The association between heat exposure and hospitalization for undernutrition in Brazil during 2000−2015: A nationwide case-crossover study

K Maleta, 2006, Undernutrition, Malawi Med J, 18, 189

M Ezzati, 2017, Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults, Lancet, 390, 2627, 10.1016/S0140-6736(17)32129-3

World Health Organization, 2018, 2018 global nutrition report, 10.30875/8f945017-en

RE Black, 2013, Maternal and child undernutrition and overweight in low-income and middle-income countries, Lancet, 382, 427, 10.1016/S0140-6736(13)60937-X

BA Swinburn, 2019, The global syndemic of obesity, undernutrition, and climate change: the Lancet Commission report, Lancet, 393, 791, 10.1016/S0140-6736(18)32822-8

N Watts, 2015, Health and climate change: policy responses to protect public health, Lancet, 386, 1861, 10.1016/S0140-6736(15)60854-6

N Watts, 2018, The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health, Lancet, 391, 581, 10.1016/S0140-6736(17)32464-9

SJ Lloyd, 2011, Climate change, crop yields, and undernutrition: development of a model to quantify the impact of climate scenarios on child undernutrition, Environ Health Perspect, 119, 1817, 10.1289/ehp.1003311

RK Phalkey, 2015, Systematic review of current efforts to quantify the impacts of climate change on undernutrition, Proc Natl Acad Sci U S A, 112, E4522, 10.1073/pnas.1409769112

SS Myers, 2017, Climate change and global food systems: potential impacts on food security and undernutrition, Annu Rev Public Health, 38, 259, 10.1146/annurev-publhealth-031816-044356

EI Benchimol, 2015, The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement, PLoS Med, 12, e1001885, 10.1371/journal.pmed.1001885

Q Zhao, 2019, The association between heatwaves and risk of hospitalization in Brazil: a nationwide time series study between 2000 and 2015, PLoS Med, 16, e1002753, 10.1371/journal.pmed.1002753

Q Zhao, 2019, Geographic, demographic, and temporal variations in the association between heat exposure and hospitalization in Brazil: a nationwide study between 2000 and 2015, Environ Health Perspect, 127, 17001, 10.1289/EHP3889

AC Xavier, 2016, Daily gridded meteorological variables in Brazil (1980–2013), Int J Climatol, 36, 2644, 10.1002/joc.4518

D Levy, 2001, A case-crossover analysis of particulate matter air pollution and out-of-hospital primary cardiac arrest, Epidemiology, 12, 193, 10.1097/00001648-200103000-00011

S Li, 2016, Acute impact of hourly ambient air pollution on preterm birth, Environ Health Perspect, 124, 1623, 10.1289/EHP200

H Janes, 2005, Case-crossover analyses of air pollution exposure data—referent selection strategies and their implications for bias, Epidemiology, 16, 717, 10.1097/01.ede.0000181315.18836.9d

X Wang, 2019, Eliminating systematic bias from case-crossover designs, Stat Methods Med Res, 28, 3100, 10.1177/0962280218797145

AG Barnett, 2010, Analysing seasonal health data, 10.1007/978-3-642-10748-1

MA Mittleman, 2005, Optimal referent selection strategies in case-crossover studies—a settled issue, Epidemiology, 16, 715, 10.1097/01.ede.0000183170.92955.25

Q Zhao, 2019, Temperature variability and hospitalization for ischaemic heart disease in Brazil: a nationwide case-crossover study during 2000–2015, Sci Total Environ, 664, 707, 10.1016/j.scitotenv.2019.02.066

NE Breslow, 1978, Estimation of multiple relative risk functions in matched case-control studies, Am J Epidemiol, 108, 299, 10.1093/oxfordjournals.aje.a112623

A. Gasparrini, 2011, Distributed lag linear and non-linear models in R: the package dlnm, J Stat Softw, 43, 1, 10.18637/jss.v043.i08

Y. Guo, 2017, Hourly associations between heat and ambulance calls, Environ Pollut, 220, 1424, 10.1016/j.envpol.2016.10.091

ST Buckland, 1997, Model selection: an integral part of inference, Biometrics, 53, 603, 10.2307/2533961

M Borenstein, 2010, A basic introduction to fixed-effect and random-effects models for meta-analysis, Res Synth Methods, 1, 97, 10.1002/jrsm.12

A Gasparrini, 2014, Attributable risk from distributed lag models, BMC Med Res Methodol, 14, 55, 10.1186/1471-2288-14-55

K Hu, 2018, Mortality burden attributable to PM1 in Zhejiang province, China, Environ Int, 121, 515, 10.1016/j.envint.2018.09.033

P. Mason, 2006, Under nutrition in hospital, Hospital Pharmacist, 13, 353

C Morral-Puigmal, 2018, Weather and gastrointestinal disease in Spain: a retrospective time series regression study, Environ Int, 121, 649, 10.1016/j.envint.2018.10.003

I Fellows, 1985, The effect of undernutrition on thermoregulation in the elderly, Clin Sci, 69, 525, 10.1042/cs0690525

GC Roman, 2013, Nutritional disorders in tropical neurology, Handb Clin Neurol, 114, 381, 10.1016/B978-0-444-53490-3.00030-3

SE Smith, 2013, Protein-energy malnutrition induces an aberrant acute-phase response and modifies the circadian rhythm of core temperature, Appl Physiol Nutr Metab, 38, 844, 10.1139/apnm-2012-0420

S Hajat, 2010, Health effects of hot weather: from awareness of risk factors to effective health protection, Lancet, 375, 856, 10.1016/S0140-6736(09)61711-6

MA Cuevas, 2017, Fiscal challenges of population aging in Brazil, 10.5089/9781475595550.001

K Hu, 2019, Evidence for urban–rural disparity in temperature–mortality relationships in Zhejiang Province, China, Environ Health Perspect, 127, 037001, 10.1289/EHP3556

The Brazil Business, 2019, Brazilian regionsThe Brazil Business

M Springmann, 2016, Global and regional health effects of future food production under climate change: a modelling study, Lancet, 387, 1937, 10.1016/S0140-6736(15)01156-3

BG Armstrong, 1998, Effect of measurement error on epidemiological studies of environmental and occupational exposures, Occup Environ Med, 55, 651, 10.1136/oem.55.10.651

DR Hyslop, 2001, Bias from classical and other forms of measurement error, J Bus Econ Stat, 19, 475, 10.1198/07350010152596727

JP Buckley, 2014, Does air pollution confound studies of temperature?, Epidemiology, 25, 242, 10.1097/EDE.0000000000000051

A Gasparrini, 2015, Mortality risk attributable to high and low ambient temperature: a multicountry observational study, Lancet, 386, 369, 10.1016/S0140-6736(14)62114-0

YH Li, 2014, Association between high temperature and mortality in metropolitan areas of four cities in various climatic zones in China: a time-series study, Environ Health, 13, 65, 10.1186/1476-069X-13-65