AUTHOR=Oluwole Olusegun Steven TITLE=El Niño-southern oscillations and lathyrism epidemics JOURNAL=Frontiers in Environmental Science VOLUME=3 YEAR=2015 URL=https://www.frontiersin.org/articles/10.3389/fenvs.2015.00060 DOI=10.3389/fenvs.2015.00060 ISSN=2296-665X ABSTRACT=Epidemics of lathyrism, a neurological syndrome of spastic paraparesis, have occurred during severe droughts in Europe, Asia, and Africa for millenia. Causation is linked to exposure to β-N-oxalyl-L-α,β-diaminopropionic acid (β-L-ODAP), a neurotoxin in Lathyrus sativus. Lathyrism shares neurological features with konzo, a syndrome of predominantly spastic paraparesis which occurs during droughts in East and Central Africa and is linked to El Niño activity. This study was done to determine the relationship of lathyrism epidemics to phases of El Niño-southern oscillation (ENSO) and Pacific decadal oscillation (PDO), and to propose a model to explain why the geospatial distributions of lathyrism and konzo are non-overlapping. Contingency table of phases of ENSO and occurrence of lathyrism epidemics in Central Provinces, India from 1833–1902 was created and odds ratio was calculated. Wavelet spectra of time series of annual occurrence of lathyrism in Rewah district, India, and its coherence with ENSO and PDO from 1894 to 1920 were performed. Lathyrism epidemic was associated with El Niño phase of ENSO, odds ratio 378 (95% 32–4475). Global spectra showed peaks at periodicities of 2.5 and 4.6 years for lathyrism; 2.7 and 5.0 years for PDO; and 2.5, 4.6, 7.0 years for ENSO. Spectrograms showed time-varying periodicities of 2.5–3.5 and 4.5–5.5 years for lathyrism; 2.0–3.0 and 6.5–9.0 years for ENSO; and 3.5 and 5.0 years for PDO, p < 0.0001. Spectral coherence were at 2.0–3.5 and 4.5–5.0 years for ENSO and lathyrism p < 0.0001, and 5.0 years for PDO and lathyrism p < 0.05. The droughts of El Niños initiate dependence on Lathyrus sativus, which exposes the population to neurotoxic β-L-ODAP. Public health control of lathyrism epidemics should include development of models to forecast El Niños and initiate food programmes in susceptible areas.