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      Development of a Healthy Dietary Habits Index for New Zealand Adults

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          Abstract

          Healthful dietary habits are individually associated with better nutrient intake and positive health outcomes; however, this information is rarely examined together to validate an indicator of diet quality. This study developed a 15-item Healthy Dietary Habits Index (HDHI) based on self-reported dietary habits information collected in the 2008/09 New Zealand Adult Nutrition Survey. The validity of HDHI as a diet quality index was examined in relation to sociodemographic factors, 24-diet recall derived nutrient intakes, and nutritional biomarkers in a representative sample of adults aged 19 years and above. Linear regression models were employed to determine associations between HDHI quintiles and energy-adjusted nutrient data and nutritional biomarkers. Significantly higher HDHI scores were found among women, older age groups, Non-Māori or Pacific ethnic groups, and less socioeconomically-deprived groups (all p < 0.001). Increasing quintiles of HDHI were associated with higher intakes of dietary fibre and seven micronutrients including calcium, iron, and vitamin C, and lower intakes of energy, macronutrients, sodium, zinc, vitamins B6 and B12. Associations in the expected directions were also found for urinary sodium, whole blood folate, serum and red blood cell folate, and plasma selenium (all p < 0.001). The present findings suggest that the HDHI is a valid measure of diet quality as it is capable of discerning quality of diets of subgroups and ranking nutrient intakes among NZ adults.

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          Most cited references 35

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Adjustment for total energy intake in epidemiologic studies.

            In epidemiologic studies, total energy intake is often related to disease risk because of associations between physical activity or body size and the probability of disease. In theory, differences in disease incidence may also be related to metabolic efficiency and therefore to total energy intake. Because intakes of most specific nutrients, particularly macronutrients, are correlated with total energy intake, they may be noncausally associated with disease as a result of confounding by total energy intake. In addition, extraneous variation in nutrient intake resulting from variation in total energy intake that is unrelated to disease risk may weaken associations. Furthermore, individuals or populations must alter their intake of specific nutrients primarily by altering the composition of their diets rather than by changing their total energy intake, unless physical activity or body weight are changed substantially. Thus, adjustment for total energy intake is usually appropriate in epidemiologic studies to control for confounding, reduce extraneous variation, and predict the effect of dietary interventions. Failure to account for total energy intake can obscure associations between nutrient intakes and disease risk or even reverse the direction of association. Several disease-risk models and formulations of these models are available to account for energy intake in epidemiologic analyses, including adjustment of nutrient intakes for total energy intake by regression analysis and addition of total energy to a model with the nutrient density (nutrient divided by energy).
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              Does social class predict diet quality?

              A large body of epidemiologic data show that diet quality follows a socioeconomic gradient. Whereas higher-quality diets are associated with greater affluence, energy-dense diets that are nutrient-poor are preferentially consumed by persons of lower socioeconomic status (SES) and of more limited economic means. As this review demonstrates, whole grains, lean meats, fish, low-fat dairy products, and fresh vegetables and fruit are more likely to be consumed by groups of higher SES. In contrast, the consumption of refined grains and added fats has been associated with lower SES. Although micronutrient intake and, hence, diet quality are affected by SES, little evidence indicates that SES affects either total energy intakes or the macronutrient composition of the diet. The observed associations between SES variables and diet-quality measures can be explained by a variety of potentially causal mechanisms. The disparity in energy costs ($/MJ) between energy-dense and nutrient-dense foods is one such mechanism; easy physical access to low-cost energy-dense foods is another. If higher SES is a causal determinant of diet quality, then the reported associations between diet quality and better health, found in so many epidemiologic studies, may have been confounded by unobserved indexes of social class. Conversely, if limited economic resources are causally linked to low-quality diets, some current strategies for health promotion, based on recommending high-cost foods to low-income people, may prove to be wholly ineffective. Exploring the possible causal relations between SES and diet quality is the purpose of this review.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                03 May 2017
                May 2017
                : 9
                : 5
                Affiliations
                [1 ]School of Healthcare Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia; wjeiin@ 123456ukm.edu.my
                [2 ]Department of Human Nutrition, University of Otago, Dunedin 9054, New Zealand; jillian.haszard@ 123456otago.ac.nz (J.J.H.); winsome.parnell@ 123456otago.ac.nz (W.R.P.)
                [3 ]Department of General Practice and Primary Health Care, University of Auckland, Auckland 1142, New Zealand; a.howe@ 123456auckland.ac.nz
                Author notes
                [* ]Correspondence: paula.skidmore@ 123456otago.ac.nz ; Tel.: +64-3-479-8374
                Article
                nutrients-09-00454
                10.3390/nu9050454
                5452184
                28467392
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                Categories
                Article

                Nutrition & Dietetics

                new zealand adults, diet quality, food habits, nutrient intake

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