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Geographic distribution of ID prevalence relative to the birth cohort n=11,034 and ID n=916: Unadjusted (A) and fully adjusted models (B) are presented using the optimal span size of each (0.10 and 0.30 respectively). The unadjusted model is significantly different than flat (global P<0.001). Areas of significantly increased and decreased risk are indicated by black contour bands. Adjusted model is not significantly different than flat (global P=0.065). Adjustment factors were year of birth; plurality; maternal age, race, and level of education; and report of tobacco use during pregnancy.
Source publication
Background
The causes of autism spectrum disorders (ASD) remain largely unknown and widely debated; however, evidence increasingly points to the importance of environmental exposures. A growing number of studies use geographic variability in ASD prevalence or exposure patterns to investigate the association between environmental factors and ASD. Ho...
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Children diagnosed with autism spectrum disorder (ASD) require substantial support to address not only core ASD symptoms but also a range of co-occurring conditions. This study explores treatment and service use among children with ASD with and without intellectual disability (ID) and parents' perception of unmet needs from these treatments.
Data w...
Objective:
To investigate if therapeutic horseback riding (THR) can improve language and cognitive function in children with autism spectrum disorder (ASD) or intellectual disability (ID).
Methods:
We conducted a prospective case-control study on children diagnosed with ASD or ID. Eighteen and 11 children were enrolled for THR and control groups...
This report describes the response of a patient with autism spectrum disorder (ASD) and moderate intellectual disability (ID) with a de novo protein truncating variant (PTV) in SYNGAP1 to lovastatin.
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Citations
... The relationships we observe with qualification level and IMD suggest that area level education and SEP may amplify genetic influences on these neurodevelopmental traits. This fits with previous phenotypic literature suggesting their prevalence is correlated with SEP (13,48,49). Qualification level tends to be higher in less deprived areas, so the fact we observe opposite correlations for these with the PRS association maps fits with this relationship. ...
Background
The genetic and environmental aetiology of autistic and Attention Deficit Hyperactivity Disorder (ADHD) traits is known to vary spatially, but does this translate into variation in the association of specific common genetic variants?
Methods
We mapped associations between polygenic scores for autism and ADHD and their respective traits in the Avon Longitudinal Study of Parents and Children (N=4,255 to 6,165) across the area surrounding Bristol, UK, and compared them to maps of environments associated with the prevalence of autism and ADHD.
Results
Our maps suggest genetic associations vary spatially, with consistent patterns for autistic traits across polygenic scores constructed at different p-value thresholds. Patterns for ADHD traits were more variable across thresholds. We found that the spatial distributions often correlated with known environmental influences.
Conclusions
These findings shed light on the factors that contribute to the complex interplay between the environment and genetic influences in autism and ADHD traits.
Key points
The prevalence of autism and ADHD vary spatially.
Our study highlights that genetic influences based on PGS also vary spatially.
This spatial variation correlates with spatial variation in environmental characteristics as well, which would be interesting to examine further.
Our findings have implications for future research in this area examining the factors that contribute to the complex interplay between the environment and genetic influences on autistic and ADHD traits.
... Research on spatial distribution of ASD has been sparse, especially at the state or country level, for which the current literature mainly includes total population studies examining time trends of ASD prevalence [5e10]. Studies exploring spatial patterns of ASD detected clusters of heightened risk in certain areas in California [11e13], North Carolina [14,15], and Utah [16]. Those studies implemented advanced spatial analyses, but the generalizability of their results may be limited to the areas surveyed only. ...
Purpose
Studies indicate an apparent sharp increasing trend in Autism Spectrum Disorder (ASD) incidence and prevalence worldwide. This nationwide study aims at depicting ASD prevalence distribution in Israel in both space and time.
Methods
Based on data from Israel National Insurance Institute, the study population included all children born in Israel 2000-2011 (N=1,786,194), of whom 11,699 (0.655%) were subsequently diagnosed with ASD (until December 31, 2016). Prevalence was calculated and mapped by dividing the number of ASD cases within each year of birth by the number of births during that year, for each spatial unit, and similarly for several spatiotemporal levels of aggregation.
Results
ASD prevalence varies substantially across different geographic areas in Israel, with considerably higher prevalence concentrated in central Israel. Strong associations were found between locality-level socioeconomic index, ethnicity, peripherality and ASD prevalence, and even after adjustment for them, excess prevalence for ASD still persisted in certain localities. No spatial dependence of prevalence, with and without adjustment for the locality-level variables, was found (Moran’s I = -0.000546, -0.00335, respectively).
Conclusions
Our findings provide important insights regarding health disparities affecting ASD diagnosis, directing further health policy intervention, as well as further research.
... It was found in the study that children who were born in New England had fifty percent higher chance of being diagnosed with ASD compared to other children that were born in other places in the United States. Another study conducted by the same author as well in 2012 showed that there were spatial variation of ASD in central North Carolina where the study took place 11 . ...
Background. Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized with disorders in cognitive, behaviour, and social interaction. It is estimated to affect 1:160 children worlwide. Despite its increasing trend, the exact cause of it is yet to be known.
Objective. This study wished to identify the geographical distribution of ASD cases in Dr. Mohammad Hoesin Hospital as one of the national reference hospitals in Indonesia for South Sumatera region.
Methods. Medical records of the patients who are diagnosed with ASD during 2014-2018 was observed in order to identify the patients’ residential area.
Results. There were 107 patients who were clinically diagnosed of having ASD during 2014-2018 in Dr Mohammad Hoesin Hospital, Palembang. Based on its residential area, ASD cases were mostly found in Palembang as the capital city of South Sumatera Province.
Conclusion. ASD is found in small and big cities across the South Sumatera province, implying its common occurrence. The varied prevalence could be signifying the role of different related risk factors identified in the area.
... Investigating geographic patterns of ASD prevalence may help identify diagnostic and environmental factors associated with prevalence. A growing number of spatially based analyses have used geographic variation in ASD to generate hypotheses about drivers of prevalence at local and state levels (4,(18)(19)(20)(21)(22). For example, Mazumdar et al. (4) reported that living in areas of California with greater diagnostic resources increased a child's odds of being diagnosed with ASD. ...
... Instead, we identify regions of increased or decreased risk. Previous research has shown that smaller-scale variation is likely (4,19). For example, we previously reported geographic variation in surveillancerecognized ASD in North Carolina (19) and Mazumdar et al. (4) reported neighborhood-specific variation in ASD risk. ...
... Previous research has shown that smaller-scale variation is likely (4,19). For example, we previously reported geographic variation in surveillancerecognized ASD in North Carolina (19) and Mazumdar et al. (4) reported neighborhood-specific variation in ASD risk. These spatial analyses have some potential limitations. ...
Data indicate that autism spectrum disorder (ASD) prevalence may be increasing and varies geographically. We investigated associations between residential location and ASD in the children of Nurses' Health Study II women in order to generate hypotheses about social and environmental factors related to etiology or diagnosis. Analyses included 13,507 children born from 1989-1999 (486 with ASD). We explored relationships between ASD and residential location at both birth and age 6 years (i.e. closer to average diagnosis age). Generalized additive models were used to predict ASD odds across the US. Children born in New England were 50% more likely to be diagnosed with ASD compared to children born elsewhere in the US. Patterns were not explained by geographic variation in maternal age, birth year, child's sex, community income or prenatal exposure to hazardous air pollutants, indicating that spatial variation is not attributable to these factors. Using the residential address at age 6 produced similar results; however, areas of significantly decreased ASD odds were observed in the Southeast, where children were half as likely to have ASD. These results may indicate that diagnostic factors are driving spatial patterns; however, we cannot rule out the possibility that other environmental factors are influencing distributions.
... Por exemplo, os endereços residenciais das pessoas que compareceram aos hospitais brasileiros muitas das vezes são incompletos. Essa é uma informação importante nos estudos epidemiológicos com enfoque espacial (Hoffman et al., 2012;Su, Jerrett, and Beckerman, 2009). E quando algum endereço apresenta uma melhor precisão, o problema passa a ser para a integração em um banco de dados geográfico. ...
Air pollution is a serious public health problem worldwide. Studies that investigate the relationship between air pollution and human health are fundamental for management that aims to promote the urban development and life quality. Data availability is an initial premise for these studies, especially, for it that have focus in the spatial evaluation. The problem is that many urban centers do not have a system to consolidate and storage data. Thus, this paper aimed to propose a method for spatial evaluation between air pollution and health in urban areas that have limitation in data availability. The method proposed was based on object orientation for geographic information system, considering hospital admissions data and air pollution inventories. Also, was applied a correlation analysis and a spatial regression – Ordinary Least Square (OLS). Results showed that the method proposed is an alternative for area with data availability. Correlations analysis and regression showed a significant relationship (p< 0.05) between air pollution and health.
... Previous studies have investigated associations between higher socioeconomic status (SES) characteristics and increased ASD diagnosis or prevalence and have consistently described differences across ethnic and socioeconomic groups with prevalence being lower in groups with lower income and education (Bhasin and Schendel, 2007;Croen et al., 2002;Durkin et al., 2010;Fountain et al., 2011;Hertz-Picciotto et al., 2010;King and Bearman, 2011;Liptak et al., 2008;Rahbar et al., 2013;Rosenberg et al., 2009;Sasanfar et al., 2010;Windham et al., 2011). This positive association has also been observed in cumulative incidence (Van Meter et al., 2010) and with geographic clustering (Bakian et al., 2014;Hoffman et al., 2012;Mazumdar et al., 2010;Yeargin-Allsopp et al., 2003). Studies have also shown lower ASD prevalence among traditionally underserved populations including Blacks and Hispanics (Windham et al., 2011;Yeargin-Allsopp et al., 2003). ...
Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.02–1.09). Results from our examination of sociodemographic factors of tract populations from which cases were drawn also showed that after controlling for other covariates, statistical significance remained for associations between optimal ascertainment and percentage of Hispanic residents (adjusted odds ratio = 0.93, 95% confidence interval = 0.88–0.99) and percentage of residents with at least a bachelor’s degree (adjusted odds ratio = 1.06, 95% confidence interval = 1.01–1.11). We identified sociodemographic factors associated with autism spectrum disorder prevalence estimates including race, ethnicity, education, and income. Determining which specific factors influence disparities is complicated; however, it appears that even in the presence of education, racial and ethnic disparities are still apparent. These results suggest disparities in access to autism spectrum disorder assessments and special education for autism spectrum disorder among ethnic groups may impact subsequent surveillance.
... In the U.S., children with autism spectrum disorder (ASD) have been found to live in spatial clusters (Mazumdar et al., 2010;Hoffman et al., 2012). From a public health perspective, these clusters mean that children in certain neighbourhoods-often overrepresented by Latinos, African Americans, and low socioeconomic status (SES) families (Durkin et al., 2010)-are less likely than others to receive important services that can improve life outcomes (Liptak et al., 2008). ...
... Theories about the causes of the ASD clustering are diverse. For example, sociologists have found strong positive correlations between the diagnosis and both SES and parental education (Van Meter et al., 2010;Hoffman et al., 2012), and others have found anecdotal evidence of a social network effect on the diagnosis . In California, ASD prevalence in low SES neighbourhoods nearly caught up to the rate in high SES neighbourhoods, and this happened as information about ASD was becoming widespread (King and Bearman, 2011). ...
... Changes in the model-selected optimal span of analysis with and without adjustment were observed and investigated, because a smaller optimal span size is selected when data presents more peaks. A change in optimal size after the inclusion of a covariate can indicate spatial confounding (Hoffman et al., 2012). Also, for both of the approaches, we stratified by sex and fit separate models for women and men as women were significantly older than men. ...
Introduction
The study investigated the geographic variation of mortality risk for hematological malignancies (HMs) in order to identify potential high-risk areas near an Italian petrochemical refinery.
Material and methods
A population-based case-control study was conducted and residential histories for 171 cases and 338 sex- and age-matched controls were collected. Confounding factors were obtained from interviews with consenting relatives for 109 HM deaths and 267 controls. To produce risk mortality maps, two different approaches were applied. We mapped (1) adptive kernel density relative risk estimation (KDE) for case-control studies which estimates a spatial relative risk function using the ratio between cases and controls’ densities, and (2) estimated odds ratios for case-control study data using generalized additive models (GAMs) to smooth the effect of location, a proxy for exposure, while adjusting for confounding variables.
Results
No high-risk areas for HM mortality were identified among all subjects (men and women combined), by applying both approaches. Using the adaptive KDE approach, we found a significant increase in death risk only among women in a large area 2–6 km southeast of the refinery and the application of GAMs also identified a similarly-located significant high-risk area among women only (global p-value<0.025). Potential confounding risk factors we considered in the GAM did not alter the results.
Conclusion
Both approaches identified a high-risk area close to the refinery among women only. Those spatial methods are useful tools for public policy management to determine priority areas for intervention. Our findings suggest several directions for further research in order to identify other potential environmental exposures that may be assessed in forthcoming studies based on detailed exposure modeling.
Keywords: Hematological malignancies, Disease mapping, Generalized Additive Models (GAMs), Kernel density estimation
... According to the same CDC report, Caucasian children are 30% more likely to be diagnosed with autism than children of African descent (MMWR, 2012). This discrepancy has been attributed to varying diagnostic practices in different socioeconomic settings and not to race or ethnicity (Durkin et al., 2010;Hoffman et al., 2012;Pedersen et al., 2012;Zuckerman et al., 2013). It seems likely that the same socioeconomic factors biasing the diagnosis of autism may also affect which patients utilize assisted reproductive technologies (ART) (Bitler and Schmidt, 2006;Jain, 2006;Chandra and Stephen, 2010;Duwe et al., 2010). ...
... According to the same CDC report, Caucasian children are 30% more likely to be diagnosed with autism than children of African descent (MMWR, 2012). This discrepancy has been attributed to varying diagnostic practices in different socioeconomic settings and not to race or ethnicity (Durkin et al., 2010;Hoffman et al., 2012;Pedersen et al., 2012;Zuckerman et al., 2013). It seems likely that the same socioeconomic factors biasing the diagnosis of autism may also affect which patients utilize assisted reproductive technologies (ART) (Bitler and Schmidt, 2006;Jain, 2006;Chandra and Stephen, 2010;Duwe et al., 2010). ...
