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  • 1
    Online Resource
    Online Resource
    Statistica Sinica (Institute of Statistical Science) ; 2018
    In:  Statistica Sinica ( 2018)
    In: Statistica Sinica, Statistica Sinica (Institute of Statistical Science), ( 2018)
    Type of Medium: Online Resource
    ISSN: 1017-0405
    Language: Unknown
    Publisher: Statistica Sinica (Institute of Statistical Science)
    Publication Date: 2018
    detail.hit.zdb_id: 1106064-5
    detail.hit.zdb_id: 2037676-5
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  • 2
    Online Resource
    Online Resource
    Termedia Sp. z.o.o. ; 2022
    In:  Biology of Sport Vol. 39, No. 1 ( 2022), p. 11-17
    In: Biology of Sport, Termedia Sp. z.o.o., Vol. 39, No. 1 ( 2022), p. 11-17
    Type of Medium: Online Resource
    ISSN: 0860-021X
    Language: Unknown
    Publisher: Termedia Sp. z.o.o.
    Publication Date: 2022
    detail.hit.zdb_id: 2620894-5
    SSG: 31
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  • 3
    Online Resource
    Online Resource
    Frontiers Media SA ; 2021
    In:  Frontiers in Nutrition Vol. 8 ( 2021-12-15)
    In: Frontiers in Nutrition, Frontiers Media SA, Vol. 8 ( 2021-12-15)
    Abstract: Heterogeneity in meat food groups hinders interpretation of research regarding meat intake and chronic disease risk. Our objective was to investigate how heterogeneity in red meat (RM) and poultry food groups influences US population intake estimates. Based on a prior systematic review, we created an ontology of methods used to estimate RM [1= unprocessed RM; 2 (reference)= unprocessed RM + processed RM; 3= unprocessed RM + processed RM + processed poultry; and 4=unprocessed RM + processed RM + processed poultry + chicken patties/nuggets/tenders (PNT)] and three for poultry [A=unprocessed poultry; B= unprocessed poultry + PNT; C (reference)= unprocessed poultry + processed poultry + PNT). We applied methods to 2015–18 National Health and Nutrition Examination Survey data to estimate RM and poultry intake prevalence and amount. We estimated and compared intakes within RM and within poultry methods via the NCI Method for individuals ≥2 years old ( n = 15,038), adjusted for age, sex, and race/Hispanic origin. We compared the population percentage that exceeded age- and sex-specific RM and poultry allotments from the Dietary Guidelines for Americans recommended eating patterns. The percent that consumed RM ranged from 47 ± 1.2% to 75 ± 0.8% across methods and mean amount ranged from 10.5 ± 0.28 to 18.2 ± 0.35 lean oz-equivalents/week; 38 ± 1.2% to 71 ± 0.7% and 9.8 ± 0.35 to 13.3 ± 0.35 lean oz-equivalents/week across poultry methods. Estimates for higher, but not lower, intake percentiles differed across RM methods. Compared to the reference, Method 1 was ≥3.0 oz-equivalents/week lower from 20th-70th percentiles, ≥6.0 oz-equivalents/week lower from 75th-90th percentiles, and ≥9.0 oz-equivalents/week lower for the 95th percentile. Method 4, but not Method 3, was ≥3.0 oz-equivalents/week higher than the reference from 50 to 95th percentiles. The population percentage that exceeded allotments was 27 ± 1.8% lower for Method 1, 9 ± 0.8% higher for Method 3, and 14 ± 0.9% higher for Method 4 compared to the reference. Differences were less pronounced for poultry. Our analysis quantifies the magnitude of bias introduced by heterogeneous meat food group methodology. Explicit descriptions of meat food groups are important for development of dietary recommendations to ensure that research studies are compared appropriately.
    Type of Medium: Online Resource
    ISSN: 2296-861X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2776676-7
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  • 4
    Online Resource
    Online Resource
    Human Kinetics ; 2011
    In:  Journal of Physical Activity and Health Vol. 8, No. s1 ( 2011-01), p. S91-S97
    In: Journal of Physical Activity and Health, Human Kinetics, Vol. 8, No. s1 ( 2011-01), p. S91-S97
    Abstract: Examining relationships between features of the built environment and physical activity is achievable with geographic information systems technology (GIS). The purpose of this paper is to review the literature to identify GIS measures that can be considered for inclusion in national public health surveillance efforts. In the absence of a universally agreed upon framework that integrates physical, social, and cultural aspects of the environment, we used a multidimensional model of access to synthesize the literature. Methods: We identified 29 studies published between 2005 and 2009 with physical activity outcomes that included 1 or more built environment variables measured using GIS. We sorted built environment measures into 5 dimensions of access: accessibility, availability, accommodation, affordability, and acceptability. Results: Geospatial land-use data, street network data, environmental audits, and commercial databases can be used to measure the availability, accessibility, and accommodation dimensions of access. Affordability and acceptability measures rely on census and self-report data. Conclusions: GIS measures have been included in studies investigating the built environment and physical activity, although few have examined more than 1 construct of access. Systematic identification and collection of relevant GIS measures can facilitate collaboration and accelerate the advancement of research on the built environment and physical activity.
    Type of Medium: Online Resource
    ISSN: 1543-3080 , 1543-5474
    Language: Unknown
    Publisher: Human Kinetics
    Publication Date: 2011
    SSG: 31
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