scholarly journals A New Index to Measure Healthy Food Diversity Better Reflects a Healthy Diet Than Traditional Measures

2007 ◽  
Vol 137 (3) ◽  
pp. 647-651 ◽  
Author(s):  
Larissa S. Drescher ◽  
Silke Thiele ◽  
Gert B. M. Mensink
Keyword(s):  
Healthy Food ◽  
Healthy Diet ◽  
Food Diversity ◽  
Healthy Food Diversity

scholarly journals Development and evaluation of the US Healthy Food Diversity index

2014 ◽  
Vol 112 (9) ◽  
pp. 1562-1574 ◽  
Author(s):  
Maya Vadiveloo ◽  
L. Beth Dixon ◽  
Tod Mijanovich ◽  
Brian Elbel ◽  
Niyati Parekh
Keyword(s):  
Diversity Index ◽  
Food Group ◽  
Healthy Food ◽  
Dietary Guidelines ◽  
Dietary Quality ◽  
Food Groups ◽  
Dietary Variety ◽  
Food Diversity ◽  
The Us ◽  
Healthy Food Diversity

Varied diets are diverse with respect to diet quality, and existing dietary variety indices do not capture this heterogeneity. We developed and evaluated the multidimensional US Healthy Food Diversity (HFD) index, which measures dietary variety, dietary quality and proportionality according to the 2010 Dietary Guidelines for Americans (DGA). In the present study, two 24 h dietary recalls from the 2003–6 National Health and Nutrition Examination Survey (NHANES) were used to estimate the intake of twenty-six food groups and health weights for each food group were informed by the 2010 DGA. The US HFD index can range between 0 (poor) and 1 − 1/n, where n is the number of foods; the score is maximised by consuming a variety of foods in proportions recommended by the 2010 DGA. Energy-adjusted Pearson's correlations were computed between the US HFD index and each food group and the probability of adequacy for fifteen nutrients. Linear regression was run to test whether the index differentiated between subpopulations with differences in dietary quality commonly reported in the literature. The observed mean index score was 0·36, indicating that participants did not consume a variety of healthful foods. The index positively correlated with nutrient-dense foods including whole grains, fruits, orange vegetables and low-fat dairy (r 0·12 to 0·64) and negatively correlated with added sugars and lean meats (r − 0·14 to − 0·23). The index also positively correlated with the mean probability of nutrient adequacy (r 0·41; P< 0·0001) and identified non-smokers, women and older adults as subpopulations with better dietary qualities. The US HFD index may be used to inform national dietary guidance and investigate whether healthful dietary variety promotes weight control.

SISTEM PAKAR MENU MAKANAN SEHAT BAGI PENDERITA KOLESTEROL DENGAN METODE FORWARD CHAINING

2017 ◽  
Vol 3 (2) ◽  
pp. 72
Author(s):  
Gusnita Darmawati
Keyword(s):  
Expert System ◽  
Cholesterol Level ◽  
Blood Group ◽  
Healthy Food ◽  
Healthy Diet ◽  
Blood Type ◽  
Forward Chaining ◽  
Cholesterol Levels ◽  
Microsoft Office ◽  
Visual Basic 6.0

<p>Penelitian ini membangun suatu sistem pakar untuk menentukan menu makanan sehat berdasarkan golongan darah dan tingkat kadar kolesterol pasien dengan metode Forward Chaining. Tujuan untuk membantu orang awam dalam menentukan menu makanan sehat untuk pasien kolesterol. Sistem ini menganalisa masalah penentuan menu makanan sehat berdasarkan golongan darah dan tingkat kadar kolesterol pasien. Hasil yang diperoleh dari sitem pakar ini adalah berupa informasi makanan sehat yang akan dikonsumsi oleh pasien kolesterol dengan jenis golongan darah dan tingkat kadar kolesterol yang berbeda. Analisa dilakukan dengan cara mengetahui jenis golongan darah dan tingkat kadar kolesterol pasien yang ditampilkan oleh program sistem pakar ini, rancangan sistem ini menggunakan inference forward chaining, dengan implementasi sistem menggunakan sistem database Microsoft Office Access dan bahasa pemrograman Visual Basic 6.0. Dari rancangan aplikasi sistem pakar yang dibuat, maka orang awam yang memderita kolesterol dapat menentukan menu makanan sehat untuk di konsumsi berdasarkan golongan darah dan tingkat kadar kolesterol dengan menjalankan aplikasi sistem pakar.</p><p><em><br /></em></p><p><em><em>This study builds an expert system to determine the healthy food menu based on blood type and cholesterol levels of patients with Forward Chaining method. The goal is to help the layman in determining a healthy diet for cholesterol patients. This system analyzes the problem of determining healthy food menu based on blood group and patient cholesterol level. The results obtained from this expert system is in the form of healthy food information that will be consumed by cholesterol patients with the type of blood group and different cholesterol levels. From the design of expert system applications created, the layman who memderita cholesterol can determine the healthy diet to be consumed by blood type and cholesterol level by running an expert system application.<br /> <br /> </em></em></p>

Rethinking household demand for food diversity

2017 ◽  
Vol 119 (6) ◽  
pp. 1176-1188 ◽  
Author(s):  
Andrea M. Leschewski ◽  
Dave D. Weatherspoon ◽  
Annemarie Kuhns
Keyword(s):  
Diversity Index ◽  
Correlation Coefficients ◽  
Household Expenditures ◽  
Content Type ◽  
Product Code ◽  
Food Diversity ◽  
Food Expenditures ◽  
Food And Nutrition ◽  
The Us ◽  
Healthy Food Diversity

Purpose The purpose of this paper is to develop a group-based food diversity index, which represents diversity in household expenditures across food subgroups. The index is compared to a product code-based index and applied to reassess determinants of food diversity demand. Design/methodology/approach A group-based food diversity index is developed by adapting the US Healthy Food Diversity Index. Using Food Acquisition and Purchase Survey data on 4,341 US households, correlation coefficients, descriptive statistics and linear regressions are estimated to compare and reassess the determinants of group and product code-based food diversity demand. Findings Results show that the group and product code indices capture different forms of food diversity. The indices are only moderately correlated and have varying means and skewness. Education, gender, age, household size, race, SNAP and food expenditures are found to significantly affect food diversity. However, the magnitude and direction of the effects vary between group and product code indices. Given these differences, it is essential that studies select a diversity index that corresponds to their objective. Results suggest that group-based indices are appropriate for informing food and nutrition policy, while product code-based indices are ideal for guiding food industry management’s decision making. Originality/value A group-based food diversity index representative of household expenditures across food subgroups is developed.

scholarly journals Development of a Cooking, Food Budgeting, and Nutrition intervention for American Indians with Type 2 Diabetes: Rationale and Study Protocol for the Cooking for Healthy Study

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1301-1301
Author(s):  
Amanda Fretts ◽  
Caitie Hawley ◽  
Meagan Brown ◽  
India Ornelas ◽  
Lyle Best ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
American Indians ◽  
Diabetes Management ◽  
Food Resource ◽  
Healthy Food ◽  
Healthy Diet ◽  
Health Study ◽  
Cooking Skills ◽  
Written Materials

Abstract Objectives Type 2 diabetes is a leading cause of morbidity among American Indians (AIs). Although healthy diet is a key component of diabetes management, many AIs face barriers to adopting a healthy diet. Preliminary work in an AI community in the north-central USA indicated that the most salient factors that influence healthy diet are: difficulty budgeting for food, low literacy/numeracy when purchasing food, and limited cooking skills. The Cooking for Health Study is a randomized controlled trial developed in partnership with the community that will evaluate the efficacy of a culturally-tailored healthy food budgeting, purchasing, and cooking program on: (1) intake of sugar-sweetened beverages and processed foods; and (2) healthy food budgeting and cooking skills, among AIs with diabetes. Methods The curriculum was informed by focus groups and meetings with community members and in partnership with the tribal diabetes program. The curriculum comprises a 12-month online/distance-learning program delivered through video and written materials. Over one year, we will recruit 165 AI participants with diabetes who are members of the community and reside on the reservation. Individuals will be randomized (using a 1:1 ratio) to intervention or control arm (i.e., delayed intervention). Participants in the intervention arm will receive the curriculum over a year. At baseline, month 6, and month 12, all participants will complete in-person study visits that include food frequency questionnaires, and assessments of food resource management and cooking confidence. Results The curriculum focuses on cooking and budgeting skills, and optimal diet for diabetes management. Lessons include: getting healthy foods; vegetables; fruits; dairy; protein and meats; grains; food budgeting and meal planning; empty calories; snacking; traditional foods; and celebrations. Each lesson comprises 3–8 videos paired with written materials. Enrollment will commence in early 2020. Conclusions Poorly controlled diabetes disproportionately affects the health of AIs compared to other racial/ethnic groups, and has profound effects on healthcare costs. Improving healthy food budgeting, purchasing, and cooking skills among AIs with diabetes should improve diet/diabetes management. Funding Sources NIH/NIMHD R01MD011596.

scholarly journals Mapping access to community-developed healthy food baskets including cost and availability

2016 ◽  
Vol 75 (8) ◽  
pp. 911-924 ◽  
Author(s):  
Alison Ginn ◽  
Anne Majumdar ◽  
Marimba Carr ◽  
Ginny Eastwood ◽  
Beth Menger
Keyword(s):  
Community Education ◽  
Healthy Food ◽  
Healthy Diet ◽  
Fruit And Vegetables ◽  
Urban Setting ◽  
Local Health ◽  
Food Groups ◽  
High Concentration ◽  
Local Health Service ◽  
Food Basket

Background: Food security is a topical issue but one that can be difficult to measure. Objective: To develop a community-approved food basket tool and use this to investigate the availability and affordability of a healthy diet in a multicultural urban setting. Design: A 7-day healthy food basket (HFB) containing 96 foods for six household types was developed through focus groups ( n = 6) with local residents recruited via the local health service and community organisations. A total of 41 stores were surveyed against the recommendations of the HFB. The availability and price of core food groups and energy dense discretionary foods were analysed. Setting: A multicultural area in Central London with a high concentration of socially and economically deprived households. Results: Healthy food for a variety of minority ethnic diets was available in the study area, although only one supermarket and three online stores stocked the full basket. Discretionary foods were readily available and often cheaper than healthier options. The largest proportions of cost were attributed to protein foods (30%–38%) and fruit and vegetables (20%–27%). Most foods in the HFB were cheaper at larger supermarkets, although fruit and vegetables cost less at markets and local stores. Total basket price varied greatly between stores, with cost savings achieved when buying from at least three stores. Conclusion: Economically disadvantaged members of the community may be excluded from accessing a healthy diet rather than cheaper foods that are energy dense and low in nutrients, particularly if they are unable to shop around. These findings provide insight for the development of voluntary sector partnership programmes, community education and local policy planning.

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