County-level socioeconomic and crime risk factors for substantiated child abuse and neglect

Morris, Matthew C.; Marco, Miriam; Maguire‐Jack, Kathryn; Kouros, Chrystyna D.; Im, Wansoo; White, Codi; Bailey, Brooklynn; Rao, Uma; Garber, Judy

doi:10.1016/j.chiabu.2019.02.004

Cited by 39 publications

(23 citation statements)

References 81 publications

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“…As opposed to a purely spatial analysis of the disease that is independent from one year to the next, the sequentially based spatio-temporal approach enabled us to study the geographical persistence and variation of the disease over multiple years across individual LHIN areal units. Furthermore, in comparison to frequentist-based approaches, the Bayesian approach enabled the modeling of unobserved factors through the use of spatial and temporal random effects, thus strengthening parameter estimation [69,70].…”

Section: Discussionmentioning

confidence: 99%

Bayesian Space–Time Analysis of Brain Cancer Incidence in Southern Ontario, Canada: 2010–2013

Persad¹

2019

Medical Sciences

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Canada has one of the highest incidence rates of brain cancer in the world. This study investigates the space–time variation of brain cancer risk across Southern Ontario, Canada. A Bayesian spatio-temporal regression model is used to estimate the relative risk of brain cancer in the 12 spatial health units of Southern Ontario over a four-year period (2010–2013). This work also explores the association between brain cancer and two potential risk factors: traumatic head injury (THI) and excess body fat (EBF). Across all areal units from 2010–2013, results show that the relative risk of brain cancer ranged from 0.83 (95% credible interval (CI) 0.74–0.91) to 1.26 (95% CI 1.13–1.41). Over the years, the eastern and western health units had persistently higher risk levels compared to those in the central areas. Results suggest that areas with elevated THI rates and EBF levels were also potentially associated with higher brain cancer relative risk. Findings revealed that the mean temporal trend for cancer risk progression in the region smoothly decreased over time. Overall, 50% of the health units displayed area-specific trends which were higher than the region’s average, thus indicating a slower decrease in cancer rates for these areas in comparison to the mean trend.

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Section: Discussionmentioning

confidence: 99%

Bayesian Space–Time Analysis of Brain Cancer Incidence in Southern Ontario, Canada: 2010–2013

Persad¹

2019

Medical Sciences

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“…In other words, looking at singular risk factors may not provide the full story. Recent studies determined that county-level data is not only readily and routinely accessible to decision makers, but can be a useful indicator of individual risk and support policy makers when determining how to prioritize resource allocation [17][18][19]. Indeed, these studies suggest that models of county-level or similar geographic levels of risk are robust.…”

Section: Original Articlementioning

confidence: 99%

Exploring Clusters of Risk and Association With Child Maltreatment in North Carolina Counties

Cruden

Brown

Lanier

et al. 2021

North Carolina Medical Journal

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background Decision makers face challenges in estimating local risk for child maltreatment and how best to prioritize which factors to intervene upon. methods Using US Census and survey data for all US counties (N = 3141), we derived US county profiles characterized by the severity of child maltreatment risk factors observed at the county level, such as parental health, health care access, and economic distress. We estimated how five child maltreatment outcomes would vary across the profiles for North Carolina counties (n = 100): total maltreatment reports (including unsubstantiated and substantiated), substantiated neglect, substantiated abuse, whether services were received, and reported child's race/ethnicity. results We derived three profiles of county-level child maltreatment risk: high, moderate, and low risk, denoting that predicted risk factors means within profiles were all high, moderate, or low levels compared to counties in other profiles. One risk factor did not follow this pattern: the drug overdose death rate. It was highest in the moderate-risk profile instead of the high-risk profile, as would have been consistent with other factor levels. Moderate-risk counties had the highest predicted rate of child maltreatment reports, with over 20 more reports per 10,000 residents compared to low-risk counties (95% CI, 1.38, 38.86). limitations We included only factors for which aggregate, county-level estimates were available, thus limiting inclusion of all relevant factors. conclusions Results suggest the need for increased family-based services and interventions that reduce risk factors such as economic distress and drug overdose deaths. We discuss the implications for tailoring county efforts to prevent child maltreatment.

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“…Verbal violence includes nicknames, reproaches, slanders, destructive criticisms, insults (whether personal, group or racial), statements about sexual harassment, terror, letters, e-mails, intimidating texts, and allegations not true, cruel and false gossip, and others. Emotional violence (neglect) includes the treatment of alienating or rejecting a friend or even damaging a friendly relationship, systematically weakening the victim's self-esteem through neglect, exclusion, exclusion or avoidance, hidden attitudes such as aggressive views (glares), eye glances, eyebrow movements, head nods, sighs, shaking shoulders, sneers, mocking laughter and rough body language 3,4 . Child abuse harms adult emotional performance, presents signs of anxiety dysfunction, reduces intelligence and memory, risks social delay, loss of empathy, and avoids social involvement 5 .…”

Section: Introductionmentioning

confidence: 99%

Children Death with Child Abuse: A Case Report at Bhayangkara Hospital, Kediri Indonesia

2020

IJFMT

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Background: Child abuse has negative impact for children including emotional performance, mental dysfunction, and decrease intelligence.Case report: A boy went to the emergency room at Bhayangkara Kediri Hospital. There was swelling on the left head, expanding on the forehead and, bruising on the left ear. Also found signs of sodomy marks in the form of abrasions around the anus. There are also bruises on the back and neck of the end.Discussion: For a definitive diagnosis, the results of the CT scan were that the patient obtained extensive cerebral contusion and caused the deviation of the midline structure to the right as far as ± 0.9 cm with subgaleal hematoma and the dilation of cerebral blood vessels. Conclusion:The body's exact death is expected to blunt force in the head, resulting in a skull fracture and bleeding of the brain.

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County-level socioeconomic and crime risk factors for substantiated child abuse and neglect

Cited by 39 publications

References 81 publications

Bayesian Space–Time Analysis of Brain Cancer Incidence in Southern Ontario, Canada: 2010–2013

Bayesian Space–Time Analysis of Brain Cancer Incidence in Southern Ontario, Canada: 2010–2013

Exploring Clusters of Risk and Association With Child Maltreatment in North Carolina Counties

Children Death with Child Abuse: A Case Report at Bhayangkara Hospital, Kediri Indonesia

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