Population-Based Indicators of Social Developmental Delay Relevant to Autism Spectrum Disorder and Association with Relevant Predictors in a Central American Country Restricted; Files Only

Bonnett, Michaela (Spring 2023)

Permanent URL: https://etd.library.emory.edu/concern/etds/765372715?locale=es
Published

Abstract

Objective

Despite autism spectrum disorder (ASD) being detected globally, many low- and middle-income countries (LMIC) do not have information about domestic ASD prevalence, hindering efforts to build efficient detection and assistance infrastructure. Many LMICs have completed UNICEF’s Multiple Indicator Cluster Survey v6 (MICS6), containing an Under 5 questionnaire (U5) with questions about young children’s development like those present in ASD screeners. The MICS6 may be utilized to create a population-based screener similar to a level-1 ASD screener focused on early social, communication, and behavioral development. The objectives of this study are to, using this tool, describe prevalence of potential social developmental delay associated with ASD, identify which characteristics of interest associated with ASD may be acting as predictors, and define any associations additional socio-economic variables may have with potential social developmental delay.

Methods

Analyses were performed on data from 1723 4-year-old respondents to the U5 of the Honduras 2019 MICS6, with consideration for complex survey design. A 10-point measure (Social developmental delay proxy score (SDDPS)) was created, with a cut-off set at ≥3. Descriptive analyses described the distribution of the SDDPS while linear and Poisson regressions described the association between three characteristics associated with ASD (early education attendance, sex, and urbanicity) and the SDDPS. Socio-demographic variables included in the analyses were age in months, sex, urbanicity, caretaker’s education level, translator usage, mother’s age, number of siblings, stunting, and wealth.

Results

A nationally representative 4.6% of 4-year-old children scored above the cut-off. Of the three associated characteristics, only urbanicity predicted on average a 0.13-point lower score on the SDDPS (p=0.017) compared to rurality. Among the additional socio-demographic variables, on average higher parental education was associated with a 0.14-point lower score (p=0.049) and children with one more sibling were 16% more likely to score above the cut-off compared to those with one fewer sibling (p=0.027).

Conclusions

The SDDPS found a prevalence within the expected range and defined several associations similar to those observed with ASD. While promising for its utility for detecting social developmental delay potentially indicative of developmental delays and differences associated with ASD among young children, further validation is necessary.

Table of Contents

Abstract   iv

Acknowledgements   vi

Introduction   1

Literature Review   2

Autism Spectrum Disorder   3

Prevalence of Autism Spectrum Disorder   4

Prevalence of Autism Spectrum Disorder in the United States   4

Global Prevalence of Autism Spectrum Disorder   5

Autism Spectrum Disorder in Honduras   6

Diagnosing and Detecting Autism Spectrum Disorder   7

Diagnosing Autism Spectrum Disorder   7

Screening and Detection of Autism Spectrum Disorder   7

Common Symptoms of Autism Spectrum Disorder   9

Social-Emotional Reciprocity   10

Non-Verbal Communicative Behaviors   10

Developing, Maintaining, and Understanding Relationships   10

Restricted, Repetitive Patterns of Behavior, Interests, or Activities   11

Barriers to Detection and Diagnosis of Autism   11

Education of the parent or caretaker   12

Income or Socioeconomic Status   12

Geography   13

Race and Ethnicity   13

Health Insurance   14

Evaluation at a Health or Education Source   15

Type of Symptoms and Co-occurring Intellectual Disability   15

Biological Sex of the Child   16

Nutrition and Stunting   16

Number of Siblings   17

Early Intervention   17

Early Intervention Techniques   18

Impact of Early Intervention   19

Delivery of Early Intervention in High-Income Countries   20

Delivery of Early Intervention in LMICs & Honduras   20

Conceptual Framework   21

Model 1: Early Childhood Education Attendance   22

Model 2: Child’s Sex   23

Model 3: Urbanicity   24

Data   25

The Multiple Indicator Cluster Survey, Round 6 (MICS6)   25

Survey Design   26

Honduras MICS6 Under 5 Questionnaire Dataset   27

Language/Ethnicity   29

Socio-Demographic   29

Physical Characteristics   30

Education   30

Early Childhood Development Index (ECDI)   31

Child Functioning   33

Use of MICS6 in the Detection of Developmental/Intellectual Delay   35

Methods   36

Social Developmental Delay Proxy Score (SDDPS)   37

Missing values   38

Coding of the outcome response variable “Social10”, the SDDPS   39

Descriptive methods   40

Analytic methods   41

Results   42

Descriptive   42

Analytic   45

Linear Regression   45

Poisson Regression   47

Discussion   48

Strengths and Limitations   51

Strengths   51

Limitations   52

Conclusions   53

Implications   53

Future Research Needs   54

References   56

Annex   65

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