# The role of begging in the survival strategies of Brussels street people

*Le rôle de la mendicité dans les stratégies de survie des habitants de la rue à Bruxelles*

*De rol van bedelen in de overlevingsstrategieën van Brusselse straatbewoners*

Stef Adriaenssens, Mieke Schrooten and Bert De Bock

Translator: Helen White

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OpenEdition
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**Electronic version**

URL: https://journals.openedition.org/brussels/8699

DOI: 10.4000/14tnx

ISSN: 2031-0293

**This article is a translation of:**

De rol van bedelen in de overlevingsstrategieën van Brusselse straatbewoners - URL : https://journals.openedition.org/brussels/8608 [nl]

**Other translation(s):**

Le rôle de la mendicité dans les stratégies de survie des habitants de la rue à Bruxelles - URL : https://journals.openedition.org/brussels/8694 [fr]

**Publisher**

Université libre de Bruxelles - ULB

**Electronic reference**

Stef Adriaenssens, Mieke Schrooten and Bert De Bock, "The role of begging in the survival strategies of Brussels street people", *Brussels Studies* [Online], General collection, no 207, Online since 01 October 2025, connection on 10 December 2025. URL: http://journals.openedition.org/brussels/8699 ; DOI: https://doi.org/10.4000/14tnx

This text was automatically generated on December 10, 2025.

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# The role of begging in the survival strategies of Brussels street people

Le rôle de la mendicité dans les stratégies de survie des habitants de la rue à Bruxelles

De rol van bedelen in de overlevingsstrategieën van Brusselse straatbewoners

Stef Adriaenssens, Mieke Schrooten and Bert De Bock

Translation : Helen White

## EDITOR'S NOTE

In order to see the figures in a better resolution, go to the article online and click on "Original" below it.

## Introduction

<footnote n="1">1 A good thirty years ago, on 1 March 1993, begging and homelessness were decriminalised after many centuries. Although the phenomenon of begging is no longer a criminal offence, it has continued to stir up emotions on a regular basis. Especially in cities like Brussels, where people begging are visibly present in the streets, the confrontation with this phenomenon frequently leads to heated political and social debate. The commotion surrounding the introduction of a ban on begging in the presence of children under the age of 16 in the city of Brussels (2022) is a recent example of this [Schrooten et al., 2023]. Even more drastically, there are calls from some quarters to reopen the debate on the criminalisation of homelessness and begging [Dive, 2024].</footnote>

<footnote n="2">2 Debates on begging often focus on the - frequently assumed - link between begging and criminality or a lack of safety. More often, however, begging is experienced as a nuisance, inappropriate or undesirable, aside from any impact on public order</footnote>
[Colombo et al., 2016; de Coulon et al., 2015; Hermer, 2019]. Begging is also strongly associated with extreme poverty and the debate surrounding that, including discussion of the extent to which people who beg are genuinely experiencing precarious poverty. Some see begging as primarily an easy way of acquiring an income, whereas others consider it to be a survival strategy for people who have few other options, if any [Flåto and Johannessen, 2010; McIntosh and Erskine, 2000]. The term “survival activities” is often used in the literature as a concept [Deckard and Auyero, 2022; Nunez Basante, 2023; Ojebuyi and Ajao, 2023], but rarely given an explicit definition. In the context of this research, it refers to activities that people and communities at the bottom of the income scale engage in to provide themselves with a livelihood. These activities are often situated in the informal economy [Portes, 2010; Venkatesh, 2006], and frequently criminalised [Wacquant, 2009].

The aspect of criminalisation appears to be a recurrent theme in the debate on begging. All too often, the debate seems to be split down the middle, between begging as a threat to safety and begging as a canary in the coalmine called poverty. It comes down to the contrasting images of the beggar as an uninvited guest or the victim of exclusion. The differing claims made in discussions of begging and people who beg, for example about the background, motives and income of beggars, are highly diverse and often irreconcilable [Donovan, 2008; Fitzpatrick and Jones, 2005]. Incidentally, the word “income” should be understood in the wider sense here: begging does not only yield cash, but also gifts in kind such as cigarettes, food or clothing [Adriaenssens and Hendrickx, 2011; Reinhard, 2023].

It is striking that the debate on begging is often conducted with great confidence, although there is actually little well-founded knowledge about people who beg [Adriaenssens and Soare, 2023; Leeson and Hardy, 2022]. The group of people who beg belong to what is referred to in the literature as a “hidden” or “hard to reach” population [Adhikari and Bryant, 2018; Tourangeau, 2019; Wallengren, 2021]. Hidden populations are groups about whom little systematic and reliable evidence exists, certainly when it comes to evidence based on existing population surveys. This has to do with the fact that many of these hidden populations are found at the bottom of society [Cobham, 2020]. A few examples of people who are underrepresented or absent from mainstream population surveys are those living in absolute poverty, homeless people or people without a valid residence permit. Besides the hidden nature of the group and the activity, another reason for the lack of knowledge may lie in the illegal or stigmatised nature of their activities. As such, people who beg can also be identified as a hidden population conducting an activity that is not highly valued.

What knowledge do we possess of begging in Brussels? The previous systematic research into begging in Brussels, now almost twenty years old [Adriaenssens and Hendrickx, 2011; Clé and Adriaenssens, 2007], is based on questionnaires. This study was largely repeated in 2021-2022 [Adriaenssens and Soare, 2023; Soare et al., 2025]. The research documented the fact that, in the study period, the living conditions and background of people who beg were fundamentally different for two groups. Firstly, there was a predominantly male, homeless, local population of beggars; secondly, there were Roma beggars, most of whom were women, who had recently migrated from Romania. The latter were sometimes accompanied by children, and often continued to travel back and forth between the two countries [see also Geurts 2015]. In the past twenty years, however, much has changed. Consider the further expansion of the EU
and an increase and diversification in migration flows [Vandekerckhove et al., 2022]. It
is only to be expected that these developments will also have impacted Brussels and the
population who beg in the city. This has been confirmed by stakeholders in social work.
Despite a recent survey [Adriaenssens and Soare, 2023; Soare et al., 2025], a gap remains
in many areas between reliable information and scientific research on the one hand,
and the social debate on people who beg in Brussels on the other.

In the light of this gap between the availability of data and the need for it and given the
difficulty of effectively reaching groups such as people who beg, the best approach
would seem to be one in which several strategies are combined. To begin with, there is
a need for a plurality of methods, using both qualitative techniques (such as in-depth
interviews and participant observation) and quantifying research (such as
questionnaires). Existing administrative and other sources that may contain
information about this group are severely underexploited, however.

In other research on poverty, administrative data has been used with considerable
success, for example to document the effectiveness of policy [Meyer and Mittag, 2019;
Pattaro et al., 2020]. However, with hidden populations this presents us with a paradox:
groups who are not reached by policy are often not included in administrative records
either. Consequently, administrative data may be distorted, for example due to a low
uptake of rights. In social policy, for example, it often occurs that a significant
proportion of those entitled to benefits do not get or apply for them [Noël, 2021; Van
den Broeck et al., 2024]. This limits both the effectiveness of policy and the
representativeness of the data [Ko and Moffitt, 2020]. A similar problem occurs in
criminological research, where victims of crime do not always report the crime to the
police [Brame et al., 2010]. Here, for example, it is possible that people in the margins of
society are less willing to report crime. If this attrition occurs at sufficient scale and
non-randomly, this data on reporting crime or receiving benefits will only give a
limited picture of the envisaged population. For a hidden population such as people
who beg, therefore, the use of administrative data risks simply reproducing the
underrepresentation of this hidden group.

Besides direct forms of surveying, recording data kept by social workers who focus
specifically on vulnerable groups may be a valuable complementary source. For
example, the recent survey-based study [Adriaenssens and Soare, 2023; Soare et al.,
2025] did not make it possible to compare people who beg with other street people who
do not beg. As such, the underlying mechanisms and associations cannot be fully
explored. This contribution is intended to help fill that gap in the knowledge of the
living circumstances of people and families who beg in the Brussels-Capital Region. We
will do so based on an analysis of the database kept by Diogenes vzw, a specialised
organisation for the homeless in the Brussels-Capital Region. For this article, we will
analyse the data from the past six years (2018-2023). This unique source of information
complements what we already know, mainly with respect to the basis of the cross-
sectional survey study referred to above [Adriaenssens and Soare, 2023; Soare et al.,
2025]. The Diogenes data makes it possible to monitor changes in the composition of
the group of beggars over time, and also to compare street people who beg with others
who do not.

A broad definition of begging is asking for handouts in public space [Dean and Melrose, 1999; Fitzpatrick and Kennedy, 2000]. According to the literature, this mainly occurs in the form of a unilateral, non-reciprocal exchange between those who beg and the
people who give something. The techniques vary: from addressing passers-by, with or
without a story, to the use of a sign or cup to make it clear that a donation is being
requested from passers-by. The profiles of people who beg are also diverse [Bose and
Hwang, 2002; Ferguson et al., 2016]. In a broader conceptualisation, the activities of
street musicians or hawkers are sometimes also considered as begging [Hawkins, 2012;
Östman, 2022], because their interaction with the public implies a form of (symbolic)
market exchange. Diogenes vzw applies a broad definition of begging: an informal
activity, whether or not it is productive, that takes place in public, semi-public or
private spaces, where one or more beneficiaries solicit financial or material donations,
explicitly or otherwise, from passers-by. This definition is used to compile the data, and
as such it constitutes the starting point of this analysis.

10 The intention of this article is to provide better documentation of the role that begging may play within a group of people who generally experience a high degree of exclusion. Even within the population covered by Diogenes, there are meaningful differences in the nature and the seriousness of people's problems. Inspired by the existing literature [for example: Adriaenssens and Hendrickx, 2011; Reinhard, 2023], we assume that the decision to beg is mainly the result of a lack of alternatives, for example due to a precarious residency status or addiction issues. By way of a working hypothesis, we will therefore document whether certain forms of exclusion and problems increase the likelihood that people will beg.

# 1. Data collection by Diogenes

11 Diogenes¹ is accredited by the United Assembly of the Common Community Commission for Brussels as an outreach and Housing First service, and by the Brussels-Capital Region (Brussels Housing) as an Association for Integration through Housing (Vereniging voor Integratie via Huisvesting / Associations d'insertion par le Logement). The organisation is accredited by the Common Community Commission of the Brussels-Capital Region as an outreach service to support people who usually live on the streets. Currently, the organisation employs about 45 people in various projects. These include outreach, Housing First, intercultural mediation and the coordination of Collectief Straatdoden (funerals for those who die on the streets), Ondersteuning bij Woonst (housing support), Metro-Verbindingen (support for homeless people in public spaces), SubLINK (for people who sleep in metro and tram stations) and Zorgzame Buurt (caring communities).

12 Diogenes aims to build bridges between the streets and the rest of society. The target group consists of people who spend much of their time in public spaces. To support this mission, the organisation systematically collects data from three channels:

1. Social workers' diaries: All social workers keep a daily diary, in which they note whom they have seen, where and when; what they did with the person, which organisations they are liaising with and which network meetings they attended. In 2023, Diogenes recorded 1,451 distinct individuals in this way²;

2. Assistance files: When sufficient information is available to identify a person, a file is opened. It contains personal details such as the person's name, date of birth, nationality, place of birth, gender and place where the person was first encountered, etc.;

3. Annual profiles: Every year, all the outreach workers create a profile of each person with an assistance file. This profile contains about fifty questions on matters including the person's
living circumstances, health and addictions, income and work, family circumstances, accommodation and administrative situation. This information reflects the situation on the last day of the year, or the last known situation in the past year.

13 The analyses in this article are based on this latter form of data collection. Diogenes has been issuing this annual profile in its current form since 2017. The data is collected as reliably as possible, partly thanks to training sessions for the social workers.

14 The population that Diogenes covers is precisely the population that our data represents. It constitutes a generally vulnerable group of people who spend a lot of time on the street or elsewhere in public space. Not everyone lives permanently on the street. As the data will show, approximately half of the documented group sleep rough in public spaces, and as such they are completely roofless (see also Table 1).

<figure><img src="image_3.png" /><figcaption>Figure 1. Number of files filled in for people, whether or not they beg, 2018-2023</figcaption></figure>

Source: Diogenes’ annual profiles, 2018-2023, own processing

15 The data from Diogenes vzw gives a unique insight into the street population of Brussels. Figure 1 shows the number of files filled in for people, whether or not they beg, from 2018 to 2023 inclusive. We see a gradual increase in the number of people recorded. This may be an indication of a growing group of people who have to survive on the streets, and thus a sign of rising, visible precarity in Brussels. However, other interpretations are possible. An improved or extended presence on the streets on the part of Diogenes, or a larger number of contacts per working hour for the social workers, may have the same effect. Over the years of observation, the number of social workers working for the organisation has indeed grown. It is striking that the increase in the number of completed files mainly concerns people who do not beg, which slightly reduces the proportion of people who do.

16 To keep the many characteristics somewhat organised and retain sufficient observations, the choice is usually made to simplify the rich data into variables with fewer categories, often even dichotomies. For a person's housing situation, for example, it has been chosen to distinguish between those who live on the streets and in public spaces with no fixed abode, and others. This is in line with the ETHOS classification
[Edgar and Meert, 2006]. The first, most excluded group corresponds to ETHOS category 1, and will be referred to henceforth as “rough sleepers”. It is also important to note that the different forms of homelessness and precarious living situations are usually highly dynamic [Elkins et al., 2024; Scutella and Wood, 2024], whereas the data set only represents a snapshot of the living situation.

17

Furthermore, of the many nationalities, the most prevalent have been retained (Belgian, Romanian, Polish) or grouped into a meaningful geographical group (Maghreb). In the data concerning addictions and mental health problems, the many, often subtly different problem have been recoded into the question of whether the social worker has observed the problem.

<table><caption>Table 1. Descriptive statistics</caption><thead><tr><th>Variable/category</th><th>%/median</th><th>n</th></tr></thead><tbody><tr><td>TOTAL (2018-2023)</td><td>100 %</td><td>5,634</td></tr><tr><td>Begs?</td><td>37 %</td><td>2,106</td></tr><tr><td>Year</td><td></td><td></td></tr><tr><td>2018</td><td>12 %</td><td>683</td></tr><tr><td>2019</td><td>15 %</td><td>872</td></tr><tr><td>2020</td><td>16 %</td><td>895</td></tr><tr><td>2021</td><td>18 %</td><td>1,021</td></tr><tr><td>2022</td><td>20 %</td><td>1,101</td></tr><tr><td>2023</td><td>19 %</td><td>1,062</td></tr><tr><td>Gender</td><td></td><td></td></tr><tr><td>Male</td><td>68 %</td><td>3,848</td></tr><tr><td>Female</td><td>27 %</td><td>1,526</td></tr><tr><td>Other</td><td>5 %</td><td>260</td></tr><tr><td>Age (in years)</td><td>46</td><td>3,452</td></tr><tr><td>Roma ?</td><td>18 %</td><td>994</td></tr><tr><td>Nationality (grouped)</td><td></td><td></td></tr><tr><td>Belgian</td><td>33 %</td><td>1,882</td></tr><tr><td>Romanian</td><td>20 %</td><td>1,116</td></tr><tr><td>Polish</td><td>12 %</td><td>669</td></tr></tbody></table>
<table><tbody><tr><td>Maghreb countries</td><td>9 %</td><td>485</td></tr><tr><td>Other</td><td>14 %</td><td>776</td></tr><tr><td>Unknown</td><td>13 %</td><td>887</td></tr><tr><td>Rough sleepers?</td><td>56 %</td><td>3,164</td></tr><tr><td>Drug or alcohol addiction?</td><td>53 %</td><td>2,967</td></tr><tr><td>Mental health problems observed?</td><td>46 %</td><td>2,591</td></tr><tr><td colspan="3"><strong>Income (grouped)</strong></td></tr><tr><td>Full benefits</td><td>23 %</td><td>1,284</td></tr><tr><td>Illness/Invalidity benefits</td><td>10 %</td><td>586</td></tr><tr><td>Unemployment benefits/pension</td><td>6 %</td><td>364</td></tr><tr><td>Income from work</td><td>4 %</td><td>245</td></tr><tr><td>No income</td><td>37 %</td><td>2,083</td></tr><tr><td>Unknown income</td><td>19 %</td><td>1,072</td></tr></tbody></table>

18 Before we look more closely at the people who beg, we would like to present a general picture of the people that Diogenes vzw works with. Table 1 offers a summary of some of their characteristics. In the distribution of personal characteristics, we see that the street population that Diogenes reaches is predominantly male, which is in line with an observation based on the survey of homeless people in Brussels [Pierre, 2025] and in most other high-income countries [OECD, 2024]. Although two thirds of the population are not Belgian, the modal group are Belgian nationals. Poles and Romanians are the other common nationalities. A large minority have Roma ethnicity. The only national group with a background in non-EU countries that is somewhat on the larger side is people from the Maghreb region, mainly of Moroccan origin. Among the non-Belgians are many people with a precarious or undocumented residency status. For EU citizens, the lack of an official address is often an extra obstacle, certainly for those who work informally or beg. This can lead to a vicious circle of exclusion [Aradau et al., 2013; Consoli, 2023; Debruyne, 2022].

19 The social workers take stock of several background characteristics of the population that will be relevant to the rest of our analysis of begging. More than half of the group are rough sleepers. Approximately half struggle with an alcohol or drug addiction. The social workers also try to assess whether the people being assisted have mental health problems. Such problems are reported in almost half of them. The type of problem varies greatly in nature and severity, with frequently occurrences of depressive feelings and psychoses. Because begging is aimed at gaining an income, in cash or in kind, it seems logical that possible other sources of income would be relevant to predict this activity. Hence the expectation is that those who can count on an income from other sources are less likely to beg as well. A clear majority of the documented group
had either no income (37 %) or their income was unknown (19 %). Only a small minority
of 4 % have an income from work, whether formal or informal. All the others have one
or another form of benefits. In the regression analyses later on, all incomes from
benefits are collated into a single category.

## 2. Focus on people who beg

20 In this section of the analysis, we will focus specifically on the group of street people who beg. We will compare their profiles and living circumstances with those of people who do not beg, based on the data from Diogenes. To begin with, we will explore the data from the perspective of begging, by homing in on people who do and do not beg from a bivariate perspective. That means that we will investigate in each case whether a given characteristic does or does not correspond to begging or not begging as a survival activity. We will test the significance of these differences using standard bivariate correlation measurements: chi-squared tests if the independent variable is also categorical, and a Mann-Whitney test for the relationship between age and begging.

21 In the central analyses, we will now bring this collection of covariates together in a single analysis. The goal is the same: to investigate which characteristics of the street population predict whether or not they beg. In this regression, age has been recoded into a categoric variable, because of the large number of missing observations (which are moreover not random). Here, the known ages are divided into four equal quartiles, and a group has also been added of people whose age is unknown.

22 We will use a “Linear Probability Model” (LPM) to estimate these relationships. This approach is robust as long as the binary division is not too strongly concentrated in a single group. With a distribution of 37-63 % for those who do beg or do not beg respectively, this does not seem to be the case. To avoid bias, we will estimate the LPM with robust standard errors. Table 2 shows the descriptive statistics for the central variables. In the basic model, the central variables are estimated together. We observed that access to an income is unequally distributed across the characteristics of rough sleeping, addiction issues, mental health issues and ethnicity (see Table 4 in the appendix). For this reason, a second model estimates whether these vulnerability indicators interact with access to an income and the likelihood of begging. This is done by adding interaction terms between income and the four other indicators.

## 3. Exploration: a profile sketch

23 A significant minority of approximately one in three observations concerns people who beg at least now and then. The increase in the number of recorded street people over the years is mainly attributable to people who do not beg (see also Figure 1). This means that the relative share of beggars drops slightly in 2022 and 2023. This relative decrease must be understood, however, against the backdrop of a nominal increase in the number of observations.

24 There are clear differences between men and women: a little under half the women beg (45 %), whereas for men that figure is only one in three (35 %). So although men dominate the group as a whole, the likelihood is higher that women within that group
will beg. That distinction also remains in the regression. There is no great age difference between beggars and non-beggars. The former are slightly younger, but although the difference is significant, it is small: people who beg are an average of one year and eight months younger than those who do not.

The most salient characteristic of the begging population is surely that there is a high concentration in terms of ethnicity and nationality among the Roma and people of Romanian nationality. This is largely to be explained by the fact that 88 % of Roma people are identified as Romanians.

Of all the observations, the social workers report that approximately half have an alcohol or drug addiction. Within this group, the number of beggars is slightly higher than among people without an addiction. It turns out that there is only a limited correlation between rough sleeping and begging; this relationship is marginally significant at most. However, the income situation is a far stronger predictor: people with no income at all beg far more often than people with a different source of income.

<table><caption>Table 2. Bivariate relationship between begging and background characteristics</caption><thead><tr><th>Variable/category</th><th>Share / median begging per group</th><th>Relationship with begging (significance)</th></tr></thead><tbody><tr><td>Entire population</td><td>37 %</td><td>NA</td></tr><tr><td>Year</td><td></td><td></td></tr><tr><td>2018</td><td>40 %</td><td rowspan="6">31.22 (p&lt;0,001)</td></tr><tr><td>2019</td><td>38 %</td></tr><tr><td>2020</td><td>36 %</td></tr><tr><td>2021</td><td>43 %</td></tr><tr><td>2022</td><td>35 %</td></tr><tr><td>2023</td><td>33 %</td></tr><tr><td>Age (years)</td><td>X&#772;<sub>beg</sub> = 44<br>X&#772;<sub>others</sub> = 46</td><td>3.36 (p&lt;0,001)</td></tr><tr><td>Gender</td><td></td><td></td></tr><tr><td>Male</td><td>36 %</td><td rowspan="3">110.77 (p&lt;0,001)</td></tr><tr><td>Female</td><td>45 %</td></tr><tr><td>Other</td><td>13 %</td></tr><tr><td>Roma?</td><td>60 %</td><td>267.59 (p&lt;0,001)</td></tr><tr><td>Nationality (grouped)</td><td></td><td>289.90 (p&lt;0,001)</td></tr></tbody></table>
<table><tbody><tr><td>Belgian</td><td>33 %</td><td></td></tr><tr><td>Romanian</td><td>57 %</td><td></td></tr><tr><td>Polish</td><td>38 %</td><td></td></tr><tr><td>Maghreb countries</td><td>24 %</td><td></td></tr><tr><td>Other</td><td>37 %</td><td></td></tr><tr><td>Unknown</td><td>25 %</td><td></td></tr><tr><td>Drug or alcohol addiction?</td><td>40 %</td><td>20.42 (p&lt;0,001)</td></tr><tr><td>Rough sleepers?</td><td>38 %</td><td>3.21 (p=0,073)</td></tr><tr><td>Mental health problems observed ?</td><td>38 %</td><td>0.48 (p=0,50)</td></tr><tr><td>Income (grouped)</td><td></td><td></td></tr><tr><td>Full benefits</td><td>33 %</td><td></td></tr><tr><td>Illness/Invalidity benefits</td><td>28 %</td><td></td></tr><tr><td>Unemployment benefits/ pension</td><td>15 %</td><td>534.26 (p&lt;0,001)</td></tr><tr><td>Income from work</td><td>14 %</td><td></td></tr><tr><td>No income</td><td>55 %</td><td></td></tr><tr><td>Unknown income</td><td>26 %</td><td></td></tr></tbody></table>

For binary variables, the percentage of this group that begs is shown; where there are several groups, the proportion is displayed per group; for the continuous variable of age, the median is given. Tests: Chi-squared test for categoric variables; Mann-Whitney test for the relationship between begging and age.

## 4. Results: What links exist between begging and background characteristics?

The regression analysis (see Table 3) offers a more complete picture of the factors linked to the likelihood that someone will beg. As suggested above by the descriptive and bivariate results, there has been a slight decrease in the proportion of people who beg over the years. It is important to note that there is not so much a drop in the number of people begging on the street (for absolute figures, see Figure 1) as a relative decrease within a growing population of street people who are in contact with social workers.

As suggested above, the greater likelihood of beggars being female still stands. In terms of age, the differences are small. The likelihood of begging hardly varies between age
groups, although it is striking that social workers often have no age data for people who beg. This indicates that social workers have less information on average about who begs; thus those who resort to begging as a survival strategy have a less well-documented status. This may indicate that people who beg are also a more difficult group on average for outreach workers to maintain intense contact with.

29

Of the attributed characteristics, ethnicity is the strongest predictor. The group that is most strongly present in begging is without doubt the Roma. If we consider this ethnic group separately, aside from their nationality, this characteristic is one of the best personal predictors of begging or not begging, at least in comparison to the reference category of Belgian nationals who beg.

30

The connections between begging and all kinds of situational problems that people who live on the streets may experience are also substantial. Specifically, addictions or mental health problems and sources of income are relevant. Among those for whom the social workers have observed addiction issues, the chance that they will also beg rises considerably. This may be based on all kinds of underlying mechanisms, one of which is probably that people with addiction issues often find it more difficult to obtain an income based on other activities. A comparable dynamic may be at play in people with mental health problems. Likewise for them, there is a significantly higher chance that they will beg. This confirms the image that people often resort to begging when they have complex problems and difficulty accessing other forms of income. It is striking, however, that rough sleeping does not significantly increase the likelihood of begging according to the regression analysis, which suggests that other factors weigh more heavily.

31

The strongest predictor of begging is the lack of another source of income. Any source of income whatsoever significantly reduces the likelihood of begging. This supports the thesis that begging is an income-generating activity engaged in as a last resort. The major underlying narrative seems to be that people who have access to other opportunities or income will resort to begging far less readily. However, those who have no form of income whatsoever and live on the streets will often beg because this remains an accessible option when the alternatives are more difficult to attain.

32

In a second model, a number of interaction terms were added to investigate whether certain combinations of vulnerabilities further increase the likelihood of begging: between not having access to an income from any source and the characteristics of Roma ethnicity, rough sleeping, addiction issues and mental health issues. In particular, street people with a Roma background and rough sleepers often have no income at all (see Table 4 in the appendix). The interaction terms certainly indicate that a combination of no income with a Roma background and/or addiction issues do indeed increase the likelihood that someone will start begging. Surprisingly enough, it turns out that people with mental health issues and an income beg more often than those without an income. This may indicate a more complex relationship between psychological vulnerability, assistance and begging behaviour. In general, those with no income will beg more often, irrespective of whether they are sleeping rough or not. Of course we must always remember here that the entire sample consists of people who live on the streets, and practically all of them live with no or in precarious accommodation.
<table><caption>Table 3. Regressions of background variables to begging as an activity</caption><thead><tr><th></th><th>Model 1</th><th>Model 2</th></tr></thead><tbody><tr><td>Year (ref.: 2018)</td><td></td><td></td></tr><tr><td>2019</td><td>-.028 (.023)</td><td>-.031 (.023)</td></tr><tr><td>2020</td><td>-.072 (.026)*</td><td>-.072 (.026)**</td></tr><tr><td>2021</td><td>-.045 (.025)</td><td>-.049 (.025)</td></tr><tr><td>2022</td><td>-.122 (.026)***</td><td>-.120 (.026)***</td></tr><tr><td>2023</td><td>-.127 (.026)***</td><td>-.118 (.026)***</td></tr><tr><td>Age in quartiles (ref.: 1st quartile)</td><td></td><td></td></tr><tr><td>Quartile 2 [36-45]</td><td>.046 (.023)*</td><td>.043 (.023)</td></tr><tr><td>Quartile 3 [46-54]</td><td>.050 (.023)*</td><td>.044 (.022)*</td></tr><tr><td>Quartile 4 (≥ 55)</td><td>.012 (.022)</td><td>.011 (.022)</td></tr><tr><td>Age unknown</td><td>.057 (.019)**</td><td>.043 (.019)*</td></tr><tr><td>Gender (ref.: female)</td><td></td><td></td></tr><tr><td>Male</td><td>-.052 (.015)***</td><td>-.051 (.015)**</td></tr><tr><td>Other</td><td>-.122 (.030)***</td><td>-.127 (.031)***</td></tr><tr><td>Nationality/ethnicity (ref.: Belgian)</td><td></td><td></td></tr><tr><td>Roma</td><td>.266 (.023)***</td><td>.463 (.031)***</td></tr><tr><td>Romanian (excl. Roma)</td><td>-.060 (.031)</td><td>-.008 (.031)</td></tr><tr><td>Polish</td><td>-.098 (.023)***</td><td>-.059 (.024)**</td></tr><tr><td>Maghreb countries</td><td>-.202 (.022)***</td><td>-.164 (.022)***</td></tr><tr><td>Other (excl. Roma)</td><td>-.061 (.022)**</td><td>-.015 (.022)</td></tr><tr><td>Unknown</td><td>-.107 (.024)***</td><td>-.074 (.024)**</td></tr><tr><td>Drug or alcohol addiction?</td><td>.185 (.014)***</td><td>.236 (.025)***</td></tr><tr><td>Mental health problems?</td><td>.083 (.014)***</td><td>.120 (.016)***</td></tr><tr><td>Rough sleepers?</td><td>.026 (.018)</td><td>.020 (.023)</td></tr><tr><td>Income (ref.: no income)</td><td></td><td></td></tr></tbody></table>
<table><tbody><tr><td>Work</td><td>-.447 (.026)***</td><td>-.327 (.037)***</td></tr><tr><td>Unspecified income</td><td>-.279 (.035)***</td><td>-.208 (.044)***</td></tr><tr><td>Unknown income</td><td>-.232 (.021)***</td><td>-.163 (.032)***</td></tr><tr><td>Benefits</td><td>-.315 (.016)***</td><td>-.235 (.032)***</td></tr><tr><td colspan="3"><strong>Interaction terms</strong></td></tr><tr><td>Roma X no income</td><td></td><td>.362 (.037)***</td></tr><tr><td>Addiction X no income</td><td></td><td>.082 (.030)**</td></tr><tr><td>Mental health problems X no income</td><td></td><td>-.107 (.029)***</td></tr><tr><td>Rough sleeper X no income</td><td></td><td>-0,010 (.026)</td></tr><tr><td>Interaction terms?</td><td>No</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>.179</td><td>.199</td></tr><tr><td>Prob > F</td><td>&lt;0.001</td><td>&lt;0.001</td></tr></tbody></table>

Effects of a Linear Probability Model with robust standard errors (SE). n=5 634

* p <0.05; ** p <0.01; *** p <0.001

Model 1 estimates all main effects; model 2 adds interaction terms.

## Conclusion and discussion

33 People who live on the street are often fairly visible in the urban landscape. When it comes to social-scientific evidence, however, they seem to be practically invisible. This leads to street people often being the subject of public discussion, political talks and debates, but these discussions are rarely based on data beyond the anecdotal. The problem is not only the possible preference for a fact-free debate or one in which evidence is scarce. Even for those who would prefer things to be different, the problem remains that reliable data and analyses concerning this excluded group are only available in limited quantities. The statistical sources that aim to document the lives of Belgians or Brussels residents hardly represent this group, if at all. They are *uncounted*, which adds an extra dimension to social exclusion [Cobham, 2020]. People who live on the streets share this statistical invisibility with many other marginalised groups. This often forces governments and institutions to implement policies in blind ignorance.

34 There are few quick wins to be found in this need for data on hidden groups. Much of the research that does try to map hidden groups does so directly, for example by means of questionnaires. Furthermore, researchers today often try to use increasing use of data that is collected by institutions anyway, for example based on government administrative procedures. For highly marginalised groups, this approach often fails to make much of a contribution, precisely because these groups are poorly or
incompletely documented by administrative sources, due among other things to the
lower uptake of rights.

35

This article shows that there may be a rich source of information available from organisations in the non-profit sector who focus specifically on vulnerable groups. Some collect highly valuable data in the context of outreach or for other reasons, which is very relevant to gaining better understanding of the poorest members of society and the policy that affects them. Those with the ambition to pursue effective policies will find a rich source of information in this type of data. By way of a case study, we might mention Bruss’Help’s rich data collection on homeless people [Pierre, 2025]. This article illustrates the usability and feasibility of this strategy, and immediately also demonstrates the type of policy-relevant conclusions a decent analysis can lead to. The data collected by organisations such as Diogenes vzw does not merely offer a rich picture of the world in which street people live. It also makes it possible to analyse trends and differences within this group. In general, it is impossible to rule out the possibility of data being misused. Nevertheless, recent experiences suggest that stigmatisation and repression are at least as likely to stem from a lack of knowledge than from the abuse of data.

36

At the same time, there are of course quality requirements that must be considered. As is the case with administrative data, it is possible in some cases that an issue or group is not documented or insufficiently documented. This risk is also present in the data obtained from outreach work. The data set we have analysed here only applies to the street people supported by Diogenes, so it is not necessarily representative for everyone who begs in Brussels. All the same, this data set offers a rare and valuable insight into a group that is difficult to reach. Moreover, the fact that Diogenes is a relatively large organisation, and that their social workers have a fairly large diversity of knowledge about specific linguistic and ethnic groups, reduces this risk considerably. Triangulation with other sources, for example survey-based research among people who beg with a different sample design (such as [Adriaenssens and Soare, 2023; Soare et al., 2025]), or more qualitative approaches such as ethnographic research, remain important to refine the image.

37

In any event, the data reported here has the significant advantage that it enables us to compare the street people who beg with members of the same group who do not beg. An important observation based on this analysis is that begging functions as a survival strategy. Indicators of vulnerability and deprivation predict whether someone will resort, or will be forced to resort, to begging as an income-generating activity. Finding and keeping a formal job is extremely difficult for street people anyway, and there are very few observations of this happening. These findings are in line with existing research into informal activities among people in highly precarious living situations but often clash with social myths about the nature of begging and people who beg. This contribution therefore confirms or supports the idea that people who have alternative sources of income are less likely to resort to begging. If begging is a “last resort”, it does of course compete with other options that exist, such as street prostitution or forms of petty crime. In all probability, these are riskier, more harmful and more problematic to society and to the people in question. For assistance providers, this will probably not come as a surprising conclusion, but for policymakers and the general public, it may be an important correction to stubborn myths about beggars. It is also important information to inform future policy.
BIBLIOGRAPHY

ADHIKARI, P. and BRYANT, L. A., 2018. Sampling hard-to-locate populations: Lessons from sampling Internally Displaced Persons (IDPs). In: L.R. ATKESON and R.M. ALVAREZ (eds.). The Oxford handbook of polling and survey methods. Oxford: Oxford University Press. pp. 155-180.

ADRIAENSSENS, S. and HENDRICKX, J., 2011. Street level informal economic activities: estimating the yield of begging in Brussels. In: Urban Studies. 01/2011. Vol. 48, no 1, pp. 23-40.

ADRIAENSSENS, S. and SOARE, T., 2023. Bedelaars in Brussel: dimensies van sociale uitsluiting en publieke perceptie. In: COENE, J., GHYS, T., HUBEAU, B., MARCHAL, S., RAEYMAECKERS, P., REMMEN, R., VANDENHOLE, W., VAN DOOREN, W. and VAN REGEMORTEL, H. (eds.). Armoede en ongelijkheid. Jaarboek 2023. Leuven: Acco. pp. 301-315.

ARADAU, C., HUYSMANS, J., MACIOTI, P. G. and SQUIRE, V., 2013. Mobility interrogating free movement: Roma acts of European citizenship. In: ISIN, E. F. and SAWARD, M. (eds.). Enacting European citizenship. Cambridge: Cambridge University Press. pp. 132-154.

BOSE, R. and HWANG, S. W., 2002. Income and spending patterns among panhandlers. In: Canadian Medical Association Journal. 03/09/2002. Vol. 167, no 5, pp. 477-479.

BRAME, R., TURBER, M. G. and PATERNOSTER, R., 2010. Missing data problems in criminological research. In: PIQUERO, A. R. and WEISBURD, D. (eds.). Handbook of quantitative criminology. Dordrecht: Springer. pp. 251-272.

CLÉ, A. and ADRIAENSSENS, S., 2007. Bedelarij onderzocht. Een beknopte samenvatting van het onderzoek. Brussels: EHSAL Management School.

COBHAM, A., 2020. The Uncounted. Cambridge: Polity Press. 200 p.

COLOMBO, A., REYNAUD, C. and DE COULON, G., 2016. Begging in Geneva: which right to the city? In: Urban Environment. 2016. Vol. 10. Available at: https://journals.openedition.org/eue/1306

CONSOLI, T., 2023. Migration and ethnicity. In: BRETHERTON, J. and PLEACE, N. (eds.). The Routledge handbook of homelessness. London: Routledge. pp. 190-199.

DE COULON, G., REYNAUD, C. and COLOMBO WIGET, A., 2015. Begging in Geneva in times of crisis: multilayered representations of beggars, begging and cohabitation in the public space. In: European Journal of Homelessness. 06/2015. Vol. 9, no 1, pp. 191-211. Available at: https://www.feantsaresearch.org/download/article-87535298787986413382.pdf

DEAN, H. and MELROSE, M., 1999. Easy pickings or hard profession? Begging as an economic activity. In: DEAN, H. (ed.). Begging questions. Street-level economic activity and social policy failure. Bristol: Policy Press. pp. 83-100.

DEBRUYNE, P., 2022. Intra-Europese migratie in Gent. Een verhaal van bottom-uppraktijken op de naad van migratie en sociale mobiliteit. In: COENE, J., GHYS, T., HUBEAU, B., MARCHAL, S., RAEYMAECKERS, P., REMMEN, R., VANDENHOLE, W., VAN HECKEN, G. and VAN PRAAG, L. (eds.). Armoede en sociale uitsluiting. Jaarboek 2022. Leuven: Acco. pp. 231-251.

DECKARD, F. M. and AUYERO, J., 2022. Poor people's survival strategies: Two decades of research in the Americas. In: Annual Review of Sociology. 07/2022. Vol. 48, no 1, pp. 373-395.
DIVE, A., 2024. Recriminaliser la mendicité en Belgique? "Cela n'a aucun sens. Au contraire, il faut consacrer dans la loi le droit de mendier". In: La Libre Belgique. 10/10/2024. Available at: https://www.lalibre.be/debats/ripostes/2024/10/10/recriminaliser-la-mendicite-en-belgique-cela-n'a-aucun-sens-au-contraire-il-faut-consacrer-dans-la-loi-le-droit-de-mendier-BKIUMSAJ7ZBKVERSNORH5OHCAQ/

DONOVAN, M. G., 2008. Informal cities and the contestation of public space: the case of Bogota's street vendors, 1988-2003. In: Urban Studies. 01/2008. Vol. 45, no 1, pp. 29-51.

EDGAR, B. and MEERT, H., 2006. The ETHOS Definition of Homelessness. Fifth Review of Statistics on Homelessness in Europe. Brussels: FEANTSA. Available at: https://www.feantsaresearch.org/download/5-2006449618011929240409.pdf

ELKINS, M., LISA, F. and FRY, J. M., 2024. Homelessness and housing insecurity among youth in Australia: sequence analysis of housing careers. In: Housing Studies. 25/11/2024. Vol. 39, no 10, pp. 2527-2552.

FERGUSON, K. M., BENDER, K. and THOMPSON S. J., 2016. Predicting illegal income generation among homeless male and female young adults: Understanding strains and responses to strains. In: Children and Youth Services Review. 01/04/2016. Vol. 63, pp. 101-109.

FITZPATRICK, S. and JONES A., 2005. Pursuing social justice or social cohesion? Coercion in street homelessness policies in England. In: Journal of social policy. 15/06/2005. Vol. 34, no 3, pp. 389-406.

FITZPATRICK, S. and KENNEDY, C., 2000. Getting by. Begging, rough sleeping and The Big Issue in Glasgow and Edinburgh. Bristol: The Policy Press.

FLÅTO, M. and JOHANNESSEN, K., 2010. Economic strategies among long-term homeless people: the concept of harvesting economy. In: European Journal of Homelessness. 12/2010. Vol. 4, pp. 89-109. Available at: https://www.feantsaresearch.org/download/article-4-28202591817572774325.pdf

GEURTS, K., 2015. Roma in beweging. Diverse groepen en evoluties in Brussel. Handvaten voor onderwijs en hulpverlening. Brussels: Regionaal Integratiecentrum Foyer.

HAWKINS, R., 2012. "Industry cannot go on without the production of some noise": New York City's street music ban and the sound of work in the New Deal era. In: Journal of Social History. 01/09/2012. Vol. 46, no 1, pp. 106-123.

HERMER, J., 2019. Policing compassion. Begging, law and power in public spaces. Oxford: Hart Publishing.

KO, W. and MOFFITT, R. A., 2020. Take-up of social benefits. In: ZIMMERMANN, K. F. (ed.). Handbook of labor, human resources and population economics. Cham: Springer International Publishing. pp. 1-42.

LEESON, P. T. and HARDY R. A., 2022. American panhandlers. In: Cities. 01/05/2022. Vol. 124.

MCINTOSH, I. and ERSKINE, A., 2000. "Money for nothing"?: Understanding giving to beggars. In: Sociological research online. 05/2000. Vol. 5, no 1, pp. 107-115.

MEYER, B. D. and MITTAG, N., 2019. Using linked survey and administrative data to better measure income: Implications for poverty, program effectiveness, and holes in the safety net. In: American Economic Journal: Applied Economics. 04/2019. Vol. 11, no 2, pp. 176-204.
NOËL, L. Non-take-up of rights and precariousness in the Brussels Region. In: Brussels Studies, General collection. 30/05/2021. no 157. Available at: https://journals.openedition.org/brussels/5593

NUNEZ BASANTE, P., 2023. Survival strategies in inner-city neighborhoods: the case of Colombian and Peruvian migrants in Brussels, Belgium. In: Urban Research & Practice. 08/08/2023. Vol. 16, no 4, pp. 605-623.

OECD, 2024. Population Experiencing Homelessness. In: OECD. Affordable Housing Database. Paris: OECD. Available at: https://oe.cd/ahd

OJEBUYI, B. R. and AJAO, H. M., 2023. Resilient dwellers of urban “slums”: An ethnographic study of struggle and communication for survival among street children in Ibadan, Nigeria. In: Comparative Sociology. 20/06/2023. Vol. 22, no 3, pp. 325-358.

ÖSTMAN, A.-C., 2022. Women as mobile vendors: petty trade and rural poverty in early twentieth-century Finland. In: History of Retailing and Consumption. 02/09/2022. Vol. 8, no 3, pp. 213-228.

PATTARO, S., BAILEY, N. and DIBBEN, C., 2020. Using linked longitudinal administrative data to identify social disadvantage. In: Social Indicators Research. 02/2020. Vol. 147, no 3, pp. 865-895. Available at: https://link.springer.com/article/10.1007/s11205-019-02173-1

PIERRE, A., 2025. Dak- en thuislozentelling in het Brussels Hoofdstedelijk Gewest. Achtste editie, 6 november 2024. Brussels: BRUSS'HELP. Available at: https://brusshelp.org/images/Rapport_denombrement_2024_NL

PORTES, A., 2010. The informal economy. In: PORTES, A. Economic sociology: a systematic inquiry. Princeton: Princeton University Press. pp. 130-161.

REINHARD, D., 2023. How much do they make? A systematic review of income generated from begging. In: International Criminal Justice Review. 03/2023. Vol. 33, no 1, pp. 66-86.

SCHROOTEN, M., SOARE, T., DEBRUYNE, P. and ADRIAENSSENS, S., 2023. Bedelen in Brussel: Voorbij de valse tegenstellingen. In: Sociaal.Net. 13/06/2023. [Accessed on 07/11/2024]. Available at: https://sociaal.net/achtergrond/bedelen-in-brussel-voorbij-de-valse-tegenstellingen/

SCUTELLA, R. and WOOD, G. A., 2024. The dynamics of homelessness. In: JOHNSON, G., CULHANE, D., FITZPATRICK, S. METRAUX, S. and O'SULLIVAN, E. (eds.). Research handbook on homelessness. Cheltenham: Edward Elgar Publishing. pp. 52-71.

SOARE, T., ADRIAENSSENS, S. and HERMANS, K., 2025. Housing quality and homelessness among people who beg. In: Housing Studies. 03/06/2025. Vol. 40, no 6, pp. 1401-1427.

TOURANGEAU, R., 2019. Surveying hard-to-survey populations despite the unfavorable environment. In: American Journal of Public Health. 10/2019. Vol. 109, no 10, pp. 1326-1327.

VAN DEN BROECK, K., BROTCORNE, P., STEENSSENS, K., MORIAU, J., WAGENER, M., 2024. Studie over non-take-up van het leefloon en afgeleide rechten. Schatting en inspirerende praktijken ter bestrijding van non-take-up. Leuven: POD Maatschappelijke Integratie. Available at: https://www.mi-is.be/sites/default/files/documents/NTU_rapport_NL.pdf

VANDEKERCKHOVE, B., GELDOF, D., DE DECKER, P., VANHAEREN, R., VAN DAMME, W., VAN HULLE, M., SCHILLEBEECKX, E., BALCAEN, R., 2022. Atlas superdiversiteit Vlaanderen. Toekomstverkenningen: Ruimtelijke verkenning van een superdiverse samenleving. Brussels: Departement Omgeving. Available at: https://omgeving.vlaanderen.be/nl/onderzoek-cijfers-en-geoloketten/atlas-superdiversiteit
VENKATESH, S. A., 2006. Off the books. The underground economy of the urban poor. Cambridge: Harvard University Press.

WACQUANT, L., 2009. Punishing the poor: the neoliberal government of social insecurity. New York: Duke University Press.

WALLENGREN, S., 2021. An insider looking in or an outsider wannabee? Studying vulnerable hard-to-reach populations in the field of victimology – the example of the Roma communities in Sweden. In: International Review of Victimology. 09/2021. Vol. 27, no 3, pp. 328-343.

## APPENDIXES

<table><caption>Table 4. Proportion with no income by background characteristics</caption><thead><tr><th></th><th></th><th>Percentage with no income</th><th>Chi²</th></tr></thead><tbody><tr><td rowspan="2">Roma</td><td>Yes</td><td>59 %</td><td rowspan="2">259.5***</td></tr><tr><td>No</td><td>32 %</td></tr><tr><td rowspan="2">Addiction</td><td>Yes</td><td>32 %</td><td rowspan="2">53.2***</td></tr><tr><td>No</td><td>42 %</td></tr><tr><td rowspan="2">Mental health problems</td><td>Yes</td><td>26 %</td><td rowspan="2">247.2***</td></tr><tr><td>No</td><td>46 %</td></tr><tr><td rowspan="2">Rough sleeper</td><td>Yes</td><td>40 %</td><td rowspan="2">26.9***</td></tr><tr><td>No</td><td>33 %</td></tr></tbody><tfoot><tr><td colspan="4">* p < 0.05 ; ** p < 0.01 ; *** p < 0.001</td></tr></tfoot></table>

## NOTES

1. www.diogenes.brussels

2. In comparison: the most recent estimate of the number of homeless people in the Brussels-Capital Region at any given time is 9,777 [Pierre, 2025]. 992 of these were living on the streets. A comparison between contacts and a point estimate at a single moment in time is obviously not opportune, but the proportions do suggest that Diogenes is in contact with a far larger proportion of people sleeping rough (ETHOS category 1) than other categories of homeless people (ETHOS categories 2-7).
ABSTRACTS

The lives of people in precarious situations are often poorly documented. Consequently, authorities and organisations lack reliable information to develop policies that meet these groups' needs. People living on the streets are one such vulnerable and hidden population. Some of them beg, and although this activity is highly controversial, it has hardly been the subject of any scientific research. In this article, we analyse six years of individual records kept by Diogenes, a Brussels-based non-profit organisation providing outreach services, to improve our understanding of the role that begging plays in the lives of street people. We investigate how the characteristics of this group living on the streets correlate with the activity of begging. The analysis indicates that certain forms of vulnerability or exclusion – such as the lack of an income, addiction issues or a Roma background – increase the likelihood of begging. This is especially the case among people with psychological or addiction issues, those who belong to the Roma minority, and above all those who have no other source of income. In this context, begging appears to be mainly a survival activity: a flexible way of obtaining income when other options seem difficult to reach. This study shows how valuable the exploitation of existing but underused data can be for the development and evaluation of policy focused on the most vulnerable groups. Therefore, we also advocate a systematic approach to data collection and analysis within social work and policy.

La vie des publics vulnérables est souvent mal documentée, privant les autorités et les
organisations d'informations fiables pour élaborer une politique adaptée à leurs besoins. Les
personnes qui vivent dans la rue forment une population vulnérable et cachée. Certaines
mendient mais cette activité, pourtant prompte à déclencher de vifs débats, reste dans l'angle
mort de la recherche scientifique. Dans cette contribution, nous analysons six années de données
individuelles enregistrées par l'ASBL bruxelloise Diogenes, un service de travail de rue, afin de
mieux comprendre le rôle de la mendicité dans la vie des habitants de la rue. Nous examinons
quelles caractéristiques de ce groupe sont corrélées au recours à la mendicité. L'analyse montre
que certaines formes de vulnérabilité ou d'exclusion – comme l'absence de revenus, une
addiction ou l'origine rome – augmentent le risque de mendicité. C'est d'autant plus vrai pour les
personnes qui souffrent de troubles psychiques ou d'une addiction, qui appartiennent à la
minorité rome et, plus encore, qui ne disposent d'aucun autre revenu. Dans ce contexte, la
mendicité semble être surtout une activité de survie : une source de revenu flexible, quand
d'autres options semblent difficilement accessibles. Cette étude montre toute l'utilité de pouvoir
accéder à des données disponibles mais sous-exploitées, afin d'élaborer et d'évaluer les politiques
ciblant les plus vulnérables. Nous plaidons pour une approche systématique de la collecte et de
l'analyse des données dans le cadre de la politique sociale et du travail social.

Het leven van mensen in kwetsbare situaties is vaak slecht gedocumenteerd. Hierdoor ontbreekt
het overheden en organisaties aan betrouwbare informatie om beleid te ontwikkelen dat aansluit
bij de noden van deze groepen. Mensen die op straat leven vormen een dergelijke kwetsbare en
verborgen populatie. Een deel van hen bedelt, en hoewel deze activiteit fel bediscussieerd is, is ze
eveneens wetenschappelijk nauwelijks onderzocht. In deze bijdrage analyseren we zes jaar aan
individuele registratiegegevens van Diogenes vzw, een Brusselse straathoekwerkdienst, om beter
te begrijpen welke rol bedelen speelt in het leven van straatbewoners. We onderzoeken welke
kenmerken van deze groep die op straat leeft samenhangen met bedelen als activiteit. De analyse
wijst erop dat bepaalde vormen van kwetsbaarheid of uitsluiting – zoals het ontbreken van een
inkomen, verslavingsproblematiek of een Roma-achtergrond – de kans op bedelen vergroten. Dat is vooral het geval voor wie psychische of verslavingsproblemen heeft, behoort tot de Romaminderheid, en vooral voor wie geen andere bronnen van inkomen heeft. Bedelen lijkt in deze context vooral een overlevingsactiviteit: een flexibele vorm om inkomen te verwerven wanneer andere opties moeilijk bereikbaar lijken. Deze studie toont hoe waardevol het ontsluiten van bestaande, maar onderbenutte gegevens kan zijn voor het ontwikkelen en evalueren van beleid gericht op de meest kwetsbare groepen. We pleiten dan ook voor een systematische aanpak van dataverzameling en -analyse binnen sociaal beleid en sociaal werk.

## INDEX

**Subjects:** 4. santé – qualité de vie – inégalités sociales

**Keywords:** housing, population, poverty, public space, social inequalities, social policies

**Trefwoorden:** huisvesting, bevolking, armoede, openbare ruimte, sociale ongelijkheden, sociaal beleid

**Mots-clés:** logement, population, pauvreté, espace public, inégalités sociales, politiques sociales

## AUTHORS

### STEF ADRIAENSSENS

Stef Adriaenssens is an economic sociologist and senior lecturer in the Department of Economics at KU Leuven. His primary research interest is informal and underground activities. Most of his work focuses on how people respond to institutions and rules, by complying with them or otherwise. This is often applied to groups and activities that are difficult to contact, such as informal workers, people who beg or sex workers. His research is quantifying and builds on statistical and econometric techniques.
stef.adriaenssens[at]kuleuven.be

### MIEKE SCHROOTEN

Mieke Schrooten is associated with Odisee University of Applied Sciences as a lecturer in social work, and with the University of Antwerp (Centre for Research on Environmental and Social Change) as a senior lecturer. Her research and teaching are mainly focused on issues surrounding urban social work, migration, transmigration and mobility, transnational social work, diversity and informal social working practices.
mieke.schrooten[at]odisee.be

### BERT DE BOCK

Bert De Bock has considerable experience as an outreach worker and works for Diogenes. He contributes to long-term solutions for homeless people in Brussels and assists with applied research that may support social work for people in precarious housing situations.
bert[at]diogenes.brussels

## TRANSLATORS

### HELEN WHITE