Relationships of Physical Activity and Diet Quality with Body Composition and Fat Distribution in US Adults

Xu, Furong; Greene, Geoffrey; Earp, Jacob E.; Adami, Alessandra; Delmonico, Matthew J.; Lofgren, Ingrid E.; Greaney, Mary L.

doi:10.1002/oby.23018

Cited by 10 publications

(8 citation statements)

References 33 publications

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“…Furthermore, their results could be influenced by a range of different factors such as changes in lifestyle trends, cultural movements, economic trends, and federal policy changes. For example, one of our previous studies found that improving dietary quality improved fat distribution when accounting for other factors like sex, race/ethnicity, education and family income [28]. Given national trends in adiposity [23], it should not be surprising that there are initial increases in visceral adipose measures across most groups.…”

Section: Discussionmentioning

confidence: 97%

“…( 4) Additionally, ratio of family income to poverty (0-4.99, 5 or above) has been classified into two categories: at or above (≥1), below poverty level (<1) [24,26]. In addition to demographics, body fat percentage has been included as one of confounding variables for certain analyses due to its possible influence on study variables [27,28].…”

Section: Confounding Variablesmentioning

confidence: 99%

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The Demographic Specific Abdominal Fat Composition and Distribution Trends in US Adults from 2011 to 2018

Earp

Blissmer

et al. 2022

IJERPH

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Despite the rising awareness of abdominal adiposity associated health problems and demographic health disparities, research is lacking about abdominal fat trends using a national representative sample of US adults. Our purpose was to examine national demographic specific abdominal fat composition and distribution trends from 2011 to 2018. This trend analysis was using National Health and Nutrition Examination Survey data (n = 13,163). Visceral adipose percent (VAT%), visceral adipose tissue area (VAA) and visceral to subcutaneous adipose area ratio (VSR) were utilized in data analyses. Multiple polynomial linear regression was utilized with adjustment for confounding variables. Our findings revealed that VAT%, VAA and VSR trends were concave among all demographic groups. The VAT%, VAA and/or VSR changes were observed in most demographic groups (p < 0.05) except younger, White and Black respondents. The pattern was consistent with biennial increases up to 2014 or 2016 followed by decreases in 2017–2018. There were demographic disparities, with middle-aged respondents and Hispanics having the most evident VAT%, VSR and/or VAA changes biennially when compared to their counterparts (p < 0.05). In conclusion, abdominal fat composition and distribution increased before 2014 or 2016 but decreased afterwards with variations by age and/or race/ethnicity. Further research is needed to explore the possible causes of abdominal fat changes overtime.

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Section: Discussionmentioning

confidence: 97%

Section: Confounding Variablesmentioning

confidence: 99%

The Demographic Specific Abdominal Fat Composition and Distribution Trends in US Adults from 2011 to 2018

Earp

Blissmer

et al. 2022

IJERPH

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“…Other factors such as the reported physical activity were low in this population and they did not differ between groups or over time; therefore, they do not explain the attenuated LBM loss in the HP group. In individuals who are not losing weight, diet quality is associated with higher LBM, with or without physical activity (34). Understanding how to preserve LBM during CR continues to be a concern in the field, and future studies might explore further whether protein sources in combination with other foods affect LBM.…”

Section: Discussionmentioning

confidence: 99%

Higher protein intake during caloric restriction improves diet quality and attenuates loss of lean body mass

Ogilvie

Schlussel

Sukumar

et al. 2022

Obesity

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Individuals with overweight or obesity often have poor-quality diets that lack fruits and vegetables, whole grains, and legumes and contain excessive amounts of added sugar and saturated, compared with unsaturated, fatty acids (1), which can lead to higher risk of greater weight gain and chronic disease (2,3). Weight loss (WL) of 5% to 10% may prevent chronic disease (4); however, WL diets that restrict energy also reduce healthy food and micronutrient intake (5).The effect of higher protein intake during WL on health outcomes has been reported extensively, and there is evidence that it can promote a healthy body weight, attenuate loss of muscle mass (6,7), and reduce chronic disease (8-10). In addition, it was shown that dietary protein contributes to nutrient adequacy in the general population (11). However, the impact of self-selected dietary protein on diet quality has not been examined, to our knowledge, in a longitudinal study (11), such as during caloric restriction (CR). The link between protein intake and diet quality is important because diet quality is suboptimal in the US, and higher-protein WL diets are popular. In addition, the nutrient adequacy in populations consuming lower

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“…Several factors affect body composition, and diet and level of physical activity are some of the most important aspects to be considered (4,5). Low-carbohydrate diets, for example, may be effective in decreasing FM in obese individuals (6), whereas high-protein diets may have a beneficial effect on weight loss, increasing FM loss and preserving fat-free mass (FFM) (7).…”

Section: Introductionmentioning

confidence: 99%

Ultra-processed food consumption is associated with increase in fat mass and decrease in lean mass in Brazilian women: A cohort study

et al. 2022

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ObjectiveTo investigate the association between ultra-processed food consumption at 23–25 years of age and measurements of body composition–fat mass, fat mass distribution and lean mass at 37–39 years of age in Brazilian adults.Methods1978/1979 birth cohort study conducted with healthy adults from Ribeirão Preto, São Paulo, Brazil. A total of 1,021 individuals participated in the fat mass analysis (measured by air displacement plethysmography) and 815 in the lean mass analysis and fat mass distribution (assessed by dual energy X-ray absorptiometry). Food consumption was evaluated by a food frequency questionnaire. Food items were grouped according to the level of processing as per the NOVA classification. Ultra-processed food consumption was expressed as a percentage of total daily intake (g/day). Linear regression models were used to estimate the effect of ultra-processed food consumption (g/day) on body mass index, body fat percentage, fat mass index, android fat, gynoid fat, android-gynoid fat ratio, lean mass percentage, lean mass index and appendicular lean mass index. Marginal plots were produced to visualize interactions.ResultsThe mean daily ultra-processed food consumption in grams was 35.8% (813.3 g). There was an association between ultra-processed food consumption and increase in body mass index, body fat percentage, fat mass index, android fat and gynoid fat and decrease in lean mass percentage, only in women.ConclusionA high ultra-processed food consumption is associated with a long-term increase in fat mass and a decrease in lean mass in adult women.

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Relationships of Physical Activity and Diet Quality with Body Composition and Fat Distribution in US Adults

Cited by 10 publications

References 33 publications

The Demographic Specific Abdominal Fat Composition and Distribution Trends in US Adults from 2011 to 2018

The Demographic Specific Abdominal Fat Composition and Distribution Trends in US Adults from 2011 to 2018

Higher protein intake during caloric restriction improves diet quality and attenuates loss of lean body mass

Ultra-processed food consumption is associated with increase in fat mass and decrease in lean mass in Brazilian women: A cohort study

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