Environmental footprints of food consumption and dietary patterns among Lebanese adults: a cross-sectional study

Background: Current scientific literature suggests healthy dietary patterns may have less environmental impact than current consumption patterns, but most of the studies rely on theoretical modeling. The aim of this study was to assess the impact on resources (land, water, and energy) use and greenhouse gas (GHG) emissions of healthy dietary patterns in a sample of Italian adults. Methods: Participants (n = 1806) were recruited through random sampling in the city of Catania, southern Italy. Dietary consumption was assessed through a validated food frequency questionnaire (FFQ); dietary patterns were calculated through dietary scores. The specific environmental footprints of food item production/processing were obtained from various available life-cycle assessments; a sustainability score was created based on the impact of the four environmental components calculated. Results: The contribution of major food groups to the environmental footprint showed that animal products (dairy, egg, meat, and fish) represented more than half of the impact on GHG emissions and energy requirements; meat products were the stronger contributors to GHG emissions and water use, while dairy products to energy use, and cereals to land use. All patterns investigated, with the exception of the Dietary Approach to Stop Hypertension (DASH), were linearly associated with the sustainability score. Among the components, higher adherence to the Mediterranean diet and Alternate Diet Quality Index (AHEI) was associated with lower GHG emissions, dietary quality index-international (DQI-I) with land use, while Nordic diet with land and water use. Conclusions: In conclusion, the adoption of healthy dietary patterns involves less use of natural resources and GHG emissions, representing eco-friendlier options in Italian adults.

Life cycle assessment of various alternative management strategies in the swine industry was performed to evaluate their impact on greenhouse gas (GHG) emissions, cumulative energy use, and cumulative water use. The management strategies included the use of immunocastration (IC), production without ractopamine (NoRAC), production without antimicrobials used for either growth promotion (NoAGP) or disease prevention (NoPREV), production of entire males (boars) (EM), and use of gestation pens (PENS). A common baseline scenario representing standard management practices in the swine industry was created against which all alternative management practices were compared pairwise. The study scope was from cradle-to-farm gate with a functional unit of 1 kg live weight at the farm gate. The baseline and each alternative management scenario was simulated in Pig Production Environmental Footprint Calculator (PPEC) model by varying key variables to populate life cycle inventory inputs for SimaPro V7.3 (Pre' Consultant, the Netherlands), a life cycle assessment modeling program. Increase in GHG emissions, energy use, and water use were observed for NoAGP (1.56, 1.75, and 1.03%, respectively), NoPREV (17.32, 18.40, and 15.58%, respectively), and NoRAC (6.52, 4.87, and 7.52%, respectively) scenarios. For EM scenario, GHG emissions and energy use increased by 2.09 and 3.75%, respectively but water use decreased by 2.29%. Lower GHG emissions, energy use, and water use were observed for PENS (0.97, 1.50, and 0.97%, respectively) and IC (2.39, 2.57, and 2.96%, respectively) scenarios. These changes in the impact categories were statistically significant (P < 0.05) for all scenarios except for changes to GHG emissions for EM and changes to water consumption for PENS and NoAGP. However, the uncertainty analysis showed that the tails of distribution for baseline and alternative management scenario pair overlapped. The impact of management practices on sustainability metrics resulted from differences in pig performance parameters, manure production, feed consumption, etc. between various management practices and the baseline scenario. Due to uncertainties in input parameters, the results should be interpreted as general trends which specifically highlight trade-offs that may result from shifts in production practices. The study identified some of the hot spots in pig production and can be useful in determining best management practices to make swine production more environmentally sustainable.

Many Mediterranean countries, including Lebanon, are experiencing a shift in food consumption away from the traditional Mediterranean diet (MD), concomitant with the escalating burden of non-communicable diseases and dwindling environmental resources. Objective: to examine the adherence to the MD and its association with environmental footprints (EFPs), including water use, energy use, and greenhouse gas (GHG) emissions, among Lebanese adults. Data of Lebanese adults were drawn from the national food consumption survey (n = 2610). Assessment of dietary intake was conducted using a food-frequency questionnaire. Adherence to the MD was examined using four published MD scores. Metrics for the EFPs were calculated using a review of existing life cycle assessments (LCAs). For all MD scores, less than 13% of participants were in the highest tertile. After adjustments for covariates, two of the MD scores were associated with lower water use. For GHG, significant inverse associations were observed with all MD scores. Energy use was not associated with MD scores. Overall, low adherence to the MD among Lebanese adults was observed, together with an inverse association between adherence to the MD and water use and GHG emissions. These findings support and enforce ongoing efforts that aim to increase adherence to the MD in order to address health issues, as well as tackle environmental sustainability.

Reply to L Aleksandrowicz et al.

This study investigated major healthy and sustainable dietary patterns in the Dutch population. Two 24-hour dietary recalls were collected in 2078 participants aged 19–79 years in the Dutch National Food Consumption Survey 2012–2016. Dietary patterns were identified using reduced rank regression. Predictor variables were food groups and response variables were Dutch Healthy Diet index 2015 (DHD15-index) score, greenhouse gas emissions (GHGE), and blue water use. Three patterns were discovered, including a “high fruit and vegetable dietary pattern”, a “low meat dietary pattern”, and a “high dairy, low fruit juices dietary pattern”. Diets in the highest quartile of these patterns had higher DHD15-index score than the average population. However, diets of the “high fruit and vegetable dietary pattern” were associated with higher dietary GHGE (14%) and blue water use (69.2%) compared to the average population. Diets of the “low meat dietary pattern” were associated with lower GHGE (19.6%) and higher blue water use (7.7%). Concluding, the “low meat dietary pattern” was the most healthy and sustainable dietary pattern in this population. The addition of blue water use as an environmental impact indicator shows the difficulty of finding existing dietary patterns that have low environmental impact in all determinants.

Providing a growing global population with healthy and sustainable diets is an immediate challenge. In the current study, estimates were obtained for the environmental footprints (land, water, and greenhouse gas (GHG) emissions) in association with the Mediterranean diet (MED) and the EAT-Lancet reference diet, which represents a healthy diet derived from sustainable food systems. We used a newly developed Sustainable Healthy Diet (SHED) index that was validated for the Israeli population by Tepper et al. in 2020.MethodsA group of 525 participants were recruited via social media, email, and phone. Demographic characteristics, quality of life, and answers to the SHED-index questionnaire were obtained. Dietary assessment was performed using the 116-item Food Frequency Questionnaire (FFQ), which was developed for the Israeli population. Adherence to the MED was calculated using a 9-point score. Adherence to the EAT-Lancet reference diet was assessed through the consumption of 14 food components. The environmental pressure of these dietary patterns was determined based on the “footprint family indicators,” which include land, water, and carbon footprints per unit of agricultural and food products. We assigned values for each food comprising the FFQ and calculated the environmental load for each dietary pattern. Statistical analyses were performed using the R package version 4.1.1 to compare environmental footprint values according to tertiles of the MED score, EAT-Lancet score, and SHED score.ResultsThe participants (n = 525) were 49% women, educated (82% had academic education), and physically active, and only 13% were smokers. The highest tertiles of adherence to the MED, adherence to the EAT-Lancet reference diet, and the SHED index were associated with the lowest GHG emissions and land use, as well as higher water use. Meat consumption contributed the most to land use, while dairy contributed the most to GHG emissions, and fruits contributed the most to water use.ConclusionsOur analysis reveals that animal protein is the highest contributor to GHG emissions and land use, while fruits and vegetables contribute the most to water consumption. Nevertheless, most of the fruits and vegetables are grown using treated wastewater, which reduces environmental pressure. Given these findings, we suggest that MED and EAT-Lancet dietary patterns should be included in national dietary guidelines.

Food consumption patterns affect the environment as well as public health, and monitoring is needed. The aim of this study was to evaluate the Dutch food consumption patterns for environmental (greenhouse gas (GHG) emissions and blue water use) and health aspects (Dutch Healthy Diet index 2015), according to age, gender, and consumption moments. Food consumption data for 4313 Dutch participants aged 1 to 79 years were assessed in 2012 to 2016, by two non-consecutive 24-h recalls. The environmental impact of foods was quantified using a life cycle assessment for, e.g., indicators of GHG emissions and blue water use. The healthiness of diet, operationalized by the Dutch Healthy Diet index 2015, was assessed for 2078 adults aged ≥19 years. The average daily diet in the Netherlands was associated with 5.0 ± 2.0 kg CO2-equivalents of GHG emissions and 0.14 ± 0.08 m3 of blue water use. Meat, dairy and non-alcoholic beverages contributed most to GHG emissions, and non-alcoholic beverages, fruits, and meat to blue water use. More healthy diets were associated with a lower GHG emission and higher blue water use. Different associations of environmental indicators (GHG emissions and blue water use) with health aspects of diets need to be considered when aligning diets for health and sustainability.

Food production is a major driver of greenhouse gas (GHG) emissions, water and land use, and dietary risk factors are contributors to non-communicable diseases. Shifts in dietary patterns can therefore potentially provide benefits for both the environment and health. However, there is uncertainty about the magnitude of these impacts, and the dietary changes necessary to achieve them. We systematically review the evidence on changes in GHG emissions, land use, and water use, from shifting current dietary intakes to environmentally sustainable dietary patterns. We find 14 common sustainable dietary patterns across reviewed studies, with reductions as high as 70–80% of GHG emissions and land use, and 50% of water use (with medians of about 20–30% for these indicators across all studies) possible by adopting sustainable dietary patterns. Reductions in environmental footprints were generally proportional to the magnitude of animal-based food restriction. Dietary shifts also yielded modest benefits in all-cause mortality risk. Our review reveals that environmental and health benefits are possible by shifting current Western diets to a variety of more sustainable dietary patterns.

IntroductionFood consumption is important for population as well as planetary health. Globally, fresh water is a scarce resource. For both fresh water use and greenhouse gas (GHG) emissions a risk of exceeding the planetary boundaries exists. Food production accounts for approximately 90% of the global water footprint and for 30% of global greenhouse gas emissions. In this study, the Dutch food consumption patterns are evaluated for blue water use and greenhouse gas emission and its association with dietary quality (Dutch Healthy Diet index 2015).Materials and MethodsFood consumption was assessed, in 2012–2016, by two non-consecutive 24 h recalls, in Dutch children and adults aged 1–79 y (n = 4313) (www.wateetnederland.nl). Environmental impact of foods was quantified using life cycle assessment for e.g. indicators (blue) water use and GHG emission. For each participant aged ≥ 18 y (n = 2078), a score was calculated for the Dutch Healthy Diet 2015 index (DHD15) to quantify the quality of diet with respect to health. Statistical analyses were stratified for age and gender.ResultsDaily diets in the Netherlands were associated with 0.14 ± 0.10 m3 blue water use and 5.3 ± 2.4 kg CO2-equivalents GHG emission. Non-alcoholic beverages, nuts and fruits were most important food groups for use of blue water, and meat, dairy and non-alcoholic beverages for GHG emission. DHD15 score was 4.2 ± 1.5 for men and 4.9 ± 1.4 for women. Diets with a higher DHD15 score had a higher blue water use (r = 0.17) and a lower GHG emission (r = -0.35).DiscussionDifferent associations of environmental indicators (blue water use and GHG emission) with health aspects of diets need to be considered when aligning diets for health and sustainability.

As part of the Net Zero Carbon Water Cycle Program (NZCWCP) for Victoria state in Australia, we have sought to understand the potential to reduce household energy consumption and related Greenhouse Gas (GHG) emissions by influencing water use. Digital metering data disaggregated into 57 million discrete water usage events across 105 households at a resolution of 10 millilitres at 10 second intervals from June 2017 to March 2020, from a previous Yarra Valley Water (Melbourne, Australia) study, was analysed, together with the dynamic relationship between the multiple energy sources (natural gas, grid electricity, solar) used to heat water for showers in each hour of the day. Water-related energy (WRE) use, including water desalination and treatment, pumping, heating, wastewater collection and treatment, comprised 12.6% of Australia&amp;#8217;s primary energy use in 2019. Water heating (by natural gas and electricity) comprised the largest component of WRE use for across residential, commercial, and industrial sectors. Furthermore, 69% of Victoria&amp;#8217;s total water usage was by residential customers in 2020-2021. WRE GHG emissions were around 3.8% of Victoria&amp;#8217;s total GHG emissions in 2018. Showers (~50% of residential WRE), system losses (~27% of residential WRE), and clothes washers (~9% of residential WRE) are the three largest components of WRE consumption. The main objective of this work is the creation of industry-accessible tools to improve knowledge and management options from the understanding of reductions in cost and GHG emissions from household showering WRE use. Potential options considered, to reduce water and energy use, as well as associated GHG emissions and customer utility bills, include (a) behaviour management such as water and energy pricing to change time of use behaviours, and (b) the adoption of efficient shower head improvements. Shower WRE and GHG emissions were found able to be strongly impacted by small changes in daily routines. GHG emissions reduction from showering could be reduced up to 20 (in summer) - 22% (in winter) by shifting demand time of showering or replacing residential showerheads. Extrapolated to state and Australian scales, reductions in water usage could be up to 14 GL (Victoria) and 144 GL (Australia), and reductions in GHG emissions 1,600 ktCO2eq (Victoria) and 17,300 ktCO2eq (Australia). It provides fundamental new information which could inform a suite of new management options to impact water-related energy from showers, and related GHG emissions and customer water and energy cost.

Background/Objectives: Contemporary food systems face dual imperatives of ensuring nutritional adequacy while minimizing environmental resource consumption, yet conventional dietary assessment methodologies inadequately integrate these competing objectives. This simulation-based proof-of-concept study developed an artificial intelligence-driven computational framework synthesizing nutritional evaluation, environmental footprint quantification, and economic accessibility assessment. Methods: The analytical architecture integrated random forest classification, dimensionality reduction, and scenario-based optimization across a simulated population cohort of 1500 individuals. Food composition data encompassed 55 representative foods across eight categories linked with greenhouse gas emissions, water use, and price parameters. Four dietary patterns (Mediterranean, Western, Plant-based, Mixed) were characterized across nutrient adequacy, greenhouse gas emissions, water consumption, and economic cost. Results: Random forest classification achieved 39.1% accuracy, with cost, greenhouse gas emissions, and water consumption emerging as the most discriminating features. Dietary patterns exhibited convergent macronutrient profiles (protein 108.8–112.8 g per day, 4% variation) despite categorical distinctions, while calcium inadequacy pervaded all patterns (867–927.5 mg per day, 7–13% below requirements). Environmental footprints demonstrated limited differentiation (greenhouse gas 3.73–3.96 kg CO2e per day, 6% range). Bootstrap resampling (n = 1000) confirmed narrow confidence intervals, with NHANES validation revealing substantial energy intake deviations (38–58% above observed means) attributable to adequacy-prioritized design rather than observed consumption patterns. Scenario modeling identified seasonally flexible dietary configurations maintaining micronutrient and protein adequacy while reducing water use to 87% of baseline at modest cost increases. Conclusions: This framework establishes a validated computational infrastructure for integrated dietary assessment benchmarked against sustainability thresholds and epidemiological reference data, demonstrating the feasibility of AI-driven evaluation of dietary patterns across nutritional, environmental, and economic dimensions.

Background: Food production is a major driver of environmental change, while dietary risks are the leading cause of global disease burden. Studies suggest that adoption of healthy diets in high-income countries can provide environmental co-benefits. However, little is known about such options in low and middle-income countries. India is home to one-fifth of the global population, and experiencing complex nutritional challenges, alongside critical environmental pressures on its ability to produce food. This project assesses the potential for dietary change to improve health and diet-related environmental footprints in India. Methods and results: A systematic review assessed the sustainable dietary patterns studied in the literature, and their impacts on a range of environmental indicators, to understand which diets may lead to improved environmental and health outcomes. Adoption of sustainable diets is generally estimated to reduce environmental footprints, though large variations in reductions are seen across sustainable diet types. Following national dietary guidelines may be a relevant public health goal with both environmental and health benefits. A comparison was undertaken of a number of dietary intake data sources in India, examining relative differences in overall intake, and intake of key food groups, to better understand data suitability for sustainable diet analyses. The comparison highlighted the 2011-2012 National Sample Survey (NSS) household expenditure surveys as a relevant data source for the project, though data sources showed high variability in intake, particularly for a set of key nutrient-dense food groups. The NSS and environmental footprint data were matched to estimate the change in greenhouse gas (GHG) emissions, land use (LU), and water footprints (WFs) that may result from national adoption of healthy dietary guidelines, and contrasted this with a scenario of widespread uptake of “affluent” diets. A shift to healthy guidelines in India would result in a small increase in environmental footprints (4-5% for GHG emissions, LU and WFs), though this national result masked large variations among sub-samples; for example, healthy diet shifts among those who consume above recommended dietary energy could decrease emissions by 6-16% across the three environmental indicators. Shifts to affluent diets would result in large increases of about 19-36% across indicators. Lastly, differences in cost were assessed between observed healthy and lowerfootprint diets, and average diets with sufficient dietary energy (“adequate” diets). Overall, healthy diets with lower footprints were slightly more expensive than an adequate diet. Large variations were observed among sub-samples of the population: improved diets were particularly more expensive for lower-income individuals and rural residents, while cheaper, or had no difference in price, for individuals in the highest quartile of socioeconomic status, and for urban residents. Higher expenditure on improved diets was particularly associated with fruit and vegetables, and dairy. Conclusions: Achieving the critical public health goal of healthy diets while minimising diet-related environmental footprints in India may require three broad strategies: increasing the efficiency of agricultural production, alongside efforts to improve the affordability of healthy dietary change, and the active promotion of healthy and lower-footprint diets for those who can currently afford them.

Agriculture is a major contributor to India's environmental footprint, particularly through greenhouse gas (GHG) emissions from livestock and fresh water used for irrigation. These impacts are likely to increase in future as agriculture attempts to keep pace with India's growing population and changing dietary preferences. Within India there is considerable dietary variation, and this study therefore aimed to quantify the GHG emissions and water usage associated with distinct dietary patterns.Five distinct diets were identified from the Indian Migration Study – a large adult population sample in India – using finite mixture modelling. These were defined as: Rice & low diversity, Rice & fruit, Wheat & pulses, Wheat, rice & oils, Rice & meat. The GHG emissions of each dietary pattern were quantified based on a Life Cycle Assessment (LCA) approach, and water use was quantified using Water Footprint (WF) data. Mixed-effects regression models quantified differences in the environmental impacts of the dietary patterns.There was substantial variability between diets: the rice-based patterns had higher associated GHG emissions and green WFs, but the wheat-based patterns had higher blue WFs. Regression modelling showed that the Rice & meat pattern had the highest environmental impacts overall, with 0.77 (95% CI 0.64–0.89) kg CO2e/capita/day (31%) higher emissions, 536 (95% CI 449–623) L/capita/day (24%) higher green WF and 109 (95% CI 85.9–133) L/capita/day (19%) higher blue WF than the reference Rice & low diversity pattern.Diets in India are likely to become more diverse with rising incomes, moving away from patterns such as the Rice & low diversity diet. Patterns such as the Rice & meat diet may become more common, and the environmental consequences of such changes could be substantial given the size of India's population. As global environmental stress increases, agricultural and nutrition policies must recognise the environmental impacts of potential future dietary changes.

BackgroundLebanon is grappling with numerous environmental challenges, including water scarcity, landfill waste, deforestation, and rising air pollution. Food choices significantly influence global greenhouse gas emissions and environmental impacts, making it crucial to evaluate the environmental footprints (EFPs) of Lebanon’s current dietary habits. This study aimed to assess food consumption patterns and their EFPs among a nationally representative sample of Lebanese adults.MethodsA cross-sectional survey was conducted from May to September 2022, involving 444 Lebanese adults aged 18 to 64 years. The sample was representative, and participants were distributed across the eight Lebanese governorates. Sociodemographic and medical data were collected via a questionnaire, food consumption was assessed through a validated Food Frequency Questionnaire (FFQ) and two non-consecutive 24-hour recalls, and anthropometric measurements were also taken. EFPs were derived from databases and repositories.ResultsThe typical EFPs of an average Lebanese adult included water usage of 2,862.39 ± 1,617.88 L/day, greenhouse gas emissions of 4.43 ± 2.29 kg CO2-eq/day, and nitrogen use of 12.72 ± 6.76 g/day. Animal products were the primary contributors to greenhouse gas emissions, while vegetable products had the highest water footprint and nitrogen loss impact on the environment. Grains and cereals, the most consumed food category, significantly influenced the water footprint and nitrogen loss. Additionally, meat consumption notably drove greenhouse gas emissions.ConclusionLebanon must address its environmental challenges and the impact of dietary choices on greenhouse gas emissions and EFPs. By evaluating and understanding the environmental consequences of current dietary patterns, Lebanon can take proactive steps towards promoting sustainable food practices and mitigating environmental degradation.

Background Current dietary patterns threaten individual and planetary health. Healthcare settings can set a positive example for dietary change, but data on the quality of food they offer is scarce. The aim of our study was to assess the environmental footprint and nutritional quality of food service in hospitals and nursing homes in Germany. Methods We collected 6-12 months of food procurement data and all available meal plans from three nursing homes and two hospitals in Germany. Procured food items were categorized into 50 food groups (e.g., potatoes, beef, apples), and the environmental footprint was calculated (i.e., land use, greenhouse gas (GHG) emissions, acidification, eutrophication, and water use) using life-cycle analysis factors based on a recent meta-analysis. Lunches from a representative week were broken down into their constituent ingredients and analyzed for adherence to the Planetary Health Diet (PHD) using an established dietary index (PHDI). Results Preliminary analysis of one nursing home and one hospital showed that animal-source foods (ASF) accounted for 70% of overall GHG emissions and land use and 76% of water use, primarily from beef, pork, milk, and cheese. Among plant-based foods, coffee disproportionately contributed to the environmental footprint. Red meat accounted for 30-45% of lunch calories consumed (13-25% of weight) and potatoes accounted for 20-24% of calories (31-35% of weight), whereas vegetables and legumes combined accounted for 11-15% of calories (33-35% of weight). Nursing home meals achieved 61 and hospital meals 71 out of 150 points on the PHDI. Conclusions Healthcare institutions in Germany have poor adherence to the PHD, with up to two-thirds of calories derived from red meat and potatoes. Unsurprisingly, ASF account for the majority of the institutions’ environmental food footprint. Policies to make healthcare foodservice more environmentally sustainable while ensuring nutritional adequacy are urgently needed. Key messages • Foodservice in German hospitals and nursing homes is neither healthy nor environmentally sustainable. • Policies are needed to improve healthcare food service for individual and planetary health.