Conflict and insecurity: a sociological perspective on perceptions of insecurity in conflict-

affected Democratic Republic of the Congo

Abstract

In this paper, we focus on insecurity perceptions in conflict-affected areas. We apply

sociological theories on the determinants of perceived security risks and test hypotheses

concerning theories on social and physical vulnerability, social disorder and social integration

in the area where the Lord’s Resistance Army (LRA) has operated. We use data from a survey

conducted in 2013 in the territory of Faradje (Haut-Uele) and apply multilevel models to 443

individuals living within 21 different villages and internally displaced persons (IDP) camps.

The results indicate that insecurity perceptions and fear for attacks are still widespread,

causing individuals to adapt their behaviour and IDPs to refrain from returning home. These

concerns are unaffected by social and physical vulnerabilities. We do find a positive

significant effect of the presence of IDPs in the villages and IDP camps on insecurity

perceptions. This suggests possible effects of social disorder and a lack of social integration

due to the arrival of IDPs in the area. Although improving the security situation itself is an

important factor, this paper shows that addressing insecurity perceptions might be an

important factor as well.

Keywords

Insecurity perceptions, Conflict, Social integration, Social disorder, Vulnerability, Internally

displaced persons, Multilevel analyses.

1

Introduction

The Haut-Uele province, located in North-eastern Democratic Republic of Congo (DRC), has

known a turbulent and violent history. In the 1960s, it has been affected by the Simba

rebellion against the Congolese government. During the two Congo Wars (1996-2003)

several rebel movements proliferated in the area and tried to impose their authority. More

recently, armed Mbororo nomad communities settled in the area, causing additional levels

of insecurity. Also foreign armed groups, including the Sudan People’s Liberation Army

(SPLA) and the Ugandan Lord’s Resistance Army (LRA), have used the area as a rear base.

The LRA moved into the area at the end of 2005, and installed its headquarters in the

Garamba National Park. Until 2007, the movement kept a low profile and refrained from

attacking the local population, with few small-scale attacks being reported. In retaliation of

local support to LRA defectors, in September 2008 the group launched its first large-scale

attacks against the local population, causing massive displacement. But the main trigger to a

brutal campaign of assaults and killings was the launch by the armies of Uganda, DRC and

South Sudan and with support from the US, on 14 December 2008, of ‘Operation Lightening

Thunder’. The aim of the operation was to destroy the LRA camps in Garamba and to finally

defeat the group. The operation failed; aerial strikes missed their main target, boots on the

ground were only deployed much later, and the LRA leadership could escape. In response to

the military operation, the movement changed tactics and started operating in small groups,

directly targeting civilians. A series of attacks by the LRA in northern DRC culminated in the

so-called Christmas massacres in December 2008 and January 2009, with hundreds of people

killed, children and adults abducted and thousands of people displaced. In early 2011, the

area around the town Faradje (Haut-Uele district in northern DRC) was again attacked by

LRA forces, causing some additional 30,000 people to flee (OCHA, 2011). In 2013, OCHA

2

estimated that over 250,000 people were internally displaced in the LRA-affected area of the

DRC (OCHA, 2013).

These attacks have deeply affected individuals’ perceptions of security in the area. As long as

no end to the LRA presence and no sustainable solution to the conflict is reached, people

fear new violent confrontations. These fears and perceptions of insecurity can have long

lasting consequences for local populations and internally displaced persons (IDP).

Perceptions of insecurity might have a negative impact on mental health and even affect the

development of posttraumatic stress disorder (PTSD) (Pedersen 2002; Pham, Weinstein and

Longman 2004). Previous research has also shown that perceptions of insecurity might deter

IDPs from returning home, even if hostilities have largely ceased (Vinck and Pham 2009).

Moreover, when perceptions of insecurity are high, people often restrict their mobility,

which affects their access to livelihoods (Young et al. 2005). Therefore, a better

understanding of perceptions of insecurity is clearly relevant for policy in conflict-affected

areas.

From an academic point of view, there is a clear gap in sociological research of perceptions

of security in conflict-affected areas. Despite the high relevance for people living in conflict

areas, research into the determinants of insecurity perceptions has mainly focused on high-

income countries (Taylor 2002). By studying perceptions of insecurity in areas where security

is actively threatened due to violent conflict, we can test the generalizability of common

theories on perceptions of insecurity.

3

It can be assumed that insecurity and perceptions of this insecurity are fundamentally

different in conflict-affected areas. There are, however, important similarities in perceptions

of insecurity across contexts. Living in a secure environment ranks among the top concerns

across high-, low- and middle-income countries (Franklin, Franklin and Fearn, 2008; Russo,

Roccato and Vieno, 2013). Moreover, the association between the actual risk and

perceptions of insecurity seems to follow similar patterns in Western and African countries.

In Western European countries, people tend to have far higher levels of fear of insecurity

than the actual security risk (Drakulich, 2013). In Kenya, according to a survey from 2011,

42% of individuals felt it likely that they would become a victim of violence over the next

year, although only 20% of the households reported being a victim during the previous year

(Wepundi et al., 2012). Given that perceptions in insecurity tend to follow similar patterns

across both politically stable and violent conflict-affected areas, it might be useful to apply

current theories on insecurity perceptions to conflict-affected areas.

With this paper, we want to test the applicability of common theories on insecurity

perceptions in a conflict-affected area. In doing so, we want to contribute to both a better

understanding of insecurity perceptions in this context on the one hand, and to the

development of theories on security perceptions in low-income countries on the other hand.

We examine perceptions of insecurity among people living in the territory of Faradje, and

include both residents and internally displaced persons (IDPs), living in villages or IDP camps.

The territory of Faradje (Haut-Uele) has been strongly affected by the LRA conflict, is

extremely remote, lacks NGO and state presence and suffers from extreme poverty, making

it a good case to study popular security perceptions. We apply sociological theories to

perceptions of insecurity through a specific focus on how social and physical vulnerability,

4

social disorder and social integration might affect perceptions of insecurity among

individuals, taking into account previous experiences with violence. By applying multilevel

models, we analyse perceptions of the security and an evaluation of improvements in the

security situation among 443 individuals within 21 different villages and IDP camps.

Context

From 2011 to 2013 LRA attacks declined progressively, which reflects a reduction of the

group’s fighting capacity, itself the result of constant military pressure. Faradje Territory

experienced only 2 attacks in the first 11 months of 2014 (Ronan, 2015). Since then, Faradje

has been largely spared from new attacks. However, these trends are very local and the LRA

conduct remains unpredictable (Ronan, 2015). Also, in neighbouring territories and the

Central African Republic, where most of the group now has settled, a continuously

fluctuating pattern has been observed with increases and decreases of attacks along the

years (UN OCHA, 2015). The unpredictability of the armed group’s behaviour and the

persisting insecurity in neighbouring territories can be important factors in insecurity

perceptions.

Data from ethnographic research conducted by two of the authors in June-August 20131

confirmed that even if security conditions improved considerably in Faradje, displaced

people remain reluctant to return home. There are three main reasons for this: persisting

fears and feelings of insecurity, the fact that the villages of origin have been completely

destroyed and the trauma caused by the very brutal LRA attacks. As a local NGO worker

argued, people fear that “the LRA is still around, they can always come back to destroy [the

1 33 interviews and 22 focusgroups with a range of state officials, IDPs, civil society organizations, local chiefs and host population.

5

fields]2”. IDPs and the host population have experienced very brutal attacks by the LRA, lost

family members, saw their children getting abducted or houses burnt. One displaced man

who saw two of his children abducted for two years by the LRA and has lost several family

members, mentioned that he does not want to return to his village of origin, as it would

remind him of the LRA atrocities. His wife and children returned, while he states to need

more time to get over it and join them.3 These reasons were also confirmed in a focus group

with civil society organizations working with IDPs: “it’s mainly because of their trauma, one

day the LRA could come back. Mostly with families most affected by the LRA atrocities. They

decide to stay, despite their living conditions”4.

There are also factors encouraging or forcing IDPs to go back, such as the lack of livelihoods,

but also conflicts with the host community and the lack of access to land in the host villages.

However, these dynamics tend to differ between localities. Some IDP camps developed close

connections with the larger social environment, with IDPs being in good terms with the host

community, whereas other IDP populations are facing serious harassment and are socially

and economically excluded. For example the IDPs in the camp of Yiyiwa, in Kurukwata, work

on small daily wages for the host population, lack the access to land and are sometimes

falsely accused. Here, the host population has claimed back the land IDPs were using, and

has tried to chase them away by several means, such as throwing a dead dog into the water

source, or accusing them falsely to the police.5 Other conflicts in Faradje originally were

about access to humanitarian aid and food distribution but since the departure of most

international NGO’s, conflicts around access to local livelihoods and land persist. The arrival

2 Interview with the coordinator of a local NGO, working with IDPs3 Interview in Nanzawa, IDP camp, Dungu, 2015. 4 Focusgroup with civil society organizations, Faradje, 2015.5 Focusgroup Yiyiwa IDP camp, 2013 and 2015. Also confirmed by civil society of Kurukwata in 2015.

6

of large numbers of IDPs produced a strong demographic pressure on fertile land,

infrastructure and livelihoods, increasing competition over it and leading to disputes.

Theory

According to Franklin and colleagues (2008), current research into the dynamics behind

perceptions and fear of risks can be divided into three categories: (1) vulnerability, (2)

disorder and (3) social integration models. In what follows, we discuss how vulnerability,

disorder and social integration might affect perceptions of insecurity in the Faradje territory.

Physical and social vulnerability

The vulnerability model stresses the importance of factors that tend to increase feelings of

being unable to resist attacks or being a more interesting target for future attacks (Franklin

et al., 2008). Scholars identify two sources of vulnerability: physical and social. Physical

vulnerability relates to the reduced ability to fend off attacks due to lower physical strength

or reduced mobility. Social vulnerability is caused by the lack of material resources to protect

oneself or recoup from victimization or the lack of social resources and networks to deal

with anxiety-provoking situations. Physical vulnerability in Western societies is often situated

in women and the elderly, while social vulnerability is projected on lower educated, people

living in poverty and racial and ethnic minorities (see Franklin et al., 2008 for an overview).

Although these factors are more applicable to Western societies, the main theoretical

grounds behind the vulnerability model can be applied to conflict-affected societies as well.

Physical vulnerability is certainly an aspect that can be translated to conflict-affected

societies. The main determinant of physical vulnerability and perceived insecurity in Western

7

countries, gender, is also at play in low-income societies. The higher perception of insecurity

among women is often explained by their vulnerability to sexual victimization (Gustafson,

1998). Sexual violence is a severe problem in conflict-affected areas in general and several

reports have shown that this is certainly the case in DRC (Peterman, Palermo and

Bredenkamp, 2011). Moreover, LRA has a history of capturing women and force them into

marriages with soldiers and commanders (Kramer, 2012). Women in LRA-affected Northern

Uganda are for instance less open towards former LRA combatants than men (Vinck and

Pham 2009). Moreover, women also report more PTSD symptoms than men in Rwanda

(Pham, Weinstein and Longman 2004). Given these risks for women, perceptions of

insecurity might be higher among women than among men in the Faradje territory.

Another cause of social vulnerability that has been studied extensively in developed

countries is poverty. Individuals and households living in poverty often lack the means to

overcome the consequences of victimization or to protect oneself against victimization

(Franklin, Franklin and Fearn 2008). Previous research has indeed reported that people living

in poverty perceive higher levels of insecurity (Smith and Jarjoura, 1989; Pantazis, 2000).

Moreover, over and above this individual effect of poverty, poor households are also

affected by neighbourhood poverty: insecurity is more prevalent in poor neighbourhoods,

leading to higher perceptions and higher fear of insecurity in poor neighbourhoods (Brunton-

Smith and Sturgis, 2011). Although these findings in Western countries often purport to

property crimes and protection against theft, the theoretical link between economic assets

and insecurity can be translated to conflict-affected areas as well. Economic assets can be an

important aspect at both the individual and contextual level. Securing incomes and

livelihoods for IDPs has positive effects on the insecurity levels in conflict-affected areas (Hill

8

et al. 2006). Economic assets also affect households’ ability to recover from displacement: in

LRA-affected Northern Uganda, IDPs in households with higher incomes are more positive

towards relocation (Vinck and Pham 2009).

IDPs might feel more vulnerable to security risks than long-term residents. Results from

ethnographic research in the area and previous research show that IDPs are often in conflict

with the host population, marginalizing and stigmatizing them further (Kumssa, Jones and

Williams, 2009). These conflicts generally concern access to basic services, land and

livelihoods. IDPs have less access to land, education and health care even if they also can

have a privileged access to humanitarian assistance when available. Therefore, IDPs might

evaluate their security worse than host populations because of conflicts they have with the

latter. Moreover, IDPs have often been confronted with brutal violence, causing them to

leave their homes. As previous victimization and traumatic experiences are linked to higher

perceptions of insecurity (Visser, Scholte and Scheepers, 2013), IDPs might overestimate

security risks, even after migrating from the area where the victimization took place.

Therefore, we expect that IDPs evaluate the security situation worse than the host

populations.

Disorder and social integration: presence of IDPs

Perceptions of insecurity might also be influenced by disorder and social integration

(Franklin et al. 2008). The basic idea behind the disorder model is that incivilities are

manifestations of lack of control that might create fears for individuals. These incivilities can

be social, for instance by disruptive behaviour, or physical, for instance by disorderly

surroundings. Perceptions of disorder might lead to uncertainty about the neighbourhood,

9

because it creates an image of lack of attention for the well-being of the neighbourhood.

This lack of attention for the well-being might motivate people to think that there is also no

attention for security risks in the neighbourhood. Therefore, where people perceive

community disorder, they tend to perceive increased security risks. Social integration, on the

other hand, can act as an inhibitor of fear (Franklin et al. 2008). The more people are socially

integrated in their community, the more secure they feel in their neighbourhood. If people

know their neighbours and have frequent interactions with them, they have more trust in

those neighbours and believe that they might intervene more easily in the case of security

risks (Gibson et al. 2002).

The arrival and presence of IDPs in villages and IDP camps might have an impact upon

perceptions of insecurity, because this is often associated with a lower social integration and

with perceptions of disorder. First of all, social integration will be lower in areas where lots

of IDPs have settled. Previous research in Western countries has shown that residential

mobility decreases the social cohesion of neighbourhoods (Tolsma, van der Meer and

Gesthuizen, 2009). People living in neighbourhoods with high levels of residential mobility

tend to invest less time in establishing social relations, due to the unstable composition of

the neighbourhood (Völker, Flap and Lindenberg, 2007). This lack of investment leads to less

social interactions and looser social networks within the neighbourhood. Hence, the

guardianship of strong social networks is lower in these neighbourhoods, possibly leading to

higher objective and perceived insecurity. The negative effect of residential mobility on

victimization rates has indeed been attested in previous research (Boggess and Hipp, 2010)

and perceptions of insecurity are also higher in neighbourhoods with lower levels of social

integration (Franklin, Franklin and Fearn, 2008; Lagrange, Ferraro and Supancic, 1992).

10

Moreover, the presence and arrival of IDPs might also signal disorder in villages and IDP

camps. The influx of IDPs has in some instances substantially altered the physical outlook

and the social composition of villages. As already indicated, this has often resulted in

increased conflicts between IDPs and host populations. The demographical pressure due to

the influx of IDPs has put stress on the division of available livelihoods, especially when

mobility has been reduced due to fear of renewed attacks. This could create perceptions of

social and physical disorder, which is in turn linked to higher levels of perceived insecurity

risks (Lagrange, Ferraro and Supancic, 1992). Access to livelihoods and basic services, such as

land and water, but even humanitarian aid, are disturbed with the arrival of the IDPs. Seen

the inaccessibility of their fields in their villages of origin, IDPs obtained a piece of land in the

host villages. Camps were settled in villages and land, water and basic services had to be

redistributed. Long-term inhabitants of some villages in Faradje report for instance tensions

on this matter with the recently arrived IDPs.

Although analyses based on the social disorder and social integration theory have so far mostly been

restricted to Western countries, these factors can also affect insecurity in areas affected by violent

conflict. Previous research in Uganda has shown that people feel least secure when meeting

strangers (Vinck and Pham 2009). In Colombia, social integration has also been hampered by

negative perceptions of IDPs, resulting in a reduced level of security (Hill et al. 2006). The

social disorder caused by the presence of IDPs has also resulted in increased conflicts with

the host population. These can be conflicts concerning the division of the available

livelihoods, but also concerning the habits or culture of IDPs (Hill et al. 2006; Vinck and Pham

2009). Due to these reasons, people in IDP camps in Uganda feel less secure than in other

11

areas (Vinck and Pham 2009). This shows that a lack of social integration and social disorder

in places where more IDPs have settled might lead to lower perceptions of security.

Hypotheses

Based on the sociological theories on perceived insecurity and previous research on the

topic in Western countries and conflict-affected areas, we propose four hypotheses:

Women will have lower perceptions of security than men (H1).

Poor households will have lower perceptions of security than less poor households (H2).

Internally displaced persons will have lower perceptions of security than long-term residents

(H3).

The higher the number of IDPs in the places where people live, the lower the levels of

perceived safety (H4).

Data

We use data from a survey by the Justice and Security Research Programme from June to

August 2013 in the Faradje territory in Haut-Uele. The design of the survey was based on

results of ethnographic research in the Faradje Territory and was subsequently tested in the

field and adjusted where needed. The original questionnaire was composed in French and

thereafter translated by the local NGO ‘Action pour la promotion rurale’ (APRU) into Lingala.

Local employees of APRU were trained to administer the questionnaires in personal face-to-

face interviews. Each interview took more or less one hour.

Two-stage sampling was applied: villages or IDP-camps were selected first, followed by the

selection of individuals within those villages and camps. In the first stage, 22 units were

12

randomly selected, 7 IDP camps and 14 villages. Due to security reasons, one of these

research sites had to be removed from the list. Within each of the remaining 21 research

sites, research assistants aimed at sampling 5% of the total adult population or 10% of all

households. Due to a lack of a reliable sampling frame containing the total adult population,

estimations of the population of each village has been derived from combining several

official sources, i.e. the territory administration and local chiefs, as well as local NGOs. The

total estimated population size of Faradje territory ranges between 295,683 and 357,529

inhabitants on a surface of 13,138 km2 (Omasombo Tshonda 2011; Faradje Territory

Administration 2011). Secondly, respondents were randomly selected within the villages and

camps, meaning that the researchers selected certain streets where they would interview all

households. In total, 559 questionnaires were registered successfully. After list wise deletion,

we retain 443 individuals in our dataset.

Variables

Dependent variables. We test the association between vulnerability, disorder and social

integration on two dependent variables: perception of insecurity and the perception of

evolutions in insecurity over the past year. Perceived insecurity is a dichotomous variable,

indicating whether individuals perceive insecurity. This variable is based on the answers to

the question ‘Do you feel protected at this moment?’. We have recoded this variable:

individuals who answered no to this question have been given a score of 1, whereas

individuals who perceive security have been given a score of 0. In this way, this variable is a

measure of the insecurity individuals perceive. Perceived evolution in insecurity is a metric

variable based on the respondents’ answers to the question ‘How do you see the evolution

of the security situation during the past 12 months?’. Answers to this question were

13

recorded in a five-point scale ranging from the ‘the security situation has deteriorated much’

(1) over ‘the security situation has remained the same’ (3) to ‘the security situation has

improved much’ (5). We have recoded the answers in a negative direction, to indicate a

worse evaluation of the security situation in the last twelve months.

Independent variables. Sex is a dichotomous variable, indicating whether an individual is male (0) or

female (1). Age is a metric variable indicating the self-assessed age of individuals in full years.

From previous research we know that people in illiterate communities tend to report their

ages inaccurately: people tend to round their age to the nearest round digit, often zero or

five. The magnitude of this age heaping can be measured using Whipple’s index (Pardeshi,

2010). For our data, we obtain a Whipple’s index of 121.9, which indicates ‘approximate

data’ according to the United Nations’ Demographic Yearbook (United Nations, 2012).

Therefore, we retain this as a metric variable in our analyses. Children in the household is a

dichotomous variable based on the answers to the question ‘How many children younger

than 18 live in your household?’. Answers were recorded numerically, which we have

dichotomized to a variable indicating whether a household contains children (1) or not (0).

Household economic situation is a categorical variable indicating the total economic security

of respondents’ household. Respondents were asked how many chicken, goats, ducks, pigs,

cows, sheep, rabbits, motorcycles, cars, bicycles, radios, ploughing tools and mobile phones

they had. To calculate the total wealth, we multiplied each number of objects by its local

market value in US Dollars, and subsequently summed it up to reflect the total wealth. Due

to the unequal distribution of the wealth and to avoid the detrimental impact of outliers, we

recoded this variable into a variable with four categories: (1) less than $50, (2) between $50

14

and $200, (3) between $200 and $350 and (4) more than $350. Displaced is a dichotomous

variable indicating whether individuals have been displaced (1) or not (0).

We also included one variable at the village-level, to examine the association between

perceptions of insecurity and disorder and social integration in the place where people live:

the percentage of displaced persons in the village. Percentage displaced is a metric variable,

which indicates the percentage of individuals within the same village who are displaced. This

variable has been calculated by using the information of the variable displaced and

aggregating this information to the level of the village. The percentage of displaced in the

villages range from 0 (i.e. one village) to 100% (i.e. the IDP camps).

As a form of sensitivity analyses, we control for previous victimization. Therefore, we include

a variable that indicates victimization experience and time since the last attack of the LRA.

Previous victimization is a dichotomous variable indicating whether respondents experienced

personal victimization in the past. This variable has been constructed by combining the

answers on three questions regarding personal victimization. Respondents were asked

whether they themselves have experienced physical mutilation, abduction or whether their

house had been burnt or destructed. A score of 1 indicates that respondents experienced at

least one of these situations, whereas a score of 0 indicates that respondents have not

experienced these kinds of victimization themselves. Years since last attack is a metric

variable based on answers to the question ‘In which years has your village been attacked by

the LRA’? Respondents could indicate for each year between 2005 and 2013 whether their

village had been attacked or not. We recoded this variable to indicate the years since the last

15

attack: a score of 0 means that the village was last attacked in 2013, a score of 3 indicates

that the village was last attacked in 2010.

Method

Given our two-stage sampling, we are able to generalize our findings across both villages and

individuals. Therefore, we performed analyses that made it possible to infer our results at

these different levels. Multilevel analyses are best suited for these surveys, given that they

allow for the modelling of influences of both individual characteristics and characteristics of

the village. Moreover, due to the clustering of individuals in villages, single-level analyses run

the risk of incorrectly finding statistically significant results.

The results of the multilevel analyses are presented in table 2. We perform separate

analyses for the influences on perceptions of insecurity and the perceived evolution in

insecurity. For each model, we present the coefficients and standard errors of the different

effects and the variance at the individual and at the village level. The variance indicates to

what extent differences in perceptions of insecurity between individuals are attributable to

their individual characteristics on the one hand, and to the villages they inhabit on the other

hand. We will use these variance components to calculate the intra-class correlation, a

coefficient that indicates the percentage of individuals’ perceptions of security attributable

to the village. We calculate this intra-class correlation for the null-model, containing only the

random intercept.

For the model of perceived insecurity, we apply logistic multilevel analyses, given that the

dependent variable is a dichotomous variable. For this model we present the log odds as

16

coefficients. These coefficients can be interpreted as the natural logarithm of the influence

on the odds of perceiving insecurity versus perceiving security: a positive effect of for

instance age, indicates that individuals who are older have, in general, higher odds of

perceiving more insecurity than security compared to younger individuals. A negative effect

on the other hand means that individuals who are older tend to perceive more security than

insecurity compared to younger individuals. For the second model, of perceived evolution of

insecurity, we present regression coefficients. A positive effect of age of for instance 0.1 can

be interpreted as an average difference of a 0.1 higher deterioration of the security over the

last year between two individuals who differ one year in age, and the other way round.

Given the low number of villages, we estimate the models using the Markov Chain Monte

Carlo algorithm (MCMC), as this provides more robust estimates.

Results

Table 1 displays the descriptive statistics for all dependent and independent variables in our

analyses. 57.6% of the respondents indicate that they themselves have been abducted or

mutilated, or that their house has been burnt down or destroyed. Even though respondents

on average indicate that the last attack of their village is 3.8 years ago, we notice that

perceptions of insecurity are still relatively high: 28.5% of individuals still perceive insecurity.

Most individuals notice improvement in the security situation, however, with an average of

2.4, which is close to reporting that the security situation has improved slightly (i.e. a score

of 2 on the dependent scale). If respondents feel protected, they indicate that this is

primarily due to the Congolese Army (Forces Armées de la République Démocratique du

Congo or FARDC): 65.1% indicate that they feel that the FARDC ensures their safety. This is in

sharp contrast with the general perception on the Congolese army in other conflict-affected

17

areas, where it is known for its human rights violations and abuses, confirmed by different

reports and studies (Spittaels and Hilgert, 2010; Oxfam, 2011; Stearns, Verweijen, and

Ericksson-Baaz, 2013). In Faradje Territory, respondents confirmed this conduct of the

Congolese army and gave many examples of abuses, but they also stated that the situation

improved considerably since the appointment of a new commander in 2011. Some

respondents have lost their trust in the army, but the majority regained their trust and

experienced its presence as an important source of protection. During a focus group in Aba

in 2013, one man said: “After the LRA, there were FARDC soldiers who had settled here, they

harassed the population, but now it is better. The current group of FARDC cohabits well with

the population. He [the new commander] welcomes everyone.”

Despite this, respondents often fear for their safety: 72.2% indicate that during the last 12

months they have had fears for their security regularly or often, and 51.7% indicate that they

have regularly or often feared attacks or passages by the LRA in their villages during the last

12 months. The relatively low perception of the security situation in the area is also

replicated in respondents’ behaviour: 22% of the respondents indicate that they have spent

the night outside of their house because of security reasons during the last 30 days. Among

the displaced, 75.9% indicate that they have never returned to their fields in the village

where they came from; 83.6% of them refrained from returning to their fields because of

security reasons.

TABLE 1 ABOUT HERE

18

Men are, with 61.3% of respondents, overrepresented in our dataset. Only 12.8% of our

respondents live in households without children. The remoteness and limited economic

development of Faradje territory is also illustrated by our sample: 28.3% of surveyed

households possess maximum $50, while more than half (51.9%) possess $200 or less. Of all

respondents in our sample, 39.6% are displaced, both in IDP camps and in villages. 75.7% of

IDPs live in IDP camps, the remaining 24.3% in villages. The intra-class correlation indicates

that 45.6% (2.754/(3.290+2.754)) of individual differences in perceived insecurity are due to

the village or camp individuals inhabit, while 24.7% (0.192/(0.585+0.192)) of differences in

perceived evolution in insecurity are due to the location where people live. This is relatively

high, compared to other research applying multilevel models. Two individuals living in the

same village, hence have a perception of insecurity, which is 45.6% alike, and a perception of

the evolution of insecurity, which is 24.7% alike. This underlines the need to apply multilevel

models. In what follows we will test our hypothesis by looking at the results of the multilevel

analyses results in table 2.

TABLE 2 ABOUT HERE

With our first hypothesis, we predicted that women would have lower perceptions of the

security situation than men (H1), due to an increased physical vulnerability. The results of

our models of perceived insecurity and the perceived evolution of insecurity do not support

this hypothesis, however. The coefficient for female respondents is not significant. Women

do not perceive lower levels of security, nor do they experience deterioration in the security

conditions over the past 12 months. Reports on security incidents in the area provide a

valuable explanation: while there are differences between men, women and children in

19

experiences with specific categories of violence, each member of the local community has an

equal chance to be a victim of LRA atrocities.

Next, we look at the effect of households’ economic security on the perceptions of

insecurity. We predicted that having less means is associated with lower perceptions of the

security situation in the area (H2). Again, the results of our analyses do not support previous

findings from the literature (Smith and Jarjoura, 1989; Pantazis, 2000): there is no significant

effect of the economic situation on the perception of security among individuals in the

Faradje territory. From the survey, it can be concluded that individuals who have more

means to overcome attacks do not have higher perceptions of the security situation than

individuals with virtually any means at their disposal.

With our third hypothesis, we predicted that displaced persons would perceive more

insecurity than residents (H3). This is, again, not confirmed by our results: displaced persons

do not perceive higher insecurity, nor evaluate the evolution in insecurity worse than non-

displaced persons. In terms of traumatic events, both IDPs and residents often suffered from

LRA violence and experienced insecurity: they have lost family members, were injured

during an attack, or have family members abducted by the LRA. While IDPs are most

vulnerable in terms of standard of living (they fled their homes due to insecurity, they can’t

go back, or have their houses destroyed), the survey results indicate their strong resilience.

Furthermore they might feel safe in the secure area where they live at the moment, but still

fear of going back to their homes, where insecurity still prevails, whether from the LRA or

other armed groups or bandits. IDPs settled along the roads or near military presence to

20

secure their houses and livelihoods, whereas before they lived remotely. Living in groups in

protected areas, might increase their sense of security.

The fourth and final hypothesis predicted lower perceived security in villages with a higher

percentage of displaced (H4), due to the lower social integration and the higher social

disorder. The results of our multilevel models deliver mixed results. There is no significant

effect of the percentage displaced on perceived insecurity, while there is significant positive

(b = 0.594; p < 0.05) effect on the perceived evolution of insecurity in the area. Individuals

who live in villages with a higher percentage of displaced persons tend to evaluate a

negative change in insecurity over the last twelve months. This means that the presence of

displaced people in the area where people live, influences individuals’ perceptions of

insecurity, for residents and displaced alike. This might also indicate why there is no

difference between residents and displaced people in terms of the perception of security

risks: stories about atrocities might spread together with the displaced, causing general

concerns about security in the area. In other words, our results indicate that the presence of

IDPs influences individuals’ perceptions on security conditions considerably.

The effect of the number of years since the last attack suggest that the evaluation of the

security situation is gradually improving and that the noxious effects of attacks by the LRA

are waning: for each year that has passed since the last attack, perceptions of insecurity

have been lower (bperceived insecurity = -0.218; p < 0.05; binsecurity evolution = -0.062; p < 0.01). If this

trend is replicated, feelings of insecurity might in the future diminish further. Additional

analyses further reveal that, for the model of the evolution in insecurity, there is a significant

negative interaction effect between the years since last attack and the percentage of

21

displaced in the village or camp. This means that the presence of displaced people in the

area where people live is predominantly important for individuals who have experienced

attacks relatively recently. The more time has passed since the last attack, the less people

are influenced by the presence of displaced in the villages and camps. This might indicate

that villages and camps are slowly adapting to the changed composition and the influx of

displaced people.

Discussion

Although previous research has looked into the security evaluations of IDPs and host

populations in conflict-affected areas (Hill et al. 2006; Vinck and Pham 2009; Wepundi et al.

2012), this is the first study to apply sociological theories to perceptions of insecurity.

Although there is a long tradition of research focusing on the effects of vulnerability,

disorder and social integration in Western countries (Franklin et al. 2008), the applicability of

these theories to conflict-affected areas has not been tested. Our approach has taught us

three important things.

First of all, notwithstanding the recent stabilization of the area after years of LRA-attacks, the

region is still strongly affected by the consequences of these attacks. People have traversed

the area, settling in villages and newly installed IDP camps: nearly 40% of the people in our

sample are IDPs, which is representative for the numbers of displaced in the conflict-affected

area of Faradje territory, more specifically on the axe Aba, Faradje, Tadu, where a lot of

displaced are settled. Although on average people feel that the security situation has

improved, they are still worried about potential attacks in the future: 28.5% do not feel

protected in the area where they live. During the past twelve months, 72.2% have had fear

22

for their security regularly or often, while 51.7% regularly or often feared attacks by the LRA

over the same period. Fears are not only widespread among the IDPs, but are equally

present among residents. These fears have important implications, one of which is replicated

in individuals’ behaviour in the area: some people spend the night outside their house due

to security reasons and IDPs are reluctant to return to their villages, even if these villages are

not far removed from where they currently live. At the same time, however, the results

show that security perceptions are gradually improving: the more time has passed since the

last attack, the less people are concerned about their security situation. Given the negative

effects of fear of crime and perceived risks of crime for the physical and mental health of

individuals (Stafford, Chandola and Marmot, 2007), our results point out that insecurity

perceptions should be paramount among the objectives in post-conflict reconstruction

efforts. Although improving the security situation itself is an important factor, addressing

insecurity perceptions might be an important factor as well.

Second, the vulnerability hypotheses are not supported by our results. Previous research,

which has been predominantly conducted in urbanized areas in developed countries, has

indicated that people who feel more vulnerable to victimization, due to social or physical

causes, perceive higher crime risks and fear crime more (Franklin et al., 2008). This is,

however, not replicated in our research on perceived risks of victimization in LRA-affected,

northern areas of the DRC. This might indicate that the vulnerability hypothesis is not

particularly suitable for research in post-conflict areas, where attacks and violence might be

more ruthless, consequences more severe and equally targeting each member of the

community. Hence, perceptions and fear of victimization might be more widespread and less

subject to physical and social factors than is the case in developed countries. This is also

23

replicated in the finding that previous victimization is unrelated to perceptions of insecurity,

which might be due to the encompassing insecurity, which struck the Faradje-area, causing

both previous victims and non-victims to perceive insecurity alike. Furthermore, an effect of

the economic situation might be ill suited in conflict-affected regions in developing

countries, where considerable numbers of people have limited means. The results of our

analyses suggest that the literature on the determinants of perceptions of insecurity are too

limited in scope to understand variation in perceptions in areas affected by extremely violent

conflict and pressing insecurity issues.

Third, we did find that the presence of IDPs in the villages and IDP camps increases

perceptions of security risks. The more IDPs in a village or a refugee camp, the less residents

and IDPs perceive improvements in the security situation. This might be one of the reasons

why we found no differences in perceptions due to social and physical factors: information

about atrocities and attacks by the LRA might migrate together with the IDPs to the camps

and villages in which these IDPs arrive. The presence of IDPs might also instil social disorder

and lower social integration in the villages and camps where they live. Direct information on

disorder and social integration was not available in the survey at hand, however. Therefore,

further research could contribute to the literature by addressing the direct link between

disorder and social integration on the one hand and perceptions of insecurity risks on the

other hand, for instance by measuring perceptions of disorder and the social integration of

individuals.

As always, this research is subject to some limitations as well. First of all, due to existing

conditions of the Faradje territory, the sampling strategy has been hampered because of a

24

lack of a decent sampling frame. We did not dispose of reliable information of population

sizes of the different villages and camps to select them in the first stage, let alone

information to verify the representativeness of the realized sample. Weighting the data is,

hence, not feasible, due to a lack of figures to compare the realized sample to the actual

distributions in the population from which we have sampled. Therefore, the

representativeness of this research cannot be guaranteed, although we took the necessary

steps to maximize representativeness in the realized sample.

A second limitation is that we were unable to control for the geographical clustering of

perceived security risks in the area. Although we used the appropriate statistical techniques

to correct for the clustering of individuals in camps and villages, by applying multilevel

models, villages and camps might be geographically clustered as well (Elliott et al., 2000).

Some villages and camps might be more susceptible to security risks due to their

geographical situation: areas closer to Garamba national park might be more at risk of LRA

attacks.

Conclusion

In this paper we addressed the insecurity perceptions in LRA-affected areas of the DRC. We

applied a sociological perspective and theories from research on insecurity in developed

countries. We tested whether these theories were applicable to the analysis of insecurity in

a conflict-affected area. Theories concerning social and physical vulnerability, social disorder

and social integration were tested using survey data. We applied multilevel analyses to test

the hypotheses on social differences in perceived security risks among 443 individuals living

in 21 villages and camps. The results taught us that social and physical vulnerability does not

25

influence perceptions of insecurity in the Faradje area. Social disorder and a lack of social

integration due to more presence of IDPs, however, have a negative impact upon insecurity

perceptions. Therefore, we can conclude that current sociological theories are only partly

applicable to violent conflict-affected areas. Furthermore, we have learned that perceptions

of insecurity are gradually improving the more time has gone by since individuals have

experienced victimization.

The results of this paper indicate that although improving the security situation itself is an

important factor, more attention needs to be devoted to resolving fears of insecurity among

individuals in post-conflict areas as well. Given that these fears steer behaviour and have an

important influence on people’s mental and physical health and mobility, reducing fear for

one’s security might be of primordial importance. Indeed, fear of insecurity inhibits IDPs in

the Faradje area to return home. Therefore, reducing fears might facilitate the relocation of

IDPs.

26

Acknowledgements

This research has been supported by the Department for International Development (UK). The

authors want to thank Jean-Claude Malitano for facilitating the survey and the editor and anonymous

reviewers for their valuable suggestions.

27

References

Boggess LN and Hipp JR (2010) Violent crime, residential instability and mobility: does the

relationship differ in minority neighbourhoods? Journal of quantitative criminology 26(3): 351-370.

Brunton-Smith I and Sturgis P (2011) Do neighbourhoods generate fear of crime? An empirical test

using the British Crime Survey. Criminology 49(2): 331-369.

Drakulich KM (2013) Perceptions of the local danger posed by crime: race, disorder, informal control,

and the police. Social science research 42: 611-632.

Elliott P, Wakefield JC, Best NG and Briggs DJ (2000) Spatial epidemiology: methods and applications.

Oxford: Oxford University Press.

Faradje Territory Administration (2011) Annual report 2011. DRC: Faradje Territory Administration.

Franklin TW, Franklin CA and Fearn NE (2008) A multilevel analysis of the vulnerability, disorder, and

social integration models of fear of crime. Social justice research 21(2): 204-227.

Gibson CL, Zhao J, Lovrich NP and Gaffney MJ (2002) Social integration, individual perceptions of

collective efficacy, and fear of crime in three cities. Justice Quarterly 19(3): 537-564.

Gustafson PE (1998) Gender differences in risk perception: theoretical and methodological

perspectives. Risk analysis 18(6): 805-811.

Hill R, Diener KJ, Miller S and White T (2006) IDP livelihoods and personal security: case studies from

Colombia and Sudan. Refugee survey quarterly 25(2): 40-59.

Human Rights Watch (2009) The Christmas Massacres. LRA attacks on Civilians in Northern Congo .

Human Rights Watch, United States of America.

Kramer S (2012) Forced marriage and the absence of gang rape: explaining sexual violence by the

Lord’s Resistance Army in Northern Uganda. The journal of politics and society 23(1): 11-49.

Kumssa A, Jones JF and Williams JH (2009) Conflict and human security in the North Rift and North

Eastern Kenya. International journal of social economics 36(10): 1008-1020.

Lagrange RL, Ferraro KF and Supancic M (1992) Perceived risk and fear of crime: role of social and

physical incivilities. Journal of research in crime and delinquency 29(3): 311-334.

28

OCHA (2011) Province Orientale - District du Bas-Uele, du Haut-Uele et d’Ituri : Mouvements de

population suite aux attaques des groupes armés : situation en Février 2011 . Via: http://www.rdc-

humanitaire.net/.

OCHA (2013) LRA Regional Update: Central African Republic, DR Congo and South Sudan. Via:

http://www.reliefweb.int/.

Omasombo Tshonda J. (2011). Haut-Uele. Trésor Touristique. Musée Royal de l’Afrique Central,

Tervuren.

Oxfam (2011) We are entirely exploitable. The lack of protection for civilians in eastern DRC. Oxfam

Briefing Note. 28 July 2011.

Pantazis C (2000) ‘Fear of crime’, vulnerability and poverty. British Journal of criminology 40(3): 414-

436.

Pardeshi GS (2010) Age heaping and accuracy of age data collected during a community survey in the

Yavatmal District, Maharashtra. Indian journal of community medicine 35(3): 391-395.

Pedersen D (2002) Political violence, ethnic conflict, and contemporary wars: broad implications for

health and social well-being. Social science & medicine 55: 175-190.

Peterman A, Palermo T and Bredenkamp C (2011) Estimates and determinants of sexual violence

against women in the Democratic Republic of Congo. American journal of public health 101(6): 1060-

1067.

Pham NP, Weinstein HM and Longman T (2004) Trauma and PTSD symptoms in Rwanda. Implications

for attitudes toward justice and reconciliation. JAMA: the journal of the American Medical

Association 292(5): 602-612.

Ronan P (2015). LRA Crisis Tracker. The State of the LRA in 2015: 8 key trends in LRA activity. The

Resolve, Invisible Children. February 2015.

Russo S, Roccato M and Vieno A (2013) Criminal victimization and crime risk perception: a multilevel

longitudinal study. Social indicators research 112: 535-548.

29

Smith DA and Jarjoura RG (1989) Household characteristics, neighbourhood composition and

victimization risk. Social Forces 68(2): 621-640.

Spittaels S and Hilgert F (2010) Mapping Conflict Motives: Province Orientale (DRC). IPIS Research.

Stafford M, Chandola T and Marmot M (2007) Association between fear of crime and mental health

and physical functioning. American journal of public health 97(11): 2076-2081.

Stearns J, Verweijen J, and Eriksson Baaz M (2013) The national army and armed groups in the

eastern Congo: untangling the Gordian knot of insecurity. Usalama Project. London: Rift Valley

Institute.

Taylor RB (2002) Fear of crime, social ties, and collective efficacy: maybe masquerading

measurement, maybe déjà vu all over again. Justice quarterly 19(4): 773-792.

Tolsma J, van der Meer T and Gesthuizen M (2009) The impact of neighbourhood and municipality

characteristics on social cohesion in the Netherlands. Acta politica 44(3): 286-313.

United Nations (2012) Demographic Yearbook. New York: United Nations.

UN OCHA (2009) Special Report. December 2009. Summary of fact finding missions on alleged human

rights violations committed by the Lord’s Resistance Army (LRA) in the districts of Haut-Uélé and Bas-

Uélé in Orientale province of the Democratic Republic of Congo. United Nations.

Vinck P & Pham P (2009) Peacebuilding and displacement in Northern Uganda: a cross-sectional

study of intentions to move and attitudes towards former combatants. Refugee Survey Quarterly.

28(1): 59-77.

Visser M, Scholte M and Scheepers P (2013) Fear of crime and feelings of unsafety in European

countries: macro and micro explanations in cross-national perspective. The sociological quarterly

54(2): 278-301.

Völker B, Flap H and Lindenberg S (2007) When are neighbourhoods communities? Community in

Dutch neighbourhoods. European sociological review 23(1): 99-114.

Wepundi M et al. (2012) Availability of Small Arms and Perceptions of Security in Kenya: An

Assessment. Geneva, Small Arms Survey.

30

Young H et al. (2005) Darfur: livelihoods under siege. Medford, Feinstein International Famine Center.

31

Table 1: descriptive statistics

RangeAve. / (Std.) /

# %

Dependent

Perceived insecurity

No 0/1 317 (71.6%)

Yes 0/1 126 (28.4%)

Insecurity evolution 1-5 2.422 (0.851)

Independent

Individual

Sex

Male 0/1 273 (61.6%)

Female 0/1 170 (38.4%)

Age 18-99 42.068 (14.645)

Children in the household

No 0/1 57 (12.9%)

Yes 0/1 386 (87.1%)

Wealth

≤ $50 0/1 125 (28.2%)

> $50 & ≤ $200 0/1 104 (23.5%)

> $200 & ≤ $350 0/1 89 (20.0%)

> $350 0/1 125 (28.2%)

Displaced

No 0/1 268 (60.5%)

Yes 0/1 175 (39.5%)

Previous victimization

No 0/1 188 (42.4%)

Yes 0/1 255 (57.6%)

Years since last attack 0-9 3.817 (1.928)

Village

Percentage displaced 0-1 0.395 (0.417)

32

Table 2: Multilevel analyses of perceived insecurity and perceived evolution in insecurity

Perceived insecurity Insecurity evolution

Coef. Std. Err. Coef.

Std. Err.

Intercept 1.197 (0.923) 2.430 *** (0.247)

Individual

Independent

Female 0.328 (0.278) 0.063 (0.079)

Age -0.013 (0.010) 0.001 (0.003)

Children in the household -0.757 ‘ (0.417) 0.033 (0.120)

Wealth

< $50 Ref. Ref.

> $50 & ≤ $200 0.150 (0.373) -0.077 (0.106)

> $200 & ≤ $350 -0.104 (0.404) -0.029 (0.114)

> $350 0.412 (0.391) 0.002 (0.110)

Displaced -0.278 (0.476) -0.076 (0.145)

Previous victimization -0.147 (0.276) -0.052 (0.078)

Years since last attack -0.218 * (0.090) -0.062 ** (0.022)

Village

Percentage displaced -0.136 (1.089) 0.594 * (0.270)

Variance

Village 2.871 (1.628) 0.161 (0.077)

Individual 3.290 0.578 (0.042)

‘ p<0.1; * p<0.05; ** p<0.01; *** p<0.001; two-sided; Nindividuals = 443; Nvillages = 21.

33