Research
Original Research
The Healthy Cooking Index: Nutrition Optimizing Home Food Preparation Practices across Multiple Data Collection Methods

https://doi.org/10.1016/j.jand.2020.01.008Get rights and content

Abstract

Background

Food preparation interventions are an increasingly popular target for hands-on nutrition education for adults, children, and families, but assessment tools are lacking. Objective data on home cooking practices, and how they are interpreted through different data collection methods, are needed.

Objective

The goal of this study was to explore the utility of the Healthy Cooking Index in coding multiple types of home food preparation data and elucidating healthy cooking behavior patterns.

Design

Parent–child dyads were recruited between October 2017 and June 2018 in Houston and Austin, Texas for this observational study. Food preparation events were observed and video recorded. Participants also wore a body camera (eButton) and completed a questionnaire during the same event.

Participants/setting

Parents with a school-aged child were recruited as dyads (n=40). Data collection procedures took place in participant homes during evening meal preparation events.

Main outcome measures

Food preparation data were collected from parents through direct observation during preparation as well as eButton and paper questionnaires completed immediately after the event.

Statistical analyses performed

All data sets were analyzed using the Healthy Cooking Index coding system and compared for concordance. A paired sample t test was used to examine significant differences between the scores. Cronbach’s α and principal components analysis were conducted on the observed Healthy Cooking Index items to examine patterns of cooking practices.

Results

Two main components of cooking practices emerged from the principal components analysis: one focused on meat products and another on health and taste enhancing practices. The eButton was more accurate in collecting Healthy Cooking Index practices than the self-report questionnaire. Significant differences were found between participant reported and observed summative Healthy Cooking Index scores (P<0.001), with no significant differences between scores computed from eButton images and observations (P=0.187).

Conclusions

This is the first study to examine nutrition optimizing home cooking practices by observational, wearable camera and self-report data collection methods. By strengthening cooking behavior assessment tools, future research will be able to elucidate the transmission of cooking education through interventions and the relationships between cooking practices, disease prevention, and health.

Section snippets

Materials and Methods

This observational study was conducted between October 2017 and June 2018 in Houston and Austin, TX. Recruitment and data collection were conducted on a rolling basis throughout the study period.

Participants

A total of 40 parent–child dyads completed this study. Participant characteristics are shown in Table 2. The majority of child participants were under 14 years, females, and non-Hispanic white or Hispanic. Most parents were highly educated, completing college or postgraduate study, and socioeconomically stable with the majority owning their homes and earning above $60,000 per year (median household income in Houston=$49,399; Austin=$63,717).38 Although participants made a variety of main dishes

Discussion

This study examined the quantification of healthy home cooking practices using the HCI across multiple data collection methods. The accuracy of self-report (HCQ) and wearable camera (eButton) data collection methods were assessed against recorded audio or visual observations of meal preparation events in 40 parent–child dyads. The eButton was more accurate, with no significant difference between HCI scores computed from unit images and observations. The self-report data had significant

Conclusions

Novel findings were obtained regarding nutrition optimizing home cooking practices that support the development of more robust cooking program evaluation tools. The eButton demonstrated potential as an accurate primary or reference measure of home cooking behaviors. As wearable technology further develops, automatic identification of food preparation practices may be wired into image-analyzing software to increase the wider utility of these devices in research and community program evaluation.

M. Raber is a graduate research assistant, Department of Pediatrics Research, University of Texas MD Anderson Cancer Center, Houston, TX

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    M. Raber is a graduate research assistant, Department of Pediatrics Research, University of Texas MD Anderson Cancer Center, Houston, TX

    K. Crawford is a research dietitian, Department of Pediatrics Research, University of Texas MD Anderson Cancer Center, Houston, TX

    E. Steinman is a summer research intern, Department of Pediatrics Research, University of Texas MD Anderson Cancer Center, Houston, TX

    J. Chandra is an associate professor, Department of Pediatrics Research, University of Texas MD Anderson Cancer Center, Houston, TX

    T. Baranowski is a professor, Department of Pediatrics, USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX

    S. V. Sharma is an associate professor, Department of Epidemiology, Department of Community Health Practice, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, TX

    V. Schick is an assistant professor, Department of Community Health Practice, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, TX

    C. Markham is an associate professor, Department of Health Promotion and Behavioral Science, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, TX

    W. Jia is an assistant professor, Department of Neurological Surgery, University of Pittsburgh, UPMC Presbyterian, Pittsburgh, PA

    M. Sun is a professor, Department of Neurological Surgery, University of Pittsburgh, UPMC Presbyterian, Pittsburgh, PA

    STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.

    FUNDING/SUPPORT This research was funded by a grant from the National Institutes of Health, National Cancer Institute (5 R21 CA172864; R01CA165255; R25CA057730) and Cancer Center Support Grant (P30-CA16672); National Heart, Lung and Blood Institute (U01HL91736); institutional support from the US Department of Agriculture, Agricultural Research Service (Cooperative Agreement 58–3092–5-001); the MD Anderson Center for Energy Balance in Cancer Prevention and Survivorship, and the James and Lois Archer Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

    ACKNOWLEDGEMENTS We acknowledge all participants that took part in this research. We also acknowledge Michael Roth, MD, Grace Yang, Allison Marshall, Emily Kelly and Mike Pomeroy, who assisted with study recruitment and data collection.

    AUTHOR CONTRIBUTIONS M. Raber managed this project, completed data collection and analysis, and wrote the first draft of the manuscript. T. Baranowski guided the data analysis approach and contributed to subsequent manuscript drafts. K. Crawford participated in data collection. S. V. Sharma, C. Markham, and V. Schick contributed to study design, recruitment, and data analysis. W. Jia managed the creation of the eButton and analysis software. M. Sun created the eButton. E. Steinman contributed to data analysis. J. Chandra supervised all aspects of this project including study design, data collection, data management, and manuscript development. All authors reviewed repeated drafts of this manuscript and approved the final draft.

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