Spatial-Temporal Footprints Assessment and Driving Mechanism of China Household Diet Based on CHNS

Association between triglyceride-glucose index and hypertension: a cohort study based on the China Health and Nutrition Survey (2009-2015)

AIM

Insulin resistance (IR) may participate in the pathogenesis of hypertension by mediating low-grade systemic inflammation. The triglycerides-glucose (TyG) index has recently been suggested as a reliable alternative biochemical marker of IR compared with traditional methods. Herein, we speculated TyG index may also be associated with hypertension.

METHODS

Data of adults were extracted from the China Health and Nutrition Survey (CHNS) in 2009-2015 in this retrospective cohort study. The TyG index was calculated using the formula: TyG = Ln [fasting triglycerides (mg/dL) ×fasting glucose (mg/dL)/2]. Associations between TyG index and hypertension were evaluated by univariate and multivariate logistic regression analyses with odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses of age and gender were also performed. In addition, we assessed the interaction effect between TyG index and body mass index (BMI) on hypertension in participants with different age and gender.

RESULTS

Among 3,413 eligible participants, 1,627 (47.67%) developed hypertension. The average TyG index in hypertension group and non-hypertension group was 8.58 and 8.39 respectively. After adjusting for covariates, we found that compared with participants with TyG index ≤ 8.41 (median value), those who had higher TyG index seemed to have higher odds of hypertension [OR = 1.17, 95%CI: (1.01-1.37)]. Similarly, this association was also discovered in participants who aged ≤ 65 years old [OR = 1.19, 95%CI: (1.01-1.39)] or were female [OR = 1.35, 95%CI: (1.10-1.65)]. Additionally, there was a potential additive interaction effect between obesity and TyG index on hypertension.

CONCLUSION

High TyG index was associated with high odds of hypertension in general population in China, but the causal relationship between them needed further exploration.

Nutrition and its footprints: Using environmental indicators to assess the nexus between sustainability and food

Current food systems are associated with the unsustainable use of natural resources; therefore, rethinking current models is urgent and is part of a global agenda to reach sustainable development. Sustainable diets encompass health, society, economy, culture as well as the environment, in addition to considering all the stages that make up the food production chain. This study aimed to perform a review on the importance of using environmental footprints (EnF) as a way of assessing the environmental impacts of food systems. The most used EnF to assess impacts related to the food system was the carbon footprint, followed by the water footprint, and the land use footprint. These EnF usually measured the impacts mainly of the current diet and theoretical diets. Animal-source foods were the ones that most contribute to the environmental impact, with incentives to reduce consumption. However, changing dietary patterns should not be restricted to changing behavior only, but should also involve all stakeholders in the functioning of food systems. We conclude that EnF are excellent tools to evaluate and guide the adoption of more sustainable diets, and can be applied in different contexts of food systems, such as food consumption analysis, menu analysis, food waste, and inclusion of EnF information on food labels.

Sensory Complexity: From Sensory Measurement to Consumption Behavior

Sensory analysis is a multidisciplinary field that includes the measurement, interpretation, and understanding of human responses to the sensory properties of products and it is essential to explore consumer behavior [...].

Urban Metabolism of Food-Sourced Nitrogen among Different Income Households: A Case Study Based on Large Sample Survey in Xiamen City, China

Food consumption is fundamental for urban households if they are to sustain production and daily life. Nitrogen resulting from food consumption has significantly contributed to pollutant emissions in urban ecosystems. Taking Xiamen city, a rapid urbanizing area of southeast China as a case study, we evaluated the food-sourced nitrogen consumption of households based on a large simple onsite questionnaire survey, as well as differences between households in the consumption of plant-based and animal-based foods. A material flow analysis (MFA) was conducted to simulate the urban metabolism of food-sourced nitrogen and environmental emissions among different income groups. The impacts of household attributes, plant-based food consumption, and animal-based food consumption on environmental nitrogen emissions were examined with a structural equation model (SEM). Our results show that the surveyed households' diets were more plant-based and less animal-based. Aquatic products and livestock were the source of 43.7% of food-sourced nitrogen, and 84.5% of the food-sourced nitrogen was discharge into the environment through direct discharge and waste treatment. Soil, water, and air emissions accounted for 62.8%, 30.1%, and 7.1% of the food-sourced nitrogen, respectively. Household income, household size, and household area are all associated with accelerating increases of nitrogen emissions released into the environment, though middle-income group households have the highest food-sourced environmental nitrogen emissions. On this basis, we discuss how to better manage the urban metabolism of food-sourced nitrogen, so as to improve urban household consumption, lower nitrogen emissions, and improve food security.

Spatial–Temporal Heterogeneity and Driving Factors of Rural Residents’ Food Consumption Carbon Emissions in China—Based on an ESDA-GWR Model

The increase in income among Chinese residents has been accompanied by dramatic changes in dietary structure, promoting a growth in carbon emissions. Therefore, in the context of building a beautiful countryside, it is of great significance to study the carbon emissions of rural residents’ food consumption to realize the goal of low-carbon food consumption. In this paper, the calculation of food consumption carbon emissions of Chinese rural residents is based on the carbon conversion coefficient method, and the spatial heterogeneity of influencing factors is analyzed with the aid of the ESDA-GWR model. The results indicate that the per capita food consumption carbon emissions of rural residents have increased by 1.68% annually, reaching 336.73 kg CO2-eq in 2020, which is 1.32 times that of 2002. Carbon emissions generated from rural residents’ food consumption have significant spatial agglomeration characteristics, showing the spatial distribution characteristics of a north–south confrontation, with a central area collapse. The influencing factors of food consumption carbon emissions have significant spatial heterogeneity, among which, as the main force to restrain the growth of food consumption carbon emissions, the price factor has a regression coefficient between −0.1 and −0.3, and its influence has weakened from northwest to southeast in 2020. The education–social factor is the main driving force for the growth of food consumption carbon emissions, with a regression coefficient between 0.58 and 0.99, and its influence has increased from east to west. In the future, formulating food consumption optimization policies should be based on the actual situation of food consumption carbon emissions in various regions to promote the realization of low-carbon food consumption.