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The impact of climate change-induced disasters on mental health in Isiolo County, Kenya


Peninah K. Mwenda
Daniel Olago
Fredrick Okatcha
Ali Adan Ali

Abstract

Isiolo County in Kenya is susceptible to the effects of extreme climate events and exposure to natural hazards, and the residents have limited capacity to adapt but also suffer from related mental health conditions that rarely researched. The modelling and projections of disease epidemiology caused by climate extreme events to foster climate-mental health initiative is insufficient. The methods of data collection used included: rainfall/temperature data derived from gridded 10km of sixteen satellite meteorological stations (1984-2013); mental disorders epidemiological data (2006-2014) from the health information system, Isiolo County and in-depth observation among 60 in-patients and 121 out-patient; six focused group discussion and workshop sessions among selected sample size (N=24); key informants (N=35) and household socio-economic survey (N=288) was conducted to gather socio-economic aspects of the target population.. The quantitative data was analysed using statistical tools in Excel, SPSS version 20 while rainfall and temperature analysis was done using R software (version 3.21) and ranked mental health data using diagnostic tools criteria. Correlation analysis was done to determine the varying trajectories of sets of bivariate data and positive correlation was noted between mental disorder cases and total annual rainfall. The prevalent mental disorders included: anxiety (54%); 32% each for dissociative, sleeping, and adjustment disorders; and 39% for eating and poly-substance disorder. The mental disorder comorbidity revealed the association to disaster risks which increase mental illnesses. The study found that the prevalence rate of mental disorders was high and resilience was low. A need to develop robust environmental health procedures to diagnose mental disorders and quantify the epidemiology caused by disaster risks is vital. The study recommends mapping of mental disorder epidemiology and make it user friendly to advice policy, scale up solutions and accelerate evidence informed advocacy on adaptation and resilience mental health programme strategies.


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