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\begin{document}

\title{A Quantitative Study on Climate Variability and Malnutrition in Fiji.~}



\author[1]{Vakaruru Cavuilati}%
\author[1]{Arindam Basu}%
\affil[1]{University of Canterbury}%


\vspace{-1em}



  
  \date{May 07, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Climate change has a significant effect on human health manifested by
the increasing number of cases of climate-sensitive diseases. Europe and
North America have experienced increasing number of deaths from heat
waves, while in the Pacific there have been frequent outbreaks of
dengue, leptospirosis, diarrhoea and typhoid. Climate change
manifestation through extreme weather events have caused substantial
loss of infrastructure and also the agricultural sector in Fiji which
has increased the risk of malnutrition in the country.

\textbf{Purpose:~}

This study aims to examine the relationship between climate variability
and the prevalence of malnutrition in Fiji between January 2006 and
December 2016. The study also examines the specific aspects of climate
variability and malnutrition during the same period.%
\end{abstract}%



\sloppy


\textbf{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.~

\textbf{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.~ \textbf{} 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.
\textbf{}

\section*{Introduction~}

{\label{556262}}

~The increase in global temperature has affected the global climatic
system and subsequently impacted the natural environment and its
inhabitants. The 5th Assessment Report of the intergovernmental panel on
climate change (IPCC) reported that climate change is unequivocal since
the 1950's and the world continues to warm through the
decades~\citep{RN1260}. Climate change is the change in average
weather over an extended period such as decades or millenniums.~ The
United Nations Framework Convention on Climate Change (UNFCCC) defines
climate change as ``the direct and indirect impacts of human activities
altering the global composition of the atmosphere in addition to the
natural climate variability over specified time ''~\citep{Pachauri2014}.
The Intergovernmental Panel on Climate Change (IPCC) defines climate
change as climate determined by statistical analysis, which is the
changes in means and properties that prolonged over time, usually in
decades or more~\cite{Pachauri2014}. Scientists can trace back past
climates using the natural resources in the environment. Paleoclimate is
the study of climate before the use of monitoring equipment. Tree rings
are precise measurements as it contains dated information about the
previous environment~\cite{RN1281}. Corals also provide information
on the past climate variability of the tropical and subtropical
oceans\citep{RN4870}. Climate change is said to be caused by
internal and external factors. External factors cause the variations in
solar energy reaching the earth caused sunspots on the sun. The little
ice age of the 17th century, when the world was unusually cold
correlated with a few sunspots~\cite{RN4708}. Discovered in the
early 20th century Milankovich cycle is the varying of the earth and the
sun geometry over time, and it has three effects. The eccentricity which
occurs every 100,000 years cause's solar irradiance to vary between
seasons, a tilt which occurs every 41,000 years and precession
influences heat distribution between latitudes and play essential roles
in the triggering of the ice ages when radiation is reaching the higher
latitudes. The tilting of the poles towards and away from the sun varies
and has a direct effect on the temperature and the seasons on the
planet\cite{RN1301,RN194,RN4698}.~ The IPCC glossary defines anthropogenic
climate change is when humans interfere with the natural gases in the
atmosphere which in turn influences the change in average weather and
climatic conditions~\citep{Pachauri2014}. The former United States
President, Mr Barack Obama claimed that ``climate change is the most
important threat to humanity in this century''~ during the Climate
Summit in New York in 2014\citep{RN195}.~

~Climate change is a threat to human health. Climate change challenges
the basic health and human rights necessities which is proper shelter,
clean air and water and adequate supply of nutritious food
~\cite{RN4671}. The density of the population, economic status,
existing environmental conditions, and accessibility to quality health
services will determine the level of vulnerability~\cite{RN1283}.
Climate change increases the likelihood of crop failures leading to food
shortages and increasing the risk of malnutrition in countries that are
dependent on agriculture to supply food to their citizens. Climate
change will affect food availability through direct effects, the
variation in rainfall causes either floods or droughts, the variation in
temperature modifies the length of the crop growing
seasons~\cite{RN159}.

The variation in rainfall caused by climate change will have an effect
on crop productions in the Pacific. The rising temperatures, climate
variabilities such as El Nino and La Nina conditions, sea level rise and
more intense cyclones also affect the agriculture sector. Many of the
rural dwellers in the Pacific still rely on locally grown food as their
main staple diet. Most of these crops are dependent on rains in the
summer (November to April), so the crops are dependent on rainfall.
Climate projections for the region are variations in total rainfall
which would be catastrophic to the crops~\cite{RN4834}.~ The South
Pacific Regional Environment Program (SPREP) warned Fiji that if it
ignores the possible effects of climate change, which include increased
vector-borne disease and increased malnutrition due to food shortages
during extreme weather events, it will lose US \$5 -19 million by
2050~\cite{RN489}.The United Nations Children Education Fund
(UNICEF) defines malnutrition as " when the body does not get the proper
amount of energy (calories), proteins, carbohydrates, fats, vitamins,
minerals and other nutrients required to keep the organs and tissues
healthy and functioning well''\cite{RN1334}. The World Health
Organisation classifies malnutrition into three categories,
undernutrition which includes wasting (low weight for height), stunting
(low height for age), and underweight which is a low weight for age.
Micronutrient malnutrition which is either lack of or excess of specific
nutrients in the body and overnutrition which is excess nutrients in the
body causing overweight and obesity are the other types of
malnutrition\cite{RN4687}.~ Malnutrition is a complex illness
caused by several factors, and to be able to prevent or minimise it,
adequate and nutritious food must be considered~\cite{RN4774}. The
importance of the study is to determine that the effects of climate
change which is the increase in temperature, variation in rainfall and
the frequency of extreme weather due to that variation are one of the
contributing factors to the prevalence of malnutrition in Fiji.~ The
Fijian Ministry of Health website\cite{RN4836} reported that
malnutrition is the number one childhood killer in the country, this is
an alarming statement coming from the health ministry. Fiji has the
abundance of fresh fruits, vegetables, root crops, marine and aquatic
food and yet reports of malnutrition and fatalities caused by
malnutrition are still happening. The United Nations Food and
Agriculture Organisation issued a statement in the media that
malnutrition was prevalent in Fiji was caused by shortages of
vegetables, four months after category five~\emph{Cyclone Winston} hit
Fiji in February of 2016\cite{RN4869}.~ Research on the
relationship between climate change and malnutrition were conducted in
Africa and Asia, and there has never been any similar kind of study
conducted in Fiji.~ This is one of the first studies of its kind in
investigating the association between climate-related variables and the
prevalence of malnutrition in Fiji.

\section*{Methods}

{\label{103227}}

\begin{quote}
\begin{quote}
\end{quote}
\end{quote}

The design is that of an ecological study.~ Secondary data collection
was used to obtain the dataset for malnutrition indicators, climate
variables and the other covariates in the study. Climate variables were
collected for the period between 1st January 2009 and 31st December
2016.~~These are the monthly averaged maximum temperature,~ the monthly
averaged minimum temperature, the monthly averaged total rainfall and
the monthly averaged humidity. In this study, the predictor variables
were the indicators of climate change ("minimum, maximum, and average
monthly temperature'`, "minimum, maximum, and average monthly
rainfall'`, "and average humidity''). The response variable was the
prevalence of malnutrition (underweight children, growth faltering,
severe malnutrition, and anaemia). Ethics approval was obtained from the
Ministry of Health Ethics committee and the UC Human Ethics Committee.

\subsection*{Climate Data}

{\label{155488}}

Climate data were extracted from the Fiji Meteorological Service (FMS)
for the years January 2006 to December 2016. The FMS database had the
average monthly maximum temperature,average monthly minimum temperature,
the average monthly humidity and the average monthly total rainfall. The
weather monitoring stations are located in the four divisions of Fiji
and provide a representative reading of the climate variables for the
country. The FMS has given the monthly readings as the average of the
monthly readings. The monthly recordings of maximum, minimum
temperature, total rainfall and relative humidity for each of the
stations were grouped together on a spreadsheet The columns had the
climate variables and the months and the rows had theweather stations.
The average of the monthly climate readings from the nine weather
stations was the reading for Fiji. ~

\subsection*{Malnutrition Data}

{\label{767515}}

Malnutrition was classified by the Fijian Ministry of Health as
underweight, growth faltering, severe malnutrition and anaemia.~ The
malnutrition data for the years between 2006 and 2008~was excluded from
the study because it had different classifications compared with
malnutrition data for the years 2009 through 2016. The new
classifications for malnutrition are mildly underweight, moderately
underweight and severe underweightbased on the consolidated monthly
return format. ~ The Fijian Ministry of Health has been using the
National Center for Health Statistics (``NCHS'') definitions until 2008,
where malnutrition was classified as mild, moderate and severe
underweight as low weight.~ The malnutrition counts include underweight,
growth faltering, severe malnutrition and anaemia. The researcher
created a separate dataset because the raw data for growth faltering,
severe malnutrition and anaemia was only available from 2009 to 2016.
The dataset for 2006 to 2008 has only raw counts of mild, moderate and
severe underweight as their classifications.~ \textbf{\textbf{~}}

\subsection*{Quantitative}

{\label{546423}}

~\textbf{~The researcher conducted time series analysis to describe the
trend of the climate variables using the dataset created where only the
readings of each of the climate variables were on the spreadsheet. A
time series analysis is a sequence of data points recorded at different
time points. It is commonly used when there are 50 or more data points
in the series, and when considering seasonality, there should be at
least 4 or 5 cycles in the data. Time series data have a natural
ordering, such as the days, months, quarters, years and so forth which
makes it distinct from cross-sectional studies. Time series data can be
either stationary or non-stationary. A stationary time series are those
whose properties such as mean, variance and autocorrelation are all
constant over time and a non-stationary time series is a series where
its properties change over time.} Data was cleaned with the Open Refine
software and exported to the R Studio software for analysis. Step one of
analysis is descriptive analysis, hence the construction of a table for
climate variables (average maximum and minimum temperature, average
rainfall and average humidity). The table had in the header the number
of months, median, mean, standard deviations and the percentiles which
were calculated using the R Studio software. The R studio software was
used to construct bar plots for the average maximum and the average
maximum monthly temperatures, the average monthly rainfall and the
average monthly humidity to determine how the climate variables behaved
over the ten year period. Each of the bar plots represented the months
the data was collected, and it was placed on the x-axis and the y-axis
showed the readings for the climate variables. The trend of the climate
variables was established using the~dataset that was created where only
the readings of each of the climate variables were recorded on the
spreadsheet. Once it was transferred to the R Studio software it was
then converted into time series data using the~\emph{ts} function from
the~\emph{tseries} library. The frequency was set at 12 since the data
were collected on a monthly basis and the first input was identified as
2006 as this was the time of the first recording. The association
between climate variables (that is, minimum temperature, maximum
temperature, average humidity, and average rainfall) and malnutrition
(underweight, severe malnutrition, and anaemia) were modelled using a
generalised additive model (GAM) using autoregressive integrated over
moving averages (ARIMA) as Poisson process.

\par\null

\section*{Findings}

{\label{292051}}

The study found the trend of the average monthly maximum and minimum
temperatures and average monthly relative humidity did not show any
variations from January 2006 to December 2016. However, there were
variations in the level of monthly average rainfall for the same period.

\par\null\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/trend-of-max-temp/trend-of-max-temp}
\caption{{The trend of the monthly average maximum temperature from January 2006
to December 2016. There was not much variation in the maximum
temperature during the ten year period.~
{\label{801872}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/trend-of-rainfall/trend-of-rainfall}
\caption{{The trend of total rainfall shows variation in rainfall from January
2006 to December 2016. There were high rainfall peaks in 2007, 2008 and
in 2012.~
{\label{995744}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/trend-of-humidity/trend-of-humidity}
\caption{{The humidity trend from January 2006 to December 2016 did not show much
variation
{\label{399676}}%
}}
\end{center}
\end{figure}

The study also found trends of malnutrition (underweight, growth
faltering, severe malnutrition and anaemia) were decreasing from the
beginning of 2011 and then made a steep increase in the second half of
the year. The increase continued into the second quarter of 2012, and
then it decreased into 2013. The study will look into detail on the
trends of malnutrition in 2011, 2012 and 2013 because these are the
years where there were unusual patterns from the usual trend. The
prevalence of indicators of malnutrition (underweight, growth faltering,
severe malnutrition and anaemia) was high in the Fiji Indians as
compared to the I- Taukei and the other races. Crop productions for Fiji
decreased in the second half of 2011 and the first half of 2012.\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/underweight/underweight}
\caption{{The trend of underweight shows the underweight decreases to its lowest
end in 2011 and then increases at the end of 2011 to the middle of 2012.
The trend then decreases in the middle of 2012 into 2013.~
{\label{786186}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/gf/gf}
\caption{{The trend of growth faltering was at its highest in 2010 and then it
decreased from the second half of 2010 into 2011. It increased at the
end of 2011 into the first quarter of 2012 before decreasing in 2013.~
{\label{358332}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/severe-mal/severe-mal}
\caption{{The trend of the severe malnutrition indicated that the trend was
decreasing in 2011 and at the end of 2011 it increased steadily to its
peak in mid 2012. The trend then decreased from the second half of 2012
to the end of 2013.~
{\label{559734}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/anaemia1/anaemia1}
\caption{{The trend of anaemia shows that it was slowly increasing from 2010 to
the middle of 2011 where it increased into 2012 and the first quarter of
2013 before decreasing into 2014.~
{\label{403385}}%
}}
\end{center}
\end{figure}



\section*{Discussion}

{\label{927862}}

There is not much variation in the seasonal fluctuation of the average
maximum and the minimum temperature for Fiji during the study period.
The pattern would show clear evidence of climate change if the study
range were at least thirty years to see any changes to the temperature.
The temperature trend confirms the findings of the temperature in the
Pacific is gradually increasing, but over a more extended period. The
average temperature increase across the Pacific is only 0.9 degrees for
the last 60 years from 1961 to 2011, and the average increase for Fiji
was 0.25 degrees Celsius during this period~\cite{RN4738}. It shows
that the temperature is increasing, but is not seen in a short time span
of ten years but over a longer time span.

The rainfall trend was at its peak during parts of 2007, 2008 and twice
in 2012. The rainfall trend peaks were consistent with the La Nina cycle
occurring in the same period. There were robust La Nina recorded for the
2007/2008 season and also a moderate La Nina for the 20011/2012
season~\citep{RN4828}.~ The humidity trend for the study period is
similar to the maximum and the minimum temperatures. It was strange as
increase humidity was expected due to the high rainfall levels recorded
during the study period.

In 2011 the average maximum and minimum temperature were stationary, the
rainfall levels increased in the first half of the year and decreased in
the second half, and the trend remained stagnant. However, all the
indicator of malnutrition (underweight, growth faltering, severe
malnutrition and anaemia) were decreasing in the first half of the year
and increased sharply in the second half of the year. Therefore there is
very little evidence to suggest that the decrease in the prevalence of
malnutrition is related to whether or climate variables. In the 2011
Budget address, the Finance Minister announced that in 2010 government
for the first time in Fiji's history was introducing food vouchers to
those on the welfare scheme which included single mothers without
employment, widows, and the
elderly~\cite{RN4844}.~\citep{RN4845} in their study stated
that many of the developing countries are establishing food safety nets
through the food assistance programs (FAP) to those at risk of
malnutrition and global estimates by the World Bank state that 115
million people annually benefit from food assistance programs. In the
2011 budget announcement, additional funds were added to the nation
employment centre to train and mobilise five hundred Fijians into the
workforce~\cite{RN4844}. The continued funding to the centre
signifies that the centre was achieving its aims and objectives in
preparing Fijians for employment and could be one of the reasons for the
increase in employment in 2011. In 2011 the Fiji Bureau of Statistics
recorded that the number of people with employment increased as compared
to the previous year. The number of waged earners employed increased by
979 and the number of salaried workers increased by
3972~\cite{RN4769}. A study by~\citep{RN4711} in urban Africa
noted that wasting in children is influenced by the monthly financial
status of the family.~~\citep{RN4848} stated that better income at
the household level leads to families spending more on food, paying for
adequate and wholesome water supply and good health care. However, they
argued that income growth alone not be strong enough to reduce
malnutrition, as there are other avenues such as nutritional programs,
micronutrients supplements and community behaviour change
scheme.~\citep{RN4772} conducted a study from twelve countries on
household consumption and GDP with child malnutrition and found that at
household levels and the cross country continued growth leads to the
reduction in malnutrition.~ It projected that countries with a growth
rate of 2.5\% per year could reduce malnutrition (low weight for age) by
27\%. These are the social factors that contributed to the decrease in
malnutrition trend during the first half of 2011.~

In 2011, the prevalence trend of indicators of malnutrition started to
increase rapidly towards the end of the year. As similar to above no
unusual weather or climate patterns were happening to indicate the
sudden increase in malnutrition. In 2011 the Fijian GDP decreased by
0.3\%~\cite{RN1355}, even though it is a small decrease it has an
effect on the economy and trickles down to the household level. As
stated by~\citep{RN4772} growth rate is vital in reducing
malnutrition especially for low weight for age classified as underweight
in this study. The Fijian government also increased Value Added Tax from
12.5\% to 15\% in 2011, an increase of 2.5\%\cite{RN4844}. The
increase in VAT lead to the increase in most of the food items consumed
by Fijians. The Consumer Council of Fiji released a media statement in
August of 2011 stating that food prices continue to increase in Fiji.
The price for essential food items such as sugar and butter increased by
18\% and 52.1\% respectively.~ The cost of sugar increased due to the
lack of supply from Fiji Sugar Corporation who is now importing sugar
from Thailand to meet the demand. The Consumer Council also highlighted
in October of 2011, that liquid milk was out of stock in most of the
major supermarkets, and they were calling on the suppliers to meet the
public demand as most of the milk in Fiji is
imported\cite{RN4851,RN4850}. The results of a study
by~\citep{RN796} on child malnutrition and spikes in food prices
in India between 2006 to 2009 revealed that food consumption of children
reduced significantly across the entire population. There were
variations across the different income groups, but nutritional risks
were more amongst low-income children.~ Sudden food price increases make
it difficult for families to adjust, crumbling their purchasing power,
minimising their calorie and nutritional intake and it is driving more
people into hunger~\citep{RN4856}. The high food prices increase
the risk of hidden hunger a term used to people suffering from
micronutrient deficiency as it usually takes time and shows when it is
severe. Hidden hunger happens when people do not have access to
micronutrient-rich foods, fruits, vegetables, meat which are either
expensive to purchase or are not available locally~\cite{RN4856}.

In 2012 the prevalence of the indicators of malnutrition (underweight,
growth faltering, severe malnutrition and anaemia) continued to increase
until the middle of the year and then it came down to 2013, where it
decreased further or became stagnant for some of this indicators. Our
findings showed that rainfall trend was high between 2007 and 2008 and
in 2012. High rainfall occurred at the beginning of the year during the
rainy season, but these peaks were above average rainfall levels. A
strong La Nina occurred between 2007 and 2008 and a moderate La Nina in
2012 which are responsible for the above average rainfalls. As a result,
two significant floods affected Fiji in the first quarter of 2012. The
first floods occurred from 21st January to 12th February affecting the
western parts of the main island. The flood caused significant damages
to the affected areas of more than 178,000 people and costing the Fijian
government FJ \$50.4 million~\cite{RN4814}. A tropical depression
TD17F caused the second flooding in the early hours of the 30th March
also affecting the western parts of the main island. It was the second
flood to hit this area in less than a month. The floods affected 150,000
people including 3,000 farmers, the costs of damages were FJ \$71.2
million dollars~\cite{RN4815}. The prevalence of the indicators of
malnutrition (underweight, severe malnutrition and anaemia) were the
highest recorded in 2012 than at any time during the study period. Our
study findings showed that the increase in the prevalence of indicators
of malnutrition (underweight, severe malnutrition and anaemia) was
compounded by episodes high rainfall and flooding replicates the
findings of~\citep{RN4796} that there was a significant
relationship between seasonal rainfall and child stunting.~ It also
supported~\citep{RN4793} findings that children exposed to two
floods are three times more likely to be severely wasted than children
not exposed to floods and twice more likely than those exposed to only
one flood.~\cite{RN626} in their study on the effect of weather
variables on child, undernutrition found that variation in rainfall
increases moderate stunting in different geographical zones of Ethiopia.
The warming of the world due to anthropogenic climate change has caused
much variability in the weather, and the increasing temperature is
increasing the intensity of extreme weather events such as rainfall and
cyclones. The second flooding was due to a tropical depression confirms
to the study by~\citep{RN4837,RN4838} that warming will intensify rainfall
events associated with cyclones. The Fijian newspapers were publishing
stories of flooded and damaged roads in the main centres and also in the
rural areas, making it inaccessible.~ The Nadi International Airport was
closed for four days due to the inaccessibility of the roads as tourists
cannot access their hotel due to the severity of the
flood~\cite{RN4858}. Accessibility is essential as it connected
people to relief and to medical service which is essential to the health
of the vulnerable population which includes children, the elderly and
the disabled. Studies conducted in Jamaica and Iran showed that the
availability and the accessibility of medical facilities to mothers and
children significantly dropped malnutrition~\cite{RN1,RN4713}

In the second half of 2012, the prevalence of indicators of malnutrition
(underweight, growth faltering, severe malnutrition and anaemia)
decreased at almost the same rate of increase at the beginning of the
year. The prevalence of malnutrition decreased subsequently after the
disaster.~ The collaboration and partnership of international aid, the
private sector, NGO's and civil society working together in the relief
efforts was one of the reasons for the sudden decline in malnutrition.
Australia, New Zealand and other countries assisted in the relief
efforts and supported the mechanism on the ground to efficiently carry
out the relief efforts. The government also waived two months land
rentals on all crown leases~\cite{RN4814}.~ The~ Ministry of
Agriculture distributed seedlings, cuttings and assisted in the land
preparation and the government has distributed more than FJ \$1 million
in food rations both the floods~\cite{RN4860}. The prevalence of
malnutrition after floods in Bangladesh is similar to Fiji as it also
subsequent decreases after the floods. They requested assistance from
the IMF and adjusted the economy, and they made food, drinking water,
medicines and shelter available to the poor~\citep{RN4859}.~ The
government also increased funding to the WAF to improve and provide safe
and consistent water supply to the Fijian people~\cite{RN4861}. A
study in Brazil by~\citep{RN4716} found that having access to piped
water supply reduced the risk of stunting.~\citep{RN1363} in their
study after adjusting for confounder has found that water and sanitation
are significantly associated with stunting. \citep{RN1361} found
that children living in homes with adequate water and sanitation had
17\% more chances of improved stunting than those living without it.

\par\null

In 2013 the prevalence of underweight, growth faltering and severe
malnutrition decreased and became stagnant while the prevalence of
anaemia started to decrease. The decrease in malnutrition in 2013, is
that the country's Gross Domestic Product (GDP) has increased by 2.5\%
in 2013 ~\cite{RN4769}.~\citep{RN4865} found that the
prevalence of underweight in children and the growth in the GDP is
compelling than for stunting, where a 10\% growth in GDP will have~7\%
decrease in underweight. The growth in the GDP on nutrition is a
combination of improved household resources, better infrastructure, and
better nutrition services. However, anaemia decreases at a measured rate
where the 10\% growth in GDP will only have a decrease in child anaemia
by 2.4\%. The government in 2013 introduced the national pension scheme
where people above 70 years receive monthly pensions. The introduction
of the poverty benefit scheme, where a maximum of four people in the
same household can receive assistance and food voucher. The government
introduced the care and protection allowance for single mothers,
deserted spouses, widows and prisoners dependents~\cite{RN4866}.~
These are social protection programs introduced or supported by the
government through increased funding in 2013. According
to~\citep{RN4846} ~social protection programs are usually used to
target to improve the standard of living and not on nutrition, even
though the primary aim is minimising poverty it usually results in
enhanced food security, health and education.~

\par\null

The prevalence trends of underweight, growth faltering, severe
malnutrition and anaemia, in general, were showing that Fiji Indian
children were having high prevalence rate, followed by the I-Taukei
children and then the children of other races. The National Nutrition
Survey further discovers that the introduction of supplementary foods to
the two ethnic groups vary a lot. More Fiji Indian babies are given
additional foods before six months and from six months to two years more
supplementary foods are given to I-Taukei babies. Most of the Fiji
Indian babies are still given milk until 12 months and the reason given
is that milk is a customary diet in a Fiji Indian traditional diet and
not as an I-Taukei traditional diet~\cite{RN1193}. Nutritional
status differs in different ethnic groups due to dietary patterns,
lifestyle, cultural and religious beliefs and socio-economic
status~\citep{RN1340}. Dietary intake and an ethnic study conducted
in Malaysia found that differences in sociocultural in regards to food
preferences caused differences in their dietary
behaviour\citep{RN1342}. Fiji is a multi-ethnic country with the
majority of the population native Fijians called the I- Taukei and the
other dominant group are Fijians of Indian descents while the other
races are other Pacific Islanders, Asians, and other minority races.~

\par\null

\section*{Conclusion}

{\label{350957}}

Malnutrition is a complex and multidimensional health issue and there
are many factors that are associated with it. In this paper, climate
change is happening in Fiji but at a slower pace as seen in the
temperature trend. However, the slightest increase in temperature causes
variability to the already fragile climate due to the climate phenomenon
such as the South Pacific Convergence Zone, the El Nino Southern
Oscillation and the Intertropical Convergence Zone affecting the
Pacific. There is no clear linkage between the effect of climate change
on the prevalence of malnutrition in Fiji, as there are many social
factors that cause the increase and the decrease in malnutrition.
However, increase in rainfall intensity, frequency and episodes of
flooding due to climate change compounds the increasing prevalence of
malnutrition in Fiji.~

\par\null

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