15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Seasonality affects dietary diversity of school-age children in northern Ghana

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background and objectives

          Dietary diversity score (DDS) is relatively easy to measure and is shown to be a very useful indicator of the probability of adequate micronutrient intake. Dietary diversity, however, is usually assessed during a single period and little is known about the effect of seasonality on it. This study investigates whether dietary diversity is influenced by seasonality.

          Methods

          Two cross-sectional surveys were conducted in two different seasons—dry season (October 2010) and rainy season (May 2011) among the same school-age children (SAC) in two rural schools in northern Ghana. The study population consisted of 228 school-age children. A qualitative 24-hour dietary recall was conducted in both seasons. Based on 13 food groups, a score of 1 was given if a child consumed a food item belonging to a particular food group, else 0. Individual scores were aggregated into DDS for each child. Differences in mean DDS between seasons were compared using linear mixed model analysis.

          Results

          The dietary pattern of the SAC was commonly plant foods with poor consumption of animal source foods. The mean DDS was significantly higher ( P < 0.001) in the rainy season (6.95 ± 0.55) compared to the dry season (6.44 ± 0.55) after adjusting for potential confounders such as age, sex, occupation (household head and mother) and education of household head. The difference in mean DDS between dry and rainy seasons was mainly due to the difference in the consumption of Vitamin A-rich fruits and vegetables between the seasons. While vitamin A-rich fruits (64.0% vs. 0.9%; P < 0.0001) and vitamin A rich dark green leafy vegetables (52.6% vs. 23.3%, P < .0001) were consumed more during the rainy season than the dry season, more children consumed vitamin A-rich deep yellow, orange and red vegetables during the dry season than during the rainy season (73.7% vs. 36.4%, P <0.001).

          Conclusion

          Seasonality has an effect on DDS and may affect the quality of dietary intake of SAC; in such a context, it would be useful to measure DDS in different seasons. Since DDS is a proxy indicator of micronutrient intake, the difference in DDS may reflect in seasonal differences in dietary adequacy and further studies are needed to establish this.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Regional alcohol consumption and alcohol-related mortality in Great Britain: novel insights using retail sales data

          Background Regional differences in population levels of alcohol-related harm exist across Great Britain, but these are not entirely consistent with differences in population levels of alcohol consumption. This incongruence may be due to the use of self-report surveys to estimate consumption. Survey data are subject to various biases and typically produce consumption estimates much lower than those based on objective alcohol sales data. However, sales data have never been used to estimate regional consumption within Great Britain (GB). This ecological study uses alcohol retail sales data to provide novel insights into regional alcohol consumption in GB, and to explore the relationship between alcohol consumption and alcohol-related mortality. Methods Alcohol sales estimates derived from electronic sales, delivery records and retail outlet sampling were obtained. The volume of pure alcohol sold was used to estimate per adult consumption, by market sector and drink type, across eleven GB regions in 2010–11. Alcohol-related mortality rates were calculated for the same regions and a cross-sectional correlation analysis between consumption and mortality was performed. Results Per adult consumption in northern England was above the GB average and characterised by high beer sales. A high level of consumption in South West England was driven by on-trade sales of cider and spirits and off-trade wine sales. Scottish regions had substantially higher spirits sales than elsewhere in GB, particularly through the off-trade. London had the lowest per adult consumption, attributable to lower off-trade sales across most drink types. Alcohol-related mortality was generally higher in regions with higher per adult consumption. The relationship was weakened by the South West and Central Scotland regions, which had the highest consumption levels, but discordantly low and very high alcohol-related mortality rates, respectively. Conclusions This study provides support for the ecological relationship between alcohol-related mortality and alcohol consumption. The synthesis of knowledge from a combination of sales, survey and mortality data, as well as primary research studies, is key to ensuring that regional alcohol consumption, and its relationship with alcohol-related harms, is better understood.
            Bookmark
            • Record: found
            • Abstract: found
            • Book: not found

            SAS for Mixed Models

            The indispensable, up-to-date guide to mixed models using SAS®. Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures in this valuable edition of the comprehensive mixed models guide for data analysis, completely revised and updated for SAS®9. The theory underlying the models, the forms of the models for various applications, and a wealth of examples from different fields of study are integrated in the discussions of these models: random effect only and random coefficients models split-plot, multilocation, and repeated measures models hierarchical models with nested random effects analysis of covariance models spatial correlation models generalized linear mixed models nonlinear mixed models Professionals and students with a background in two-way ANOVA and regression and a basic knowledge of linear models and matrix algebra will benefit from the topics covered. Includes a free CD-ROM with example SAS code!
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Measurement of dietary intake in children.

              When children and adolescents are the target population in dietary surveys many different respondent and observer considerations surface. The cognitive abilities required to self-report food intake include an adequately developed concept of time, a good memory and attention span, and a knowledge of the names of foods. From the age of 8 years there is a rapid increase in the ability of children to self-report food intake. However, while cognitive abilities should be fully developed by adolescence, issues of motivation and body image may hinder willingness to report. Ten validation studies of energy intake data have demonstrated that mis-reporting, usually in the direction of under-reporting, is likely. Patterns of under-reporting vary with age, and are influenced by weight status and the dietary survey method used. Furthermore, evidence for the existence of subject-specific responding in dietary assessment challenges the assumption that repeated measurements of dietary intake will eventually obtain valid data. Unfortunately, the ability to detect mis-reporters, by comparison with presumed energy requirements, is limited unless detailed activity information is available to allow the energy intake of each subject to be evaluated individually. In addition, high variability in nutrient intakes implies that, if intakes are valid, prolonged dietary recording will be required to rank children correctly for distribution analysis. Future research should focus on refining dietary survey methods to make them more sensitive to different ages and cognitive abilities. The development of improved techniques for identification of mis-reporters and investigation of the issue of differential reporting of foods should also be given priority.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: Writing – original draft
                Role: InvestigationRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                14 August 2017
                2017
                : 12
                : 8
                : e0183206
                Affiliations
                [1 ] Department of Community Nutrition, School of Allied Health Sciences, University for Development Studies, Tamale, Ghana
                [2 ] Department of Family and Consumer Sciences, Faculty of Agriculture, University for Development Studies, Tamale, Ghana
                [3 ] Division of Human Nutrition, Wageningen University, The Netherlands
                University Sains Malaysia, MALAYSIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-1771-0482
                Article
                PONE-D-16-23472
                10.1371/journal.pone.0183206
                5555613
                28806418
                79c205f8-515e-4d7e-a7a3-f7e6f00e73ad
                © 2017 Abizari et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 June 2016
                : 1 August 2017
                Page count
                Figures: 0, Tables: 6, Pages: 16
                Funding
                Funded by: Nestle Foundation for Nutrition Research
                Award Recipient :
                Funding for this research was received from Nestle Foundation for Nutrition Research with Grant number FN4042. The grant was received by Abdul-Razak Abizari. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Earth Sciences
                Seasons
                Physical Sciences
                Chemistry
                Chemical Compounds
                Organic Compounds
                Vitamins
                Physical Sciences
                Chemistry
                Organic Chemistry
                Organic Compounds
                Vitamins
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Food Consumption
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Food Consumption
                Biology and Life Sciences
                Organisms
                Plants
                Fruits
                Biology and Life Sciences
                Organisms
                Plants
                Vegetables
                Biology and Life Sciences
                Nutrition
                Diet
                Food
                Medicine and Health Sciences
                Nutrition
                Diet
                Food
                People and Places
                Population Groupings
                Age Groups
                Children
                People and Places
                Population Groupings
                Families
                Children
                Biology and Life Sciences
                Organisms
                Plants
                Legumes
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article