adolescents: Tehran Lipid and Glucose Study. J Pediatr. 2018;197:134–9.e2.

    PubMed  Article  Google Scholar 

  150. 150.

    US Department of Agriculture. The Food Guide Pyramid. Washington, DC: US Department of Agriculture; 1992.

    Google Scholar 

  151. 151.

    Keshani P, Salehi M, Kaveh MH, Faghih S. Self-efficacy and cues to action: Two main predictors of modified version of diet quality index in Iranian adolescents. Progress Nutr. 2018;20(2):197–204.

    Google Scholar 

  152. 152.

    Kranz S, McCabe GP. Examination of the five comparable component scores of the diet quality indexes HEI-2005 and RC-DQI using a nationally representative sample of 2–18 year old children: NHANES 2003–2006. J Obes. 2013;2013:376314.

    PubMed  PubMed Central  Article  Google Scholar 

  153. 153.

    Fogli-Cawley JJ, Dwyer JT, Saltzman E, McCullough ML, Troy LM, Jacques PF. The 2005 Dietary Guidelines for Americans Adherence Index: development and application. J Nutr. 2006;136(11):2908.

    CAS  PubMed  Article  Google Scholar 

  154. 154.

    Mohseni-Takalloo S, Hosseini-Esfahani F, Mirmiran P, Azizi F. Associations of pre-defined dietary patterns with obesity associated phenotypes in Tehranian adolescents. Nutrients. 2016;8(8):505.

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  155. 155.

    Perry CP, Keane E, Layte R, Fitzgerald AP, Perry IJ, Harrington JM. The use of a dietary quality score as a predictor of childhood overweight and obesity Chronic Disease epidemiology. BMC Public Health. 2015;15(1):581.

    PubMed  PubMed Central  Article  Google Scholar 

  156. 156.

    Food Safety Authority of Ireland. Scientific Recommendations for Healthy Eating Guidelines in Ireland. 2011.

    Google Scholar 

  157. 157.

    Alkerwi A. Diet quality concept; 2014. p. 613–8.

    Google Scholar 

  158. 158.

    Gerber M. Qualitative methods to evaluate Mediterranean diet in adults. Public Health Nutrition. 2006;9(1a):147–51.

    PubMed  Article  Google Scholar 

  159. 159.

    Tarabusi V, Cavazza C, Pasqui F, Gambineri A, Pasquali R. Quality of diet, screened by the Mediterranean diet quality index and the evaluation of the content of advanced glycation endproducts, in a population of high school students from Emilia Romagna. Mediterranean J Nutr Metabol. 2010;3(2):153–7.

    Article  Google Scholar 

  160. 160.

    National Research Council Committee on Diet and Health. Diet and Health: Implications for Reducing Chronic Disease Risk. In: Food and Nutrition Board Commission on Life Sciences. Washington, DC: National Academy of Sciences; 1989.

    Google Scholar 

  161. 161.

    Food and Nutrition Board. Recommended Dietary Allowances. Washington, DC: National Academy of Sciences; 1989.

    Google Scholar 

  162. 162.

    Gerber MJ, Scali JD, Michaud A, Durand MD, Astre CM, Dallongeville J, et al. Profiles of a healthful diet and its relationship to biomarkers in a population sample from Mediterranean southern France. J Am Diet Assoc. 2000;100(10):1164–71.

    CAS  PubMed  Article  Google Scholar 

  163. 163.

    Nishimura T, Murakami K, Livingstone MBE, Sasaki S, Uenishi K. Adherence to the food-based Japanese dietary guidelines in relation to metabolic risk factors in young Japanese women. Br J Nutr. 2015;114(4):645–53.

    CAS  PubMed  Article  Google Scholar 

  164. 164.

    Kuriyama N, Murakami K, Livingstone MBE, Okubo H, Kobayashi S, Suga H, et al. Development of a food-based diet quality score for Japanese: associations of the score with nutrient intakes in young, middle-aged and older Japanese women. J Nutr Sci. 2016;5:e41.

    PubMed  PubMed Central  Article  Google Scholar 

  165. 165.

    Choi Y, You Y, Go KA, Tserendejid Z, You HJ, Lee JE, et al. The prevalence of obesity and the level of adherence to the Korean Dietary Action Guides in Korean preschool children. Nutr Res Pract. 2013;7(3):207–15.

    PubMed  PubMed Central  Article  Google Scholar 

  166. 166.

    Ministry of Health and Welfare. The 2003 Dietary Guidelines for Koreans-Dietary Action Guides for Infants & Toddlers: Pregnant & Lactating Women, Children, and Adolescents. Seoul: Ministry of Health and Welfare; 2003.

    Google Scholar 

  167. 167.

    Moursi MM, Arimond M, Dewey KG, Trèche S, Ruel MT, Delpeuch F. Dietary diversity is a good predictor of the micronutrient density of the diet of 6- to 23-month-old children in Madagascar. J Nutr. 2008;138(12):2448–53.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  168. 168.

    Onyango AW. Dietary diversity, child nutrition and health in contemporary African communities. Comp Biochem Physiol A. 2003;136(1):61–9.

    Article  CAS  Google Scholar 

  169. 169.

    FAO/WHO. Vitamin and mineral requirements in human nutrition.. Rome and Geneva. 2002.

    Google Scholar 

  170. 170.

    Institute of Medicine. Dietary reference intakes for calcium, phosphorus, magnesium, vitamin D and fluoride. Washington, DC: National Academy Press; 1997.

    Google Scholar 

  171. 171.

    Institute of Medicine. Dietary reference intakes for vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, vanadium and zinc: National Academy Press; 2003.

  172. 172.

    Chen L-W, Fung SM, Fok D, Leong LP, Toh JY, Lim HX, et al. The Development and Evaluation of a Diet Quality Index for Asian Toddlers and Its Perinatal Correlates: The GUSTO Cohort Study. Nutrients. 2019;11(3):535.

    CAS  PubMed Central  Article  PubMed  Google Scholar 

  173. 173.

    Health Promotion Board Singapore. A Healthy Food Foundation—For Kids and Teens. 2016.

    Google Scholar 

  174. 174.

    Lee T, Norimah A, Safiah M. Development of Healthy Eating Index for Malaysian adults. Proceedings of 26th Scientific Conference of the Nutrition Society of Malaysia; 2011.

    Google Scholar 

  175. 175.

    Rezali FW, Chin YS, Shariff ZM, Mohd Yusof BN, Sanker K, Woon FC. Evaluation of diet quality and its associated factors among adolescents in Kuala Lumpur, Malaysia. Nutr Res Pract. 2015;9(5):511–6.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  176. 176.

    Ministry of Health Malaysia. Malaysian Dietary Guidelines for Children and Adolescents: Summary. Putrajaya: Nutrition NCCoFa; 2013.

    Google Scholar 

  177. 177.

    Voortman T, Kiefte-de Jong JC, Geelen A, Villamor E, Moll HA, de Jongste JC, et al. The development of a diet quality score for preschool children and its validation and determinants in the Generation R Study. J Nutr. 2015;145(2):306–14.

    PubMed  Article  CAS  Google Scholar 

  178. 178.

    van der Velde LA, Nguyen AN, Schoufour JD, Geelen A, Jaddoe VW, Franco OH, et al. Diet quality in childhood: the Generation R Study. Eur J Nutr. 2019;58:1259–69.

  179. 179.

    Health Council of the Netherlands (Gezondheidsraad). Dutch Guidelines for a Healthy diet 2015.

    Google Scholar 

  180. 180.

    Netherlands Nutrition Centre. Dutch food-based dietary guidelines (Richtlijnen voedselkeuze). Voedingscentrum. 2011.

    Google Scholar 

  181. 181.

    Kersting MH. Annett. Erna¨hrung bei Kleinkindern: Empfehlungen und Erna¨hrungspraxis [Nutrition in infants: recommendations and nutritional practice]. J für Ernährungsmedizin. 2014;14(2):24–9.

    Google Scholar 

  182. 182.

    Schweizerische Gesellschaft. fu¨r Erna¨hrung. Erna¨hrung von Kindern [Nutrition of children]. 2011.

    Google Scholar 

  183. 183.

    Flemish Institute for Health Promotion and Disease Prevention. De actieve voedingsdriehoek [The Active Food Guide Pyramid]. Brussels; 2012. p. 37.

  184. 184.

    Public Health Agency. Maternal and pre-school child nutrition guidelines. Belfast; 2012.

  185. 185.

    US Department of Health and Human Services. Dietary guidelines for Americans. Agriculture UDo, editor; 2010. p. 79–80.

    Google Scholar 

  186. 186.

    Skinner AC, Skelton JA. Prevalence and Trends in Obesity and Severe Obesity Among Children in the United States, 1999–2012. JAMA Pediatr. 2014;168(6):561–6.

    PubMed  Article  Google Scholar 

  187. 187.

    Cattaneo A, Williams C, Pallás-Alonso CR, Hernández-Aguilar MT, Lasarte-Velillas JJ, Landa-Rivera L, et al. ESPGHAN's 2008 recommendation for early introduction of complementary foods: how good is the evidence? Matern Child Nutr. 2011;7(4):335–43.

    PubMed  PubMed Central  Article  Google Scholar 

  188. 188.

    Imhoff-Kunsch B, Briggs V, Goldenberg T, Ramakrishnan U. Effect of n-3 Long-chain Polyunsaturated Fatty Acid Intake during Pregnancy on Maternal, Infant, and Child Health Outcomes: A Systematic Review. Paediatr Perinatal Epidemiol. 2012;26:91–107.

    Article  Google Scholar 

  189. 189.

    Delshad M, Beck KL, von Hurst PR, Mugridge O, Conlon CA. The validity and reliability of the Dietary Index for a Child's Eating (DICE) in 2–8 year old children living in New Zealand. Matern Child Nutr. 2018;15:e12758.

    Google Scholar 

  190. 190.

    NZ Ministry of Health. Food and Nutrition Guidelines for Healthy Children and Young People (Aged 2–18 Years). Wellington: NZ Ministry of Health; 2012.

    Google Scholar 

  191. 191.

    NZ Ministry of Health. Nutrient reference values for Australia and New Zealand, (including recommended dietary intakes). Wellington: NZ Ministry of Health; 2005.

    Google Scholar 

  192. 192.

    Wong J, Parnell W, Howe A, Black K, Skidmore P. Development and validation of a food-based diet quality index for New Zealand adolescents. BMC Public Health. 2013;13(1).

  193. 193.

    NZ Ministry of Health. Food and Nutrition Guidelines for Healthy Adolescents: A background paper. Wellington: NZ Ministry of Health; 1998.

    Google Scholar 

  194. 194.

    Wong JE, Skidmore PML, Williams SM, Parnell WR. Healthy dietary habits score as an indicator of diet quality in New Zealand adolescents. J Nutr. 2014;144(6):937.

    CAS  PubMed  Article  Google Scholar 

  195. 195.

    Handeland K, Kjellevold M, Wik Markhus M, Eide Graff I, Frøyland L, Lie Ø, et al. A Diet Score Assessing Norwegian Adolescents’ Adherence to Dietary Recommendations-Development and Test-Retest Reproducibility of the Score. Nutrients. 2016;8(8):467.

    PubMed Central  Article  PubMed  Google Scholar 

  196. 196.

    Helsedirektoratet (Norwegian Directorate of Health). Nutrition Recommendations to Promote Public Health and Prevent Chronic Diseases. Oslo: Helsedirektoratet (Norwegian Directorate of Health); 2011.

  197. 197.

    Kennedy GL, Pedro MR, Seghieri C, Nantel G, Brouwer I. Dietary diversity score is a useful indicator of micronutrient intake in non-breast-feeding Filipino children. J Nutr. 2007;137(2):472–7.

    CAS  PubMed  Article  Google Scholar 

  198. 198.

    Vilela S, Oliveira A, Ramos E, Moreira P, Barros H, Lopes C. Association between energy-dense food consumption at 2 years of age and diet quality at 4 years of age. 2014;111(7):1275–1282.

  199. 199.

    World Health Organisation. Food and Nutrition Policy for Schools: A Tool for the Development of School Nutrition Programmes in the European Region.. In: Europe TROf, editor. Copenhagen2006.

  200. 200.

    Ríos EM, Sinigaglia O, Diaz B, Campos M, Palacios C. Development of a Diet Quality Score for Infants and Toddlers and its association with weight. Journal of nutritional health & food science. 2016;4(4).

  201. 201.

    Women I, and Children (WIC),. Infant Feeding Guide, A Guide for Use in the WIC and CSF Programs. Washington, DC2009.

  202. 202.

    World Health Organisation. Guiding Principles for Complementary Feeding of the Breastfeed Child.. In: Pan American Health Organization, editor. Washington, DC2001.

  203. 203.

    American Academy of Pediatrics. Food and Feeding 2011.

  204. 204.

    Crombie IK, Kiezebrink K, Irvine L, Wrieden WL, Swanson V, Power K, et al. What maternal factors influence the diet of 2-year-old children living in deprived areas? A cross-sectional survey. Public Health Nutr. 2009;12(8):1254–60.

    PubMed  Article  Google Scholar 

  205. 205.

    Caroline Walker Trust. Eating Well for Under-5s in Care. Report of an Expert Working Group. In: Lomdon; 1998.

    Google Scholar 

  206. 206.

    Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. The New England journal of medicine. 2003;348(26):2599–608.

    PubMed  Article  PubMed Central  Google Scholar 

  207. 207.

    Mariscal-Arcas M, Velasco J, Monteagudo C, Caballero-Plasencia MA, Lorenzo-Tovar ML, Olea-Serrano F. Comparison of methods to evaluate the quality of the Mediterranean diet in a large representative sample of young people in Southern Spain. Nutricion hospitalaria. 2010;25(6):1006.

    CAS  PubMed  PubMed Central  Google Scholar 

  208. 208.

    Mariscal-Arcas M, Romaguera D, Rivas A, Feriche B, Pons A, Tur JA, et al. Diet quality of young people in southern Spain evaluated by a Mediterranean adaptation of the Diet Quality Index-International (DQI-I). Br J Nutr. 2007;98(6):1267–73.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  209. 209.

    World Health Organisation. Preparation and Use of Food-Based Dietary Guidelines. Report of a Joint FAO/WHO Consultation. Cyprus: Nicosia; 1996.

    Google Scholar 

  210. 210.

    U.S. Department of Agriculture (USDA). Dietary Guidelines from Around the World. In: Food and Nutrition Information Center; 2001.

    Google Scholar 

  211. 211.

    INFH-CAPM (Institute of Nutrition and Food Hygiene CAoPM. The Food Consumption Tables.. House PsMP, editor. n.d.

  212. 212.

    SBCNS (Standing Board of the Chinese Nutrition Society). Dietary guidelines and the food guide pagoda for Chinese residents, balanced diet, rational nutrition and health promotion.. 1999.

    Google Scholar 

  213. 213.

    Ortega R, Lopez-Sobaler AM, Requejo AM, Andre’s P. La composicio’n de los alimentos. Madrid: Herramienta ba’sica para la valoracio’n nutricional; 2004.

    Google Scholar 

  214. 214.

    Serra-Majem L, Ribas L, Ngo J, Ortega RM, Garcia A, Perez-Rodrigo C, et al. Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents. Public Health Nutr. 2004;7(7):931–5.

    PubMed  Article  Google Scholar 

  215. 215.

    Serra M. ¿Ma’s beneficios de la dieta mediterra’nea? Nutricio’n y Obesidad. 2001;4:43–6.

    Google Scholar 

  216. 216.

    Monteagudo C, Palacín-Arce A, del Mar Bibiloni M, Pons A, Tur JA, Olea-Serrano F, et al. Proposal for a Breakfast Quality Index (BQI) for children and adolescents. Public Health Nutr. 2012;16(4):639–44.

    PubMed  Article  Google Scholar 

  217. 217.

    Arimond M, Cohen, R., Dewey, K., Ruel, M. Developing and validating simple indicators of complementary food intake and nutrient density for infants and young children in developing countries: protocol for data analysis.. Washington; 2005.

    Google Scholar 

  218. 218.

    National Research Council. Diet and Health Implications for Reducing Chronic Disease Risk. Washington, DC: Committee on Diet and Health FaNB, Commission on Life Sciences; 1989.

    Google Scholar 

  219. 219.

    U.S Department of Health and Human Services. The Surgeon General’s Report on Nutrition and Health. Washington, DC: US Government Printing Office; 1988.

    Google Scholar 

  220. 220.

    Chiang P-H, Wahlqvist ML, Lee M-S, Huang L-Y, Chen H-H, ST-Y H. Fast-food outlets and walkability in school neighbourhoods predict fatness in boys and height in girls: a Taiwanese population study. Public Health Nutr. 2011;14(9):1601.

    PubMed  Article  Google Scholar 

  221. 221.

    Lee MS, Huang LY, Chang YH, Huang STY, Yu HL, Wahlqvist ML. Lower birth weight and diet in Taiwanese girls more than boys predicts learning impediments. Res Dev Disabil. 2012;33(6):2203–12.

    PubMed  Article  Google Scholar 

  222. 222.

    U.S Department of Agriculture. Nutrition and Your Health: Dietary Guidelines for Americans. Washington, DC; 1995.

  223. 223.

    Chen YC, Huang YC, Lo YTC, Wu HJ, Wahlqvist ML, Lee MS. Secular trend towards ultra-processed food consumption and expenditure compromises dietary quality among Taiwanese adolescents. Food Nutr Res. 2018;62.

  224. 224.

    Ruel MT, Menon P. Child feeding practices are associated with child nutritional status in Latin America: innovative uses of the demographic and health surveys. J Nutr. 2002;132(6):1180–7.

    CAS  PubMed  Article  Google Scholar 

  225. 225.

    World Health Organisation. Complementary feeding of young children in developing countries. A review of current scientific knowledge. Geneva; 1998.

  226. 226.

    Academy for Educational Development (AED). Recommended feeding and dietary practices to improve infant and maternal nutrition. Washington, DC; 1999.

  227. 227.

    T Kennedy E, Ohls J, Carlson S, Fleming K. The healthy eating index: design and applications. J Am Dietetic Assoc. 1995;95(10):1103–8.

    Article  Google Scholar 

  228. 228.

    Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, et al. Update of the healthy eating index: HEI-2010. J Acad Nutr Diet. 2013;113(4):569–80.

    PubMed  Article  Google Scholar 

  229. 229.

    US Department of Agriculture. Nutrients in 2010 USDA Food Patterns at all calorie levels. In: Center for Nutrition Policy and Promotion, editor; 2020.

    Google Scholar 

  230. 230.

    Britten P, Marcoe K, Yamini S, Davis C. Development of Food Intake Patterns for the MyPyramid Food Guidance System. J Nutr Educ Behav. 2006;38(6, Supplement 1):S78–92.

    PubMed  Article  Google Scholar 

  231. 231.

    Guenther PM, Reedy J, Krebs-Smith SM. Development of the healthy eating index-2005. J Am Diet Assoc. 2008;108(11):1896–901.

    PubMed  Article  Google Scholar 

  232. 232.

    Marcoe K, Juan W, Yamini S, Carlson A, Britten P. Development of Food Group Composites and Nutrient Profiles for the MyPyramid Food Guidance System. J Nutr Educ Behav. 2006;38(6):S93–S107.

    PubMed  Article  Google Scholar 

  233. 233.

    Kranz S, Siega-Riz AM, Herring AH. Changes in diet quality of American preschoolers between 1977 and 1998. Am J Public Health. 2004;94(9):1525–30.

    PubMed  PubMed Central  Article  Google Scholar 

  234. 234.

    US Dept of Agriculture. The Food Guide Pyramid for Young Children 2 to 6 Years Old. In: Center for Nutrition Policy and Promotion, editor. US Dept of Agriculture; 1998.

  235. 235.

    Kranz S, Hartman T, Siega-Riz AM, Herring AH. A Diet Quality Index for American Preschoolers Based on Current Dietary Intake Recommendations and an Indicator of Energy Balance. J Am Diet Assoc. 2006;106(10):1594–604.

    PubMed  Article  Google Scholar 

  236. 236.

    Marshall TA, Eichenberger Gilmore JM, Broffitt B, Stumbo PJ, Levy SM. Diet Quality in Young Children Is Influenced by Beverage Consumption. J Am College Nutr. 2005;24(1):65–75.

    Article  Google Scholar 

  237. 237.

    Institute of Medicine of the National Academy of Sciences. Dietary Reference Intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids—Macronutrients. Washington, DC: National Academies Press; 2002.

    Google Scholar 

  238. 238.

    Cox DR, Skinner JD, Carruth BR, Moran Iii J, Houck KA. Food Variety Index for Toddlers (VIT): Development and Application. J Am Diet Assoc. 1997;97(12):1382–6.

    CAS  PubMed  Article  Google Scholar 

  239. 239.

    Skinner JD, Carruth BR, Houck KS, Bounds W, Morris M, Cox DR, et al. Longitudinal study of nutrient and food intakes of white preschool children aged 24 to 60 months. J Am Diet Assoc. 1999;99(12):1514–21.

    CAS  PubMed  Article  Google Scholar 

  240. 240.

    Sharafi M, Peracchio H, Scarmo S, Huedo-Medina TB, Mayne ST, Cartmel B, et al. Preschool-Adapted Liking Survey (PALS): A brief and valid method to assess dietary quality of preschoolers. Childhood Obes. 2015;11(5):530–40.

    Article  Google Scholar 

  241. 241.

    Drewnowski A. Defining nutrient density: development and validation of the nutrient rich foods index. J Am College Nutr. 2009;28(4):421S–6S.

    CAS  Article  Google Scholar 

  242. 242.

    The American Dietetic Association. Practice paper of : nutrient density: meeting nutrient goals within calorie needs. J Am Diet Assoc. 2007;107:860–9.

    Article  Google Scholar 

  243. 243.

    Chiuve SE, Fung TT, Rimm EB, Hu FB, McCullough ML, Wang M, et al. Alternative dietary indices both strongly predict risk of chronic disease. J Nutr. 2012;142(6):1009–18.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  244. 244.

    Harris HR, Willett WC, Vaidya RL, Michels KB. Adolescent dietary patterns and premenopausal breast cancer incidence. Carcinogenesis. 2016;37(4):376–84.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  245. 245.

    McCullough ML, Feskanich D, Stampfer MJ, Giovannucci EL, Rimm EB, Hu FB, et al. Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. Am J Clin Nutr. 2002;76(6):1261–71.

    CAS  PubMed  Article  Google Scholar 

  246. 246.

    Fung TT, McCullough M, van Dam RM, Hu FB. A Prospective Study of Overall Diet Quality and Risk of Type 2 Diabetes in Women. Diabetes Care. 2007;30(7):1753–7.

    PubMed  Article  Google Scholar 

  247. 247.

    Belin RJ, Greenland P, Allison M, Martin L, Shikany JM, Larson J, et al. Diet quality and the risk of cardiovascular disease: the Women’s Health Initiative (WHI). Am J Clin Nutr. 2011;94(1):49–57.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  248. 248.

    Feskanich D, Rockett HR, Colditz GA. Modifying the Healthy Eating Index to assess diet quality in children and adolescents. J Am Diet Assoc. 2004;104(9):1375–83.

    PubMed  Article  Google Scholar 

  249. 249.

    U.S Department of Agriculture. Nutrition and Your Health: Dietary Guidelines for Americans. Washington, DC: Office UGP; 2000.

    Google Scholar 

  250. 250.

    Patterson RE, Haines PS, Popkin BM. Diet Quality Index: Capturing a multidimensional behavior. J Am Diet Assoc. 1994;94(1):57–64.

    CAS  PubMed  Article  Google Scholar 

  251. 251.

    Kim S, Haines PS, Siega-Riz AM, Popkin BM. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J Nutr. 2003;133(11):3476–84.

    CAS  PubMed  Article  Google Scholar 

  252. 252.

    Setayeshgar S, Maximova K, Ekwaru JP, Gray-Donald K, Henderson M, Paradis G, et al. Diet quality as measured by the Diet Quality Index–International is associated with prospective changes in body fat among Canadian children. Public Health Nutrition. 2017;20(3):456–63.

    PubMed  Article  Google Scholar 

  253. 253.

    Falciglia GA, Troyer AG, Couch SC. Dietary Variety Increases as a Function of Time and Influences Diet Quality in Children. J Nutr Educ Behav. 2004;36(2):77–83.

    PubMed  Article  Google Scholar 

  254. 254.

    Martin-Calvo N, Chavarro JE, Falbe J, Hu FB, Field AE. Adherence to the Mediterranean dietary pattern and BMI change among US adolescents. Int J Obes. 2016;40(7):1103–8.

    CAS  Article  Google Scholar 

  255. 255.

    Mediterránea. FD. Pirámide de la diéta mediterránea: un estilo de vida actual. Guía para la población adulta. 2010. Available from: http://dietamediterranea.com/piramide-dietamediterranea/.

  256. 256.

    Anderson S, Kaye G, Andridge R, Smathers C, Peng J, Pirie P. Interrelationships of More Healthful and Less Healthful Aspects of Diet Quality in a Low-Income Community Sample of Preschool-Aged Children. Matern Child Health J. 2015;19(12):2663–72.

    PubMed  Article  Google Scholar 

  257. 257.

    US Department of Agriculture. Health and nutrition information for preschoolers. 2014.

    Google Scholar 

  258. 258.

    Au LE, Gurzo K, Paolicelli C, Whaley SE, Weinfield NS, Ritchie LD. Diet Quality of US Infants and Toddlers 7–24 Months Old in the WIC Infant and Toddler Feeding Practices Study-2. J Nutr. 2018;148(11):1786–93.

    PubMed  Article  Google Scholar 

  259. 259.

    Mursu J, Steffen LM, Meyer KA, Duprez D, Jacobs DR. Diet quality indexes and mortality in postmenopausal women: the Iowa Women's Health Study. Am J Clin Nutr. 2013;98(2):444.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  260. 260.

    Hu T, Jacobs DR, Larson NI, Cutler GJ, Laska MN, Neumark-Sztainer D. Higher Diet Quality in Adolescence and Dietary Improvements Are Related to Less Weight Gain During the Transition From Adolescence to Adulthood. J Pediatr. 2016;178:188–93.e3.

    PubMed  PubMed Central  Article  Google Scholar 

  261. 261.

    Günther AL, Liese AD, Bell RA, Dabelea D, Lawrence JM, Rodriguez BL, et al. Association between the dietary approaches to hypertension diet and hypertension in youth with diabetes mellitus. Hypertension. 2009;53(1):6–12.

    PubMed  Article  CAS  Google Scholar 

  262. 262.

    Materials Research Society. World Bank classifications for developing countries 2019. Available from: https://www.mrs.org/developing-countries-list.

    Google Scholar 

  263. 263.

    Centres for Disease Control and Prevention. National health and nutrition examination survey 2019. Available from: https://www.cdc.gov/nchs/nhanes/index.htm.

    Google Scholar 

  264. 264.

    Vicente-Rodriguez G, Libersa C, Mesana MI, Béghin L, Iliescu C, Moreno Aznar LA, Dallongeville J, Gottrand F. Healthy Lifestyle by Nutrition in Adolescence (HELENA). A New EU Funded Project. Société Française de Pharmacologie et de Thérapeutique. 2007;62(3):259–70.

    Google Scholar 

  265. 265.

    Golley RK, McNaughton SA, Hendrie GA. A dietary guideline adherence score is positively associated with dietary biomarkers but not lipid profile in healthy children. The Journal of nutrition. 2015;145(1):128.

    CAS  PubMed  Article  Google Scholar 

  266. 266.

    Toffano R, Hillesheim E, Mathias M, Coelho-Landell C, Salomão R, Almada M, et al. Validation of the Brazilian Healthy Eating Index-Revised Using Biomarkers in Children and Adolescents. Nutrients. 2018;10(2).

  267. 267.

    Aramouny E, Sacy R, Chokr I, Joudy B. Local Validation Study for NutricheQ Tool in Lebanon. J Comprehensive Pediatr. 2018. In Press.

  268. 268.

    Delshad M, Beck KL, Von Hurst PR, Mugridge O, Conlon CA. The validity and reliability of the Dietary Index for a Child's Eating in 2–8-year old children living in New Zealand. Maternal Child Nutr. 2018;15:e12758.

    Google Scholar 

  269. 269.

    Golley RK, Smithers LG, Mittinty MN, Emmett P, Northstone K, Lynch JW. Diet quality of U.K. infants is associated with dietary, adiposity, cardiovascular, and cognitive outcomes measured at 7–8 years of age. J Nutr. 2013;143(10):1611–7.

  270. 270.

    Hurley KM, Oberlander SE, Merry BC, Wrobleski MM, Klassen AC, Black MM. The healthy eating index and youth healthy eating index are unique, nonredundant measures of diet quality among low-income, African American adolescents. J Nutr. 2009;139(2):359.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  271. 271.

    Lazarou C, Panagiotakos DB, Spanoudis G, Matalas A-L. E-KINDEX: A Dietary Screening Tool to Assess Children's Obesogenic Dietary Habits. J Am College Nutr. 2011;30(2):100–12.

    Article  Google Scholar 

  272. 272.

    Moursi M, Treche S, Martin-Prevel Y, Maire B, Delpeuch F. Association of a summary index of child feeding with diet quality and growth of 6–23 months children in urban Madagascar. Eur J Clin Nutr. 2009;63(6):718.

    CAS  PubMed  Article  Google Scholar 

  273. 273.

    Barnes TL, Crandell JL, Bell RA, Mayer-Davis EJ, Dabelea D, Liese AD. Change in DASH diet score and cardiovascular risk factors in youth with type 1 and type 2 diabetes mellitus: The SEARCH for Diabetes in Youth Study. Nutr Diabetes. 2013;3:e91.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  274. 274.

    Liese AD, Bortsov A, Gunther AL, Dabelea D, Reynolds K, Standiford DA, et al. Association of DASH diet with cardiovascular risk factors in youth with diabetes mellitus: the SEARCH for Diabetes in Youth study. Circulation. 2011;123(13):1410–7.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  275. 275.

    Jacka FN, Kremer PJ, Berk M, de Silva-Sanigorski AM, Moodie M, Leslie ER, et al. A prospective study of diet quality and mental health in adolescents. PLoS One. 2011;6(9):e24805.

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Acknowledgements

Thank you to David Honeyman and Bronwyn Linthwaite for their assistance with the search strategy and assistance with databases throughout the screening process. Thank you to Fiona Eberhardt for her assistance and support to the study authors during the implementation of this review. Thank you to Ann Zhang with assistance in translating a paper to English.

Funding

This study received no specific funding. CC is supported by an Australian National Health and Medical Research Council (NHMRC) of Australia Senior Research Fellowship and a University of Newcastle, Faculty of Health and Medicine, Gladys M Brawn Senior Research Fellowship. TB is supported by a NHMRC investigator grant. SM is partially supported by a Commonwealth of Australia Innovations Connections Grant.

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PD led the design of the study, data extraction, and manuscript drafting. PD and SM performed record screening. All authors contributed to assessment of the risk of bias and revision of the manuscript. The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Skye Marshall.

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Competing interests

SM, TB, and CC have designed, validated, and published several of the DQIs reviewed in this paper. The authors of this review report no other existing or potential conflicts of interest; financial or otherwise.

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Appendix

Appendix

Table 5 Full systematic search strategy and search results implemented across five electronic databases

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Dalwood, P., Marshall, S., Burrows, T.L. et al. Diet quality indices and their associations with health-related outcomes in children and adolescents: an updated systematic review. Nutr J 19, 118 (2020). https://doi.org/10.1186/s12937-020-00632-x

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Keywords

  • Diet quality, diet index, pediatrics
  • Child
  • Infant
  • Adolescent
  • Nutrition assessment
  • Child development
  • Non-communicable diseases
  • Systematic review