Dietary Reference Intakes for Energy (2023) / Chapter Skim
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6 Assessing Energy Intakes, Physical Activity, and Indicators of Overweight and Obesity
6 Assessing Energy Intakes, Physical Activity, and Indicators of Overweight and Obesity
Pages 111-144
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From page 111... ...
and Canadian populations is one of four key components of the DRI organizing framework that is now a routine component of the DRI process, as described in Chapter 2. APPROACH TO ASSESSING ENERGY INTAKES AND PHYSICAL ACTIVITY EXPENDITURES As part of its task, the committee considered methods used to estimate energy intakes and physical activity and to evaluate the prevalence of long-term energy intake imbalances.
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Data on physical activity behaviors for the United States and Canada from NHANES and CHMS were not provided directly to the committee and thus, prevalence on meeting guidelines or average activity levels were obtained from published articles. These population-based data provide background information for subsequent discussions in Chapter 8 on the public health risks associated with energy intake imbalances among population groups. METHODS FOR ASSESSING ENERGY INTAKE Self-Reported Dietary Assessment Accurate dietary assessment methods are needed to identify not only intake deviations from EERs, but also to relate energy intakes to health outcomes in research contexts.
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Measurement error is broadly classified into systematic and random, and an error in self-reported dietary assessment is often referred to as misreporting. Understanding of the types and structure of measurement error with regard to dietary energy comes from studies that use doubly labeled water (DLW)
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The committee's literature search identified eight systematic reviews of measurement error in dietary assessment (See Appendix J, Table J-14)
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A systematic review of the validity of dietary assessment methods compared to DLW specifically in children concluded that 24HRs were valid for energy intake reporting at the group but not at the individual level and that the accuracy of energy reporting was not related to the sex, age, or weight status of the child (Burrows et al., 2020) , which differs from previous reports (Burrows et al., 2010)
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or FR (n = 36) as the dietary assessment tool and DLW, and five studies used a diet history method (Burrows et al., 2019)
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In general, device-based methods provide better estimates of total energy expenditure compared to report-based methods. Self-Report Estimates of Physical Activity Several systematic reviews have explored comparisons of self-report estimates of total energy expenditure to estimates via DLW.
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For indirect calorimetry and wholeroom calorimetry, activity monitor estimates of energy expenditure mean percent differences ranged from 41.4 to 115.7 percent (indirect calorimetry) and –16.7 to –15.7 percent (whole-room calorimetry)
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For this report, data on U.S. energy intakes and various body composition measures were estimated using the 2015–2018 NHANES.
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method (Tooze et al., 2006, 2010) was used to estimate usual energy intakes in both U.S.
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INDICATORS OF BODY WEIGHT AND ADIPOSITY Given that self-reported intake data do not accurately reflect recent energy intakes, an alternative approach for estimating long-term energy intakes is to measure body weight and body composition. Higher BMIs and increased adiposity are of public health concern because of their associations with adverse health outcomes (CDC, 2022; Statistics Canada, 2019; WHO, 2021)
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TABLE 6-1 Mean and Percentiles for Usual Daily Intake of Energy (kcal) , United States 122 Age or Life 5th 10th 25th 50th 75th 90th 95th Sex Stage N Mean SEM %tile SE %tile SE %tile SE %tile SE %tile SE %tile SE %tile SE Male 0–6 mo 182 683 23 377 36 435 32 540 25 666 23 817 31 949 42 1,036 51 Female 0–6 mo 187 *
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Includes participants with reliable 24-hour dietary recall on day 1 and breastfeeding children with dietary recall status = reported consuming breast milk and have dietary data; estimates other than for pregnant and lactating women adjusted for age, day of the week, and weekend. Selected percentiles are provided in this table, see the Supplemental Appendix Table X-1 for the complete set of percentiles.
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TABLE 6-2 Total Energy Intake (kcal/d) : Usual Intake from Food, Canada, 2015 124 Age or 5th 10th 25th 50th 75th 90th 95th Sex Life Stage n Mean SEM %tile SE %tile SE %tile SE %tile SE %tile SE %tile SE %tile SE Male 1–3 y 665 1,367 25 858 148*
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from 16.6% to 33.3%; interpret with caution. SOURCES: Summary data table of estimates of usual intakes for energy, nutrients and other dietary components from food, using data collected from Canadians in the 2015 Canadian Community Health Survey (CCHS)
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Data are from Appendix Tables L-1, L-2, L-5, L-6 and Supplemental Appendix Tables Y-1 and Y-2. See Supplemental Appendix Y for the expanded set of tables.
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Data are from Appendix Tables L-3, L-4, L-7, and L-8. See Supplemental Appendix Y for the expanded set of tables.
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* NOTES: SE = standard error.
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Data on the prevalence of obesity by race and ethnicity are also available for U.S. and Canadian populations (See Supplemental Appendix Tables Y-14, Y-15, Y-16, and Y-17)
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and Canadian life-stage groups using Z-statistic; Z-score > 1.96 significant at p < .05 SOURCE: From Appendix Tables L-11 and L-12. See Supplemental Appendix Y for expanded tables.
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males 19 years and older are 26.1 for non-Hispanic Asians, 29.1 for non-Hispanic Blacks, 29.4 for 6 More detailed data on distributions, comparisons among different types of anthropomet ric variables, and race/ethnicity are available in Appendix L and Supplemental Appendix Y
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DXA measures from NHANES for race/ethnicity groups (see Supplemental Appendix Tables Y-93 and Y-94) indicate that mean percent body fat for U.S.
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* NOTES: BMI = body mass index; cm = centimeter; kg = kilogram; m = meter; SE = standard error.
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The Canadian surveys do not have data on average sagittal abdominal diameter. Pregnant and lactating women excluded from NHANES; pregnant women excluded from the Canadian Health Measures Survey.
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Lean Mass Index Fat Mass Index Visceral Adipose Tissue (g) (years)
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Clearly, more research is needed on interpretive criteria for the different indices and, in some cases, for race/ethnicity, age/sex, and other subgroups. Identifying the best indicator or combination of indicators for predicting adverse health outcomes associated with energy intake imbalances and the risk of specific chronic diseases is also needed.
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FINDINGS AND CONCLUSIONS Assessment of Energy Intake and Expenditure Findings he committee finds that although it is possible to characterize usual T energy intakes using statistical methods to account for random error,
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In the absence of self-report, tracking indicators of long-term energy intakes that exceed the requirements for maintenance of a healthy weight are used rather than tracking energy intakes for the population. Conclusions rom the evidence reviewed, the committee concludes that research efforts F to improve the accuracy of dietary intake data are needed and that users of these data need to be aware of significant underreporting bias.
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than for Canadian populations. Further, while anthropometric and DXA data require more research to confirm interpretive criteria and to assess their validity as predictors of risk of adverse health outcomes, the reference values suggest that these data could help identify individuals at the greatest risk of energy intakes that exceed intakes required to maintain healthy body weights.
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2010. A systematic review of the validity of dietary assessment methods in children when compared with the method of doubly labeled water.
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2020. Validity of image-based dietary assessment methods: A systematic review and meta-analysis.
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1982. Measurement of energy expenditure in humans by doubly labeled water method.
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2019. People with a body mass index 30 under-report their dietary intake: A systematic review.
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