Methods:
The ecological study design was used as aggregated data on climate change were used in the study. The study conducted complementary quantitative analyses. This paper will discuss the quantitative part of the study that was based on time series analysis, the additive model and smoothed using the moving aver- age to determine the trend of climate, malnutrition and crop production. 
Findings:
The study found evidence of seasonality in the climate variables, but there was no statistically significant fluctuations in the trends of minimum and maximum temperatures and humidity. However, there were fluctuations shown in average total rainfall. High rainfall periods in 2012 coincided with an active La Nina and episodes of floods. The general trend of total rainfall shows that Fiji is getting drier.
There was seasonality found in child malnutrition where there was an increase in cases during the wet and hot summer season (November-April) and decrease in cases in the cold, dry winter season (May-September). The trend showed the prevalence of the indicators of malnutrition (underweight, growth faltering, severe malnutrition and anaemia) decreased in the first half of 2011 increased from the middle of 2011 to its highest peak in the first quarter of 2012 and decreased from the third quarter of 2012 until 2013. The extreme weather events (episodes of flooding) caused by La Nina and a tropical disturbance in the first quarter of 2012 exacerbated the prevalence of malnutrition.
The effects of climate change such as episodes of flooding exacerbate the prevalence of malnutrition in Fiji. Climate change, through the increase in the intensity and the frequency of extreme weather events will be more severe in the future. The limitations in the data for malnutrition and the changing classification limited the expanding of the timeline for the study to be more than 10 years to determine the relationship between climate change and malnutrition.  This study has shown the patterns of howindividual climate variables and malnutrition classification behave, and how the two variablesbehave together. The study will lay a platform for a more detailed study of the precise relation-ship between malnutrition climate change in the future where a Poisson process or a negativebinomial regression will be used.