An analysis of elder abuse rates in Milwaukee County. 2011

Mary J Thomson, and Lauren K Lietzau, and Megan M Doty, and Linda Cieslik, and Ramona Williams, and Linda N Meurer
Medical College of Wisconsin, Milwaukee, USA. mthomson@mcw.edu

BACKGROUND The elder abuse and neglect burden in Milwaukee County, Wisconsin, is substantial, with 3384 reports made from 2006 to 2009. Current prevalence estimates are determined from reported cases only and are likely underestimated. Provider awareness of victim and perpetrator characteristics is necessary to increase recognition and response. METHODS A cross-sectional analysis of elder abuse and neglect cases reported to the Milwaukee County Department on Aging (MCDA) from 2006 to 2009 was performed to provide a profile of the county's elder abuse burden by victim, perpetrator, and reporter characteristics. Annual reporting trends were identified using Poisson regression analysis. RESULTS Fifty-eight percent of MCDA reports of abuse were substantiated after investigation. Victims in Milwaukee County tended to be older than 75 (64%), female (64%), and white (62%). Reporting rates to the MCDA were significantly lower in 2009 than 2006. Perpetrators were often adult children (48%) or a spouse (14%). Forty percent of life-threatening cases of self-neglect were due to unfulfilled medical needs. Most reports were made by medical professionals (23%), relatives of the victim (21%), and community agencies (18%). Only 13% of elder abuse victims were placed in nursing homes and assisted living centers; many received services to assist independent living. CONCLUSIONS Although this study is limited to reported cases only, it provides a valuable profile of pertinent elder abuse characteristics in Milwaukee County. CONCLUSIONS Characteristics of vulnerable elders, potential abusers, and investigation outcomes are described to inform clinical practice about this important social issue.

UI MeSH Term Description Entries
D008297 Male Males
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D004552 Elder Abuse Emotional, nutritional, financial, or physical maltreatment, exploitation, or abandonment of the older person generally by family members or by institutional personnel. Abuse Experiences, Elder,Aged Abuse,Elder Abuse Experiences,Elder Maltreatment,Elder Mistreatment,Elder Neglect,Elderly Abuse,Experience of Elder Abuse,Senior Abuse,Senior Neglect,Abuse Experience, Elder,Abuse, Aged,Abuse, Elder,Abuse, Elderly,Abuse, Senior,Elder Abuse Experience,Elderly Abuses,Experience, Elder Abuse,Maltreatment, Elder,Mistreatment, Elder,Neglect, Elder,Neglect, Senior,Senior Abuses,Senior Neglects
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D000369 Aged, 80 and over Persons 80 years of age and older. Oldest Old
D012307 Risk Factors An aspect of personal behavior or lifestyle, environmental exposure, inborn or inherited characteristic, which, based on epidemiological evidence, is known to be associated with a health-related condition considered important to prevent. Health Correlates,Risk Factor Scores,Risk Scores,Social Risk Factors,Population at Risk,Populations at Risk,Correlates, Health,Factor, Risk,Factor, Social Risk,Factors, Social Risk,Risk Factor,Risk Factor Score,Risk Factor, Social,Risk Factors, Social,Risk Score,Score, Risk,Score, Risk Factor,Social Risk Factor
D014505 Urban Population The inhabitants of a city or town, including metropolitan areas and suburban areas. Urban Residence,Urban Spatial Distribution,Distribution, Urban Spatial,Distributions, Urban Spatial,Population, Urban,Populations, Urban,Residence, Urban,Urban Populations,Urban Residences,Urban Spatial Distributions
D014922 Wisconsin State bounded on the north by Lake Superior and Michigan, on the east by Lake Michigan, on the south by Illinois and Iowa, and on the west by Minnesota and Iowa.

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