Using semiparametric models to study nutrition improvement and dietary change with different indices: The case of China

Tian, Xu; Yu, Xiaohua

doi:10.1016/j.foodpol.2015.04.006

Cited by 87 publications

(92 citation statements)

References 54 publications

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“…These findings are consistent with the current literature (e.g. Gallet, 2011a;2011b;Tian and Yu, 2015;Zhou, Yu and Herzfeld, 2015;Chen et al, 2015) and meat consumption statistics. The FAO statistics show that the global per capita meat consumption reached 42.4 kg per year in 2011, which represents a relatively high level 2 .…”

Section: Estimation Proceduressupporting

confidence: 93%

Meat consumption and democratic governance: A cross-national analysis

Hasiner

2020

China Economic Review

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Section: Estimation Proceduressupporting

confidence: 93%

Meat consumption and democratic governance: A cross-national analysis

Hasiner

2020

China Economic Review

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“…The average proportion of teens and elders in the households are 8.53% and 4.1%, respectively. 2 The sum of preferences for five food categories, including healthy foods (i.e., fruits and vegetables) and unhealthy foods (i.e., fast food, salty snacks, soft drinks, and sugared fruit drinks), on a five-point Likert scale, the higher preference index indicates a healthier food preference; 3 Defined by a multidimensional 12-component urbanization index, including the population density, physical, social, cultural, and economic environment; 4 Labor intensity levels: 1 = very light physical activity, working in a sitting position; 2 = light physical activity, working in a standing position; 3 = moderate physical activity; 4 = heavy physical activity; and 5 = very heavy physical activity; 5 Drinking: 1 = no drinking; 2 = no more than once a month; 3 = once or twice a month; 4 = once or twice a week; 5 = 3-4 times a week; 6 = almost every day. Source: Calculated by the authors.…”

Section: Methodsmentioning

confidence: 99%

“…Overall, the dynamics of the DQD present the transition of Chinese diet from staple cereals and vegetables to high protein and quality foods. standing position; 3 = moderate physical activity; 4 = heavy physical activity; and 5 = very heavy physical activity; 5 Drinking: 1 = no drinking; 2 = no more than once a month; 3 = once or twice a month; 4 = once or twice a week; 5 = 3-4 times a week; 6 = almost every day. Source: Calculated by the authors.…”

Section: Methodsmentioning

confidence: 99%

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Dynamics of Chinese Diet Divergence from Chinese Food Pagoda and Its Association with Adiposity and Influential Factors: 2004–2011

Zhou

Leepromrath

Tian

et al. 2020

IJERPH

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Nutrition transition in China has a strong impact on dietary quality and health of Chinese consumers. This study developed the diet quality divergence Index (DQD), the divergence between real food consumption and the Chinese food pagoda 2016 (CFP), to measure the quality of diet in China. Using four waves of data (2004, 2006, 2009, and 2011) from China Health and Nutrition Survey (CHNS), this study shed light on the transition of diet quality for Chinese residents. Results indicate that the DQD generally decreased and Chinese diet quality improved during 2004–2011. The divergence was mainly caused by over-consumption of legumes and nuts, and under-consumption of milk and milk products. Rising income and urbanization were positively correlated with diet quality for the people with low DQD. However, both of them had negative impacts on diet quality for those with high DQD. Females and rural residents held a lower DQD than their counterparts. The results also revealed that healthy food preference, education, dining at home, household size, proportions of teens (6–17) and elders (over 64) in the families are positively correlated with Chinese diet quality. However, labor intensity, frequency of drinking alcohol, and smoking have negative impacts on diet quality. Moreover, higher DQD was found to be associated with increasing risks of overweight/obesity. Therefore, we suggest national healthy policies should pay more attention to nutrition education. It is also necessary to focus on populations with poor diet quality and to adopt measures to control drinking alcohol and smoking.

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“…Like any other welfare indicator, these indices though theoretically ele-245 gant, have their own disadvantages in capturing food security (64). Here, we focus on the food expenditure patterns and dietary diversity as the measure of food security.…”

Section: Dietary Diversity Indicatormentioning

confidence: 99%

Does Non-farm Income Affect Food Security? Evidence from India

Rahman

Mishra

2019

The Journal of Development Studies

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Livelihood diversification and greater non-farm income have been considered as useful mechanisms to propel growth, lower rural poverty and augment farm income in the developing countries. Little, however, is known about its im-plications for nutritional outcomes such as dietary diversity. This article con-tributes to the literature by investigating whether greater non-farm income helps in improving food consumption patterns and dietary diversity. Using a nationally representative panel data of rural India and an instrumental variable (IV) approach, we investigate this association and find that non-farm income increases expenditure on food products especially non-cereal prod-ucts, leading to greater household dietary diversity. This has crucial policy implications for nutrition transition and livelihood diversification, further contributing to the existing knowledge on agriculture-nutrition pathways. Acknowledegment:JEL Codes: O12, J48 #481 30 kets for food consumption which exposes households to the vagaries of price fluctuations and could potentially undermine their food security. Similarly, non-farm activities could shift resources such as land and labor, previously used to produce food, towards other expenditures. At the same time, higher income increases household access to greater quantity and better variety of 35 food.Against the above background, this paper is an empirical investigation into the relationship between household dietary diversity and non-farm income. We focus on India as the country of analysis where non-farm incomewhere the discourse on hunger and food security has been synonymous with poverty. There are subtle differences in what these terms imply for welfare. Poverty levels are a money metric which captures purchasing power. Dietary diversity, on the other hand, tells us about actual consumption and the ability of a household to acquire food, which is essential for human development. 50Also, while the link between non-farm income and poverty is straightforward, the nature of relationship between the non-farm income and dietary diversity is theoretically ambiguous.Pathways from agriculture to nutrition (36, 56,27,37), often tend over-55 look the importance of non-farm activities for nutrition, which is an issue of concern. Non-farm activities are a major source of income in rural areas. Income from non-farm sources account for about 35% of total rural income in Africa and around 50% in Asia and Latin America (29). In India, 88% of the rural households which are primarly engaged in agriculture and allied 60 activities, also undertake additional economic activity in the non-farm sector (17). In this paper, we provide evidence on the role played by income from the non-farm sector for food consumption and dietary diversity. Using a nationally representative panel data for the years 2004-05 and 2011-12 for rural India, we find that increase in non-farm income significantly improves 65 household diets, which is an intermediate pathway to improved nutritional outcomes. Given migration and remittan...

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Using semiparametric models to study nutrition improvement and dietary change with different indices: The case of China

Cited by 87 publications

References 54 publications

Meat consumption and democratic governance: A cross-national analysis

Meat consumption and democratic governance: A cross-national analysis

Dynamics of Chinese Diet Divergence from Chinese Food Pagoda and Its Association with Adiposity and Influential Factors: 2004–2011

Does Non-farm Income Affect Food Security? Evidence from India

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