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Carbon footprint of self-selected US diets: nutritional, demographic, and behavioral correlates.

ABSTRACT: BACKGROUND:A substantial portion of greenhouse gas emissions (GHGE) has been attributed to the food sector, but little is known about the association between the carbon footprint of individual self-selected diets in the United States and nutritional quality. OBJECTIVES:The aims of this study were to assess the GHGE from individual self-selected diets in the United States and examine their association with nutritional quality of the diets, demographic patterns, and food-related behaviors. METHODS:The dietary GHGE from US adults (>18 y, N = 16,800) in the 2005-2010 National Health and Nutrition Examination Survey (NHANES) were calculated by linking all foods consumed in their 24-h recall diets to our new database of food environmental impacts. Diets were ranked by GHGE/1000 kcal. Those in the top and bottom quintiles were compared on the US Healthy Eating Index (HEI) and on the amounts of specific nutrients known to be under- or overconsumed in the US population. Demographic and behavioral variables from the NHANES were also correlated to these dietary carbon footprints. RESULTS:Diets in the bottom quintile accounted for one-fifth the total emissions (GHGE/1000 kcal) of those in the top quintile, yet had significantly higher (P < 0.001) HEI scores by 2.3 ± 0.7 points on a 100-point scale. These low-GHGE diets contained higher amounts of fiber and vitamin E and lower amounts of sodium and saturated fats, whereas high-GHGE diets contained higher amounts of vitamins A and D, choline, calcium, iron, and potassium. Low-GHGE diets had less meat, dairy, and solid fats, and more poultry, plant protein foods, oils, whole and refined grains, and added sugars. CONCLUSIONS:Food patterns responsible for lower GHGE had a better overall diet quality and were more nutritious on several key dimensions, although not all. These results can inform dietary guidance and other policies that seek to address the goals of improved dietary intakes and reduced food-related emissions.

SUBMITTER: Rose D

PROVIDER: S-EPMC6408204 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Carbon footprint of self-selected US diets: nutritional, demographic, and behavioral correlates.

Rose Donald D Heller Martin C MC Willits-Smith Amelia M AM Meyer Robert J RJ

The American journal of clinical nutrition 20190301 3

<h4>Background</h4>A substantial portion of greenhouse gas emissions (GHGE) has been attributed to the food sector, but little is known about the association between the carbon footprint of individual self-selected diets in the United States and nutritional quality.<h4>Objectives</h4>The aims of this study were to assess the GHGE from individual self-selected diets in the United States and examine their association with nutritional quality of the diets, demographic patterns, and food-related beh ...[more]

PMID: 30698631

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Project description:BackgroundThe role of diet in health is well established and, in the past decade, more attention has been given to the role of food choices in the environment. The agricultural sector produces about a quarter of the world's greenhouse gas emissions (GHGE), and meat production, especially beef, is an important contributor to global GHGE. Our study aimed to address a fundamental gap in the diet-climate literature: identifying consumers who are receptive to making dietary changes, and the effect of their potential changes on GHGE, diet healthfulness, and diet costs.MethodsDietary data on US individuals from a nationally representative survey were linked to food-related GHGE. We identified individuals receptive to changing their diets (potential changers) as those who reported trying US dietary guidance and were likely to agree that humans contribute to climate change. We assessed GHGE, diet healthfulness measured by the Healthy Eating Index (HEI), and diet costs before and after hypothetical changes replacing either beef or meats with poultry or plant-protein foods.FindingsOur sample comprised 7188 individuals, of whom 16% were potential changers. These were disproportionately women, highly educated, or had higher income compared with individuals deemed not likely to change. Replacing 100% of beef intake in potential changers with poultry reduced mean dietary GHGE by 1·38 kg CO2-equivalents per person per day (95% CI 1·19-1·58), a 35·7% decrease. This replacement also increased mean HEI by 1·7% and reduced mean diet costs by 1·7%. We observed the largest changes when replacing all beef, pork, or poultry intake with plant-protein foods (GHGE decreased by 49·6%, mean HEI increased by 8·7%, and dietary costs decreased by 10·5%). Hypothetical replacements in the potential changers alone resulted in whole population reductions in 1-day dietary GHGE of 1·2% to 6·7%, equivalent to 22-126 million fewer passenger vehicle km.InterpretationIndividual-level diet studies that include a variation in response by consumers can improve our understanding of the effects of climate policies such as those that include sustainability information in national dietary guidance. In our study, we found that changes by a small percentage of motivated individuals can modestly reduce the national dietary GHGE. Moreover, these substitutions can modestly improve diet healthfulness and reduce diet costs for individuals who make these changes.FundingWellcome Trust.

Project description:STUDY OBJECTIVES:Individuals with primary insomnia often have poorer self-reported sleep than objectively measured sleep, a phenomenon termed negative sleep discrepancy. Recent studies suggest that this phenomenon might differ depending on comorbidities. This study examined sleep discrepancy, its night-to-night variability, and its correlates in comorbid insomnia and fibromyalgia. METHODS:Sleep diaries and actigraphy data were obtained from 223 adults with fibromyalgia and insomnia (age = 51.53 [standard deviation = 11.90] years; 93% women) for 14 days. Sleep discrepancy was calculated by subtracting diary from actigraphy estimates of sleep onset latency (SOL-D), wake after sleep onset (WASO-D), and total sleep time (TST-D) for each night. Night-to-night variability in sleep discrepancy was calculated by taking the within-individual standard deviations over 14 days. Participants completed measures of mood, pain, fatigue, sleep/pain medications, nap duration, and caffeine consumption. RESULTS:Average sleep discrepancies across 14 days were small for all sleep parameters (< 10 minutes). There was no consistent positive or negative discrepancy. However, sleep discrepancy for any single night was large, with average absolute discrepancies greater than 30 minutes for all sleep parameters. Greater morning pain was associated with larger previous-night WASO-D, although diary and actigraphy estimates of WASO remained fairly concordant. Taking prescribed pain medications, primarily opioids, was associated with greater night-to-night variability in WASO-D and TST-D. CONCLUSIONS:Unlike patients with primary insomnia, patients with comorbid fibromyalgia do not exhibit consistent negative sleep discrepancy; however, there are both substantial positive and negative discrepancies in all sleep parameters at the daily level. Future research is needed to investigate the clinical significance and implications of high night-to-night variability of sleep discrepancy, and the role of prescribed opioid medications in sleep perception.

Dataset Information

Carbon footprint of self-selected US diets: nutritional, demographic, and behavioral correlates.

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Carbon footprint of self-selected US diets: nutritional, demographic, and behavioral correlates.

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