Presentation on theme: "Environment, Migration, and Human Health in Latin America and Africa: Evidence, Gaps and Opportunities (from a geographer’s perspective) David Lopez Carr."— Presentation transcript:
Environment, Migration, and Human Health in Latin America and Africa: Evidence, Gaps and Opportunities (from a geographer’s perspective) David Lopez Carr Human-Environment Dynamics Lab Geography Department UC Santa Barbara 7th Summer Institute on Migration and Global Health Los Angeles, California, USA
Current Projects in Latin America Some Current/Recent Projects Population Dynamics, Urbanization, and Tropical Deforestation/LUCC Guatemala (NIH K01; R03; NSF GSS; with Laurel Suter) Ecuador (with JHU, UNC-CPC; NASA; NIH R01 and R03) Central and South America (with M. Aide, CIESIN, et al; NSF CNH Biocomplexity Award) Rural, Urban, and International Migration Remittances, Population Change, and Environmental Impacts in Guatemala (NSF, UC-Pacific Rim, and NASA ESSF with J. Davis) and in Ecuador (with A. Barbieri, R. Bilsborrow et al; NASA & NIH R01 and R03) Fertility and Maternal and Child Health Ecuador (with W. Pan and colleagues at JHU and UNC-CPC; NIH R03) Guatemala. NIH K01
Human Impacts and Adaptation in Marine Protected Areas Mesoamerican Reef (Mellon Foundation), Moorea, Polynesia and S. California (with NSF LTER social science supplements) Integrated Population, Health, and Environment (PHE) in Global Ecological Hot Spots (with PRB, WWF and USAID) Demographic and Health Surveys (DHS) e.g., Petén, Guatemala (with USAID) Population and Health Dimensions of Climate Change Climate change connections to population and health in Sub-Saharan Africa. (with FEWSNet colleagues, NOAA). Nutrition Transition: Population, health, and the environment in Ghana. With colleagues from SDSU and Harvard Public Health. NIH R01, PI John Weeks, NASA ROSES award, PI Doug Stowe. Most publications available online at:
Two Big Geographical Framing Concepts for Coupled Migration-Health Transitions: 1) Available agricultural land is a diminishing and constraining resource. Human-land relations are critically linked to demography (particularly migration!), health (both nutrition and disease), economic sustainability, and environmental /climate change. 2) Space (scale) and place matter!
Demographic and Nutritional Transitions and Migration 1) (Despite rapid urbanization) Remote rural demographic transitions will have a disproportionate effect on future global population size and distribution. R-R to R-U migration transition will be important and the pace and timing of this transition will have huge health and land change implications. 2) How many people eat what produced where? This will describe the vast majority of future land changes on the face of the earth and much of the future health of humanity. Where people are vis a vis migration will largely influence this.
Global Demographic Transition: Urbanization & Aging
Demographic Transition Variation in Latin America Let’s now discuss an example from Guatemala of early demographic transition, rural food insecurity as a link to migration and exposure to new health problems in destination areas….
Processes in distant places - skewed land distribution, demographic pressures, poverty, war, and food insecurity - lead to environmental change in another place Migration to the Maya Biosphere Reserve: Where did migrants come from, why from there, and what are health implications?
Why do people migrate to the Maya Biosphere Reserve? Land for Food Ecological Factors Socio-economic Factors Demographic Factors Political-economic Factors
Macro-Scale demographic, political-economic, social, and ecological dynamics Urban or International Destinations Rural Destination Agricultural Extensification Agricultural Intensification Return to Top of Chart MigrationFertility regulation Off-farm Labor Household Responses Local Variation Land Management Migration to the SLNP Other response??
Health Implications -Food security increases in the short term but as forest reserves decline, food insecurity may decrease in a matter of several years. -High infant mortality – common for a mother to have 1-3 infant deaths in her lifetime -Very high intestinal infection rates among infants and malaria is endemic -TFR exceeding 7 has further implications for food security -MIGRATION is an adaptation used by many – But the destination is not random
Household migration, retention and destinations from 2009 survey: Frontier- frontier migration selection may lead to recurrence of health and food security issues
Guatemala Case Study Conclusions -Food insecurity remains a major and recurrent rural-rural migration determinant -the most food insecure are disproportionately selected for frontier migration where food insecurity is a short- term trade-off for other health problems. -Within a generation, food insecurity recurs and migration is an adaptation response – often to another forest frontier where the cycle repeats.
Now to an African Case Study: Mali -Climate as a driver of deleterious health outcomes and implications for migration
Malnutrition, and Migration: What about Climate Change? Human adaptation critical for managing health/nutritional effects of climate change Decreased yield Decreased income and nutritional well-being (Brown & Funk, 2008) Migration, an alternative option for adaptation Population growth Poverty Environmental degradation Health deterioration Migration (Bremner, et al., 2010)
Vulnerability to climate change: Migration & Health is a missing link: Migration as adaptation? But to where? Global climate-demography vulnerability index (Samson et al., 2011)
Shifting and Stagnating Demographic Transitions in Africa
…and the Shifting Sands of the Sahel The Sahel, comprising portions of 10 African countries, from left to right: [northern] Senegal, [southern] Mauritania, [central] Mali, [northern] Burkina Faso, [southern] Algeria, [southwestern] Niger, [northern] Nigeria, [central] Chad, [central] Sudan and [northern] Eritrea.
Climate in the Sahel Predictions of climate change vary: – Warming of northern tropical Atlantic Increased Sahelian rainfall (Cook, 2008; Hoerling, et al., 2006) – Drying in eastern Sahel and increased rain in the west (most accurate) (Held, et al., 2005) Present climate trends produce unreliable results – Rectified by USAID’s Famine Early Warning System Network (FEWS NET) FEWS NET Trend Analyses (FTA) FEWS NET Climatology (FCLIM)
The case of Mali Wide range of land cover and agricultural livelihoods Mali’s climate and related nutritional situations can be generalized for the Sahel and other sub- Saharan African countries
Methods for Climatic Measurement Variables represent spatial gradients of temperature and precipitation – Variables: Latitude, longitude, elevation, slope and satellite observations of rainfall, infrared brightness temperatures and LST PPET = Rainfall – PET (potential evapotranspiration) – Used as an input variable for the malnutrition modeling
Modeling Malnutrition using Demographic and Health Surveys Conclusions drawn at cluster level Simple OLS regression model for child malnutrition Relationship between PPET, livelihood zones, and three measures of child malnutrition – Child malnutrition measures: anemia, underweight, and stunting
Individual/Household Variables number of durable goods age of household head years of mother’s education children ever born to mother wealth index of household the use of an unprotected well by the household the child’s age in months
Warming Results , Kenya- Ethiopia and Sudan- Niger-Mali warmed – Disrupted seasonal cycle of crops – Additional water from soil/plants drawn – Reduced grain production
Malnutrition Results Cluster’s location within PPET<-100 predicts severity for stunting and underweight – Likely due to climate driven livelihoods that fail to support cereal crops Cluster’s location within PPET<-100 predicts lower cluster anemia measures – Likely due to the practice of livestock rearing Meat and iron consumption
Shifting of PPET The PPET<-100 contour is demonstrably shifting southward due to drying and warming – Enveloping more Malians and therefore vulnerable children PPET<-100 negatively influences underweight and stunting and positively influences anemia Shifting of PPET into the southern, agricultural areas of the country would impact Mali’s ability to sustain its food needs and export cash crops
Migration implications More people will be pushed into the vulnerable arid zones or will migrate out of them Total [millions]PPET -100 position based on climatology PPET -100 position based on climatology PPET > -100PPET <= -100PPET > -100PPET <=
Conclusions Available agricultural land is a diminishing and constraining resource. Human-land relations are critically linked to demography, health, economic sustainability, and environmental/climate change Space (scale) and place matter! Future research may usefully consider the concept of shifting places of vulnerability and climate front-lines and climate- health-migration linkages. Coupled migration-health transitions remain a missing link in environmental change and climate adaptation science and policy The environment and climate change remain a missing link in migration-health research. Opportunities abound in collaboration!
VariableDescriptionMean Standard Deviation AnemiaCluster anemia measure (rank 1 to 4) StuntingCluster stunting measure (height/age std. deviations) UnderweightCluster underweight measure (weight/age std. deviations) Age of HeadCluster average of age of household head (years) CEBChildren ever born per mother in cluster WealthAverage cluster household wealth (based on index from poorest to richest, 1 to 5) Age of ChildAverage age of children in cluster (months) Unprotected WellPercent of cluster using an unprotected well for drinking water Table 2. Global cluster descriptive statistics for model input variables.
PPET and Livelihoods Results Mali’s climate transitions significantly, providing a wide variety of livelihoods – All livelihoods are dependent on the Niger River and its inland delta for water
Malnutrition Results To test if the climatic health effects found in the first set of models was entirely explained by livelihoods, the all cluster climate models were re-run to include both PPET < -100 and the significant livelihoods for each health outcome. The following table shows only the PPET < -100 and livelihood results.