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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences
|
|---|---|
| Published in |
International Journal of Health Geographics, October 2017
|
| DOI | 10.1186/s12942-017-0111-y |
| Pubmed ID | |
| Authors |
Enrique Gracia, Antonio López-Quílez, Miriam Marco, Marisol Lila |
| Abstract |
'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more localized prevention and intervention strategies. This new approach can also contribute to an improved epidemiological surveillance system to detect ecological variations in risk, and to assess the effectiveness of the initiatives to reduce this risk. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 38% |
| Switzerland | 1 | 13% |
| Mexico | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 88% |
| Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 89 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 15% |
| Researcher | 8 | 9% |
| Student > Doctoral Student | 8 | 9% |
| Student > Master | 7 | 8% |
| Professor | 6 | 7% |
| Other | 21 | 24% |
| Unknown | 26 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 14 | 16% |
| Social Sciences | 14 | 16% |
| Medicine and Dentistry | 9 | 10% |
| Business, Management and Accounting | 4 | 4% |
| Arts and Humanities | 3 | 3% |
| Other | 12 | 13% |
| Unknown | 33 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 March 2018.
All research outputs
#6,334,584
of 25,698,912 outputs
Outputs from International Journal of Health Geographics
#193
of 654 outputs
Outputs of similar age
#92,535
of 337,524 outputs
Outputs of similar age from International Journal of Health Geographics
#5
of 13 outputs
Altmetric has tracked 25,698,912 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 654 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,524 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.