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Development and evaluation of an index assessing adherence to the Norwegian food-based dietary guidelines: the … – BioMed Central

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We found that the NDGI captured variance in adherence to dietary guidelines on a continuous scale. Hence, it represents a suitable tool for monitoring trends in adherence to the Norwegian FBDGs. It also has the potential to identify dietary challenges and specific subgroups of importance, which altogether may help guide priorities in public health policies.

The mean score of 65 out of 100 (range 21–99), where 100 would represent a diet adhering to the Norwegian FBDGs, suggests that the adult population of Norway has a potential of improved adherence to the FBDGs. Results from the latest nationally representative dietary survey among adults in Norway from 2010–11 indicated that each of the FBDGs was achieved by between 15 to 45% of men and 13 to 67% of women [28]. Vegetable intake accounted for the lowest percentage and red meat intake to the highest percentage of adherence in both sexes. In the same population, between 5 and 65% had high adherence to each of 12 dietary components as reflected in the FBDGs according to the Norwegian Diet Index [22].

The specific FBDGs differ somewhat between countries, and dietary indices across countries do not cover all the same aspects of dietary recommendations and FBDGs [14]. Findings in studies using different dietary indices are therefore not directly comparable. However, similar adherence to the FBDGs measured through dietary quality indices has been described in previous population studies from Australia and Denmark [16, 17]. A score closer to half-way adherence was observed in other European countries [18, 30], the United States [31], and more recently in Vietnam [20]. In the United States, a decrease in diet quality between 2011–2018 in adults was shown using a FBDG index, with a significant change in score from 55% in 2011–2012 to 53% in 2017–2018 [31].

The distribution of sociodemographic characteristics across quintiles of NDGI scores shows the ability of the index to capture population variation in diet quality. Overall, women, and participants of older age, higher education and better self-perceived household economy, had better adherence to the Norwegian FBDGs. This is expected and consistent with findings from testing other food-based indices [16,17,18, 20, 30] or a combination of nutrient- and food-based indices [19, 26]. Better adherence to the FBDGs in women has also been reported in other countries [16, 17, 26]. The association between higher age and adherence to FBDGs in our sample has consistently been reported in other Norwegian representative samples [28, 32] as well as in population-based surveys in other countries [16,17,18,19, 26]. Older individuals may follow FBDGs to a larger extent as they may be more health conscious and independent in old age [33]. In Norway, older generations tend to eat more traditional dishes rather than dishes of different origins, eat less fast foods and in restaurants than younger individuals, although they more often eat out in shopping centers and cafes than middle aged adults [34]. Higher education [19, 28] and better socioeconomic position [19] have consistently been associated with a better adherence to the FBDGs in Scandinavian studies, as in other parts of the world [16, 20]. However, two studies from the Netherlands [30] and Spain [18] did not find an association between adherence to the dietary guidelines and education.

Smoking was used as a proxy to whether the NDGI was able to detect differences in scores by health behavior between groups of people with known differences in diet quality. Better adherence to the FBDGs was found for non-smokers, which agrees with findings in other studies [18, 26, 30].

Methodological considerations

The NDGI was developed to evaluate adherence of habitual dietary intake to the Norwegian FBDGs. The implementation of an index measuring adherence to Norwegian FBDGs is of importance in a nutrition surveillance perspective. The tool is based on a short food frequency questionnaire with 19 items. In comparison, the Norwegian Diet Index, recently published by the University of Oslo, is aiming to measure a healthy diet and a healthy lifestyle in line with the national guidelines in Norway [22]. However, its practicality as a nutrition surveillance tool in large-scale public health surveys may be limited due to its requirement for more detailed information. Yet another index has been developed to measure adherence to a New Nordic Diet, measuring adherence to an environmentally sustainable and healthy Nordic diet rather than the Norwegian FBDGs [24]. The NDGI is developed with the purpose to measure adherence to the Norwegian FBDGs as communicated by the Norwegian Directorate of Health [12], with the possibility to be carried out in a frequent manner in larger population groups. The use of the NDGI is based on the proposed short food frequency questionnaire but is also feasible to apply on more comprehensive data sources, such as larger food frequency questionnaires, 24 h recalls and food records, provided that data on the specific components are included.

Each component in the NDGI was given a standard for maximum and minimum score, based on a rationale derived from quantitative and qualitative FBDGs where applicable. Intake frequency in the population was also considered, to ensure distribution of scores in the total NDGI score. Similar to the Healthy Eating Index [26], the index gave a maximum of 60 points (out of 100) to components to eat in adequacy, and 40 points allocated to components to be consumed in moderation. The level of detail between the two indices differs extensively, as the Healthy Eating Index is based on a much more comprehensive tool, measuring alignment of nutrients in addition to the FBDGs. In contrast to the Healthy Eating Index, the NDGI does not capture all aspects such as the fat content in meat and dairy products.

The median population-weighted score for each component in the NDGI shows that all have potential to improve the NDGI score. Using principal component analysis, we found the index to be multidimensional and predominantly three patterns explained the most variance in scores. These findings indicate that dietary behavior in accordance with the FBDGs is not a unidimensional construct where all factors that contribute to a healthy diet are strongly correlated. Rather, the score captures several dimensions or dietary patterns. This corresponds with the findings for evaluation of the American Healthy Eating Index [26].

The intercorrelations between components in the NDGI score were between -0.06 to 0.59, and the Cronbach’s alpha was 0.50 indicating a low to moderate internal consistency of the components in the score. This agrees with the finding of multidimensionality, as all people do not necessarily meet all the same aspects of the FBDGs. As mentioned by Reedy et al. when an index is multidimensional, captures a full diet, and is evaluated in an entire population, a lower Cronbach’s alpha is expected [26].

Implications

The NDGI is calculated based on a compact tool that is suitable for being incorporated in large public health surveys. Hence, it may aid in following time trends in adherence to the FBDGs in the adult population and subgroups living in Norway, by synthesizing several dietary components into one overall score. The NDGI can be used in nutrition surveillance for monitoring trends in food choices over time and may thus provide a basis for planning, prioritizing, and targeting public health policy aimed to improve diet, also in subgroups of age, sex, and socioeconomic factors. Additionally, the NDGI can be used as an indicator of diet quality when studying associations between lifestyle factors and health outcomes. The NDGI is flexible and could be adapted to updated country specific guidelines and may also be an applicable instrument in other countries or settings with comparable FBDGs.

When applying the NDGI in the current sample, we observed that men and individuals with low education had the greatest potential for improving their diet to correspond with the FBDGs. Furthermore, the FBDGs covering fruit, vegetables, wholegrain and dairy (milk/yoghurt) obtained the lowest relative median component scores of adherences and hold a large potential for improvement. Thus, these FBDGs should be given more attention when trying to improve adherence to the FBDGs in the population. Further studies are required to validate the dietary questions included in the NDGI, and to investigate associations between the NDGI and health outcomes in longitudinal studies.

Strengths and limitations

Although the NDGI does not capture all aspects in the FBDGs, it provides a continuous score suitable for capturing important parts of the dietary complexity and adherence to the Norwegian FBDGs in a relatively simple way. With reasonable participation and few missing values, this may indicate a feasible tool to be used in larger public health surveys. We consider this as a strength and to be of interest to public health researchers and to policy- and decision makers.

A limitation of the study is that dietary intake was self-reported, which may introduce bias either consciously or unconsciously. The use of a food frequency questionnaire relies on the self-report of data retrospectively, which may be affected by the ability to accurately recall information. Another limitation is the lack of knowledge about the degree to which the questionnaire reflects the actual diet in the population. A study of the relative validity of these dietary questions is planned in the ongoing national dietary survey among adults in Norway. The lack of additional details about dietary intake from the food frequency questionnaire hindered us from evaluating some of the specific recommendations in the FBDGs such as portion sizes and specific advice on food quality, such as the content of fat in meat and dairy products. As some of the FBDGs do not include quantitative measures, a pragmatic and partly data driven approach was used to include both quantitative and qualitative guidelines in the weighing of components, which may have influenced the scoring of the NDGI.

The study population was limited to adults, and thus there is a lack of generalizability to children and adolescents. The National Public Health Survey had a 38% participation rate. Of the individuals who were unreachable by phone or e-mail, 56% were aged above 75 years, and the web-based questionnaire was probably not adequate to capture the variance in diet in the oldest part of the population in Norway. Self-reported education and self-perceived household economy may not necessarily reflect the equivalent data in official registries but did still capture variance in adherence in the diet. Additionally, the design of the study may introduce healthy volunteer bias. Notwithstanding these limitations, our study was based on a representative sample of adults living in Norway.

The scoring of components was made on a continuous scale between minimum and maximum cut-off points, which allows for preserving the statistical power of the data. However, the score did not account for food habits other than the FBDGs, such as with a restricted diet or alternative dietary regimes. Despite the lack of details in the scoring of components, measurement errors are expected to be consistent over time, and the NDGI may as such be suitable to monitor adherence to FBDG if repeated over time. The NDGI can be used in nutrition surveillance as a diet quality tool to complement the more extensive national dietary surveys.

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