5 datasets found
  1. f

    Multilevel linear regression models used to test the association of food...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
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    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett (2023). Multilevel linear regression models used to test the association of food outlet density and dietary patterns. [Dataset]. http://doi.org/10.1371/journal.pgph.0001069.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Multilevel linear regression models used to test the association of food outlet density and dietary patterns.

  2. f

    Association of household SEP and food outlet density; data from the...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
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    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett (2023). Association of household SEP and food outlet density; data from the nationally representative, cross-sectional, 2012 ENSANUTa, N = 22,219. [Dataset]. http://doi.org/10.1371/journal.pgph.0001069.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Association of household SEP and food outlet density; data from the nationally representative, cross-sectional, 2012 ENSANUTa, N = 22,219.

  3. f

    Sociodemographic, and economic characteristics of Mexican adults aged 18+...

    • plos.figshare.com
    xls
    Updated Jun 20, 2023
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    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett (2023). Sociodemographic, and economic characteristics of Mexican adults aged 18+ inhabiting urban areas of Mexico a. [Dataset]. http://doi.org/10.1371/journal.pgph.0001069.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 20, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Mexico
    Description

    Sociodemographic, and economic characteristics of Mexican adults aged 18+ inhabiting urban areas of Mexico a.

  4. c

    3D Food Printing Market Will Grow at a CAGR of 48.90% from 2024 to 2031.

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
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    Cognitive Market Research, 3D Food Printing Market Will Grow at a CAGR of 48.90% from 2024 to 2031. [Dataset]. https://www.cognitivemarketresearch.com/3d-food-printing-market-report
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    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, the global 3D Food Printing market size was USD 199.4 million in 2024 and will expand at a compound annual growth rate (CAGR) of 48.9% from 2024 to 2031. Market Dynamics of 3D Food Printing Market

    Key Drivers for 3D Food Printing Market

    Increasing Demand for Gourmet Food to Increase the Demand Globally - The increasing demand for gourmet food is driving the market for 3D food printing by encouraging culinary innovation and customization. 3D food printing technology enables chefs and food enthusiasts to create intricate and visually appealing dishes with precise ingredient placement and complex designs. This capability aligns with the expectations of gourmet consumers for unique dining experiences, personalized flavors, and artistic presentations, thereby fueling the adoption of 3D food printing in upscale culinary settings. Sustainability and Environmentally Friendly Practices-The adoption of sustainability and environmentally friendly practices in 3D food printing drives market growth by aligning with consumer demand for eco-conscious solutions in food production.

    Key Restraints for 3D Food Printing Market

    Limited Ingredient Compatibility and Design Complexity- The limited compatibility of ingredients and the complexity of designing food structures currently restrict the broader adoption and market penetration of 3D food printing technology. Slow Processing Time Involved- The slow processing time involved in 3D food printing limits its market potential by hindering scalability and mass production capabilities in commercial food settings.

    Slow processing time for 3D printing involve hamper the market growth
    

    Slowed processing time is a major limitation that's hindering the development of the 3D food printing market. Although 3D food printing does hold great potential in terms of customization, design versatility, and sustainability, the technology itself is still under development and struggles in terms of speed and efficiency. Printing food products in layers is inherently a time-consuming process, particularly if working with intricate shapes or multi-component recipes. This gradual production rate renders it challenging to expand for mass production or commercial food service environments where volume and speed are of essence. For instance, The printer's extruder or laser must move precisely along the designated path to ensure the material is deposited accurately. This careful movement is crucial for the quality of the final product but takes time, especially for prints with complex shapes or intricate details. (Source- https://pmc.ncbi.nlm.nih.gov/articles/PMC10221300/) In such settings as restaurants, catering establishments, or food processing units, the existing speed of 3D food printers cannot compete with the efficiency of conventional cooking and processing. This restricts its applicability and acceptance, especially in high-demanding environments. Also, some food materials could demand certain temperature or consistency regulation, which also contributes to processing time and technical sophistication. In addition, extended printing durations can cause inconsistency in quality, impact texture, or even result in food safety issues if ingredients are not processed within acceptable time periods. Unless dramatic breakthroughs occur in printer speed, integration of multiple materials, and automation, the time-consuming processing will continue to hinder wider commercialization and market expansion of 3D food printing technology.

    Opportunities for 3D Food Printing

    Growth in demand from the hospitality industry is opportunity for the market growth.
    

    The increasing demand from the hospitality sector is a major opportunity for the growth of the 3D food printing market. Hotels, restaurants, and catering services are always looking for new ways to improve customer experience, differentiate their products, and optimize operations. 3D food printing provides the capability to produce visually appealing, customized food that is hard to achieve with conventional cooking techniques. For instance, 3D food printing has come as a revolutionary technology in the food sector, providing innovative solutions for customized nutrition, cooking creativity, and enhanced food texture. (Source-https://www.ijcrt.org/papers/IJCRT2410254.pdf) This degree of personalization and creativity is particularly attractive in high-end dining ...

  5. f

    Multivariate associations between dietary patterns and food outlet density;...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
    Share
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    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett (2023). Multivariate associations between dietary patterns and food outlet density; data from the nationally representative, cross-sectional, 2012 ENSANUTa—Dietary assessment component. [Dataset]. http://doi.org/10.1371/journal.pgph.0001069.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Multivariate associations between dietary patterns and food outlet density; data from the nationally representative, cross-sectional, 2012 ENSANUTa—Dietary assessment component.

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Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett (2023). Multilevel linear regression models used to test the association of food outlet density and dietary patterns. [Dataset]. http://doi.org/10.1371/journal.pgph.0001069.t001

Multilevel linear regression models used to test the association of food outlet density and dietary patterns.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 21, 2023
Dataset provided by
PLOS Global Public Health
Authors
Elisa Pineda; Diana Barbosa Cunha; Mansour Taghavi Azar Sharabiani; Christopher Millett
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Multilevel linear regression models used to test the association of food outlet density and dietary patterns.

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