The impact of demographic dynamics on food consumption and its environmental outcomes:Evidence from China

With increasing population and changing demographics,food consumption has experienced a significant transition in quantity and quality.However,a dearth of knowledge remains regarding its environmental impacts and how it responds to demographic dynamics,particularly in emerging economies like China.Using the two-stage Quadratic Almost Demand System(QUAIDS)model,this study empirically examines the impact of demographic dynamics on food consumption and its environmental outcomes based on the provincial data from 2000 to 2020 in China.Under various scenarios,according to changes in demographics,we extend our analysis to project the long-term trend of food consumption and its environmental impacts,including greenhouse gas(GHG)emissions,water footprint(WF),and land appropriation(LA).The results reveal that an increase in the proportion of senior people significantly decreases the consumption of grain and livestock meat and increases the consumption of poultry,egg,and aquatic products,particularly for urban residents.Moreover,an increase in the proportion of males in the population leads to higher consumption of poultry and aquatic products.Correspondingly,in the current scenario of an increased aging population and sex ratio,it is anticipated that GHG emissions,WF,and LA are likely to decrease by 1.37,2.52,and 3.56%,respectively.More importantly,in the scenario adhering to the standards of nutritional intake according to the Dietary Guidelines for Chinese Residents in 2022,GHG emissions,WF,and LA in urban areas would increase by 12.78,20.94,and 18.32%,respectively.Our findings suggest that changing demographics should be considered when designing policies to mitigate the diet-environment-health trilemma and achieve sustainable food consumption.

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.

The impact of Internet access on household dietary quality:Evidence from rural China

Over the past few decades,the Internet has rapidly diffused across China.The spread of the Internet has had a profound economic and social impact on Chinese rural areas.Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’income.Beyond these,the Internet can affect other dimensions of social welfare.However,research about the impact of Internet access on dietary quality in rural China remains scarce.This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis.Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity.The estimates show that Internet access has significantly increased rural household dietary quality(measured by the Chinese Diet Balance Index).Further research finds that Internet access has increased the consumption of animal products,such as aquatic and dairy products.We also examine the underlying mechanisms.Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure.These results encourage the promotion of Internet access as a valuable tool for nutritional improvements,especially in rural areas.

Driving factors of direct greenhouse gas emissions from China's pig industry from 1976 to 2016

Livestock cultivation is a significant source of greenhouse gas(GHG) emissions, accounting for 14.5% of the total anthropogenic emissions. China is responsible for a considerable share of the global livestock emissions, particularly caused by pork production. We used the Kaya identity and the logarithmic mean Divisia index(LMDI) to decompose the national annual GHG emissions from enteric fermentation and manure management in pig farming in China from 1976 to 2016. We decomposed the sources of the emissions into five driving factors:(1) technological progress(e.g., feed improvement);(2) structural adjustment in the livestock sector;(3) structural adjustment in agriculture;(4) affluence;and(5) population growth. The results showed that the net GHG emissions from the pig sector in China increased 16 million tons(Mt) of carbon dioxide equivalents(CO2 eq) during the study period. The decomposition analysis revealed that structural adjustment in agriculture, growing affluence, and population growth contributed to an increase of the GHG emissions of pork production by 23, 41, and 13 Mt CO2 eq, respectively. The technological progress and structural changes in animal husbandry mitigated emissions by –51 and –11 Mt CO2 eq, respectively. Further technological progress in pig production and optimizing the economic structures are critical for further reducing GHG emissions in China's pig industry. Our results highlight the dominant role of technological changes for emission reductions in the pig farming.

Economic growth and nutrition transition: an empirical analysis comparing demand elasticities for foods in China and Russia

This study provides empirical evidence on the link between economic growth and nutrition transition in two emerging economies, China and Russia. Both countries have experienced rising average incomes, accompanied by an increasing rate of nutrition-related chronic diseases in recent years. Given the regional heterogeneity between these two countries, we analyze the extent to which income growth as a major driver of nutrition transition has a significant effect on the consumption of different food aggregates and how these effects differ between Chinese and Russian consumers. Our results indicate that with increasing household incomes over time the demand for carbohydrates decreases, while the demand for meat and dairy products, as well as fruits increases. This is a development generally known as nutrition transition. Further, we estimate a Quadratic Almost Ideal Demand System（QUAIDS） for nine different food aggregates for China and Russia. Our results indicate that in both countries all food aggregates have positive expenditure elasticities and are thus normal goods. Moreover, our results indicate that in 2008/2009 meat is still a luxury good in China yet a necessity good in Russia. For 2009, the highest own-price elasticities in China are found for non-meat protein sources and dairy products. Within the meat group, beef, poultry and mutton have the highest price elasticities in China. In Russia, the milk and dairy group, together with the vegetable group, is the most price-elastic food group in 2008. In line with the definition of a nutrition transition, our overall results underscore the finding that income growth in China and Russia tends to increase the demand for animal-based products much stronger than, for example, the demand for carbohydrates. Despite being a positive signal for problems of malnutrition in rural China, this trend of increasing meat consumption might further increase the incidence of chronic diseases in urban areas since there is convincing scientific evidence that increasing meat consumption, especially red and processed meat, is associated with an increased risk of chronic diseases.

Modifying Hargreaves-Samani Equation for Estimating Reference Evapotranspiration in Dryland Regions of Amudarya River Basin

Reference evapotranspiration (ETo) is a key factor in determining the amount of water needed for crops, which is crucial to correct irrigation planning. FAO Penman-Monteith (EToPM) is among the most popular method to estimate ETo. Apparently sometimes it is difficult to compute ETo using Penman-Monteith due to challenges on data availability. FAO Penman-Monteith method requires many parameters (solar radiation, air temperature, wind speed and humidity), while Hargreaves-Samani method calculates ETo based on air temperature. Because Central Asia is a data limited region with weather stations unable to provide all required parameters for the PM method, this study aimed to estimate ETo using the Hargreaves and Samani (HS) method in Karshi Steppe, in Kashkadarya province, in southern Uzbekistan, based on data from 2011 to 2017. Reference evapotranspiration calculated by non-modified HS method is underestimated during the summer months. The reason for this underestimation might be higher air temperature and wind speed during these months. Therefore, the HS method in its original form cannot be used in our study area to estimate ETo. Modification of the EToHS, through application of a bias correction factor, had better performance and allowed improving the accuracy of the ETo calculation for this region. The calculated ETo values can inform decision making and management practices regarding water allocation, irrigation scheduling and crop selection in dry land regions of Amudarya river basin and the greater Central Asia area.

Low-income and overweight in China:Evidence from a life-course utility model

Previous literature has demonstrated that low-income people are more likely to settle for poor health choices in developed countries. By using income as a budget constraint and signal for future wellbeing in a life-course utility model, we examine the association amongst income and overweight. The data used for this study are from the China Health and Nutrition Survey(CHNS). Estimations are conducted for overweight initiation, cessation, and participation mirroring a decision to begin and a past decision to not terminate. Our findings propose that body weight and the likelihood of overweight commencement rise with additional income but at a diminishing degree, representing a concave relation;while the likelihood of overweight discontinuance declines with additional income but at an accelerating degree, suggesting a convex relation.We presume that, as opposed to developed countries, low-income people are less inclined to be overweight in China, a country in transition. This could be explained by an income constraint for unhealthy foodstuff. Nevertheless, it will switch when income surpasses the critical threshold of the concave or inverted U-shape curve indicating that low-income people appear to receive not as much utility from future health. Specifically, this adjustment seems to occur earlier for females and inhabitants of urban areas.

Do credit constraints affect households'economic vulnerability?Empirical evidence from rural China

Poverty alleviation is still one of the major challenges in developing countries,especially in transitional economy like China.From the perspective of anti-poverty,this paper examines the impact of formal credit constraints(FCCs)and informal credit constraints(IFCCs)on economic vulnerability(EV)using the data from the China Household Income Project(CHIP)survey for 2013(CHIPs 2013)of rural households.The potential endogeneity problem of credit constraints(CCs)is addressed by applying the control function approach within an ordered probit model.The results show that both FCCs and IFCCs have a robust positive and significant impact on the EV of rural households and that the impact of FCCs is greater than that of IFCCs.To identify the potential mechanisms through which CCs affect EV,the seemingly unrelated regressions are used and the potential intercorrelation among these mechanisms is examined.We find that the impact of CCs on EV is partly mediated by health,trust,per capita financial assets and per capita income,whereby health and per capita income contribute to most of the total indirect effect.Thus,policies focus on supply-side and demand-side to improve credit accessibility could reduce rural households'EV,especially through its positive effect on health and per capita income.

Improving risk reduction potential of weather index insurance by spatially downscaling gridded climate data-a machine learning approach

Open-access gridded climate products have been suggested as a potential source of data for index insurance design and operation in data-limited regions.However,index insurance requires climate data with long historical records,global geographical coverage and fine spatial resolution at the same time,which is nearly impossible to satisfy,especially with open-access data.In this paper,we spatially downscaled gridded climate data(precipitation,temperature,and soil moisture)in coarse spatial resolution with globally available longterm historical records to finer spatial resolution,using satellite-based data and machine learning algorithms.We then investigated the effect of index insurance contracts based on downscaled climate data for hedging spring wheat yield.This study employed countylevel spring wheat yield data between 1982 and 2018 from 56 counties overall in Kazakhstan and Mongolia.The results showed that in the majority of cases(70%),hedging effectiveness of index insurances increases when climate data is spatially downscaled with a machine learning approach.These improvements are statistically significant(p≤0.05).Among other climate data,more improvements in hedging effectiveness were observed when the insurance design was based on downscaled temperature and precipitation data.Overall,this study highlights the reasonability and benefits of downscaling climate data for insurance design and operation.

The Perception of Flood Risks: A Case Study of Babessi in Rural Cameroon

Although risk perception of natural hazards has been identified as an important determinant for sound policy design,there is limited empirical research on it in developing countries.This article narrows the empirical literature gap.It draws from Babessi,a rural town in the Northwest Region of Cameroon.Babessi was hit by a severe flash flood in 2012.The cross-disciplinary lens applied here deciphers the complexity arising from flood hazards,often embedded in contexts characterized by poverty,a state that is constrained in disaster relief,and market-based solutions being absent.Primary data were collected via snowball sampling.Multinomial logistic regression analysis suggests that individuals with leadership functions,for example,heads of households,perceive flood risk higher,probably due to their role as household providers.We found that risk perception is linked to location,which in turn is associated with religious affiliation.Christians perceive floods riskier than Muslims because the former traditionally reside at the foot of hills and the latter uphill;rendering Muslims less exposed and eventually less affected by floods.Finally,public disaster relief appears to have built up trust and subsequently reduced risk perception,even if some victims remained skeptical of state disaster relief.This indicates strong potential benefits of public transfers for flood risk management in developing countries.

Projected drought conditions in Northwest China with CMIP6 models under combined SSPs and RCPs for 2015—2099

Northwest China is one of the most arid regions in the world and has experienced intriguing climate warming and humidification.Nonetheless,future climate conditions in Northwest China still remain uncertain.In this study,we applied an ensemble of the 12 latest model simulations of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess future drought conditions until 2099 in Northwest China,as inferred from the Palmer Drought Severity Index(PDSI).Future drought conditions were projected under three climate change scenarios through the combination of shared socioeconomic pathways(SSPs)and representative concentration pathways(RCPs),namely,SSP126(SSP1+RCP2.6,a green development pathway),SSP245(SSP2+RCP4.5,an intermediate development pathway),and SSP585(SSP5+RCP8.5,a high development pathway).For 2015-2099,drought severity showed no trend under SSP126,in contrast,for the SSP245 and SSP585 scenarios,a rapid increase during 2015-2099 was observed,especially under SSP585.We also found that the drought frequency in Northwest China under SSP585 was generally lower than that under SSP126 and SSP245,although the drought duration under SSP585 tended to be longer.These findings suggest the green development pathway in drought mitigation and adaptation strategies in Northwest China,an arid and agricultural region along the Silk Road.

The Impact of COVID-19 on the Dietary Diversity of Children and Adolescents:Evidence from a Rural/Urban Panel Study

This paper offers the first empirical evidence of the impact of COVID-19 on dietary diversity among children and adolescents in urban and rural families by using panel data collected in 2019(before COVID-19)and 2020(during COVID-19)in northern China.Our study uses panel data from 2,201 primary school students and 1,341 junior high-school students to apply the difference in differences(DID)method to estimate the impact of COVID-19 on dietary diversity among students in urban and rural families.We found that the dietary diversity score(DDS)of rural students decreased by 0.295 points(p<0.01)compared with that of urban students during COVID-19.Specifically,COVID-19 significantly reduced the frequency of rural students'consumption of vegetables by 1.8 percent,protein-rich foods such as soybean products and nuts by 6.0 percent,meats by 4.0 percent,aquatic products by 6.7 percent,and eggs by 5.3 percent,compared with urban students.Further,COVID-19 had a significant negative effect on the dietary diversity of students from low-and middle-income groups,with the DDS of the low-income group decreasing by 0.31 points(p<0.01)and that of the middle-income group by 0.12 points(p<0.1).