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      Dietary species richness as a measure of food biodiversity and nutritional quality of diets

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          Significance

          Current research linking biodiversity and human diets has used metrics without justification from a nutritional point of view. Diet species richness, or a count of the number of different species consumed per day, assesses both nutritional adequacy and food biodiversity of diets for women and children in rural areas. The positive association of food species richness with dietary quality was observed in both the wet and the dry season. Food biodiversity contributes to diet quality in vulnerable populations in areas with high biodiversity. Reporting the number of species consumed during dietary assessment provides a unique opportunity to cut across two critical dimensions of sustainable development—human and environmental health—and complements existing indicators for healthy and sustainable diets.

          Abstract

          Biodiversity is key for human and environmental health. Available dietary and ecological indicators are not designed to assess the intricate relationship between food biodiversity and diet quality. We applied biodiversity indicators to dietary intake data from and assessed associations with diet quality of women and young children. Data from 24-hour diet recalls (55% in the wet season) of n = 6,226 participants (34% women) in rural areas from seven low- and middle-income countries were analyzed. Mean adequacies of vitamin A, vitamin C, folate, calcium, iron, and zinc and diet diversity score (DDS) were used to assess diet quality. Associations of biodiversity indicators with nutrient adequacy were quantified using multilevel models, receiver operating characteristic curves, and test sensitivity and specificity. A total of 234 different species were consumed, of which <30% were consumed in more than one country. Nine species were consumed in all countries and provided, on average, 61% of total energy intake and a significant contribution of micronutrients in the wet season. Compared with Simpson’s index of diversity and functional diversity, species richness (SR) showed stronger associations and better diagnostic properties with micronutrient adequacy. For every additional species consumed, dietary nutrient adequacy increased by 0.03 ( P < 0.001). Diets with higher nutrient adequacy were mostly obtained when both SR and DDS were maximal. Adding SR to the minimum cutoff for minimum diet diversity improved the ability to detect diets with higher micronutrient adequacy in women but not in children. Dietary SR is recommended as the most appropriate measure of food biodiversity in diets.

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          Most cited references19

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          Food variety and dietary diversity scores in children: are they good indicators of dietary adequacy?

          To assess whether a food variety score (FVS) and/or a dietary diversity score (DDS) are good indicators of nutrient adequacy of the diet of South African children. Secondary data analyses were undertaken with nationally representative data of 1-8-year-old children (n = 2200) studied in the National Food Consumption Study in 1999. An average FVS (mean number of different food items consumed from all possible items eaten) and DDS (mean number of food groups out of nine possible groups) were calculated. A nutrient adequacy ratio (NAR) is the ratio of a subject's nutrient intake to the estimated average requirement calculated using the Food and Agriculture Organization/World Health Organization (2002) recommended nutrient intakes for children. The mean adequacy ratio (MAR) was calculated as the sum of NARs for all evaluated nutrients divided by the number of nutrients evaluated, expressed as a percentage. MAR was used as a composite indicator for micronutrient adequacy. Pearson correlation coefficients between FVS, DDS and MAR were calculated and also evaluated for sensitivity and specificity, with MAR taken as the ideal standard of adequate intake. The relationships between MAR and DDS and between anthropometric Z-scores and DDS were also evaluated. The children had a mean FVS of 5.5 (standard deviation (SD) 2.5) and a mean DDS of 3.6 (SD 1.4). The mean MAR (ideal = 100%) was 50%, and was lowest (45%) in the 7-8-year-old group. The items with the highest frequency of consumption were from the cereal, roots and tuber group (99.6%), followed by the 'other group' (87.6%) comprising items such as tea, sugar, jam and sweets. The dairy group was consumed by 55.8%, meat group by 54.1%, fats by 38.9%, other vegetables by 30.8%, vitamin-A-rich by 23.8%, other fruit by 22%, legumes and nuts by 19.7% and eggs by 13.3%. There was a high correlation between MAR and both FVS (r = 0.726; P < 0.0001) and DDS (r = 0.657; P < 0.0001), indicating that either FVS or DDS can be used as an indicator of the micronutrient adequacy of the diet. Furthermore, MAR, DDS and FVS showed significant correlations with height-for-age and weight-for-age Z-scores, indicating a strong relationship between dietary diversity and indicators of child growth. A DDS of 4 and an FVS of 6 were shown to be the best indicators of MAR less than 50%, since they provided the best sensitivity and specificity. Either FVS or DDS can be used as a simple and quick indicator of the micronutrient adequacy of the diet.
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            Functional traits in agriculture: agrobiodiversity and ecosystem services.

            Functional trait research has led to greater understanding of the impacts of biodiversity in ecosystems. Yet, functional trait approaches have not been widely applied to agroecosystems and understanding of the importance of agrobiodiversity remains limited to a few ecosystem processes and services. To improve this understanding, we argue here for a functional trait approach to agroecology that adopts recent advances in trait research for multitrophic and spatially heterogeneous ecosystems. We suggest that trait values should be measured across environmental conditions and agricultural management regimes to predict how ecosystem services vary with farm practices and environment. This knowledge should be used to develop management strategies that can be easily implemented by farmers to manage agriculture to provide multiple ecosystem services.
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              The nutrition transition: new trends in the global diet.

              Analyses of economic and food availability data for 1962-1994 reveal a major shift in the structure of the global diet marked by an uncoupling of the classic relationship between incomes and fat intakes. Global availability of cheap vegetable oils and fats has resulted in greatly increased fat consumption among low-income nations. Consequently, the nutrition transition now occurs at lower levels of the gross national product than previously, and is accelerated further by high urbanization rates. Data from Asian nations, where diet structure is rapidly changing, suggest that diets higher in fats and sweeteners are also more diverse and more varied. Given that preferences for palatable diets are a universal human trait, fat consumption may be governed not by physiological mechanisms but by the amount of fat available in the food supply. Whereas economic development has led to improved food security and better health, adverse health effects of the nutrition transition include growing rates of childhood obesity. The implications of these trends are explored.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                2 January 2018
                18 December 2017
                18 December 2017
                : 115
                : 1
                : 127-132
                Affiliations
                [1] aDepartment of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent University , 9000 Ghent, Belgium;
                [2] bHealthy Diets from Sustainable Food Systems Initiative, Bioversity International , 00057 Maccarese (Rome), Italy;
                [3] cLaboratory of Tropical and Subtropical Agronomy and Ethnobotany, Faculty of Bioscience Engineering, Ghent University , 9000 Ghent, Belgium;
                [4] dDepartment of Crop Sciences and Agroforestry, Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague , 165 21 Prague 6, Suchdol, Czech Republic;
                [5] eRural Research Center, Faculty of Life Sciences, Nutrition, Escuela Superior Politecnica del Litoral , Guayaquil, 090608 Ecuador;
                [6] fKERMIT, Department of Mathematical Modeling, Statistics, and Bioinformatics, Faculty of Bioscience Engineering, Ghent University , 9000 Ghent, Belgium;
                [7] gDepartment of Agricultural Biology, Faculty of Agriculture, University of Ruhuna , 81100 Matara, Sri Lanka;
                [8] hHealthBridge Foundation of Canada , 10000 Hanoi, Vietnam
                Author notes
                2To whom correspondence should be addressed. Email: carl.lachat@ 123456ugent.be .

                Edited by David Tilman, University of Minnesota, St. Paul, MN, and approved November 9, 2017 (received for review June 6, 2017)

                Author contributions: C.L., J.E.R., R.R., and C.T. designed research; C.L. and J.E.R. performed research; J.E.R., G.K., and H.T.K. contributed data from Vietnam; D.P. contributed data from Ecuador; K.V., D.H., and D.R. contributed data from Sri Lanka; G.N.-B. contributed data from Benin; P.V.D. contributed data from Democratic Republic of Congo, Ecuador, and Cameroon; W.V. contributed data from Cameroon; F.O.O. contributed data from Kenya; C.T. contributed data from Democratic Republic of Congo, Benin, Kenya, and Cameroon; J.E.R., P.K., P.V.D., and R.R. contributed new reagents/analytic tools; C.L., K.W.S., P.K., B.D.B., and R.R. analyzed data; and C.L., J.E.R., K.W.S., P.K., P.V.D., K.V., D.P., W.V., G.K., D.H., F.O.O., G.N.-B., B.D.B., D.R., H.T.K., R.R., and C.T. wrote the paper.

                1C.L. and J.E.R. contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-1389-8855
                Article
                201709194
                10.1073/pnas.1709194115
                5776793
                29255049
                04c37c73-e5de-4e25-bdb4-ac421fd4acdc
                Copyright © 2017 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 6
                Funding
                Funded by: Ministry of Foreign Affairs Finland
                Award ID: FoodAfrica 29891501
                Funded by: Vlaamse Interuniversitaire Raad (VLIR) 501100006338
                Award ID: ICP PhD 2010-012
                Funded by: Global environmental facility
                Award ID: Biodiversity for food and nutrition project GFL-2328-2715-4B07
                Funded by: Daniel and Nina Carasso Foundation
                Award ID: PG008608
                Funded by: International institute for Tropical Agriculture and Bioversity International
                Award ID: Humidtropics A4NH: CRP4-002
                Categories
                9
                Biological Sciences
                Applied Biological Sciences
                Biological Sciences
                Sustainability Science

                sustainable diets,diet quality,malnutrition,biodiversity,food biodiversity

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