Age of diagnosis of autism spectrum disorder in Latino children: The case of Venezuelan children

Abstract

Latino children are diagnosed with autism spectrum disorder later in life, usually with more severe symptoms, and lower IQs, compared with non-Latino children. Possible reasons for such disparities could be due to lower levels of parent education, lower socioeconomic status, limited knowledge of parents about autism spectrum disorder, and diminished health-care knowledge. The goal of the study was to describe the age of parental concerns and at first autism spectrum disorder diagnosis, and factors associated with age at the first diagnosis in a sample of Venezuelan children. Diagnostic and demographic data were collected from 103 children between 2 and 7 years of age. Although the mean age of first concerns was 17 months, the age of diagnosis varied from 53.03 months for the Pervasive Developmental Disorders–Not Otherwise specified group to 54.38 months for the autism group. Although parents were aware of developmental difficulties before the second year of life, their children were diagnosed 36 months later. In Latin cultures, behavior problems are usually attributed to poor parenting skills, so parents might take longer to seek professional help. A better understanding of cultural influences on age of diagnosis will translate to quicker use of services independent of ethnicity.

Keywords

age of diagnosis autism spectrum disorders culture early diagnosis Hispanics Latino

Introduction

Autism spectrum disorder (ASD) is a developmental disorder usually diagnosed after the age of 36 months, even though parents commonly recognize difficulties much earlier. Many studies have reported mean ages of ASD diagnosis ranging from 38 to 120 months (Daniels and Mandell, 2014; Emerson et al., 2016; Mandell et al., 2005; Shattuck et al., 2009). Research in this field has evolved from diagnostic and prevalence to enhancement and improvement of early identification methods. Early identification is desirable because it is linked to better outcomes; for instance, it plays a significant role in the reduction of cognitive, behavioral, and functional impairment (Dawson et al., 2010; Emerson et al., 2016; Klin et al., 2015). Early identification and diagnosis might improve the likelihood of referral to early intervention.

Although there is no evidence that clinical presentation of ASD varies across cultures, ethnicity, or race, there is a disparity in prevalence and age of diagnosis (Magaña et al., 2013; Yeargin-Allsopp et al., 2003). ASD prevalence has increased, and age of diagnosis has decreased but not for ethnic minorities (Chaidez et al., 2014; Jo et al., 2015; Mandell et al., 2009; Yeargin-Allsopp et al., 2003). ASD is not only underdiagnosed in Latino children; such diagnosis is also attained on an average of 2.5 years later than with Caucasian children (Mandell, Listerud et al., 2002; Zuckerman et al., 2013). Factors that have been explored as responsible for the later diagnosis in Latino children include diminished access to health and educational services, severity of symptoms (children with less severe symptoms would seek help later), comorbid intellectual impairment, parents’ language proficiency (in general, parent’s command of English could hinder their ability to communicate with health professionals and to reach out for available services), and shortage of accessible Spanish-speaking specialists (Daniels and Mandell, 2014; Liptak et al., 2008; Mandell et al., 2010; Parish et al., 2012). Overton et al. (2007) reported that Texas, California, and New Mexico have lower-than-expected rates of ASD as well as the largest Latino population in the United States.

Evidence from recent studies offers nonconclusive explanations for disparity in age of diagnosis in diverse ethnic populations (Mandell et al., 2009). Many of these reports show mixed results: either no association for ethnicity and age of diagnosis or Latino children being diagnosed later than Caucasian children (Daniels and Mandell, 2014). In the CHARGE (Childhood Autism Risk for Genetics and Environment) study, Latino children showed more similarities with non-Latinos in clinical variables (autism phenotypes and scale scores) but not in demographic elements (health insurance, use of more than one language) (Chaidez et al., 2014). The National Survey of Children’s Health (NSCH) documented that Latino children with foreign-born parents have a substantially lower prevalence than do Latino children with US-born parents (Schieve et al., 2012).

To our knowledge, there are no reports about the age of diagnosis of children living in Latin American countries. Because of this, there is little or no information about how Latino ethnicity itself has an impact on age of diagnosis. Exploring these variables in Latino children raised in their countries would shed light on the protective or risk role of culture in the early identification of ASD, which also has clinical implications for Latino and other minority children with ASD. In most studies, Latino is used to describe those children who were born in Central/South America or whose parents were born in Central/South America, including Portuguese-speaking Brazilians. Using this term as a way of characterizing an ethnic group has some limitations because it includes people of Latin American origin or ancestry who live in the United States. Latin American origin/ancestry refers to a large number of countries that have many different cultural characteristics.

The goal of the study was to describe the age of parental concern, types of first parental concerns, the age of first ASD diagnosis, and factors associated with age of the first diagnosis in a sample of Venezuelan children.

Method

Setting

This study was carried out in Maracaibo, the second largest city in Venezuela. According to the national census (Instituto Nacional de Estadistica, 2012), it has an estimated 1,571,885 people, which constitutes 5.43% of the Venezuelan population. It is located in the west of the country, very close to the Colombian border. Maracaibo County encompasses more than 40% of the state’s population. At the time of the study, it was home to a total of 702,128 registered children (0–9 years old) and had a male:female ratio of 1.05:1.

Ethnicities/races are not clearly differentiated in Venezuela and are not used on government forms. Except for native Indians, the rest of the country is considered mestizo. The children included in this study are all mestizos (native Indians live in reservations apart from the urban areas).

Venezuela does not keep public records of health services, which is a great hindrance to all types of epidemiological surveys. Also, the diagnostic process for any developmental disability could be completed in either private or public institutions, and it is not mandatory for the clinician or institution to report the identified cases. Furthermore, there is no financial allowance for these children or their families.

Sampling

Children aged 3–7 years were recruited from the Research Unit for ASD at the Institute of Human Genetics of La Universidad del Zulia (HGI). HGI is part of a pediatric hospital (tertiary care facility) and usually receives children who have suspected genetic and/or developmental issues. Data were collected from September 2010 through December 2011. Prospective cases were identified through a screening process with parents at the time of consultation. Children screened for this study were those who attended the genetic clinic for various complaints, including language delays, motor difficulties, and cognitive impairment. A total of 177 consecutive children attended the center during that period. We could not complete the assessment of 17 children (9.60%) because of missed scheduled assessment sessions or loss of contact information (changed phone numbers). A total of 42 (23.73%) children did not meet the criteria for ASD. Of those 118 (66.67%) who did meet the criteria for ASD, 15 (8.47%) were excluded because of the presence of some neurogenetic known condition (X fragile, tuberous sclerosis, or neurofibromatosis). The final sample was composed of 103 children (58.19% of the total sample) with a mean age of 4.48 years (standard deviation (SD) = 1.56), with a male:female ratio of 3.91:1 (Table 1).

Table 1.

Demographic characteristics.

	Diagnostic group		Totaln = 103	F	χ²
	Autismn = 82	PDD–NOSn = 21	Totaln = 103	F	χ²
Gender					0.16
Male (%)	64 (78)	16 (76.19)	80 (77.67)
Female (%)	18 (22)	5 (23.81)	23 (22.33)
Age group					0.95
3−4 years (%)	45 (54.87)	12 (57.14)	57 (55.33)
5−7 years (%)	37 (45.13)	9 (42.86)	46 (44.67)
SES					0.04
Low−mid (%)	75 (91.46)	19 (90.47)	94 (91.26)
High (%)	7 (8.54)	2 (9.53)	9 (8.74)
Mother’s education level					0.03
Elementary−high school (%)	65 (79.27)	17 (80.95)	82 (79.61)
College and graduate (%)	17 (20.73)	4 (19.05)	21 (20.39)
Father’s education level					0.61
Elementary−high school (%)	47 (57.32)	14 (66.67)	61 (59.22)
College and graduate (%)	35 (42.68)	7 (33.33)	42 (40.78)
Age of mother	29.18 ± 5.68	30.7 ± 6.11	29.4 ± 5.77	1.19
Age of father	33.37 ± 7.95	32.8 ± 11.11	33.25 ± 8.63	0.069
ADOS severity	18.25 ± 7.01	9.47 ± 6.85	16.51 ± 7.78	24.05***
Cognitive impairment (IQ < 70)	57 (68.51)	6 (28.57)	63 (61.17)		1.08***
Verbal skills	73.73 ± 24.03	79.21 ± 19.9	75.13 ± 23.03	0.79

PDD-NOS: Pervasive Developmental Disorders–Not Otherwise specified; SES: socioeconomic status; ADOS: Autism Diagnostic Observation Schedule.

***

p < 0.001.

Pediatricians, child neurologists, and geneticists who worked at HGI administered a pediatric questionnaire to their patients, and the age of first ASD diagnosis was obtained from this developmental questionnaire. Families with children aged 3–7 years who attended HGI for child neurology or genetic consultation and who manifested any preoccupation with their child’s development as part of the reason for consultation were administered the Social Communication Questionnaire (SCQ; Rutter et al., 2003) and then referred to the research unit to complete the ASD assessment. Some of the children had already been diagnosed, whereas others were diagnosed at the end of the assessment process.

Measures

Parents of children participating in this study provided informed consent for the screening and clinical assessment under procedures approved by the University of Zulia Institutional Review Boards.

ASD diagnosis

Participants had a confirmed diagnosis of ASD based on (a) scores above 15 on the SCQ, (b) algorithm scores within the clinical range from the Autism Diagnostic Observation Schedule (ADOS; Lord et al., 2002) and Autism Diagnostic Interview–Revised (ADI-R; Rutter et al., 2003), and (c) an expert clinician confirming the diagnosis. The clinician reviewed all the information pertaining to assessment tools and informed the diagnosis.

The SCQ is a parent report questionnaire that asks about autistic behavior. Total scores range from 0 to 39 (Rutter et al., 2003).

The ADOS is a play-based examination designed to directly assess communication and social interaction skills, as well as play and repetitive behaviors (Lord et al., 2002). Autism symptom severity was measured with the ADOS calibrated severity score.

The ADI-R is a semistructured interview administered to parents that encompasses communication, social interaction, and play and repetitive behaviors (Rutter et al., 2003). This instrument was used for the identification of not only the age of parental concern but also the initial concerns. Item 2 was used to identify the age of first parental concern and then was confirmed with item 4. Item 2 is referred to age that parents noted first concerns (age (in months) when parents first notice that something wasn’t right with language, relationships, or behaviors); while item 4 refers also to age of parental first concerns, it is a more detailed item. (In hindsight, when do you think that he or she exhibited developmental or behavioral difficulties/problems for the first time? Do you think that everything was completely ok before that?) The same item 2 has a descriptive part that was used to build the categories for the type of parental concern. Parents’ responses to these inquiries were classified in five categories: communication, social interaction, restricted and repetitive behaviors, loss of skills, and other (behavioral and medical concerns that did not fit the other categories; Table 2). The first four categories are aligned with the major diagnostic categories or symptoms of ASD. Assessment procedures were performed by psychologists who have achieved research reliability for the ASD measures (ADOS and ADI-R).

Table 2.

Symptoms arousing parental concerns.

Category	Behaviors described by parents
Communication	Deficit and/or language delay
Social behavior	No eye contact
	Deficits in socialization
	Isolated
	No response to name
	Seemed deaf
Restricted and repetitive behaviors	Afraid of noises
	Liked routines
	Obsession/fascination with objects
	Preoccupation with bike wheels
	Hand flapping/finger movements
	Body rocking
	Pacing
	Picky eater
Loss of skills	Stopped talking
Behavioral symptoms	No sense of danger
	Crying spells
	Self-aggression
	Restlessness
	Irritability
Motor delay	Late to walk
	Late to crawl
	Does not push self to sitting position
Medical conditions	Seizures
	Respiratory problems
	Hypotonia

Cognitive ability

Children were assessed using a modified version of Raven’s Colored Progressive Matrices Modified Form Board, sets A, AB, and B (Raven et al., 1998), which was developed as part of the Autism Genetic Resource Exchange (AGRE) protocol used in this study. Each set was contained in a separate notebook, with a form board using laminated Velcro-backed pieces that the child placed on the matrix above the pieces. This modified version expanded the age for administration, starting at 3 years 3 months (Pletcher, 25 February 2016, personal communication).

Socioeconomic status

As in other Venezuelan studies (Montiel et al., 2008), the socioeconomic status (SES) was established using school type (private or public) as an indicator according to the following criteria: (a) low SES: public schools (totally free) and schools with fees equal to or lower than 20% of the minimum monthly salary at the time of the study; (b) medium SES: those schools with fees between 21% and 40% of the minimum monthly salary at the time of the study; and (c) high SES: schools with fees above 41% of the minimum monthly salary at the time of the study. At the time of the study, the minimum monthly salary was US$151. Almost all affluent families send their children to private schools, whose fees are usually beyond the reach of the rest of the population. Because cases in the medium level were few, low and medium SES were collapsed into one category.

Exclusion criteria

Children with known brain lesions, tuberous sclerosis, neurofibromatosis, hemiparesis, ataxia, or any “hard” neurological condition participated in the screening and diagnostic procedures; however, they were excluded from any statistical analysis. Only those children without a known cause of ASD were included. The presence of other medical or genetic conditions might require early intervention, raising the likelihood of having been monitored and hence the likelihood of early identification of ASD symptoms.

Statistical analysis

Group comparisons were conducted using chi-square tests for categorical variables and analysis of covariance for continuous variables. We performed statistical analysis to examine the age of diagnosis of ASD and its association with demographic and clinical variables and used multiple regression with age of first concerns and age of diagnosis as dependent variables and reported standardized effect size. Categorical variables included gender, another family member with ASD, SES, maternal education level, the types of symptoms that prompted initial concerns (communication, social interaction, restricted behaviors, loss of skills, and other symptoms), and cognitive impairment. Age of first concerns and age of diagnosis (dependent variables) were compared between diagnostic groups (autism and Pervasive Developmental Disorders–Not Otherwise specified (PDD-NOS)) in all of the above independent variables. Before running the multiple regression, we checked for and confirmed that the assumptions of linearity, normality, and multicollinearity of multiple linear regression had not been violated.

Results

From the total sample of 103 children, 80% (n = 82) were diagnosed with autism and the other 20% (n = 21) with PDD-NOS; 61.17% (n = 63) had cognitive impairment (IQ < 70). Although the majority of mothers (79.61%) and fathers (59.22%) had an elementary or high school level of education, low SES was prevalent for this sample (91.26%; Table 1). As expected, the two diagnostic groups (autism and PDD-NOS) were similar in all demographic variables, and ADOS severity was higher for the autistic group (p = 0.003). One important difference between the two diagnostic groups was the presence of cognitive impairment (IQ < 70), which was more frequent in the autistic children (68.51%) than in the PDD-NOS children (28.57%; p < 0.001; Table 1).

The reported mean age for first recognition of ASD symptoms was 18.96 months (SD = 10.83) for the total sample. A closer look at the distribution for first concerns showed that 36.9% of parents reported some symptoms by 12 months of age, 19.42% by 18 months, 24.27% by 24 months, 16.50% by 36 months, and 2.91% by 48 months. These data indicate that 80% of parents reported first signs at or before 24 months of age. When divided by diagnostic groups, parents of children with autism noticed first signs at 18.90 months (SD = 10.27 months), while parents of children with PDD-NOS reported concerns being present at 19.19 months (SD = 13.07), with no statistical differences between the two groups.

Behaviors that alerted parents to seek help were language delay (54.36%), lack of response to name (33.01%), restlessness (19.42%), and repetitive behaviors (14.56%). Other nonspecific symptoms that alerted parents included seizures (14.56%), motor delay (12.62%), sleep disturbances (8.74%), and developmental regression (9.7%). Behaviors were clustered into the three main ASD symptoms (communication, social interaction, and restricted behaviors), behavioral symptoms (no sense of danger, crying spells, self-aggression, restlessness, and irritability), and medical conditions (seizures, respiratory problems, and hypotonia; Table 2); social interaction (57.38%) was the most prevalent category, followed by communication symptoms (50%), restricted behaviors (29.27%), and loss of skills (12.19%). On the contrary, for the PDD-NOS group, the most common category was communication (52.38%), social interaction (42.86%), and medical conditions (14.29%; Table 3). The distribution of first concerns showed significant differences between the two diagnostic groups (autism and PDD-NOS) for the restricted behaviors category (p = 0.039) and behavioral symptoms (p = 0.009), which were more frequent in the children with autism, whereas motor delay (p = 0.04) was more prevalent in children with PDD-NOS (p = 0.03). Also, loss of skills was present only in the autism group (p = 0.49; Table 3). Even though the mean age of first concerns was 18.90 months, the age at diagnosis varied from 51.43 months for PDD-NOS to 55.02 months for the autism group. The diagnostic category did not provide differences in the distribution of age of diagnosis, with the majority of children being diagnosed before or at 60 months (73.8%), and only 26.2% had a diagnosis before or at 36 months.

Table 3.

Symptoms at first concerns.

	Autism (n = 82)		PDD (n = 21)		χ²
	n	%	N	%	χ²
Communication	41	50	11	52.38	0.006
Social interaction	47	57.38	9	42.86	2.98
Restricted behaviors	24	29.27	2	9.52	3.86*
Loss of skills	10	12.19	0	0	6.54*
Behavioral symptoms	35	42.68	3	1.43	3.58*
Motor delay	3	3.66	12	57.14	3.45*
Medical conditions	21	25.60	3	14.29	1.09

PDD: Pervasive Developmental Disorders.

p < 0.05.

We conducted regression analysis to determine the association and influence of different characteristics of the children (diagnostic group, initial symptoms, clinical symptoms (ADOS severity score)), presence of cognitive impairment, and demographic factors (gender, SES, mother’s and father’s education level, mother’s and father’s age, family member with ASD) on age of first concerns and age of diagnosis. None of the mentioned variables were found to influence the age of first parental concern F (0.663), p = 0.824, R² = 0.173. On the contrary, these variables statistically significantly predicted age of diagnosis F = 94.66, p = 0.009, R² = 0.968. Specifically, SES, father’s age and mother’s age, mother’s education level, the presence of motor delay, and cognitive impairment predicted an earlier age of diagnosis (Table 4).

Table 4.

Results of multiple regression predicting age of ASD diagnosis.

Variable	β	SE	T
Diagnostic group	−0.05	1.36	−1.51
Gender	0.02	1.32	0.61
SES	−0.11	1.91	−3.45***
Mother’s education level	−0.06	1.51	−1.83
Father’s education level	0.003	1.11	0.11
Mother’s age	0.08	0.12	2.29*
Father’s age	−0.11	0.09	−2.86**
Family member with ASD	0.03	1.31	0.89
Communication (ADI-R)	0.05	1.29	1.50
Social interaction (ADI-R)	0.05	1.33	1.32
Restricted/repetitive behavior (ADI-R)	−0.003	1.30	−0.09
Loss of skills (ADI-R)	0.04	2.10	1.17
Behavioral symptoms (ADI-R)	−0.05	2.97	−0.49
Motor delay (ADI-R)	0.21	4.15	2.0*
Medical conditions (ADI-R)	0.11	5.38	1.13
ADOS Severity Score (ADI-R)	−0.03	0.087	−0.86
Cognitive impairment (ADI-R)	0.08	0.020	2.53
Verbal skills (ADI-R)	−0.01	0.027	−0.41

ASD: autism spectrum disorder; SES: socioeconomic status; ADI-R: Autism Diagnostic Interview–Revised; ADOS: Autism Diagnostic Observation Schedule; SES: socioeconomic status.

p < 0.05; **p < 0.01; ***p < 0.001.

Discussion

This study found that Venezuelan parents of children with ASD were aware of abnormal or atypical behaviors in their children before the second year of life. In all, 82% of children in this sample reported ASD-related symptoms by 24 months of age, but only 9.7% had a diagnosis by that age. These children received a diagnosis within the same range that has been found in previous studies of Latinos in the United States (Daniels and Mandell, 2014; Maenner et al., 2013; Mandell et al., 2010). The results were interesting: only some of the demographic and clinical variables had an effect on the age of diagnosis. Mother’s and father’s ages, initial concerns related to other non-ASD behaviors, and cognitive impairment were found to have an impact on age of diagnosis. The younger the father, the later the diagnosis, whereas the younger the mother, the earlier the diagnosis. The presence of non-ASD behaviors (seizures, crying spells, irritability, motor delay, self-aggression, and restlessness) was related to a later age of diagnosis. Cognitive impairment in ASD children as a delaying factor for early diagnosis has been the most prevalent result in the literature on ethnic disparity factors (Chaidez et al., 2014; De Giacomo and Fombonne, 1998; Maenner et al., 2013; Mishaal et al., 2014).

Consistent with most other studies, the symptoms that triggered parents’ recognition were mostly related to language and speech delay, lack of response to name, and motor delay—the same clinical presentation described in studies carried out in other countries (China, the United States, France, and the United Kingdom, among others; Baghdadli et al., 2003; De Giacomo and Fombonne, 1998; Qian et al., 2012; Shattuck et al., 2009). In a study conducted with children participating in the Autism and Developmental Disabilities Monitoring Network in 2006, Maenner et al. (2013) reported that Latino children in the United States exhibited fewer behaviors from the repetitive/restricted domain; for our sample, these behaviors were among the least frequent categories reported by parents as alert behaviors.

We had speculated that Venezuelan children would have an earlier age of diagnosis than that of Latino children living in the United States; however, the results fell into the same range of age of diagnosis reported for Latinos in other studies (Daniels and Mandell, 2010; Schieve et al., 2012; Shattuck et al., 2009). Some studies in the United States have reported a median age of ASD diagnosis after the fourth birthday (Christensen et al., 2016; Klin et al., 2015). These findings imply that the age of diagnosis of ASD in Venezuela is not so distant from the age of diagnosis reported in the US studies. There was a wide interval between recognition of first signs and the final diagnosis, which might be affected by cultural factors related to the availability of services and the impact of having a child with developmental delays. Although health and education in the country are universal and free, there are not enough professionals trained in the diagnosis of ASD and very few free referral services outside the urban areas. Thus, access to health and educational services might be listed as a possible reason for diagnostic delays in Venezuela. One factor worth mentioning is the lack of awareness of ASD, which is common in Third World countries, and was mentioned in one study of cultural conceptualization of autism in the Latino community (Zuckerman et al., 2014). In Latin cultures, behavior problems are usually attributed to poor parenting skills, so parents might take longer to seek professional help. It is also possible that for Latino parents, symptoms related to ASD are not recognized as disorders or problems that warrant the help of a professional, resulting in later diagnosis (Chaidez et al., 2014; Magaña et al., 2013).

Similarly, Venezuelan parents were aware of some developmental difficulties as early as 18 months; the delay in diagnosis could be thus attributed to the lack of ASD knowledge, which might lead to tardiness in looking for professional help. Magaña et al. (2013) expressed that disparities in age of diagnosis, access to treatment, and consequent use of treatment may be entwined with availability of resources such as money, knowledge, power, and social connections. Although we did not find that maternal level of education was a predictor of earlier age of diagnosis, lower SES was one of the demographic predictors for a later diagnosis. The majority of the children belonged to low SES families, who likely lack resources.

This is a clinical-based study with selective study sample from a research unit for ASD, which hinders generalizability. However, this is a well-characterized sample with diagnostic confirmation through standardized tests (SCQ, ADI-R, ADOS, Raven’s matrices). This study is, to our knowledge, the first in examining the age of parental concerns and the age of ASD diagnosis in a Latin American country. Also, the data are likely to provide information about clinical elements related to time of diagnosis, which might help in developing future research about Latino children in different countries and contexts. Clinical characterization and age of recognition of autism by Latino parents in Venezuela warrant further study of the cultural impact on autism diagnosis. A better understanding of cultural influences on age of diagnosis would likely translate to the timelier use of services independent of ethnicity.

Our findings emphasize the need for programs that target underserved groups, such as Latino, African-American, and other minority children, as well as children living in Third World countries and their families. These are programs that focus on ASD awareness, understanding the social implications of ASD symptoms, and developmental delays for each culture. The use of such programs might imply culture-sensitive training for health-care providers and health and education professionals to facilitate earlier referral, timely diagnosis, and the opportune initiation of autism-specific interventions that can enhance child development.

These results have clinical implications for screening, diagnosis, and intervention. Health authorities in Venezuela and other Latin American countries must develop public health policies and practices to correctly identify and diagnose ASD children, and clinicians must actively search for and identify those children and refer them to the best available treatment. Delays in identification and diagnosis have direct consequences in the timing of intervention. The later we start, the less opportunity the children will have to reach optimal outcomes.

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Baghdadli

Picot

Pascal

. (2003) Relationship between age of recognition of first disturbances and severity in young children with autism. European Child & Adolescent Psychiatry 12(3): 122–127.

Chaidez

Hansen

Hertz-Picciotto

(2014) Autism spectrum disorders in Hispanics and non-Hispanics. Autism 16(4): 381–397.

Christensen

Baio

Braun

. (2016) Prevalence and characteristics of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States. MMWR Surveillance Summaries 65(3): 1–23.

Daniels

Mandell

(2014) Explaining differences in age at autism spectrum disorder diagnosis: a critical review. Autism 18(5): 583–597.

Dawson

Rogers

Munson

. (2010) Randomized, controlled trial of an intervention for toddlers with autism. The Early Start Denver Model. Pediatrics 125(1): e17–e23.

De Giacomo

Fombonne

(1998) Parental recognition of developmental abnormalities in autism. European Child & Adolescent Psychiatry 7(3): 131–136.

Emerson

Morrell

Neece

(2016) Predictors of age of diagnosis for children with autism spectrum disorder: the role of a consistent source of medical care, race, and condition severity. Journal of Autism and Developmental Disorders 46: 127–138.

Instituto Nacional de Estadistica (2012) Censo poblacional. Available at: http://www.ine.gov.ve/ (accessed 15 March 2013).

Schieve

Rice

. (2015) Age at autism spectrum disorder (ASD) diagnosis by race, ethnicity, and primary household language among children with special health care needs, United States, 2009−2010. Maternal and Child Health Journal 19(8): 1687–1697.

10.

Klin

Klaiman

Jones

(2015) Reducing age of autism diagnosis: developmental, social neuroscience meets public health challenge. Revista De Neurologia 25(60 Suppl. 1): S3–S11.

11.

Liptak

Benzoni

Mruzek

. (2008) Disparities in diagnosis and access to health services for children with autism: data from the National Survey of Children’s Health. Journal of Developmental and Behavioral Pediatrics 29(3): 152–160.

12.

Lord

Rutter

DiLavore

. (2002) Autism Diagnostic Observation Schedule. WPS ed. Los Angeles, CA: Western Psychological Services.

13.

Maenner

Schieve

Rice

. (2013) Frequency and pattern of documented diagnostic features and the age of autism identification. Journal of the American Academy of Child and Adolescent Psychiatry 52(4): 401–413.

14.

Magaña

Lopez

Aguinaga

. (2013) Access to diagnosis and treatment services among Latino children with autism spectrum disorders. Intellectual and Developmental Disabilities 51(3): 141–153.

15.

Mandell

Listerud

Levy

. (2002) Race differences in the age at diagnosis among Medicaid-eligible children with autism. Journal of the American Academy of Child and Adolescent Psychiatry 41(12): 1447–1453.

16.

Mandell

Morales

Xie

. (2010) Age of diagnosis among Medicaid-enrolled children with autism, 2001–2004. Psychiatric Services 61(8): 822–829.

17.

Mandell

Novak

Zubritsky

(2005) Factors associated with age of diagnosis among children with autism spectrum disorders. Pediatrics 116(6): 1480–1486.

18.

Mandell

Wiggins

Carpenter

. (2009) Racial/ethnic disparities in the identification of children with autism spectrum disorders. American Journal of Public Health 99(3): 493–498.

19.

Mishaal

Ben Itzchak

Zachor

(2014) Age of autism spectrum disorder diagnosis is associated with child’s variables and parental experience. Research in Autism Spectrum Disorders 8(7): 873–880.

20.

Montiel

Peña

Montiel-Barbero

. (2008) Prevalence rates of attention deficit/hyperactivity disorder in a school sample of Venezuelan children. Child Psychiatry and Human Development 39(3): 311–322.

21.

Overton

Fielding

Garcia de Alba

(2007) Differential diagnosis of Hispanic children referred for autism spectrum disorders: complex issues. Journal of Autism and Developmental Disorders 37(10): 1996–2007.

22.

Parish

Magaña

Rose

. (2012) Health care of Latino children with autism and other developmental disabilities: quality of provider interaction mediates utilization. American Journal on Intellectual and Developmental Disabilities 117(4): 304–315.

23.

Qian

Reichle

Bogenschutz

(2012) Chinese parents’ perceptions of early development of their children diagnosed with autism spectrum disorders. Journal of Comparative Family Studies 43(6): 903–913.

24.

Raven

Court

(1998) Standard Progressive Matrices—Parallel Form. Oxford: Oxford Psychologists Press.

25.

Rutter

Bailey

Lord

. (2003) Social Communication Questionnaire. Los Angeles, CA: Western Psychological Services.

26.

Rutter

Le Couteur

Lord

(2003) Autism Diagnostic Interview—Revised. Los Angeles, CA: Western Psychological Services.

27.

Schieve

Rice

Yeargin-Allsopp

. (2012) Parent-reported prevalence of autism spectrum disorders in US-born children: an assessment of changes within birth cohorts from the 2003 to the 2007 National Survey of Children’s Health. Maternal and Child Health Journal 16(Suppl. 1): S151–S157.

28.

Shattuck

Durkin

Maenner

. (2009) Timing of identification among children with an autism spectrum disorder: findings from a population-based surveillance study. Journal of the American Academy of Child and Adolescent Psychiatry 48(5): 474–483.

29.

Yeargin-Allsopp

Rice

Karapurkar

. (2003) Prevalence of autism in a US metropolitan area. Journal of the American Medical Association 289(1): 49–55.

30.

Zuckerman

Mattox

Donelan

. (2013) Pediatrician identification of Latino children at risk for autism spectrum disorder. Pediatrics 132(3): 445–453.

31.

Zuckerman

Sinche

Cobian

. (2014) Conceptualization of autism in the Latino community and its relationship with early diagnosis. Journal of Developmental and Behavioral Pediatrics 35(8): 522–532.