health, drugs & service use among single male …article type: research date submitted by the...

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Health, Drugs & Service use among Single Male Welfare Recipients with a different Distance to the Labour Market in

Amsterdam

Journal: BMJ Open

Manuscript ID: bmjopen-2013-004247

Article Type: Research

Date Submitted by the Author: 14-Oct-2013

Complete List of Authors: Kamann, Tjerk; Public Health Service Amsterdam, Epidemiology Documentation & Health Promotion de Wit, Matty; Public Health Service Amsterdam, Epidemiology,

Documentation & Health Promotion Cremer, Stephan; Public Health Service Amsterdam, Epidemiology, Documentation & Health Promotion Beekman, Aartjan; VU University Medical Center, Department of Psychiatry

<b>Primary Subject Heading</b>:

Public health

Secondary Subject Heading: Rehabilitation medicine

Keywords: EPIDEMIOLOGY, Public health < INFECTIOUS DISEASES, MENTAL HEALTH, SOMATIC HEALTH, SERVICE USE, UNEMPLOYMENT

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Health, Drugs & Service use among Single Male Welfare Recipients with a

different Distance to the Labour Market in Amsterdam.

Authors:

T.C.Kamann - M.A.S. de Wit - S. Cremer – A.T.F Beekman

Primary subject heading: PUBLIC HEALTH

Secondary subject heading: REHABILITATION MEDICINE

Keywords

EPIDEMIOLOGY

PUBLIC HEALTH

MENTAL HEALTH

SOMATIC HEALTH

SERVICE USE

UNEMPLOYMENT

Affiliations

Tjerk C. Kamann; Academic Collaborative Urban Social Exclusion Research (USER-G4); Public

Health Service Amsterdam, department of Epidemiology, Documentation and Health Promotion, VU

Medical Center, department of psychiatry.

Dr. Matty A.S. de Wit; Public Health Service Amsterdam, department of Epidemiology,

Documentation and Health Promotion; Netherlands.

Stephan Cremer; Public Health Service Amsterdam, department of Epidemiology, Documentation

and Health Promotion; Netherlands.

Prof. dr. Aartjan T.F Beekman; VU Medical center, department of psychiatry; Amsterdam,

Netherlands

Corresponding author:

Tjerk C. Kamann

PO BOX 2200; 1000 CE, Amsterdam, Netherlands

Email: [email protected]

Tel: +31 622728815

Fax: +31 205555160

Word count:

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Abstract: 298 words; Main document: 2977 words

ABSTRACT

Objectives

The majority of homeless are single men. To aid prevention of this social drop out, we aimed to

explore the (unmet) health needs of an expectedly vulnerable population little was known about: single

male welfare recipients (SIM-welfare).

Design

A cross-sectional study incorporating peer-to-peer methodology to approach and survey SIM-welfare.

Socio-demographics, prevalence of ill health, harmful drug use and healthcare utilization for

subgroups of SIM-welfare with a different distance to the labour market, were described and compared

against single employed men (SIM-work).

Setting

Males between the age of 23-64, living in single person households in Amsterdam.

Participants

A random and representative sample of 472 SIM-welfare was surveyed during 2009-2010. A reference

sample of 212 SIM-work was taken from the 2008 Amsterdam Health Survey.

Outcome measures

Standardised instruments were used to assess self-reported ill somatic and mental health, harmful drug

use and service use. SIM-welfare’s distance to labour market was assessed by professionals from the

welfare agency.

Results

SIM-welfare are mostly long term jobless, low educated, older men; 70% are excluded from re-

employment policy due to multiple personal barriers. Health: 50% anxiety & depression; 47% harmful

drug use; 41% multiple somatic illnesses. Health differences compared to SIM-work: (1) controlled for

background characteristics, SIM-welfare report more mental (OR 4.0; 95%CI 2.1 to 4.7) and somatic

illnesses (OR 3.1; 95%CI 2.7 to 6.0); (2) SIM-welfare with the largest distance to the labour market

report most somatic and mental health problems. Controlled for ill health, SIM-welfare are more likely

to have service contacts than SIM-work.

Conclusion

SIM-welfare form a selection of men with disadvantaged human capital and health. Reintegration

towards work for those with the largest distance to work, needs to take into account combined somatic

and mental health barriers. Findings do not support a need to improve access to health care.

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ARTICLE SUMMARY

Article Focus

- The majority of homeless are single men. This social drop out is painful for individuals and

it’s remedy costly for society. Prevention of social drop is therefore favourable.

- With single men on welfare, risk factors for further social drop out can be expected to

accumulate, but their labour market position is unclear and prevalence of (unmet) health needs

is undocumented

- This study takes first steps in providing information to support preventive public policy

towards single men on welfare.

Key Messages

- 70% of single male welfare recipients are asserted to take a distant position to the labour

market due to multiple personal barriers. Somatic illnesses, anxiety and depression and drug

use seem to play a major role in these barriers.

- Most distant positions towards the labour market are taken by those having not only mental

but also somatic health problems.

- A substantial part (14%) of SIM-welfare constitute former rough sleepers who now have roof

and income, but not yet work. Findings suggest no need for promoting access to healthcare.

Findings do suggest a need for rehabilitation interventions in which vocational and (public)

health perspectives are combined.

Strengths and limitations of this study

- By applying methodology of peer interviewers, this is the first study to draw epidemiological

results from a seemingly representative sample of single male welfare recipients that authors

are aware of.

- By combining standardised health indicators and drug use indicators with registration data

concerning distance to the labour market, the study adds to few studies in which both a

vocational and public health perspective are served for the long term jobless.

- Lack of diagnostic information about the nature and severity of illnesses and lack of more

specific information about use of healthcare services make us careful in interpreting findings

that participants more often have healthcare contacts than working single men, controlled for

health differences.

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INTRODUCTION

Background

In cities throughout Europe and other OECD countries, most homeless rough sleepers are

single men (SIM), in the middle age range, with addictions and other health problems[1]. The

dominance of this profile among the homeless can be considered “one of the strongest comparative

findings on homelessness in Europe that exists”[2]. Also in the Netherlands, with accessible healthcare

and relatively high expenditure on social security[3], individuals falling through social safety nets, are

mostly single men. In the four largest Dutch cities, 90% of the homeless are men, mostly single[4].

Most evident “triggers” for homelessness in OECD countries are relation breakdown and

house eviction[1]. Underlying interacting structural, institutional, relationship, and personal

characteristics[5], responsible for the mechanisms at work here, are likely to vary across welfare

settings. Job loss due to an economic crisis, for instance, in countries with high unemployment

benefits is an unlikely direct cause for homelessness. However, job loss, resulting in long term

unemployment or economic inactivity, with its well established negative consequences on health, cash

reserves, social network and family relations[6-9], can be seen as an important pathway into

homelessness and seems especially relevant in the current time with rising unemployment.

To assist prevention of homelessness among single men, the Public Health Service of

Amsterdam (PHS) initiated a study to assess the health needs of a group of single males below the

epidemiological radar, among whom risk factors for (further) dropout from society seem likely to

accumulate: single men residing in the last safety net of social security; single male welfare recipients

in Amsterdam (SIM-welfare).

Target population

In Amsterdam, like in the rest of the Netherlands, one third of working age welfare recipients

are men living in single person households[10]. In January 2009 this group totalled 10.270 single men

in Amsterdam[10]. In this study, SIM-welfare are targeted that are not currently homeless (86%)[11].

Common characteristics of SIM-welfare are (a) running a single person household - they all

have a roof over their head and live there alone (b) being dependent on welfare benefits set at around

70% of minimum wages (c) having no paid job – they might miss out on immaterial benefits of

performing a job like the time structure, status and social contacts[12, 13] (d) having no entitlement

for social insurance benefits (eg. unemployment or disability benefits) (e) having mandatory

healthcare insurance – like all Dutch citizens - and can therefore access care; and finally (f) being

registered at and in contact with the municipal agency responsible for providing welfare services in

Amsterdam (the municipal Service for Work and Income - SWI). SIM-welfare can be found and

targeted for specific interventions.

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Policy Setting

Both from a public health perspective and from a vocational welfare-towards-work

perspective, finding re-employment can be considered a desired outcome[14, 9]. To effectively re-

integrate welfare clients towards the labour market, SWI assesses the severity of clients barriers to

employment based on clients’ demographics, human capital indicators, health problems and other

personal barriers. Based on the assessment, clients are positioned on a “stairway to work” ranging

from step 1 (largest distance to labour market) to step 4 (closest to work). Trajectories to work do not

necessarily proceed from step 1, to 2, to 3 to 4. Clients on different steps are shown to differ in

employability[15] and are exposed to different re-integration policies (see box 1 for a description).

Objectives

To aid both public health and welfare-towards-work policy, we aim to describe the population

of SIM-welfare in terms of socio demographics, prevalence of ill somatic and mental health, harmful

drug use and healthcare utilization in relation to distance to the labour market.

1. Explore characteristics of SIM-welfare (socio demographics, prevalence of somatic and mental

illness, harmful drug use and service utilization) and compare these between subgroups of SIM-

welfare on different steps of SWI’s stairway to work and employed single men (SIM-work).

2. Analyse health differences in relation to distance to labour market (controlled for demographics)

3. Analyse service use differences in relation to distance to labour market (controlled for health

problems)

Step 1. “Care”

-Personal barriers like

illness and addiction need

attention first, before

climbing the stairway. -Clients have no obligation

to participate in society or

engage in job-search activities.

-Linkages to healthcare

through referral.

Step 2. “Social Activation”

-Personal barriers prohibit

exposure to employment

activation.

-Clients are obliged to

participate in low-threshold

social activation

programmes that suit

individual needs.

Step 3. “Employment activation”


placement on labour

market.


participate in activation

programmes to learn basic

employment skills (coming

in time, accepting

directives), orientation on labour market, specific

vocational training and

education.

Step 4. “Employment placement”

-Clients are available to the

labour market.


show sufficient effort in job

search activities.

-If needed, support is offered to enhance job

search skills and specific

vocational training.

Box 1. “Stairway to work” model used by the municipal service for work and income in Amsterdam to re-

integrate clients from welfare-towards-work. Source: SWI Participation Policy 2008-2011

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METHOD

Research as a reintegration programme

The current study holds elements of participatory action research. Collaboration was

developed between the PHS, SWI and a private company specialised in empowerment of long term

unemployed. Together these partners set up a social activation programme aimed at (a) activating

participants a step closer towards the labour market and (b) improving our research by recruiting a

total of fifty single men on welfare from SWI to take part in the research as advisors and ‘peer’-

interviewers. One of the main tasks for participants was to approach and collect survey data from a

random sample of other single men on welfare: ‘peers’.

To safeguard the quality of data collected, in thirteen three hour sessions, participants were

activated and trained in performing structured interviews. Teams of two were formed to conduct the

interviews, so men with language or other problems that could hamper the quality of the survey, could

also participate with help of their “buddy”. Interviews were recorded and based on these recordings,

feedback was given to improve quality.

Study sample and procedures

In January 2009, a sample frame was created from the registration of SWI containing 9200

non institutionalized men, between the age of 23-65, receiving welfare benefits for single person

households, living in a house (1403 men who were registered as homeless/received integrated care

were excluded), and for whom the distance to the labour market was registered.

The 9200 clients included in our sample frame were randomly numbered and subsequently approached

in different rounds. Table 1 shows results from the approach.

Table 1. Results of fieldwork (July 2009 – December 2010)

n %

Non-response before personal approach by peers 596 33%

Excluded from sample: no longer receiving

welfare benefits

170 9%

Refused transfer of personal contact

information from social services to the public health service

426 24%

Non-response after personal approach by peers 732 41%

Refused interview 494 27%

Not reached after at least 20 calls and 6

different house visits at different times and

days of the week

193 11%

Other: deceased, institutionalized, unable to

conduct interview due to disease or language

problems, wrong contact information.

48 3%

Response 472 26%

Interviewed by trained peers 415 23%

Interviewed by professional interviewers 57 3%

Total 1800 100%

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After 10 months of fieldwork (July 2009-May 2010), peer interviewers had personally

interviewed 415 respondents. Respondents still not reached, were re-approached by professional non-

peer interviewers in October - December 2010. In the end, 472 out of 1800 randomly sampled eligible

clients were successfully interviewed (26%).

Reference data

Reference data for single employed men in the general population of Amsterdam (SIM-work;

n=294) were derived from the Amsterdam health survey of 2008[16]. A questionnaire was sent to a

random sample of Amsterdam inhabitants stratified by (1) age and (2) prioritized deprivation areas.

Men living in a single person household (n=463) aged 23 to 64 years were selected from the survey

and individual weights were calculated based on the distribution of age group*deprivation area as

registered[17] for the total population of single men in Amsterdam (N=72,751). Single men reporting

to work > 12 hours per week were selected from the sample (n=294).

Measures

For mental illness, the Kessler Psychological Distress Scale[18] was used to screen for

common mental disorders (anxiety and depression) using a cut off point of >19[19, 20].

For somatic illness, a standard questionnaire of the Dutch population health monitors was

used, measuring 18 of the most common chronic somatic diseases. The cut off was set at two or more

medically diagnosed somatic illnesses in the past 12 months.

For harmful drug use, we incorporated five indicators: (1) harmful drinking: scoring >7 on the

Alcohol Use Disorders Identification Test (AUDIT)[21, 22] (2) daily cannabis use (3) recent

substance abuse: use of heroin, crack, coke, methadone, or GHB, in the past thirty days. Self reported

addiction to alcohol, cannabis or other drugs was taken into account with respective indicators. If (4)

respondents scored positive on any of the three mentioned measures of harmful drug use, they scored

positive on the summery measure of harmful drug use. The only indicator of harmful drug use

comparable with the reference sample is (5) excessive drinking, defined as on average drinking > 21

alcoholic beverages per week.

The indicator for multi-problems was set at two or more of the following three indicators:

mental health, somatic health and excessive drinking.

To measure service use, a standard list in Dutch population health monitors was used to

assess whether or not respondents had contact with the GP, mental health, specialist care and addiction

care in the past 12 months. Having no contact with healthcare at all in the past 12 months was

calculated over a larger variety of possible healthcare contacts including contact with social care, a

dentist, dietician, physiotherapist, speech therapist and receiving home care.

Registered data concerning distance to the labour market between SIM-welfare (1; furthest

away -4;closest) was collected from SWI when creating the sample frame (January 2009).

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Migration history was divided into two categories: (1) ethnic Dutch: man and his parents are

born in the Netherlands; (0) first- or second-generation migrant: man and/or parents are born outside

of the Netherlands.

Low educational level refers to self reported completed education below the level of senior

general secondary, pre-university or senior secondary vocational education. According to Dutch

standards, in accordance with EU norms, this implies having insufficient qualification for accessing

the labour market.

Analysis

In all analyses a p-value <.05 is considered statistically significant. When comparing

characteristics between the total sample of SIM-welfare and SIM-work, without controlling for

differences in background variables, calculated weights were applied to the stratified sample of SIM-

work. Significance of found differences between samples were corrected for the design effect caused

by weights[23].

Binary logistic regression analyses are performed to control for background variables (in

relation illness – distance to labour market) or for illness indicators (in relation service use – distance

to labour market).

RESULTS

Representative sample?

Non response analysis showed no significant differences in level of education, distance to the

labour market and duration of welfare dependence between the response and non response group.

Older men between the age of 55-64 were slightly overrepresented, and men between 23-35 years

were slightly underrepresented.

Composition of the target group

SIM-welfare are distributed over SWI’s stairway to work as follows: step 1, 37:%; step 2,

32%, step 3, 28%; step 4, 3%. Step 3 and 4 are merged in the analyses, because of the small size of

step 4 (n=15).

Table 2 provides descriptives for and comparisons between (subgroups of) SIM-welfare and

SIM-work. Prevalence of somatic and mental illness and service utilization is higher among SIM-

welfare than among SIM-work. SIM-welfare further away from the labour market generally show

higher prevalence of illness, harmful drug use and service use. Also differences in background

variables are found between subgroups.

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Table 2. Description of socio demographics, health, drug use and service utilization compared between single male

welfare recipients with a different distance to the labour market and single employed men in Amsterdam.

Single men receiving welfare benefits in Amsterdam Employed single

men in

Amsterdam†

(SIM-work)

n=294

Step 1

“Care”

n=174

Step 2

“Social

activation”

n=150

Step 3&4

“Re-

employment“

n=148

Total

n=472

Socio-demographic variables

Mean age (sd) 52.2 (8.2)* 49.5 (10.0)* 46.7 (9.6)* 49.6 (9.5)* 40.3 (10.5)

Age categories

23-34 years 2%* 9% 16%* 9%* 33%

35-44 years 20% 22% 21%* 21%* 33%

45-54 years 32% 28%* 41%* 33%* 22%

55-65 years 47% 41%* 23%* 38%* 12%

% Low level of education 53% 59% 48%* 53%* 16%

% Migrant Dutch‡ 47% 58% 68%* 57%* 34%

% History of homelessness 16% 14% 12% 14% n.a.

Median years of work history 12* 10 10 10 n.a.

Years of work history in categories

Never worked 8% 12% 10% 10% n.a.

1-5 years of work 19% 22% 25% 22% n.a.

6-15 years of work 35% 36% 37% 36% n.a.

>15 years of work 39% 30% 29% 33% n.a.

Median years of joblessness (if ever worked). 11* 9* 4 8

Years of joblessness in categories.


=<3 years 13% 16%* 41% 22% n.a.

4-10 years 32%* 43% 36% 37% n.a.

11-15 years 15% 10% 7% 11% n.a.

> 15 years 32%* 20%* 7% 20% n.a.

Health indicators

% Anxiety/depression (K10>19) 54% 54%* 40%* 50%* 26%

% 2+ chronic somatic ilnesses 54%* 39% 33%* 43%* 11%

% Excessive drinking (>21 alc/week) 21% 25%* 12%* 19% 20%

% 2+ of above health indicators 42% 34%* 19%* 32%* 11%

% Harmful drinking (AUDIT > 7) 37% 34%* 23% 32% n.a.

% Daily cannabis use 18% 13% 18% 17% n.a.

% Recent substance abuse 15% 15%* 6% 12% n.a.

% Summery drug use 54% 46% 39% 47% n.a.

Contacts with healthcare in past 12 months

% GP 82%* 73%* 85%* 80%* 64%

% Specialist 65%* 55% 46%* 56%* 29%

% Mental health 24% 22% 13% 20%* 10%

% Addiction care 14%* 6% 6% 9%* 3%

% Social care 18% 17% 15%* 17%* 1%

% No care 4%* 10% 5% 6% 7%

*Significant (p<0,05) difference with proportion (χ²-test), mean (T-test) or median (Mann Whitney-test) one column to the right; for

participants closest to the labour market (step 3&4), comparison is made with employed single men in Amsterdam. †Proportions for SIM-

work are weighted (age*deprivation area) to represent employed (>12h) single men in Amsterdam; significance of differences is corrected

for design-effects of weighs. ‡92% of migrants are first generation migrants with a wide variation of cultural backgrounds.

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Illness, harmful drug use & distance to labour market

Controlled for differences in age, deprivation area, low education and migration history, figure

1 shows a significantly higher odds of anxiety & depression, multiple chronic somatic illnesses and

multi-problems for both the total group of SIM-welfare compared against SIM-work and all subgroups

compared to SIM-work. The difference is largest for the proportion of ill mental health and

insignificant for the percentage of excessive drinkers (omitted from graph).

Illness unmet by service use & distance to labour market

In table 3 is shown that, SIM-welfare are more likely than SIM-work, to have contact with

addiction care (controlled for excessive drinking), mental health care (controlled for mental health)

and specialist care (controlled for multiple chronic somatic illnesses). Comparing between subgroups

of SIM-welfare, further distance to labour market is related to higher odds of service use for mental

and specialist somatic care (controlled for relevant health needs).

3.1

4.6

2.72.5

4.0

5.4 5.3

2.4

3.8

5.4

4.4

1.9

0

1

2

3

4

5

6

7

8

9

10

total step 1 step 2 step 3 total step 1 step 2 step 3 total step 1 step 2 step 3

OR

2+ somatic ilnesses Mental health problem Multi health problem

Figure 1. OR and confidence intervals for prevalence of health problems and harmful drug use for (subgroups of)

single men on welfare compared against single men working > 12 hours/week in Amsterdam; controlled for

differences in age, deprivation area, low education and migration history

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Table 3. Use of health services, controlled for relevant health needs and socio demographic background variables,

contrasted between SIM-welfare and SIM-work (model 1) and between SIM-welfare with a different distance to the

labour market (model 2).

DISCUSSION

The primary objective in this study was to describe the expectedly vulnerable population of

single male welfare recipients (SIM-welfare) from a public health and vocational perspective.

SIM-welfare were found to be a population of older (mean 49.6), often low educated (53%),

mostly long term workless men (median 8 years), with considerable health problems: 43% multiple

somatic illnesses, 50% anxiety & depression; 47% harmful drug use; 32% multi-problems. Also, 14%

of SIM-welfare had experienced a spell of homelessness in their lives. Apparently, a substantial

proportion of housed SIM-welfare, constitute former rough sleepers who can now fulfil basic needs

(roof and income from welfare benefits), but have not found employment.

Judged from how SIM-welfare are stratified on SWI’s stairway to work, their labour market

position is mostly one of economic inactivity as 96% are judged not readily available to the labour

market. The majority (69%) are judged to take distant positions from the labour market and are either

exempted from vocational progress and subject to case-first care (37%) or low threshold participation

programs (32%).

To gain insight in the degree and nature of health related problems that might restrict

participation on the labour market, relative vulnerability was determined in relation to distance to the

labour market as reflected by SWI’s stairway to work.

Binary logistic regression models

Contact with healthcare services in past 12 months (1=yes)

GP SPECIALIST

CARE

MENTAL

HEALTH

CARE

ADDICTION

CARE NO CARE

(exp)B (95% CI) (exp)B (95% CI) (exp)B (95% CI) (exp)B (95% CI) (exp)B (95% CI)

Model 1 Predictors of service utilization

Controlled for

relevant health

needs

Chron2+ 4.1 (2.4-7.0) 5.0 (3.4-7.4) 0.2 (0.1-0.6)

K10>19 2.1 (1.4-3.2) 4.2 (2.6-6.8) 0.5 (0.2-1.0)

Drink>21 0.4 (0.3-0.7) 6.0 (1.4-26.2) 2.3 (1.2-4.4)

Welfare SIM-welfare ns 1.0 1.9 (1.3-2.8) 2.9 (1.6-5.3) 5.6 (1.6-20.3) ns 1.3

SIM-work (ref) 1 1 1 1 1

Model 2 Predictors of service utilization

Controlled for

relevant health

needs

Chron2+ 6.0 (2.8-13.0) 5.0 (3.2-7.8) 0.2 (0.0–0.8)

K10>19 2.6 (1.3-5.1) 4.1(2.3-7.2) ns, 0.4

Drink>21 0.4 (0.2-0.8) 0.2 (0.0-1.8) 3.0 (1.0-9.0)

cannabis ns, 0.6 Ns; 2.0 ns, 1.6

Recent substance use ns, 0.7 4.0 (1.4-11.3) ns, 1.2

Distance to labour

market Step 1 “care” ns 0.8 1.8 (1.0-3.0) 2.3 (1.2-4.7) ns 3.2 ns, 1.0

Step 2 “social

activation” ns 0.5 ns 1.5 2.0 (1.0-4.1) ns 1.6 ns, 2.6

Step 3&4 (ref) “re-

employment” 1 1 1 1 1

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Illness, drug use & distance to labour market

Stratifying SIM-welfare along SWI’s stairway to work proved useful as it reflected not only

differences in age and duration of joblessness, but also significant health differences. It was found that

one step up, from the “care” category, to the “social activation” category, was mainly a step up in

somatic health. Again one step closer to the labour market, to the “re-employment” category of

increased pressure and opportunity to participate, SIM-welfare showed less mental health problems,

less drug use and less combined health problems but were still worse of on all health indicators

compared to SIM-work.

Found health disadvantages among SIM-welfare compared to SIM-work, are in line with

mechanisms of causation and health-selection mostly supported by findings from studies[6-9] in which

workers are compared to the unemployed, especially for mental health. What seems out of line, are the

substantial barriers somatic illnesses seem to pose.

Adding somatic illnesses to the equation of combined health problems and disadvantaged

human capital, is most likely to put clients in a position in which vocational improvement is of

secondary importance (eg. little return on investment) and the main priority is to improve/stabilise

health (financed from other funds). Somatic illnesses may pose a more important barrier for

(involuntary) inactive populations than for unemployed populations and as such seem to ask for

attention in research and policy towards the group.

For harmful drug use, comparison with SIM-work was limited to differences in the prevalence

of excessive drinking, which were insignificant. More studies report small or insignificant differences

in excessive or hazardous drinking between employed and unemployed populations but a higher

prevalence for alcohol dependence, illicit drug use and cannabis use, is generally found[24]. Adequate

reference data on drug use indicators among SIM-work are needed to further elaborate on this. Since

recent substance abuse and excessive drinking were related to distance to the labour market, we

conclude that harmful drug use among SIM-welfare is likely to form a barrier towards re-employment

and as such, might need attention in vocational policy towards this group.

Illness unmet by service use & distance to labour market

Controlled for (relevant) health problems and background variables, SIM-welfare were found

more likely to have healthcare contacts than SIM-work.

Since we did not correct for severity of health problems, the finding might reflect that health

problems among SIM-welfare are more severe. Other studies[25-27], with correction for severity also

showed higher service use for jobless populations, compared to the employed. As an explanation for

higher service use, Honkonen et al.[25] point to the extra time jobless individuals have and the strong

linkages between healthcare and the welfare agency. These supportive findings, make it unlikely that

controlling for severity of symptoms, would have yielded opposite results. In terms of unmet needs,

SIM-welfare seem no more vulnerable than SIM-work.

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Not accessing healthcare, while this is needed from a health professionals’ perspective, might

still be one of the explanations why single men are overrepresented among the homeless. Future

research comparing for instance single men with non-single men or single men against single woman

might shed more light on this.

Generalising findings

In this study, extra effort was put into creating a representative sample of a population which

is hard to reach. On average, clients not reached, were visited at least 6 times at their homes and

contacted 20 times by telephone. This led to a 26% response rate, which demonstrates that this specific

group would probably be missed in general (health) surveys.

Although particular subgroups might be underrepresented in the sample, the non-response

analysis showed accurate representation on compared variable and authors are unaware of studies to

date with better response rates among this particular group, voluntarily interviewed outside the welfare

setting.

Generalisibility of findings across time and space, is limited, but seems accurate for other

urban settings with mixed ethnicities, health care with low financial barriers and universal entitlements

to welfare benefits enabling to fulfil basic needs.

Conclusion & Policy implications

Findings confirm that a public health perspective is appropriate for this group. And that

transitions from welfare towards work among SIM-welfare, applies to the further rehabilitation of a

substantial group of former rough sleepers towards work.

Mental health, somatic illnesses and harmful drug use seem important components in personal

barriers hindering participation on the labour market. These findings underline the importance of a

rehabilitation perspective on welfare-towards-work policy taking these health barriers into account.

Since relative vulnerability in terms of unmet needs was not found among welfare clients,

promoting access of healthcare seems no more a priority among single male welfare recipients than

among single male workers.

SWI’s “stairway to work” shows that clients can be stratified along dimensions reflecting both

health needs (eg barriers) and traditional human capital indicators. With these kinds of classifications

it seems possible to stratify clients and expose them to programmes in which a mix of health

promotion, labour market activation and care is balanced towards adequately improving both

vocational progress, health and possibly preventing homelessness. In Amsterdam, the perspectives of

“care” and vocational progress hardly seem to mix. Adding vocational perspectives to case-first-care,

and rehabilitation care perspectives to re-employment practices, could improve both health and re-

employment outcomes.

More research from this integrated perspective is asked for, to distinguish effective and

economically feasible policy interventions promoting both health and labour market participation. A

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theoretical framework in which vocational and rehabilitation research are integrated and linked to

local policy (interventions), seems necessary to draw synthesis from international knowledge on the

subject and create a common framework inter-disciplinary professionals can work on.

Acknowledgements: The authors thank the peer interviewers for their effort and perseverance during

data collection. The Service for Work and Income, Amsterdam Statistics and Radar Advies are

thanked for their corporation.

Funding: ZONmw, Public health service Amsterdam, Municipal Service for Work & Income

Amsterdam, ACHMEA healthcare insurance.

Conflicting interests: None declared

Contributorship:

T.C.Kamann contributed to the study design, coordinated data collection, helped train peer

interviewers, performed analysis and wrote the article.

M.de Wit, initiated the research, contributed to study design, analysis and commented on

article.

S.Cremer, contributed to the study design and commented on article

AJ Beekman, contributed to the study design and made important contributions to the

article.

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REFERENCES

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London: Department for Communities and Local Government 2007:17

2 Stephens M., Fitzpatrick S, Elsinga M, et al. Study on Housing Exclusion: Welfare Policies,

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3 European Union. http://ec.europa.eu/europe2020/pdf/themes/25_poverty_and_social_inclusion.pdf

(accessed on Jan 17 2013)

4 Buster MCA, Hensen M, De Wit M et al. Feitelijk dakloos in de G4. GGD Amsterdam, GGD Rotterdam-Rijnmond, GGD Den Haag, GG&GD Utrecht 2012

5 Edgar B. European Review of Statistics on Homelessness. Brussels: FEANTSA 2009;6-10.

6 McKee Ryan F, Song Z, Wanberg CR, et al. Psychological and physical well-being during

unemployment: A meta-analytic study. J Appl Psychol 2009;90:53-75

7 Paul KI, Moser K. Unemployment impairs mental health: Meta-analyses. J Vocat Behav

2009;74:254-282.

8 Wanberg CR. The individual experience of unemployment. Annu Rev Psychol 2012;63:369-396.

9 Waddell G, Burton K. Is working good for your health and well-being? Cardiff & Huddersfield:

Cardiff University & University of Huddersfield 2006.

10 Statistics Netherlands; Statline database: http://statline.cbs.nl/statweb/?LA=en (accessed on June

20 2013)

11 Municipal Service for Work & Income Amsterdam; Client Registration January 2009

12 Jahoda M. Employment and unemployment: a social-psychological analysis. Cambridge: Cambridge Univeristy Press 1982.

13 Warr P. Work, unemployment, and mental health. Oxford:Clarendon Press 1987.

14 Perkins D. Improving Employment Participation for Welfare Recipients Facing Personal Barriers.

Social Policy and Society 2008;7:13-26.

15 Koen J, Klehe UC, Vianen A van. Competentieontwikkeling & Re-integreerbaarheid van DWI

Klanten. Amsterdam: UvA 2008.

16 Dijkshoorn H, Dijk TK van, Janssen AP. Zo gezond is Amsterdam!: eindrapport Amsterdamse

Gezondheidsmonitor 2008. Amsterdam: GGD Amsterdam, 2009.

17 Municipal Personal Records Database Amsterdam; January 2010

18 Kessler RC, Barker PR, Colpe LJ, et al. Screening for serious mental illness in the general

population. Arch Gen Psychiat 2003;60:184-189.

19 Andrews G, Slade T. Interpreting scores on the Kessler Psychological Distress Scale (K10) Aust N

Z J Public Health 2001;25:494–497.

20 Victorian Government. Victorian population health survey 2001: selected findings. Melbourne:

Department of Human Services, 2002.

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21 Babor TF, Higgins-Biddle JC, Saunders JB, et al. AUDIT: the Alcohol Use Disorders Identification

Test: guidelines for use in primary care. Geneva: World Health Organization, 2001.

22 Conigrave KM, Hall WD, Saunders JB. The AUDIT questionnaire: choosing a cut-off score:

Alcohol Use Disorders Identification Test. Addiction 1995;90:1349-1356.

23 Kish l, Weighting for Unequal Pi, Journal of Official Statistics 1992;8:183–200

24 Henkel D. Unemployment and substance use: a review of the literature (1990-2010). Curr Drug

Abuse Rev 2011;4:4-27.

25 Honkonen T, Virtanen M, Ahola K, et al. Employment status, mental disorders and service use in

the working age population. Scand J Work Environ Health 2007;33:29–36.

26 Bijl RV, Ravelli A. Psychiatric morbidity, service use, and need for care in the general population:

results of the Netherlands Mental Health Survey and Incidence Study. Am J Public Health

2000;90:602–7.

27 Kraut A, Mustard C, Walld R, et al. Unemployment and health care utilization. Scand J Work

Environ Health 2000;26:169–77.

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Health, Drugs & Service use among deprived Single Males: comparing (subgroups) of single male welfare

recipients against employed single men in Amsterdam.

Journal: BMJ Open

Manuscript ID: bmjopen-2013-004247.R1


Date Submitted by the Author: 13-Dec-2013




Public health




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1

Health, Drugs & Service use among deprived Single Males: comparing 1

(subgroups) of single male welfare recipients against employed single men 2

in Amsterdam. 3

4

Authors: T.C.Kamann - M.A.S. de Wit - S. Cremer – A.T.F Beekman 5

Primary subject heading: PUBLIC HEALTH 6

Secondary subject heading: REHABILITATION MEDICINE 7

Keywords 8

EPIDEMIOLOGY 9

PUBLIC HEALTH 10

MENTAL HEALTH 11

SOMATIC HEALTH 12

SERVICE USE 13

UNEMPLOYMENT 14

15

Affiliations 16

Tjerk C. Kamann; Academic Collaborative Urban Social Exclusion Research (USER-G4); Public 17

Health Service Amsterdam, department of Epidemiology, Documentation and Health Promotion, VU 18

Medical Center, department of psychiatry. 19

20

Dr. Matty A.S. de Wit; Public Health Service Amsterdam, department of Epidemiology, 21

Documentation and Health Promotion; Netherlands. 22

23

Stephan Cremer; Public Health Service Amsterdam, department of Epidemiology, Documentation 24

and Health Promotion; Netherlands. 25

26

Prof. dr. Aartjan T.F Beekman; VU Medical Center, department of psychiatry; Amsterdam, 27

Netherlands 28

29

Corresponding author: 30

Tjerk C. Kamann 31

PO BOX 2200; 1000 CE, Amsterdam, Netherlands 32

Email: [email protected] 33

Tel: +31 622728815 34

Fax: +31 205555160 35

Word count: 36

Abstract: 300 words; Main document: 4001 words 37

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2

ABSTRACT 1

2

Objectives 3

To aid public health policy in preventing severe social exclusion (like homelessness) and promoting 4

social inclusion (like labour market participation), we aimed to quantify (unmet) health needs of an 5

expectedly vulnerable population little was known about: single male welfare recipients (SIM-6

welfare). One of the main policy questions was: is there need to promote access to healthcare for this 7

specific group? 8

Design 9

A cross-sectional study incorporating peer-to-peer methodology to approach and survey SIM-welfare. 10

Socio-demographics, prevalence of ill health, harmful drug use and healthcare utilization for 11

subgroups of SIM-welfare asssessed with a different distance to the labour market, and exposed to 12

different reintegration policy were described and compared against single employed men (SIM-work). 13

Setting 14

Males between the age of 23-64, living in single person households in Amsterdam. 15

Participants 16

A random and representative sample of 472 SIM-welfare was surveyed during 2009-2010. A reference 17

sample of 212 SIM-work was taken from the 2008 Amsterdam Health Survey. 18

Outcome measures 19

Standardised instruments were used to assess self-reported ill somatic and mental health, harmful drug 20

use and service use. 21

Results 22

SIM-welfare are mostly long term jobless, low educated, older men; 70% are excluded from re-23

employment policy due to multiple personal barriers. Health: 50% anxiety & depression; 47% harmful 24

drug use; 41% multiple somatic illnesses. Health differences compared to SIM-work: (1) controlled for 25

background characteristics, SIM-welfare report more mental (OR 4.0; 95%CI 2.1 to 4.7) and somatic 26

illnesses (OR 3.1; 95%CI 2.7 to 6.0); (2) SIM-welfare assessed with the largest distance to the labour 27

market report most combined health problems. Controlled for ill health, SIM-welfare are more likely 28

to have service contacts than SIM-work. 29

Conclusion 30

SIM-welfare form a selection of men with disadvantaged human capital and health. Findings do not 31

support a need to improve access to health care. The stratification of welfare clients distinguishes 32

between health needs. 33

34

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3

ARTICLE SUMMARY 1

2

3 4

Article Focus





is undocumented



Key Messages











are aware of.







health differences.

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4

INTRODUCTION 1

2

In this study we aim to describe some demographics and quantify (unmet) health needs for an 3

expectedly vulnerable population that has remained below the epidemiological radar: single male 4

welfare recipients. With this information we aim to assist public (health) policy in preventing severe 5

social exclusion (like homelessness) and promoting social inclusion (like labour market participation) 6

7

Why target single men on welfare (SIM-welfare)? 8

Within every society, there is a group of people who are not able to sufficiently access and 9

mobilize personal and social resources to meet life’s necessities. For some reason, especially single 10

men are over represented among the most severely excluded individuals of society. 11

Homelessness, for instance is a form of severe material deprivation associated with higher 12

mortality rates, adverse health outcomes and substance abuse[1-5]. In cities throughout Europe and 13

other OECD countries, most homeless rough sleepers are single men (SIM), in the middle age range, 14

with addictions and other health problems[6]. The dominance of this profile among the homeless can 15

be considered “one of the strongest comparative findings on homelessness in Europe that exists”[7]. 16

Also in the Netherlands, with accessible healthcare and relatively high expenditure on social 17

security[8], individuals falling through social safety nets, are mostly single men. In the four largest 18

Dutch cities, 90% of the homeless are men, mostly single[9]. 19

These most marginalized people like the homeless and severe drug addicts are targeted as 20

client groups for (individual) Public Mental Healthcare (PHMC). Clients receiving individual PMHC 21

are typically homeless, drug addicted and/or suffering from severe mental disorders, but more broadly, 22

individual PMHC is aimed at individuals who are in an unacceptable health condition and social 23

situation, from a healthcare’s perspective, but who for whatever reason fail to access private (regular) 24

care and support to meet these needs by themselves, and therefore need outreaching, often integrated 25

care. In Amsterdam, between 2006 – 2011, single men represented 80% of clients receiving integrated 26

Public Mental Healthcare (PMHC)[10] 27

PMHC does not only operate at the individual level. At a risk group-level, PMHC-services are 28

concerned with the prevention of psychosocial deterioration in specific subgroups subject to risk-29

factors such as long-term unemployment, social isolation, and psychiatric disorders[11]. In this study, 30

single jobless males residing in the last safety net of Dutch social security are put forward as a specific 31

subgroup where such risk factors are expected to accumulate: single male welfare recipients (SIM-32

welfare). 33

Before stating our research questions we first (1) describe some common characteristics of 34

SIM-welfare and then (2) distinguish between subgroups of SIM-welfare exposed to a different policy 35

context. 36

37

38

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5

Characteristics of the target group 1

In the Netherlands, all citizens who do not manage to provide themselves with sufficient 2

income, are eligible for income support. In Amsterdam, like in the rest of the Netherlands, one third of 3

working age welfare recipients are men living in single person households[12]. In January 2009 this 4

group totalled 10.270 single men in Amsterdam[12]. Common characteristics of SIM-welfare we study 5

are (a) running a single person household - they all have a roof over their head and live there alone (b) 6

being dependent on welfare benefits set at around 70% of minimum wages – they belong to the 7

poorest people in the Netherlands (c) having no paid job – they might miss out on immaterial benefits 8

of performing a job like the time structure, status and social contacts[13, 14] and perhaps most 9

importantly (d) SIM-welfare are all registered at and in contact with the municipal agency responsible 10

for providing welfare services in Amsterdam (the municipal Service for Work and Income - SWI): 11

SIM-welfare can be found and targeted for specific interventions. 12

13

Policy context: subgroups 14

Within the population of SIM-welfare, subgroups of SIM-welfare can be distinguished that 15

are (a) exposed to different reintegration policy and (b) probably have different health needs. 16

Both from a public health perspective and from a vocational welfare-to-work perspective, 17

finding re-employment can be considered a desired rehabilitation outcome [15, 16]. To cater for the 18

diversity in reintegration needs among the heterogeneous population of welfare clients, SWI assesses 19

clients ‘distance to the labour market’ based on clients’ demographics, human capital indicators, 20

health problems and other personal barriers hindering re-employment. Based on the assessment, 21

clients are positioned on a “stairway to work” ranging from step 1 (largest distance to labour market) 22

to step 4 (smallest distance to the labour market). Clients on different steps are shown to differ in 23

employability[17] and are exposed to different re-integration policies (see box 1 for a description). 24

25

26

Step 1. “Care”

-Personal barriers like illness and addiction need






through referral.




activation.



social activation


individual needs.



placement on labour

market.



programmes to learn basic employment skills (coming

in time, accepting



education.



labour market.



search activities.

-If needed, support is

offered to enhance job





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6

To aid prevention of psychosocial deterioration, unfavoured dropout from society and it’s 1

costly remedy –integrated PMHC--, between 2009-2012 a cohort study was set up to assess the needs 2

among the hypothesised risk group of SIM-welfare. In the present manuscript, first results from this 3

study at baseline are presented. 4

5

Finding place? 6

We aim to put this group on the epidemiological map by describing socio demographics, 7

prevalence of ill health harmful drug use and healthcare use. These prevalences are useful for welfare-8

to-work-policy, public health policy and other studies in need of hard to reach reference groups. 9

10

Disadvantaged health? 11

From common characteristics of SIM-welfare, we can hypothesise health disadvantages. The 12

association between unemployment and ill health is well established in the scientific literature. Due to 13

combined mechanisms of health selection (disadvantaged health restricts labour market participation 14

and increases risk of job loss) and social causation (exposure to involuntary joblessness and its 15

material and immaterial disadvantages has a negative effect on health), we expect a selection of single 16

men with disadvantaged human capital, health and addiction problems[18-21]. We test whether indeed 17

SIM-welfare have disadvantaged health and harmful drug use compared to SIM-work. 18

19

Disadvantaged service use? 20

To prevent possible psychosocial deterioration resulting in a need for costly outreaching 21

individual PMHC at a later stage we ask: do we find evidence suggesting a need to improve access to 22

healthcare for this specific group? 23

24

Useful subgroups? 25

We examine whether subgroups (a) assessed with a different distance to the labour market and 26

(b) exposed to different reintegration policy, also differ in (unmet) health needs. If so, this 27

classification might also be useful for a differentiation in public health interventions. Also, it provides 28

us with insight, as to what specific health needs are more and less associated with distance to the 29

labour market, as assessed by SWI. 30

31

Objectives 32

1. Describe (subgroups) of SIM-welfare in terms of socio demographics, prevalence of ill health, 33

drugs misuse, and healthcare use. 34

2. Analyse risk for ill health and harmful druguse for (subgroups of) SIM-welfare compared to SIM-35

work (controlled for socio demographic background variables) 36

3. Analyse risk for service use for (subgroups of) SIM-welfare compared to SIM-work (controlled 37

for socio demographic background variables and relevant health needs) 38

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7

METHOD 1

Research as a reintegration programme 2

The current study holds elements of participatory action research. Collaboration was 3

developed between the Public Health Service (PHS), SWI and a private company specialised in 4

empowerment of long term jobless people. Together these partners set up a social activation 5

programme aimed at (a) activating participants a step closer towards the labour market and (b) 6

improving our research by recruiting a total of fifty single men on welfare from SWI to take part in the 7

research as advisors and ‘peer’-interviewers. One of the main tasks for participants was to approach 8

and collect survey data from a random sample of other single men on welfare: ‘peers’. 9

To safeguard the quality of data collected, in thirteen three hour sessions, participants were 10

activated and trained in performing structured interviews. Teams of two were formed to conduct the 11

interviews, so men with language or other problems that could hamper the quality of the survey, could 12

also participate with help of their “buddy”. Interviews were recorded and based on these recordings, 13

feedback was given to improve quality. 14

15

Study sample and procedures 16

In January 2009, a sample frame was created from the registration of SWI containing 9200 17

non institutionalized men, between the age of 23-65, receiving welfare benefits for single person 18

households, living in a house (1403 men who were registered as homeless/received integrated care 19

were excluded), and for whom the distance to the labour market was registered. 20

The 9200 clients included in our sample frame were randomly numbered and subsequently approached 21

in different rounds. Table 1 shows results from the approach. 22

23


n %



welfare benefits

170 9%



426 24%





days of the week

193 11%




48 3%

Response 472 26%



Total 1800 100%

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8

1

After 10 months of fieldwork (July 2009-May 2010), peer interviewers had personally 2

interviewed 415 respondents. Respondents still not reached, were re-approached by professional non-3

peer interviewers in October - December 2010. In the end, 472 out of 1800 randomly sampled eligible 4

clients were successfully interviewed (26%). 5

6

Reference data 7

Reference data for single employed men in the general population of Amsterdam (SIM-work; 8

n=294) were derived from the Amsterdam health survey of 2008[22]. A questionnaire was sent to a 9

random sample of Amsterdam inhabitants stratified by (1) age and (2) prioritized deprivation areas. 10

The Amsterdam monitor was based on a random sample of 13.600 adults from the municipal 11

population register, stratified by borough and age, who were invited by mail to complete a 12

written or digital questionnaire in Dutch or Turkish language. Extensive effort was made to 13

urge citizens of minority groups to respond to the survey: non-responders received follow-up 14

letters, phone-calls and house-visits and were offered personal help to fill in the questionnaire. 15

The overall response was 50%, with higher response rates in women, elder persons, native 16

Dutch citizens and residents of deprived neighbourhoods. 17

Men living in a single person household (n=463) aged 23 to 64 years were selected from the 18

survey and individual weights were calculated based on the distribution of age group*deprivation area 19

as registered[23] for the total population of single men in Amsterdam (N=72,751). Single men 20

reporting to work > 12 hours per week were selected from the sample (n=294). 21

22

Measures 23

For mental illness, the 10-item Kessler Psychological Distress Scale (K10)[24] was used to 24

screen for common mental disorders (anxiety and depression) using a cut off point of ≥20[25, 26]. On 25

5-point Likert-type scales, individuals indicate the degree to which symptoms of psychological 26

distress are present (1; none of the time) (5; all of the time). With the chosen cut-off point of ≥20 on 27

the aggregate scale, the Dutch version of the K10 was shown to reach a sensitivity of 0.80 and a 28

specificity of 0.81 for any depressive and/or anxiety disorder as assessed with the Composite 29

International Diagnostic Interview [27]. 30

For somatic illness, a standard questionnaire of the Dutch population health monitors was 31

used. A list of 18 common chromatic somatic illnesses was presented to participants (high blood 32

pressure, diabetes, arthritis, cancer, stroke…). The number of self reported medically diagnosed 33

somatic illnesses was counted and dichotomized at a cut off count of ≥2. 34

For harmful drug use, we incorporated five indicators: (1) harmful drinking: alcohol 35

consumption that is actually or potentially related to current social and medical problems is commonly 36

measured with the Alcohol Use Disorders Identification Test (AUDIT)[28] With a cut off score of 37

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9

≥8, the AUDIT is shown to provide good sensitivity and specificity in the detection of current social 1

and medical problems related to alcohol[29]. (2) daily cannabis use (3) recent substance abuse: use of 2

heroin, crack, coke, methadone, or GHB, in the past thirty days. Self reported addiction to alcohol, 3

cannabis or other drugs was taken into account with respective indicators. If (4) respondents scored 4

positive on any of the three mentioned measures of harmful drug use, they scored positive on the 5

summery measure of harmful drug use. The only indicator of harmful drug use comparable with the 6

reference sample is (5) excessive drinking, defined as on average drinking > 21 alcoholic beverages 7

per week. 8

The indicator for multi-problems was set at two or more of the following three indicators: 9

mental illness, somatic illness and excessive drinking. 10

To measure service use, a standard list in Dutch population health monitors was used to 11

assess whether or not respondents had contact with the GP, mental health, specialist care and addiction 12

care in the past 12 months. Having no contact with healthcare at all in the past 12 months was 13

calculated over a larger variety of possible healthcare contacts including contact with social care, a 14

dentist, dietician, physiotherapist, speech therapist and receiving home care. 15

SIM-welfare’s current position on SWI’s stairway to work (1; largest distance to labour 16

market - 4; smallest distance to labour market) was collected from the SWI registry when creating the 17

sample frame (January 2009). 18

Migration history was divided into two categories: (1) ethnic Dutch: man and his parents are 19

born in the Netherlands; (0) first- or second-generation migrant: man and/or parents are born outside 20

of the Netherlands. 21

Low educational level refers to self reported completed education below the level of senior 22

general secondary, pre-university or senior secondary vocational education. According to Dutch 23

standards, in accordance with EU norms, this implies having insufficient qualification for accessing 24

the labour market. 25

26

Analysis 27

In all analyses a p-value <.05 is considered statistically significant. 28

When comparing characteristics between (subgroups of) SIM-welfare and SIM-work, without 29

controlling for differences in background variables, calculated weights were applied to the stratified 30

sample of SIM-work. Significance of found differences between samples were corrected for the design 31

effect caused by weights[30]. When testing for disadvantaged health and drugs misuse of (subgroups 32

of) SIM-welfare compared to SIM-work, binary logistic regression analyses were performed in which 33

background variables were entered as control variables. When testing for disadvantaged health service 34

utilisation of (subgroups of) SIM-welfare compared to SIM-work, binary logistic regression analyses 35

were performed to in which differences in specific service use (for instance mental healthcare) were 36

controlled for differences in relevant health needs (for instance mental illness) and background 37

variables. 38

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RESULTS 1

2

Representative sample? 3

Non response analysis showed no significant differences in level of education, distance to the 4

labour market, duration of welfare dependence and frequency of contacts with social services between 5

the response and non response group. The distributions of all these variables, closely resemble the 6

‘true’ distributions as registered for the research population (eg. the sample frame; n=9200). Only 7

for age we find a significant over representation of older men in the reponse group. Older men 8

between the age of 55-64 were slightly overrepresented, and men between 23-35 years were slightly 9

underrepresented in the response sample. See Table A.1 in the Appendix for detailed information 10

concerning the non-response. 11

12

Composition of the target group 13

SIM-welfare are distributed over SWI’s stairway to work as follows: step 1, 37:%; step 2, 14

32%, step 3, 28%; step 4, 3%. Step 3 and 4 are merged in the analyses, because of the small size of 15

step 4 (n=15). 16

Table 2 provides descriptives for and comparisons between (subgroups of) SIM-welfare and 17

SIM-work. Prevalence of somatic and mental illness and service utilization is higher among SIM-18

welfare than among SIM-work. SIM-welfare in subgroups assessed with a larger distance to the 19

labour market generally show higher prevalence of illness, harmful drug use and service use. Also 20

differences in background variables are found between subgroups. 21

22

Table 2. Description of socio demographics, health, drug use and service utilization compared between single male 23

welfare recipients assessed with a different distance to the labour market and single employed men in Amsterdam. 24


men in

Amsterdam†

(SIM-work)

n=294

Step 1

“Care”

n=174

Step 2

“Social

activation”

n=150

Step 3&4

“Re-

employment“

n=148

Total

n=472


Mean age (sd) 52.2 (8.2)* 49.5 (10.0)* 46.7 (9.6)* 49.6 (9.5)* 40.3 (10.5)

Age categories

23-34 years 2%* 9% 16%* 9%* 33%

35-44 years 20% 22% 21%* 21%* 33%

45-54 years 32% 28%* 41%* 33%* 22%

55-65 years 47% 41%* 23%* 38%* 12%


% Migrant Dutch‡ 47% 58% 68%* 57%* 34%





1-5 years of work 19% 22% 25% 22% n.a.

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6-15 years of work 35% 36% 37% 36% n.a.

>15 years of work 39% 30% 29% 33% n.a.




=<3 years 13% 16%* 41% 22% n.a.

4-10 years 32%* 43% 36% 37% n.a.

11-15 years 15% 10% 7% 11% n.a.

> 15 years 32%* 20%* 7% 20% n.a.

Health indicators










% GP 82%* 73%* 85%* 80%* 64%

% Specialist 65%* 55% 46%* 56%* 29%

% Mental health 24% 22% 13% 20%* 10%

% Addiction care 14%* 6% 6% 9%* 3%

% No care 4%* 10% 5% 6% 7%





1


Controlled for differences in age, deprivation area, low education and migration history, table 3

3 shows a significantly higher risk of ill mental health, somatic illness and multi-problems for the 4

total group of SIM-welfare and each of the subgroups compared against SIM-work. The difference is 5

insignificant for the percentage of excessive drinkers and largest for the proportion of ill mental health. 6

Except for excessive drinking, risks generally increase for subgroups assessed with an 7

increasing distance to the labour market, i.e. subgroups on lower steps of SWI’s stairway to work. 8

This increase in risk is especially incremental for multi-problems. For somatic illness the highest risk 9

is observed in subgroup 1. For mental illness similarly high risk are observed in subgroup 1 and 2. 10

11

Table 3. Risk of ill health and excessive drinking for (subgroups of) single men on welfare compared against

employed single men in Amsterdam; controlled for differences in age, deprivation area, low education and

migration history.

OR (95% CI) P

SOMATIC ILLNESS

Employed single men (n=294) 1

Single men on welfare; total group (n=472) 3.11 (2.06- 4.71) <.001

Single men on welfare; stairway to work step 1 4.42 (2.72- 7.20) <.001

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MENTAL ILLNESS






EXCESSIVE DRINKING


Single men on welfare; total group (n=472) .89 (.57- 1.40) .622

Single men on welfare; stairway to work step 1 .83 (.47- 1.46) .515

Single men on welfare; stairway to work step 2 1.42 (.81- 2.48) .227


MULTI-PROBLEM*





Single men on welfare; stairway to work step 3 2.04 (1.13- 3.69) .018

1

2 3

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In table 4 is shown that controlled for differences on socio-demographic background variables, 2

SIM-welfare are more likely than SIM-work, to have contact with addiction care (controlled for 3

excessive drinking), mental health care (controlled for mental illness) and specialist care (controlled 4

for somatic illness). 5

Comparing between subgroups of SIM-welfare, further distance to labour market is related to 6

higher odds of service use for mental and specialist somatic care (controlled for relevant health needs). 7

8

Table 4. Use of health services, contrasted between SIM-welfare and SIM-work (model 1) and between subgroups of 9

SIM-welfare with a different distance to the labour market (model 2), controlled for differences in relevant health 10

needs and socio demographic background variables 11

12

13

DISCUSSION 14

The primary objective in this study was to put the expectedly vulnerable population of single 15

male welfare recipients (SIM-welfare) on the epidemiological map by describing socio demographic 16

characteristics, prevalence of ill health and harmful drug use. With this, we aimed to assist both 17

public (mental) health policy and welfare-to-work policy to gain insight in this population so little is 18

known about. 19

20

Finding place? 21

SIM-welfare were found to be a population of older (mean 49.6), often low educated (53%), 22

mostly long term workless men (median 8 years), with considerable health problems: 43% multiple 23

somatic illnesses, 50% anxiety & depression; 47% harmful drug use; 32% multi-problems. Also, 14% 24

of SIM-welfare had experienced a spell of homelessness in their lives. Apparently, a substantial 25



GP SPECIALIST

CARE

MENTAL

HEALTH

CARE

ADDICTION

CARE NO CARE

OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)

Model 1: comparing SIM-welfare to SIM-

work*


SIM-work 1 1 1 1 1

Model 2: comparing between sungroups of

SIM-Welfare **

Distance to labour


Step 2 “social


Step 3&4 “re-


*All analyses were conducted with control variables: age; education; deprivation area; migration history

*Relevant health variables controlled for in model 1: GP; mental illness; somatic illness, excessive drinking; Specialist care: somatic illness;

Mental health care; mental illness; Addiction care; excessive drinking; No care; mental illness; somatic illness, excessive drinking .

** Relevant health variables controlled for in model 2: Same as model 1 except Control variables entered in model 2; GP; Specialist vare:

Mental health care’addiction care; no care.

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proportion of housed SIM-welfare, constitute former rough sleepers who can now fulfil basic needs 1

(roof and income from welfare benefits), but have not found employment. 2

Judged from how SIM-welfare are stratified on SWI’s stairway to work, their labour market 3

position is mostly one of economic inactivity as 96% are judged not readily available to the labour 4

market. The majority (69%) are judged to take distant positions from the labour market and are either 5

exempted from vocational progress and subject to case-first care (37%) or low threshold participation 6

programs (32%). 7

8

To gain insight in the degree and nature of health disadvantages and disadvantaged healthcare 9

utilisation for health needs, we compared single men on welfare with employed single men. In 10

addition, we studied whether subgroups assessed with a larger distance to the labour market, were also 11

more vulnerable from a public health perspective. If so, the classification used to differentiate 12

reintegration policy, might also be used to differentiate public health inventions. 13

14


As expected, health disadvantages among SIM-welfare compared to SIM-work are substantial 16

and in line with mechanisms of causation and health-selection mostly supported by findings from 17

studies[18-20] in which workers are compared to the unemployed, especially for mental health. 18

For harmful drug use, comparison with SIM-work was limited to differences in the prevalence 19

of excessive drinking, which were insignificant. More studies report small or insignificant differences 20

in excessive or hazardous drinking between employed and unemployed populations but a higher 21

prevalence for alcohol dependence, illicit drug use and cannabis use, is generally found[21]. 22

Adequate reference data on drug use indicators among SIM-work are needed to further elaborate on 23

this. 24

25


We aimed to asses unmet normative needs, to find evidence for normative health needs, single 27

men might not recognise or act upon by seeking out healthcare. No evidence was found for a higher 28

proportion of unmet needs among SIM-welfare compared to SIM-work. On the contrary: controlled 29

for (relevant) health problems and background variables, SIM-welfare were found more likely to have 30

healthcare contacts than SIM-work. 31

Since we did not correct for severity of health problems, the finding might reflect that health 32

problems among SIM-welfare are more severe. Other studies[31-33], with correction for severity also 33

showed higher service use for jobless populations, compared to the employed. As an explanation for 34

higher service use, Honkonen et al.[31] point to the extra time jobless individuals have and the strong 35

linkages between healthcare and the welfare agency. These supportive findings, make it unlikely that 36

controlling for severity of symptoms, would have yielded opposite results. In terms of unmet needs, 37

SIM-welfare seem no more vulnerable than SIM-work. 38

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Not accessing healthcare, while this is needed from a health professionals’ perspective, might 1

still be one of the explanations why single men are overrepresented among clients of public mental 2

healthcare. Future research comparing for instance single men with non-single men or single men 3

against single woman might shed more light on this. 4

5

Usefull subgroups? 6

Stratifying SIM-welfare along SWI’s stairway to work proved useful as it reflected not only 7

differences in age and duration of joblessness, but also significant health differences if controlled for 8

these background variables. As such, the classification seems to do what it is supposed to do: it takes 9

into account health related participation restrictions. As such it provides information about (a) what 10

kind of reintegration policy is (locally) associated with what kind of health problems and (b) what kind 11

of health problems can be ‘found’ and targeted within each of this (registered) categories. This 12

information is especially relevant for local policy in Amsterdam, but also for other Dutch cities with 13

comparable classifications for welfare recipients. 14

It was found that one step up, from the “care” category, to the “social activation” category, 15

was mainly a step up in somatic health. Again one step closer to the labour market, to the “re-16

employment” category of increased pressure and opportunity to participate, SIM-welfare showed less 17

mental health problems, less drug use and less combined health problems but were still worse of on all 18

health indicators compared to SIM-work. 19

Apparently, especially adding somatic illnesses to the equation of disadvantaged human 20

capital and other health problems is most likely to put clients in a position in which vocational 21

improvement is of secondary importance and the main priority is to improve/stabilise health (financed 22

from other funds). It is hard to interpret this finding as possibly somatic illnesses are most likely to be 23

picked up and assessed as a major personal barrier by SWI, while in fact mental illness might more 24

severely restrict labour market participation. It does however implicate, that for this long term jobless 25

population of SIM-welfare, somatic health problems pose a more important barrier than the 26

unemployment research suggests. Also, it raises the question whether this population of welfare clients 27

differs much from the population of people receiving disability benefits. 28

29

Generalising findings 30

In this study, extra effort was put into creating a representative sample of a population which 31

is hard to reach. On average, clients not reached, were visited at least 6 times at their homes and 32

contacted 20 times by telephone. This led to a 26% response rate, which demonstrates that this specific 33

group would probably be missed in general (health) surveys. 34

Although particular subgroups might be underrepresented in the sample, the non-response 35

analysis showed accurate representation on compared variable and authors are unaware of studies to 36

date with better response rates among this particular group, voluntarily interviewed outside the welfare 37

setting. 38

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Generalisibility of findings across time and space, is limited, but seems accurate for other 1

urban settings with mixed ethnicities, health care with low financial barriers and universal entitlements 2

to welfare benefits enabling to fulfil basic needs. 3

4

Conclusion & Policy implications 5

Findings confirm that SIM-welfare are a vulnerable group with disadvantaged human capital 6

and health problems. Transitions from welfare towards work among SIM-welfare, applies to the 7

further rehabilitation of a substantial group of former rough sleepers towards work. 8

Findings underline the importance of a rehabilitation perspective on welfare-towards-work 9

policy, taking health barriers into account. Since relative vulnerability in terms of unmet needs was 10

not found among welfare clients, promoting access of healthcare seems no more a priority among 11

single male welfare recipients than among single male workers. 12

SWI’s “stairway to work” shows that clients can be stratified along dimensions reflecting both 13

health needs (eg barriers) and traditional human capital indicators. With these kinds of classifications 14

it seems possible to stratify clients and expose them to programmes in which a mix of health 15

promotion, labour market activation and care is balanced towards adequately improving both 16

vocational progress, health and possibly preventing homelessness. In Amsterdam, the perspectives of 17

“care” and vocational progress hardly seem to mix. Adding vocational perspectives to case-first-care, 18

and rehabilitation care perspectives to re-employment practices, could improve both health and re-19

employment outcomes. In order to accomplish this, “care” and “vocational training” should probably 20

cooperate within a shared financing structure integrating costs and benefits. 21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

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Ethical approval: the necessity for ethical approval for the study was waived by the ethical 1

commission of the Amsterdam University Medical Center 2

Contributorship: T.C.Kamann contributed to the study design, coordinated data collection, 3

helped train peer interviewers, performed analysis and wrote the article. 4

M.de Wit, initiated the research, contributed to study design, analysis and commented on 5

article. 6

S.Cremer, contributed to the study design and commented on article 7

AJ Beekman, contributed to the study design and made important contributions to the article. 8

Acknowledgements: The authors thank the peer interviewers for their effort and perseverance during 9

data collection. The Service for Work and Income, Amsterdam Statistics and Radar Advies are 10

thanked for their corporation. 11

12

Funding: ZONmw, Public health service Amsterdam, Municipal Service for Work & Income 13

Amsterdam, ACHMEA healthcare insurance. 14

15

Conflicting interests: None declared 16

17

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APPENDIX

Table A.1. Background characteristics of single male welfare recipients compared between response and non response groups.

SAMPLE FRAME RESPONSE

TOTAL NON

RESPONSE

NON RESPONSE BEFORE

PERSONAL APPROACH

NON RESPONSE AFTER PERSONAL

APPROACH

Sample frame

(n=9200)

Random

sample

(n=1800)

Response

(n=472)

Non response

(n=1328)

Refusal info

transfer

(n=426)

No longer

receiving

welfare n=170)

Refusal

interview

(n=492)

Not reached

(n=194)

Other

(n=46)

Mean Age (sd)+ 47,7 (10,0) 47,6 (10,1) 48,8 (9,6) 47,2* (10,2) 49,8 (9,0) 45,2* (11,6) 46,8* (9,9) 43,8* (10,6) 50,1 (10,9)

Mean duration of welfare (sd)

6,2 (4,7) 6,1 (4,6) 6,0 (4,5) 6,1 (4,6) 7,1* (4,6) 4,3* (4,4) 6,4 (4,6) 5,1* (4,3) 5,8 (4,5)

Mean contacts with social services (sd)

5,6 (6,3) 5,7 (6,3) 5,7 (6,1) 5,7 (6,4) 5,0 (6,0) 7,4* (8,5) 5,6 (5,7) 6,1 (6,3) 6,0 (7,1)

Education

lowest 721 11,5% 136 10,9% 41 11,7% 95 10,5% 20 6,6%* 15 14,4% 41 12,2% 17 13,2% 2 7,4%

lower 2505 40,0% 517 41,3% 138 39,5% 379 42,0% 143 46,9% 43 41,3% 132 39,2% 48 37,2% 13 48,1%

higher 2368 37,8% 461 36,9% 129 37,0% 332 36,8% 111 36,4% 32 30,8% 132 39,2% 49 38,0% 8 29,6%

highest 666 10,6% 137 11,0% 41 11,7% 96 10,6% 31 10,2% 14 13,5% 32 9,5% 15 11,6% 4 14,8%

total 6260 100% 1251 100% 349 100% 902 100% 305 100% 104 100% 337 100% 129 100% 27 100%

missing 2940

549

123

426

121

66

155

65

19

Reintegration step

1 3601 39,1% 686 38,1% 174 36,9% 512 38,6% 182 42,7% 55 32,4% 191 38,8% 74 38,1% 10 21,7%*

2 2642 28,7% 513 28,5% 150 31,8% 363 27,3% 119 27,9% 33 19,4%* 139 28,3% 51 26,3% 21 45,7%

3 2545 27,7% 514 28,6% 133 28,2% 381 28,7% 110 25,8% 58 34,1% 146 29,7% 56 28,9% 11 23,9%

4 412 4,5% 87 4,8% 15 3,2% 72 5,4% 15 3,5% 24 14,1%* 16 3,3% 13 6,7%* 4 8,7%

total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%

Age groups

23 - 34 years 1102 12,0% 223 12,4% 46 9,7% 177 13,3%* 27 6,3%* 34 20,0%* 64 13,0% 47 24,2%* 5 10,9%

35 – 44 years 2309 25,1% 450 25,0% 109 23,1% 341 25,7% 92 21,6% 50 29,4% 141 28,7% 51 26,3% 7 15,2%

45 – 54 years 3066 33,3% 589 32,7% 153 32,4% 436 32,8% 154 36,2% 44 25,9% 163 33,1% 61 31,4% 14 30,4%

55 – 64 years 2723 29,6% 538 29,9% 164 34,7% 374 28,2%* 153 35,9% 42 24,7%* 124 25,2%* 35 18,0%* 20 43,5%

Total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%

+Mean age recorded from social services Amsterdam registry at December 2008; deviates from age at interview as used in other tables for the response group in this article . *significant deviation from mean or proportion in response group (p<.05)

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on December 20, 2020 by guest. Protected by copyright. http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2013-004247 on 20 February 2014. Downloaded from



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1

Health, Drugs & Service use among deprived Single Males: comparing 1


in Amsterdam. 3

4

Authors: T.C.Kamann - M.A.S. de Wit - S. Cremer – A.T.F Beekman 5



Keywords 8

EPIDEMIOLOGY 9

PUBLIC HEALTH 10

MENTAL HEALTH 11

SOMATIC HEALTH 12

SERVICE USE 13

UNEMPLOYMENT 14

15

Affiliations 16




20



23



26


Netherlands 28

29


Tjerk C. Kamann 31



Tel: +31 622728815 34

Fax: +31 205555160 35

Word count: 36


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2

ABSTRACT 1

2

Objectives 3





specific group? 8

Design 9



subgroups of SIM-welfare asssessed with a different distance to the labour market, and exposed to 12


Setting 14


Participants 16



Outcome measures 19



Results 22








Conclusion 30




34

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3

ARTICLE SUMMARY 1

2

3 4

Article Focus





is undocumented



Key Messages











are aware of.







health differences.

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4

INTRODUCTION 1

2





7


























welfare). 33



context. 36

37

38

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5













13


Within the population of SIM-welfare, subgroups of SIM-welfare can be distinguished that 15

are (a) exposed to different reintegration policy and (b) probably have different health needs. 16









25

26

Step 1. “Care”







through referral.




activation.



social activation


individual needs.



placement on labour

market.




in time, accepting



education.



labour market.



search activities.







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6





5

Finding place? 6


prevalence of ill health harmful drug use and healthcare use. These prevalences are useful for welfare-8

to-work-policy, public health policy and other studies in need of hard to reach reference groups. 9

10









19


To prevent possible psychosocial deterioration resulting in a need for costly outreaching 21

individual PMHC at a later stage we ask: do we find evidence suggesting a need to improve access to 22

healthcare for this specific group? 23

24


We examine whether subgroups (a) assessed with a different distance to the labour market and 26

(b) exposed to different reintegration policy, also differ in (unmet) health needs. If so, this 27

classification might also be useful for a differentiation in public health interventions. Also, it provides 28

us with insight, as to what specific health needs are more and less associated with distance to the 29

labour market, as assessed by SWI. 30

31

Objectives 32



2. Analyse risk for ill health and harmful druguse for (subgroups of) SIM-welfare compared to SIM-35

work (controlled for socio demographic background variables) 36


for socio demographic background variables and relevant health needs) 38

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7

METHOD 1














15








23


n %



welfare benefits

170 9%



426 24%





days of the week

193 11%




48 3%

Response 472 26%



Total 1800 100%

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8

1





6

Reference data 7









The overall response was 50%, with higher response rates in women, elder persons, native 16

Dutch citizens and residents of deprived neighbourhoods. 17





22

Measures 23









used. A list of 18 common chromatic somatic illnesses was presented to participants (high blood 32






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per week. 8


















26

Analysis 27











variables. 38

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10

RESULTS 1

2





‘true’ distributions as registered for the research population (eg. the sample frame; n=9200). Only 7

for age we find a significant over representation of older men in the reponse group. Older men 8




12




step 4 (n=15). 16



welfare than among SIM-work. SIM-welfare in subgroups assessed with a larger distance to the 19

labour market generally show higher prevalence of illness, harmful drug use and service use. Also 20

differences in background variables are found between subgroups. 21

22




men in

Amsterdam†

(SIM-work)

n=294

Step 1

“Care”

n=174

Step 2

“Social

activation”

n=150

Step 3&4

“Re-

employment“

n=148

Total

n=472


Mean age (sd) 52.2 (8.2)* 49.5 (10.0)* 46.7 (9.6)* 49.6 (9.5)* 40.3 (10.5)

Age categories

23-34 years 2%* 9% 16%* 9%* 33%

35-44 years 20% 22% 21%* 21%* 33%

45-54 years 32% 28%* 41%* 33%* 22%

55-65 years 47% 41%* 23%* 38%* 12%


% Migrant Dutch‡ 47% 58% 68%* 57%* 34%





1-5 years of work 19% 22% 25% 22% n.a.

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6-15 years of work 35% 36% 37% 36% n.a.

>15 years of work 39% 30% 29% 33% n.a.




=<3 years 13% 16%* 41% 22% n.a.

4-10 years 32%* 43% 36% 37% n.a.

11-15 years 15% 10% 7% 11% n.a.

> 15 years 32%* 20%* 7% 20% n.a.

Health indicators










% GP 82%* 73%* 85%* 80%* 64%

% Specialist 65%* 55% 46%* 56%* 29%

% Mental health 24% 22% 13% 20%* 10%

% Addiction care 14%* 6% 6% 9%* 3%

% No care 4%* 10% 5% 6% 7%





1










11



migration history.

OR (95% CI) P

SOMATIC ILLNESS




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12



MENTAL ILLNESS






EXCESSIVE DRINKING


Single men on welfare; total group (n=472) .89 (.57- 1.40) .622


Single men on welfare; stairway to work step 2 1.42 (.81- 2.48) .227


MULTI-PROBLEM*





Single men on welfare; stairway to work step 3 2.04 (1.13- 3.69) .018

1

2 3

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13








8


SIM-welfare with a different distance to the labour market (model 2), controlled for differences in relevant health 10

needs and socio demographic background variables 11

12

13

DISCUSSION 14





known about. 19

20

Finding place? 21







GP SPECIALIST

CARE

MENTAL

HEALTH

CARE

ADDICTION

CARE NO CARE



work*


SIM-work 1 1 1 1 1

Model 2: comparing between sungroups of

SIM-Welfare **

Distance to labour


Step 2 “social


Step 3&4 “re-


*All analyses were conducted with control variables: age; education; deprivation area; migration history

*Relevant health variables controlled for in model 1: GP; mental illness; somatic illness, excessive drinking; Specialist care: somatic illness;

Mental health care; mental illness; Addiction care; excessive drinking; No care; mental illness; somatic illness, excessive drinking .

** Relevant health variables controlled for in model 2: Same as model 1 except Control variables entered in model 2; GP; Specialist vare:

Mental health care’addiction care; no care.

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14







programs (32%). 7

8






14










this. 24

25


We aimed to asses unmet normative needs, to find evidence for normative health needs, single 27

men might not recognise or act upon by seeking out healthcare. No evidence was found for a higher 28

proportion of unmet needs among SIM-welfare compared to SIM-work. On the contrary: controlled 29

for (relevant) health problems and background variables, SIM-welfare were found more likely to have 30

healthcare contacts than SIM-work. 31








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5

Usefull subgroups? 6























29









setting. 38

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16

Generalisibility of findings across time and space, is limited, but seems accurate for other 1



4










health needs (eg barriers) and traditional human capital indicators. With these kinds of classifications 14








22



25




29



32

Conflicting interests: None declared 33

34

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17

REFERENCES 1


Amsterdam: a descriptive study. BMC Health Serv Res 2009;1:1-8. 5 6 2 Nusselder WJ, Slockers MT, Krol L, Slockers CT et al. Mortality and Life Expectancy in Homeless 7

Men and Women in Rotterdam: 2001–2010. PloS one 2013;8:e73979. 8 9 3 Nielsen SF, Hjorthøj CR, Erlangsen A, et al. Psychiatric disorders and mortality among people in 10


13 4 Fazel S, Khosla V, Doll H, Geddes J. The prevalence of mental disorders among the homeless in 14

Western countries: Systematic review and meta regression analysis. PLoS Med 2008;12:e225 15 16 5 Hwang SW, Homelessness and health. CMAJ 2001;164:229–233. 17 18 6 Fitzpatrick S, Stephens M. An International Review of Homelessness and Social Housing Policy. 19















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Abuse Rev 2011;4:4-27. 7



















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19

APPENDIX



TOTAL NON

RESPONSE

NON RESPONSE BEFORE

PERSONAL APPROACH


APPROACH

Sample frame

(n=9200)

Random

sample

(n=1800)

Response

(n=472)

Non response

(n=1328)

Refusal info

transfer

(n=426)

No longer

receiving

welfare n=170)

Refusal

interview

(n=492)

Not reached

(n=194)

Other

(n=46)

Mean Age (sd)+ 47,7 (10,0) 47,6 (10,1) 48,8 (9,6) 47,2* (10,2) 49,8 (9,0) 45,2* (11,6) 46,8* (9,9) 43,8* (10,6) 50,1 (10,9)


6,2 (4,7) 6,1 (4,6) 6,0 (4,5) 6,1 (4,6) 7,1* (4,6) 4,3* (4,4) 6,4 (4,6) 5,1* (4,3) 5,8 (4,5)


5,6 (6,3) 5,7 (6,3) 5,7 (6,1) 5,7 (6,4) 5,0 (6,0) 7,4* (8,5) 5,6 (5,7) 6,1 (6,3) 6,0 (7,1)

Education

lowest 721 11,5% 136 10,9% 41 11,7% 95 10,5% 20 6,6%* 15 14,4% 41 12,2% 17 13,2% 2 7,4%

lower 2505 40,0% 517 41,3% 138 39,5% 379 42,0% 143 46,9% 43 41,3% 132 39,2% 48 37,2% 13 48,1%

higher 2368 37,8% 461 36,9% 129 37,0% 332 36,8% 111 36,4% 32 30,8% 132 39,2% 49 38,0% 8 29,6%

highest 666 10,6% 137 11,0% 41 11,7% 96 10,6% 31 10,2% 14 13,5% 32 9,5% 15 11,6% 4 14,8%

total 6260 100% 1251 100% 349 100% 902 100% 305 100% 104 100% 337 100% 129 100% 27 100%

missing 2940

549

123

426

121

66

155

65

19

Reintegration step

1 3601 39,1% 686 38,1% 174 36,9% 512 38,6% 182 42,7% 55 32,4% 191 38,8% 74 38,1% 10 21,7%*

2 2642 28,7% 513 28,5% 150 31,8% 363 27,3% 119 27,9% 33 19,4%* 139 28,3% 51 26,3% 21 45,7%

3 2545 27,7% 514 28,6% 133 28,2% 381 28,7% 110 25,8% 58 34,1% 146 29,7% 56 28,9% 11 23,9%

4 412 4,5% 87 4,8% 15 3,2% 72 5,4% 15 3,5% 24 14,1%* 16 3,3% 13 6,7%* 4 8,7%

total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%

Age groups

23 - 34 years 1102 12,0% 223 12,4% 46 9,7% 177 13,3%* 27 6,3%* 34 20,0%* 64 13,0% 47 24,2%* 5 10,9%

35 – 44 years 2309 25,1% 450 25,0% 109 23,1% 341 25,7% 92 21,6% 50 29,4% 141 28,7% 51 26,3% 7 15,2%

45 – 54 years 3066 33,3% 589 32,7% 153 32,4% 436 32,8% 154 36,2% 44 25,9% 163 33,1% 61 31,4% 14 30,4%

55 – 64 years 2723 29,6% 538 29,9% 164 34,7% 374 28,2%* 153 35,9% 42 24,7%* 124 25,2%* 35 18,0%* 20 43,5%

Total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%


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Health, Drugs & Service use among deprived Single Men: comparing (subgroups) of single male welfare

recipients against employed single men in Amsterdam.

Journal: BMJ Open

Manuscript ID: bmjopen-2013-004247.R2


Date Submitted by the Author: 23-Jan-2014




Public health




BMJ Open on D



jopen.bmj.com

/B

MJ O


ebruary 2014. Dow

nloaded from



1

Health, Drugs & Service use among deprived Single Men: comparing 1


in Amsterdam. 3

4

Authors: T.C.Kamann - M.A.S. de Wit - S. Cremer – A.T.F. Beekman 5



Keywords 8

EPIDEMIOLOGY 9

PUBLIC HEALTH 10

MENTAL HEALTH 11

SOMATIC HEALTH 12

SERVICE USE 13

UNEMPLOYMENT 14

15

Affiliations 16




20



23



26


Netherlands 28

29


Tjerk C. Kamann 31



Tel: +31 622728815 34

Fax: +31 205555160 35

Word count: 36


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2

ABSTRACT 1

2

Objectives 3





specific group? 8

Design 9



subgroups of SIM-welfare assessed with a different distance to the labour market, and exposed to 12


Setting 14


Participants 16



Outcome measures 19



Results 22








Conclusion 30




34

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3

ARTICLE SUMMARY 1

2

3 4

Article Focus





is undocumented



Key Messages











are aware of.







health differences.

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4

INTRODUCTION 1

2






























welfare). 32



context. 35

36

37

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5













13


Within the population of SIM-welfare, subgroups can be distinguished that are (a) exposed to 15

different reintegration policy and (b) probably have different health needs. 16









25

26

Step 1. “Care”







through referral.




activation.



social activation


individual needs.



placement on labour

market.




in time, accepting



education.



labour market.



search activities.







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6





5

Finding place? 6


prevalence of ill health, harmful drug use and healthcare use. These prevalences are useful for 8

welfare-to-work-policy, public health policy and other studies in need of hard to reach reference 9

groups. 10

11









20


Improving access to healthcare for groups under-utilising health services, could prevent 22

psychosocial deterioration and a possible need for costly outreaching individual PMHC at a later 23

stage. In this study, we look to find evidence for relative under-utilisation of health services (i.e. 24

disadvantaged service use) among SIM-welfare by comparing their unmet health needs against SIM-25

work.. 26

27


We examine whether subgroups of SIM-welfare (a) assessed with a different distance to the 29

labour market and (b) exposed to different reintegration policy, also differ in (unmet) health needs. If 30

so, this classification might also be useful for a differentiation in public health interventions. Also, it 31

provides us with insight, as to what specific health needs are more and less associated with distance to 32

the labour market, as assessed by SWI. 33

34

Objectives 35



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7

2. Analyse risk for ill health and harmful drug use for (subgroups of) SIM-welfare compared to SIM-1

work (controlled for socio demographic background variables). 2


for socio demographic background variables and relevant health needs). 4

5

METHOD 6














20








28


n %



welfare benefits

170 9%


information from social services to the public

health service

426 24%





days of the week

193 11%

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8




48 3%

Response 472 26%



Total 1800 100%

1





6

Reference data 7









The overall response was 50% with higher response rates in women, elder persons, native 16

Dutch citizens and residents of deprived neighbourhoods. Specifically for single men, aged 25 17

to 64, the response rate was 28%. 18





23

Measures 24








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9


used. A list of 18 common chronic somatic illnesses was presented to participants (high blood 2













per week. 15


















33

Analysis 34





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10







variables. 7

8

RESULTS 9

10





‘true’ distributions as registered for the research population (i.e. the sample frame; n=9200). Only 15

for age we find a significant over representation of older men in the response group. Older men 16




20




step 4 (n=15). 24



welfare than among SIM-work. SIM-welfare in subgroups assessed with a larger distance to the labour 27

market generally show higher prevalence of illness, harmful drug use and service use. Also differences 28

in background variables are found between subgroups. 29

30




men in

Amsterdam†

(SIM-work)

n=294

Step 1

“Care”

n=174

Step 2

“Social

activation”

n=150

Step 3&4

“Re-

employment“

n=148

Total

n=472


Mean age (sd) 52.2 (8.2)* 49.5 (10.0)* 46.7 (9.6)* 49.6 (9.5)* 40.3 (10.5)

Age categories

23-34 years 2%* 9% 16%* 9%* 33%

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11

35-44 years 20% 22% 21%* 21%* 33%

45-54 years 32% 28%* 41%* 33%* 22%

55-65 years 47% 41%* 23%* 38%* 12%


% Migrant Dutch‡ 47% 58% 68%* 57%* 34%





1-5 years of work 19% 22% 25% 22% n.a.

6-15 years of work 35% 36% 37% 36% n.a.

>15 years of work 39% 30% 29% 33% n.a.




=<3 years 13% 16%* 41% 22% n.a.

4-10 years 32%* 43% 36% 37% n.a.

11-15 years 15% 10% 7% 11% n.a.

> 15 years 32%* 20%* 7% 20% n.a.

Health indicators










% GP 82%* 73%* 85%* 80%* 64%

% Specialist 65%* 55% 46%* 56%* 29%

% Mental health 24% 22% 13% 20%* 10%

% Addiction care 14%* 6% 6% 9%* 3%

% No care 4%* 10% 5% 6% 7%



work are weighted (age*deprivation area) to represent employed (>12h) single men in Amsterdam; significance of differences is corrected for design-effects of weighs. ‡92% of migrants are first generation migrants with a wide variation of cultural backgrounds.

1








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3



migration history.

OR (95% CI) P

Somatic illness


Single men on welfare; total group (n=472) 3.11 (2.06-4.71) <.001

Single men on welfare; stairway to work step 1 4.42 (2.72-7.20) <.001



Mental illness






Excessive drinking


Single men on welfare; total group (n=472) .89 (.57-1.40) .622

Single men on welfare; stairway to work step 1 .83 (.47-1.46) .515

Single men on welfare; stairway to work step 2 1.42 (.81-2.48) .227


Multi-problem





Single men on welfare; stairway to work step 3 2.04 (1.13-3.69) .018

4

5 6

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8


SIM-welfare assessed with a different distance to the labour market (model 2), controlled for differences in relevant 10

health needs and socio demographic background variables†. 11

12

13

DISCUSSION 14





known about. 19

20

Finding place? 21







GP SPECIALIST

CARE

MENTAL

HEALTH

CARE

ADDICTION

CARE NO CARE



work‡


SIM-work 1 1 1 1 1

Model 2: comparing between subgroups of

SIM-Welfare ††

Distance to labour

market Step 1 “care” ns 0.8 1.8 (1.0-3.0) 2.3 (1.2-4.7) ns 3.2 ns 1.0

Step 2 “social

activation” ns 0.5 ns 1.5 2.0 (1.0-4.1) ns 1.6 ns 2.6

Step 3&4 “re-


†All analyses were conducted with control variables: age; education; deprivation area; migration history

‡Relevant health variables controlled for in model 1: GP: mental illness, somatic illness, excessive drinking; Specialist care: somatic illness;

Mental health care: mental illness; Addiction care; excessive drinking; No care; mental illness; somatic illness, excessive drinking .

†† Relevant health variables controlled for in model 2: same as model 1 except instead of excessive drinking, harmful drinking, daily

cannabis use and recent substance abuse were entered as control variables.

ns: association is non significant (p>.05)

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14







programs (32%). 7

8






14










this. 24

25


No evidence was found for a higher proportion of unmet needs among SIM-welfare compared 27

to SIM-work. On the contrary: controlled for (relevant) health problems and background variables, 28

SIM-welfare were found more likely to have healthcare contacts than SIM-work. 29










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3

Useful subgroups? 4























27









setting. 36

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Generalisability of findings across time and space, is limited, but seems accurate for other 1



4










health needs (i.e. barriers) and traditional human capital indicators. With these kinds of classifications 14








22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

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Contributorship: T.C.Kamann contributed to the study design, coordinated data collection, helped 1

train peer interviewers, performed analysis and wrote the article. 2

M.de Wit, initiated the research, contributed to study design, analysis and commented on article. 3

S.Cremer, contributed to the study design and commented on article 4

AJ Beekman, contributed to the study design and made important contributions to the article. 5

6



9




13



16

Conflicting interests: None declared 17 18

Data sharing: Requests to use study data may be send to the corresponding author. 19

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1

REFERENCES 2


Amsterdam: a descriptive study. BMC Health Serv Res 2009;1:1-8. 6 7 2 Nusselder WJ, Slockers MT, Krol L, et al. Mortality and Life Expectancy in Homeless Men and 8

Women in Rotterdam: 2001–2010. PloS one 2013;8:e73979. 9 10 3 Nielsen SF, Hjorthøj CR, Erlangsen A, et al. Psychiatric disorders and mortality among people in 11


14 4 Fazel S, Khosla V, Doll H, et al. The prevalence of mental disorders among the homeless in Western 15

countries: Systematic review and meta regression analysis. PLoS Med 2008;12:e225 16 17 5 Hwang SW, Homelessness and health. CMAJ 2001;164:229–233. 18 19 6 Fitzpatrick S, Stephens M. An International Review of Homelessness and Social Housing Policy. 20













Klanten. Amsterdam: UvA 2008. 51 52

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18 McKee Ryan F, Song Z, Wanberg CR, et al. Psychological and physical well-being during 1 unemployment: A meta-analytic study. J Appl Psychol 2009;90:53-75 2




Abuse Rev 2011;4:4-27. 9


















Environ Health 2000;26:169–7735

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1

Health, Drugs & Service use among deprived Single Men: comparing 1


in Amsterdam. 3

4

Authors: T.C.Kamann - M.A.S. de Wit - S. Cremer – A.T.F. Beekman 5



Keywords 8

EPIDEMIOLOGY 9

PUBLIC HEALTH 10

MENTAL HEALTH 11

SOMATIC HEALTH 12

SERVICE USE 13

UNEMPLOYMENT 14

15

Affiliations 16




20



23



26


Netherlands 28

29


Tjerk C. Kamann 31



Tel: +31 622728815 34

Fax: +31 205555160 35

Word count: 36


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2

ABSTRACT 1

2

Objectives 3





specific group? 8

Design 9



subgroups of SIM-welfare assessed with a different distance to the labour market, and exposed to 12


Setting 14


Participants 16



Outcome measures 19



Results 22








Conclusion 30




34

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3

ARTICLE SUMMARY 1

2

3 4

Article Focus





is undocumented



Key Messages











are aware of.







health differences.

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4

INTRODUCTION 1

2





7


























welfare). 33



context. 36

37

38

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5













13


Within the population of SIM-welfare, subgroups can be distinguished that are (a) exposed to 15

different reintegration policy and (b) probably have different health needs. 16









25

26

Step 1. “Care”







through referral.




activation.



social activation


individual needs.



placement on labour

market.




in time, accepting



education.



labour market.



search activities.







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6





5

Finding place? 6


prevalence of ill health, harmful drug use and healthcare use. These prevalences are useful for 8

welfare-to-work-policy, public health policy and other studies in need of hard to reach reference 9

groups. 10

11









20


Improving access to healthcare for groups under-utilising health services, could prevent 22

psychosocial deterioration and a possible need for costly outreaching individual PMHC at a later 23

stage. In this study, we look to find evidence for relative under-utilisation of health services (i.e. 24

disadvantaged service use) among SIM-welfare by comparing their unmet health needs against SIM-25

work.. 26

27


We examine whether subgroups of SIM-welfare (a) assessed with a different distance to the 29

labour market and (b) exposed to different reintegration policy, also differ in (unmet) health needs. If 30

so, this classification might also be useful for a differentiation in public health interventions. Also, it 31

provides us with insight, as to what specific health needs are more and less associated with distance to 32

the labour market, as assessed by SWI. 33

34

Objectives 35



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2. Analyse risk for ill health and harmful drug use for (subgroups of) SIM-welfare compared to SIM-1

work (controlled for socio demographic background variables). 2


for socio demographic background variables and relevant health needs). 4

5

METHOD 6














20








28


n %



welfare benefits

170 9%


information from social services to the public

health service

426 24%





days of the week

193 11%

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48 3%

Response 472 26%



Total 1800 100%

1





6

Reference data 7









The overall response was 50% with higher response rates in women, elder persons, native 16

Dutch citizens and residents of deprived neighbourhoods. Specifically for single men, aged 25 17

to 64, the response rate was 28%. 18





23

Measures 24








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used. A list of 18 common chronic somatic illnesses was presented to participants (high blood 2













per week. 15


















33

Analysis 34





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10







variables. 7

8

RESULTS 9

10





‘true’ distributions as registered for the research population (i.e. the sample frame; n=9200). Only 15

for age we find a significant over representation of older men in the response group. Older men 16




20




step 4 (n=15). 24



welfare than among SIM-work. SIM-welfare in subgroups assessed with a larger distance to the labour 27

market generally show higher prevalence of illness, harmful drug use and service use. Also differences 28

in background variables are found between subgroups. 29

30




men in

Amsterdam†

(SIM-work)

n=294

Step 1

“Care”

n=174

Step 2

“Social

activation”

n=150

Step 3&4

“Re-

employment“

n=148

Total

n=472


Mean age (sd) 52.2 (8.2)* 49.5 (10.0)* 46.7 (9.6)* 49.6 (9.5)* 40.3 (10.5)

Age categories

23-34 years 2%* 9% 16%* 9%* 33%

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11

35-44 years 20% 22% 21%* 21%* 33%

45-54 years 32% 28%* 41%* 33%* 22%

55-65 years 47% 41%* 23%* 38%* 12%


% Migrant Dutch‡ 47% 58% 68%* 57%* 34%





1-5 years of work 19% 22% 25% 22% n.a.

6-15 years of work 35% 36% 37% 36% n.a.

>15 years of work 39% 30% 29% 33% n.a.




=<3 years 13% 16%* 41% 22% n.a.

4-10 years 32%* 43% 36% 37% n.a.

11-15 years 15% 10% 7% 11% n.a.

> 15 years 32%* 20%* 7% 20% n.a.

Health indicators










% GP 82%* 73%* 85%* 80%* 64%

% Specialist 65%* 55% 46%* 56%* 29%

% Mental health 24% 22% 13% 20%* 10%

% Addiction care 14%* 6% 6% 9%* 3%

% No care 4%* 10% 5% 6% 7%



work are weighted (age*deprivation area) to represent employed (>12h) single men in Amsterdam; significance of differences is corrected for design-effects of weighs. ‡92% of migrants are first generation migrants with a wide variation of cultural backgrounds.

1








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3



migration history.

OR (95% CI) P

Somatic illness






Mental illness






Excessive drinking


Single men on welfare; total group (n=472) .89 (.57-1.40) .622


Single men on welfare; stairway to work step 2 1.42 (.81-2.48) .227


Multi-problem





Single men on welfare; stairway to work step 3 2.04 (1.13-3.69) .018

4

5 6

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8


SIM-welfare assessed with a different distance to the labour market (model 2), controlled for differences in relevant 10

health needs and socio demographic background variables†. 11

12

13

DISCUSSION 14





known about. 19

20

Finding place? 21







GP SPECIALIST

CARE

MENTAL

HEALTH

CARE

ADDICTION

CARE NO CARE



work‡


SIM-work 1 1 1 1 1

Model 2: comparing between subgroups of

SIM-Welfare ††

Distance to labour

market Step 1 “care” ns 0.8 1.8 (1.0-3.0) 2.3 (1.2-4.7) ns 3.2 ns 1.0

Step 2 “social

activation” ns 0.5 ns 1.5 2.0 (1.0-4.1) ns 1.6 ns 2.6

Step 3&4 “re-


†All analyses were conducted with control variables: age; education; deprivation area; migration history

‡Relevant health variables controlled for in model 1: GP: mental illness, somatic illness, excessive drinking; Specialist care: somatic illness;

Mental health care: mental illness; Addiction care; excessive drinking; No care; mental illness; somatic illness, excessive drinking .

†† Relevant health variables controlled for in model 2: same as model 1 except instead of excessive drinking, harmful drinking, daily

cannabis use and recent substance abuse were entered as control variables.

ns: association is non significant (p>.05)

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14







programs (32%). 7

8






14










this. 24

25


No evidence was found for a higher proportion of unmet needs among SIM-welfare compared 27

to SIM-work. On the contrary: controlled for (relevant) health problems and background variables, 28

SIM-welfare were found more likely to have healthcare contacts than SIM-work. 29










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3

Useful subgroups? 4























27









setting. 36

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16

Generalisability of findings across time and space, is limited, but seems accurate for other 1



4










health needs (i.e. barriers) and traditional human capital indicators. With these kinds of classifications 14








22



25




29



32

Conflicting interests: None declared 33 34

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17

REFERENCES 1


Amsterdam: a descriptive study. BMC Health Serv Res 2009;1:1-8. 5 6 2 Nusselder WJ, Slockers MT, Krol L, Slockers CT et al. Mortality and Life Expectancy in Homeless 7

Men and Women in Rotterdam: 2001–2010. PloS one 2013;8:e73979. 8 9 3 Nielsen SF, Hjorthøj CR, Erlangsen A, et al. Psychiatric disorders and mortality among people in 10


13 4 Fazel S, Khosla V, Doll H, Geddes J. The prevalence of mental disorders among the homeless in 14

Western countries: Systematic review and meta regression analysis. PLoS Med 2008;12:e225 15 16 5 Hwang SW, Homelessness and health. CMAJ 2001;164:229–233. 17 18 6 Fitzpatrick S, Stephens M. An International Review of Homelessness and Social Housing Policy. 19















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Abuse Rev 2011;4:4-27. 7



















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19

APPENDIX



TOTAL NON

RESPONSE

NON RESPONSE BEFORE

PERSONAL APPROACH


APPROACH

Sample frame

(n=9200)

Random

sample

(n=1800)

Response

(n=472)

Non response

(n=1328)

Refusal info

transfer

(n=426)

No longer

receiving

welfare n=170)

Refusal

interview

(n=492)

Not reached

(n=194)

Other

(n=46)

Mean Age (sd)+ 47,7 (10,0) 47,6 (10,1) 48,8 (9,6) 47,2* (10,2) 49,8 (9,0) 45,2* (11,6) 46,8* (9,9) 43,8* (10,6) 50,1 (10,9)


6,2 (4,7) 6,1 (4,6) 6,0 (4,5) 6,1 (4,6) 7,1* (4,6) 4,3* (4,4) 6,4 (4,6) 5,1* (4,3) 5,8 (4,5)


5,6 (6,3) 5,7 (6,3) 5,7 (6,1) 5,7 (6,4) 5,0 (6,0) 7,4* (8,5) 5,6 (5,7) 6,1 (6,3) 6,0 (7,1)

Education

lowest 721 11,5% 136 10,9% 41 11,7% 95 10,5% 20 6,6%* 15 14,4% 41 12,2% 17 13,2% 2 7,4%

lower 2505 40,0% 517 41,3% 138 39,5% 379 42,0% 143 46,9% 43 41,3% 132 39,2% 48 37,2% 13 48,1%

higher 2368 37,8% 461 36,9% 129 37,0% 332 36,8% 111 36,4% 32 30,8% 132 39,2% 49 38,0% 8 29,6%

highest 666 10,6% 137 11,0% 41 11,7% 96 10,6% 31 10,2% 14 13,5% 32 9,5% 15 11,6% 4 14,8%

total 6260 100% 1251 100% 349 100% 902 100% 305 100% 104 100% 337 100% 129 100% 27 100%

missing 2940

549

123

426

121

66

155

65

19

Reintegration step

1 3601 39,1% 686 38,1% 174 36,9% 512 38,6% 182 42,7% 55 32,4% 191 38,8% 74 38,1% 10 21,7%*

2 2642 28,7% 513 28,5% 150 31,8% 363 27,3% 119 27,9% 33 19,4%* 139 28,3% 51 26,3% 21 45,7%

3 2545 27,7% 514 28,6% 133 28,2% 381 28,7% 110 25,8% 58 34,1% 146 29,7% 56 28,9% 11 23,9%

4 412 4,5% 87 4,8% 15 3,2% 72 5,4% 15 3,5% 24 14,1%* 16 3,3% 13 6,7%* 4 8,7%

total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%

Age groups

23 - 34 years 1102 12,0% 223 12,4% 46 9,7% 177 13,3%* 27 6,3%* 34 20,0%* 64 13,0% 47 24,2%* 5 10,9%

35 – 44 years 2309 25,1% 450 25,0% 109 23,1% 341 25,7% 92 21,6% 50 29,4% 141 28,7% 51 26,3% 7 15,2%

45 – 54 years 3066 33,3% 589 32,7% 153 32,4% 436 32,8% 154 36,2% 44 25,9% 163 33,1% 61 31,4% 14 30,4%

55 – 64 years 2723 29,6% 538 29,9% 164 34,7% 374 28,2%* 153 35,9% 42 24,7%* 124 25,2%* 35 18,0%* 20 43,5%

Total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%


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TOTAL

NON

RESPONSE

NON RESPONSE BEFORE

PERSONAL APPROACH


APPROACH

Sample

frame

(n=9200)

Random

sample

(n=1800)

Response

(n=472)

Non response

(n=1328)

Refusal info

transfer

(n=426)

No longer

receiving

welfare

n=170)

Refusal

interview

(n=492)

Not reached

(n=194)

Other

(n=46)

Mean Age (sd)+ 47,7 (10,0) 47,6 (10,1) 48,8 (9,6) 47,2* (10,2) 49,8 (9,0) 45,2* (11,6) 46,8* (9,9) 43,8* (10,6) 50,1 (10,9)


6,2 (4,7) 6,1 (4,6) 6,0 (4,5) 6,1 (4,6) 7,1* (4,6) 4,3* (4,4) 6,4 (4,6) 5,1* (4,3) 5,8 (4,5)


5,6 (6,3) 5,7 (6,3) 5,7 (6,1) 5,7 (6,4) 5,0 (6,0) 7,4* (8,5) 5,6 (5,7) 6,1 (6,3) 6,0 (7,1)

Education

lowest 721 11,5% 136 10,9% 41 11,7% 95 10,5% 20 6,6%* 15 14,4% 41 12,2% 17 13,2% 2 7,4%

lower 2505 40,0% 517 41,3% 138 39,5% 379 42,0% 143 46,9% 43 41,3% 132 39,2% 48 37,2% 13 48,1%

higher 2368 37,8% 461 36,9% 129 37,0% 332 36,8% 111 36,4% 32 30,8% 132 39,2% 49 38,0% 8 29,6%

highest 666 10,6% 137 11,0% 41 11,7% 96 10,6% 31 10,2% 14 13,5% 32 9,5% 15 11,6% 4 14,8%

total 6260 100% 1251 100% 349 100% 902 100% 305 100% 104 100% 337 100% 129 100% 27 100%

missing 2940

549

123

426

121

66

155

65

19

Reintegration step

1 3601 39,1% 686 38,1% 174 36,9% 512 38,6% 182 42,7% 55 32,4% 191 38,8% 74 38,1% 10

21,7%*

2 2642 28,7% 513 28,5% 150 31,8% 363 27,3% 119 27,9% 33

19,4%*

139 28,3% 51 26,3% 21 45,7%

3 2545 27,7% 514 28,6% 133 28,2% 381 28,7% 110 25,8% 58 34,1% 146 29,7% 56 28,9% 11 23,9%

4 412 4,5% 87 4,8% 15 3,2% 72 5,4% 15 3,5% 24

14,1%*

16 3,3% 13 6,7%* 4 8,7%

total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%

Age groups

23 - 34 years 1102 12,0% 223 12,4% 46 9,7% 177

13,3%*

27 6,3%* 34 20,0%*

64 13,0% 47 24,2%*

5 10,9%

35 – 44 years 2309 25,1% 450 25,0% 109 23,1% 341 25,7% 92 21,6% 50 29,4% 141 28,7% 51 26,3% 7 15,2%

45 – 54 years 3066 33,3% 589 32,7% 153 32,4% 436 32,8% 154 36,2% 44 25,9% 163 33,1% 61 31,4% 14 30,4%

55 – 64 years 2723 29,6% 538 29,9% 164 34,7% 374

28,2%*

153 35,9% 42 24,7%*

124 25,2%*

35 18,0%*

20 43,5%

Total 9200 100% 1800 100% 472 100% 1328 100% 426 100% 170 100% 492 100% 194 100% 46 100%


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