EU FP6 Coordination Action on Human Rights Violations
Denmark National Report on Statistical Information on Men’s Practices
Work Package 81
LeeAnn Iovanni and Keith Pringle
1. Key points
a. Statistics Denmark generates enormous amounts of statistical material and produces special
reports and analyses on topics of policy/governmental interest. Gender-disaggregated statistics are
available in many areas. Some national institutes also carry out statistical studies on topics of
policy/governmental interest.
b. There is a large amount of statistical information on gender and the labor market and the gender
wage gap. Gender equality and time use has also been a focus. There is a particular statistical
focus on ethnicity as it relates to the labor market and education as well as to criminal behavior.
This emphasis reflects the government’s interest in the integration of foreigners.
c. There is a large amount of statistical information on crime. Statistical information on violence is
available primarily through the criminal statistics, which as of 2002, began to report victimization
data. Additional government reports shed light on the victim-offender relationship. Although
violence against women is now a particular governmental focus, there is a lack of statistical
information in this area.
d. Gender differences in health have recently become a focus.
2. The national gender background and context
a. general info
Statistics Denmark publishes a large amount of information annually, semi-regularly, or in special
reports. Some of this information is gathered through telephone interviews and mail-in surveys.
Statistics Denmark is usually the key source of information when various centers or government
offices publish a report. Much statistical information is available free on the Internet from the
Statistics Denmark databank. News from Statistics Denmark is an accessible publication of tables,
graphs and text also available free on the Internet. Additional information in Statistical Reports is
obtainable from the library. Gender-disaggregated statistics are available in many areas. Select
gender-disaggregated statistics are jointly published by the Ministry for Gender Equality and
Statistics Denmark and are available in an accessible and continuously updated Internet database,
Statistics on Women and Men. Special reports are sometimes published by Statistics Denmark on
topics of political interest. Ethnicity is a topic of political interest in terms of the integration of
foreign-born persons living in Denmark. Some statistical information is disaggregated by
ethnicity/national origin/birth origin (Danish versus non-Danish) given that integration of foreigners
in general, and descendants of foreigners in particular, is high on the political agenda. Some data is
further disaggregated into foreigners from western versus non-western countries and also by
specific country of origin. Statistics Denmark sometimes conducts statistical analyses with respect
to issues of political interest, for instance, the criminal involvement of ethnic minority group
members compared to ethnic Danes.
b. timescale
The focus of this report is the most recent statistical information. Some of this material includes
changes and developments over time. Gender comparisons are made wherever possible.
1
The work on this report was funded by the Framework 6-funded Coordinated Action on Human Rights Violations
(CAHRV-Project PL 506348).
1
3. Home & Work
Maternity, paternity and parental leave: Parental leave schemes have recently changed in
Denmark as of early 2002. First, under the earlier scheme, from 1996 to 2001, there was little
change in fathers’ use of paternity leave (the 2-week period to be taken within the 14 weeks of postbirth maternity leave), where on average 60% of fathers took this leave. Additionally, in the years
1996 to 2001, only 3% of fathers took any leave during the 10-week parental leave period (leave
that follows the 14-week post-birth maternity leave) that could be taken by either parent i.e., not
both simultaneously.2 In 1998 a new 2-week paternity leave was implemented to be taken in week
25 and week 26. Since that time, there was a gradual increase in the number of fathers taking this
new leave.3 In 2001, 25% of fathers took advantage of this leave up from 20% in 2000. In the
years 1998 and 1999, approximately 7% and 17% of fathers, respectively, took this leave.
The new leave policy, effective 27 March 2002, entitles parents to a total of 48 weeks of leave after
the birth, where mothers take the first 14 weeks and the remaining 32 weeks can be shared between
the parents. This new policy represents a longer guaranteed leave and an overall higher financial
benefit than the previous scheme. While this change has coincided with a slight increase in the
average length of time fathers spend on leave (2.4 weeks, 2001; 2.6 weeks, 2002; 3.2 weeks, 2003),
the absolute number of men on leave – beyond the 2-week paternity leave taken within the first 14
weeks of post-birth maternity leave which has remained stable – decreased somewhat from 2002 to
2003, in absolute numbers, from 13,581 to 10,965. Alternatively, the absolute numbers of women
taking the 14-week plus the 32-week leave increased from 2002 to 2003, 46,382 to 63,809.4 This
relatively low take-up by men of parental leave available to them in a country which, to the rest of
the world is often seen as a model of gender equality, is paralleled by the situation in other Nordic
countries equally famed for their gender equality in matters of parenting: for instance see the
national report for Sweden.
Work – labor force participation, employment sectors, branches, flex-time: Based on recent
data for the third quarter of 20045 for all ages combined, women comprised 47% of those in the
labor force (1,294,000) compared to men who comprised 53% (1,462,000). The proportion of
women and men in the category of unemployed was 48% (81,000) and 52% (88,000), respectively.
However, women comprised a much greater proportion of those outside the labor force for reasons
other than unemployment (which can be for a variety of reasons including some type of leave, see
note 12) at 59.4% (447,000) compared to men who comprised 40.6% (306,000). Women also
comprise a greater proportion of those working part-time (less than 37 hours per week) and a
smaller proportion of those working full-time (37 hours per week) or more than full-time. In the
third quarter of 20046 for all ages combined, the proportions of women and men working 14 hours
per week or less were 56.8% and 43.1%, respectively. In the 15-36 hour category the proportions
for women and men were 75.5% and 24.5%, respectively. However, in the 37-hour category, the
proportion of women was 44.5% compared to 55.4% for men. In the 38-48 hour and the 48 hour +
categories, women comprised only 31% and 14.2%, respectively.
Stated another way, overall in 2003, 32% of working women were employed part-time compared
to 11% of working men; the difference is most stark in the 30-54 age range, where 26% of working
women were employed part-time compared to 4% of working men (Andersen, Pedersen & Skov
2
News from Statistics Denmark, Nr. 82, February 15, 2001. Appendix Figure 1
News from Statistics Denmark, Nr. 138, April 11, 2002. Appendix Figure 2
4
News from Statistics Denmark, Nr. 143, April 5, 2004. Appendix Figure 3
5
Statistics Denmark. Statistikbanken.dk/AKU1. Appendix Table 1a and 1b
6
Statistics Denmark. Statbank.dk/AKU6. Appendix Table 2a and 2b
3
2
2004 Table 10, p. 16). Among those women working part-time, over half do so because they are
caring for children or other family members or they do not desire full-time work; on the other hand,
over half of the men who work part-time do so because of educational reasons (Andersen et al.,
2004, Figure 9, p. 17). Thus, the part-time/full-time labor market pattern reflects the interaction of
gender and age. With respect to employment sectors for year 2003 (Andersen et al. 2004, Table 7,
p. 13), 80% of working men ages 15-66 were employed in the private sector compared to 50% of
working women. Women are more likely to be employed in the public sector and more likely at the
local level, regardless of age. In 2003, 40% of employed women worked in the local public sector
compared to 10% of employed men; 6.5% of both employed men and women worked at the central
state level. The labor market is also gendered by branch Andersen et al. 2004, Figure 7, p. 15)
where men comprise 70% of those employed in: Agriculture/fishing/raw materials, Energy/water
supply, Construction/installation, Transport/postal/telecommunication, while women comprise 70%
of those employed in Public and Personal services. Both men and women work in the
Commerce/hotel/restaurant and Financing/business service branches. The report also notes that
while it is in part related to the branch and job function, more men work flexible working hours
than do women. Among those ages 30-54, 37% of working men compared to 27% of working
women have flex-time (Andersen et al. 2004, Table 13, p. 22). Moreover, when family type is
examined (4 types: single/coupled, with/without children) more men with children have flex-time
(single men, 37.2%; coupled men, 36.2%) than women with children (single women, 26.3%;
coupled women, 27.0%). The report takes the view that flex-time is beneficial to single parents and
notes that single fathers appear to have an advantage over single mothers (Andersen et al. 2004,
Table 15 & text p. 23).
Home & Work – time use: See the time use surveys (Lausten & Sørup, 2003; Bonke et al., 2003)
discussed in the Denmark National Report on Academic Research.
Work – wage gap: With respect to the unadjusted pay gap, women generally earn less than men in
the private sector as well as in both the local and central public sectors. In 2002,7 women’s overall
share of men’s pay across the private, local public and central public sectors was 78%, 83% and
91% respectively. Across all sectors, the gap varies according to job function/occupation. For
example, the gap advantaged women in clerical work in the central public sector in 2000 and 2001
(102%) and in sales or service work in the local public sector in 2000 to 2002 (101% to 102%). On
the other hand, the gap was widest for high level managerial work in the private as well as the local
public sector in 2000 to 2002, ranging from 76% to 79%. Women’s pay approaches that of men’s
in terms of jobs with medium-high level qualifications such as nurses or teachers in the local public
sector (95% in 2000 to 2001), but was less in the private sector in the same category, ranging from
78% to 80%.
Work – management: In the Danish statistical information,8 top management is defined as a
position at the highest level including the word “management” within a private sector business
employing a minimum of 10 persons which carries an annual salary of at least 500,000 DKK
(67,300 €). Top management is then divided into: (1) uppermost management level, managing
director/CEO, a director with reference to a board or to parent company management; and (2) a
manager who works across areas or a managing director who is not working in one specific area. In
2002, women comprised 4% of the first category and 7% of the second category. For seven salary
7
8
Statistics on Women and Men. Appendix Table 3
Statistics on Women and Men. Appendix Table 4
3
categories9 ranging from 500,000 DKK (67,300 €) to over 1,750,000 DKK (over 235,000 €), the
number of women as a proportion of the total of each category decreases as salary increases in the
first management group. In the second management group, the number of women as a proportion
of the total is more stable.
With respect to management in the public sector in 2003,10 Danish statistical information provides 2
categories: municipal and county, each with 3 levels: top (municipal or county director, hospital
director, managing director), upper-middle (administrative manager, deputy director) and lowermiddle (department head, office head, institution head, group leader, or head). At the municipal
level women comprise 60%, 43% and 14% of lower-middle, upper middle and top management,
respectively. The corresponding figures at the county level are 62%, 38% and 24%, respectively.
Work – academia: In 2000,11 women comprised 20.3% of the scientific staff in Danish
universities which represents an increase from 16% in 1993. In 2000, women comprised 7.3% of
professors, 21.4% of associate professors, and 36.7% of assistant professors. The corresponding
figures for 1993 are 4.4%, 17.2% and 24.9% respectively.
4. Social Exclusion
Ethnicity and the labor market, income, education: A recent report, Statistical yearbook on
foreigners in Denmark 2004: status and development (Pedersen 2004), published by the Ministry
for Refugee, Immigration and Integration Affairs, compares immigrants and descendants of
immigrants, both from western and nonwestern countries, with Danish nationals on numerous
dimensions with data from 2003.12 Immigrants and descendants from nonwestern countries overall
showed higher unemployment rates (11.7%) than either immigrants and descendants from western
countries (5.2%) or Danish nationals (4.0%) (Pedersen, 2004, Table 6.1, p.184). In addition,
immigrants and descendants from western (34%) and nonwestern countries (47%) evidenced higher
proportions of those outside the labor force for reasons other than unemployment13 compared to
Danish nationals (20%).
Comparisons by country groupings, birth origin and gender reveal the following patterns (Pedersen,
2004, Table 6.3, p.190): First, there are not large gender differences in unemployment rates within
any group (immigrants and descendants, western and nonwestern countries). In addition,
unemployment rates are highest among immigrants from nonwestern countries (men 12%, women
13%) compared to all other groups (5% to 7%). Gender differences are evident with respect to
being outside the labor force for reasons other than unemployment and with respect to birth origin.
With respect to immigrants, as opposed to descendants, more women than men are outside the labor
force. Gender differences are least stark for descendants from western countries (men 23 %,
women 26%) and nonwestern countries (men 34%, women 37%). They are stronger for immigrants
9
Statistics on Women and Men. Appendix Table 5
Statistics on Women and Men. Appendix Table 6
11
Statistics on Women and Men. Appendix Table 7
12
Attachment to the labor market is measured in various ways including: the unemployment rate (the ratio of those
unemployed to the sum of those working and those unemployed but available for work, i.e., not early retired, not on
temporary leave, not permanently stay-at-home, etc.); the employment rate (the ratio of those employed to an entire
population age 16-64); the economic activity rate (the ratio of those working and those unemployed to an entire
population age 16-64) (Pedersen, 2004). The present discussion deals with the unemployment rate.
13
The category ‘outside the labor force’ can include: some students; persons on various types of leave, persons on
disability; persons in job training; early retirees; newly arrived immigrants on cash assistance or introductory social
benefits; persons considered permanently stay-at-home; immigrants in job training or language education. Some of
these persons will eventually become part of the labor force. Persons with any type of formal job connection are not
included in this category (Pedersen 2004, footnotes to Table 6.6, p. 196).
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of western countries (men 30%, women 39%) and most stark for nonwestern countries (men 41%,
women 55%).
The western/nonwestern distinction is also very significant with respect to comparisons on average
annual income (Pedersen, 2004, Table 6.7, p.198). There are overall large differences between
immigrants and descendants and Danish nationals, and in the case of descendants a large part of this
difference can be explained by the age distribution in this population. In 2002, the overall average
income (in DKK) for immigrants (171,104) and for descendants (155,455) was significantly lower
than that of Danish nationals (244,469). However, the differences compared to Danes are greater
with respect to nonwestern countries (for immigrants, 152,317 and for descendants, 115,140).
Whereas, the average income for immigrants and descendants from western countries (208,761 and
231,849, respectively), is much closer to that of Danish nationals. Furthermore, taking into account
age reduces the difference between descendants (236, 475) and Danish nationals.
With respect to immigrants from nonwestern countries, there are income differences by country of
origin and gender (Pedersen, 2004, Table 6.8, p.200). Men from Somalia have the lowest average
income of all nonwestern men, even lower than women from Somalia (118,892 vs. 132,391);
women from Afghanistan and Pakistan have the lowest average income of all (116,221 and
116,652, respectively). Men (197,196) and women (164,714) from Yugoslavia have the highest
average income. It is also the case that for all educational levels, immigrants from nonwestern
countries have a lower average income than do Danish nationals and women have lower average
incomes than do men, for all educational levels. Further, for both men and women from
nonwestern countries, the greatest income difference compared to Danes is in the category of
advanced higher education (i.e., beyond the bachelor degree); the smallest difference is among
those completing a general gymnasium education (Pedersen, 2004, Table 6.9, p.201).
Regarding education itself – with respect to youth education for 16- to 19-year-olds (education
beyond public school, which can be general gymnasium, business/technical gymnasium or
vocational education) – immigrants from nonwestern countries evidence the weakest representation.
For the 2002/2003 school year (Pedersen, 2004, Table 5.1, p.154), only half (49%) of immigrants
age 16-19 who could have been in this type of education were, as opposed to 69% of descendants
and 76% of Danish nationals. Furthermore, the proportion of young female, nonwestern
descendants in this education was somewhat greater than that of young male descendants (73% vs.
65%). Not surprisingly, this overall pattern and gender difference holds for education beyond
gymnasium level (includes 2-4 year technical programs, 3-5 year programs such as teaching and
nursing, university and other higher education programs such as medical, legal, and engineering).
Only 13% of nonwestern immigrants were in post-gymnasium education compared to 37% of
descendants and 33% of Danish nationals. In addition, 32% of young female, nonwestern
descendants were in post-gymnasium education compared to 22% of males (Pedersen, 2004, Table
5.4, p.160).
Ethnicity and crime: Statistics Denmark examined crime and national origin for the year 2000
(Statistics Denmark 2002). The statistics compared crime rates for persons of foreign national origin
(immigrants and descendants of immigrants) and the rest of the population (persons with at least
one parent of Danish national origin) ages 15-64 on various other social dimensions. Based on
disposition data in 2000 (which represents case processing decisions by police, prosecutors and
courts for both penal and traffic offenses and thus could reflect a selection bias in the criminal
justice system) persons of foreign national origin evidence higher overall rates of law violation
compared to Danish citizens. The analysis notes the skewed age distribution of the population:
60% of immigrants and 86% of descendants of immigrants are in the 15-39 age range compared to
5
51% of the rest of the population. Furthermore, 32% of the descendants of immigrants are in the
15-19 age range compared to less than 8% of immigrants and of the rest of the population. That is
to say that there is an overrepresentation of persons of ethnic minority groups in the age ranges that
are also associated with the highest rates of law violation. (Therefore, Statistics Denmark controls
for this problem in certain analyses by creating a weighted index.) Young men of ethnic minority
groups appear to have the highest rates. For example, within age groups, 11.9% and 18.5% of
descendants of immigrants and 11.3% and 10.9% of immigrants in the 15-19 and 20-29 age ranges
respectively were found guilty of a law violation compared to 6.0% and 8.0% of the rest of the
population.14 An analysis based simply on the age conditional index yields a similar pattern.
However, controlling for age in conjunction with other social factors individually, Statistics
Denmark finds that the difference in rates of law violation between persons of foreign national
origin and the rest of the population is markedly reduced – though does not entirely disappear –
when receiving social benefits, income and employment status are individually taken into account.
It was also reported that rates based on the age conditional index were higher for persons from
nonwestern nations than from other western nations.15
Another way of looking at this is to note that in year 2000 immigrants and descendants ages 15-64
comprised 11.3% of all dispositions for law violations but comprised only 7.7% of all persons ages
15-64. Immigrants and descendants are thus overrepresented in the crime statistics compared to
their size in the national population.16 This pattern is more pronounced for nonwestern countries
separately; in 2002 immigrants and descendants of nonwestern countries comprised 10.0% of all
dispositions and only 4.7% of the national population over age 15 (Pedersen, 2004, p. 142).
Similarly, immigrants and descendants are also overrepresented in prisons and jails. A recent
statement from the Danish Bureau of Prisons noted that as of May 2004, every fifth inmate in
prisons and jails is an immigrant or descendant, a figure which corresponds to immigrants and
descendants housed behind bars at 2.5 times their size in the national population over age 15
(Pedersen, 2004, p.142).
Gaps:
 More data on men and disability, men and age
 Data that allows examination of the intersection of dimensions of social exclusion with
gender, class, age, disability, sexuality and ethnicity
5. Violences
Violent Victimization: The Danish Health and Morbidity Survey 2000 (SUSY 2000) (Kjøller &
Rasmussen 2002) conducted by the National Institute of Public Health posed a variety of questions
via personal interviews (response rate 74%) and self-administered questionnaires (response rate
63%) to a random sample of 22,500 Danish citizens age 16 and over. The survey included
questions about exposure to interpersonal violence, but it is important to note that since these were
embedded in a health-related survey, results related to violence could reflect underreporting.
Furthermore, the abbreviated question format was not designed to explore the context or
consequences of the violence. Out of a total 10,434 respondents, more men than women had been
exposed to violence in the previous year (6% vs. 3.8%, respectively) 17 and more men had been
14
News from Statistics Denmark, Nr. 191, May 14, 2002. Appendix Table 8
Statistical Yearbook 2004, Table 223. Appendix Table 9
16
News from Statistics Denmark, Nr. 191, May 14, 2002. Appendix Table 8
17
Kjøller & Rasmussen 2002, p. 470. Appendix Figure 4
15
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exposed to violence or threats of violence ever (34.2% vs. 24.2%).18 Exposure to violence appeared
to be a youthful phenomenon for both men and women. The highest prevalence rates of violence in
the past year were found in the age 16-24 age range, 26.5% for men and 10.6 for women, compared
to the 25-44 age range, where only 5.5% of men and 4.9% of women report having experienced
violence in the past year. Percentages decreased even further in the upper age ranges. 19 Women are
far more likely than men to report experiencing sexual assault (defined as any actual or attempted
sexual activity by force) overall (4.7% vs. 0.4%) and in all age groups. For age 16-24, 4.1% of
women report sexual assault compared to 0.2% of men.20 Women are also more likely overall to
report experiencing sexual assault as a child than are men (8.1% vs. 1.6%).21
Some additional information from the SUSY 2000 data is available for women only who
experienced physical violence in the past year from the special report Men’s Violence Against
Women (Helweg-Larsen & Kruse 2004, text p.66). There was a slight tendency for women in the
age ranges over 40 to report having experienced more serious forms of violence compared to
younger women. There were also more single, unmarried women reporting violence in the past
year (9.3%) compared to married women (2.4%); more separated women reported violence in the
past year (3.7%) compared to married women. These trends remained after the researchers
controlled for age and education. In the cases where there is information on the relation between
the woman and the perpetrator, 2/3 report the violence was perpetrated by a current or former
partner. It was also revealed that among women age 30-39 who experienced violence in the past
year, four out of five had children living in the home, and the researchers cautiously estimate that
3% of all Danish children under age 15 have witnessed violence against their mothers.
Violent victimization – police records: Crime victimization statistics have been published by the
police in Denmark since 2001. According to police reports for 2002,22 women comprised over half
(55.8%) of crime victims. With respect to crimes against persons, women comprised nearly all of
the victims of morals offenses (incest 87%, rape 98%, indecent exposure 92%, hetero- and
homosexual morals offenses 76%). Women also comprised 33% overall of the victims of violent
crimes; thus more men were victims of violent crimes. Men comprised 72% of murder or attempted
murder victims and 70% of assault victims; men’s proportion of assault victimization increased
with the severity of assault (simple 68%, more serious 77%, aggravated 82%); thus women’s
proportions decreased. Men comprised 56% of threat victims. A study conducted by the Ministry
of Justice (Kyvsgaard, 2000) aimed at assessing the feasibility of compiling victim statistics from
police records analyzed 955 police records in 11 police districts for a 6-month period for crimes of
interpersonal violence including simple and serious assaults, rape, homicide and attempted
homicide. Again, the pattern emerged where men comprised a greater share of the overall violent
victimizations (65%, n= 586) compared to women (27%, n=234) in the cases where the gender and
age of the victim were known with certainty. In addition, details such as the victim-offender
relationship were examined. This analysis revealed that in 50% of the cases of violence against
women, the perpetrator was a current or former partner; in 15% and 9% the offender a total stranger
or a distant acquaintance, respectively.23 On the other hand, in only 1% of the male victim cases
18
Kjøller & Rasmussen 2002, p. 472. Appendix Figure 5
Kjøller & Rasmussen 2002, p. 473. Appendix Figure 6
20
Kjøller & Rasmussen 2002, p. 479. Appendix Figure 7
21
Kjøller & Rasmussen 2002, p. 477. Appendix Figure 8
22
Statistical Yearbook 2004, Table 210. Appendix Table 10
23
Kyvsgaard, 2000, Table 23. Appendix Table 11
19
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was the offender a current or former partner; for male victims the offender was much more likely to
be a total stranger (46%) or a distant acquaintance (27%).24
Violent Victimization – prevalence survey: In a large scale national survey Vold på gaden, i
hjemmet og på arbejdet [Violence on the street, in the home and in the workplace] (Rigspolitichefen
1998), a total of 26,193 persons were interviewed by telephone about their exposure to violence.
This report was not designed to specifically measure partner violence but rather violent
victimization in general. Respondents were asked “Have you been subjected to violence or threats
of violence in the past 12 months that were so serious as to make you afraid?” A positive response
was followed by a series of questions including where and when the violence occurred, whether it
resulted in physical injury, who the perpetrator was – stranger, acquaintance, relationship to victim,
whether a weapon was used, and whether the violence was reported to the police. Only 1% of the
female respondents reported that they had been exposed to violence in the past year and 5% had
been exposed to threats. Prevalence was somewhat higher in the younger age ranges: 3% and 8%
of women age 16-24 had experienced violence and threats, respectively, compared to 1% and 5% of
women age 25-29 and 1% and 0% for age 60-74.25 Furthermore, 81% of the women exposed to
physical violence in the past year reported that the perpetrator was a male and 20% reported that the
perpetrator was a current or former partner; prevalence rates on these dimensions were higher for
women under age 60 compared to women age 60-74.26 With respect to gender differences (See
Rigspolitichefen 1998, Table C.1, men vs. Table D.1, women), 2% of male respondents reported
they had experienced violence in the past year and 5% had experienced threats; prevalence was
highest in the 16-24 year range where 7% and 11% had been exposed to violence and threats,
respectively. Nearly all (99%) of the men exposed to violence reported that the perpetrator was a
male and 74% reported that the perpetrator was an unknown person. Interestingly, 38% of women
reported their perpetrator was an unknown person and this was the case in 100% of the women
respondents ages 60-74. Moreover, while 29% of women reported the violence took place in a
private residence, 30% and 34% respectively reported the violence took place in a work or
educational setting or in a public place. Only 9% of men reported that violence took place in a
private residence; men were far more likely (89% in total) to experience violence in a bar/café,
workplace or educational setting, or in a public place.
Violent criminal behavior – Dispositions: police/court data: According to disposition data for
2002,27 which represents case processing decisions by police, prosecutors and courts, men comprise
the majority of criminal law violations overall for violent crimes at 92% compared to 8% for
women. This breakdown essentially holds for simple and more serious assault, but for aggravated
assault, men comprise 71% of the offenders compared to women who comprise 29%. Men also
comprise 95% and 78% of homicide and attempted homicide offenders, respectively, whereas the
corresponding proportions for women are 5% and 22%. Similarly, men also comprise 98% of the
offenders for moral offenses (incest, rape, indecent exposure, heterosexual morals offenses against
children under age 12.
Men’s violence to women: A recent report Men’s Violence Against Women (Helweg-Larsen &
Kruse 2004) presents no new data but instead documents what is known about men’s violence
24
Kyvsgaard, 2000, Table 26. Appendix Table 12
Helweg Larsen & Kruse, 2004, Victim Statistics Table B. Appendix Table 14
26
Helweg Larsen & Kruse, 2004, Victim Statistics Table C. Appendix Table 15
27
Statistical Yearbook 2004, Table 213. Appendix Table 13
25
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against women (and its treatment) from various existing indicators. Some of these sources are
already reported on in this survey with the addition of what they say about men, so some additional
key information from the report is now presented. Given the authors’ affiliation with the National
Institute of Public Health, the report is especially strong on data from health system records. The
researchers note that in recent years approximately 5000 women (0.2% of all adult women) per year
contact emergency rooms because of violence (up from approximately 4000 in 1995) and that 2/3 of
these women are under 40 years old. The increase is evident in all age groups, but particularly in the
15-19 age range (858 contacts in 2003, or 343 per 100,000 compared to 541, or 606 per 100,000 in
1995). The authors speculate that, rather than an actual increase in violence against women, the
increase could reflect greater societal awareness such that battered women are more open to
contacting emergency rooms as well as to reporting violence to the police, who often request
medical documentation of the violence. Emergency room records may thus reflect better
registration of the cause of injury. They further note that there has been an increase in violence to
women occurring outside the home (the victim-offender relationship unknown) and speculate that
the character of this violence has become more serious and thus more likely to result in injury
requiring medical attention. The report cannot conclude a rise in intimate partner violence based on
emergency room records.
Combining different data sources, the researchers shed light on police-reported violence against
women in terms of the victim-offender relationship and cohabitation. It was determined that of the
5777 cases of violence perpetrated against adult women reported to the police during 2001 and
2002, information on a known perpetrator was available in 4833 (84%) of the cases, those with
charging and sentencing decisions. Of these, it was further determined that in 1258 (26%) of the
cases with a known perpetrator, perpetrators shared an address with the victim during one or more
years in 1996-2002. The researchers thus concluded that at least 26% of the cases of violence
against adult women reported to police represented, with certainty, intimate partner violence
(Helweg-Larsen & Kruse, 2004, text p. 53).
The report also informs on the social status of victims and offenders, based on police data on 5214
separate female victims of violence in 2001-2002. Approximately 60% of victims are women who
are unemployed or outside the workforce due to early retirement, educational reasons or other
reasons not stated in the report, compared to 25% of the total female population ages 16-59.28
Additionally, 55% of the male perpetrators are unemployed or outside the workforce compared to
20% in the total male population ages 16-59.29
We note that this report provides valuable information on the picture of violence against women in
Denmark based on existing data from both raw and combined sources. However, the study was
structured around 7 indicators proposed by the Danish EU presidency in response to the 1995
Beijing Platform for Action – Violence Against Women, with an invitation to future presidencies to
follow up. Beyond availability, it is not known precisely how these indicators were arrived at, i.e.,
in any formal international collaboration. Furthermore, this raises the question as to why resources
were not also devoted to collecting new data based on the most recent research techniques in this
area. This may be due in part to the fact that in 2003 Denmark participated in the International
Violence Against Women Survey (IVAWS) coordinated by The European Institute for Crime
Prevention and Control, affiliated with the United Nations (HEUNI) with inputs from the United
Nations Office on Drug and Crime (UNODC), UNICRI and Statistics Canada. The study applies
methodology from the International Crime Victimization Survey (ICVS) and is based on a survey
28
29
Helweg Larsen & Kruse, 2004, Crime Statistics Table A. Appendix Table 16
Helweg Larsen & Kruse, 2004, Crime Statistics Table B. Appendix Table 16
9
instrument used by Statistics Canada in 1993, which has been used as a model for prevalence
studies of violence against women. The findings from the data collected in 2003 have not been
published yet, but were expected to be available in early 2005.
Women’s shelter statistics: Recent statistics from the National Organization of Shelters for
Battered Women and their Children (Nielsen 2004) based on data from 35 shelters show the
following for year 2003: 2008 women and 2019 children moved into shelters; the extent of repeat
move-ins is not reported. Of the women, 878 (44%) were born in a country other than Denmark;
624 and 31% were citizens of a country other than Denmark. Over half of the women with nonDanish citizenship (54%) came to Denmark to be reunited with family; the remaining are primarily
refugees (14%) and immigrants (10%). Foreign women come primarily from countries in the
Middle East. They also come from Somalia, Bosnia, Sri Lanka, Thailand, Greenland, Poland and
Vietnam. Some women of non-Danish citizenship (33%), primarily from eastern European and
East Asian lands, came to Denmark to marry men with Danish citizenship. Women of nonwestern,
ethnic minority groups were approximately twice as likely to be married with children than were
women born in Denmark or women from other Nordic or western countries, who were more often
cohabitating, with or without children. Of the total 2008 women, 63% were receiving some type of
welfare aid. With respect to violence, the majority of women in shelters were escaping violence
committed by a current (77%) or former (13%) husband or cohabiting partner; 66% of the
perpetrators are of Danish citizenship. In addition, 69% of the women reported experiencing both
physical and psychological violence, 2% have experienced only physical violence and 17% only
psychological violence. Also, 5% reported having experienced rape on a regular basis, 32% threats
of violence, and 11% reported a weapon or object has been used in a violent incident. Property
damage was reported by 15% and economic violence, forced marriage and sexual assault was
reported by 5%. These experiences of various types of violence differed little across ethnic groups.
Child sexual abuse: See the prevalence study (Helweg-Larsen & Larsen 2002) discussed in the
Denmark National Report on Academic Research.
Gaps:
 Additional data on men’s violence against women particularly a prevalence study that
takes into account ethnicity
 Additional data on child sexual abuse in the form of a retrospective survey of adults
6. Health
Health-related behaviour - smoking, alcohol consumption, use of euphoric substances:
The Danish Health and Morbidity Survey 2000 (SUSY) (Kjøller & Rasmussen 2002) included
questions about certain health-related behaviours. Among the findings for 2000, it was found that
36.3% of men compared to 31.8% of women smoked daily. Higher prevalence rates were found for
men in all age groups (from 5-8 percentage points) with the exception of the 25-44 age range with
35% of men and 34% of women reporting they smoked daily.30 More men than women also
reported being heavy smokers (more than 15 cigarettes per day) in all age groups and this was most
evident in the 16-24 and 25-44 age ranges (18% vs. 11% and 25% vs. 19%, respectively). The
report also notes relationships between daily smoking and education and socioeconomic status.
Both daily and heavy smoking prevalence rates were higher among those with the least education,
higher among unskilled workers and the unemployed and relatively high among those self30
Kjøller & Rasmussen, 2002, p. 514. Appendix Figure 9
10
employed without employees. They were also highest among those separated and divorced
compared to other couple statuses. With respect to alcohol consumption, the survey found that in
all age groups, more men than women reported having had at least one drink on the most recent
weekday (46.2% vs. 29.0%) and the size of the difference increased with age, the largest being a 27
percentage point difference in the 67+ age range. In addition, almost twice as many men as women
(14.8% vs. 8.7%) reported exceeding the weekly limit set by the National Board of Health (14
standard drinks for women and 21 for men).31 Differences were evident in all age groups, the
largest being a 9 percentage point difference in the youngest age range, 16-24. Prevalence rates for
drinking on the most recent weekday were higher among those with more education and higher for
those self-employed with employees as well as among the lowest level of salaried employees. They
were highest among married people and those separated or divorced. There was a tendency for
prevalence rates for exceeding the weekly limit to increase with the amount of education; this rate
was also highest among the unemployed.
The survey also found that the most often used euphoric substance in the Danish population is
cannabis, i.e., hashish, marijuana, etc. (9.7 of the population reported using it within the last year),
followed by amphetamines (2.2%) and cocaine (1.4%); other substances such as ecstasy and LSD
were under 1%. More than twice as many men compared to women (13.7% vs. 6.3%) reported
cannabis use within the last year, and the difference was most evident in the younger age ranges. In
the 16-24 age range, 25.8% of men compared to 15.0% of women reported cannabis use within the
last year; the corresponding figures for the 25-44 age range were 9.5% of men compared to 3.3% of
women.32 A higher prevalence of cannabis use was also found among those with shorter education,
unskilled workers and those unemployed. Married persons had the lowest prevalence rate
compared to other couple statuses.
Diseases affecting both genders: With respect to diseases that can affect both genders and can
lead to hospital admissions, data from 2002 (Kruse & Helweg-Larsen 2004) revealed some gender
differences.33 Although the difference is more pronounced in the younger age ranges, in all age
groups there were more men than women admitted to hospitals for cardiovascular disease, the
gender ratio being 1.81. The researchers note that while woman’s (pre-menopausal) hormonal
make-up provides some protection from cardiovascular disease, women are more adversely affected
by smoking than are men in this regard. More men were also admitted for stomach and intestinal
cancers, the gender ratio being 1.25. The gender difference in terms of a higher rate for men was
most pronounced for cancer of the alimentary canal (food tube) and could be attributed to men’s
higher overall alcohol intake as well as its content (e.g. whisky). More women than men were
admitted for autoimmune diseases, the overall gender ratio being 0.57 and this could be due to
hormonal, genetic and environmental differences. Women and men were admitted to psychiatric
units overall at nearly equal rates but at the youngest age range (15-24) more women were admitted,
whereas there were more men in the 35-44 year range. Differences were evident in the reasons for
psychiatric admissions where over twice as many men were admitted for problems related to
substance abuse and nearly three times as many women were admitted for affective disorders such
as depression and manic depressive psychosis. Nearly twice as many men were admitted for
schizophrenia.34
31
Kjøller & Rasmussen, 2002, p. 515. Appendix Figure 10
Kjøller & Rasmussen, 2002, p. 523. Appendix Figure 11
33
Kruse & Helweg-Larsen (2004), Table 6.1, p. 35. Appendix Table 18
34
Kruse & Helweg-Larsen (2004), Table 6.12, p. 45. Appendix Figure 12
32
11
Average life span; mortality: Average life span increased throughout the 1990s for both men and
women and the difference between men and women decreased slightly. From 1990/91 to 2002/03,
the average life span for men increased from 72.2 to 74.9 years and for women it went from 77.8 to
79.5. The gender difference decreased from 5.6 to 4.6 years during the same time period.35 Men
show generally higher mortality rates than women in all age groups. For 2002/03, the gender ratio
is highest in the 10-20 and 20-30 age ranges at 2.4; from age range 30-40 through 70-80, the gender
ratio steadily decreases from 1.9 to 1.4.36
In a special study of mortality rates and occupations, Statistics Denmark reports that mortality
rates do vary by occupational groups. Regarding men and mortality rates for 1991-95, unskilled
hotel and restaurant workers had a mortality rate well above the average for all employed men (180
vs. 100) whereas architects, consulting engineers, teachers in higher education and independent
farmers showed mortality rates well below the average (50-65 vs. 100).37 Regardless of skill level
(unskilled, skilled, or self-employed, men in the hotel and restaurant business have high mortality
rates (182 to 159 respectively.)38 It was also found that the difference in mortality rate for men in
high- versus low-skilled positions was greater than that of similarly positioned women in the same
occupational group (Andersen, Laursen & Petersen, 2001). An additional analysis of the larger
occupational groups going back to 1970 revealed that mortality rates between unskilled men and
those in skilled occupational positions increased steadily in 25 years. While there was essentially
no difference between the two groups in 1970-75, there was a 20 percentage point difference
(unskilled being higher) in 1991-95.39
With respect to cause of death,40 gender differences are notable in cardiovascular disease with
respect to age. For 1999, the number of deaths of men in the 35-49 and the 50-59 age groups was
significantly higher than for women, the gender ratios being 5.1 and 4.2, respectively. The gap
lessens in the 60-69 age range at 2.6 and the number of deaths of women exceeds that of men in the
70+ range, the ratio being 0.87. In 1999, more men than women died in motor vehicle accidents
overall (375 vs. 139) and this was particularly evident in the 15-34 age range with a gender ratio of
4.2. In addition, while more women than men died overall in “other accidents” (1038 vs. 905), 904
of the women’s accidents (87%) were in the 70+ age range. The numbers for men were higher in
the younger age ranges, again particularly in the 15-34 range with a gender ratio of 7.4.
Mortality: Suicide – attempts, completed acts, methods: Based on data provided from
Denmark’s Center for Suicide Research, in 1999, a total of 559 men committed suicide compared to
199 women. These numbers correspond to rates of 26.2 and 9.0 per 100,000, respectively. The
1999 data showed that suicide rates increased gradually with age for both genders, but elderly men
age 70+ evidenced a dramatic increase at 49.6, the second highest rate being 30.1 in the 40-49 age
range.41 Gender differences in suicide attempts are not as stark and women actually showed
somewhat higher rates, 222.8 compared to 187.6 for men in 2001.42 There were also gender
differences in methods for both completed acts and attempts. Data on actual suicide methods
(1995-1999) showed that more women use poisoning and drowning than do men whereas more men
35
News from Statistics Denmark, Nr. 234, May 27, 2004. Appendix Figure 13
News from Statistics Denmark, Nr. 234, May 27, 2004. Appendix Table 20
37
News from Statistics Denmark, Nr. 268, June 21, 2001. Appendix Figure 14
38
Statistical Yearbook 2004, Table 56. Appendix Table 21
39
News from Statistics Denmark, Nr. 268, June 21, 2001.
40
Statistical Yearbook 2004, Table 52. Appendix Table 22a and 22b
41
Center for Suicide Research. Appendix Table 23a
42
Center for Suicide Research. Appendix Table 23b
36
12
use hanging and shooting.43 Data on attempts (1997-2001) showed poisoning is the most prevalent
method for both genders and more women use it. More men than women attempt suicide with a
sharp object or by hanging.44
Gaps:
 Additional data on men’s health practices
 Data that allows examination of the intersection of men’s health and well-being to
other areas of life
7. Discussion
The statistical information seems to be heavily weighted by the area of home and work. This
emphasis may be due to the prominence of the gender equality debate in that area. The gender
equality discourse is gradually expanding into other areas such as violence against women.
8. Bibliography
Andersen, Monica, Steen Bielefeldt Pedersen & Vesla Skov (2004) Køn og arbejdsliv [Gender and
working life]. Copenhagen: Statistics Denmark.
Andersen, Otto, Lisbeth Laursen & Jørn Korsbø Petersen (2001) Dødlighed og erhverv, 1981-1995
[Mortality and occupation, 1981-1995]. Copenhagen: Statistics Denmark.
Helweg-Larsen, Karin & Marie Kruse, eds. (2004) Mænds vold mod kvinder: omfang, karakter og
indsats om vold [Men’s violence against women: extent, characteristics and measures to eliminate
violence]. Copenhagen: Minister for Gender Equality, The National Observatory on Violence
Against Women & The National Institute of Public Health. Retrieved December 13, 2004 from
http://www.det-nationale-voldsobservatorium.org/database/www_database/database_index.htm
Kjøller, Mette & Niels Kr. Rasmussen (2002) Sundhed og sygelighed i Danmark 2000: og
udviklingen siden 1987(SUSY 2000) [Health and morbidity in Denmark 2000: and development
since 1987]. Copenhagen: National Institute of Public Health.
Kruse, Marie & Karin Helweg-Larsen (2004) Kønsforskelle i sygdom og sundhed [Gender
differences in sickness and health]. Copenhagen: Minister for Gender Equality. Retrieved October
13, 2004 from http://www.lige.dk/Default.asp?Id=372&AjrNws=318&AjrNwsPg=1
Kyvsgaard, Britta (2000) “Offerstatistik og statistik om gerningssituationen, november 2000
[Victim statistics and statistics on the crime situation, November 2000]. Copenhagen: Ministry of
Justice. Retrieved from http://www.jm.dk/wimpdoc.asp?page=document&objno=51673
Nielsen, Sissel Lea (2004) Landsorganisation af Kvindekrisecentre, LOKK Årsstatistic 2003
[National Organization of Shelters for Battered Women and their Children-Annual Statistics 2003].
Esbjerg: Videns- & Formidlingscenter for Socialt Udsatte. Retrieved January 3, 2005 from:
http://www.lokk.dk/statistik/LOKKaarsstatistik2003.pdf
43
44
Center for Suicide Research. Appendix Table 23c
Center for Suicide Research. Appendix Table 23d
13
Pedersen, Michala Mørup, ed. (2004) Årbog om udlændinge i Danmark 2004 – status og udvikling
[Statistical yearbook on foreigners in Denmark 2004: status and development]. Copenhagen:
Ministry for Refugee, Immigration and Integration Affairs. Retrieved December 2, 2004 from:
http://www.inm.dk/publikationer/aarbog_udlaendinge_04/
Rigspolitichefen [National Police Commissioner] (1998) Vold på gaden, i hjemmet og på arbejdet:
oversigt over resultater fra voldsofferundersøgelsen 1995/1996 [Violence on the street, in the home
and at work: an overview of the results from a violence victimization study 1995/1996].
Copenhagen: Rigspolitichefens Trykkeri.
Statistics Denmark. News from Statistics Denmark. http://www.dst.dk/Statistik/Nyt.aspx
or http://www.dst.dk/HomeUK/Statistics/ofs/News.aspx
Statistics Denmark (2002) Sociale forhold, sundhed og retsvæsen (Statistiske Efterretninger) [Social
conditions, health and the legal system (Statistical Reports)] 2002:9.
Statistics Denmark. Statistical Yearbook 2004.
http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx?
or http://www.dst.dk/HomeUK/Statistics/ofs/Publications/Yearbook.aspx
Websites
Center for Suicide Research www.selvmordsforskning.dk/home.htm
Statistics Denmark www.dst.dk
Statistics on Women and Men http://www.dst.dk/ligestilling.aspx
14
APPENDIX: Denmark National Report on Statistical Information
Home and Work
Figure 1: Fathers receiving leave benefit during the 2-week period, in 15th - 24th week,
and in 25th -26th week, in percent of live births, 1995-2000.
Source: News from Statistics Denmark, Nr. 82, February 15, 2001
http://www.dst.dk/Statistik/Nyt.aspx
---------------------------------------------------------------------------------------------------------Figure 2: Fathers on leave during the 2-week period, in 15th - 24th week,
and in 25th -26th week, in percent of live births, 1996-2001.
Source: News from Statistics Denmark, Nr. 138, April 11, 2002
http://www.dst.dk/Statistik/Nyt.aspx
15
Figure 3: Average number of weeks for fathers on leave, 1993-2003
Source: News from Statistics Denmark, Nr. 143, April 5, 2004
http://www.dst.dk/Statistik/Nyt.aspx
--------------------------------------------------------------------------------------------------------------
16
Table 1a: Population (15-66 years) in thousands by sex, employment status - 2004Q3
Men
Employed
Persons outside the labour force
Unemployed
1462
306
87
Women
Employed
Persons outside the labour force
Unemployed
1293
447
82
Table 1b: Population (15-66 years) in thousands by sex, age, employment status – 2004Q3
Men
Women
15-29 years Employed
Persons outside the labour force
Unemployed
349
87
42
30-54 years Employed
Persons outside the labour force
Unemployed
868
75
34
55-66 years Employed
Persons outside the labour force
Unemployed
245
144
12
15-29 years Employed
Persons outside the labour force
Unemployed
326
116
24
30-54 years Employed
Persons outside the labour force
Unemployed
781
124
47
55-66 years Employed
Persons outside the labour force
Unemployed
187
207
10
Source: Tables 1a and 1b - http://statistikbanken.dk/AKU1
http://www.statistikbanken.dk/statbank5a/default.asp?w=1024
17
Table 2a: Employed (in thousands) by sex, working time - 2004Q3
Men
14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
88
145
659
348
211
11
Women
14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
116
444
530
157
36
10
Source: http://statbank.dk/AKU6
http://www.statistikbanken.dk/statbank5a/default.asp?w=1024
18
Table 2b: Employed (in thousands) by sex, age, working time - 2004Q3
Men
Women
15-29 years 14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
69
50
136
62
28
3
30-54 years 14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
7
71
404
235
146
5
55-66 years 14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
12
23
119
51
37
4
15-29 years 14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
93
81
119
28
2
2
30-54 years 14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
13
283
346
108
25
6
55-66 years 14 hours and under
15-36 hours
37 hours
38-48 hours
49 hours and over
no hours given
10
80
65
21
8
3
Source: http://statbank.dk/AKU6
http://www.statistikbanken.dk/statbank5a/default.asp?w=1024
19
Table 3: Women’s proportion of men’s wage by job function/occupation for private, local
public and central public sectors 2000-2002
Source: Statistics on Women and Men.
http://www.dst.dk/Sites/KVM/Indkomst%20og%20l%C3%B8n/kv_andel.aspx
-----------------------------------------------------------------------------------------------------------------Table 4: Top Management in private sector by gender and position category - 2002
Top Mgt. - category 1 Top Mgt. - category 2
Men
Women
4103
161
4264
(96%)
(4%)
(100%)
1281
96
1377
(93%)
(7%)
(100%)
Category 1 = uppermost management level, managing director/CEO, a director with reference to a
board or to parent company management
Category 2 = a manager who works across areas or a managing director who is not working in one
specific area
Source: Adapted from Statistics on Women and Men.
http://www.dst.dk/Sites/KVM/Ledelse/oversigt.aspx
-------------------------------------------------------------------------------------------------------------------
20
Table 5: Top Management in private sector by gender, position category and annual salary
(DKK) - 2002
Source: Statistics on Women and Men.
http://www.dst.dk/Sites/KVM/Ledelse/Aarsloen.aspx
------------------------------------------------------------------------------------------------------------------Table 6: Local and county public sector management by gender - 2003
Local Public Mgt.
Top
Upper-middle
Lower-middle
County Public Mgt.
Top
Upper-middle
Lower-middle
Women – pct.
14
43
60
Men – pct.
86
57
40
24
38
62
76
62
38
Source: Adapted from Statistics on Women and Men.
http://www.dst.dk/Sites/KVM/Ledelse/ledelse_kom_amt.aspx
----------------------------------------------------------------------------------------------------------------------
21
Table 7: Women in scientific positions in universities – 1993-2000
Source: Statistics on Women and Men.
http://www.dst.dk/Sites/KVM/Uddannelse/Uni_vid_pers.aspx
22
Social Exclusion
Ethnicity and crime
Table 8: Crime frequency by age and national origin 2000
Source: News from Statistics Denmark, Nr. 191, May 14, 2002
http://www.dst.dk/Statistik/Nyt.aspx
----------------------------------------------------------------------------------------
Table 9: Crime frequency by age, gender and national origin 2000
Source: Statistical Yearbook 2004, Table 223
http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx
23
Violences
Figure 4: Percentage of men and women exposed to violence in the past year (SUSY)
Source: Kjøller and Rasmussen, 2002, p. 470, Provided by Statistics on Women and Men:
http://www.dst.dk/Sites/KVM/Helbredsforhold/vold_overgreb.aspx
---------------------------------------------------------------------------------------------------------Figure 5: Percentage of men and women ever exposed to violence and sexual assault (SUSY)
Source: Kjøller and Rasmussen, 2002, p. 472, Provided by Statistics on Women and Men:
http://www.dst.dk/Sites/KVM/Helbredsforhold/vold_overgreb.aspx
-----------------------------------------------------------------------------------------------------------
24
Figure 6: Percentage of men and women ever exposed to violence by age groups (SUSY)
Source: Kjøller and Rasmussen, 2002, p. 473, Provided by Statistics on Women and Men:
http://www.dst.dk/Sites/KVM/Helbredsforhold/vold_overgreb.aspx
-------------------------------------------------------------------------------------------------Figure 7: Percentage of men and women exposed to sexual assault as adult by age group
(SUSY)
Source: Kjøller and Rasmussen, 2002, p. 479, Provided by Statistics on Women and Men:
http://www.dst.dk/Sites/KVM/Helbredsforhold/vold_overgreb.aspx
--------------------------------------------------------------------------------------------------
25
Figure 8: Percentage of men and women exposed to sexual assault as child by age group
(SUSY)
Source: Kjøller and Rasmussen, 2002, p. 477, Provided by Statistics on Women and Men:
http://www.dst.dk/Sites/KVM/Helbredsforhold/vold_overgreb.aspx
----------------------------------------------------------------------------------------------------------------
Table 10: Victims of crime by crime type and gender 2002
Source: Statistical Yearbook 2004, Table 210
http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx
26
Table 11: Violent episodes against women by victim-offender relationship and type of
violence (simple vs. serious assault)
Nuv./tidl. ægtefælle, samlever,
kæreste
Anden familierelation
Tidligere og nuværende venner
Afhængighedsforhold
Bekendte
Svagt kendskab
Intet kendskab
Uoplyst
I alt
I alt (N)
Simpel
vold
48%
Alvorlig
vold
71%
I alt
3%
7%
5%
4%
10%
17%
7%
100%
217
0%
12%
0%
0%
0%
0%
18%
100%
17
3%
7%
4%
4%
9%
15%
8%
100%
234
50%
Source: Adapted from Kyvsgaard 2000, Table 23.
http://www.jm.dk/wimpdoc.asp?page=document&objno=51673
-------------------------------------------------------------------------------------------------------------------Table 12: Violent episodes against men by victim-offender relationship and type of violence
(simple vs. serious assault)
Nuv./tidl. ægtefælle, samlever,
kæreste
Anden familierelation
Tidligere og nuværende venner
Afhængighedsforhold
Bekendte
Svagt kendskab
Intet kendskab
Uoplyst
I alt
I alt (N)
Simpel
vold
1%
Alvorlig
vold
1%
I alt
3%
9%
2%
7%
26%
47%
6%
101%
490
3%
10%
1%
2%
32%
43%
7%
99%
96
3%
9%
2%
6%
27%
46%
6%
100%
586
1%
Source: Adapted from Kyvsgaard 2000, Table 26.
http://www.jm.dk/wimpdoc.asp?page=document&objno=51673
27
Table 13: Criminal dispositions by age and gender
Source: Statistical Yearbook 2004, Table 213
http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx
28
Table 14:
Source: Helweg-Larsen & Kruse (2004): Victim Statistics Table B.
http://www.det-nationale-voldsobservatorium.org/database/www_database/database_index.htm
(Adapted from Rigspolitichefen, 1998, Table D.1, p.164-5)
---------------------------------------------------------------------------------------------------Table 15:
Source: Helweg-Larsen & Kruse (2004): Victim Statistics Table C.
http://www.det-nationale-voldsobservatorium.org/database/www_database/database_index.htm
(Adapted from Rigspolitichefen, 1998, Table D.1, p.164-5)
----------------------------------------------------------------------------------------------------------
29
Table 16:
Source: Helweg-Larsen & Kruse (2004): Crime Statistics Table A
http://www.det-nationale-voldsobservatorium.org/database/www_database/database_index.htm
.
30
Table 17:
Source: Helweg-Larsen & Kruse (2004): Crime Statistics Table B
http://www.det-nationale-voldsobservatorium.org/database/www_database/database_index.htm
.
31
Health
Figure 9:
Source: Kjøller & Rasmussen, 2002, p. 514., http://www.si-folkesundhed.dk/susy/
-----------------------------------------------------------------------------------------------------Figure 10:
Source: Kjøller & Rasmussen, 2002, p. 515., http://www.si-folkesundhed.dk/susy/
32
Figure 11:
Source: Kjøller & Rasmussen, 2002, p. 523., http://www.si-folkesundhed.dk/susy/
------------------------------------------------------------------------------------------------------------------Table 18: Diseases affecting both genders - number of first time hospital admissions, 2002
Source: Kruse & Helweg-Larsen (2004), Table 6.1, p. 35
Provided by Statistics on Women and Men:
http://www.dst.dk/Sites/KVM/Helbredsforhold/Koensforskelle_sygdomme.aspx
----------------------------------------------------------------------------------------------------------
33
Figure 12: Psychiatric diseases by diagnosis and gender - first-time admissions, 2002
Source: Kruse & Helweg-Larsen (2004), Table 6.12, p. 45
---------------------------------------------------------------------------------------------------------
Figure 13: Average life span for men and women, 1990/91-2002/03
Table 19: Average life span for men and women, 1990/91-2002/03
Source: News from Statistics Denmark, Nr. 234, May 27, 2004
http://www.dst.dk/Statistik/Nyt.aspx
------------------------------------------------------------------------------
34
Table 20: Deaths per 1000 by age and sex
Source: News from Statistics Denmark, Nr. 234, May 27, 2004
http://www.dst.dk/Statistik/Nyt.aspx
Figure 14: Mortality index among occupational groups, Men 1991-95, where for all men in
occupations: index=100
Source: News from Statistics Denmark, Nr. 268, June 21, 2001
http://www.dst.dk/Statistik/Nyt.aspx
35
Table 21: Mortality and occupation 1991-1995
Source: Statistical Yearbook 2004, Table 56
http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx
36
Table 22a: Deaths by cause, 1999 - Men
Source: Statistical Yearbook 2004, http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx
37
Table 22b: Deaths by cause, 1999 - Women
Source: Statistical Yearbook 2004, http://www.dst.dk/Statistik/ags/Statistiskaarbog.aspx
38
Table 23a: Suicides in Denmark in 1999 (number, rate per 100,000)
Age
15-19
20-29
30-39
40-49
50-59
60-69
70+
Total
Men
Number
13
73
86
113
102
60
112
559
Rate
9.1
19.9
20.6
30.1
27.5
26.0
49.6
26.2
Women
Number
1
20
13
41
41
27
56
199
Rate
0.7
5.6
3.3
11.2
11.2
10.9
16.2
9.0
Total
Number
14
93
99
154
143
87
168
758
Rate
5.0
12.9
12.1
20.8
19.4
18.2
29.4
17.4
Source: Center for Suicide Research - http://www.selvmordsforskning.dk/home.htm
-----------------------------------------------------------------------------------------------------------Table 23b: Suicide Attempts (incidents) in Funen County 2001 (number, rate per 100,000)
Age
15-19
20-29
30-39
40-49
50-59
60-69
70+
Total
Men
Number
19
72
116
69
50
8
13
347
Rate
149.7
247.7
339.2
210.0
151.3
36.5
61.1
187.6
Women
Number
58
119
71
99
56
13
13
429
Rate
482.2
424.1
216.8
307.9
171.6
56.7
40.6
222.8
Total
Number
77
191
187
168
106
21
26
776
Rate
311.5
334.4
279.3
258.4
161.4
46.9
48.8
205.6
Source: Center for Suicide Research - http://www.selvmordsforskning.dk/home.htm
(As noted on the CFS website, there is no national level data on suicide attempts. Funen County is
considered representative of Denmark in terms of sociodemographic, socioeconomic and healthrelated conditions. The population of Funen comprises 10% of the total Denmark population.)
----------------------------------------------------------------------------------------------------------------Table 23c: Methods of suicide (1995-1999)
Method
Poisoning
Hanging
Drowning
Shooting
Other
Men (%)
26.8
39.3
5.3
14.5
14.1
Women (%)
40.2
30.6
13.0
0.6
15.6
Source: Center for Suicide Research - http://www.selvmordsforskning.dk/home.htm
39
Table 23d: Methods of suicide attempts (1997-2001)
Method
Poisoning
Hanging
Drowning
Sharp object
Other
Men (%)
63.9
3.2
0.7
27.4
4.8
Women (%)
77.8
0.8
0.7
17.6
2.9
Source: Center for Suicide Research - http://www.selvmordsforskning.dk/home.htm
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40