Malnutrition remains a leading cause of death in children in low- and middle-income countries; this will be aggravated by climate change. Annually, 6.9 million deaths of children under 5 were attributable directly or indirectly to malnutrition. Although these figures have recently decreased, evidence shows that a world with a medium climate (local warming up to 3–4 °C) will create an additional 25.2 million malnourished children. This proof of concept study explores the relationships between childhood malnutrition (more specifically stunting), regional agricultural yields, and climate variable  through the use of remote sensing (RS) satellite imaging along with algorithms to predict the effect of climate variability on agricultural yields and on malnutrition of children under 5. The success of this proof of purpose study, NUTRItion and CLIMate (NUTRICLIM), should encourage researchers to apply both concept and tools to study of the link between weather variability, crop yield, and malnutrition on a larger scale. It would also allow for linking such micro-level data to climate models and address the challenge of projecting the additional impact of childhood malnutrition from climate change to various policy relevant time horizons

A Anyamba

A Woodward

DB Lobell

GC Nelson

O Sankoh

R Phalkey

S Whitmee

SJ Lloyd

UNICEF

Public Health Reviews

Springer - Publisher Connector

COMMENTARY Open Access
NUTRItion and CLIMate (NUTRICLIM):
investigating the relationship between
climate variables and childhood
malnutrition through agriculture, an
exploratory study in Burkina Faso
Raissa Sorgho1*, Jonas Franke2, Seraphin Simboro3, Revati Phalkey4 and Rainer Saeurborn1
* Correspondence:
raissa.sorgho@uni-heidelberg.de
1Institute of Public Health,
Universitats Klinikum, Heidelberg,
Germany
Full list of author information is
available at the end of the article
Abstract
Malnutrition remains a leading cause of death in children in low- and middle-income
countries; this will be aggravated by climate change. Annually, 6.9 million deaths of
children under 5 were attributable directly or indirectly to malnutrition. Although
these figures have recently decreased, evidence shows that a world with a medium
climate (local warming up to 3–4 °C) will create an additional 25.2 million malnourished
children. This proof of concept study explores the relationships between childhood
malnutrition (more specifically stunting), regional agricultural yields, and climate variables
through the use of remote sensing (RS) satellite imaging along with algorithms to
predict the effect of climate variability on agricultural yields and on malnutrition of
children under 5. The success of this proof of purpose study, NUTRItion and CLIMate
(NUTRICLIM), should encourage researchers to apply both concept and tools to study of
the link between weather variability, crop yield, and malnutrition on a larger scale. It
would also allow for linking such micro-level data to climate models and address the
challenge of projecting the additional impact of childhood malnutrition from climate
change to various policy relevant time horizons.
Keywords: Malnutrition, Low- and middle-income countries, Climate change, Stunting,
Remote sensing, Weather
Main text
Malnutrition is globally recognized as having one of the largest adverse effects on the
growth of nations, because it not only poses a challenge to the health but also to the
productivity of populations [1]. Unfortunately, climate change will have an additional
negative impact on childhood nutrition through a large number of factors [1, 2]. While
malnutrition in children has globally decreased over the past few decades, climate
change has the potential to reverse the recent gains in the global reduction of malnu-
trition [3]. A median climate (local warming up to 3–4 °C) is projected to create an
additional 25.2 million malnourished children [2, 4]. The 2015 Rockefeller Foundation
and Lancet Commission on Planetary Health publication titled: Safeguarding human
health in the Anthropocene epoch, states along with the IPCC that “… median crop
© 2016 The Author(s). Open Access This 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.
Sorgho et al. Public Health Reviews  (2016) 37:16 
DOI 10.1186/s40985-016-0031-6
yields would decrease by 0–2 % per decade for the remainder of the century, as a result
of climate change alone, with or without adaptation, whereas demands for crops are
projected to increase by 14 % per decade up to 2050” [5, 6]. The publication continues
by detailing that the projected decreases in crop yields result in increasing numbers of
stunted children, especially in Asia and Africa. More than 90 % of the world’s stunted
children live in Africa and Asia [7]. Currently, 36 % of all children under 5 years in
sub-Saharan Africa suffer from stunting—a severe form of malnutrition [1, 2]. Projec-
tions forecast that stunting will increase by approximately 23 % in the region; this is
why we selected a sub-Saharan African country as the site of this proof of concept
exploratory study [2].
The relationship between changing climate, agriculture, and malnutrition is influenced
by a multitude of factors. The complexity and interdisciplinary nature of these three issues
converge into an elaborate web, which is represented in Fig. 1. The convolution of these
links is precisely the reason these connections have been understudied.
Figure 1 illustrates an aspect of the complexity of the relationships investigated. Each
of the three colored boxes represents one of three pillars: climate, agriculture, and mal-
nutrition. Each arrow represents a relationship between two variables or factors. The
three pillars converge on the subject of food crops and food yields.
This exploratory study, NUTRItion and CLIMate (NUTRICLIM), in Burkina Faso
aims to investigate the relationship between weather variability, crop yields, household
socioeconomic variables, and malnutrition. The study village of Bourasso, which has
12,548 inhabitants, in the rural Kossi Province is located 25 km from the small town of
Nouna. The study involves 156 individuals, subdivided into 20 households with 29 chil-
dren under the age of 5. This first sample was randomly selected from the INDEPTH
Human Demographic Surveillance System (HDSS) database of the Centre de Recherché
en Santé de Nouna (CRSN) and the second sample from local Bourasso Health Post’s
database of malnourished children [8]. The 20 households can thus be subdivided into
sample 1: 10 households that were randomly selected and coincidentally had no mal-
nourished children under the age of 5, and sample 2: 10 households that were purpose-
fully selected for having children under the age of 5 who were undergoing treatment
Fig. 1 The complexity and interdisciplinary nature of these three issues converge into an elaborate web.
Adapted from Phalkey et al. [1]
Sorgho et al. Public Health Reviews  (2016) 37:16 Page 2 of 5
for malnutrition. The additional selection criteria were that all 20 households be sub-
sistence farmers, living in the village of Bourasso, with at least one child under the age
of 5.
Data for the first pillar, climate, were acquired through the two nearest local weather
stations of the HDSS. The weather stations provide information on median daily
temperature, daily rainfall, as well as seasonal distribution and variability of rainfall.
Data for the second pillar, agriculture, was collected through two methods. The first
method was harvest yields reported by farmers and converted from local measures into ki-
lograms. The second was innovative in that it estimated plot level yields by household and
crop using special algorithms from remotely sensed data of the village and its surroundings.
This required the delineation of each field of all households with the farmers using a GPS
to establish the polygons. These were overlaid with scenes from the RapidEye satellite, cov-
ering the agricultural fields of the 20 selected households. We carried out ground validation
through verification and comparison of the results from remote sensing (RS) satellite im-
aging; field agents physically verified that the satellite readings matched ground data. Post-
harvest, the figures of the actual agricultural yields are used as input data to better calibrate
the algorithms for modeling crop yields on a micro-level (household level).
The third pillar covered malnutrition and health. This data was collected using a socio-
economic and morbidity questionnaire for the selected households. The survey assessed
(i) household assets, revenues, and expenditure, (ii) a 24-hour nutritional recall journal of
all children under 5, and (iii) all recent child illnesses within the household, both chronic
and acute (episodes of diarrhea, malaria, etc.). Furthermore, we used standard anthropom-
etry (weight, height, and mid-upper-arm circumference) to assess the nutritional status of
children under the age of 5.
As data analysis was still in progress at the time of the presentation at the COP21, no
definitive results could be stated. But preliminary findings indicate the possibility of dis-
parities in the agricultural yield of households with and without malnourished children
and between years with average and low rainfall. The differences were noticed not only
in the types of crops sown but also in the number of plots owned by the households:
households with healthy children had, on average, a greater number of fields. When the
subsistence farmers were questioned on their yields, only one third classified their har-
vest as good, allowing the household to be fed in a satisfactory manner for the entire
year until the next harvest. The remaining two thirds of all households attributed insuf-
ficient yields to bad rains, changing rain patterns, or unpredictable rain patterns. This
potentially highlights the significance of changing weather patterns and their conse-
quences in terms of droughts [4, 9].
Conclusions
We laid out a number of field methods in the fields of meteorology, agriculture, nutrition,
and health that allow for the study of the web of causation of childhood malnutrition with
a particular focus on the role of weather and climate in the future.
We propose that large-scale studies using these methods, amongst others, be considered.
These could then be linked to downscaled climate models in cooperation with climate sci-
entists in order to establish data-based projections of the future impact of climate change
on malnutrition rather than relying on a set of assumptions and mono-disciplinary frag-
mented studies.
Sorgho et al. Public Health Reviews  (2016) 37:16 Page 3 of 5
Abbreviations
CRSNm: Centre de Recherche en Sante de Nouna; HDSS: Human Demographic Surveillance System
Acknowledgements
We would like to thank the people of Bourasso for the time they accorded to the collection of this pilot study data.
Funding
Pilot study was funded by the institute of Public Health at the University of Heidelberg.
Availability of data and materials
The datasets generated during the current study are not publicly available due to the fact that they are still being
analyzed and are to be utilized for further publication before public release. But this data can be made available from
the corresponding author on reasonable request.
Authors’ contributions
RSorgho is the field research coordinator, author and COP21 presenter. JF is the Remote Sensing and Rapid Eye
Imaging expert. SS is the cartography and GIS expert. RP is the study co-supervisor. RSauerborn is the editor, reviwer
and study supervisor. All authors read and approved the final manuscript.
Authors’ information
Raissa Sorgho is a researcher on two climate and health studies at the Institute of Public Health in Heidelberg, Germany.
Her background is in biology, and she is currently a candidate for a Master of Science in International Health while
simultaneously working on her doctorate. Her research interests include agriculture, nutrition, health financing, and
climate change.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
The study NUTRICLIM was approved by the Heidelberg University ethical committee “Ethik Kommission Medizinische
Fakultät Heidelberg”. Furthermore, in observation of ethically appropriate scientific research, NUTRICLIM followed the
procedures of the ongoing Nouna Socioeconomic and Health Panel Survey (SOHPS). This is the process, which has
been utilized by the CRSN research center since 2000. For the anthropometric component of the study, NUTRICLIM
followed standard WHO procedures. The study team ensured that all malnutrition cases discovered during the course
of the study would be presented to the CSPS and, if needed, be referred to Centre de Rehabilitation Nutritional (CREN) in
the district capital Nouna. The project contributed 50 % of all rehabilitation and care cost for such children. Lastly, the
project had no environment impact.
All participants consented verbally and in written form to partake in the study. Participation in the research study
was entirely voluntary; it had and will continue to have no effects or repercussions on the work or social life of
participants. Participants were free to change their minds at any point, ceasing participation at will. There were no
costs associated with participation nor were there financial incentives. The information collected in the framework
of this research project was confidential. This information was stored in a file number anonymously. All consequent
files were replaced with a unique identification number. No information was shared with anybody outside the
research team. The knowledge gained from this research will be published so that other interested persons may
learn from the research.
Author details
1Institute of Public Health, Universitats Klinikum, Heidelberg, Germany. 2Remote Sensing Solution GmBh (RSS),
Environmental Consulting, Baierbrunn, Germany. 3Centre de Recherche en Santé de Nouna (CRSN), Research Center,
INDEPTH Network, HDSS, Nouna, Burkina Faso. 4Division of Epidemiology and Public Health, University of Nottingham,
Nottingham, UK.
Received: 15 September 2016 Accepted: 22 September 2016
References
1. Phalkey R, Aranda-Jan C, Marx S, Höfle B, Sauerborn R. A systematic review of current efforts to quantify the
impacts of climate change on undernutrition. PNAS. 2015;112(33):E4522–9. doi:10.1073/pnas.1409769112.
2. Lloyd SJ, et al. Climate change, crop yields, and undernutrition: development of a model to quantify the impact
of climate scenarios on child undernutrition. Environ Health Perspect. 2011;119(12):1817–23.
3. Woodward A, Smith K, Campbell-Lendrum D, Chadee D, Honda Y, Liu Q, Olwoch J, Revich B, Sauerborn R, Chafe Z,
Haines A. Climate change and health—the latest report from the IPCC. Lancet. 2014;283:1185–9.
4. Whitmee S, Haines A, Beyrer C, Boltz F, Capon AG, de Souza Dias BF, et al. Safeguarding human health in the
Anthropocene epoch: report of The Rockefeller Foundation-Lancet Commission on planetary health (Haines A
Chair of Commission). Lancet. 2015;386:1973–2028.
5. Lobell DB, et al. Prioritizing climate change adaptation needs for food security in 2030. Science. 2008;319(5863):607–10.
Sorgho et al. Public Health Reviews  (2016) 37:16 Page 4 of 5
6. Nelson GC, Rosegrant MW, Koo J, Robertson R, Sulser T, Zhu T, et al. Climate change: impact on agriculture
and costs of adaptation. food policy report. Washington, DC: International Food Policy Research Institute;
2009. p. 1–30.
7. UNICEF. UNICEF-WHO-World Bank Joint Child Malnutrition Estimates. 2012. Available at www.who.int/nutgrowthdb/
jme_unicef_who_wb.pdf. Accessed January 10, 2015.
8. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. Intl J Epidem.
2012;41:579–88.
9. Anyamba A, Chretien JP, Small J, Tucker CJ, Linthicum KJ. Developing global climate anomalies suggest potential
disease risks for 2006-2007. Int J Health Geogr. 2006;28:5. 60.
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NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso

Raissa Sorgho

Jonas Franke

Seraphin Simboro

Revati Phalkey

Rainer Saeurborn

Sorgho, Raissa

Franke, Jonas

Simboro, Seraphin

Phalkey, Revati

Saeurborn, Rainer

Name not available

Repository@Nottingham

COMMENTARY Open AccessNUTRItion and CLIMate (NUTRICLIM):investigating the relationship betweenclimate variables and childhoodmalnutrition through agriculture, anexploratory study in Burkina FasoRaissa Sorgho1*, Jonas Franke2, Seraphin Simboro3, Revati Phalkey4 and Rainer Saeurborn1* Correspondence:raissa.sorgho@uni-heidelberg.de1Institute of Public Health,Universitats Klinikum, Heidelberg,GermanyFull list of author information isavailable at the end of the articleAbstractMalnutrition remains a leading cause of death in children in low- and middle-incomecountries; this will be aggravated by climate change. Annually, 6.9 million deaths ofchildren under 5 were attributable directly or indirectly to malnutrition. Althoughthese figures have recently decreased, evidence shows that a world with a mediumclimate (local warming up to 3–4 °C) will create an additional 25.2 million malnourishedchildren. This proof of concept study explores the relationships between childhoodmalnutrition (more specifically stunting), regional agricultural yields, and climate variablesthrough the use of remote sensing (RS) satellite imaging along with algorithms topredict the effect of climate variability on agricultural yields and on malnutrition ofchildren under 5. The success of this proof of purpose study, NUTRItion and CLIMate(NUTRICLIM), should encourage researchers to apply both concept and tools to study ofthe link between weather variability, crop yield, and malnutrition on a larger scale. Itwould also allow for linking such micro-level data to climate models and address thechallenge of projecting the additional impact of childhood malnutrition from climatechange to various policy relevant time horizons.Keywords: Malnutrition, Low- and middle-income countries, Climate change, Stunting,Remote sensing, WeatherMain textMalnutrition is globally recognized as having one of the largest adverse effects on thegrowth of nations, because it not only poses a challenge to the health but also to theproductivity of populations [1]. Unfortunately, climate change will have an additionalnegative impact on childhood nutrition through a large number of factors [1, 2]. Whilemalnutrition in children has globally decreased over the past few decades, climatechange has the potential to reverse the recent gains in the global reduction of malnu-trition [3]. A median climate (local warming up to 3–4 °C) is projected to create anadditional 25.2 million malnourished children [2, 4]. The 2015 Rockefeller Foundationand Lancet Commission on Planetary Health publication titled: Safeguarding humanhealth in the Anthropocene epoch, states along with the IPCC that “… median crop© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 InternationalLicense (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, andindicate 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.Sorgho et al. Public Health Reviews  (2016) 37:16 DOI 10.1186/s40985-016-0031-6yields would decrease by 0–2 % per decade for the remainder of the century, as a resultof climate change alone, with or without adaptation, whereas demands for crops areprojected to increase by 14 % per decade up to 2050” [5, 6]. The publication continuesby detailing that the projected decreases in crop yields result in increasing numbers ofstunted children, especially in Asia and Africa. More than 90 % of the world’s stuntedchildren live in Africa and Asia [7]. Currently, 36 % of all children under 5 years insub-Saharan Africa suffer from stunting—a severe form of malnutrition [1, 2]. Projec-tions forecast that stunting will increase by approximately 23 % in the region; this iswhy we selected a sub-Saharan African country as the site of this proof of conceptexploratory study [2].The relationship between changing climate, agriculture, and malnutrition is influencedby a multitude of factors. The complexity and interdisciplinary nature of these three issuesconverge into an elaborate web, which is represented in Fig. 1. The convolution of theselinks is precisely the reason these connections have been understudied.Figure 1 illustrates an aspect of the complexity of the relationships investigated. Eachof the three colored boxes represents one of three pillars: climate, agriculture, and mal-nutrition. Each arrow represents a relationship between two variables or factors. Thethree pillars converge on the subject of food crops and food yields.This exploratory study, NUTRItion and CLIMate (NUTRICLIM), in Burkina Fasoaims to investigate the relationship between weather variability, crop yields, householdsocioeconomic variables, and malnutrition. The study village of Bourasso, which has12,548 inhabitants, in the rural Kossi Province is located 25 km from the small town ofNouna. The study involves 156 individuals, subdivided into 20 households with 29 chil-dren under the age of 5. This first sample was randomly selected from the INDEPTHHuman Demographic Surveillance System (HDSS) database of the Centre de Recherchéen Santé de Nouna (CRSN) and the second sample from local Bourasso Health Post’sdatabase of malnourished children [8]. The 20 households can thus be subdivided intosample 1: 10 households that were randomly selected and coincidentally had no mal-nourished children under the age of 5, and sample 2: 10 households that were purpose-fully selected for having children under the age of 5 who were undergoing treatmentFig. 1 The complexity and interdisciplinary nature of these three issues converge into an elaborate web.Adapted from Phalkey et al. [1]Sorgho et al. Public Health Reviews  (2016) 37:16 Page 2 of 5for malnutrition. The additional selection criteria were that all 20 households be sub-sistence farmers, living in the village of Bourasso, with at least one child under the ageof 5.Data for the first pillar, climate, were acquired through the two nearest local weatherstations of the HDSS. The weather stations provide information on median dailytemperature, daily rainfall, as well as seasonal distribution and variability of rainfall.Data for the second pillar, agriculture, was collected through two methods. The firstmethod was harvest yields reported by farmers and converted from local measures into ki-lograms. The second was innovative in that it estimated plot level yields by household andcrop using special algorithms from remotely sensed data of the village and its surroundings.This required the delineation of each field of all households with the farmers using a GPSto establish the polygons. These were overlaid with scenes from the RapidEye satellite, cov-ering the agricultural fields of the 20 selected households. We carried out ground validationthrough verification and comparison of the results from remote sensing (RS) satellite im-aging; field agents physically verified that the satellite readings matched ground data. Post-harvest, the figures of the actual agricultural yields are used as input data to better calibratethe algorithms for modeling crop yields on a micro-level (household level).The third pillar covered malnutrition and health. This data was collected using a socio-economic and morbidity questionnaire for the selected households. The survey assessed(i) household assets, revenues, and expenditure, (ii) a 24-hour nutritional recall journal ofall children under 5, and (iii) all recent child illnesses within the household, both chronicand acute (episodes of diarrhea, malaria, etc.). Furthermore, we used standard anthropom-etry (weight, height, and mid-upper-arm circumference) to assess the nutritional status ofchildren under the age of 5.As data analysis was still in progress at the time of the presentation at the COP21, nodefinitive results could be stated. But preliminary findings indicate the possibility of dis-parities in the agricultural yield of households with and without malnourished childrenand between years with average and low rainfall. The differences were noticed not onlyin the types of crops sown but also in the number of plots owned by the households:households with healthy children had, on average, a greater number of fields. When thesubsistence farmers were questioned on their yields, only one third classified their har-vest as good, allowing the household to be fed in a satisfactory manner for the entireyear until the next harvest. The remaining two thirds of all households attributed insuf-ficient yields to bad rains, changing rain patterns, or unpredictable rain patterns. Thispotentially highlights the significance of changing weather patterns and their conse-quences in terms of droughts [4, 9].ConclusionsWe laid out a number of field methods in the fields of meteorology, agriculture, nutrition,and health that allow for the study of the web of causation of childhood malnutrition witha particular focus on the role of weather and climate in the future.We propose that large-scale studies using these methods, amongst others, be considered.These could then be linked to downscaled climate models in cooperation with climate sci-entists in order to establish data-based projections of the future impact of climate changeon malnutrition rather than relying on a set of assumptions and mono-disciplinary frag-mented studies.Sorgho et al. Public Health Reviews  (2016) 37:16 Page 3 of 5AbbreviationsCRSNm: Centre de Recherche en Sante de Nouna; HDSS: Human Demographic Surveillance SystemAcknowledgementsWe would like to thank the people of Bourasso for the time they accorded to the collection of this pilot study data.FundingPilot study was funded by the institute of Public Health at the University of Heidelberg.Availability of data and materialsThe datasets generated during the current study are not publicly available due to the fact that they are still beinganalyzed and are to be utilized for further publication before public release. But this data can be made available fromthe corresponding author on reasonable request.Authors’ contributionsRSorgho is the field research coordinator, author and COP21 presenter. JF is the Remote Sensing and Rapid EyeImaging expert. SS is the cartography and GIS expert. RP is the study co-supervisor. RSauerborn is the editor, reviwerand study supervisor. All authors read and approved the final manuscript.Authors’ informationRaissa Sorgho is a researcher on two climate and health studies at the Institute of Public Health in Heidelberg, Germany.Her background is in biology, and she is currently a candidate for a Master of Science in International Health whilesimultaneously working on her doctorate. Her research interests include agriculture, nutrition, health financing, andclimate change.Competing interestsThe authors declare that they have no competing interests.Consent for publicationNot applicable.Ethics approval and consent to participateThe study NUTRICLIM was approved by the Heidelberg University ethical committee “Ethik Kommission MedizinischeFakultät Heidelberg”. Furthermore, in observation of ethically appropriate scientific research, NUTRICLIM followed theprocedures of the ongoing Nouna Socioeconomic and Health Panel Survey (SOHPS). This is the process, which hasbeen utilized by the CRSN research center since 2000. For the anthropometric component of the study, NUTRICLIMfollowed standard WHO procedures. The study team ensured that all malnutrition cases discovered during the courseof the study would be presented to the CSPS and, if needed, be referred to Centre de Rehabilitation Nutritional (CREN) inthe district capital Nouna. The project contributed 50 % of all rehabilitation and care cost for such children. Lastly, theproject had no environment impact.All participants consented verbally and in written form to partake in the study. Participation in the research studywas entirely voluntary; it had and will continue to have no effects or repercussions on the work or social life ofparticipants. Participants were free to change their minds at any point, ceasing participation at will. There were nocosts associated with participation nor were there financial incentives. The information collected in the frameworkof this research project was confidential. This information was stored in a file number anonymously. All consequentfiles were replaced with a unique identification number. No information was shared with anybody outside theresearch team. The knowledge gained from this research will be published so that other interested persons maylearn from the research.Author details1Institute of Public Health, Universitats Klinikum, Heidelberg, Germany. 2Remote Sensing Solution GmBh (RSS),Environmental Consulting, Baierbrunn, Germany. 3Centre de Recherche en Santé de Nouna (CRSN), Research Center,INDEPTH Network, HDSS, Nouna, Burkina Faso. 4Division of Epidemiology and Public Health, University of Nottingham,Nottingham, UK.Received: 15 September 2016 Accepted: 22 September 2016References1. Phalkey R, Aranda-Jan C, Marx S, Höfle B, Sauerborn R. A systematic review of current efforts to quantify theimpacts of climate change on undernutrition. PNAS. 2015;112(33):E4522–9. doi:10.1073/pnas.1409769112.2. Lloyd SJ, et al. Climate change, crop yields, and undernutrition: development of a model to quantify the impactof climate scenarios on child undernutrition. Environ Health Perspect. 2011;119(12):1817–23.3. Woodward A, Smith K, Campbell-Lendrum D, Chadee D, Honda Y, Liu Q, Olwoch J, Revich B, Sauerborn R, Chafe Z,Haines A. Climate change and health—the latest report from the IPCC. Lancet. 2014;283:1185–9.4. Whitmee S, Haines A, Beyrer C, Boltz F, Capon AG, de Souza Dias BF, et al. Safeguarding human health in theAnthropocene epoch: report of The Rockefeller Foundation-Lancet Commission on planetary health (Haines AChair of Commission). Lancet. 2015;386:1973–2028.5. Lobell DB, et al. Prioritizing climate change adaptation needs for food security in 2030. Science. 2008;319(5863):607–10.Sorgho et al. Public Health Reviews  (2016) 37:16 Page 4 of 56. Nelson GC, Rosegrant MW, Koo J, Robertson R, Sulser T, Zhu T, et al. Climate change: impact on agricultureand costs of adaptation. food policy report. Washington, DC: International Food Policy Research Institute;2009. p. 1–30.7. UNICEF. UNICEF-WHO-World Bank Joint Child Malnutrition Estimates. 2012. Available at www.who.int/nutgrowthdb/jme_unicef_who_wb.pdf. Accessed January 10, 2015.8. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. Intl J Epidem.2012;41:579–88.9. Anyamba A, Chretien JP, Small J, Tucker CJ, Linthicum KJ. Developing global climate anomalies suggest potentialdisease risks for 2006-2007. Int J Health Geogr. 2006;28:5. 60.•  We accept pre-submission inquiries •  Our selector tool helps you to find the most relevant journal•  We provide round the clock customer support •  Convenient online submission•  Thorough peer review•  Inclusion in PubMed and all major indexing services •  Maximum visibility for your researchSubmit your manuscript atwww.biomedcentral.com/submitSubmit your next manuscript to BioMed Central and we will help you at every step:Sorgho et al. Public Health Reviews  (2016) 37:16 Page 5 of 5

Nottingham eTheses

Malnutrition remains a leading cause of death in children in low- and middle-income countries; this will be aggravated by climate change. Annually, 6.9 million deaths of children under 5 were attributable directly or indirectly to malnutrition. Although these figures have recently decreased, evidence shows that a world with a medium climate (local warming up to 3–4°C) will create an additional 25.2 million malnourished children. This proof of concept study explores the relationships between childhood malnutrition (more specifically stunting), regional agricultural yields, and climate variables through the use of remote sensing (RS) satellite imaging along with algorithms to predict the effect of climate variability on agricultural yields and on malnutrition of children under 5. The success of this proof of purpose study, NUTRItion and CLIMate (NUTRICLIM), should encourage researchers to apply both concept and tools to study of the link between weather variability, crop yield, and malnutrition on a larger scale. It would also allow for linking such micro-level data to climate models and address the challenge of projecting the additional impact of childhood malnutrition from climate change to various policy relevant time horizons

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Sorgho, Raissa and Franke, Jonas and Simboro, Seraphin and Phalkey, Revati and Saeurborn, Rainer (2016) NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso. Public Health Reviews, 37 (16). pp. 1-5. ISSN 2107-6952 Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/38414/1/Sorgho%202016%20Public%20Health%20Reviews.pdfCopyright and reuse: The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions.This article is made available under the Creative Commons Attribution licence and may be reused according to the conditions of the licence.  For more details see: http://creativecommons.org/licenses/by/2.5/A note on versions: The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.ukCOMMENTARY Open AccessNUTRItion and CLIMate (NUTRICLIM):investigating the relationship betweenclimate variables and childhoodmalnutrition through agriculture, anexploratory study in Burkina FasoRaissa Sorgho1*, Jonas Franke2, Seraphin Simboro3, Revati Phalkey4 and Rainer Saeurborn1* Correspondence:raissa.sorgho@uni-heidelberg.de1Institute of Public Health,Universitats Klinikum, Heidelberg,GermanyFull list of author information isavailable at the end of the articleAbstractMalnutrition remains a leading cause of death in children in low- and middle-incomecountries; this will be aggravated by climate change. Annually, 6.9 million deaths ofchildren under 5 were attributable directly or indirectly to malnutrition. Althoughthese figures have recently decreased, evidence shows that a world with a mediumclimate (local warming up to 3–4 °C) will create an additional 25.2 million malnourishedchildren. This proof of concept study explores the relationships between childhoodmalnutrition (more specifically stunting), regional agricultural yields, and climate variablesthrough the use of remote sensing (RS) satellite imaging along with algorithms topredict the effect of climate variability on agricultural yields and on malnutrition ofchildren under 5. The success of this proof of purpose study, NUTRItion and CLIMate(NUTRICLIM), should encourage researchers to apply both concept and tools to study ofthe link between weather variability, crop yield, and malnutrition on a larger scale. Itwould also allow for linking such micro-level data to climate models and address thechallenge of projecting the additional impact of childhood malnutrition from climatechange to various policy relevant time horizons.Keywords: Malnutrition, Low- and middle-income countries, Climate change, Stunting,Remote sensing, WeatherMain textMalnutrition is globally recognized as having one of the largest adverse effects on thegrowth of nations, because it not only poses a challenge to the health but also to theproductivity of populations [1]. Unfortunately, climate change will have an additionalnegative impact on childhood nutrition through a large number of factors [1, 2]. Whilemalnutrition in children has globally decreased over the past few decades, climatechange has the potential to reverse the recent gains in the global reduction of malnu-trition [3]. A median climate (local warming up to 3–4 °C) is projected to create anadditional 25.2 million malnourished children [2, 4]. The 2015 Rockefeller Foundationand Lancet Commission on Planetary Health publication titled: Safeguarding humanhealth in the Anthropocene epoch, states along with the IPCC that “… median crop© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 InternationalLicense (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, andindicate 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.Sorgho et al. Public Health Reviews  (2016) 37:16 DOI 10.1186/s40985-016-0031-6yields would decrease by 0–2 % per decade for the remainder of the century, as a resultof climate change alone, with or without adaptation, whereas demands for crops areprojected to increase by 14 % per decade up to 2050” [5, 6]. The publication continuesby detailing that the projected decreases in crop yields result in increasing numbers ofstunted children, especially in Asia and Africa. More than 90 % of the world’s stuntedchildren live in Africa and Asia [7]. Currently, 36 % of all children under 5 years insub-Saharan Africa suffer from stunting—a severe form of malnutrition [1, 2]. Projec-tions forecast that stunting will increase by approximately 23 % in the region; this iswhy we selected a sub-Saharan African country as the site of this proof of conceptexploratory study [2].The relationship between changing climate, agriculture, and malnutrition is influencedby a multitude of factors. The complexity and interdisciplinary nature of these three issuesconverge into an elaborate web, which is represented in Fig. 1. The convolution of theselinks is precisely the reason these connections have been understudied.Figure 1 illustrates an aspect of the complexity of the relationships investigated. Eachof the three colored boxes represents one of three pillars: climate, agriculture, and mal-nutrition. Each arrow represents a relationship between two variables or factors. Thethree pillars converge on the subject of food crops and food yields.This exploratory study, NUTRItion and CLIMate (NUTRICLIM), in Burkina Fasoaims to investigate the relationship between weather variability, crop yields, householdsocioeconomic variables, and malnutrition. The study village of Bourasso, which has12,548 inhabitants, in the rural Kossi Province is located 25 km from the small town ofNouna. The study involves 156 individuals, subdivided into 20 households with 29 chil-dren under the age of 5. This first sample was randomly selected from the INDEPTHHuman Demographic Surveillance System (HDSS) database of the Centre de Recherchéen Santé de Nouna (CRSN) and the second sample from local Bourasso Health Post’sdatabase of malnourished children [8]. The 20 households can thus be subdivided intosample 1: 10 households that were randomly selected and coincidentally had no mal-nourished children under the age of 5, and sample 2: 10 households that were purpose-fully selected for having children under the age of 5 who were undergoing treatmentFig. 1 The complexity and interdisciplinary nature of these three issues converge into an elaborate web.Adapted from Phalkey et al. [1]Sorgho et al. Public Health Reviews  (2016) 37:16 Page 2 of 5for malnutrition. The additional selection criteria were that all 20 households be sub-sistence farmers, living in the village of Bourasso, with at least one child under the ageof 5.Data for the first pillar, climate, were acquired through the two nearest local weatherstations of the HDSS. The weather stations provide information on median dailytemperature, daily rainfall, as well as seasonal distribution and variability of rainfall.Data for the second pillar, agriculture, was collected through two methods. The firstmethod was harvest yields reported by farmers and converted from local measures into ki-lograms. The second was innovative in that it estimated plot level yields by household andcrop using special algorithms from remotely sensed data of the village and its surroundings.This required the delineation of each field of all households with the farmers using a GPSto establish the polygons. These were overlaid with scenes from the RapidEye satellite, cov-ering the agricultural fields of the 20 selected households. We carried out ground validationthrough verification and comparison of the results from remote sensing (RS) satellite im-aging; field agents physically verified that the satellite readings matched ground data. Post-harvest, the figures of the actual agricultural yields are used as input data to better calibratethe algorithms for modeling crop yields on a micro-level (household level).The third pillar covered malnutrition and health. This data was collected using a socio-economic and morbidity questionnaire for the selected households. The survey assessed(i) household assets, revenues, and expenditure, (ii) a 24-hour nutritional recall journal ofall children under 5, and (iii) all recent child illnesses within the household, both chronicand acute (episodes of diarrhea, malaria, etc.). Furthermore, we used standard anthropom-etry (weight, height, and mid-upper-arm circumference) to assess the nutritional status ofchildren under the age of 5.As data analysis was still in progress at the time of the presentation at the COP21, nodefinitive results could be stated. But preliminary findings indicate the possibility of dis-parities in the agricultural yield of households with and without malnourished childrenand between years with average and low rainfall. The differences were noticed not onlyin the types of crops sown but also in the number of plots owned by the households:households with healthy children had, on average, a greater number of fields. When thesubsistence farmers were questioned on their yields, only one third classified their har-vest as good, allowing the household to be fed in a satisfactory manner for the entireyear until the next harvest. The remaining two thirds of all households attributed insuf-ficient yields to bad rains, changing rain patterns, or unpredictable rain patterns. Thispotentially highlights the significance of changing weather patterns and their conse-quences in terms of droughts [4, 9].ConclusionsWe laid out a number of field methods in the fields of meteorology, agriculture, nutrition,and health that allow for the study of the web of causation of childhood malnutrition witha particular focus on the role of weather and climate in the future.We propose that large-scale studies using these methods, amongst others, be considered.These could then be linked to downscaled climate models in cooperation with climate sci-entists in order to establish data-based projections of the future impact of climate changeon malnutrition rather than relying on a set of assumptions and mono-disciplinary frag-mented studies.Sorgho et al. Public Health Reviews  (2016) 37:16 Page 3 of 5AbbreviationsCRSNm: Centre de Recherche en Sante de Nouna; HDSS: Human Demographic Surveillance SystemAcknowledgementsWe would like to thank the people of Bourasso for the time they accorded to the collection of this pilot study data.FundingPilot study was funded by the institute of Public Health at the University of Heidelberg.Availability of data and materialsThe datasets generated during the current study are not publicly available due to the fact that they are still beinganalyzed and are to be utilized for further publication before public release. But this data can be made available fromthe corresponding author on reasonable request.Authors’ contributionsRSorgho is the field research coordinator, author and COP21 presenter. JF is the Remote Sensing and Rapid EyeImaging expert. SS is the cartography and GIS expert. RP is the study co-supervisor. RSauerborn is the editor, reviwerand study supervisor. All authors read and approved the final manuscript.Authors’ informationRaissa Sorgho is a researcher on two climate and health studies at the Institute of Public Health in Heidelberg, Germany.Her background is in biology, and she is currently a candidate for a Master of Science in International Health whilesimultaneously working on her doctorate. Her research interests include agriculture, nutrition, health financing, andclimate change.Competing interestsThe authors declare that they have no competing interests.Consent for publicationNot applicable.Ethics approval and consent to participateThe study NUTRICLIM was approved by the Heidelberg University ethical committee “Ethik Kommission MedizinischeFakultät Heidelberg”. Furthermore, in observation of ethically appropriate scientific research, NUTRICLIM followed theprocedures of the ongoing Nouna Socioeconomic and Health Panel Survey (SOHPS). This is the process, which hasbeen utilized by the CRSN research center since 2000. For the anthropometric component of the study, NUTRICLIMfollowed standard WHO procedures. The study team ensured that all malnutrition cases discovered during the courseof the study would be presented to the CSPS and, if needed, be referred to Centre de Rehabilitation Nutritional (CREN) inthe district capital Nouna. The project contributed 50 % of all rehabilitation and care cost for such children. Lastly, theproject had no environment impact.All participants consented verbally and in written form to partake in the study. Participation in the research studywas entirely voluntary; it had and will continue to have no effects or repercussions on the work or social life ofparticipants. Participants were free to change their minds at any point, ceasing participation at will. There were nocosts associated with participation nor were there financial incentives. The information collected in the frameworkof this research project was confidential. This information was stored in a file number anonymously. All consequentfiles were replaced with a unique identification number. No information was shared with anybody outside theresearch team. The knowledge gained from this research will be published so that other interested persons maylearn from the research.Author details1Institute of Public Health, Universitats Klinikum, Heidelberg, Germany. 2Remote Sensing Solution GmBh (RSS),Environmental Consulting, Baierbrunn, Germany. 3Centre de Recherche en Santé de Nouna (CRSN), Research Center,INDEPTH Network, HDSS, Nouna, Burkina Faso. 4Division of Epidemiology and Public Health, University of Nottingham,Nottingham, UK.Received: 15 September 2016 Accepted: 22 September 2016References1. Phalkey R, Aranda-Jan C, Marx S, Höfle B, Sauerborn R. A systematic review of current efforts to quantify theimpacts of climate change on undernutrition. PNAS. 2015;112(33):E4522–9. doi:10.1073/pnas.1409769112.2. Lloyd SJ, et al. Climate change, crop yields, and undernutrition: development of a model to quantify the impactof climate scenarios on child undernutrition. Environ Health Perspect. 2011;119(12):1817–23.3. Woodward A, Smith K, Campbell-Lendrum D, Chadee D, Honda Y, Liu Q, Olwoch J, Revich B, Sauerborn R, Chafe Z,Haines A. Climate change and health—the latest report from the IPCC. Lancet. 2014;283:1185–9.4. Whitmee S, Haines A, Beyrer C, Boltz F, Capon AG, de Souza Dias BF, et al. Safeguarding human health in theAnthropocene epoch: report of The Rockefeller Foundation-Lancet Commission on planetary health (Haines AChair of Commission). Lancet. 2015;386:1973–2028.5. Lobell DB, et al. Prioritizing climate change adaptation needs for food security in 2030. Science. 2008;319(5863):607–10.Sorgho et al. Public Health Reviews  (2016) 37:16 Page 4 of 56. Nelson GC, Rosegrant MW, Koo J, Robertson R, Sulser T, Zhu T, et al. Climate change: impact on agricultureand costs of adaptation. food policy report. Washington, DC: International Food Policy Research Institute;2009. p. 1–30.7. UNICEF. UNICEF-WHO-World Bank Joint Child Malnutrition Estimates. 2012. Available at www.who.int/nutgrowthdb/jme_unicef_who_wb.pdf. Accessed January 10, 2015.8. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. Intl J Epidem.2012;41:579–88.9. Anyamba A, Chretien JP, Small J, Tucker CJ, Linthicum KJ. Developing global climate anomalies suggest potentialdisease risks for 2006-2007. Int J Health Geogr. 2006;28:5. 60.•  We accept pre-submission inquiries •  Our selector tool helps you to find the most relevant journal•  We provide round the clock customer support •  Convenient online submission•  Thorough peer review•  Inclusion in PubMed and all major indexing services •  Maximum visibility for your researchSubmit your manuscript atwww.biomedcentral.com/submitSubmit your next manuscript to BioMed Central and we will help you at every step:Sorgho et al. 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NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso

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