Climate, seasonality and spatial studies
byANH Academy
Academy Week Research Conference
| Agriculture, Environment
Date and Time
From: 2 July 2020, 14:15
To: 2 July 2020, 15:15
Location
Country: United Kingdom
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Intro animation:

Climate, seasonality and spatial studies at ANH2020

 

Session recording:

ANH2020: Climate, seasonality and spatial studies

 

Speakers and presentations:

  • Session chair: Todd Rosenstock, World Agroforestry Centre (ICRAF)
    @todd_rosenstock @ICRAF

  • Adamu Belay, Ethiopian Public Health Institute
    @EPHIEthiopia
    Selenium deficiency is widespread and spatially dependent in Ethiopia
    Presentation | Slides

  • Emily Amondo, University of Bonn
    @UniBonn
    Whose health is affected by climate variability? Evidence from households in rural Uganda
    Presentation | Slides

  • Josiah Mwangi Ateka, Jomo Kenyatta University of Agriculture & Technology
    @MwangiAteka @DiscoverJKUAT
    Forest dependence and household food and nutrition security in Kenya
    Presentation | Slides

  • Naomi Saville, University College London
    @naomi_saville @UCLGlobalHealth
    Complex and comprehensive seasonality of neonatal and maternal nutrition in the plains of Nepal
    Presentation | Slide

Abstracts:

Selenium deficiency is widespread and spatially dependent in Ethiopia

Adamu Belay1,2

Dawd Gashu2

Edward J. M. Joy3

R. Murray Lark4

Dilnesaw Zerfu1

E. Louise Ander5

Scott D. Young4

Liz Bailey4

Martin R. Broadley4


1Food Science and Nutrition Research Directorate, Ethiopian Public Health Institute, Gulele Sub City, P.O.Box 1242 Addis Ababa, Ethiopia.
2Center for Food Science and Nutrition, Addis Ababa University, P. O. Box 1176, Addis Ababa, Ethiopia
3Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
4School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, LE12 5RD, UK.
5Inorganic Geochemistry, Centre for Environmental Geochemistry, British Geological Survey, Nottingham, NG12 5GG, UK.

Introduction

Estimates of Micronutrient Nutrient Deficiencies at national and sub-national scales are inadequate across sub-Saharan Africa for reasons which include a lack of spatial information on food systems, reliable biomarkers of micronutrient status, and links between Micronutrient Deficiencies and health outcomes with multiple etiologies. This poses immense challenges for policy makers for prioritizing/targeting policy decisions, and for private sector investments. Selenium (Se) is an important micronutrient, which is essential in trace amounts in diets for optimal human and livestock health. In Ethiopia, there are no data which reflect the status of selenium at national and regional level.

Methods

The study design is multi-stage, cross-sectional survey including preschool and school-aged children, women and men. Participants (n=3297) were included for serum selenium analysis from the archived samples of the Ethiopian National Micronutrient Survey (ENMS) which covered nine regions and two city administrations between March 2015 and July 2016. The ENMS enumeration areas (EAs) or clusters are geographic areas defined by the Central Statistics Agency (CSA) for the Ethiopia Population and Housing Census (CSA 2008). In the ENMS, 366 EAs were randomly selected from all region or city administrations with probability of inclusion proportional to size. All preschool children (PSC, 6-59 months), 6 school aged children (SAC, 5-15 years), 3 men and 7 women of reproductive age (WRA) in 11 households per EA were selected for the actual survey. Socio-demographic information, geographic coordinate, anthropometry and blood were collected. A total of 4026 households in 366 clusters were selected; 92% (n=3700) of households in 353 clusters gave consent and were included in the study. Concentration of Se in serum samples was determined using ICPMS at the University of Nottingham under an MTA. Data were merged and analyzed using STATA; predictions of Se status were conducted using geospatial modelling in R.

Findings

Median serum Se concentration was 98.1 μg/L; 27.1% of a population had serum Se concentration less than an indicative threshold for deficiency (<70 μg/L). Age of participant was positively associated with selenium status (r=0.25, P<0.001). The median serum Se of Benishangul-Gumuz, Amhara and Oromia Regions were 56.3 µg/L, 66.9 µg/L and 77.4 µg/L, respectively. Altitude was positively associated with serum selenium status of the participants (r=0.312, P=0.018). Inflammation was negatively associated with selenium status. With presence of infection, the participants had 8.8 µg/L lower selenium concentration (95% CI:-15.37,-2.17) (P=0.009). Variation in serum Se status was observed across the country showing that Se status is under strong geospatial control. Using geostatistical methods it is possible to identify where individuals are likely to have serum Se concentrations below the thresholds for optimal activity of GPx3, an important antioxidant, and for the production of the thyroid hormone iodothyronine deiodinase. At ANH these results will be presented as maps.

Conclusion

The present study reveals that Se deficiency in Ethiopia is widespread, especially among PSC and SAC. Risk of Se deficiency is highly spatially dependent, which is likely to be due to environment-food system factors including soil type, landscape features, and food production and distribution. Serum Se concentrations were greater among populations living in the Rift Valley. These data suggest that the need to establish routine monitoring of Se status of the Ethiopian population in future surveys and investigate different strategies to enhance the intake of Se, including dietary diversity and agronomic biofortification, using multi-disciplinary and multi-sectoral approaches.

References

Joy EJM, Kumssa DB, Broadley MR, Watts MJ, Young SD, Chilimba ADC, Ander EL. Dietary mineral supplies in Malawi: spatial and socioeconomic assessment. BMC nutrition. 2015;1:42.

Rayman MP. Selenium and human health Role of selenium : selenoproteins. Lancet. 2012;379(9822):1256–68.

Phiri FP, Ander EL, Bailey EH, Chilima B, Chilimba ADC, Gondwe J, Joy EJM, Kalimbira AA, Kumssa DB, Lark RM, Phuka JC, Salter A, Suchdev PS, Watts MJ, Young SD, Broadley MR. The risk of selenium deficiency in Malawi is large and varies over multiple spatial scales. Scientific Reports. 2019;9(1):1-8.

Whose health is affected by climate variability? Evidence from households in rural Uganda

Emily Injete Amondo1

Alisher Mirzabaev

1Center for Development Research (ZEF), University of Bonn

Introduction

Rural farming households are vulnerable to a multitude of risks including health risks associated with climate change and variability. This study empirically explores the relationship between climate variability and major symptoms of climate-sensitive illnesses including nutritional health outcomes of rural children and households. Agriculture mechanisms through which climate variability impacts the nutritional outcomes was tested since rural smallholder farmers are highly dependent on agricultural production for both food and income. Heterogeneous effects of climate variability on males, females and children on the short-term health outcomes in households were further assessed.

Methods

We combined four waves of secondary data; the rich Uganda National Panel Survey (UNPS), part of the World Bank Living Standards Measurement Studies (LSMS) for the period 2009-2014 with high quality and consistent remotely sensed satellite data products from 2004 to 2014. In particular, rainfall and temperature datasets were downloaded from Climate Hazards group Infrared Precipitation Station (CHIRPS) and Moderate Resolution Imaging Spectroradiometer (MODIS) respectively. Additionally, FEWS NET seasonal calendar for a typical year in Uganda was used to develop several weather indices from the downloaded rainfall and temperature data considering months in the planting and growing periods for both seasons. Seasonal rainfall, dry spell months, heat-waves months and their lags were used as main weather indices. A further indicator of climate risk , the seasonal rainfall variability- the coefficient of variation (CV) was constructed. Rainfall and temperature preceding interview months were used. The dependent variables were the anthropometric z-scores and counts of different household members who suffered from the climate sensitive health outcomes (diarrhoea, fever, chills and headache). Empirical strategy consisted of two estimations; first at individual level by applying fixed effects regressions and second at household level using mixed-effects negative binomial econometric model. Analysis was done in STATA.

Findings

Overall, the results showed evidence of strong and significant negative associations between children anthropometric measures (Height- for- Age Z scores; Weight-for-Age Z-scores and Weight-for-Height Z-scores) and temperature based indicators, after controlling for other factors such as asset and water sanitation and hygiene (WASH) index. Seasonal rainfall on the otherhand had a positive effect on HAZ and WHZ scores. Agricultural production was the main transmission channel. There was a positive and significant impact of seasonal rainfall on crop out. However, rainfall coefficient of variation and extreme temperatures had a significant negative effect on total crop output. Rainfall is crucial for agricultural production especially during the planting and growing periods of crops while heat stress is one of the major limiting factors in crop production. Interaction term between heat wave months and improved seed was positive. Negative binomial model confirmed the positive and significant association between temperature and diarrhea, headache incidence rates especially among children and females. Additionally, a positive and significant association of rainfall on fever and headache incidence rates among female, and diarrhea in children was observed. Results further revealed that households who engaged in ex-ante or anticipatory risk reducing strategies experienced lower incidence rates of illnesses.

Conclusion

Evidence of significant association between rainfall and temperature based indicators on children health outcomes through agriculture mechanism. Climate variability has a heterogeneous effect on health outcomes of different members of household. The results further suggest the importance of adaptation in smoothing the harmful effects of climate variability on health of rural households. Therefore, right adaptation strategies have the capacity to minimize health effects resulting from climate change.

References

Funk C, Peterson, Landsfeld M and Pedreros D et al (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific. Data. 2:150066 doi: 10.1038/sdata.2015.66 (2015).

Uganda Bureau of Statistics- Government of Uganda (2016). National Panel Survey 2013-2014. UGA_2013_UNPS_v01_M. The World Bank Microdata Library. Accessed on 14/05/2019 Uganda Bureau of Statistics- Government of Uganda. National Panel Survey 2005-2009. DDI_UGA_2005-2009_UNPS_v01_M_W. The World Bank Microdata Library. Accessed on 14/05/2019.

Uganda Bureau of Statistics- Government of Uganda (2014). National Panel Survey 2010-2011. UGA_2010_UNPS_v01_M. The World Bank Microdata Library. Accessed on 14/05/2019

Uganda Bureau of Statistics- Government of Uganda (2014). National Panel Survey 2011-2012. UGA_2011_UNPS_v01_M.DDI_UGA_2011_UNPS_v01_M_WB. The World Bank Microdata Library. Accessed on 14/05/2019

Forest dependence and household food and nutrition security in Kenya

Josiah M Ateka1

Robert M Mbeche1

Esther Wangari1


1Jomo Kenyatta University of Agriculture & Technology

Introduction

About 1 billion poor people globally depend on forests for their livelihoods (Angelsen et al. 2014; HLPE. 2017). While there is growing recognition that forests complement farmland agriculture in providing food security and nutrition (FSN), few studies have focused on this dimension of livelihoods. As a result, the complex, overlapping and interconnecting processes which link forest products and services to FSN are currently not adequately represented in forestry, agriculture, food or nutrition-related strategies at global and national levels (Powell et al. 2015). This paper assesses the effect of forest dependence on household food security in rural western Kenya.

Methods

Data for this paper were collected using a cross sectional survey of 924 households in Mt Elgon, Western Kenya. During the first stage, two counties hosting state protected forests were selected. In the second stage, 30 villages were sampled with probability proportional to the size of village’s population. During the last stage, a sample size of forest dependent households in each sampled village was randomly chosen from a list of households with equal probability selection. The survey was undertaken between November 2018 and January 2019. Forest dependency was measured in terms of both a count of total number and aggregate value of forest products extracted. Food security on the other hand was measured using three indicators – Food Insecurity Experience Scale (FIES), Household Dietary Diversity (HDD) and the share of food expenditure. The influence of forest dependency on food security and nutrition (FSN) was analyzed using a set of Poisson and two-stage residual inclusion (2SRI) regressions.

Findings

The results show that about half (48.9%) of the households were engaged in forest extraction which contributes to FSN in numerous ways including direct food provisioning (fruits and vegetables (21.7%), energy for cooking (62.0%), medicinal plants (4.2%), fodder (1.9%) and timber for income (1.3%). The number of forest product extracted ranged between 1 and 7, while the mean annual value of forest products extracted was approximately US$ 320 accounting for about 23% of overall household expenditure. The level of food insecurity was generally high with only about a quarter (23.5 percent) of the households being food secure while over 40% were severely insecure. While dietary patterns on a weekly basis were rather diversified (6.3), consumption of vitamin A (1.7) and iron rich foods (0.82) was limited. The share of expenditure spent on food was generally high (47.5%), suggesting high vulnerability to food insecurity. The econometric results show that while the value the forest products extracted had a positive influence on household food security, forest dependency measured as a count of number of products extracted was associated with higher levels of food insecurity. These findings suggest that household decisions on the type and extent of extraction have important implications for FSN.

Conclusion

Overall, the paper has shown that forests can play an important role in complementing agricultural production in providing better and more nutritionally-balanced diets; wood fuel for cooking and greater control over food consumption choices. However, this depends on context specific factors which determine whether a household engages in forest extraction for survival or as a means for enhancing livelihood conditions.

References

Agrawal, A., Cashore, B., Hardin, R., Shepherd, G., Benson, C., Miller, D., 2013. Economic contributions of forests. Background Paper for the United Nations Forum on Forests (http://www.un.org/esa/forests/pdf/session_documents/unff10/EcoContrFores...).
Angelsen, A., Jagger, P., Babigumira , R., Belcher, B., Hogarth, N., Bauch, B., Börner, J., Smith-Hall, C., Wunder, S., 2014. Environmental income and rural livelihoods: A global-comparative analysis. World Development 64: 12–28.
HLPE. 2017. Sustainable forestry for food security and nutrition. A report by the High-Level Panel of Experts on Food Security and Nutrition of the Committee on World Food Security, Rome.
Powell, B., Thilsted, S.H., Ickowitz, A., Termote, C., Sunderland, T., Herforth, A., 2015. Improving diets with wild and cultivated biodiversity from across the landscape. Food Security, 7(3): 535–554.

Complex and comprehensive seasonality of neonatal and maternal nutrition in the plains of Nepal

Naomi M. Saville1
Mario Cortina-Borja2
Bianca de Stavola2
Emma Pomeroy4
Akanksha Marphatia3
Dharma S. Manandhar5
Jonathan Wells2

1Institute for Global Health (IGH), University College London (UCL), London, UK
2Great Ormond Street Institute of Child Health (ICH), University College London (UCL), London, UK
3Department of Geography, University of Cambridge, Cambridge, UK
4Department of Archaeology, University of Cambridge, Cambridge, UK
5Mother and Infant Research Activities (MIRA), Kathmandu, Nepal

Introduction

In the Nepal plains, weather patterns, agricultural labor, food availability and disease prevalence vary greatly by season and are likely to affect food intakes, morbidity, and anthropometry of pregnant women and neonates. During pre-monsoon/ monsoon seasons, high temperatures and humidity cause heat stress, which has been associated with lower birth weight and diarrhea. Fragmented evidence on seasonal effects on maternal nutrition and birth size is available from the Gambia, Bangladesh, India and Nepal, but we provide a more comprehensive analysis in a disadvantaged lowland Nepal population.

Methods

Using Low Birth Weight South Asia Trial cohort data from Nepal plains districts of Dhanusha and Mahottari, we applied cosinor analysis to detect seasonal effects in annual and half-yearly cycles as used by Fernandez and Pomeroy. We regressed each seasonally varying variable against the sine and cosine terms of the day out of 365 (or the day out of 182.5), using bootstrapping to compute confidence intervals of the acrophase (n=1,348 to 3,832). We plotted predicted seasonal patterns using ggplot2 package in R.
Outcomes included: z-scores of newborn length-, weight- and head circumference-for age and weight-for-length <=72 hours from birth (LAZ, WAZ, WHZ, HCAZ); early and late pregnancy Mid-Upper Arm Circumference (MUAC), body mass index (BMI), dietary diversity and number of eating occasions (main meals plus snacks) per day, eating less than when not pregnant, vomiting, and consumption of each of nine food groups (meat/fish, dairy, eggs, pulses, nuts/seeds, green leafy vegetables, vitamin A-rich fruits and vegetables, other vegetables and other fruits). Aversion to food/ lack of appetite and recall of diarrhea in the last 2 weeks were analyzed for late pregnancy only. Amongst those that experienced food shortages, we assessed prevalence of food insecurity by month.

Findings

We observed differing seasonal patterns in newborn and pregnant women’s anthropometry, food aversion and eating down, vomiting, meal frequency, dietary diversity and consumption of individual micronutrient-rich foods (meat/fish, nuts/seeds, pulses, and vegetables). Neonates were born shorter but heavier in the winter, and thinner with relatively high LAZ in the hot season. Annual variation was highest for WLZ but negligible for HCAZ. Pregnant mothers’ seasonal consumption varied by food group. Food aversion and eating down were highest in the hot season and early pregnancy vomiting peaked in the monsoon / hot season.
We postulate that being born short in winter may be due to the poor nutritional condition of the mother some months earlier in October/November when late pregnancy BMI is lowest, MUAC is relatively low, food insecurity peaks, and dietary diversity in late pregnancy has a small dip. However, the sudden improvement in food security at harvest (November/December) may lead to increased mother’s energy intake and associated weight gain of the fetus, such that neonates are born less thin in winter. In contrast, being born thin in the hot season may be associated with heat stress manifested as late pregnancy aversion to food and eating less than when not pregnant.

Conclusion

Generally, neonatal anthropometry tracked pregnant mothers’ nutritional status, but patterns of eating behavior, workload, food availability, and morbidity were complicated by various ecological and cultural factors, including heat stress. Public health interventions to prevent under-nutrition should account for seasonality in their design and evaluations. Studies should aim to collect data across different seasons wherever feasible and to adjust for seasonality in their analyses. In longitudinal studies with repeated data collection occasions between years, data should be collected in the same season so as to avoid misinterpretation of apparent time trends that might be attributable to differing season of measurement.

References

Pradhan B, Shrestha S., Shrestha R., Pradhanang S., Kayastha B., Pradhan P. 2013. Assessing Climate Change and Heat Stress Responses in the Tarai Region of Nepal. Industrial Health, 51 (1) 101-12.
Wells J.C.K.., Cole T.J. 2002. Birth weight and environmental heat load: A between-population analysis. Am J Phys Anthropol., 119 (3) 276-82.
Moffat T. Diarrhea, respiratory infections, protozoan gastrointestinal parasites, and child growth in Kathmandu, Nepal. 2003. Am J Phys Anthropol., 122 (1) 85-97..
WFP Nepal. 2010. The Food Security Atlas of Nepal. Kathmandu: WFP.
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Prentice A.M., Cole T., Foord F.A., Lamb W.H., Whitehead R.G. 1987. Increased birthweight after prenatal dietary supplementation of rural African women. The American Journal of Clinical Nutrition, 46 (6) 912–25.
Shaheen, R., Shaheen, R., de Francisco, A., El Arifeen, S., Ekström, E.C. and Persson, L.Å., 2006. Effect of prenatal food supplementation on birth weight: an observational study from Bangladesh. The American journal of clinical nutrition, 83 (6) 1355-1361.
Huffman S., Wolff M., Lowell S., Huffman S.L., Wolff M., Lowell S. 1985. Nutrition and fertility in Bangladesh: nutritional status of nonpregnant women. Am J Clin Nutr 42, 725-738.
Rao S., Kanade A.N., Yajnik C.S., Fall C.H. 2009. Seasonality in maternal intake and activity influence offspring's birth size among rural Indian mothers-Pune Maternal Nutrition Study. Int J Epidemiol. 38(4):1094-103.
Campbell R.K., Talegawkar S.A., Christian P., LeClerq S.C., Khatry S.K., Wu L.S.F., et al. 2014. Seasonal Dietary Intakes and Socioeconomic Status among Women in the Terai of Nepal. Journal of Health, Population, and Nutrition, 32 (2) 198-216.
Fernandez J.R., Herminda R.C., Mojon A. 2009. Chronobiological analysis techniques. Application to blood pressure. Philos Trans A Math Phys Eng Sci., 367 (1887) 431-45.
Pomeroy E., Wells J.C.K., Stanojevic S., Miranda J.J., Cole T.J., Stock J.T. 2014. Birth month associations with height, head circumference, and limb lengths among Peruvian children. Am J Phys Anthropol., 154 (1) 115-24.
Wickham H. 2016. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York.

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