Study 1: Long-term language stability in typical development

Participants. The ALSPAC is a prospective, population-based, longitudinal transgenerational observational study investigating influences on health and development across the life course. All births in the former Avon Health Authority with an expected date of delivery between 1 April 1991 and 31 December 1992 were eligible. Of the initial 14,541 pregnancies, there were a total of 14,676 fetuses, resulting in 14,062 live births and 13,988 children who were alive at 1 year of age. Because only 2.6% of the ALSPAC sample was non-White (of those participants who provided this data point), and this group was heterogeneous (0.9% Asian, 1.0% Black, and 0.7% other), we focused on the majority group (51, 52). From the 12,075 White European participants in the ALSPAC data, the following exclusion criteria were followed (some children might fall into multiple categories): Children who (i) were twins (n = 306), (ii) were born preterm (born less than 37 weeks, n = 677), (iii) were hearing impaired (n = 233), (iv) had dyslexia (n = 332), (v) were diagnosed with autism (n = 91), and (vi) were bilingual or spoke a language other than English as their main language (n = 280) were excluded, resulting in 9794 children. An additional 8869 children were excluded from study 1 because they were not from the CiF cohort and/or did not have the additional CiF assessments used in the current study. Children who did not fall into the exclusion criteria and provided data at any of the data collection waves were included in study 1.

Maternal education, collected at 32 weeks of pregnancy as an ordinal variable according to increasing levels of achievement, was varied: certificate of secondary education (13.0%), vocational (10.8%), O level (35.2%), A level (25.9%), and university degree (15.1%). Maternal social class ranged from unskilled (2.0%), partly skilled (7.8%), skilled manual (7.2%), skilled nonmanual (42.8%), managerial and technical (33.8%), to professional (6.4%).

Procedures. Child language data were derived from caregiver reports and direct child assessments by trained psychologists during research clinics. The ALSPAC study website includes descriptions of measures used and scoring methods. In addition to the language measures detailed below, caregivers completed questionnaires that supplied demographic information about children’s health status, family language, and the like.

Language assessments. We used data collected across 13 ALSPAC collection waves (Table 1). However, we aggregated data collected at ages 1 year 3 months and 1 year 6 months (two waves) into year 1 measures, and those collected at ages 2 years and 2 years 1 month (2 waves) into year 2 measures; thus, we studied 13 waves but calculated stability across 11 ages.

Caregiver report: At age 6 months, caregivers completed an ALSPAC-modified Denver Developmental Screening Test (hereinafter referred to as modified DDST) (53) adapted for caregiver completion. The “communication” scores were used.

Caregiver report: At age 1 year 3 months, the understand, vocabulary, and social (nonverbal) communication scores on the ALSPAC-modified MacArthur Communication Development Inventories (hereinafter referred to as modified MCDI) (11) Words and Gestures were used. Twelve of the 28 questions (called “phrases” on the original MCDI) were asked for the understand scale, and the vocabulary checklist was cut by removing entire sections (i.e., toys, small household items, people, action words, words about time, pronouns, question words, prepositions and locations, and quantifiers), as well as some items from other sections from the original MCDI. Furthermore, some American English items were adapted or replaced with the British English equivalents (e.g., lorry instead of truck; sweater or jumper). Ten of the 12 social communication items (called “first communicative gestures” on the original MCDI) were asked. See the Supplementary Materials for more details about the modified MCDI.

Caregiver report: At age 2 years, the vocabulary, grammar, plurals, and tense scores on the modified MCDI Words and Sentences were used. The vocabulary checklist was cut by removing sound effects and animal sounds, small household items, and connecting words as well as by removing items from other sections from the original MCDI. The 4 grammar items (called “word endings” on the original MCDI), 5 irregular plurals (called “word forms—nouns” on the original MCDI), and 20 past tense (called “word forms—verbs” on the original MCDI) items were unmodified.

Direct assessment: At age 2 years 1 month, children in the CiF cohort were administered the RDLS (54). The RDLS comprehension scale measures a child’s verbal comprehension by administering a series of activities where the child is asked to respond to and carry out a series of spoken tasks. The raw score was used.

Caregiver report: At age 3 years 2 months, the vocabulary, plurals, past tense, and word combination scores on the modified MCDI Words and Sentences were used. The vocabulary checklist was the same as the one used at year 2. The 5 irregular plurals (called “word forms—nouns” on the original MCDI) and 20 past tense (called “word forms—verbs” on the original MCDI) items were unmodified. In addition, two items that ask whether the child uses plurals by adding “-s” to the end of words or uses past tense by adding “-ed” to the end of words were included in the plurals and past tense scales, respectively. The word combination items were modified from the 14 “complexity” items of the original MCDI. Two items were dropped, and some items were adapted to add a third option (e.g., two feet, two foots, two foot) or to change the object (e.g., “that’s my book” versus “that’s my truck”).

Direct assessment: At age 4 years 1 month, four verbal subscale scaled scores (M = 10 and SD = 3) of the Wechsler Preschool and Primary Scale of Intelligence—Revised UK Edition (WPPSI) (41) were used: information, comprehension, vocabulary, and similarity.

Direct assessment: At age 5 years 1 month, the Bus Story Test (55), a screening test of verbal expression, was administered. The assessment involves children listening to a spoken narrative about a bus, accompanied by pictures depicting the events that occur in the story. Children then retell the story with the pictures as support. The child’s narrative is recorded orthographically and scored for information content (number of relevant pieces of information given) and sentence length (mean sentence length of the five longest sentences). In addition, the same RDLS comprehension scale that was used at 2 years 1 month was repeated at age 5 years 1 month. Last, the Initial Consonant Detection Test (56) asked children to identify which two of three words illustrated by line drawings began with the same initial consonants. A total of 10 trials were given, and the number of correct responses was recorded.

Direct assessment: At age 7 years 6 months, reading was assessed with measures on the basis of the Wechsler Objective Reading Dimensions (WORD) (57). Pictures and words were used to assess decoding and word reading. The child was shown a series of four pictures. Each picture had four short, simple words underneath it. The child was asked to point to the word that had the same beginning or ending sound as the picture. This request was then followed by a series of three pictures, each with four words beneath, each starting with the same letter as the picture. The child was asked to point to the word that correctly named the picture. The child was then asked to read aloud a series of 48 unconnected words that increased in difficulty. Total numbers of correct responses were used. Spelling was assessed by a series of 15 words that were piloted and chosen by the ALSPAC team (e.g., chin, brought, and telephone). Each word was read aloud on its own, within a specific sentence incorporating the word, and lastly read alone again. The child was asked to write down the spelling of the word even if he or she was just guessing. The total number of words spelled correctly was tallied and used. In addition to the WORD, the Phoneme Detection Task (58) comprised 40 test items of increasing difficulty. It involved asking the child to repeat a word and then to say it again, but with some part of the word (a phoneme or number of phonemes) removed. Total numbers of correct responses were used.

Direct assessment: At age 8 years 6 months, four verbal subscale raw scores on the Wechsler Intelligence Scale for Children—III UK Edition (WISC) (59) were used: information, comprehension, vocabulary, and similarity. Two subtests of the Wechsler Objective Language Dimensions (WOLD) (60) were used to measure listening comprehension and oral expression. Listening comprehension involves the child listening to the tester reading aloud a paragraph about a displayed picture. The child then answers questions on what was heard. The child has to make inferences about what was read to them and answer the questions verbally. Expressive vocabulary was assessed by a series of 10 pictures. The total numbers of correct responses on comprehension and expressive vocabulary were each tallied and used.

Direct assessment: At age 9 years 6 months, reading was assessed using the basic reading subtest of the WORD (57). Children were asked to read aloud 10 real words (e.g., huge, union, and unusual), followed by 10 nonreal words (e.g., duter, uningest, and smape). Both the real and nonreal words were selected from a larger list of words taken from research conducted by Nunes et al. (61). Total numbers of correct responses on real and nonreal words were each tallied and used. The revised Neale Analysis of Reading Ability (NARA II) (62) was used to assess children’s reading skills and comprehension. In this test, children read aloud short passages of stories that resulted in an accuracy score, and their answers to a series of questions about the content of the story resulted in a reading comprehension score.

Direct assessment: At age 13 years 6 months, word reading efficiency was assessed by word and pseudoword tests of the Test of Word Reading Efficiency (TOWRE) (63). Children were asked to read out loud 104 real words (e.g., complete and wonderful), followed by a list of 63 nonreal words (e.g., glack and framble). Total numbers of correct responses on real and nonreal words were tallied; because of a very high correlation between the two reading scores, r = 0.81, a mean standard score was computed and used in analysis.

Direct assessment: At age 15 years 6 months, the vocabulary subscale raw score on the Wechsler Abbreviated Scale of Intelligence (WASI) (64) was used.

Covariates. We assessed the possibility that child nonverbal intelligence (29) and sociability (65), both of which are known to be associated with child language, and mothers’ age and education, both of which are also known to be associated with child language, would account for some of the stability of language competence and performance. Specific covariates (child nonverbal intelligence and sociability) were presumed to be associated with child language variables concurrently or prospectively (but not retrospectively). General covariates (maternal age and education) were presumed to be associated with all child language variables, regardless of the child’s age.

Children’s nonverbal intelligence was assessed three times at clinic visits. At age 4 years 1 month, the performance IQ score of the WPPSI (41) was used. At age 8 years 6 months, the performance IQ score of the WISC (59) was used. At age 15 years 6 months, nonverbal intelligence was measured by the Matrix Reasoning subtest of the WASI (64).

Child sociability was obtained from caregiver reports across data collection waves. At ages 6 months, 1 year 6 months, and 2 years 6 months, the social achievement scores of the adapted DDST (53) were used. At ages 3 years 2 months, 4 years 9 months, and 5 years 9 months, the sociability scores from the Emotionality, Activity, Sociability Temperament questionnaire (66, 67) were used.

Maternal age at childbirth was calculated from the date of delivery and the mother’s date of birth recorded at enrollment. Educational attainment was obtained from a questionnaire sent home at 32 weeks gestation.

Statistical analysis. The SDs and ranges of all language measures (table S1) indicated considerable variation, as is common in the literature and prerequisite to assessments of stability. Variable distributions were examined for univariate normality (68), and transformations were applied to improve distributions. Because of the range of child age at each wave, we explored correlations of child age with all raw test scores to determine whether age adjustment was warranted. Age-adjusted scores were computed for all language variables that showed significant concurrent correlations with child age and were used in structural equation models (SEMs).

Language stability was evaluated by fitting SEMs using maximum likelihood functions (MLFs) and followed the mathematical models of Bentler and Weeks (69), as implemented in EQS 6.1 (70). SEM is a robust tool for assessing stability because latent variables capture shared variance among their indicators, and so variance uniquely associated with rater bias, random measurement error, or specific error (variance arising from some characteristic unique to a particular indicator that was not accounted for by the factor) is relegated to its error term.

Missing data points (20.4% of the total data) were handled in EQS using full information maximum likelihood with a two-stage Expectation-Maximization estimation of the structured model and the MLF (71). Monte Carlo studies have demonstrated the general superiority of the structured-model EM method implemented in EQS 6.1 compared to other techniques to recover missing data (72, 73). In the course of fitting SEMs, we evaluated Mardia (74) coefficients of multivariate kurtosis and the cases that contributed most to those estimates, as well as the stability of parameter estimates and the cases that contributed disproportionately to parameter estimates. No significant problems with influential cases emerged. Model fit was assessed using scaled Y-B χ2 statistic, robust CFI, standardized SRMR (75), and RMSEA. Cutoff values ≈0.95 for CFI and ≈0.09 and ≈0.06 for SRMR and RMSEA, respectively, are indicative of a relatively good fit between the hypothesized model and observed data (21). We gave greater weight to the incremental/approximate fit indices than to χ2 because the χ2 value is known to be sensitive to sample size (76) and the size of the correlations in the model (77). Standardized path coefficients are presented in text and figures.

For correlations and standardized path coefficients, we adopted conventional magnitudes of r corresponding to small, medium, and large effect sizes as ≈0.10, 0.30, and 0.50, respectively (78, p. 61). All stabilities were large except two medium-sized stabilities between 6 months and year 1 and between the single observed variables at 13 and 15 years.

Next, we explored whether specific covariates were associated with child language measures. We calculated correlations of (i) year 4 WPPSI performance IQ with years 4, 5, 6, and 7 language variables; (ii) year 8 WISC performance IQ with years 8, 9, and 13 language variables; (iii) year 15 WASI matrix reasoning with vocabulary; (iv) child sociability with concurrent language variables from ages 6 months through year 5; and (v) year 5 child sociability with all language variables from years 7 through 15. Children’s nonverbal intelligence significantly correlated with all language variables (r values ranged from 0.15 to 0.50, all P ≤ 0.001); however, children’s sociability related to only some language variables, with significant correlations ranging from 0.07 (P < 0.05) to 0.46 (P < 0.001). To test whether the stability model held controlling for specific covariates and the two general covariates, we re-evaluated the a priori model (Fig. 1) using the adjusted language scores with the shared variance with specific covariates removed and adding the two general covariates as exogenous variables to the SEM. Direct paths from maternal age and education to all eight language-latent variables, and the three observed variables at 6 months and 13 and 15 years, were added to the model.

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