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      Agricultural trade policies and child nutrition in low- and middle-income countries: a cross-national analysis

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          Abstract

          Background

          There has been growing interest in understanding the role of agricultural trade policies in diet and nutrition. This cross-country study examines associations between government policies on agricultural trade prices and child nutrition outcomes, particularly undernutrition.

          Methods

          This study links panel data on government distortions to agricultural incentives to data from 212,258 children aged 6 to 35 months participating in Demographic and Health Surveys from 22 countries between 1991 and 2010. Country fixed-effects regression models were used to examine the association between within-country changes in nominal rates of assistance to tradable agriculture (government price distortions as a percentage of original prices) and child nutritional outcomes (height-for-age, weight-for-age, and weight-for-height Z-scores) while controlling for a range of time-varying country covariates.

          Results

          Five-year average nominal rates of assistance to tradable agriculture ranged from − 72.0 to 45.5% with a mean of − 5.0% and standard deviation of 18.9 percentage points. A 10-percentage point increase in five-year average rates of assistance to tradable agriculture was associated with improved height-for-age (0.02, 95% CI,0.00–0.05) and weight-for-age (0.05, 95% CI: 0.02–0.09) Z-scores. Improvements in nutritional status were greatest among children who had at least one parent earning wages in agriculture, and effects decreased as a country’s proportion of tradable agriculture increased, particularly for weight-for-age Z-scores.

          Conclusions

          Government assistance to tradable agriculture, such as through reduced taxation, was associated with small but significant improvements in child nutritional status, especially for children with a parent earning wages in agriculture when the share of tradable agriculture was not high.

          Electronic supplementary material

          The online version of this article (10.1186/s12992-019-0463-0) contains supplementary material, which is available to authorized users.

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          Most cited references66

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          Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

          Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation.
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            Does globalization affect growth? Evidence from a new index of globalization

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              Nutrition-sensitive interventions and programmes: how can they help to accelerate progress in improving maternal and child nutrition?

              Acceleration of progress in nutrition will require effective, large-scale nutrition-sensitive programmes that address key underlying determinants of nutrition and enhance the coverage and effectiveness of nutrition-specific interventions. We reviewed evidence of nutritional effects of programmes in four sectors--agriculture, social safety nets, early child development, and schooling. The need for investments to boost agricultural production, keep prices low, and increase incomes is undisputable; targeted agricultural programmes can complement these investments by supporting livelihoods, enhancing access to diverse diets in poor populations, and fostering women's empowerment. However, evidence of the nutritional effect of agricultural programmes is inconclusive--except for vitamin A from biofortification of orange sweet potatoes--largely because of poor quality evaluations. Social safety nets currently provide cash or food transfers to a billion poor people and victims of shocks (eg, natural disasters). Individual studies show some effects on younger children exposed for longer durations, but weaknesses in nutrition goals and actions, and poor service quality probably explain the scarcity of overall nutritional benefits. Combined early child development and nutrition interventions show promising additive or synergistic effects on child development--and in some cases nutrition--and could lead to substantial gains in cost, efficiency, and effectiveness, but these programmes have yet to be tested at scale. Parental schooling is strongly associated with child nutrition, and the effectiveness of emerging school nutrition education programmes needs to be tested. Many of the programmes reviewed were not originally designed to improve nutrition yet have great potential to do so. Ways to enhance programme nutrition-sensitivity include: improve targeting; use conditions to stimulate participation; strengthen nutrition goals and actions; and optimise women's nutrition, time, physical and mental health, and empowerment. Nutrition-sensitive programmes can help scale up nutrition-specific interventions and create a stimulating environment in which young children can grow and develop to their full potential. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                k.adjaye-gbewonyo@ucl.ac.uk
                svollmer@uni-goettingen.de
                mauricio.avendano_pabon@kcl.ac.uk
                kenneth.harttgen@nadel.ethz.ch
                Journal
                Global Health
                Global Health
                Globalization and Health
                BioMed Central (London )
                1744-8603
                15 March 2019
                15 March 2019
                2019
                : 15
                : 21
                Affiliations
                [1 ]ISNI 0000 0004 1936 7531, GRID grid.429997.8, Innovative Methods & Metrics for Agriculture and Nutrition Actions, , Tufts University Friedman School of Nutrition Science and Policy, ; 150 Harrison Avenue, Boston, MA 02111 USA
                [2 ]ISNI 0000000121901201, GRID grid.83440.3b, Institute of Advanced Studies, University College London, ; Gower Street, London, WC1E 6BT UK
                [3 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard T. H. Chan School of Public Health, ; 677 Huntington Avenue, Boston, MA 02115 USA
                [4 ]ISNI 0000 0001 2364 4210, GRID grid.7450.6, University of Göttingen; Center for Modern Indian Studies, ; Waldweg 26, Altbau 1.118, 37073 Göttingen, Germany
                [5 ]ISNI 0000 0001 2322 6764, GRID grid.13097.3c, Department of Global Health and Social Medicine, , King’s College London, Strand Campus, ; Strand, London, WC2R2LS UK
                [6 ]ISNI 0000 0001 2156 2780, GRID grid.5801.c, ETH Zürich, NADEL Center for Development and Cooperation, ; Clausiusstrasse 37, 8092 Zurich, Switzerland
                Author information
                http://orcid.org/0000-0002-8919-6518
                Article
                463
                10.1186/s12992-019-0463-0
                6420724
                30876446
                7ef137e1-c1c4-43ed-ac92-97bada19f7d7
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 October 2018
                : 28 February 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000278, Department for International Development;
                Award ID: Innovative Methods and Metrics for Agriculture and Nutrition Actions (IMMANA)
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Health & Social care
                nutrition status,trade,agriculture,policy,food prices,nominal rate of assistance,liberalization

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