Impacts of
Displacement on Socio-economic status of Local Community in the Western
Ethiopia: Empirical Evidence from Survey Data
Gemechu Bekana Fufa
Assistant Professor of
Statistics, Department of Statistics, College of Natural and Computational
Science, Wollega University, Nekemte,
Ethiopia.
*Corresponding Author E-mail:
gemechu.bekana@yahoo.com
ABSTRACT:
This study was undertaken to
assess the socio-economic impact of displacement on the livelihoods of the
households, in western Ethiopia. The major objective of this study is to assess
the socio-economic impact of displacement on socio-economic status of local
community in terms of education, housing condition, living standard, health
condition and ability to finance. Random samples of 400 local communities were
selected using multistage random sampling from the study area. Comparisons were
made between displaced and displacers using the hypothesis testing. This study
defines displaced community as those who were not live in the normal residence
and displacers’ community those who were forced and fled the displaced people
from their normal residence. To assess the impact of displacement on the
educational status of the family, the ratio of children in schools to the total
number of school aged children in the family, expressed as percentage. The
ability of the household to feed the family was also seen in terms of the
frequency of feeding the children and the adult. It was found that
non-displaced community are better off than the displaced in terms of sending
children to school, housing conditions, health condition, probability of
survival for future life and ability to finance. The mean difference of family
members attending the school, in both displacers and displaced was not high,
shows that the displaced and displacers were affected as opposed to the general
opinion that the displaced people were highly affected. After all analysis, it
can be concluded that displacement of local community has high impacts on the
socioeconomic status of the households. The results also reveal that the
displaced communities were highly affected by communicable and non-communicable
diseases. Finally, the results were recommended as the government, heath
institution and non-displaced community should support the displaced community
and try to stop or reduce the displacement for further.
KEYWORDS: Displacement,
Community, Socioeconomic, Education, Western Ethiopia.
1.
INTRODUCTION:
1.1 Background Fo The Study:
Internally displaced persons
(IDPs) are persons or groups of persons who have been forced or obliged to flee
or to leave their homes or places of habitual residence, in particular as a
result of or in order to avoid the effects of armed conflict, situations of
generalized violence, violations of human rights or natural or human-made
disasters, and who have not crossed an internationally recognized State border
(1998, Guiding Principles on Internal Displacement). As of the end of 2018,
more than 20 thousand people were internally displaced by conflict and violence
across in Ethiopia.
There are four categories of
causes of internal displacement: natural disaster-induced displacement (NDID);
Man-made-disaster-induced displacement (MDID); Conflict-induced displacement
(CID); and Development-induced displacement (DID). Internal displacement in
Ethiopia has been predominantly characterized by spontaneous, short-term
displacement. Spontaneous movements of pastoral communities have been the
traditional form of internal and cross-border displacement. This study focused
on Conflict-induced Displacement (CID) (Edwards, A. (2016)).
Conflict-induced displacement
refers to people who are forced to leave their habitual place of residence as a
result of escalation of internal violence or internal armed conflict.
Conflict-related displacement includes displacement induced by international
and/or internal armed conflict, civil war, foreign occupation or intervention,
internal strife, communal or generalized violence and violent raids (Morel,
2013). An ethnic conflict was main cause for internal displacement in Ethiopia
(Taye D, (2018)).
Ethnic conflicts in Ethiopia
are not new, but the levels of violence taking place across the country are
rising, leading to increased displacement and humanitarian needs. There were a
lot of internal displacements of people in Ethiopia since 2016 – 2018 (SNNPR, 2018).
This includes, Somali – oromia, Gedeo
– Guji and Beneshangul gumuz - oromia were some of the
recent internal displacement in Ethiopia (OCHA, 2018).
Over 100,000 people fleeing
ethnic violence have been displaced in Benishangul-Gumuz
(mainly in Kamashi Zone) and Oromia regions (mainly
East Wollega and West Wollega
zones). There are indications that displacement is rising, though the size of
the displaced population is not clear. Urgent humanitarian needs are reported,
including food, shelter, non-food items and health (Ethiopia, 2018). Currently,
there are over 273,338 IDPs in 21woredas residing in the temporary shelter,
collective sites, and host community; 110,999 IDPs in East Wollega,
103,502 in West Wollega, 42,000 in Kamashi and 17,045 in Asossa zone
(NDRMC, 2019).
According to Ethiopian report
(NDRMC, 2019), the displaced people from beneshangul gumuz (Kemashi Zone) were
residing in East Wollega and West Wollega
Zones. According to west Wollega zone report (west wollega, 2019), the majority (95%) of the IDPs reside in
collective centers such as youth centers, multipurpose buildings, and temporary
shelters, while the remaining (5%) live with the host community either renting
or accommodated by friends and families. IDPs in collective centers and temporary
shelters are living in congested conditions; furthermore, lack of privacy,
exposure to weather, and absence of light in the sites are major concerns
mentioned by 63% of the interviewed individuals. Similarly, the report of West Wollega Zone (west wollega, 2019)
shows majority (90%) of the IDPs are settled in collective sites and the
remaining (10%) are living with the host community either renting or
accommodated by families and friends.
1.2 Statement of
problems:
Internal displacement is a problem
for the country and has high impacts on households’ living standard (Randell,
(2016)). Different studies were discussed on the internal displacement in
Ethiopia. Taye D, (2018) was conducted a study on “forced displacement: ethnic
Conflict in focus.” The result show that as the people were displaced from
their home land, they were affected by different problems like poverty, hung,
damage of properties, death of family members and loss of moral value. Ethnic
conflicts in Ethiopia are increasing from time to time since 2016 and affecting
the people in Ethiopia. This cause low development of economic growth,
suffering of people by hunger social disabled (OCHA, 2018).
The displaced people were loss
their properties, land, home and other food and non-food items. According to
Ethiopian report (NDRMC, 2019), the displaced people were supporting by local
community and government bodies. The people in the study area had been
prohibited to almost all sorts of socioeconomic services, the agricultural
products for both displaced and displacers were not collected and they couldn’t
move freely from place to place due to insecurity (Taye D, (2018)). To the best
of my knowledge, there has been no study undertaken on the impact of
displacement on socioeconomic status of the country. So, this study focuses on
the impact of displacement on socioeconomic status of local community in terms
of education, housing conditions, health condition, living standard and the
ability to finance in the family.
The main objective of this
study is to assess the impact of displacement on socioeconomic status of local
community in terms of basic needs for human and education. The
specifically, the objectives of this study are as follow:
·
To
assess the impact of displacement on displaced and displacers community in
terms of education.
·
To
analysis the housing conditions of the displaced and non-displaced households.
·
To
analysis the survival probability of displaced peoples.
·
To
compare the displaced and non-displaced of households in terms of living
standard and housing condition
2. DATA AND
METHODOLOGY:
2.1. Data Collection Methods:
This study was conducted in
western Ethiopia, in oromia and Beneshangul
gumuz regions, where the displacements of the people
were happened (kemash zone). The data were collected
from primary source using interview of the displaced and
non-displaced/displacers people, focus group of the people at the site,
observation and secondary source namely median, government and non-government
report. A number of participants are selected from target population
displacers, non-displaced and displaced people and 400 samples were selected in
to the study.
2.2. METHODS OF DATA
ANALYSIS:
The main objective of this
study was to assess the impact of displacement on socioeconomic status of local
community. To meet this objective, different comparisons were made between the
displaced and displacers. This study displaced peoples as those who were not
live in the normal residence (home land) and displacers’ people those who were
living at their normal residence and cases for the displacement. To assess the
impact of displacement on the educational status of the family, the researchers
were used the ratio of family members in schools and those who have attended
regular schools to the total number of school aged children in the family,
expressed as percentage.
Since a lot of the people lost
their life and displaced from their homes and properties. So, the probability
of survival of displaced people were depends on non-displaced, displaced
themselves, local community and government body. To analysis the
probability of survival of displaced people were seen as the function of
non-displaced (ND), displaced (DD), local community (LC) and government body
(GB). Similarly, the displaced people were lost their economy and social life
because of internal displacement. So, the socioeconomic status of the displaced
people also depends on the following relations: community-community (CC)
relation, community-government (CG) relation, community-economy (CE) relation
and community-social (CS) relations. Socioeconomic status of community were considered as binary outcome as economic and social.
The researcher classified the
households in the study area as four types of household displaced people
(DP), non-displaced people (non-DP), mixed displaced people
(wife displaced), and mixed displaced people (husband displaced) were
compared on a variety of household level, socio-economic measures: standard of
living and ability to provide housing for family members. First, the
household’s standard of living was measured as the respondent’s rating on a
four-level scale: good, average, poor, or very poor. Second, each household
reported its perceived ability to procure housing over the next time. The
ability to provide housing reflects the household standard of living. Finally,
we compared households by size o f house. To compare
the four household types further on these measures, we conducted logistic,
multinomial, and linear regression models that controlled for survey time,
number of household members, educational level, and gender and age of the head
of household.
The Z- test for the difference
between two population means:
Suppose that there are two
samples drawn independently from two populations with mean µ1 and µ2,
respectively. Then, the test about the significance of the difference between
the two means takes one of the following forms:
H0: µ1 - µ2
= 0 Vs H1
: µ1 - µ2 
(1)
OR
H0: µ1 - µ2
= 0 Vs H1 :
µ1 - µ2 
(2)
OR
H0: µ1 - µ2
= 0 Vs H1
: µ1 - µ2 <
0
(3)
Where, H0
and H1 stand for the null and alternative hypotheses,
respectively.
The test statistic is then
given by:
(4)
Where, n1 is sample
size from population1, n2 is sample size from population2, 
is the mean
of the sample taken from population1, 
is the mean
of the sample taken from population 2, 
is the
variance of the sample taken from population 1, 
is the
variance of the sample taken from population 2.
For a specified Type I error
α, the null hypothesis will be rejected if: |Z| > Zα/2,
for the first form; Z > Zα for the second form; and Z <
-Zα for the third form of the hypothesis. Rejecting the null
hypothesis means that there is a significant difference between the means of
the two groups.
The
Regression Analysis:
A linear regression equation
of the a dependent variable Y on k independent
variables X1, X2, …, Xk
is given by
Y = β0 +
β1X1 + β2X2 + …........ +
βkXk +
ε (5)
Where β1,
β2, …, βk are the slopes (the change in Y
for the unit change in the explanatory/independent variable Xi),
β0 is the value of Y when all explanatory/independent variables
assumes zero value ε is the random term. After fitting a linear regression model by estimating the
coefficients, we have to test whether the coefficients are statistically
significant. This can be done either by testing the overall significance of the
model or by testing the significance of the individual coefficients.
Logistic Regression Analysis:
Logistic regression is a
popular modeling approach when the dependent variable is dichotomous or
polytomous. This model allows one to predict the log odds of outcomes of a
dependent variable from a set of variables that may be continuous, discrete,
categorical, or a mix of any of these. Hosmer and Lemeshow
(2000) have described logistic regression focusing on its theoretical and
applied aspect. In this study, for identifying the determinants of inflation we
were compute a dichotomous variable indicating whether there is inflation or
Otherwise.
(6)
Where PS denotes population
status.
In logistic regression
analysis, it is assumed that the explanatory variables affect the response
through a suitable transformation of the probability of the success. This
transformation is a suitable link function of P, and is called the
logit-link, which is defined as:
Where β0,
β1, β2, ... βp are the
model parameters and X1, Xp
will the predictor/independent chosen variables. The transformed variable
denoted by logit (P) is the log-odds and is related to the explanatory
variables as in equation (7).
3. RESULTS AND
DISCUSSIONS:
3.1. The Impact of displacement on the Educational
Status of the family:
The percentage of family
members was taken to compare the educational statuses of the displaced and
displacers. The result shows that there are 227 displaced and 173
displacers having students in the school. The mean percentage of students who
attending the schools at the time of the survey was found to be 56.75% and
43.25% for the displacers and displaced, respectively as shown in table 3.1
below.
Table 3.1:
Comparison of the average percentage of family members who attending the school.
|
People classification |
Sample Size |
Mean |
Stand. deviation |
Percentage |
|
Displacers |
173 |
41.2 |
40.94 |
56.75% |
|
Displaced |
227 |
30.86 |
34.94 |
43.25% |
To test the significance of
this difference we used the one tailed test. The calculated Z calculated was
found to be Zc = -1.96. This value is less
than the corresponding tabulated value, -1.64, at α = 0.05. Thus we reject the null hypothesis that there is no
difference in the mean of students attending the schools between the displaced
and displacers and conclude that the percentage is higher in the displacers
group. As we can see from table 3.1, the mean difference of family members
attending the school, in both displacers and displaced, was not high (41.2 and
30.86 for displacers and displaced people respectively). This shows that the
displaced and displacers were affected as opposed to the general opinion that
the displaced people were highly affected. Because of the internal conflict in
the study area, the schools were either partly or fully closed. This cases either displacers or displaced family members
were difficult to send the student to the school due to insecurity.
From above results, the mean
average of family members of displaced people who attending the school were
lower than that displacer’s person. This attempt was also made to determine
other factors contributing to the variation in the percentage of school aged
family members sent to schools. Regression analysis using the method of
ordinary least square yielded the following results.
Table 3.2: Coefficients of
multiple regressions, assuming E as response variable
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
T |
Sig. |
Collinearity Statistics |
||
|
B |
Std. Error |
Beta |
Tolerance |
VIF |
|||
|
(Constant) |
38.612 |
2.247 |
- |
32.010 |
.000 |
|
|
|
Area of farm land (X1) |
2.501 |
.360 |
.003 |
24.120 |
.000 |
0.958 |
1.23 |
|
Number of cows (X2) |
5.910 |
.500 |
.012 |
1.003 |
.001 |
0.962 |
1.04 |
|
Economic level (X3) |
2.132 |
.077 |
-.021 |
-8.720 |
.004 |
0.982 |
1.41 |
|
Fathers education (X4) |
4.230 |
.089 |
.028 |
6.118 |
.004 |
0.782 |
0.98 |
|
Total no. of children (X5) |
0.129 |
.045 |
.051 |
1.873 |
.054 |
0.871 |
1.27 |
|
Mothers education (X6) |
2.067 |
.086 |
-.315 |
-24.019 |
.000 |
0.721 |
1.02 |
|
Employment status (X7) |
-1.466 |
.321 |
.284 |
12.060 |
.060 |
0.472 |
1.00 |
|
Age of student (X8) |
0.024 |
.055 |
.006 |
.437 |
.662 |
0.142 |
0.85 |
|
Housing Condition (X9) |
-.322 |
.051 |
-.088 |
-.297 |
.003 |
0.874 |
1.01 |
|
No. of Sheep & Goats (X10) |
.250 |
.124 |
-.010 |
-.832 |
.406 |
0.873 |
1.02 |
Dependent Variable: E (the number of
family members who ever reached school).
The linear
regression equation characterizing the effect of Area of farm land, father’s education,
mother’s education, number of cows, economic level of households, housing
condition and number of sheep and goats on the mean total number of school aged
children expressed as percentage of this analysis. From above SPSS output of table
3.2, we can write the equation of linear regression as follow:
E = 38.61 + 2.5X1 +
5.9X2 + 2.1X3 + 4.2X4 + 2.1X6 +
1.5X9 + 2.50X10
(8)
Equation (8) shows that as the
area of farm land increases by 1 timad, the
percentage of children sent to school increases by 2.5. As the number of cows’
increases, the percentage of children sent to school also increases. In similar
ways, as the economic level of the family increases by 1 unit, the percentage
of children sent school increases by 2.1, as the father’s education increases
by 1 year, the percentage of children sent school increases by 4.2, as the
mother's education increases by 1 year, the percentage of children sent to
school increases by 2.1. Similarly, housing condition and number of sheep and
goats positively determine the mean of sending the children to the school.
Other variable like total number of children, employment status and student age
were found to be insignificant in determining the dependent variable under
consideration (table 3.2).
To analysis the economic level
of community in the study area, the researcher classified the population as
displaced and displacers and economic level as low, middle and high. The result
of the survey show that the economic level of the displaced and displacers
people were almost equal, low (50.25%), middle
(38.22%) and (11.53%) for displacers and low (57.55%), middle (34.42%) and
(8.08%) for displaced people. It was caused as the people in the study area had
been prohibited to almost all sorts of socioeconomic services including market,
credit, health and transportation for more than three months. In addition, the
agricultural products for both displaced and displacers were not collected, the
school and offices were either party or fully closed, the salary of workers
were not paid and they couldn’t move freely from place to place due to
insecurity. The displacers’ people suffered a lot from diseases, food shortages
and humanitarian aid couldn’t reach them. The result also reveals that the
displaced people faced similar challenges but at least they had been visited by
the emergency aids in food and non-food items. Finally, the result shows that
both displaced and displacers were almost equally affected due to conflict
displacement and low in economy status.
3.2. Impacts of displacements
on the survival of displaced people:
As it was done for other
variables, determination of the factors contributing to the probability of
survival of displaced people as one of the strategies or the sole strategy in
times of food of shortfalls or any problems/ was done using the logistic
regression analysis. The survival status of the displaced people were depends on non-displaced (ND), displaced (DD), local
community (LC) and government body (GB), was considered as explanatory
variables. The backward conditional variable selection method yielded the
following result.
Table 3.3: The back ward elimination of all variables, assuming, Sad as
dependent variable.
|
|
B |
S.E. |
Wald |
Df |
Sig. |
Exp(B) |
95.0% C.I.for EXP(B) |
|
|
Model |
Lower |
Upper |
||||||
|
ND |
0.70** |
.016 |
20.002 |
1 |
0.000 |
.932 |
.904 |
.961 |
|
DD |
4.23** |
0.002 |
0.254 |
1 |
0.001 |
0.031 |
.000 |
. |
|
LC |
7.25** |
.008 |
.052 |
1 |
.0.000 |
1.000 |
.985 |
1.015 |
|
GB |
0.500 |
.004 |
.041 |
1 |
0.2501 |
.999 |
.991 |
1.008 |
|
(Constant) |
- 2.095 |
6.083 |
.119 |
1 |
0.7312 |
8.127 |
|
|
Log-likelihood =
22.736**, Probability = 0.0000.
Note: ** and * indicates that
the coefficients are significant at 5% and 10% Levels of significant
Where, Sad =
probability of survival.
The empirical result shows
that, all the coefficients are significantly different from zero at 5% level of
significance. The variables/predictors non-displaced (ND), displaced (DD),
local community (LC) and government body (GB) have wald
value of greater than zero (see Table 3.3), which confirms their
positive relation with the probability of survival. From above table 3.3,
we can write the fitted model as:
Fad = -
2.1 + 0.7ND + 4.23DD + 7.25LC + 0.52GB (9)
As it can be seen from
equation (9), the probability of survival of displaced people increases by 0.7
with the unit increase in the support of non-displaced, by 4.23 with the unit
increase in the displaced and by 0.52 with the unit increase in the government
body; and increases by 7.25 with the increase the unit in the local community.
The implication may be that displaced people can be supported by non-displaced,
themselves, local communities and government body to survive. This implies the
non-displacer, local community and government body also sharing the problems of
the displaced people by supporting them. It shows that, as the support of
displaced people by supporters (non-displacer, local community and government
body) increases, the economic level of the community become decline;
displacement had a positive impact on the economic level of the local community
and government body.
3.3. Impacts of displacements
on the health condition and social relation of displaced people:
The health condition of the
displaced people at different sites was surveyed. The results from survey show
that, out of the total displaced people more than half (50.12%) were patients,
suffered by diseases and food shortages. The displaced people were living with
together closely; using common eating and drinking materials, shows the
transmission of communicable diseases were high among the displaced people.
Using the data collected from
the displaced people, the socioeconomic status of the displaced people was depends on the relations: community-community (CC) relation,
community-government (CG) relation, community-economy (CE) relation and
community-social (CS) relations. Hence, the displaced communities were loss
cultural, social relation, separated from their relatives and the government
support them rather than asking income like; land rental, tax, etc. These
reveal that the social and economic levels of the community as well as the
country were decrease
3.4. Impacts of displacements
on living standard and housing condition of displaced people:
The reported standard of
living differed across the four types of households. As shown in table 3.4, the
proportion of households that reported a low standard of living (‘poor’ or
‘very poor’ ) was highest among displaced households (38 percent), followed by
mixed households with a displaced husband (32 per cent), mixed households with
a displaced wife (31 percent), and finally non-displaced house-holds (22
percent). A logistic model accounting for household size, the gender, age and
years of schooling of the head of household showed that the odds of reporting a
low standard of living were almost twice as high among displaced households as
among non-displaced ones (odds ratio = 1.8, p < 0.05) (see Table 3.4). There
was no statistically significant difference between any other combinations of
household types in the odds of reporting a low standard of living. In addition,
the odds of reporting a low standard of living were positively associated with
household size (odds ratio =1.2, p < 0.05) and negatively associated with
both years of schooling (odds ratio = 0.8, P < 0.01) and age of the head of
household (odds ratio = 0.97, P < 0.05).
The chance/ability to provide
housing units for survival differed across the four household types, net of
household characteristics. Among non-displaced households and mixed households
with a displaced wife, 61 and 64 percent, respectively, reported that they
would be able to provide a housing unit during this period. In comparison, 50 percent
of displaced households (odds ratio = 0.7, P < 0.05) and mixed households
with a displaced husband (odds ratio = 0.6, P < 0.05) reported that they
could provide a housing unit (see Table 3.4).
Table 3.4: Household standard
of living and Housing condition
|
Types of household |
Low Standard of living (% poor & very poor) |
Odds Ratio |
Ability to provide house (%) |
Odds Ratio |
|
Displaced |
38 |
1.8 |
50 |
0.7 |
|
Mixed, displaced male |
32 |
1.6 |
50 |
0.6 |
|
Mixed, displaced female |
31 |
0.9 |
64 |
1.2 |
|
Non-displaced |
22 |
Ref. |
61 |
Ref. |
|
Age |
- |
0.97 |
- |
1.03 |
|
Gender (Ref. male) |
- |
1.5 |
- |
0.3 |
|
Year of schooling |
- |
0.8 |
- |
1.2 |
|
Size of household |
- |
1.2 |
- |
0.94 |
|
Constant |
- |
2.5 |
- |
0.13 |
Notes: Ref. refers to the
reference category. n/a refers to non-applicable. Age, gender, and years of
schooling refer to the head of household.
In addition, relative to their
non-displaced counterparts, displaced households housing and type of house were
considered. The study considered the having/not having their own house as well
as roofing, wall, floor, to assess the housing conditions of the people (see
table 3.5).
Table 3.5:
Distribution of household by housing condition, where they live at the study
time.
|
Types of household |
Owner of house |
Roofing Material |
|||
|
Their own house (%) |
Not their own (%) |
Grass (%) |
Plastic (%) |
Iron sheet (%) |
|
|
Displaced |
4.55 |
95.45 |
12.50 |
49.23 |
38.27 |
|
Mixed, displaced male |
27.35 |
72.65 |
27.65 |
18.25 |
54.10 |
|
Mixed, displaced female |
31.45 |
68.55 |
32.23 |
19.12 |
51.35 |
|
Non-displaced |
87.65 |
12.35 |
31.65 |
3.25 |
65.10 |
As we can see from table 3.5,
on average living in their own house for displaced households were smaller
(4.55%) than that of non-displaced ones (87.65%) and only 4.55% of displaced
households, those had other house at different town, were living in their own
house at study time. Most of the displaced households were living in plastic
roofing house (49.23%) and non-displaced household were living in iron sheet
roofing (65.10%). In addition, the mixed displaced households those living in
their own house (27.35% for male displaced and 31.45% for female displaced)
were lower than that of non-displaced (87.65%).
4. CONCLUSION AND
RECOMMENDATIONS:
4.1. Conclusion:
The main objective of this
study was to assess the impact of displacement on socioeconomic status of
community with particular emphasis to education, health, living standard and
housing conditions. The results of the analysis showed that the non-displaced
people were better off than the displaced in their abilities to send children
to school, own houses roofed with corrugated iron sheet, living standard and
ability to finance the family in times of food shortage.
The number of oxen, area of
farm land, fathers education, mother education,
economic level of family, number of goats and sheep and housing condition were
positively affected the percentage of children to be sent to school. The
probability of survival of displaced was positively determined by the support
from non-displaced, local community and government body. This reveals that, the
economic level of the community, the investment by government and were
decreases, since the limited economy of the community were consumed by a lot of
displaced people. In addition, displaced people were highly affected by the
communicable and non-communicable diseases and suffering by hunger.
The findings reveal that the
aspects of the severe downward mobility caused by displacement: the loss of
land, loss of properties, loss of privacy due to loss house and moral damage
caused by forcing people to leave their homes and communities. The displaced
people were enforced to leave their home and properties, and they had left
empty-handed. Hence, the communities were supporting some of basic needs, the
displaced people are unmet in basic needs, health service was rarely met and
shelters were in difficult ways.
Comparing the four types of
households on a variety of socio-economic indicators showed that, compared with
non-displaced households, displaced ones suffered higher levels of poverty,
lower ability to provide residential units study time, lived in plastic house,
and were less likely to own a their house. In
addition, the comparisons revealed that mixed households with a displaced
husband were more like displaced households (than non-displaced ones) while
mixed households with a displaced wife were more like non-displaced households
(than displaced ones).
4.2. Recommendations:
Based on the result the
following recommendations were forwarded:
· The human right for
all ethnic in the country should respect and rules and regulation of the
country should be applied to the concerned body immediately.
· The government,
heath institution and non-displaced community should support the displaced
community and try to stop or reduce the displacement for further.
· The Social
relations, government and community support will increases
to reduce the status of conflict among the displaced and displacer groups.
5. ACKNOWLEDGEMENT:
The authors gratefully
acknowledged the anonymous reviewers for their contributions towards this work.
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Received on 05.12.2019
Modified on 01.01.2020
Accepted on 31.01.2020 ©A&V
Publications All right reserved
Res. J. Pharmacognosy and Phytochem. 2020; 12(1):. 07-13.
DOI: 10.5958/0975-4385.2020.00002.3