Comprehensive dataset containing 75 verified Homeless shelter businesses in Massachusetts, United States with complete contact information, ratings, reviews, and location data.

There are several forms, regulations and data associated with the Emergency Assistance (EA) Family Shelter Program for our business partners and constituents.

The Community Housing & Homeless Shelters industry in Massachusetts is expected to grow an annualized x.x% to $x.x billion over the five years to 2025, while the national industry will likely grow at x% during the same period. Industry establishments increased an annualized x.x% to xxx locations. Industry employment has increased an annualized x.x% to x,xxx workers, while industry wages have increased an annualized x.x% to $x.x million.

Comprehensive dataset of 36 Homeless services in Massachusetts, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The most recent rate of homelessness is calculated using ACS population estimates from the previous year, unless otherwise noted.

Data Source: HUD's Annual Homeless Assessment Report (AHAR) Point-in-Time (PIT) Estimates by State and American Community Survey (ACS) 1-Year Estimates

Why this MattersSafe, adequate, and stable housing is a human right and essential for the health and well-being of individuals, families, and communities.People who experience homelessness also struggle to maintain access to healthcare, employment, education, healthy relationships, and other basic necessities in life, according to the DC Interagency Council on Homelessness Strategic Plan.BIPOC populations are disproportionately affected by homelessness due to housing discrimination, mass incarceration, and other policies that have limited socioeconomic opportunities for Black, Latino, and other people of color.

The District's Response Strategic investments in proven strategies for driving down homelessness, including the Career Mobility Action Plan (Career MAP) program, operation of non-congregate housing, and expansion of the District’s shelter capacity.Homelessness prevention programs for at-risk individuals and families, such as emergency rental assistance, targeted affordable housing, and permanent supporting housing.Programs and services to enhance resident’s economic and employment security and ensure access to affordable housing.

When analyzing the ratio of homelessness to state population, New York, Vermont, and Oregon had the highest rates in 2023. However, Washington, D.C. had an estimated ** homeless individuals per 10,000 people, which was significantly higher than any of the 50 states. Homeless people by race The U.S. Department of Housing and Urban Development performs homeless counts at the end of January each year, which includes people in both sheltered and unsheltered locations. The estimated number of homeless people increased to ******* in 2023 – the highest level since 2007. However, the true figure is likely to be much higher, as some individuals prefer to stay with family or friends - making it challenging to count the actual number of homeless people living in the country. In 2023, nearly half of the people experiencing homelessness were white, while the number of Black homeless people exceeded *******. How many veterans are homeless in America? The  number of homeless veterans in the United States has halved since 2010. The state of California, which is currently suffering a homeless crisis, accounted for the highest number of homeless veterans in 2022. There are many causes of homelessness among veterans of the U.S. military, including post-traumatic stress disorder (PTSD), substance abuse problems, and a lack of affordable housing.

Abstract copyright UK Data Service and data collection copyright owner. A comparative study of the causes of new episodes of homelessness among people aged 50 or more years was undertaken in Boston, Massachusetts (USA), Melbourne, Australia, and four English cities. The aims were to make a substantial contribution to the predominantly American debate on the causes of homelessness, and to make practice recommendations for the improvement of prevention. The study had several objectives. It aimed to collect information about the antecedents, triggers and risk factors for becoming homeless in later life and about the national and local policy and service contexts. Furthermore, the researchers aimed to analyse and interpret the findings with reference to an integrated model of the causes of homelessness that represented structural and policy factors, including housing, health and social service organisation and delivery factors, and personal circumstances, events, problems and dysfunctions. The aim was to do this collaboratively, by drawing on the project partners' experience and knowledge. Finally, it was hoped to develop recommendations for housing, primary health care and social welfare organisations for the prevention of homelessness. This was to be done by identifying the common sequences and interactions of events that precede homelessness and their markers (or 'early warning' indicators) and by holding workshops in England with practitioners and their representative organisations on new ways of working. By the study of contrasting welfare and philanthropic regimes in a relatively homogeneous category of homeless incidence (i.e. recent cases among late middle-aged and older people), it was hoped that valuable insights into the relative contributions of the policy, service and personal factors would be obtained. The study focused on older people who had recently become homeless, purposely to gather detailed and reliable information about the prior and contextual circumstances. To have included people who had been homeless for several years would have reduced the quality of the data because of 'recall' problems. Users should note that data from the Australian sample for the study are not included in this dataset. Main Topics: The data file includes information about the English respondents and those from Boston. It was compiled in two stages. The first stage involved each project partner entering the pre-coded responses into the file. All partners then identified themes and created codes for the open-ended responses, and the resulting variables were added. Data quality-control procedures included blind checks of the data coding and keying. The first 200 variables pertain to information collected from the respondents. They comprise descriptive variables of the circumstances prior to homelessness, including housing tenure during the three years prior to the survey, previous homelessness, employment history, income, health and addiction problems, and contacts with family, friends and formal services. The respondents were asked to rate whether specific factors were implicated in becoming homeless, and where appropriate, a following open-ended question sought elaboration. The remaining variables comprise information collected from the respondents' 'key workers' about their understanding of the events and states that led to their clients becoming homeless. No sampling frame was available. The sample profiles have been compared with those of all homeless people (not just the recently homeless) in the study locations, most effectively in London and Boston. No gross biases were revealed. The samples represent a large percentage of the clients who presented to the collaborating organisations during the study period and who gave their informed consent to participate. Agreed definitions of homelessness were: sleeping on the streets or in temporary accommodation such as shelters; being without accommodation following eviction or discharge from prison or hospital; living temporarily with relatives or friends because the person has no accommodation, but only if the stay had not exceeded six months, and the person did not pay rent and was required to leave. People who had been previously homeless were included in the survey if they had been housed for at least 12 months prior to the current episode of homelessness. Face-to-face interview Self-completion the 'key workers' (case managers) completed questionnaires about their assessments of the respondents’ problems and of the events and states that led to homelessness. Further clarifications and checks were made by telephone.

Geospatial data about Boston Homeless Shelters. Export to CAD, GIS, PDF, CSV and access via API.

Homelessness has been a consistent problem for the city of Louisville for decades now. Despite efforts from the city government and local nonprofits, homelessness increased 139% last year alone. The Covid-19 pandemic significantly worsened the crisis, but the risk factors that contribute to homelessness are still endemic across the city: lack of affordable housing, lack of access to physical and mental healthcare, stagnant wages, etc. Homelessness has negative effects on mortality, personal health of the homeless, and public health in general (also see here, no paywall). When I recently attended a strategy meeting for the Louisville Downtown Partnership, one of the top issues voted by attendees was the rise of homelessness downtown. This could come from genuine care or that many Americans associate homeless people with crime. Everyone benefits when the issues that cause homelessness are addressed effectively, and a vital part of that is knowing what areas are most at-risk.The app above was made to map certain risk factors across Jefferson County. The risk factors include percent of households with 50%+ income going to rent, persons without health insurance coverage, percent of households at or below the poverty line, percent of households using public assistance, percent of persons reporting extensive physical and mental distress, unemployment, along with other economic and health-based factors. This doesn’t include every possible factor that could cause homelessness, but many that have strong effects. A dummy census tract was made with all the worst possible outcomes for risk factors, which was then used to rank the similarity of every census tract in Jefferson County; the lower the rank, the more at-risk the tract is. The app allows you to click through every tract in the county and see the ten most at-risk ones.The most at-risk places tend to line up with the west end and areas of the city that were historically redlined. These areas also saw mass amounts of “urban renewal” in the 60s and 70s. They also tend to line up with areas of the city that face the highest eviction rates (thanks to Ryan Massey for pointing this out).

BMI was dichotomized into two categories: obese and overweight (BMI > 24.9) and not obese or overweight (BMI < = 24.9). BMI was calculated as weight in kilograms divided by height in meters squared (weight (kg)/height (m2)).Changes in Overweight/Obesity status from Baseline to 24 Months.

Baseline Characteristics of Toronto At Home/Chez Soi Participants (N = 561) stratified by Need Level.

In this dataset you will learn about the list of homeless dogs of the Murovanska AH in different sections, namely: the number of sterilized, potentially proprietary, puppies, pregnant, damaged, with morbidity, thin, thick, ideal mass, males, females, etc.

BackgroundPeople experiencing homelessness are more likely to experience poor health with physical functioning deficits and frailty commonly reported. It is not well known how strategies to target physical functioning deficits and frailty work in practice in this group. The primary aim of this study was to explore the feasibility of an exercise intervention with protein supplementation to target physical functioning and frailty in people experiencing homelessness evaluated by recruitment and retention rates, adherence to the exercise sessions and protein supplement, adverse effects, programme feedback and characteristics of non-returners, sporadic and frequent attenders. The secondary aim was to evaluate changes in effectiveness outcomes of grip strength, muscle mass, lower extremity physical function, pain, frailty, and risk of malnutrition.MethodThis prospective single-arm study evaluated the feasibility of a 16-week rolling, low-threshold, ‘drop-in’ once weekly exercise programme with protein supplementation. The main recruitment site was a day-service centre for people who are homeless. Feasibility was assessed by the recruitment and retention rates, adherence to the exercise sessions and protein supplement as well as adverse effects, programme feedback and evaluation of characteristics of non-returners, sporadic (≤50% of available sessions) and frequent attenders (≥50% of available sessions). Effectiveness outcomes included pain (Visual Analogue Scale), physical functioning and performance (hand-grip dynamometry, limb circumference, the Short Physical Performance Battery), frailty (SHARE-FI and Clinical Frailty Scale) and nutritional status (Mini Nutritional Assessment).ResultsThirty-one participants were recruited mean (SD) age 45(16) years. There was a recruitment rate of a median (IQR) of 2(1–3) new participants per week. The retention rate was 45% (n = 14) to the main recruitment site. Adherence to the exercise sessions and nutritional intervention was 90% and 100% respectively. Three adverse events were recorded during 74 interventions over the 16-week programme. The acceptability of the programme was highlighted in participant feedback. Characteristics of frequent returners (≥50%) were older age, female, more stably housed and more stable in addiction. The programme did not induce any changes in effectiveness outcomes.ConclusionThe feasibility of this programme was demonstrated. Overall, the programme was well received with higher retention rates in older participants, females, those more stably housed and those stable in addiction. A higher powered, more intense programme is needed to demonstrate programme effectiveness.

In this dataset you will learn about the list of stray dogs of the city in different sections, namely: number of sterilized, potentially proprietary, puppies, pregnant, damaged, with morbidity, thin, thick, ideal mass, males, females, etc./p>

BackgroundPeople experiencing homelessness are more likely to experience poor health with physical functioning deficits and frailty commonly reported. It is not well known how strategies to target physical functioning deficits and frailty work in practice in this group. The primary aim of this study was to explore the feasibility of an exercise intervention with protein supplementation to target physical functioning and frailty in people experiencing homelessness evaluated by recruitment and retention rates, adherence to the exercise sessions and protein supplement, adverse effects, programme feedback and characteristics of non-returners, sporadic and frequent attenders. The secondary aim was to evaluate changes in effectiveness outcomes of grip strength, muscle mass, lower extremity physical function, pain, frailty, and risk of malnutrition.MethodThis prospective single-arm study evaluated the feasibility of a 16-week rolling, low-threshold, ‘drop-in’ once weekly exercise programme with protein supplementation. The main recruitment site was a day-service centre for people who are homeless. Feasibility was assessed by the recruitment and retention rates, adherence to the exercise sessions and protein supplement as well as adverse effects, programme feedback and evaluation of characteristics of non-returners, sporadic (≤50% of available sessions) and frequent attenders (≥50% of available sessions). Effectiveness outcomes included pain (Visual Analogue Scale), physical functioning and performance (hand-grip dynamometry, limb circumference, the Short Physical Performance Battery), frailty (SHARE-FI and Clinical Frailty Scale) and nutritional status (Mini Nutritional Assessment).ResultsThirty-one participants were recruited mean (SD) age 45(16) years. There was a recruitment rate of a median (IQR) of 2(1–3) new participants per week. The retention rate was 45% (n = 14) to the main recruitment site. Adherence to the exercise sessions and nutritional intervention was 90% and 100% respectively. Three adverse events were recorded during 74 interventions over the 16-week programme. The acceptability of the programme was highlighted in participant feedback. Characteristics of frequent returners (≥50%) were older age, female, more stably housed and more stable in addiction. The programme did not induce any changes in effectiveness outcomes.ConclusionThe feasibility of this programme was demonstrated. Overall, the programme was well received with higher retention rates in older participants, females, those more stably housed and those stable in addiction. A higher powered, more intense programme is needed to demonstrate programme effectiveness.

Demographic characteristics of participants who had an opportunity to return stratified into those who did not return, sporadic returners (attended ≤50% of available sessions) and frequent returners (attended ≥50% of available sessions).

Description of secondary outcomes, derived from [31].

Demographic characteristics of participants (n = 31).