Abstract:This article reviews the 2015-2020 Dietary Guidelines for Americans released in 2016. Key recommendations are summarized and significant changes in the guidelines are highlighted. Implications for nursing practice to promote nutrition health are identified and resources to support implementation are included.
“… Figure 7 The application of the EBT may lead to unintended weight gain. Current dietary guidelines advise subjects with adequate body weight to minimize health risks and avoid weight gain by adopting isocaloric LFDs [ 43 ]. Such practice may, however, result in unplanned weight gain.…”
Energy metabolism theory affirms that body weight stability is achieved as over time the average energy intake equals the average energy expenditure, a state known as energy balance. Here it is demonstrated, however, that weight stability coexists with a persistent energy imbalance. Such unexpected result emerges as a consequence of the answers to three fundamental problems: 1. Is it possible to model body weight fluctuations without the energy balance theory? And if so, what are the benefits over the energy balance strategy? 2. During energy balance, how the oxidized macronutrient distribution that underlies the average energy expenditure is related to the macronutrient distribution of the average energy intake? 3. Is energy balance possible under a low-fat diet that simultaneously satisfies the following conditions? (a) The fat fraction of the absorbed energy intake is always less than the oxidized fat fraction of the energy expenditure. (b) The carbohydrate fraction of the absorbed energy intake is always greater or equal to the oxidized carbohydrate fraction of the energy expenditure. The first of these issues is addressed with the axiomatic method while the rest are managed through analythical arguments. On the whole, this analysis identifies inconsistencies in the principle of energy balance. The axiomatic approach results also in a simple mass balance model that fits experimental data and explains body composition alterations. This model gives rise to a convincing argument that appears to elucidate the advantage of low-carbohydrate diets over isocaloric low-fat diets. It is concluded, according to the aforementioned model, that weight fluctuations are ultimately dependent on the difference between daily food mass intake and daily mass loss (e.g., excretion of macronutrient oxidation products) and not on energy imbalance. In effect, it is shown that assuming otherwise may caused unintended weight gain.
“… Figure 7 The application of the EBT may lead to unintended weight gain. Current dietary guidelines advise subjects with adequate body weight to minimize health risks and avoid weight gain by adopting isocaloric LFDs [ 43 ]. Such practice may, however, result in unplanned weight gain.…”
Energy metabolism theory affirms that body weight stability is achieved as over time the average energy intake equals the average energy expenditure, a state known as energy balance. Here it is demonstrated, however, that weight stability coexists with a persistent energy imbalance. Such unexpected result emerges as a consequence of the answers to three fundamental problems: 1. Is it possible to model body weight fluctuations without the energy balance theory? And if so, what are the benefits over the energy balance strategy? 2. During energy balance, how the oxidized macronutrient distribution that underlies the average energy expenditure is related to the macronutrient distribution of the average energy intake? 3. Is energy balance possible under a low-fat diet that simultaneously satisfies the following conditions? (a) The fat fraction of the absorbed energy intake is always less than the oxidized fat fraction of the energy expenditure. (b) The carbohydrate fraction of the absorbed energy intake is always greater or equal to the oxidized carbohydrate fraction of the energy expenditure. The first of these issues is addressed with the axiomatic method while the rest are managed through analythical arguments. On the whole, this analysis identifies inconsistencies in the principle of energy balance. The axiomatic approach results also in a simple mass balance model that fits experimental data and explains body composition alterations. This model gives rise to a convincing argument that appears to elucidate the advantage of low-carbohydrate diets over isocaloric low-fat diets. It is concluded, according to the aforementioned model, that weight fluctuations are ultimately dependent on the difference between daily food mass intake and daily mass loss (e.g., excretion of macronutrient oxidation products) and not on energy imbalance. In effect, it is shown that assuming otherwise may caused unintended weight gain.
“…Dietary diversity (DD) is recognized as an important determinant of health and survival. Not only that, but most dietary guidelines around the world recommend increasing DD [ 13 , 14 , 15 ]. DD refers to the consumption of different food group quantities over a given period of time, and it is assessed using the Dietary Diversity Score (DDS), which is a concise and efficient indicator of dietary quality [ 16 ].…”
Diet is a modifiable factor in healthy population aging. Additionally, oral health and diet are important factors affecting depressive symptoms. To assess the mediating role of dietary diversity (DD) in oral health and depressive symptoms in older adults, we selected 8442 participants aged ≥ 65 years from the 2018 Chinese Longitudinal Health Longevity Survey (CLHLS) for a cross-sectional study. Depressive symptoms were determined based on scores on the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10). Dietary diversity scores (DDS) were established based on the frequency of intake of food groups. Oral health was measured by denture use and toothbrushing frequency. Stepwise multiple linear regression and PROCESS macros were used for mediated effects analysis and testing. The sample had a positive detection rate of 44.1% for depressive symptoms, 40.8% for denture use, and 41.9% for once-a-day toothbrushing. Denture use (ρ = −0.077, p < 0.01) and toothbrushing frequency (ρ = −0.115, p < 0.01) were negative predictors of depressive symptoms in older adults. DD significantly mediated the association between denture use (indirect effect −0.047; 95%CI: −0.068–0.028; p < 0.001), toothbrushing frequency (indirect effect −0.041; 95%CI: −0.054–0.030; p < 0.001), and depressive symptoms. Denture use and toothbrushing frequency not only directly reduce the risk of depressive symptoms in older adults, but also indirectly affect depressive symptoms through DD.
Background & aims: The association between dietary diversity (DD) changes and mortality remains unclear. We aimed to investigate the association between DD changes and all-cause mortality among older people. Methods: A total of 17,959 participants with a mean age of 84.8 years old were enrolled at baseline. Food groups were collected at baseline and follow-up using simplified food frequency questionnaire (FFQ), and then overall, plant-based and animal-based dietary diversity score (DDS) were calculated. DDS changes were calculated using DDS at baseline and the first follow-up. The association between three DDS changes (overall, plant-based and animal-based DDS) and subsequent all-cause mortality were evaluated. Nonparametrically restricted cubic splines and a multivariable-adjusted Cox proportional hazards model were used to estimate HRs and 95% CIs. Results: We documented 12,974 deaths over a 129,590 person-years of follow up. Compared with highto-high DDS pattern, participants with lower overall DDS patterns had increased mortality risk with HRs (95%CI) of 1.39 (1.29e1.49), 1.53 (1.37e1.70), 1.38 (1.18e1.60) and 1.55 (1.31e1.83) for medium-tomedium, low-to-low, low-to-high and high-to-low patterns, respectively. And compared with high-tohigh DDS pattern, the estimates were 1.34 (1.23e1.46), 1.49 (1.35e1.65), 1.43 (1.23e1.67) and 1.62 (1.40e1.88) for plant-based DDS, and 1.23 (1.15e1.31), 1.29 (1.20e1.40), 1.24 (1.12e1.37) and 1.28 (1.15 e1.44) for animal-based DDS for medium -to-medium, low-to-low, low-to-high and high-to-low patterns, respectively. There was a U-shaped association between DDS change scores and mortality, and compared with participants with whose DDS remained stable, those with extreme declines and extreme improvements had higher risks of mortality with HRs (95% CI) of 1.15 (1.09e1.22) and 1.11 (1.04e1.17). Conclusions: Maintaining a lower DDS, extreme declines and extreme improvements in DDS were all associated with an increased risk of all-cause mortality.
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