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The Home Language Environment and Early Childhood Development: A LENA Study from Rural and Peri-Urban China

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Title: The Home Language Environment and Early Childhood Development: A LENA Study from Rural and Peri-Urban China
Language: English
Authors: Xinwu Zhang, Delei Liu, Lucy Pappas, Sarah-Eve Dill, Tianli Feng, Yunting Zhang, Jin Zhao, Scott Rozelle, Yue Ma
Source: Applied Developmental Science. 2024 28(4):655-673.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 19
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Foreign Countries, Infants, Child Development, Developmental Delays, Delayed Speech, Rural Areas, Suburbs, Language Acquisition, Parent Child Relationship, Mothers, Interpersonal Communication
Geographic Terms: China
DOI: 10.1080/10888691.2023.2267440
ISSN: 1088-8691
1532-480X
Abstract: The home language environment is a significant correlate of early childhood development outcomes; however, less is known about this mechanism in rural and peri-urban China where rates of developmental delay are as high as 52%. This study examines associations between the home language environment and child development in a sample of 158 children (58% boys) aged 18-24 months (M[subscript age] = 21.5) from rural and peri-urban households in Western China. Results show a significant association between adult-child conversation count and language development, suggesting the home language environment may be a mechanism for child development in rural and peri-urban China. 22.5% of the sample were at risk of language delay. Mother's employment and child's age were significant factors in the home language environment.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1443405
Database: ERIC
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  Value: <anid>AN0180230223;7lf01oct.24;2024Oct15.04:43;v2.2.500</anid> <title id="AN0180230223-1">The home language environment and early childhood development: a LENA study from rural and peri-urban China </title> <p>The home language environment is a significant correlate of early childhood development outcomes; however, less is known about this mechanism in rural and peri-urban China where rates of developmental delay are as high as 52%. This study examines associations between the home language environment and child development in a sample of 158 children (58% boys) aged 18–24 months (M<sub>age</sub> = 21.5) from rural and peri-urban households in Western China. Results show a significant association between adult-child conversation count and language development, suggesting the home language environment may be a mechanism for child development in rural and peri-urban China. 22.5% of the sample were at risk of language delay. Mother's employment and child's age were significant factors in the home language environment.</p> <p>RESEARCH HIGHLIGHTS: This research investigates the links between the home language environment and ECD in rural and peri-urban communities in China. This study shows significant positive associations between measures of the home language environment and language development outcomes, as well as with overall ECD outcomes. Adult-child conversations were more important for language development outcomes than was the number of adult words spoken. Female-initiated conversations were more important than child-initiated conversations for language development.</p> <p>The home language environment is a key factor of early childhood development (ECD) (Gilkerson et al., [<reflink idref="bib26" id="ref1">26</reflink>]; Rowe, [<reflink idref="bib61" id="ref2">61</reflink>]). Studies in Western and high-income samples have shown that higher rates of and more diverse adult speech are correlated with increased child vocabulary development, processing speeds, lexical diversity, and higher levels of cognition (Anderson et al., [<reflink idref="bib1" id="ref3">1</reflink>]; Ferjan Ramírez et al., [<reflink idref="bib19" id="ref4">19</reflink>]; d'Apice et al., [<reflink idref="bib12" id="ref5">12</reflink>]). Moreover, conversational speech between caregivers and children has been shown to be positively correlated with language, cognitive, and social-emotional development (Gómez & Strasser, [<reflink idref="bib28" id="ref6">28</reflink>]; Ferjan Ramírez et al., [<reflink idref="bib19" id="ref7">19</reflink>]; Gilkerson et al., [<reflink idref="bib26" id="ref8">26</reflink>]). While less research has focused on non-Western and lower-resourced environments (in terms of income levels, educational attainment, and access to quality health care), studies in these settings do suggest similar associations between the language a child hears at home and their developmental outcomes (Rowe et al., [<reflink idref="bib63" id="ref9">63</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref10">80</reflink>]).</p> <p>Why is ECD important? Development across cognitive, language, motor, and social-emotional domains in the first three years of life can determine the trajectories of both early and long-term life outcomes (Gilkerson et al., [<reflink idref="bib26" id="ref11">26</reflink>]; Black et al., [<reflink idref="bib3" id="ref12">3</reflink>]; Wake et al., [<reflink idref="bib75" id="ref13">75</reflink>]). While important for all children, not all children experience positive ECD trajectories. In fact, many children from low-resource settings are at risk of not reaching their full developmental potentials. In 2016, one study estimated that 250 million children aged 0–5 years living in low- and middle-income countries (LMICs) were at risk of developmental delays (Black et al., [<reflink idref="bib3" id="ref14">3</reflink>]). At the time of that study, 250 million children equated to 43% of all children living in LMICs. Rural China, where more than half (55%) of China's population lives, is an example of a low-resource, LMIC setting where ECD is a pressing concern. Compared to children raised in high-resource and urban areas of China, where the rate of developmental delay is 3–15% (Bai et al., [<reflink idref="bib2" id="ref15">2</reflink>]), children raised in rural communities are at a much higher risk of delay. Research from samples in both rural and peri-urban China has identified among children aged 0–3 years, the rate of delay is 49% for cognitive delays, 52% for language delays, 53% for social-emotional delays, and 30% for motor delays (Wang et al., [<reflink idref="bib76" id="ref16">76</reflink>]).</p> <p>While rates of developmental delay in rural China are high, research has found positive associations between the home language environment and ECD outcomes, suggesting the home language environment might be one mechanism for improving developmental outcomes. Although research on the home language environment in rural China is rare, one study found that children raised in rural households hear less adult speech and engage in fewer adult-child conversations than children in urban China (Ma et al., [<reflink idref="bib49" id="ref17">49</reflink>]). This study also found wide variation in rural home language environments, as some households are characterized by high rates of adult speech and conversation with children, and others report substantially lower measures (Ma et al., [<reflink idref="bib49" id="ref18">49</reflink>]). Moreover, evidence from studies shows that the home language environment in rural households is a significant correlate of language, cognitive, social-emotional, and motor development in Chinese samples (Gao et al., [<reflink idref="bib24" id="ref19">24</reflink>]; Ma et al., [<reflink idref="bib49" id="ref20">49</reflink>]), though these links have not been explicitly studied in peri-urban samples. This leads us to our study. Based on previous findings, we ask if the home language environment in rural and peri-urban Western China has significant associations with ECD outcomes (cognition, language, social-emotional, and motor development), and whether the home language environment may be a significant mechanism of ECD.</p> <hd id="AN0180230223-2">The home language environment</hd> <p>Several elements of the home language environment have been linked to ECD outcomes in the international literature (d'Apice & von Stumm, [<reflink idref="bib11" id="ref21">11</reflink>]; d'Apice et al., [<reflink idref="bib12" id="ref22">12</reflink>]). The quantity of speech is one important factor in a child's language acquisition, lexical diversity, language abilities (d'Apice et al., [<reflink idref="bib12" id="ref23">12</reflink>]; Gilkerson et al., [<reflink idref="bib25" id="ref24">25</reflink>]; Rowe, [<reflink idref="bib61" id="ref25">61</reflink>]), as well as cognitive development (d'Apice & von Stumm, [<reflink idref="bib11" id="ref26">11</reflink>]). However, despite positive findings, other research suggests that the number of words spoken may not matter. For example, Pan et al. ([<reflink idref="bib58" id="ref27">58</reflink>]), a study on 108 low-income mothers with children aged 14 months, found null associations between maternal word quantity and a child's growth in the number of different words spoken. While the literature remains mixed on the quantity of speech, there are other aspects of the home language environment that are important for ECD outcomes.</p> <p>A second important element of the home language environment is the quality of the language spoken, often measured through the amount and type of conversational speech. Linguistic interaction between adults and children has been shown to promote development across domains: language, cognitive, and social-emotional (Gómez & Strasser, [<reflink idref="bib28" id="ref28">28</reflink>]; Ferjan Ramírez et al., [<reflink idref="bib19" id="ref29">19</reflink>]). More specifically, parental responsivity encourages the development of children's problem-solving and cognitive skills (Hirsh-Pasek et al., [<reflink idref="bib31" id="ref30">31</reflink>]), as responding to children with more wh-questions ("what," "who," "where," "when," and "why") is correlated with vocabulary skill development, learning ability, and cognitive development (Rowe et al., [<reflink idref="bib63" id="ref31">63</reflink>]; Leech et al., [<reflink idref="bib41" id="ref32">41</reflink>]; Valian & Casey, [<reflink idref="bib74" id="ref33">74</reflink>]).</p> <p>Thus, looking at conversational speech even closer, who initiates a conversation might be significant for ECD outcomes. For example, preliminary research suggests there exist differences in how male and female caregivers interact with their children, which may lead to differences in child development outcomes. Regarding the quantity of speech, Davidson and Snow ([<reflink idref="bib13" id="ref34">13</reflink>]) and Kokkinaki ([<reflink idref="bib38" id="ref35">38</reflink>]) found that fathers talk less to children than mothers, but Rowe et al. ([<reflink idref="bib62" id="ref36">62</reflink>]) found no difference between the number of female- and male-initiated conversations. Regarding conversation-eliciting speech, studies suggest that male caregivers use more clarifying questions when speaking with their children than female caregivers (Kokkinaki, [<reflink idref="bib38" id="ref37">38</reflink>]; Leaper et al., [<reflink idref="bib40" id="ref38">40</reflink>]). Such research falls under the scope of language socialization, which is how children are socialized into linguistic and interactional practices (Ochs & Schieffelin, [<reflink idref="bib56" id="ref39">56</reflink>]). This includes how children are spoken to, what types of conversations are being had in the home, and so on, all of which differ based on the cultural contexts in which children are raised. For example, much of the research in language socialization focuses on particular interactional practices in different cultural settings in Western settings (e.g. Jonk & Enns, [<reflink idref="bib36" id="ref40">36</reflink>]; Simmons & Johnston, [<reflink idref="bib69" id="ref41">69</reflink>]) versus LMICs (Shohet, [<reflink idref="bib68" id="ref42">68</reflink>]), as well as studying how language is used in interactions and how it influences the development of children's communicative skills and their abilities to think, feel, and interact like others (e.g. Ganek et al., [<reflink idref="bib23" id="ref43">23</reflink>]; Duranti et al., [<reflink idref="bib16" id="ref44">16</reflink>]; Burdelski, [<reflink idref="bib4" id="ref45">4</reflink>]). Thus, the cultural context in which children are raised may have significant effects on who says what in the household.</p> <p>Beyond whether conversations are initiated by female or male adults, research on language socialization suggests that whether an adult or a child initiates a conversation matters. Previous studies show that both child-initiated and adult-initiated conversations are positively associated with a child's productive vocabulary in Western settings (Salo et al., [<reflink idref="bib65" id="ref46">65</reflink>]; Lopez et al., [<reflink idref="bib65" id="ref47">65</reflink>]). In high-resource settings, Salo et al. ([<reflink idref="bib65" id="ref48">65</reflink>]) found that children typically engage in more adult-initiated conversations than child-initiated conversations and that the positive impact of adult–infant conversations at the age of 6 months on language development one year later is driven by adult-initiated conversations, not child-initiated conversations. This suggests that adult-initiated interactions may be more important than child-initiated conversations for language development, though additional research on this topic in non-high-resource and non-Western settings is still warranted.</p> <hd id="AN0180230223-3">The Language Environment Analysis (LENA™) system</hd> <p>The home is where young children spend the majority of their time with caregivers, yet naturalistic home observations of children's exposure to adult language are rare, due to the high costs of recording equipment and the phenomenon of observer reactivity that is often triggered by researchers operating recording devices (d'Apice et al., [<reflink idref="bib12" id="ref49">12</reflink>]). However, these challenges have recently been addressed by a digital recording technology known as the Language Environment Analysis (LENA™) system. Capable of distinguishing adult, child, and electronic voices, the LENA system quantitatively measures a child's home language environment without observer biases for up to 16 hours of audio (Ford et al., [<reflink idref="bib20" id="ref50">20</reflink>]). Despite being a breakthrough for naturalistic observations, the LENA technology has some shortcomings. First, it only collects auditory information and does not capture visual data. In other words, gestural communication is not included in this analysis, which could provide helpful data for better understanding the specifics of language socialization practices in different households. Second, LENA does not count conversational turns between nearby peer children and adults, which may represent a significant amount of the language stimulation a child is exposed to in some cultures (Ochs, [<reflink idref="bib55" id="ref51">55</reflink>]). Third, as discussed in Ganek and Eriks-Brophy ([<reflink idref="bib22" id="ref52">22</reflink>]), the LENA system excludes sound segments where two speakers overlap or when a speaker is talking amidst significant background noise, making such elements of the home language environment unavailable for analysis.</p> <p>Numerous studies in Western and high-income settings have used LENA to assess the relations between the home language environment and ECD (d'Apice et al., [<reflink idref="bib12" id="ref53">12</reflink>]; Gilkerson et al., [<reflink idref="bib26" id="ref54">26</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref55">80</reflink>]). Using LENA, the quantity of caregiver speech in the home environment has been strongly associated with infant language development (Zimmerman et al., [<reflink idref="bib90" id="ref56">90</reflink>]) and predictive of later life language skills (Gilkerson et al., [<reflink idref="bib26" id="ref57">26</reflink>]). Additionally, the social context, style, and quantity of speech addressed to children have been linked to stronger language development outcomes (Ramírez-Esparza et al., [<reflink idref="bib60" id="ref58">60</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref59">80</reflink>]).</p> <p>Such LENA studies have revealed important elements of the home language environment; however, most LENA studies come from Western and higher income samples. In our literature review, we found few studies that have used LENA to assess associations between the home language environment and ECD in non-Western settings (e.g., Casillas et al., [<reflink idref="bib6" id="ref60">6</reflink>]; Weber et al., [<reflink idref="bib79" id="ref61">79</reflink>]; Pae et al., [<reflink idref="bib57" id="ref62">57</reflink>]; Zhang et al., [<reflink idref="bib89" id="ref63">89</reflink>]). Even fewer investigated the home language environment among low-resource populations (Ma et al., [<reflink idref="bib49" id="ref64">49</reflink>]; Casillas et al., [<reflink idref="bib6" id="ref65">6</reflink>]; Weber et al., [<reflink idref="bib79" id="ref66">79</reflink>]). Among the few LENA studies in China, Ma et al. ([<reflink idref="bib49" id="ref67">49</reflink>]) found that the average number of adult words and conversational turns experienced by infants aged 20–28 months in rural Shaanxi were significantly lower than those experienced by even younger infants (5–30 months) in urban Shanghai (Zhang et al., [<reflink idref="bib89" id="ref68">89</reflink>]). To our knowledge, no literature has used LENA to study the relations between the home language environment and multiple domains of ECD in lower-income families or families from diverse rural backgrounds (i.e., rural and peri-urban) in China.</p> <hd id="AN0180230223-4">The household and the home language environment</hd> <p>Household characteristics, such as household resources, income, child characteristics, and family dynamics, may influence the quantity and type of speech present in the home language environment. Studies show that compared to high-income households, low-income or low-resource households often have less speech and fewer conversations at home (Ganek & Eriks-Brophy, [<reflink idref="bib22" id="ref69">22</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref70">80</reflink>]). Furthermore, evidence suggests that caregivers from lower-resource households tend to use less language and a less varied vocabulary compared to parents from higher-resource households (Rowe, [<reflink idref="bib61" id="ref71">61</reflink>]). However, within low-resource samples, several studies have found considerable variation in the amount of adult speech and the number of adult-child conversations, indicating the presence of outliers (Ma et al., [<reflink idref="bib49" id="ref72">49</reflink>]; Leech et al., [<reflink idref="bib41" id="ref73">41</reflink>]).</p> <p>The influence of child age on the home language environment remains inconclusive, as Casillas et al. ([<reflink idref="bib6" id="ref74">6</reflink>]) found no correlation between child-directed speech and the age of the child, while Casillas et al. ([<reflink idref="bib5" id="ref75">5</reflink>]) found positive correlations between child age and the quantity of parent linguistic input. Anderson et al. ([<reflink idref="bib1" id="ref76">1</reflink>]) also found that parent linguistic quality positively correlates with child age. Child gender may be another important variable based upon mixed findings: Johnson et al. ([<reflink idref="bib35" id="ref77">35</reflink>]) found that in the first months of life, female caregivers respond more frequently to female children than male children, while the opposite is observed in male caregivers. However, a study by Gilkerson et al. ([<reflink idref="bib25" id="ref78">25</reflink>]) found no significant differences between boys' and girls' LENA measures among children aged 2–48 months.</p> <p>Examining household characteristics, Ma et al. ([<reflink idref="bib49" id="ref79">49</reflink>]) showed that older mothers were significantly more likely to have more conversations with children than younger mothers. Additionally, the number of siblings in the household was associated with fewer conversational turns between the focus child and adults. Previous studies suggest that household size is an influential factor in the home language environment and language development (Mayor et al., [<reflink idref="bib51" id="ref80">51</reflink>]). The identity of the primary caregiver is also an important aspect of the home environment, as about one-third of primary caregivers of young children in rural China are grandmothers—a caregiver type that has been shown to influence early childhood development outcomes (Yue et al., [<reflink idref="bib85" id="ref81">85</reflink>]).</p> <p>Finally, in the context of China, <emph>hukou</emph> (or household registration status) may be significant, as it identifies individuals by their "places of origin," either rural or urban. An urban <emph>hukou</emph> confers more privileges than a rural hukou, such as better education quality, occupation opportunities, and income outcomes (Li, [<reflink idref="bib43" id="ref82">43</reflink>]). Past research suggests that educational attainment, occupation, and income are all associated with language development outcomes, indicating that <emph>hukou</emph> status might be a relevant factor (Ganek & Eriks-Brophy, [<reflink idref="bib22" id="ref83">22</reflink>]; Gilkerson et al., [<reflink idref="bib25" id="ref84">25</reflink>]; Ramírez-Esparza et al., [<reflink idref="bib59" id="ref85">59</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref86">80</reflink>]).</p> <hd id="AN0180230223-5">The present study</hd> <p>This study aimed to examine the correlations and mechanisms between the home language environment and early childhood development (ECD) in low-resource rural and peri-urban communities in China. Previous research has indicated that nearly half of the sampled infants in rural China experience developmental delays (Yue et al., [<reflink idref="bib86" id="ref87">86</reflink>]), and these delays have been linked to low rates of parental responsivity and parent-child interactions (Wang et al., [<reflink idref="bib76" id="ref88">76</reflink>]; Yue et al., [<reflink idref="bib86" id="ref89">86</reflink>]). Additionally, preliminary research on the home language environment in rural China has shown its impact on ECD across cognitive, language, motor, and social-emotional domains (Gao et al., [<reflink idref="bib24" id="ref90">24</reflink>]; Ma et al., [<reflink idref="bib49" id="ref91">49</reflink>]). Considering these findings, rural and peri-urban China provided a unique opportunity to examine the home language environment of low-resource families representing China's rural populations.</p> <p>To investigate the associations between the home language environment and ECD among rural and peri-urban families in Western China, we pursued three specific objectives. First, using LENA technology, we described the home language environment, and through caregiver-reported surveys, we described ECD outcomes among sample households with children aged 18–24 months. Second, we examined the demographic characteristics associated with the home language environment. Third, we explored the correlations between the home language environment and overall ECD outcomes, as well as specific cognitive, language, motor, and social-emotional outcomes.</p> <hd id="AN0180230223-6">Methods</hd> <p></p> <hd id="AN0180230223-7">Sampling and participants</hd> <p>Data for this study were collected from rural (including peri-urban) households in two areas of Province A, located in Western China. The first area included two rural counties in Prefecture A. In 2019, the annual per capita income of rural residents in Prefecture A was 18,177 yuan ($2806) (Hu & Liu, [<reflink idref="bib33" id="ref92">33</reflink>]), which was less than half the per capita income of urban residents in the capital of Province A (Wang, [<reflink idref="bib77" id="ref93">77</reflink>]). The second area was a peri-urban district located in the eastern suburbs of City A, Province A's provincial capital. Originally a rural farming area, this district had an urbanization rate of 73% in 2020, with most urban development occurring since 2010 (Wang, [<reflink idref="bib77" id="ref94">77</reflink>]). Despite its recent urban transformation, over one-third of the district's residents were still legally classified as rural (based on <emph>hukou</emph> status) at the time of surveying. In 2019, the annual per capita income of rural residents in the district was 30,405 yuan ($4691), much lower than the 45,962 yuan ($7092) per capita income for urban residents (Wang, [<reflink idref="bib78" id="ref95">78</reflink>]). Together, these areas are relatively representative of low-resource households from rural backgrounds in Western China.</p> <p>Due to geographic and administrative differences between rural and peri-urban China, the research team followed two separate sampling protocols for households in each area. To select the rural sample, the research team followed a two-step sampling protocol. First, all townships in the two rural counties were included in the study, except for the one township in each county that housed the county seat of government (which is typically wealthier and more urban than the rest of the county). Second, the research team obtained a list of households with children aged 18–24 months (Zangl & Fernald, [<reflink idref="bib87" id="ref96">87</reflink>]) from each township government, totaling 175 households. Households that were not legally classified as rural were excluded, and all remaining households were enrolled in the study. From the rural counties, a total of 109 households completed the survey, and 77 agreed to record the home language environment using the LENA recording device.</p> <p>To select the peri-urban sample, the research team first obtained a list of all children aged 18–24 months from two local hospitals in the district. To confirm peri-urban households met the eligibility criteria of being rural migrants or urbanized farmers, as defined by the Chinese government, enumerators called households to randomly screen participants. To be a "rural migrant," (a) the legal residence of either caregiver had to be a rural area outside of the city; and (b) one caregiver had to be living in the district for at least 6 months (Children in China: An Atlas of Social Indicator, [<reflink idref="bib8" id="ref97">8</reflink>]). To be an "urbanized farmer," (a) the legal residence of either caregiver had to be within the district; (b) all or part of the household's farmland had to have been acquired by the government; and (c) any remaining land owned by the household had to average <200 square meters per adult (Hu, [<reflink idref="bib32" id="ref98">32</reflink>]). From the peri-urban district, a total of 109 eligible households agreed to participate in the survey, and 81 households agreed to collect recordings of their home language environments using the LENA recording device.</p> <p>The final analytical sample included 158 households from rural and peri-urban Province A. All sampled male caregivers were of Han ethnicity. Out of the 158 female caregivers, 155 were Han, and 3 were from minority ethnicities (Dong, Qiang, and Tibetan). All participating children (58% were male) were aged between 18 and 24 months (<emph>M</emph> = 21.5). The research team conducted a balance test to compare the demographic characteristics of households that consented to provide LENA data and those that did not (see Supplementary Appendix Table 1). The results show that across the whole sample, there were no statistically significant differences between the LENA consent and reject groups.</p> <p>Table 1. Descriptive statistics of household characteristics (<emph>N</emph> = 158).</p> <p> <ephtml> <table><thead><tr><td>Variables</td><td>Mean/Share</td><td>Std. Dev.</td></tr><tr><td>(1)</td><td>(2)</td></tr></thead><tbody valign="top"><tr><td>Child characteristics</td></tr><tr><td> Age (months)</td><td char=".">21.48</td><td char=".">1.64</td></tr><tr><td> Gender (1 = boy)</td><td char=".">0.58</td><td char=".">0.49</td></tr><tr><td>Household characteristics</td></tr><tr><td> Mother's age (years)</td><td char=".">28.34</td><td char=".">4.53</td></tr><tr><td> Mother's education level (1 = completed college or above)</td><td char=".">0.15</td><td char=".">0.36</td></tr><tr><td> Mother has a job (1 = yes)</td><td char=".">0.62</td><td char=".">0.49</td></tr><tr><td> Number of siblings in the household</td><td char=".">0.24</td><td char=".">0.44</td></tr><tr><td> Asset index (PCA score)</td><td char=".">0.00</td><td char=".">1.35</td></tr><tr><td> Number of adults in the household</td><td char=".">2.75</td><td char=".">1.09</td></tr><tr><td> Mother is the primary caregiver (1 = yes)</td><td char=".">0.53</td><td char=".">0.50</td></tr><tr><td> Mother has urban hukou (1 = yes)</td><td char=".">0.17</td><td char=".">0.38</td></tr></tbody></table> </ephtml> </p> <hd id="AN0180230223-8">Data collection</hd> <p>Data from the rural and peri-urban communities were collected in the summer and fall of 2020 by trained survey enumerators following a standardized four-day data collection protocol. After introducing the study and providing time for caregivers to ask questions, trained enumerators obtained oral consent from all caregivers of sample children, using a script in Mandarin Chinese. All participants understood that their recordings would be collected and used for the purpose of this study.</p> <p>On the first day, enumerators surveyed the sample child's primary caregiver at their home or the hospital, collecting data on ECD outcomes using the Caregiver Reported Early Development Instrument (CREDI) and the Mandarin version of the MacArthur Bates Communicative Developmental Inventory (CDI), and demographic characteristics using a separate survey. After the surveys concluded, enumerators instructed the caregiver on how to use the LENA recording device. On the second and third days, caregivers used the LENA device to record the home language environment. On the fourth day, enumerators retrieved the LENA recorders and conducted exit interviews with the families to ensure compliance with the LENA recording process. This study received ethical approval from the Stanford University Institutional Review Board (IRB Protocol 49552).</p> <hd id="AN0180230223-9">Measuring the home language environment</hd> <p>To implement the LENA data collection in this study, each child's primary caregiver was given a fully charged LENA recorder, a specialized LENA shirt, and a LENA charger. Caregivers were instructed to record two 16-hour-long days that were representative of the child's typical at-home experiences. Following LENA validation protocols (Zhang et al., [<reflink idref="bib89" id="ref99">89</reflink>]), the recorder was placed in the chest pocket of the specialized shirt that the child wore throughout the day. Caregivers were instructed to remove the LENA recorder and LENA-specialized shirt only when their child was bathed or slept at night. Caregivers were also instructed to charge the LENA recorder between the first and second days of recording. Each 16-hour-long LENA recording was standardized into a 12-hour-long recording to account for variation in recording start times across households and to adjust for skewing commonly seen with count data.</p> <p>The recordings were analyzed using LENA software to produce two standardized, quantitative measures of the home language environment: adult word count or AWC (total number of adult words the child heard) and conversational turns count or CTC (the number of alternations in conversation between the child and adult). Distributions of AWC and CTC over the duration of a day, averaged across households, were calculated (see Supplementary Appendix Figure 1). Using the LENA Advanced Data Extractor (ADEX), recordings could be further broken into vocalization activity blocks (VABs) that include conversations between the focus child and an adult (male or female) (Cunha et al., [<reflink idref="bib10" id="ref100">10</reflink>]). We generated the number of VABs initiated by the initiator (child, female adult, or male adult) and the number of conversational turns (CT) within VABs, categorized by who initiated the CT (child, female adult, or male adult).</p> <p>Graph: Figure 1. The distribution of home language environment measures (N = 158). (A) Adult word count. (B) Conversational turn count. (C) Conversational turns in VABs initiated by the focus child. (D) Conversational turns in VABs initiated by a female adult. (E) Conversational turns in VABs initiated by a male adult. (F) Number of VABs initiated by the focus child. (G) Number of VABs initiated by a female adult (N = 158). (H) Number of VABs initiated by a male adult.</p> <p>The LENA system has been validated across different languages and linguistic contexts when compared with trained human transcribers (Ganek & Eriks-Brophy, [<reflink idref="bib22" id="ref101">22</reflink>], [<reflink idref="bib21" id="ref102">21</reflink>]; Gilkerson et al., [<reflink idref="bib27" id="ref103">27</reflink>]; Pae et al., [<reflink idref="bib57" id="ref104">57</reflink>]), including in Mandarin Chinese (Ma et al., [<reflink idref="bib50" id="ref105">50</reflink>]; Gilkerson et al., [<reflink idref="bib27" id="ref106">27</reflink>]; Zhang et al., [<reflink idref="bib89" id="ref107">89</reflink>]). Gilkerson et al. ([<reflink idref="bib27" id="ref108">27</reflink>]) reported strong correlations between AWC and human annotations of adult words (<emph>r</emph> = 0.73) but weaker correlations between CTC and human annotations of conversations.</p> <hd id="AN0180230223-10">Measuring ECD</hd> <p>The CREDI was used to measure language, cognitive, social-emotional, motor, and overall ECD outcomes. The CREDI was designed to serve as a population-level measure of ECD for children aged 0–3 years (Li et al., [<reflink idref="bib45" id="ref109">45</reflink>]; McCoy et al., [<reflink idref="bib52" id="ref110">52</reflink>]). The survey was completed by a primary caregiver who answered ECD-related questions about their child with "yes" or "no" answers (if caregivers were unsure of their response, they could choose to respond with "don't know"). The CREDI long-form test was used in this study and consists of a total of 108 items, with the starting point determined by the participating child's age, and the ending point determined by a five-link error/uncertainty factor. The CREDI long form produces an overall developmental z-score (CREDI overall score), as well as z-scores for each developmental domain (CREDI cognitive, CREDI language, CREDI motor, and CREDI social-emotional scores) which are constructed by comparing the raw score in each domain to the average raw score in our CREDI reference population of a particular age. A z-score of "0" means that the child has the same score on that particular domain as the average same-age child in the CREDI reference population. A z-score of "−1" means that the child's raw score is 1 standard deviation (<emph>SD</emph>) below the same-age average of the reference population. According to the work of Russell et al. ([<reflink idref="bib64" id="ref111">64</reflink>]), 1 <emph>SD</emph> or more below the global reference population mean (CREDI z-score < −1 <emph>SD</emph>) is defined as being at risk of developmental delay. The accuracy, reliability, and validity of the CREDI have been proven in Western and non-Western LMICs and high-income countries, including China (Li et al., [<reflink idref="bib45" id="ref112">45</reflink>]; McCoy et al., [<reflink idref="bib52" id="ref113">52</reflink>]).</p> <p>Second, our team administered the Mandarin version of the CDI expressive vocabulary assessment (a list of 113 words) for children between 16 and 30 months to measure child language skills. The child's primary caregiver was asked whether their child could say each word on the list, with each word counting for one point. By comparing the parent-reported results with empirically determined cutoff scores established by Tardif et al. ([<reflink idref="bib73" id="ref114">73</reflink>]), the status of a child's vocabulary developmental progress was determined. Rates of delay were established for each age group using group cutoff scores from Tardif et al. ([<reflink idref="bib73" id="ref115">73</reflink>]) (any child under the 10th percentile of language development in their one-month age group was considered delayed) and then combined to produce a full sample cutoff for delay. The CDI has been adapted to and validated in Mandarin Chinese (Fenson et al., [<reflink idref="bib18" id="ref116">18</reflink>]; Tardif et al., [<reflink idref="bib73" id="ref117">73</reflink>]) and proven reliable in studying early language development in China (Ma et al., [<reflink idref="bib49" id="ref118">49</reflink>]; Zhang et al., [<reflink idref="bib89" id="ref119">89</reflink>]).</p> <hd id="AN0180230223-11">Demographic characteristics</hd> <p>The last survey data collected were child and household demographic characteristics (Table 1). Child characteristics included the child's age (months) and gender. Household characteristics consisted of the mother's highest level of educational attainment, the age of the mother, whether the mother has a job, the number of siblings in the household, the number of adults in the household, whether the mother is the primary caregiver, and whether the mother has urban hukou and a family asset index. We established and used a family asset index using polychoric principal components analysis (PCA) based on whether a family owned or had access to running water, a flush toilet, a water heater, a washing machine, a computer, Internet, a refrigerator, an air conditioner, a motorbike/motorcycle, and a car/truck (Kolenikov & Angeles, [<reflink idref="bib39" id="ref120">39</reflink>]).</p> <hd id="AN0180230223-12">Statistical analysis</hd> <p>Our statistical analysis consists of three components. First, to describe the home language environment and ECD outcomes, we perform a graphical descriptive analysis of LENA, CREDI, and CDI measures. For LENA, CREDI, and CDI distributions, we describe the mean, standard deviation (<emph>SD</emph>), and range of each of the key variables. Second, to examine the demographic characteristics associated with the home language environment, we conduct multivariate multiple linear regressions between demographic characteristics and LENA measures. Third, to examine the correlations between the home language environment measures and ECD outcomes, we perform multivariate multiple linear regressions between LENA and CREDI, and LENA and CDI. For the multivariate multiple linear regression analyses, we include the child's age, child's gender, mother's age, mother's highest level of educational attainment (measured as a binary variable with the variable equaling 1 if the mother completed an associate degree or above), mother's employment status (measured as a binary variable with the variable equaling 1 if the mother was employed at the time of the survey), the total number of siblings in the household, the family asset index PCA score, the number of adults in the household, whether the mother is the primary caregiver (measured as a binary variable with the variable equaling 1 if the mother was the primary caregiver), and whether the mother has urban <emph>hukou</emph> (measured as a binary variable with the variable equaling 1 if the mother had urban <emph>hukou</emph>) as potential confounders.</p> <p>According to previous studies (Wooldridge, [<reflink idref="bib81" id="ref121">81</reflink>]), taking logs usually narrows the range of the variable, in some cases by a considerable amount. For ease of interpretation, we employ a log scale for each home language environment outcome in our regression analysis. We used STATA 16.1 to perform all statistical analyses, and <emph>p</emph>-values at or below 0.05 were considered statistically significant.</p> <hd id="AN0180230223-13">Results</hd> <p></p> <hd id="AN0180230223-14">Describing the home language environment</hd> <p>Figures 1(A,B) display the distributions of AWC and CTC, respectively. The mean AWC of the sample was 14,025 words (<emph>SD</emph> = 4173), and there was a 2.6-fold difference between the third quartile (AWC = 20,540) and the first quartile (AWC = 8032) (<emph>p</emph> < 0.001). For CTC, the mean score was 566 (<emph>SD</emph> = 292), and there was a 3.3-fold difference between the third quartile (CTC = 897) and the first quartile (CTC = 273) (<emph>p</emph> < 0.001).</p> <p>Figures 1(C–E) illustrate the distributions of CTs within VABs initiated by the focus child, female adult, and male adult, respectively. The mean score for CT in VABs initiated by the focus child was 272 (<emph>SD</emph> = 154), with a 3.5-fold difference between the third quartile (<reflink idref="bib447" id="ref122">447</reflink>) and the first quartile (<reflink idref="bib129" id="ref123">129</reflink>) (<emph>p</emph> < 0.001). The mean score for CT in VABs initiated by a female adult was 234 (<emph>SD</emph> = 133), with a 3.6-fold difference between the third quartile (<reflink idref="bib382" id="ref124">382</reflink>) and the first quartile (<reflink idref="bib106" id="ref125">106</reflink>) (<emph>p</emph> < 0.001). Additionally, the mean CT in VABs initiated by female adults was significantly higher than the CT in VABs initiated by a male adult (<emph>p</emph> < 0.001). The mean score for CT in VABs initiated by a male adult was 53 (<emph>SD</emph> = 49), and there was an 8.2-fold difference between the third quartile (<reflink idref="bib106" id="ref126">106</reflink>) and the first quartile (<reflink idref="bib13" id="ref127">13</reflink>) (<emph>p</emph> < 0.001).</p> <p>Figures 1(F–H) depict the distributions of the number of VABs initiated by the focus child, female adult, and male adult, respectively. The mean score for the number of VABs initiated by the focus child was 430 (<emph>SD</emph> = 126), with a 1.9-fold difference between the third quartile (<reflink idref="bib562" id="ref128">562</reflink>) and the first quartile (<reflink idref="bib296" id="ref129">296</reflink>) (<emph>p</emph> < 0.001). Concerning the number of VABs initiated by a female adult, the mean score was 370 (<emph>SD</emph> = 114), which is significantly higher than the number of VABs initiated by a male adult (<emph>p</emph> < 0.001). Moreover, there was a 2-fold difference between the third quartile (<reflink idref="bib494" id="ref130">494</reflink>) and the first quartile (<reflink idref="bib247" id="ref131">247</reflink>) of the number of VABs initiated by a female adult. Lastly, the mean score for the number of VABs initiated by a male adult was 119 (<emph>SD</emph> = 89), and there was a 6.1-fold difference between the number of VABs in the third quartile (<reflink idref="bib225" id="ref132">225</reflink>) and the first quartile (<reflink idref="bib37" id="ref133">37</reflink>) (<emph>p</emph> < 0.001).</p> <hd id="AN0180230223-15">Describing ECD outcomes</hd> <p>Figure 2 presents the distribution of CREDI outcomes. The results show significant variation in CREDI outcomes among the sample children, with 4.5-, 23.8-, 1.8-, 3.9-, and 4.4-fold differences (<emph>p</emph> < 0.001) for the motor, cognitive, language, and social-emotional domains, and the overall CREDI z-score, respectively, between the participant scores in the second quartile and third quartile. The average z-score for the motor domain was 0.35 (<emph>SD</emph> = 0.98), and 8.9% of children were at risk of motor developmental delay. For the CREDI cognitive domain, the average z-score was 0.06 (<emph>SD</emph> = 0.94), and 12% of children were at risk of cognitive developmental delay. The average z-scores for the language and social-emotional domains were 0.46 (<emph>SD</emph> = 1.20) and 0.28 (<emph>SD</emph> = 0.90), respectively. Moreover, the proportions of children at risk of social-emotional or language developmental delays were 8.2 and 14.6%, respectively. Finally, the average z-score for CREDI Overall was 0.31 (<emph>SD</emph> = 0.92), and only 5% of children were at risk of overall developmental delay.</p> <p>PHOTO (COLOR): Figure 2. Distribution of Caregiver Reported Early Development Instrument outcomes (N = 158).</p> <p>Figure 3 presents the distribution of CDI scores, with children in the sample scoring on average 45 (<emph>SD</emph> = 29). The results also show significant variation in CDI scores with a 5.7-fold (<emph>p</emph> < 0.001) difference between the first quartile (CDI = 14) and the third quartile (CDI = 80). Additionally, 22.15% of children were below the Mandarin CDI cutoff scores for typical language development across age ranges.</p> <p>Graph: Figure 3. Distribution of Mac-Arthur Bates Communicative Developmental Inventory scores (N = 158).</p> <hd id="AN0180230223-16">The home language environment and household characteristics</hd> <p>Table 2 presents the results from multivariate multiple linear regression between the home language environment and household characteristics. Older children tended to have higher CTC (<emph>p</emph> < 0.01) and CT in VABs initiated by the focus child (<emph>p</emph> < 0.01), but lower numbers of VABs initiated by a female adult (<emph>p</emph> < 0.05). Children of employed mothers had higher AWC (<emph>p</emph> < 0.05), CTC (<emph>p</emph> < 0.05), and CT in VABs initiated by both the focus child (<emph>p</emph> < 0.01) and a female adult (<emph>p</emph> < 0.05). Moreover, children who had fewer siblings reported higher CT in VABs initiated by a male adult (<emph>p</emph> < 0.05).</p> <p>Table 2. Multivariate multiple linear regressions between home language environment measures and household characteristics.</p> <p> <ephtml> <table><thead><tr><td>Variables</td><td>lnAWC</td><td>lnCTC</td><td>ln(CT in VABs initiated by the focus child)</td><td>ln(CT in VABs initiated by a female adult)</td><td>ln(CT in VABs initiated by a male adult)</td><td>ln(Number of VABs initiated by the focus child)</td><td>ln(Number of VABs initiated by a female adult)</td><td>ln(Number of VABs initiated by a male adult)</td></tr><tr><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td><td>(8)</td></tr></thead><tbody valign="top"><tr><td>(1)</td><td>Child's age (months)</td><td char=".">0.03</td><td char=".">0.07<xref ref-type="table-fn" rid="tfn4">**</xref></td><td char=".">0.08<xref ref-type="table-fn" rid="tfn4">**</xref></td><td char=".">0.04</td><td char=".">0.04</td><td char=".">0.02</td><td char=".">−0.04*</td><td char=".">−0.03</td></tr><tr><td /><td /><td char=".">(0.02)</td><td char=".">(0.03)</td><td char=".">(0.03)</td><td char=".">(0.03)</td><td char=".">(0.05)</td><td char=".">(0.02)</td><td char=".">(0.02)</td><td char=".">(0.04)</td></tr><tr><td>(2)</td><td>Child's gender (1 = boy)</td><td char=".">−0.03</td><td char=".">−0.10</td><td char=".">−0.06</td><td char=".">−0.11</td><td char=".">−0.07</td><td char=".">0.03</td><td char=".">−0.04</td><td char=".">−0.07</td></tr><tr><td /><td /><td char=".">(0.08)</td><td char=".">(0.09)</td><td char=".">(0.10)</td><td char=".">(0.10)</td><td char=".">(0.17)</td><td char=".">(0.06)</td><td char=".">(0.06)</td><td char=".">(0.14)</td></tr><tr><td>(3)</td><td>Mother's age (years)</td><td char=".">0.01</td><td char=".">0.00</td><td char=".">0.01</td><td char=".">0.01</td><td char=".">0.03</td><td char=".">0.00</td><td char=".">0.00</td><td char=".">0.03</td></tr><tr><td /><td /><td char=".">(0.01)</td><td char=".">(0.01)</td><td char=".">(0.01)</td><td char=".">(0.01)</td><td char=".">(0.02)</td><td char=".">(0.01)</td><td char=".">(0.01)</td><td char=".">(0.02)</td></tr><tr><td>(4)</td><td>Mother's education level (1 = completed college or above)</td><td char=".">−0.00</td><td char=".">0.05</td><td char=".">0.03</td><td char=".">−0.06</td><td char=".">0.26</td><td char=".">0.02</td><td char=".">−0.15</td><td char=".">0.28</td></tr><tr><td /><td /><td char=".">(0.10)</td><td char=".">(0.12)</td><td char=".">(0.13)</td><td char=".">(0.14)</td><td char=".">(0.23)</td><td char=".">(0.08)</td><td char=".">(0.08)</td><td char=".">(0.19)</td></tr><tr><td>(5)</td><td>Mother has a job (1 = yes)</td><td char=".">0.17*</td><td char=".">0.18</td><td char=".">0.26*</td><td char=".">0.23</td><td char=".">0.28</td><td char=".">0.11</td><td char=".">0.13</td><td char=".">0.17</td></tr><tr><td /><td /><td char=".">(0.10)</td><td char=".">(0.12)</td><td char=".">(0.12)</td><td char=".">(0.13)</td><td char=".">(0.22)</td><td char=".">(0.08)</td><td char=".">(0.07)</td><td char=".">(0.18)</td></tr><tr><td>(6)</td><td>Number of siblings in the household</td><td char=".">−0.10</td><td char=".">−0.17</td><td char=".">−0.17</td><td char=".">−0.12</td><td char=".">−0.44*</td><td char=".">−0.06</td><td char=".">−0.08</td><td char=".">−0.21</td></tr><tr><td /><td /><td char=".">(0.08)</td><td char=".">(0.10)</td><td char=".">(0.11)</td><td char=".">(0.11)</td><td char=".">(0.19)</td><td char=".">(0.07)</td><td char=".">(0.06)</td><td char=".">(0.16)</td></tr><tr><td>(7)</td><td>Asset index (PCA score)</td><td char=".">−0.03</td><td char=".">−0.03</td><td char=".">−0.02</td><td char=".">−0.00</td><td char=".">−0.01</td><td char=".">−0.01</td><td char=".">−0.02</td><td char=".">−0.01</td></tr><tr><td /><td /><td char=".">(0.03)</td><td char=".">(0.04)</td><td char=".">(0.04)</td><td char=".">(0.04)</td><td char=".">(0.07)</td><td char=".">(0.02)</td><td char=".">(0.02)</td><td char=".">(0.05)</td></tr><tr><td>(8)</td><td>Number of adults in the household</td><td char=".">−0.02</td><td char=".">−0.04</td><td char=".">−0.03</td><td char=".">−0.02</td><td char=".">−0.05</td><td char=".">0.04</td><td char=".">0.02</td><td char=".">−0.03</td></tr><tr><td /><td /><td char=".">(0.03)</td><td char=".">(0.04)</td><td char=".">(0.04)</td><td char=".">(0.05)</td><td char=".">(0.08)</td><td char=".">(0.03)</td><td char=".">(0.03)</td><td char=".">(0.06)</td></tr><tr><td>(9)</td><td>Mother is the primary caregiver (1 = yes)</td><td char=".">0.02</td><td char=".">−0.01</td><td char=".">0.01</td><td char=".">−0.03</td><td char=".">−0.01</td><td char=".">0.09</td><td char=".">0.05</td><td char=".">0.09</td></tr><tr><td /><td /><td char=".">(0.10)</td><td char=".">(0.12)</td><td char=".">(0.12)</td><td char=".">(0.13)</td><td char=".">(0.22)</td><td char=".">(0.07)</td><td char=".">(0.07)</td><td char=".">(0.18)</td></tr><tr><td>(10)</td><td>Mother has urban hukou (1 = yes)</td><td char=".">−0.06</td><td char=".">−0.05</td><td char=".">−0.12</td><td char=".">−0.10</td><td char=".">−0.23</td><td char=".">−0.12</td><td char=".">−0.01</td><td char=".">−0.11</td></tr><tr><td /><td /><td char=".">(0.10)</td><td char=".">(0.12)</td><td char=".">(0.13)</td><td char=".">(0.14)</td><td char=".">(0.23)</td><td char=".">(0.08)</td><td char=".">(0.08)</td><td char=".">(0.19)</td></tr><tr><td>(11)</td><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(12)</td><td>R-squared</td><td char=".">0.07</td><td char=".">0.12</td><td char=".">0.13</td><td char=".">0.08</td><td char=".">0.08</td><td char=".">0.05</td><td char=".">0.09</td><td char=".">0.06</td></tr></tbody></table> </ephtml> </p> <p>1 AWC: adult word count; CTC: conversational turn count; CT: conversational turn; VAB: vocalization activity block.</p> <ulist> <item>2 <emph>Note.</emph> Standard errors in parentheses.</item> <item>3 Source: Author's survey.</item> <item>4 **<emph>p</emph> < 0.01, *<emph>p</emph> < 0.05. One unit increase of [controls factor] is associated with 100*beta percent change in home language environment outcomes.</item> </ulist> <hd id="AN0180230223-17">The home language environment and ECD outcomes</hd> <p>Table 3 presents the results of the multivariate multiple linear regression examining the relationship between the home language environment measures and ECD outcomes. As depicted in Panel A, higher CTC was associated with higher CREDI overall z-scores. Specifically, a 1% increase in CTC corresponded to a 0.0039 <emph>SD</emph>[<reflink idref="bib1" id="ref134">1</reflink>] increase in CREDI overall scores, even after controlling for household characteristics (<emph>p</emph> < 0.01).</p> <p>Table 3. Multivariate multiple linear regressions between the home language environment measures and child development outcomes.</p> <p> <ephtml> <table><thead><tr><td>(A)</td></tr><tr><td>Variables</td><td>CREDI overall</td><td>CREDI motor</td><td>CREDI cognitive</td></tr><tr><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td><td>(8)</td><td>(9)</td><td>(10)</td><td>(11)</td><td>(12)</td></tr></thead><tbody valign="top"><tr><td>(1)</td><td>lnAWC</td><td>0.22</td><td>0.27</td><td /><td /><td>−0.01</td><td>0.06</td><td /><td /><td>−0.03</td><td>−0.02</td><td /><td /></tr><tr><td /><td /><td>(0.17)</td><td>(0.17)</td><td /><td /><td>(0.18)</td><td>(0.18)</td><td /><td /><td>(0.17)</td><td>(0.17)</td><td /><td /></tr><tr><td>(2)</td><td>lnCTC</td><td /><td /><td>0.34*</td><td>0.39<xref ref-type="table-fn" rid="tfn8">**</xref></td><td /><td /><td>0.09</td><td>0.18</td><td /><td /><td>0.13</td><td>0.14</td></tr><tr><td /><td /><td /><td /><td>(0.13)</td><td>(0.14)</td><td /><td /><td>(0.14)</td><td>(0.15)</td><td /><td /><td>(0.14)</td><td>(0.14)</td></tr><tr><td>(3)</td><td>Controls</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td></tr><tr><td>(4)</td><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(5)</td><td><italic>R</italic>-squared</td><td>0.01</td><td>0.13</td><td>0.04</td><td>0.17</td><td>0.00</td><td>0.11</td><td>0.00</td><td>0.12</td><td>0.00</td><td>0.11</td><td>0.01</td><td>0.12</td></tr></tbody></table> </ephtml> </p> <p> <ephtml> <table><thead><tr><td>(B)</td></tr><tr><td>Variables</td><td>CREDI language</td><td>CREDI social-emotional</td><td>CDI</td></tr><tr><td>(13)</td><td>(14)</td><td>(15)</td><td>(16)</td><td>(17)</td><td>(18)</td><td>(19)</td><td>(20)</td><td>(21)</td><td>(22)</td><td>(23)</td><td>(24)</td></tr></thead><tbody valign="top"><tr><td>(1)</td><td>lnAWC</td><td>0.54*</td><td>0.61<xref ref-type="table-fn" rid="tfn8">**</xref></td><td /><td /><td>−0.05</td><td>−0.03</td><td /><td /><td>21.31<xref ref-type="table-fn" rid="tfn8">**</xref></td><td>19.37<xref ref-type="table-fn" rid="tfn8">**</xref></td><td /><td /></tr><tr><td /><td /><td>(0.21)</td><td>(0.21)</td><td /><td /><td>(0.16)</td><td>(0.17)</td><td /><td /><td>(4.97)</td><td>(4.44)</td><td /><td /></tr><tr><td>(2)</td><td>lnCTC</td><td /><td /><td>0.64<xref ref-type="table-fn" rid="tfn8">**</xref></td><td>0.70<xref ref-type="table-fn" rid="tfn8">**</xref></td><td /><td /><td>0.11</td><td>0.14</td><td /><td /><td>22.36<xref ref-type="table-fn" rid="tfn8">**</xref></td><td>18.63<xref ref-type="table-fn" rid="tfn8">**</xref></td></tr><tr><td /><td /><td /><td /><td>(0.17)</td><td>(0.17)</td><td /><td /><td>(0.13)</td><td>(0.14)</td><td /><td /><td>(3.83)</td><td>(3.58)</td></tr><tr><td>(3)</td><td>Controls</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td><td>No</td><td>Yes</td></tr><tr><td>(4)</td><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(5)</td><td>R-squared</td><td>0.04</td><td>0.16</td><td>0.09</td><td>0.20</td><td>0.00</td><td>0.12</td><td>0.00</td><td>0.13</td><td>0.11</td><td>0.38</td><td>0.18</td><td>0.41</td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 AWC: adult word count; CTC: conversational turn count; CREDI: Caregiver Reported Early Development Instrument; CDI: Mac-Arthur Bates Communicative Developmental Inventory.</item> <item>6 <emph>Note.</emph> Standard errors in parentheses.</item> <item>7 Source: Author's survey.</item> <item>8 **<emph>p</emph> < 0.01, *<emph>p</emph> < 0.05. One percent increase of [home language environment outcomes] is associated with beta/100 <emph>SD</emph> or (beta/mean value) % change in outcome variable.</item> </ulist> <p>Moving to Panel B, we observed that children with higher AWC scores also achieved higher CREDI language z-scores and CDI scores. For every 1% increase in AWC, there was a corresponding 0.0061 <emph>SD</emph>[<reflink idref="bib2" id="ref135">2</reflink>] increase in CREDI language z-scores and a 0.1937 increase in CDI scores, both statistically significant after controlling for household characteristics (<emph>p</emph> < 0.01). Moreover, an increase of 1% in CTC correlated with a 0.0070 <emph>SD</emph>[<reflink idref="bib3" id="ref136">3</reflink>] increase in CREDI language z-scores (<emph>p</emph> < 0.01) and a 0.1863 increase in CDI scores (<emph>p</emph> < 0.01), even after accounting for household characteristics. However, neither AWC nor CTC significantly influenced CREDI cognitive, motor, or social-emotional z-scores.</p> <p>Table 4 presents the results from our multiple linear regression model for the initiation of VABs and CREDI outcomes. In Panel A, the data show that children who initiated more CT in VABs had higher CREDI language, CREDI overall z-scores, and CDI scores (<emph>p</emph> < 0.01). Specifically, a 1% increase in the number of CT in VABs initiated by the focus child corresponded to a 0.0036 <emph>SD</emph>[<reflink idref="bib4" id="ref137">4</reflink>] increase in CREDI overall z-scores, a 0.0063 <emph>SD</emph>[<reflink idref="bib5" id="ref138">5</reflink>] increase in CREDI language z-scores, and a 0.1619-point increase in CDI scores.</p> <p>Table 4. Multivariate multiple linear regressions between child development outcomes and initiation of VABs with focus child and an adult.</p> <p> <ephtml> <table><thead><tr><td /><td>Motor</td><td>Cognitive</td><td>Language</td><td>Social emotional</td><td>Overall</td><td>CDI</td></tr></thead><tbody valign="top"><tr><td>(A) Multivariate multiple linear regression between CREDI and CDI outcomes, and CTs in VABs initiated by the focus child</td></tr><tr><td>ln (CT in VABs initiated by the focus child)</td><td>0.17</td><td>0.12</td><td>0.63<xref ref-type="table-fn" rid="tfn12">**</xref></td><td>0.15</td><td>0.36<xref ref-type="table-fn" rid="tfn12">**</xref></td><td>16.19<xref ref-type="table-fn" rid="tfn12">**</xref></td></tr><tr><td /><td>(0.14)</td><td>(0.14)</td><td>(0.17)</td><td>(0.13)</td><td>(0.13)</td><td>(3.47)</td></tr><tr><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(B) Multivariate multiple linear regression between CREDI and CDI outcomes, and CTs in VABs initiated by a female adult</td></tr><tr><td>ln (CT in VABs initiated by a female adult)</td><td>0.16</td><td>0.11</td><td>0.64<xref ref-type="table-fn" rid="tfn12">**</xref></td><td>0.12</td><td>0.35<xref ref-type="table-fn" rid="tfn12">**</xref></td><td>16.75<xref ref-type="table-fn" rid="tfn12">**</xref></td></tr><tr><td /><td>(0.13)</td><td>(0.13)</td><td>(0.15)</td><td>(0.12)</td><td>(0.12)</td><td>(3.20)</td></tr><tr><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(C) Multivariate multiple linear regression between CREDI and CDI outcomes, and CTs in VABs initiated by a male adult</td></tr><tr><td>ln (CT in VABs initiated by a male adult)</td><td>−0.05</td><td>−0.04</td><td>−0.03</td><td>−0.01</td><td>−0.03</td><td>1.16</td></tr><tr><td /><td>(0.08)</td><td>(0.08)</td><td>(0.10)</td><td>(0.07)</td><td>(0.07)</td><td>(2.07)</td></tr><tr><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(D) Multivariate multiple linear regression between CREDI and CDI outcomes, and number of VABs initiated by the focus child</td></tr><tr><td>ln (Number of VABs initiated by the focus child)</td><td>0.13</td><td>0.07</td><td>0.36</td><td>0.20</td><td>0.23</td><td>6.76</td></tr><tr><td /><td>(0.23)</td><td>(0.22)</td><td>(0.28)</td><td>(0.21)</td><td>(0.22)</td><td>(5.99)</td></tr><tr><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(E) Multivariate multiple linear regression between CREDI and CDI outcomes, and number of VABs initiated by a female adult</td></tr><tr><td>ln (Number of VABs initiated by a female adult)</td><td>0.02</td><td>−0.14</td><td>0.62*</td><td>−0.08</td><td>0.21</td><td>16.98<xref ref-type="table-fn" rid="tfn12">**</xref></td></tr><tr><td /><td>(0.24)</td><td>(0.23)</td><td>(0.28)</td><td>(0.22)</td><td>(0.22)</td><td>(6.02)</td></tr><tr><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr><tr><td>(F) Multivariate multiple linear regression between CREDI and CDI outcomes, and number of VABs initiated by a male adult</td></tr><tr><td>ln (Number of VABs initiated by a male adult)</td><td>−0.08</td><td>−0.11</td><td>−0.25*</td><td>−0.09</td><td>−0.16</td><td>−3.80</td></tr><tr><td /><td>(0.10)</td><td>(0.09)</td><td>(0.12)</td><td>(0.09)</td><td>(0.09)</td><td>(2.51)</td></tr><tr><td>Observations</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td><td>158</td></tr></tbody></table> </ephtml> </p> <ulist> <item>9 CREDI: Caregiver Reported Early Development Instrument; CDI: Mac-Arthur Bates Communicative Developmental Inventory; CT: conversational turn; VAB: vocalization activity block.</item> <item>10 <emph>Notes.</emph> Standard errors in parentheses. We control the variables about child characteristics and household; All regressions are controlled with all of the household characteristics in above regression.</item> <item>11 Source: Author's survey.</item> <item>12 **<emph>p</emph> < 0.01, *<emph>p</emph> < 0.05. One percent increase of [home language environment outcomes] is associated with beta/100 <emph>SD</emph> or (beta/mean value) % change in outcome variable.</item> </ulist> <p>In Panel B, children who lived in houses with more CT in VABs initiated by a female adult also achieved higher CREDI language, CREDI overall z-scores, and CDI scores (<emph>p</emph> < 0.01). Specifically, a 1% increase in the number of CT was associated with a 0.0035 <emph>SD</emph>[<reflink idref="bib6" id="ref139">6</reflink>] increase in CREDI overall z-scores, a 0.0064 <emph>SD</emph>[<reflink idref="bib7" id="ref140">7</reflink>] increase in CREDI language z-scores, and a 0.1675-point increase in CDI scores.</p> <p>In contrast, Panel C shows that the number of CT in VABs initiated by a male adult did not significantly affect CREDI z-scores and CDI outcomes. Similarly, Panel D demonstrates that the number of VABs initiated by the focus child did not significantly impact CREDI or CDI. However, Panel E reveals that a 1% increase in the number of VABs initiated by a female adult corresponded to a 0.0062 <emph>SD</emph>[<reflink idref="bib8" id="ref141">8</reflink>] increase in CREDI language z-scores and a 0.1698-point increase in CDI scores. Finally, we found that children's CREDI language z-scores decreased when VABs initiated by a male adult were more prevalent (Panel F).</p> <hd id="AN0180230223-18">Discussion</hd> <p>In this study, we investigated the associations between the home language environment and ECD outcomes among 158 rural and peri-urban households with children aged 18–24 months in Western China. First, the results demonstrated that large variations in the home language environment and ECD outcomes existed in both rural and peri-urban households, though the risk of developmental delay was similar to children from other low-resource samples. Second, we found several statistically significant associations between household characteristics and the home language environment, including a mother's employment status and a child's age. Third, the results showed a positive association between the home language environment and language development, as well as overall ECD outcomes. Thus, the home language environment in households with young children in rural and peri-urban China may be a key mechanism for improving and supporting early language development.</p> <hd id="AN0180230223-19">Describing the home language environment in the context of rural and peri-urban China</hd> <p>Although families living in peri-urban China typically have higher levels of income and education than those in rural areas (Shi et al., [<reflink idref="bib66" id="ref142">66</reflink>]; Sun et al., [<reflink idref="bib71" id="ref143">71</reflink>]), both rural and peri-urban households are usually considered low-resourced in comparison to their urban counterparts (He & Wang, [<reflink idref="bib30" id="ref144">30</reflink>]; Zhan, [<reflink idref="bib88" id="ref145">88</reflink>]). Evidence suggests that factors such as a lack of resources, lower income, and lower levels of educational attainment may lead to lower-quality home language environments (Gilkerson et al., [<reflink idref="bib25" id="ref146">25</reflink>]). Besides socioeconomic factors, the physical structure and layout of homes may also play a role in understanding interactions within peri-urban and rural settings. For instance, migrants in China often reside in two- or three-room houses or apartments in peri-urban neighborhoods, living with extended family members, with the mother or grandmother of the household usually taking care of the children at home or in the community. Due to the higher cost of living in urban areas compared to rural ones, peri-urban households often have more family members working outside the home than rural households (Fan et al., [<reflink idref="bib17" id="ref147">17</reflink>]), resulting in fewer adults at home to engage verbally with the child. On the other hand, in rural households, families typically live in houses with small courtyards and two or three rooms, and rural caregivers (mothers and grandmothers) spend most of their time taking care of children at their own home or a neighbor's house. However, research indicates that in rural China, most caregivers do not regularly engage in interactive parenting practices that encourage early language development, such as storytelling, reading, or using toys to play with children (Luo et al., [<reflink idref="bib48" id="ref148">48</reflink>]; Yue et al., [<reflink idref="bib86" id="ref149">86</reflink>]). These variations in cultural practices and parenting beliefs between rural and urban communities may influence interactions in practice. Therefore, understanding the unique environments of peri-urban and rural households can provide insights into the types and frequency of interactions with children at home.</p> <p>In our sample, despite relatively similar household characteristics, there was substantial variation across all measures of the home language environment in rural and peri-urban households, consistent with other studies examining low-resource communities (Ma et al., [<reflink idref="bib49" id="ref150">49</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref151">80</reflink>]). While some households demonstrated highly interactive home environments, most reported less adult talk and fewer conversations compared to high-resource and low-resource communities (e.g. Weber et al., [<reflink idref="bib79" id="ref152">79</reflink>]; Pae et al., [<reflink idref="bib57" id="ref153">57</reflink>]; Suskind et al., [<reflink idref="bib72" id="ref154">72</reflink>]; Zhang et al., [<reflink idref="bib89" id="ref155">89</reflink>]). Moreover, our findings on the difference between CT in VABs and the number of VABs initiated by female and male adults replicate previous findings in high-resource households, suggesting that female caregivers speak more in the home, regardless of resources (Davidson & Snow, [<reflink idref="bib13" id="ref156">13</reflink>]). This may be due to different interactional, familial, and cultural contexts between male and female caregivers. For instance, Yeung et al. ([<reflink idref="bib83" id="ref157">83</reflink>]) suggests that male caregivers interact with their children through more physical play, while female caregivers engage in more conversations. However, Strom et al. ([<reflink idref="bib70" id="ref158">70</reflink>]) found that fathers in China enjoy playing with their children and discussing feelings and ideas. Additionally, fathers have been shown to be more animated and provocative in response to stages of development in the infant's awareness, while mothers respond with attentive engagement in response to the infant's interest in intimacy (Kokkinaki, [<reflink idref="bib38" id="ref159">38</reflink>]). In rural China, fathers are typically the "breadwinners" of households, while mothers and other female caregivers (e.g. grandmothers) are in charge of childcare and house chores (Li & Lamb, [<reflink idref="bib44" id="ref160">44</reflink>]; Yeung & Alipio, [<reflink idref="bib82" id="ref161">82</reflink>]), resulting in fathers spending less time with their children than mothers (Liu & Zhao, [<reflink idref="bib46" id="ref162">46</reflink>]), leading to less child-directed interactions (Chi, [<reflink idref="bib7" id="ref163">7</reflink>]). Across China's diverse cultural contexts (i.e. rural and urban), previous studies found that fathers use less total language, less supportive language, less negative language, and more directive and informing language than mothers during parent-child interactions (Chi, [<reflink idref="bib7" id="ref164">7</reflink>]; Li & Fang, [<reflink idref="bib42" id="ref165">42</reflink>]). From our results, we found significant variation between children who engaged in the fewest and most conversations initiated by children, female adults, and male adults. These findings suggest that female caregivers could be integral in increasing measures of the home language environment in rural and peri-urban China. However, the LENA devices alone cannot answer many of these questions, so future research should examine the multi-faceted home environment (including home language environment, physical home environment, and interpersonal home environment) to possibly answer such culturally-confounding research questions.</p> <hd id="AN0180230223-20">Describing ECD outcomes in rural and peri-urban China</hd> <p>There was a large variation in ECD outcomes, particularly in language development. The range of scores in this study was substantially larger than the variation seen in a sample from poor rural China (Ma et al., [<reflink idref="bib49" id="ref166">49</reflink>]). These data support past findings of significant heterogeneity in children's early development outcomes in low-resource communities (Gilkerson et al., [<reflink idref="bib26" id="ref167">26</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref168">80</reflink>]). Similar to a recent study among 17–24 months old children in rural China (Yue et al., [<reflink idref="bib84" id="ref169">84</reflink>]), this study found that 22.15% of children were below the CDI cutoff for proficient language development (Tardif et al., [<reflink idref="bib73" id="ref170">73</reflink>]). This suggests that a portion of children from rural and peri-urban China are at heightened risk of language delay, which can have negative effects on their long-term educational and life outcomes.</p> <p>Comparing the rates of language developmental delays in our sample to similarly aged samples from other LMICs, we found that the rate of language delay was similar. For instance, Chunsuwan et al. ([<reflink idref="bib9" id="ref171">9</reflink>]) examined 90 children aged 18 months in Thailand and reported that expressive language was the most delayed domain (28.9%). Dias et al. ([<reflink idref="bib15" id="ref172">15</reflink>]) reported a language delay rate of 19.16% among 170 children aged between 1 and 2 years in Brazil. In India, Kavitha and Nair ([<reflink idref="bib37" id="ref173">37</reflink>]) found a prevalence of 29.7% for speech and language delay among children aged 13 to 24 months. Thus, rates of delay around 20% seem to be consistent across children from similarly low-resourced settings, suggesting that this is a socioeconomic issue.</p> <hd id="AN0180230223-21">What is associated with the home language environment?</hd> <p>Ultimately, our findings indicated that a mother's employment status and the child's age have strong associations with the home language environment. The significance of the mother's employment status as a factor influencing the home language environment is somewhat unique to our sample, as past research in Western and high-resourced samples has not focused on this demographic variable or found much evidence of its significance. One plausible reason for this finding is that employed mothers in our study may have higher levels of educational attainment than those who are unemployed. Since a mother's education tends to be positively associated with stronger parenting practices (Yue et al., [<reflink idref="bib85" id="ref174">85</reflink>]), employed and more educated mothers may engage in more frequent and interactive communication with their children. Research in the U.S. has shown that the quality of caregiving, measured by observed parental sensitivity, stimulation, and quality of assistance during parent-child interactions, is a stronger predictor of ECD outcomes than the quantity of caregiving, measured in hours (NICHD Early Child Care Research Network, [<reflink idref="bib53" id="ref175">53</reflink>], [<reflink idref="bib54" id="ref176">54</reflink>]). Therefore, employed mothers may still engage in more frequent and interactive communication with their children despite not being at home as much due to work, thus providing a higher quality of investment in their home language environment. In fact, we found positive associations between maternal employment and educational attainment (college level and above) in our sample, suggesting that this may be an important relationship. Another possible reason for this association might be that maternal employment is positively associated with higher levels of parental self-efficacy (Jackson & Scheines, [<reflink idref="bib34" id="ref177">34</reflink>]), which, in turn, is positively associated with parent-child interactions, including verbal interactions (DesJardin & Eisenberg, [<reflink idref="bib14" id="ref178">14</reflink>]). Despite their working hours, employed mothers may communicate with their child more frequently and interactively because they feel more confident in their parenting abilities, thus providing higher levels of investment in their child's home language environment. While these are two possible reasons for the relationship between a mother's employment and the home language environment, further research is needed to directly study this association.</p> <p>Another demographic characteristic associated with the home language environment in our sample was the child's age, which is consistent with previous studies (Gilkerson et al., [<reflink idref="bib25" id="ref179">25</reflink>]). We found that as a child's age increased, the number of adult-child conversations and the number of conversations initiated by the child increased, while the number of VABs initiated by female caregivers decreased. Gilkerson et al. ([<reflink idref="bib25" id="ref180">25</reflink>]) and Shneidman and Goldin-Meadow ([<reflink idref="bib67" id="ref181">67</reflink>]) present two plausible reasons for why these associations may exist. On one hand, as a child's age increases, they may be more likely to elicit speech from those around them, leading to more speech directed to them, and subsequently, a smaller number of VABs initiated by adults in relation to the child's vocalizations. On the other hand, as children develop and increase their locomotive capacities with age, they may actively seek out individuals who provide more opportunities for directed interaction, thus changing their own language environment.</p> <hd id="AN0180230223-22">What are the links between the home language environment and ECD?</hd> <p>Our results showed significant associations between the home language environment and overall development, as well as language development measured by the CREDI. These findings are consistent with previous studies (Gilkerson et al., [<reflink idref="bib26" id="ref182">26</reflink>]; Weisleder & Fernald, [<reflink idref="bib80" id="ref183">80</reflink>]) that also found a strong connection between the home language environment and language development. Specifically, our study revealed that adult-child conversations had a stronger link with child language development than the quantity of adult words, which aligns with the results of previous research (Gilkerson et al., [<reflink idref="bib26" id="ref184">26</reflink>]; Zimmerman et al., [<reflink idref="bib90" id="ref185">90</reflink>]). Furthermore, we found that VABs initiated by a female adult had a stronger association with child language development than VABs initiated by the child. This pattern was also observed in conversation turns between the child and a female adult, suggesting that adult-initiated conversations may be particularly important for later language development compared to child-initiated conversations, which is in line with a recent study by Salo et al. ([<reflink idref="bib65" id="ref186">65</reflink>]).</p> <p>In contrast to some previous studies (d'Apice & von Stumm, [<reflink idref="bib11" id="ref187">11</reflink>]; d'Apice et al., [<reflink idref="bib12" id="ref188">12</reflink>]; Gilkerson et al., [<reflink idref="bib26" id="ref189">26</reflink>]), we did not find an association between the home language environment and cognitive development. One possible explanation for this discrepancy may be that parents are not engaging in enough conversations or using the types of language that stimulate child cognitive development. d'Apice et al. ([<reflink idref="bib12" id="ref190">12</reflink>]) found that lexical diversity in conversations positively correlated with children's cognitive ability among 107 children aged 2–4 years. Other research suggests that during caregiver-child interactions, caregivers' language richness is positively and significantly associated with cognitive development (Gao et al., [<reflink idref="bib24" id="ref191">24</reflink>]; Hart & Risley, [<reflink idref="bib29" id="ref192">29</reflink>]). Hence, the quality and content of adult-child interactions may matter more for cognitive development than the sheer number of conversations, which could explain why we found no significant associations between the home language environment and cognitive development. Additionally, we did not observe any associations between the home language environment and motor or social-emotional development, which contradicts previous findings from rural China (Gao et al., [<reflink idref="bib24" id="ref193">24</reflink>]). According to Gao et al. ([<reflink idref="bib24" id="ref194">24</reflink>]), caregivers' language richness (i.e. how interactive parents are with children in conversation and play) was positively and significantly associated with motor and social-emotional development in children aged 6–30 months in rural China. Overall, these findings highlight the need for further research, as the relationship between the home language environment and non-language domains of ECD remains unclear in rural populations in China.</p> <hd id="AN0180230223-23">Limitations</hd> <p>While this study has made significant contributions to the literature on early childhood development (ECD) in rural and peri-urban China, there were several limitations to consider. First, we collected only two days of LENA recordings for each sample household, which is less than other LENA studies that often use weekly or bi-weekly recording schedules. To address this limitation, we carefully ensured that the two days of recording represented the child's typical at-home experiences. Caregivers were instructed to wait until they could capture recordings of their child's most representative days if the initial recording days were not likely to be typical.[<reflink idref="bib9" id="ref195">9</reflink>] Additionally, we implemented a standardized process to convert the 16-h recordings into 12-h audio data, averaging the AWC and CTC results from the two days to compensate for the shorter recording windows.</p> <p>The second limitation of this study is that the results are correlational, not causal. While we identified strong correlations between language development and the home language environment, these results cannot establish causality. To better understand the causal factors influencing ECD in rural and peri-urban China, future research should consider employing experimental or longitudinal research designs.</p> <p>Another limitation is the lack of specific data on household characteristics that could provide more context for rural and peri-urban living conditions. For instance, we did not collect data on bodily placement, room placement, or other structural elements that might offer deeper insights into the home language environments in these households. Gathering data on daily household interactions could provide a more detailed picture of the home language environment. However, this kind of data collection might introduce observer bias, as it would be challenging to collect such information in a naturalistic way, similar to how the LENA device functions.</p> <p>Despite these limitations, our study sheds light on the associations between the home language environment and ECD outcomes in rural and peri-urban China. It provides valuable insights for future research in this area and underscores the importance of early language development for children in low-resource communities.</p> <hd id="AN0180230223-24">Conclusions</hd> <p>The evidence from this study provides preliminary insights into crucial mechanisms of ECD in a previously overlooked sample selection: rural China, including peri-urban communities. The data collected revealed a strong association between the home language environment and child language development within several low-resource communities in rural and peri-urban China. However, there were no significant associations between the home language environment and cognitive, motor, or social-emotional development.</p> <p>The most influential aspect of the home language environment on ECD outcomes was adult-child conversations. These conversations played a more critical role in language development outcomes than the mere number of adult words spoken. Additionally, female-initiated conversations were found to be more influential than child-initiated conversations for language development.</p> <p>In conclusion, these findings underscore the need for applying experimental or longitudinal research approaches to identify the factors that causally influence language development in other rural and peri-urban settings in China. By further investigating these mechanisms, we can better understand and support early language development in these underrepresented communities.</p> <hd id="AN0180230223-25">Acknowledgments</hd> <p>We would like to thank the local collaborators and survey enumerators for their assistance with contacting local families and assisting with the survey and LENA data collection, and the children and families who participated in this study.</p> <hd id="AN0180230223-26">Disclosure statement</hd> <p>No potential conflict of interest was reported by the author(s).</p> <hd id="AN0180230223-27">Data availability statement</hd> <p>The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy or ethical restrictions.</p> <ref id="AN0180230223-28"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref3" type="bt">1</bibl> <bibtext> Increase in CTC by 1% corresponded to an increase in CREDI overall z-scores by 1.23%.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref15" type="bt">2</bibl> <bibtext> Increase in AWC by 1% corresponded to an increase in CREDI language z-scores by 1.30%.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref12" type="bt">3</bibl> <bibtext> Increase in CTC by 1% corresponded to an increase in CREDI language z-scores by 1.49%.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref45" type="bt">4</bibl> <bibtext> Increase in the number of CT in VABs initiated by the focus child by 1% corresponded to an increase in CREDI overall z-scores by 1.13%.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref75" type="bt">5</bibl> <bibtext> Increase in number of CT in VABs initiated by the focus child by 1% corresponded to an increase in CREDI language z-scores by 1.34%.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref60" type="bt">6</bibl> <bibtext> Increase in the number of CT by 1% was associated with an increase in CREDI overall z-scores by 1.10%.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref140" type="bt">7</bibl> <bibtext> Increase in the number of CT by 1% was associated with an increase in CREDI language z-scores by 1.36%.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref97" type="bt">8</bibl> <bibtext> Increase in the number of VABs initiated by a female adult by 1% corresponded to an increase in CREDI language z-scores by 1.32%.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref171" type="bt">9</bibl> <bibtext> On a typical day, the mother or grandmother of the household wakes up around 6:00 am and proceeds with household chores, such as cleaning and cooking breakfast. 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  Label: Title
  Group: Ti
  Data: The Home Language Environment and Early Childhood Development: A LENA Study from Rural and Peri-Urban China
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Xinwu+Zhang%22">Xinwu Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Delei+Liu%22">Delei Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Lucy+Pappas%22">Lucy Pappas</searchLink><br /><searchLink fieldCode="AR" term="%22Sarah-Eve+Dill%22">Sarah-Eve Dill</searchLink><br /><searchLink fieldCode="AR" term="%22Tianli+Feng%22">Tianli Feng</searchLink><br /><searchLink fieldCode="AR" term="%22Yunting+Zhang%22">Yunting Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Jin+Zhao%22">Jin Zhao</searchLink><br /><searchLink fieldCode="AR" term="%22Scott+Rozelle%22">Scott Rozelle</searchLink><br /><searchLink fieldCode="AR" term="%22Yue+Ma%22">Yue Ma</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Applied+Developmental+Science%22"><i>Applied Developmental Science</i></searchLink>. 2024 28(4):655-673.
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  Label: Availability
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 19
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Infants%22">Infants</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Development%22">Child Development</searchLink><br /><searchLink fieldCode="DE" term="%22Developmental+Delays%22">Developmental Delays</searchLink><br /><searchLink fieldCode="DE" term="%22Delayed+Speech%22">Delayed Speech</searchLink><br /><searchLink fieldCode="DE" term="%22Rural+Areas%22">Rural Areas</searchLink><br /><searchLink fieldCode="DE" term="%22Suburbs%22">Suburbs</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Acquisition%22">Language Acquisition</searchLink><br /><searchLink fieldCode="DE" term="%22Parent+Child+Relationship%22">Parent Child Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Mothers%22">Mothers</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+Communication%22">Interpersonal Communication</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/10888691.2023.2267440
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1088-8691<br />1532-480X
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The home language environment is a significant correlate of early childhood development outcomes; however, less is known about this mechanism in rural and peri-urban China where rates of developmental delay are as high as 52%. This study examines associations between the home language environment and child development in a sample of 158 children (58% boys) aged 18-24 months (M[subscript age] = 21.5) from rural and peri-urban households in Western China. Results show a significant association between adult-child conversation count and language development, suggesting the home language environment may be a mechanism for child development in rural and peri-urban China. 22.5% of the sample were at risk of language delay. Mother's employment and child's age were significant factors in the home language environment.
– Name: AbstractInfo
  Label: Abstractor
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  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1443405
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1443405
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/10888691.2023.2267440
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 655
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Infants
        Type: general
      – SubjectFull: Child Development
        Type: general
      – SubjectFull: Developmental Delays
        Type: general
      – SubjectFull: Delayed Speech
        Type: general
      – SubjectFull: Rural Areas
        Type: general
      – SubjectFull: Suburbs
        Type: general
      – SubjectFull: Language Acquisition
        Type: general
      – SubjectFull: Parent Child Relationship
        Type: general
      – SubjectFull: Mothers
        Type: general
      – SubjectFull: Interpersonal Communication
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: The Home Language Environment and Early Childhood Development: A LENA Study from Rural and Peri-Urban China
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Xinwu Zhang
      – PersonEntity:
          Name:
            NameFull: Delei Liu
      – PersonEntity:
          Name:
            NameFull: Lucy Pappas
      – PersonEntity:
          Name:
            NameFull: Sarah-Eve Dill
      – PersonEntity:
          Name:
            NameFull: Tianli Feng
      – PersonEntity:
          Name:
            NameFull: Yunting Zhang
      – PersonEntity:
          Name:
            NameFull: Jin Zhao
      – PersonEntity:
          Name:
            NameFull: Scott Rozelle
      – PersonEntity:
          Name:
            NameFull: Yue Ma
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 1088-8691
            – Type: issn-electronic
              Value: 1532-480X
          Numbering:
            – Type: volume
              Value: 28
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Applied Developmental Science
              Type: main
ResultId 1