In 2023, about **** percent of the estimated number of homeless individuals in the United States were male, compared to ** percent who were female.

Yearly statewide and by-Continuum of Care total counts of individuals receiving homeless response services by age group, race, gender, veteran status, and disability status.

This data comes from the Homelessness Data Integration System (HDIS), a statewide data warehouse which compiles and processes data from all 44 California Continuums of Care (CoC)—regional homelessness service coordination and planning bodies. Each CoC collects data about the people it serves through its programs, such as homelessness prevention services, street outreach services, permanent housing interventions and a range of other strategies aligned with California’s Housing First objectives.

The dataset uploaded reflects the 2024 HUD Data Standard Changes. Previously, Race and Ethnicity were separate files but are now combined.

Information updated as of 11/13/2025.

In 2024/25, ****** men were reported to be sleeping rough in London with a further ***** women, and ** non-binary people. Since 2010/11 there has been an increase in the number of people reported to be sleeping rough in London, increasing from almost ***** in 2010/11 to more than ****** by 2022/23. Throughout this time period, the majority of people seen to be sleeping rough in London have been men. Characteristics of homeless people in London Of the rough sleepers seen in London in 2023/24, the most common age group were those aged between 36 and 45, at *****. In terms of nationality, most rough sleepers were from the United Kingdom at ***** people, with Romanian being the second-highest nationality, at *** people. The London Borough which had the highest number of people sleeping rough was Westminster, at ***** people, while the borough of Sutton had the fewest rough sleepers, at **. Tragic implications of homelessness In 2021, *** homeless people in London lost their lives, which was the highest number of homeless deaths per region in England and Wales. In terms of the homeless death rate, the worst region was also London, at **** deaths per million people in 2021. North West England had the second-highest deaths per million people, at **. Between 2013 and 2019, the number of homeless deaths in England and Wales increased from 392 to ***, before falling to *** in 2020 and *** in 2021.

As of 31 January 2024, ** percent of homeless people in Germany were men. ** percent were women and of around *** percent, the gender was unknown. Therefore, more than half of the homeless people in homeless accommodation* were men.

Yearly statewide and by-Continuum of Care total counts of individuals receiving homeless response services by age group, race, and gender. This data comes from the Homelessness Data Integration System (HDIS), a statewide data warehouse which compiles and processes data from all 44 California Continuums of Care (CoC)—regional homelessness service coordination and planning bodies. Each CoC collects data about the people it serves through its programs, such as homelessness prevention services, street outreach services, permanent housing interventions and a range of other strategies aligned with California’s Housing First objectives. The dataset uploaded reflects the 2024 HUD Data Standard Changes. Previously, Race and Ethnicity are separate files but are now combined. Information updated as of 7/15/2024.

In 2023, about *** percent of the estimated number of unaccompanied homeless youth in the United States were transgender. In comparison, **** percent were male.

Gender demographics of the homeless population in the City of Corona, CA.

This data set contains calls for service at homeless shelters. Disclaimer - Race/Age/Gender/Ethnicity data is not captured for all records. Update Frequency: Daily

The Point In Time Unsheltered Homeless Census by Gender data. The Housing Inventory Count Submitted to the U.S. Department of Housing and Urban Development (HUD) Additional information available at: https://www.hudexchange.info/resources/documents/Notice-CPD-17-08-2018-HIC-PIT-Data-Collection-Notice.pdf 2017 data collected January 26, 2017, 2018 data collected February 22, 2018.

Experimental Statistics showing the number of deaths of homeless people in England and Wales, by sex, five-year age group .

https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsofhomelesspeopleinenglandandwales

Photo by Jon Tyson on Unsplash

In 2024, there were reported to be ***** men sleeping rough on a single night in England, and *** women, with a further *** people whose gender was not known. Between 2017 and 2024, the majority of rough sleepers reported in England have been men.

Accommodated homeless persons: Federal states, reference date, nationality, gender, age groups, household type

ABSTRACT Objectives: to analyze characteristics of homeless people and factors associated with living on the streets. Methods: a census-type sectional survey carried out between 2015 and 2018, in the municipality of Maringá-Paraná. A total of 701 homeless answered a structured questionnaire with sociodemographic data, living conditions, and drug use. We used Pearson’s correlation test for the association analysis of the variables at a 95% confidence level. Results: men (90.7%) the average age of 37.7 years had been homeless for an average of 5.39 years. Most had little education (54.2%), and homelessness was due to drug use (47.2%) and family disagreements (38.9%). Conclusions: drug use and family disagreements were the main reasons for homelessness. Time on the street, gender, and drugs were associated with a negative correlation to be homeless; and age, mean daily income, the number of daily meals, having been in prison, and having an income source were associated with positive correlation.

This statistic displays the gender distribution of the homeless population in South Korea in 2016. During the measured time period, men accounted for **** percent of the entire population who did not have a permanent dwelling in South Korea.

The information is collected in order to establish the number and type of households that were accepted as homeless by local authorities during the period and the reasons why these households are homeless. It is also used to establish the number of homeless households in temporary accommodation and the types of accommodation provided. This data is used by the Welsh Government, homelessness agencies and other housing organisations, in order to help monitor trends in the overall level of statutory homelessness across Wales. Quality information 1. This data covers the age and sex of the applicant, not the age and sex of every person in the household. 2. Homelessness data may be subject to seasonal variations, however the data shown in this cube has not been seasonally adjusted and care should be taken when making comparisons between successive quarters. 3. All the figures are rounded independently to the nearest 5 to protect the identity of individuals. As a result, there may be a difference between the sum of the constituent items and the total. An asterisk is shown when the data item is disclosive or not sufficiently robust for publication.

The information is based on an annual statistical return completed by local authorities in Wales. The information is collected in order to establish the number and type of households that were provided with assistance by local authorities during the period. This data is used by the Welsh Government, homelessness agencies and other housing organisations, in order to help monitor trends in the overall level of statutory homelessness across Wales.

In 2024, about **** percent of the estimated number of homeless veterans in the United States were male, compared to **** percent who were female.

BC Stats (with partners at the Ministry of Housing, Ministry of Social Development and Poverty Reduction (SDPR), and BC Housing) has developed aggregated summary statistics estimating the homeless population in B.C. These estimates were derived from three administrative service use datasets from the Data Innovation Program (DIP): shelter use from BC Housing, social assistance payments from SDPR, demographic information from the Health medical service plan (MSP) central demographics file. The analytic definition of homelessness includes individuals who received income assistance with no fixed address for at least three consecutive months or those who visited a shelter at any time throughout the year. Estimates have been aggregated into four tables: * Annual estimates of the homeless population by age and gender * Annual estimates of the homeless population by chronicity category (chronic vs non-chronic homelessness) * Annual estimates of the homeless population by census division * Monthly estimates of the homeless population by service use (income assistance with no fixed address, shelter use, or both) \ Estimates are available for 2019-2022. Full methodology details are available in the Homeless Cohort Development - Technical Documentation resource.

This study was undertaken to establish: the characteristics of single homeless people; the reasons why single people become and remain homeless; the accommodation and support needs and preferences of single homeless people. Demographic details (age, gender, ethnic background, education, employment, income, health, experience of institutions and the armed forces); present and previous accommodation; experience of sleeping rough; reasons for leaving last home; looking for accommodation; accommodation expectations and preferences; need for care and support.

A key objective of the project was to compare and contrast the priorities and agendas of multiply excluded homeless people (MEHP) with those of a diverse range of agencies which support, or routinely come into contact with MEHP, in order to better understand the causes and potential solutions to multiple exclusion homelessness. Several strategies to ensure user participation were built into the project. Specifically, two teams (four people in Nottingham and six in London), of former homeless people who had previously made use of services provided by Framework and Thames Reach (two housing associations that provide a wide range of accommodation and support services for homeless people), were recruited and trained to work as co-researchers on the project. Purposive, non random sampling was used to identify suitable fieldwork participants. Semi structured interviews were conducted in the city of Nottingham (55) and the London Boroughs of Lambeth, Southwark and Lewisham (53) with a total of 108 single multiply excluded homeless people (74 men, 34 women). Homeless participants were recruited from a range of organisations. They included people who used, (or who had recently used), an assortment of services provided by Framework and Thames Reach and also users of various services offered by a number of other statutory and voluntary agencies. Additionally, semi structured interviews with 44 key informants (24 Nottingham, 20 London) from 40 statutory and voluntary sector agencies which routinely come into contact with MEHP, were conducted.

This study explores how far multiple exclusion homelessness might be explained by inconsistencies between the priorities of homeless people and those of supporting agencies. It aims to: 1) explore the relationship between homelessness and other factors in generating 'deep' social exclusion. 2) investigate the priorities and aspirations of multiply excluded homeless people in addressing the problems they face. 3) compare and contrast the priorities of multiply excluded homeless people with those of agencies that provide support services to multiply excluded homeless people. 4) examine the role of these potentially incompatible priorities in explaining multiple exclusion homelessness. 5) explore the ways in which place and gender may mediate these incompatible priorities. 6) validate the accounts of homeless people and their priorities by fully involving a team of formerly homeless volunteers in the design, conduct and outputs of this study. 7) disseminate findings among support agencies and policy makers so that policy and practice accords more closely with the priorities of multiply excluded homeless people. The project will be underpinned by an a user participatory methodology that utilises qualitative techniques (focus groups and semi-structured interviews) with 20 support agencies and 100 multiply excluded homeless people in Nottingham and London.