View in EDS HTML Full Text PDF Full Text

Associations between Urbanization and the Home Language Environment: Evidence from a LENA Study in Rural and Peri-Urban China

Saved in:
Bibliographic Details
Title: Associations between Urbanization and the Home Language Environment: Evidence from a LENA Study in Rural and Peri-Urban China
Language: English
Authors: Yue Ma, Xinwu Zhang, Lucy Pappas (ORCID 0000-0002-2476-3286), Andrew Rule (ORCID 0000-0001-5674-8550), Yujuan Gao, Sarah-Eve Dill (ORCID 0000-0002-9321-6606), Tianli Feng, Yue Zhang, Hong Wang, Flavio Cunha, Scott Rozelle
Source: Child Development. e74-e92 2024 95(2):e74-e92.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 19
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Rural Urban Differences, Family Environment, Language Usage, Infants, Child Language, Language Acquisition, Foreign Countries
Geographic Terms: China
DOI: 10.1111/cdev.14034
ISSN: 0009-3920
1467-8624
Abstract: In low- and middle-income countries, urbanization has spurred the expansion of peri-urban communities, or urban communities of formerly rural residents with low socioeconomic status. The growth of these communities offers researchers an opportunity to measure the associations between the level of urbanization and the home language environment (HLE) among otherwise similar populations. Data were collected in 2019 using Language Environment Analysis observational assessment technology from 158 peri-urban and rural households with Han Chinese children (92 males, 66 females) aged 18-24 months in China. Peri-urban children scored lower than rural children in measures of the HLE and language development. In both samples, child age, gender, maternal employment, and sibling number were positively correlated with the HLE, which was in turn correlated with language development.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1418608
Database: ERIC
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
    Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwFbjyu2tZtpGboAa7WiikDzAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDCyMQR3qghaPherGLQIBEICBm1I1kzwX6fxnhbJ4aKlOFYsPqudb-zxpiVI0Ybb6bIZsm4s1PLsYxW5y2e_GjJxlZ7urjFmqh1QwWnj2htqnDNMYDLA-hOgsZABqgywzw0ufcV5PNrpmgc5-LbpIVRnhGZQ3lIQeBIYzXusfm_ISLnTpd7uLKwLLPH6zt-qfcXhASMRQycfBBfbBNgwOj5G2bIWVQW4vTybyIuKE
Text:
  Availability: 1
  Value: <anid>AN0175750708;cdv01mar.24;2024Mar04.02:59;v2.2.500</anid> <title id="AN0175750708-1">Associations between urbanization and the home language environment: Evidence from a LENA study in rural and peri‐urban China </title> <p>In low‐ and middle‐income countries, urbanization has spurred the expansion of peri‐urban communities, or urban communities of formerly rural residents with low socioeconomic status. The growth of these communities offers researchers an opportunity to measure the associations between the level of urbanization and the home language environment (HLE) among otherwise similar populations. Data were collected in 2019 using Language Environment Analysis observational assessment technology from 158 peri‐urban and rural households with Han Chinese children (92 males, 66 females) aged 18–24 months in China. Peri‐urban children scored lower than rural children in measures of the HLE and language development. In both samples, child age, gender, maternal employment, and sibling number were positively correlated with the HLE, which was in turn correlated with language development.</p> <p></p> <ulist> <item> Abbreviations</item> <p></p> <item> AWC adult word count</item> <p></p> <item> CDI MacArthur–Bates Communicative Development Inventories</item> <p></p> <item> CTC conversational turn count</item> <p></p> <item> CTS conversational turns within segments</item> <p></p> <item> CVC child vocalization count</item> <p></p> <item> ECD early childhood development</item> <p></p> <item> HLE home language environment</item> <p></p> <item> LENA Language Environment Analysis</item> <p></p> <item> LMIC low‐ and middle‐income countries</item> <p></p> <item> NS number of segment</item> <p></p> <item> SES socioeconomic status</item> <p></p> <item> VIF variance inflation factor</item> </ulist> <p>The first 3 years of life is a critical period for early childhood development (ECD), especially early language development (Emmers et al., [<reflink idref="bib26" id="ref1">26</reflink>]). Language development between the ages of 0 and 3 years predicts school‐age language, cognitive, and learning outcomes, laying the foundations for lifelong development (Demir‐Lira et al., [<reflink idref="bib24" id="ref2">24</reflink>]). Delayed development in the first years of life, on the other hand, can affect educational achievement and employment outcomes later in life, limiting children from reaching their full potential (Attanasio, [<reflink idref="bib3" id="ref3">3</reflink>]; Knudsen et al., [<reflink idref="bib44" id="ref4">44</reflink>]).</p> <p>The home language environment (HLE) plays a crucial role in ECD, acting as an important input to language development and future outcomes (Fernald et al., [<reflink idref="bib29" id="ref5">29</reflink>]; Hart & Risley, [<reflink idref="bib39" id="ref6">39</reflink>]; Hoff, [<reflink idref="bib42" id="ref7">42</reflink>]; Huttenlocher et al., [<reflink idref="bib43" id="ref8">43</reflink>]; Rowe, [<reflink idref="bib70" id="ref9">70</reflink>]; Tamis‐LeMonda et al., [<reflink idref="bib77" id="ref10">77</reflink>]). Specifically, the quantity of adult speech and adult–child interactions are two key characteristics of the HLE (d'Apice et al., [<reflink idref="bib21" id="ref11">21</reflink>]; d'Apice & von Stumm, [<reflink idref="bib22" id="ref12">22</reflink>]). These quantities are widely measured using the Language Environment Analysis (LENA™) system, a small recording device and software used to conduct unintrusive observation of the HLE (Gilkerson & Richards, [<reflink idref="bib32" id="ref13">32</reflink>]). Using LENA, many studies from low‐, middle‐, and high‐income settings have found that infants who grow up in households with richer HLE (characterized by more adult speech and more adult–child interactions) learn vocabulary faster, demonstrate increased processing speed, and develop stronger language skills (Gilkerson & Richards, [<reflink idref="bib32" id="ref14">32</reflink>]; Weber et al., [<reflink idref="bib84" id="ref15">84</reflink>]; Zhang et al., [<reflink idref="bib100" id="ref16">100</reflink>]). Thus, the HLE is a strong predictor of language development (Gilkerson et al., [<reflink idref="bib33" id="ref17">33</reflink>]; Ramírez‐Esparza et al., [<reflink idref="bib67" id="ref18">67</reflink>]; Weisleder & Fernald, [<reflink idref="bib85" id="ref19">85</reflink>]).</p> <p>Adult speech and adult–child conversation are important measures of the HLE. The amount of adult speech (i.e., the number of words spoken by adults) that a child hears has been shown to correlate with stronger language skills and cognitive abilities (d'Apice et al., [<reflink idref="bib21" id="ref20">21</reflink>]; d'Apice & von Stumm, [<reflink idref="bib22" id="ref21">22</reflink>]; Hoff, [<reflink idref="bib42" id="ref22">42</reflink>]). For instance, Hoff ([<reflink idref="bib42" id="ref23">42</reflink>]) found that 2‐year‐old children who heard more maternal speech had richer productive vocabularies. Using LENA technology, d'Apice et al. ([<reflink idref="bib21" id="ref24">21</reflink>]) found that home language input (i.e., number of words and lexical diversity) of preschoolers aged 2.03 to 3.99 years was positively associated with children's cognitive ability and lexical diversity. Adult–child conversation is another important aspect of the HLE that is also associated with improved language and cognitive development (Lopez et al., [<reflink idref="bib53" id="ref25">53</reflink>]; Ramírez et al., [<reflink idref="bib66" id="ref26">66</reflink>]). For instance, Lopez et al. ([<reflink idref="bib53" id="ref27">53</reflink>]) found that parental responses to child vocalizations were positively associated with vocabulary development for children aged 11–14 months in the United States.</p> <p>Higher rates of child vocalizations, or sounds and prespeech noises made by children, have also been shown to predict a child's expressive vocabulary development and overall language skills (Greenwood et al., [<reflink idref="bib37" id="ref28">37</reflink>]; Wang et al., [<reflink idref="bib83" id="ref29">83</reflink>]; Werwach et al., [<reflink idref="bib86" id="ref30">86</reflink>]). A recent meta‐analysis found positive associations between the number of child vocalizations and both expressive and receptive language skills among children under 4 years old (Wang et al., [<reflink idref="bib83" id="ref31">83</reflink>]). Thus, we follow several previous studies in using child vocalizations as an indicator of language development in this study (Ramírez‐Esparza et al., [<reflink idref="bib67" id="ref32">67</reflink>]; Wang et al., [<reflink idref="bib83" id="ref33">83</reflink>]). However, it is also important to note that child vocalizations are closely related to the HLE, as they are driven by interaction with other social entities (Moeller et al., [<reflink idref="bib61" id="ref34">61</reflink>]), and auditory feedback models also suggest that hearing one's own voice is important for language development (Brainard & Doupe, [<reflink idref="bib8" id="ref35">8</reflink>]).</p> <p>The HLE, as measured by these variables, is closely correlated with language development, which in turn strongly predicts future academic outcomes (Duncan et al., [<reflink idref="bib25" id="ref36">25</reflink>]; Fernald et al., [<reflink idref="bib29" id="ref37">29</reflink>]; Lee & Burkam, [<reflink idref="bib48" id="ref38">48</reflink>]; Uccelli et al., [<reflink idref="bib80" id="ref39">80</reflink>]; Walker et al., [<reflink idref="bib81" id="ref40">81</reflink>]) and is, therefore, essential to long‐term learning and achievement. One widely used and validated assessment for child language development is the MacArthur–Bates Communicative Development Inventories (CDI; deMayo et al., [<reflink idref="bib23" id="ref41">23</reflink>]; Frank et al., [<reflink idref="bib31" id="ref42">31</reflink>]). Studies have repeatedly found measures of the HLE to be associated with higher CDI scores, including adult speech (Ma et al., [<reflink idref="bib55" id="ref43">55</reflink>]), adult–child conversation (Ma et al., [<reflink idref="bib55" id="ref44">55</reflink>]; Ramírez et al., [<reflink idref="bib66" id="ref45">66</reflink>]; Zhang et al., [<reflink idref="bib100" id="ref46">100</reflink>]), and child vocalizations (Zhang et al., [<reflink idref="bib100" id="ref47">100</reflink>]). Understanding the HLE, therefore, can help researchers pinpoint the factors that impact children's language development and their long‐term outcomes by extension.</p> <hd id="AN0175750708-2">Urbanization and the HLE</hd> <p>Studies have long shown certain environmental factors to be associated with lower rates of child‐directed speech in the HLE. For instance, the literature to date has largely focused on socioeconomic status (SES), with a large body of literature from Western countries showing that children from lower SES households tend to hear less child‐directed speech than their higher SES peers (Dailey & Bergelson, [<reflink idref="bib20" id="ref48">20</reflink>]; Golinkoff et al., [<reflink idref="bib35" id="ref49">35</reflink>]; Hart & Risley, [<reflink idref="bib39" id="ref50">39</reflink>]; Hoff, [<reflink idref="bib42" id="ref51">42</reflink>]; Rowe, [<reflink idref="bib69" id="ref52">69</reflink>], [<reflink idref="bib70" id="ref53">70</reflink>]; Wood et al., [<reflink idref="bib89" id="ref54">89</reflink>]). Studies in low‐ and middle‐income countries (LMICs) have largely echoed these findings, suggesting that low‐SES populations in these countries also confront issues of low parent–child engagement (Casillas et al., [<reflink idref="bib13" id="ref55">13</reflink>], [<reflink idref="bib14" id="ref56">14</reflink>]; Cristia et al., [<reflink idref="bib17" id="ref57">17</reflink>]; Weber et al., [<reflink idref="bib84" id="ref58">84</reflink>]) and high rates of language delay (Sania et al., [<reflink idref="bib71" id="ref59">71</reflink>]). For example, Cristia et al. ([<reflink idref="bib17" id="ref60">17</reflink>]) used live observation by enumerators to estimate that children under the age of 4 years in Bolivian villages heard less than 1 min of child‐directed speech per hour during the day. Using manual transcriptions of at‐home audio recordings, Casillas et al. ([<reflink idref="bib13" id="ref61">13</reflink>]) found that Tseltal Mayan children under the age of 3 heard an average of only 3.63 min of child‐directed speech per hour during the day, although this was not accompanied by significant language delay. Using the same method, Casillas et al. ([<reflink idref="bib14" id="ref62">14</reflink>]) found that Papua New Guinean children under the age of 3 heard even less child‐directed speech than Tseltal Mayan children (3.13 min per hour), again without significant signs of language delay. While all of these studies show low rates of child‐directed speech in low‐SES populations in LMICs, the lack of a clear correlation between low rates of child‐directed speech and the prevalence of language delay in some of these settings also suggests that the links between the HLE and language delay in specific cultural contexts in LMICs need to be further explored (Weber et al., [<reflink idref="bib84" id="ref63">84</reflink>]). Additionally, few studies in LMICs have compared the HLE of specific low‐SES subpopulations with one another, meaning that the potential impacts of environmental factors other than SES on the HLE have rarely been explored among these populations.</p> <p>In particular, the potential impact of urbanization on the HLE of low‐SES households in LMICs has gone largely unexamined in the literature to date. In this paper, urbanization refers to the transplanting of a household from a primarily rural to a primarily urban environment, either through migration or through the encroachment of urban boundaries into previously rural lands (Hamnett, [<reflink idref="bib38" id="ref64">38</reflink>]; Heurlin, [<reflink idref="bib41" id="ref65">41</reflink>]; Smith, [<reflink idref="bib72" id="ref66">72</reflink>]). While urbanization can be accompanied by a rise in income, it is not synonymous with increased SES. In fact, many low‐SES households in LMICs that undergo urbanization remain much closer to their rural counterparts in terms of SES than to their urban neighbors (He & Wang, [<reflink idref="bib40" id="ref67">40</reflink>]; Heurlin, [<reflink idref="bib41" id="ref68">41</reflink>]; Li, [<reflink idref="bib50" id="ref69">50</reflink>]; Li & Placier, [<reflink idref="bib49" id="ref70">49</reflink>]; Tong et al., [<reflink idref="bib79" id="ref71">79</reflink>]; Zhan, [<reflink idref="bib96" id="ref72">96</reflink>]). These recently urbanized, low‐SES residents tend to settle in communities on the outskirts of large cities (Buckingham & Chan, [<reflink idref="bib10" id="ref73">10</reflink>]; Macdonald & Winklerprins, [<reflink idref="bib56" id="ref74">56</reflink>]). Following the example of several other recent studies, we refer to these urban communities of low‐SES residents from primarily rural backgrounds as peri‐urban communities (Smith, [<reflink idref="bib72" id="ref75">72</reflink>]; Wu et al., [<reflink idref="bib91" id="ref76">91</reflink>]).</p> <p>Increasing urbanization in LMICs in recent decades has led to rapid growth in peri‐urban communities and spurred dramatic changes for their low‐SES inhabitants. Some of these changes may be positive, including increased access to education, employment opportunities, or other urban resources in comparison with their rural counterparts (Le et al., [<reflink idref="bib47" id="ref77">47</reflink>]; Nauman et al., [<reflink idref="bib62" id="ref78">62</reflink>]; Song & Xie, [<reflink idref="bib73" id="ref79">73</reflink>]; Winarso et al., [<reflink idref="bib87" id="ref80">87</reflink>]). At the same time, peri‐urban residents may be subject to a host of negative effects that rural residents do not face, including longer work hours, the need to take on more part‐time jobs, or the lack of an inclusive social community (Buckingham & Chan, [<reflink idref="bib10" id="ref81">10</reflink>]; Liu et al., [<reflink idref="bib52" id="ref82">52</reflink>]; Mandere et al., [<reflink idref="bib57" id="ref83">57</reflink>]; Palmer et al., [<reflink idref="bib64" id="ref84">64</reflink>]; Tacoli et al., [<reflink idref="bib76" id="ref85">76</reflink>]; Tong et al., [<reflink idref="bib79" id="ref86">79</reflink>]).</p> <p>Moreover, there is ample reason to believe that these changes spurred by urbanization might impact the cognitive development or HLE of peri‐urban children. In developing countries, urbanization has been linked to lower undernutrition rates (Firestone et al., [<reflink idref="bib30" id="ref87">30</reflink>]; Zhang et al., [<reflink idref="bib101" id="ref88">101</reflink>]) and increased access to health care services, education resources, and safe water supply (McDade & Adair, [<reflink idref="bib60" id="ref89">60</reflink>]). These benefits of urbanization are positively associated with cognitive and language development outcomes (Alderman & Fernald, [<reflink idref="bib2" id="ref90">2</reflink>]; Chang et al., [<reflink idref="bib15" id="ref91">15</reflink>]; Chen et al., [<reflink idref="bib16" id="ref92">16</reflink>]; Grantham‐McGregor & Ani, [<reflink idref="bib36" id="ref93">36</reflink>]; Prado & Dewey, [<reflink idref="bib65" id="ref94">65</reflink>]). At the same time, due to the higher costs of living in urban areas compared to rural areas, peri‐urban households often have more family members working outside the home than rural households (Fan et al., [<reflink idref="bib27" id="ref95">27</reflink>]), meaning that there may be fewer adults at home to engage verbally with the child. Because peri‐urban residents tend to live near strangers rather than in the closer‐knit communities that may characterize rural communities, urbanization might erode traditional social solidarity and weaken neighborhood social capital (Zhang et al., [<reflink idref="bib97" id="ref96">97</reflink>]), which in turn could contribute to a lower language environment and child language skills (Sperry et al., [<reflink idref="bib74" id="ref97">74</reflink>]).</p> <p>Given the growth of peri‐urban populations in LMICs and the existing evidence that urbanization might impact early childhood language development, there is a pressing need to determine how and to what extent urbanization is associated with the HLE. Despite this, to the best of our knowledge, no study to date has investigated the associations between measures of the HLE and language development among peri‐urban children in LMICs. Moreover, no study has yet systematically compared measures of the HLE between peri‐urban and rural households in these countries.</p> <hd id="AN0175750708-3">Peri‐urban China</hd> <p>Over the last four decades, China has undergone the most rapid and large‐scale urbanization in the world. According to data from China's National Bureau of Statistics, between 1978 and 2020, China's urbanization rate increased from 17.92% to 63.89%, rising by 1.04% per year on average (Liu & Ye, [<reflink idref="bib51" id="ref98">51</reflink>]; Zhu, [<reflink idref="bib103" id="ref99">103</reflink>]). This pace of urbanization far outstripped the global average urbanization rate of 0.4% per year (from 39% to 56%) during the same period (World Bank, [<reflink idref="bib90" id="ref100">90</reflink>]). In spite of this, more than 70% of young children in China are still born and raised either in low‐SES rural areas or in similarly low‐SES peri‐urban communities whose residents primarily come from rural backgrounds (Emmers et al., [<reflink idref="bib26" id="ref101">26</reflink>]). Rates of developmental delay among these rural and peri‐urban children are concerningly high. According to one recent estimate, as many as 45% of rural and peri‐urban experience cognitive delays, and 46% experience language delays (Emmers et al., [<reflink idref="bib26" id="ref102">26</reflink>]). Moreover, studies in rural China show that rural children are exposed to a less rich HLE than their urban peers. For instance, a LENA study in rural Shaanxi Province (Ma et al., [<reflink idref="bib55" id="ref103">55</reflink>]) found that a sample of children aged 20–27 months heard significantly fewer words and engaged in fewer conversational turns than a sample of even younger urban children from Shanghai (Zhang, Xu, et al., [<reflink idref="bib102" id="ref104">102</reflink>]).</p> <p>Despite these findings on rural children as a whole, only limited research has been conducted on the developmental outcomes of peri‐urban children specifically, and none has been conducted on the HLE of these children. Both rural and peri‐urban populations have typically been characterized as "rural" in the literature (Bai et al., [<reflink idref="bib4" id="ref105">4</reflink>]), making it difficult to compare the language development outcomes of rural and peri‐urban children based on existing evidence. However, a small number of studies that differentiate between the two populations have found rates of language delay among peri‐urban children that are comparable to those among children from rural backgrounds as a whole. For example, Wang et al. ([<reflink idref="bib82" id="ref106">82</reflink>]), examining a sample of peri‐urban families who had migrated from rural areas, found that the rate of language delay among children in these families was 39%. Zhang et al. ([<reflink idref="bib98" id="ref107">98</reflink>]) further divided peri‐urban families into rural migrants and urbanized farmers (i.e., farmers who had been living in the district when it became urbanized) and determined that the rates of child language delay among these families were 36% and 38%, respectively. These estimates, which are lower than estimated rates of language delay among rural and peri‐urban children as a whole, provide further reason to suspect that differences between peri‐urban and rural households may lead to differences in the HLE and ultimately to differential language development outcomes. However, more in‐depth analyses and larger samples are still needed to better understand the HLE and language development among rural and peri‐urban children in China.</p> <hd id="AN0175750708-4">The present study</hd> <p>Therefore, the primary goal of this study is to provide the first‐ever quantification and comparison of the HLE in China's rural and peri‐urban populations. To achieve this, we pursue three specific objectives. First, we compare measures of the HLE between the rural and peri‐urban populations. Second, we examine the correlations between the HLE and language development among households in rural and peri‐urban China. Finally, we identify specific household characteristics associated with differences in the HLE between the rural and peri‐urban populations. As prior evidence of the relative richness of the HLE between these two populations in China is mixed, and no previous studies have determined the influence of urbanization on the HLE in LMICs, this research can be considered primarily exploratory in nature.</p> <hd id="AN0175750708-5">METHOD</hd> <p></p> <hd id="AN0175750708-6">Sample</hd> <p></p> <hd id="AN0175750708-7">Study location</hd> <p>Data for the study were collected in two rural communities and one peri‐urban community in Sichuan, a province in southwestern China. The two rural communities were located in two different counties that were selected as being representative of rural Sichuan. The counties had 192,200 and 1,524,700 local residents, respectively, of whom 75% (<reflink idref="bib143" id="ref108">143</reflink>,<reflink idref="bib200" id="ref109">200</reflink>) and 70% (<reflink idref="bib1" id="ref110">1</reflink>,032,<reflink idref="bib300" id="ref111">300</reflink>), respectively, held rural legal residency status or hukou. Hukou, a hereditary status indicating whether the holder is of rural or urban family background, restricts which public services the holder can access outside their registered home district (Bengoa & Rick, [<reflink idref="bib5" id="ref112">5</reflink>]). In the first rural county, the monthly per capita income for residents with rural hukou status was RMB 1617 (USD 234) in 2019 (Liu & Ye, [<reflink idref="bib51" id="ref113">51</reflink>]). In the second rural county, the monthly per capita income for residents with rural hukou status was RMB 1368 (USD 198; Liu & Ye, [<reflink idref="bib51" id="ref114">51</reflink>]). Compared to the monthly per capita income for rural households in the province overall (RMB 1222; USD 177) and in China overall (RMB 1335; USD 193), households from these two rural counties reported slightly higher per capita incomes (Liu & Ye, [<reflink idref="bib51" id="ref115">51</reflink>]). However, these rural households had substantially lower monthly per capita incomes than urban households in the province (RMB 3012; USD 436) and urban households nationwide (RMB 3529; USD 511; Liu & Ye, [<reflink idref="bib51" id="ref116">51</reflink>]) and can, thus, be considered representative of low‐SES households in rural China. Most caregivers in these rural communities speak the local provincial (Sichuanese) dialect at home, which shares the same syllable structure as Standard Mandarin and is, therefore, widely distinguishable and easily interpreted (Zhang, [<reflink idref="bib99" id="ref117">99</reflink>]).</p> <p>The sampled peri‐urban community was located in a district on the outskirts of Chengdu, the provincial capital of Sichuan. The district was selected as being very representative of peri‐urban areas in Sichuan. With an urbanization rate of 73% in 2019, this district was one of the most rapidly developing in the province but was still classified as a second‐tier district (Liu & Ye, [<reflink idref="bib51" id="ref118">51</reflink>]). It was less developed than the area's five first‐tier districts, which each had an urbanization rate of 100% and enjoyed greater economic development, political influence, and population sizes than second‐, third‐, and fourth‐tier districts (Bland & Hernández, [<reflink idref="bib6" id="ref119">6</reflink>]; Liu & Ye, [<reflink idref="bib51" id="ref120">51</reflink>]). In 2019, out of the district's total 740,000 residents, approximately one third had rural hukou status, and about one quarter were registered as non‐local residents (Liu & Ye, [<reflink idref="bib51" id="ref121">51</reflink>]), indicating a large population of peri‐urban residents. Like in the rural communities, most caregivers in the sampled peri‐urban community speak the Sichuanese dialect of Mandarin at home (Xu, [<reflink idref="bib93" id="ref122">93</reflink>]).</p> <hd id="AN0175750708-8">Sampling protocol</hd> <p>Due to the geographic and administrative differences between the rural and peri‐urban communities, the research team followed different sampling protocols in each location. A detailed description of the specific sampling protocols used is provided in Appendix S2, which also includes a graphic presentation of the protocol used to select the rural sample (Figure S1). The sample was restricted to households with infants between the ages of 18 and 24 months (Zangl & Fernald, [<reflink idref="bib95" id="ref123">95</reflink>]). As noted by Gilkerson et al. ([<reflink idref="bib33" id="ref124">33</reflink>]), early talk and interaction during the critical, yet narrow, developmental window of 18–24 months are particularly predictive of children's later linguistic and cognitive outcomes. The final samples contained 77 rural households and 81 peri‐urban households who participated in the LENA analysis.</p> <hd id="AN0175750708-9">Data collection</hd> <p>The data for the study were collected in the summer and fall of 2020. Our research team was extensively trained to follow a standardized data collection protocol and LENA recording process that lasted 4 days. On the first day, researchers conducted surveys at the home of each participating family to collect household demographic information. After the surveys were completed, the researchers taught caregivers how to use the LENA recorder, instructing them to charge the LENA recorder between the second and third days. During the second and third days, caregivers used the LENA recorders to record two full days of the HLE, charging the recorder overnight as instructed. Finally, on the fourth day, the research team retrieved the LENA recorders and conducted exit interviews with caregivers on their use of the LENA recorders. Caregivers were compensated for their participation in the study with books and educational toys.</p> <p>This study received ethical approval from the Stanford University Institutional Review Board (IRB; Protocol ID 49552). Informed oral consent was obtained from the caregivers of all sample children by members of the field survey team who were trained in the consent process. After introducing the research and providing a period for caregivers to ask questions, enumerators used a script in both Mandarin Chinese and the Sichuanese dialect to obtain oral consent from caregivers. The participating caregivers understood that their recordings would be collected and listened to for the purpose of this study.</p> <hd id="AN0175750708-10">Measures</hd> <p></p> <hd id="AN0175750708-11">LENA: The HLE</hd> <p>The LENA software produces three measures related to the HLE: (a) adult word count (AWC) or the number of adult words overheard by the child; (b) conversational turn count (CTC) or the number of back‐and‐forth interactions between an adult and the child; and (c) child vocalization count (CVC) or the number of speech‐like vocalizations made by the child. While CVC can be considered a measure of the HLE, it is also used as an indicator of child language development (Ramírez‐Esparza et al., [<reflink idref="bib67" id="ref125">67</reflink>]). LENA‐reported AWC, CTC, and CVC have all been reliably used in previous studies in the United States, China, and other countries (Busch et al., [<reflink idref="bib11" id="ref126">11</reflink>]; Canault et al., [<reflink idref="bib12" id="ref127">12</reflink>]; Gilkerson et al., [<reflink idref="bib33" id="ref128">33</reflink>]; Pae et al., [<reflink idref="bib63" id="ref129">63</reflink>]; Weisleder & Fernald, [<reflink idref="bib85" id="ref130">85</reflink>]; Zhang, Xu, et al., [<reflink idref="bib102" id="ref131">102</reflink>]). All three measures have been found to correlate closely with word counts generated from human manual transcription, including among Chinese‐speaking populations (Standard Mandarin and Shanghai dialect; Gilkerson et al., [<reflink idref="bib34" id="ref132">34</reflink>]; Ma et al., [<reflink idref="bib55" id="ref133">55</reflink>]).</p> <p>In addition to AWC, CTC, and CVC, the initiator of vocalizations and interactions may also be important to the HLE. Using the LENA Advanced‐Data Extractor (ADEX), recordings could be further broken into vocalization activity blocks (or segments)—that is, audio segments containing conversations between the focus child and an adult (Cunha et al., [<reflink idref="bib19" id="ref134">19</reflink>]). To be identified as a conversation, child vocalizations and adult speech must alternate, with no more than 5 s of silence or other non‐speech separation between them. LENA is able to automatically detect whether the segments are initiated by the focus child or a male or female adult. We used this feature to assess two groups of variables: (a) the number of conversational turns within segments (CTS) initiated by the focus child, by a female adult, and by a male adult; and (b) the number of segments (NS) initiated by the focus child, by a female adult, and by a male adult (Cunha et al., [<reflink idref="bib19" id="ref135">19</reflink>]; Xu et al., [<reflink idref="bib92" id="ref136">92</reflink>]). These measures allow us to estimate how often the child or an adult instigates the interaction and assess the impacts of child‐initiated versus adult‐initiated interactions on language development. CTS and NS initiated by the child or adults have been widely used in studies conducted in both high‐SES and low‐SES settings (Cunha et al., [<reflink idref="bib19" id="ref137">19</reflink>]; Weber et al., [<reflink idref="bib84" id="ref138">84</reflink>]), although validation studies for these measures do not yet exist.</p> <p>A detailed description of how LENA data were collected and managed can be found in Appendix S1. The main outcomes of our LENA results were normally distributed (Figures S2–S4). In our correlational analysis, we used the logarithm measure for each HLE outcome for ease of interpretation.</p> <hd id="AN0175750708-12">CDI: Child language development</hd> <p>In addition to CVC, we used the Mandarin version of the CDI to measure child language development. The CDI is a parent‐reported assessment that has been adapted and validated in Mandarin Chinese (Fenson et al., [<reflink idref="bib28" id="ref139">28</reflink>]; Tardif et al., [<reflink idref="bib78" id="ref140">78</reflink>]) and has proven reliable in studying early language development in China (Zhang, Xu, et al., [<reflink idref="bib102" id="ref141">102</reflink>]). Two methods are used to assess the reliability of the CDI short form: internal consistency (how likely each of the items on the scale is measuring the same ability) and test–retest reliability (how likely one is to receive a similar ability ranking when the same test is used at different times; Tardif et al., [<reflink idref="bib78" id="ref142">78</reflink>]). We calculated internal consistency by computing Cronbach's alpha for each of the short‐form subscales. Cronbach's alpha was more than.8, indicating high internal consistency. Simple bivariate correlations between the various sections of each of the instruments at different test times were also high (.67–.90). In this study, we used the short‐form expressive CDI vocabulary assessment, which consists of 113 words. Researchers asked the child's caregiver whether their child could say each word on the list, with each word the child could say counting as one point. As seen in Figure S5, the CDI scores were normally distributed. In our correlational analysis, we use the standardized CDI scores for ease of interpretation.</p> <hd id="AN0175750708-13">Household survey: Demographic information</hd> <p>The initial survey collected demographic information about participating households. Researchers recorded the focus child's gender and age in months. Household characteristics were also recorded, including the mother's age (in years), whether the mother had completed an associate degree or above, whether the mother had a job, whether the father had completed an associate degree or above, whether the father had lived at home for at least 6 months of the last year, the total number of adults in the household, and the total number of siblings of the focus child living in the household. The researchers also collected information on household wealth by creating a household asset index based on whether the household owned or had access to running water, a toilet, a water heater, a washing machine, a computer, internet access, a refrigerator, air conditioning, a motorcycle, and a car or truck. The final household asset index was generated using polychoric principal component analysis (Kolenikov & Angeles, [<reflink idref="bib45" id="ref143">45</reflink>]).</p> <p>Our focus on these demographic characteristics is rooted in the literature. Child age and gender were collected because previous studies have found differences in language development outcomes between girls and boys (Yue et al., [<reflink idref="bib94" id="ref144">94</reflink>]; Zhang, Xu, et al., [<reflink idref="bib102" id="ref145">102</reflink>]) and between older and younger children (Gilkerson et al., [<reflink idref="bib33" id="ref146">33</reflink>]). Parental characteristics related to SES, including parental age, parental educational attainment, and parental migration status, have also been shown to be associated with child language development (Lee & Burkam, [<reflink idref="bib48" id="ref147">48</reflink>]; Ramírez et al., [<reflink idref="bib66" id="ref148">66</reflink>]; Weisleder & Fernald, [<reflink idref="bib85" id="ref149">85</reflink>]). Household wealth (asset index) has been shown to be associated with ECD as well (Gilkerson et al., [<reflink idref="bib33" id="ref150">33</reflink>]; Yue et al., [<reflink idref="bib94" id="ref151">94</reflink>]). Finally, the number of adults and siblings in the household was collected because previous studies suggest that household size is an influential factor in the HLE and language development (Mayor et al., [<reflink idref="bib58" id="ref152">58</reflink>]; McCartney, [<reflink idref="bib59" id="ref153">59</reflink>]).</p> <p>The descriptive statistics for both rural and peri‐urban samples are shown in Table 1. The average age of rural children in the sample was approximately 22 months (SD = 1.60) and the average age of the peri‐urban children in the sample was roughly 21 months (SD = 1.60). For both rural and peri‐urban samples, just under half (46%) of children from each sample were male. In terms of household characteristics, rural and peri‐urban mothers were 27.5 (SD = 4.25) and 29 (SD = 4.69) years old, respectively. In comparison with the peri‐urban sample, fewer rural mothers had completed an associate degree or above (18.18% of the rural sample compared to 51.85% of the peri‐urban sample), but a similar number of rural and peri‐urban mothers had a job at the time of the survey (61.04% and 62.96%, respectively). On average, a smaller proportion of rural fathers had an associate degree or above (9.09% in the rural sample and 51.85% in the peri‐urban sample). Moreover, a larger proportion of peri‐urban fathers reported that they had lived at home for at least 6 months of the last year (79.01% of the peri‐urban sample compared to 31.17% of the rural sample). Each rural household had an average of two adults living in the household, and each peri‐urban household had an average of three adults living in the household. Finally, rural households had more children than peri‐urban households (0.36 and 0.12 siblings of the focus child, respectively).</p> <p>1 TABLE Descriptive statistics of child and household characteristics.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Variables</th><th align="left">Rural sample (<italic>N</italic> = 77)</th><th align="left">Peri‐urban sample (<italic>N</italic> = 81)</th><th align="left">Difference</th><th align="left"><italic>p</italic>‐Value</th></tr><tr><th align="left">(1)</th><th align="left">(2)</th><th align="left">(3) = (2) – (1)</th><th align="left">(4)</th></tr></thead><tbody valign="top"><tr><td align="left">Child characteristics</td></tr><tr><td align="left">Age, months, M (SD)</td><td align="char" char=".">21.88 (1.60)</td><td align="char" char=".">21.10 (1.60)</td><td align="char" char=".">−0.78 [0.25]</td><td align="char" char=".">.003</td></tr><tr><td align="left">Male (n, %)</td><td align="char" char=".">46 (59.74)</td><td align="char" char=".">46 (56.79)</td><td align="char" char=".">−0.03 [0.08]</td><td align="char" char=".">.709</td></tr><tr><td align="left">Household characteristics</td></tr><tr><td align="left">Age of mother, years, M (SD)</td><td align="char" char=".">27.52 (4.25)</td><td align="char" char=".">29.11 (4.69)</td><td align="char" char=".">1.59 [0.71]</td><td align="char" char=".">.027</td></tr><tr><td align="left">Mother completed associate degree or above (n, %)</td><td align="char" char=".">14 (18.18)</td><td align="char" char=".">42 (51.85)</td><td align="char" char=".">0.34 [0.07]</td><td align="char" char="."><.001</td></tr><tr><td align="left">Mother has a job (n, %)</td><td align="char" char=".">47 (61.04)</td><td align="char" char=".">51 (62.96)</td><td align="char" char=".">0.02 [0.08]</td><td align="char" char=".">.805</td></tr><tr><td align="left">Father completed associate degree or above (n, %)</td><td align="char" char=".">7 (9.09)</td><td align="char" char=".">42 (51.85)</td><td align="char" char=".">0.43 [0.07]</td><td align="char" char="."><.001</td></tr><tr><td align="left">Father lived at home for at least 6 months of the last year (n, %)</td><td align="char" char=".">24 (31.17)</td><td align="char" char=".">64 (79.01)</td><td align="char" char=".">0.48 [0.07]</td><td align="char" char="."><.001</td></tr><tr><td align="left">Number of adults in the household, M (SD)</td><td align="char" char=".">2.43 (1.08)</td><td align="char" char=".">3.05 (1.01)</td><td align="char" char=".">0.62 [0.17]</td><td align="char" char="."><.001</td></tr><tr><td align="left">Number of siblings in the household, M (SD)</td><td align="char" char=".">0.36 (0.51)</td><td align="char" char=".">0.12 (0.33)</td><td align="char" char=".">−0.24 [0.07]</td><td align="char" char="."><.001</td></tr><tr><td align="left">Asset index (PCA score)</td><td align="char" char=".">−0.50 (1.45)</td><td align="char" char=".">0.47 (1.07)</td><td align="char" char=".">0.97 [0.20]</td><td align="char" char="."><.001</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>: Standard errors are given in square brackets. The asset index principal component analysis (PCA) score was computed using a dimensionality reduction method, which created a visualization of data that minimized residual variance in the least squares sense and maximized the variance of the projection coordinates. The weights for each principal component were given by the eigenvectors of the correlation matrix or the covariance matrix (Krishnan, [<reflink idref="bib46" id="ref154">46</reflink>]).</p> <p>To determine whether the inclusion of these demographic information variables was valid for our study, we first used variance inflation factors (VIF) to test multicollinearity (Table S2). The VIF values are all less than 5, indicating that there was no collinearity problem. We next used Kernel density plots to test the distribution of the continuous covariates and analyzed the variances of the binary covariates. We found that all continuous covariates were normally distributed (Figures S6–S10) and that the variance of all binary covariates was appropriate for use in our analysis. Thus, we feel justified in our inclusion of all demographic variables in our analysis.</p> <hd id="AN0175750708-14">Analytic strategy</hd> <p>All statistical analyses were performed using STATA 16.1. Statistical significance was defined as two‐sided <emph>p</emph> < .05. To compare the HLE of rural and peri‐urban populations, we conducted T‐tests between the LENA outcomes of the rural and peri‐urban households. Outcomes are reported for the full samples, as well as for the top half (upper 50% above the median level) and bottom half (lower 50% below the median level) of the samples. To examine the correlations between the HLE and language development, and to identify specific household characteristics associated with differences in the HLE between rural and peri‐urban populations, multivariate multiple linear regressions were conducted. All demographic characteristics collected in our survey were included as potential confounders. The specific analytic models used can be found in Appendix S3.</p> <hd id="AN0175750708-15">RESULTS</hd> <p></p> <hd id="AN0175750708-16">Rural versus peri‐urban: How do HLE and child language development outcomes differ?</hd> <p>Table 2 summarizes the language development and HLE outcomes for the two samples. Regarding language development, the average CDI for the peri‐urban sample (37 [SD = 27]) was significantly lower than the average of the rural sample (54 [SD = 28]; <emph>p</emph> < .001). Moreover, the top half of peri‐urban households had an average score of 59 (SD = 21), which was significantly lower than that of the top half of rural households (77 [SD = 17], <emph>p</emph> < .001), while the bottom half had an average CDI score of 16 (SD = 10), which was also significantly lower than the bottom half of the rural sample (32 [SD = 16], <emph>p</emph> < .001).</p> <p>2 TABLE Home language environment outcome and language skill outcome differences between rural and peri‐urban children.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Groups</th><th align="left">Rural sample (<italic>N</italic> = 77)</th><th align="left">Peri‐urban sample (<italic>N</italic> = 81)</th><th align="left">Peri‐urban versus rural</th></tr><tr><th align="left">Observations</th><th align="left"><italic>M</italic> (SD)</th><th align="left">Observations</th><th align="left"><italic>M</italic> (SD)</th><th align="left">Difference</th><th align="left"><italic>p</italic>‐Value</th></tr><tr><th align="left">(1)</th><th align="left">(2)</th><th align="left">(3)</th><th align="left">(4)</th><th align="left">(5) = (4) – (2)</th><th align="left">(6)</th></tr></thead><tbody valign="top"><tr><td align="left">(1)</td><td align="left">Full sample AWC</td><td align="char" char=".">77</td><td align="char" char=".">15,783 (5597)</td><td align="char" char=".">81</td><td align="char" char=".">12,354 (5522)</td><td align="char" char=".">−3429 [885]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(2)</td><td align="left">Upper 50% AWC</td><td align="char" char=".">38</td><td align="char" char=".">20,046 (4386)</td><td align="char" char=".">40</td><td align="char" char=".">16,756 (4360)</td><td align="char" char=".">−3290 [991]</td><td align="char" char=".">.0014</td></tr><tr><td align="left">(3)</td><td align="left">Lower 50% AWC</td><td align="char" char=".">39</td><td align="char" char=".">11,630 (2838)</td><td align="char" char=".">41</td><td align="char" char=".">8059 (2040)</td><td align="char" char=".">−3571 [551]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(4)</td><td align="left">Full sample CTC</td><td align="char" char=".">77</td><td align="char" char=".">655 (297)</td><td align="char" char=".">81</td><td align="char" char=".">482 (262)</td><td align="char" char=".">−173 [44]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(5)</td><td align="left">Upper 50% CTC</td><td align="char" char=".">38</td><td align="char" char=".">890 (214)</td><td align="char" char=".">40</td><td align="char" char=".">682 (233)</td><td align="char" char=".">−208 [51]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(6)</td><td align="left">Lower 50% CTC</td><td align="char" char=".">39</td><td align="char" char=".">425 (151)</td><td align="char" char=".">41</td><td align="char" char=".">286 (71)</td><td align="char" char=".">−139 [26]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(7)</td><td align="left">Conversational turns in segments initiated by the focus child</td><td align="char" char=".">77</td><td align="char" char=".">313 (158)</td><td align="char" char=".">81</td><td align="char" char=".">232 (140)</td><td align="char" char=".">−81 [24]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(8)</td><td align="left">Upper 50% conversational turns in segments initiated by the focus child</td><td align="char" char=".">38</td><td align="char" char=".">441 (117)</td><td align="char" char=".">39</td><td align="char" char=".">332 (143)</td><td align="char" char=".">−109 [30]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(9)</td><td align="left">Lower 50% conversational turns in segments initiated by the focus child</td><td align="char" char=".">39</td><td align="char" char=".">189 (69)</td><td align="char" char=".">42</td><td align="char" char=".">140 (38)</td><td align="char" char=".">−49 [12]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(10)</td><td align="left">Conversational turns in segments initiated by a female adult</td><td align="char" char=".">77</td><td align="char" char=".">270 (136)</td><td align="char" char=".">81</td><td align="char" char=".">200 (122)</td><td align="char" char=".">−71 [20]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(11)</td><td align="left">Upper 50% conversational turns in segments initiated by a female adult</td><td align="char" char=".">38</td><td align="char" char=".">372 (115)</td><td align="char" char=".">40</td><td align="char" char=".">293 (107)</td><td align="char" char=".">−79 [25]</td><td align="char" char=".">.0026</td></tr><tr><td align="left">(12)</td><td align="left">Lower 50% conversational turns in segments initiated by a female adult</td><td align="char" char=".">39</td><td align="char" char=".">172 (61)</td><td align="char" char=".">41</td><td align="char" char=".">109 (34)</td><td align="char" char=".">−63 [11]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(13)</td><td align="left">Conversational turns in segments initiated by a male adult</td><td align="char" char=".">77</td><td align="char" char=".">59 (57)</td><td align="char" char=".">81</td><td align="char" char=".">47 (40)</td><td align="char" char=".">−12 [8]</td><td align="char" char=".">.1148</td></tr><tr><td align="left">(14)</td><td align="left">Upper 50% conversational turns in segments initiated by a male adult</td><td align="char" char=".">38</td><td align="char" char=".">98 (57)</td><td align="char" char=".">40</td><td align="char" char=".">74 (39)</td><td align="char" char=".">−24 [11]</td><td align="char" char=".">.0342</td></tr><tr><td align="left">(15)</td><td align="left">Lower 50% conversational turns in segments initiated by a male adult</td><td align="char" char=".">39</td><td align="char" char=".">21 (12)</td><td align="char" char=".">41</td><td align="char" char=".">20 (12)</td><td align="char" char=".">−1 [3]</td><td align="char" char=".">.6954</td></tr><tr><td align="left">(16)</td><td align="left">Number of segments initiated by the focus child</td><td align="char" char=".">77</td><td align="char" char=".">432 (149)</td><td align="char" char=".">81</td><td align="char" char=".">428 (102)</td><td align="char" char=".">−4 [20]</td><td align="char" char=".">.8435</td></tr><tr><td align="left">(17)</td><td align="left">Upper 50% number of segments initiated by the focus child</td><td align="char" char=".">38</td><td align="char" char=".">550 (102)</td><td align="char" char=".">40</td><td align="char" char=".">510 (53)</td><td align="char" char=".">−40 [18]</td><td align="char" char=".">.0316</td></tr><tr><td align="left">(18)</td><td align="left">Lower 50% number of segments initiated by the focus child</td><td align="char" char=".">39</td><td align="char" char=".">317 (81)</td><td align="char" char=".">41</td><td align="char" char=".">348 (70)</td><td align="char" char=".">31 [17]</td><td align="char" char=".">.0685</td></tr><tr><td align="left">(19)</td><td align="left">Number of segments initiated by a female adult</td><td align="char" char=".">77</td><td align="char" char=".">380 (105)</td><td align="char" char=".">81</td><td align="char" char=".">360 (122)</td><td align="char" char=".">−20 [18]</td><td align="char" char=".">.2633</td></tr><tr><td align="left">(20)</td><td align="left">Upper 50% number of segments initiated by a female adult</td><td align="char" char=".">38</td><td align="char" char=".">462 (62)</td><td align="char" char=".">40</td><td align="char" char=".">461 (83)</td><td align="char" char=".">−1 [17]</td><td align="char" char=".">.9554</td></tr><tr><td align="left">(21)</td><td align="left">Lower 50% number of segments initiated by a female adult</td><td align="char" char=".">39</td><td align="char" char=".">300 (70)</td><td align="char" char=".">41</td><td align="char" char=".">261 (52)</td><td align="char" char=".">−39 [14]</td><td align="char" char=".">.0051</td></tr><tr><td align="left">(22)</td><td align="left">Number of segments initiated by a male adult</td><td align="char" char=".">77</td><td align="char" char=".">108 (81)</td><td align="char" char=".">81</td><td align="char" char=".">129 (95)</td><td align="char" char=".">20 [14]</td><td align="char" char=".">.1471</td></tr><tr><td align="left">(23)</td><td align="left">Upper 50% number of segments initiated by a male adult</td><td align="char" char=".">38</td><td align="char" char=".">173 (68)</td><td align="char" char=".">40</td><td align="char" char=".">205 (79)</td><td align="char" char=".">32 [17]</td><td align="char" char=".">.0575</td></tr><tr><td align="left">(24)</td><td align="left">Lower 50% number of segments initiated by a male adult</td><td align="char" char=".">39</td><td align="char" char=".">46 (21)</td><td align="char" char=".">41</td><td align="char" char=".">55 (24)</td><td align="char" char=".">9 [5]</td><td align="char" char=".">.0795</td></tr><tr><td align="left">(25)</td><td align="left">Full sample CVC</td><td align="char" char=".">77</td><td align="char" char=".">2142 (863)</td><td align="char" char=".">81</td><td align="char" char=".">1734 (749)</td><td align="char" char=".">−408 [128]</td><td align="char" char=".">.0018</td></tr><tr><td align="left">(26)</td><td align="left">Upper 50% CVC</td><td align="char" char=".">38</td><td align="char" char=".">2830 (614)</td><td align="char" char=".">40</td><td align="char" char=".">2272 (705)</td><td align="char" char=".">−558 [150]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(27)</td><td align="left">Lower 50% CVC</td><td align="char" char=".">39</td><td align="char" char=".">1472 (435)</td><td align="char" char=".">41</td><td align="char" char=".">1209 (255)</td><td align="char" char=".">−263 [79]</td><td align="char" char=".">.0014</td></tr><tr><td align="left">(28)</td><td align="left">Full sample CDI</td><td align="char" char=".">77</td><td align="char" char=".">54 (28)</td><td align="char" char=".">81</td><td align="char" char=".">37 (27)</td><td align="char" char=".">−17 [4]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(29)</td><td align="left">Upper 50% CDI</td><td align="char" char=".">37</td><td align="char" char=".">77 (17)</td><td align="char" char=".">39</td><td align="char" char=".">59 (21)</td><td align="char" char=".">−18 [4]</td><td align="char" char="."><.001</td></tr><tr><td align="left">(30)</td><td align="left">Lower 50% CDI</td><td align="char" char=".">40</td><td align="char" char=".">32 (16)</td><td align="char" char=".">42</td><td align="char" char=".">16 (10)</td><td align="char" char=".">−16 [3]</td><td align="char" char="."><.001</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 <emph>Note</emph>: All AWC, CTC, and CVC are averaged with 2‐day recordings; Standard deviations in parentheses; and Standard errors in square brackets.</item> <item>3 <emph>Source</emph>: Authors' survey.</item> <item>4 Abbreviations: AWC, adult word count; CDI, MacArthur–Bates Communicative Development Inventories; CTC, conversational turn count; CVC, child vocalization count.</item> </ulist> <p>We found large variations and significant differences between rural and peri‐urban households across all LENA measures. The average AWC of peri‐urban households was 12,354 (SD = 5522), which was significantly lower than that of rural households (15,783 [SD = 5597], <emph>p</emph> < .001). The average CTC for the peri‐urban sample was also significantly lower than that of rural households (482 [SD = 262] and 655 [SD = 297], respectively, <emph>p</emph> < .001), as was the average CVC (1734 [SD = 749] for peri‐urban and 2142 [SD = 683] for rural, <emph>p</emph> < .0018). The average CTS initiated by the focus child for the peri‐urban sample was significantly lower than for the rural sample (232 [SD = 140] and 313 [SD = 158], respectively, <emph>p</emph> < .001), and the average CTS initiated by a female adult for the peri‐urban sample was also significantly lower than that of the rural sample (200 [SD = 122] and 270 [SD = 136], respectively, <emph>p</emph> < .001). Among the bottom half of households for AWC, children living in rural households (11,630 [SD = 2838]) heard significantly more adult words than children in peri‐urban households (8059 [SD = 2040]; <emph>p</emph> < .001). Moreover, peri‐urban households in both the top half and bottom half of CTC had significantly fewer conversational turns than rural households (<emph>p</emph> < .001). To check the robustness of these results, we ran a multivariate analysis (Table S3), which confirmed the results in Table 2.</p> <hd id="AN0175750708-17">Links between household characteristics and the HLE</hd> <p>Tables 3–5 display results from multivariate multiple linear regression analyses between household characteristics and the HLE. First, Table 3 shows the multivariate multiple linear correlations for the combined rural and peri‐urban samples. Higher child age was significantly associated with higher CTC (<emph>p</emph> < .01), CVC (<emph>p</emph> < .01), and CTS initiated by the focus child (<emph>p</emph> < .01). Higher child age was also significantly associated with lower NS initiated by a female adult (<emph>p</emph> < .05). Children whose mothers had a job had higher CTS initiated by the focus child (<emph>p</emph> < .05) and CTS initiated by a female adult (<emph>p</emph> < .05). Children whose fathers lived at home for at least 6 months of the last year had lower NS initiated by a female adult (<emph>p</emph> < .05). Finally, having more siblings in the household was significantly and negatively associated with CTS initiated by a male adult (<emph>p</emph> < .05).</p> <p>3 TABLE Multivariate correlations between household characteristics and adult word count (AWC), conversational turn count (CTC), child vocalization count (CVC), and initiation of conversational turns (CT) in audio segments in rural and peri‐urban samples.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Variables</th><th align="left">lnAWC</th><th align="left">lnCTC</th><th align="left">lnCVC</th><th align="left">ln(CTS initiated by the focus child)</th><th align="left">ln(CTS initiated by a female adult)</th><th align="left">ln(CTS initiated by a male adult)</th><th align="left">ln(NS initiated by the focus child)</th><th align="left">ln(NS initiated by a female adult)</th><th align="left">ln(NS initiated by a male adult)</th></tr><tr><th align="left">(1)</th><th align="left">(2)</th><th align="left">(3)</th><th align="left">(4)</th><th align="left">(5)</th><th align="left">(6)</th><th align="left">(7)</th><th align="left">(8)</th><th align="left">(9)</th></tr></thead><tbody valign="top"><tr><td align="left">(1)</td><td align="left">Age of child (months)</td><td align="char" char=".">.03 (.02)</td><td align="char" char=".">.07<xref ref-type="fn" rid="tfn9" /> (.03)</td><td align="char" char=".">.08<xref ref-type="fn" rid="tfn9" /> (.02)</td><td align="char" char=".">.08<xref ref-type="fn" rid="tfn9" /> (.03)</td><td align="char" char=".">.04 (.03)</td><td align="char" char=".">.03 (.05)</td><td align="char" char=".">.02 (.02)</td><td align="char" char=".">−.04<xref ref-type="fn" rid="tfn8" /> (.02)</td><td align="char" char=".">−.03 (.04)</td></tr><tr><td align="left">(2)</td><td align="left">Male (1 = yes)</td><td align="char" char=".">−.01 (.08)</td><td align="char" char=".">−.08 (.09)</td><td align="char" char=".">−.04 (.08)</td><td align="char" char=".">−.04 (.10)</td><td align="char" char=".">−.07 (.10)</td><td align="char" char=".">−.07 (.18)</td><td align="char" char=".">.04 (.06)</td><td align="char" char=".">−.02 (.06)</td><td align="char" char=".">−.12 (.14)</td></tr><tr><td align="left">(3)</td><td align="left">Age of mother (years)</td><td align="char" char=".">.01 (.01)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">−.00 (.01)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">.02 (.02)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">.03 (.02)</td></tr><tr><td align="left">(4)</td><td align="left">Mother completed associate degree or above (1 = yes)</td><td align="char" char=".">.06 (.10)</td><td align="char" char=".">.12 (.12)</td><td align="char" char=".">.10 (.10)</td><td align="char" char=".">.16 (.12)</td><td align="char" char=".">.21 (.13)</td><td align="char" char=".">.05 (.22)</td><td align="char" char=".">.06 (.08)</td><td align="char" char=".">.03 (.07)</td><td align="char" char=".">−.15 (.18)</td></tr><tr><td align="left">(5)</td><td align="left">Mother has a job (1 = yes)</td><td align="char" char=".">.14 (.07)</td><td align="char" char=".">.17 (.09)</td><td align="char" char=".">.07 (.07)</td><td align="char" char=".">.22<xref ref-type="fn" rid="tfn8" /> (.09)</td><td align="char" char=".">.21<xref ref-type="fn" rid="tfn8" /> (.10)</td><td align="char" char=".">.28 (.17)</td><td align="char" char=".">.04 (.06)</td><td align="char" char=".">.07 (.06)</td><td align="char" char=".">.14 (.14)</td></tr><tr><td align="left">(6)</td><td align="left">Father completed associate degree or above (1 = yes)</td><td align="char" char=".">−.14 (.10)</td><td align="char" char=".">−.11 (.12)</td><td align="char" char=".">−.04 (.10)</td><td align="char" char=".">−.10 (.13)</td><td align="char" char=".">−.21 (.13)</td><td align="char" char=".">−.08 (.23)</td><td align="char" char=".">.03 (.08)</td><td align="char" char=".">−.07 (.08)</td><td align="char" char=".">.22 (.19)</td></tr><tr><td align="left">(7)</td><td align="left">Father lived at home for at least 6 months of the last year (1 = yes)</td><td align="char" char=".">−.13 (.08)</td><td align="char" char=".">−.14 (.10)</td><td align="char" char=".">−.07 (.08)</td><td align="char" char=".">−.21 (.11)</td><td align="char" char=".">−.21 (.11)</td><td align="char" char=".">−.13 (.19)</td><td align="char" char=".">−.06 (.07)</td><td align="char" char=".">−.13<xref ref-type="fn" rid="tfn8" /> (.06)</td><td align="char" char=".">.11 (.16)</td></tr><tr><td align="left">(8)</td><td align="left">Number of adults in the household</td><td align="char" char=".">.00 (.04)</td><td align="char" char=".">−.01 (.05)</td><td align="char" char=".">.01 (.04)</td><td align="char" char=".">.01 (.05)</td><td align="char" char=".">.01 (.05)</td><td align="char" char=".">−.02 (.09)</td><td align="char" char=".">.04 (.03)</td><td align="char" char=".">.04 (.03)</td><td align="char" char=".">−.04 (.07)</td></tr><tr><td align="left">(9)</td><td align="left">Number of siblings in the household</td><td align="char" char=".">−.14 (.09)</td><td align="char" char=".">−.19 (.11)</td><td align="char" char=".">−.07 (.09)</td><td align="char" char=".">−.18 (.11)</td><td align="char" char=".">−.14 (.12)</td><td align="char" char=".">−.48<xref ref-type="fn" rid="tfn8" /> (.20)</td><td align="char" char=".">−.02 (.07)</td><td align="char" char=".">−.09 (.07)</td><td align="char" char=".">−.18 (.16)</td></tr><tr><td align="left">(10)</td><td align="left">Asset index (PCA score)</td><td align="char" char=".">−.02 (.03)</td><td align="char" char=".">−.02 (.03)</td><td align="char" char=".">−.03 (.03)</td><td align="char" char=".">−.01 (.04)</td><td align="char" char=".">.01 (.04)</td><td align="char" char=".">−.00 (.07)</td><td align="char" char=".">−.02 (.02)</td><td align="char" char=".">−.01 (.02)</td><td align="char" char=".">−.02 (.05)</td></tr><tr><td align="left">(11)</td><td align="left">Observations</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td><td align="char" char=".">158</td></tr><tr><td align="left">(12)</td><td align="left">R<sup>2</sup></td><td align="char" char=".">.10</td><td align="char" char=".">.13</td><td align="char" char=".">.13</td><td align="char" char=".">.15</td><td align="char" char=".">.11</td><td align="char" char=".">.07</td><td align="char" char=".">.04</td><td align="char" char=".">.09</td><td align="char" char=".">.06</td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 <emph>Note</emph>: Standard errors in parentheses. One unit increase [controls factor] is associated with 100 × beta percent change in home language environment outcomes.</item> <item>6 <emph>Source</emph>: Authors' survey.</item> <item>7 Abbreviations: CTS, the number of conversational turns within segments; NS, the number of segments; PCA, principal component analysis.</item> <item>8 * <emph>p</emph> < .05;</item> <item>9 ** <emph>p</emph> < .01.</item> <item>4 TABLE Multivariate correlations between household characteristics and adult word count (AWC), conversational turn count (CTC), child vocalization count (CVC), and initiation of conversational turns (CT) in audio segments in the rural sample.</item> </ulist> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Variables</th><th align="left">lnAWC</th><th align="left">lnCTC</th><th align="left">lnCVC</th><th align="left">ln(CTS initiated by the focus child)</th><th align="left">ln(CTS initiated by a female adult)</th><th align="left">ln(CTS initiated by a male adult)</th><th align="left">ln(NS initiated by the focus child)</th><th align="left">ln(NS initiated by a female adult)</th><th align="left">ln(NS initiated by a male adult)</th></tr><tr><th align="left">(1)</th><th align="left">(2)</th><th align="left">(3)</th><th align="left">(4)</th><th align="left">(5)</th><th align="left">(6)</th><th align="left">(7)</th><th align="left">(8)</th><th align="left">(9)</th></tr></thead><tbody valign="top"><tr><td align="left">(1)</td><td align="left">Age of child (months)</td><td align="char" char=".">.03 (.03)</td><td align="char" char=".">.05 (.04)</td><td align="char" char=".">.07<xref ref-type="fn" rid="tfn13" /> (.04)</td><td align="char" char=".">.07 (.04)</td><td align="char" char=".">.01 (.04)</td><td align="char" char=".">.06 (.07)</td><td align="char" char=".">.03 (.03)</td><td align="char" char=".">−.03 (.02)</td><td align="char" char=".">.04 (.06)</td></tr><tr><td align="left">(2)</td><td align="left">Male (1 = yes)</td><td align="char" char=".">.21<xref ref-type="fn" rid="tfn13" /> (.09)</td><td align="char" char=".">.21 (.13)</td><td align="char" char=".">.17 (.12)</td><td align="char" char=".">.27 (.14)</td><td align="char" char=".">.23 (.14)</td><td align="char" char=".">.00 (.26)</td><td align="char" char=".">.10 (.10)</td><td align="char" char=".">.09 (.08)</td><td align="char" char=".">−.10 (.20)</td></tr><tr><td align="left">(3)</td><td align="left">Age of mother (years)</td><td align="char" char=".">.01 (.01)</td><td align="char" char=".">.01 (.02)</td><td align="char" char=".">.00 (.02)</td><td align="char" char=".">.01 (.02)</td><td align="char" char=".">.02 (.02)</td><td align="char" char=".">.02 (.03)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">.01 (.01)</td><td align="char" char=".">.02 (.03)</td></tr><tr><td align="left">(4)</td><td align="left">Mother completed associate degree or above (1 = yes)</td><td align="char" char=".">.21 (.15)</td><td align="char" char=".">.18 (.21)</td><td align="char" char=".">.04 (.20)</td><td align="char" char=".">.24 (.23)</td><td align="char" char=".">.34 (.22)</td><td align="char" char=".">.02 (.41)</td><td align="char" char=".">.03 (.16)</td><td align="char" char=".">.14 (.13)</td><td align="char" char=".">−.27 (.32)</td></tr><tr><td align="left">(5)</td><td align="left">Mother has a job (1 = yes)</td><td align="char" char=".">.11 (.09)</td><td align="char" char=".">.20 (.13)</td><td align="char" char=".">.12 (.12)</td><td align="char" char=".">.33<xref ref-type="fn" rid="tfn13" /> (.14)</td><td align="char" char=".">.22 (.14)</td><td align="char" char=".">.35 (.26)</td><td align="char" char=".">.19 (.10)</td><td align="char" char=".">.03 (.08)</td><td align="char" char=".">.28 (.20)</td></tr><tr><td align="left">(6)</td><td align="left">Father completed associate degree or above (1 = yes)</td><td align="char" char=".">−.02 (.19)</td><td align="char" char=".">.10 (.28)</td><td align="char" char=".">.16 (.26)</td><td align="char" char=".">.11 (.30)</td><td align="char" char=".">−.04 (.29)</td><td align="char" char=".">.68 (.54)</td><td align="char" char=".">.19 (.21)</td><td align="char" char=".">−.01 (.17)</td><td align="char" char=".">1.02<xref ref-type="fn" rid="tfn13" /> (.42)</td></tr><tr><td align="left">(7)</td><td align="left">Father lived at home for at least 6 months of the last year (1 = yes)</td><td align="char" char=".">−.01 (.11)</td><td align="char" char=".">.07 (.15)</td><td align="char" char=".">.04 (.14)</td><td align="char" char=".">−.00 (.16)</td><td align="char" char=".">.08 (.16)</td><td align="char" char=".">.06 (.30)</td><td align="char" char=".">−.08 (.12)</td><td align="char" char=".">−.08 (.10)</td><td align="char" char=".">−.01 (.23)</td></tr><tr><td align="left">(8)</td><td align="left">Number of adults in the household</td><td align="char" char=".">−.06 (.05)</td><td align="char" char=".">−.09 (.07)</td><td align="char" char=".">−.02 (.06)</td><td align="char" char=".">−.05 (.07)</td><td align="char" char=".">−.10 (.07)</td><td align="char" char=".">−.17 (.13)</td><td align="char" char=".">.05 (.05)</td><td align="char" char=".">−.00 (.04)</td><td align="char" char=".">−.12 (.10)</td></tr><tr><td align="left">(9)</td><td align="left">Number of siblings in the household</td><td align="char" char=".">−.20<xref ref-type="fn" rid="tfn13" /> (.09)</td><td align="char" char=".">−.28<xref ref-type="fn" rid="tfn13" /> (.14)</td><td align="char" char=".">−.10 (.13)</td><td align="char" char=".">−.23 (.14)</td><td align="char" char=".">−.25 (.14)</td><td align="char" char=".">−.49 (.26)</td><td align="char" char=".">.02 (.10)</td><td align="char" char=".">−.12 (.08)</td><td align="char" char=".">−.14 (.21)</td></tr><tr><td align="left">(10)</td><td align="left">Asset index (PCA score)</td><td align="char" char=".">−.02 (.03)</td><td align="char" char=".">−.02 (.04)</td><td align="char" char=".">−.03 (.04)</td><td align="char" char=".">−.02 (.05)</td><td align="char" char=".">−.00 (.04)</td><td align="char" char=".">.02 (.08)</td><td align="char" char=".">−.01 (.03)</td><td align="char" char=".">−.02 (.03)</td><td align="char" char=".">.03 (.07)</td></tr><tr><td align="left">(11)</td><td align="left">Observations</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td><td align="char" char=".">77</td></tr><tr><td align="left">(12)</td><td align="left">R<sup>2</sup></td><td align="char" char=".">.22</td><td align="char" char=".">.20</td><td align="char" char=".">.13</td><td align="char" char=".">.23</td><td align="char" char=".">.19</td><td align="char" char=".">.17</td><td align="char" char=".">.14</td><td align="char" char=".">.13</td><td align="char" char=".">.17</td></tr></tbody></table> </ephtml> </p> <ulist> <item>10 <emph>Note</emph>: Standard errors in parentheses. One unit increase [controls factor] is associated with 100 × beta percent change in home language environment outcomes.</item> <item>11 <emph>Source</emph>: Authors' survey.</item> <item>12 Abbreviations: CTS, the number of conversational turns within segments; NS, the number of segments; PCA, principal component analysis.</item> <item>13 * <emph>p</emph> < .05;</item> <item>14 ** <emph>p</emph> < .01.</item> <item>5 TABLE Multivariate correlations between household characteristics and adult word count (AWC), conversational turn count (CTC), child vocalization count (CVC), and initiation of conversational turns (CT) in audio segments in the peri‐urban sample.</item> </ulist> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Variables</th><th align="left">lnAWC</th><th align="left">lnCTC</th><th align="left">lnCVC</th><th align="left">ln(CTS initiated by the focus child)</th><th align="left">ln(CTS initiated by a female adult)</th><th align="left">ln(CTS initiated by a male adult)</th><th align="left">ln(NS initiated by the focus child)</th><th align="left">ln(NS initiated by a female adult)</th><th align="left">ln(NS initiated by a male adult)</th></tr><tr><th align="left">(1)</th><th align="left">(2)</th><th align="left">(3)</th><th align="left">(4)</th><th align="left">(5)</th><th align="left">(6)</th><th align="left">(7)</th><th align="left">(8)</th><th align="left">(9)</th></tr></thead><tbody valign="top"><tr><td align="left">(1)</td><td align="left">Age of child (months)</td><td align="char" char=".">−.02 (.03)</td><td align="char" char=".">.05 (.04)</td><td align="char" char=".">.08<xref ref-type="fn" rid="tfn19" /> (.03)</td><td align="char" char=".">.05 (.04)</td><td align="char" char=".">.02 (.04)</td><td align="char" char=".">−.08 (.08)</td><td align="char" char=".">.02 (.02)</td><td align="char" char=".">−.06<xref ref-type="fn" rid="tfn18" /> (.03)</td><td align="char" char=".">−.13<xref ref-type="fn" rid="tfn18" /> (.06)</td></tr><tr><td align="left">(2)</td><td align="left">Male (1 = yes)</td><td align="char" char=".">−.24<xref ref-type="fn" rid="tfn18" /> (.11)</td><td align="char" char=".">−.37<xref ref-type="fn" rid="tfn19" /> (.12)</td><td align="char" char=".">−.27<xref ref-type="fn" rid="tfn19" /> (.09)</td><td align="char" char=".">−.34<xref ref-type="fn" rid="tfn19" /> (.12)</td><td align="char" char=".">−.38<xref ref-type="fn" rid="tfn19" /> (.14)</td><td align="char" char=".">−.02 (.25)</td><td align="char" char=".">.02 (.08)</td><td align="char" char=".">−.12 (.09)</td><td align="char" char=".">.08 (.21)</td></tr><tr><td align="left">(3)</td><td align="left">Age of mother (years)</td><td align="char" char=".">.02 (.01)</td><td align="char" char=".">.01 (.01)</td><td align="char" char=".">−.00 (.01)</td><td align="char" char=".">.01 (.01)</td><td align="char" char=".">.01 (.01)</td><td align="char" char=".">.04 (.03)</td><td align="char" char=".">−.01 (.01)</td><td align="char" char=".">.00 (.01)</td><td align="char" char=".">.04 (.02)</td></tr><tr><td align="left">(4)</td><td align="left">Mother completed associate degree or above (1 = yes)</td><td align="char" char=".">−.08 (.13)</td><td align="char" char=".">.07 (.13)</td><td align="char" char=".">.12 (.10)</td><td align="char" char=".">.10 (.14)</td><td align="char" char=".">.14 (.15)</td><td align="char" char=".">−.11 (.28)</td><td align="char" char=".">.04 (.09)</td><td align="char" char=".">−.07 (.10)</td><td align="char" char=".">−.33 (.23)</td></tr><tr><td align="left">(5)</td><td align="left">Mother has a job (1 = yes)</td><td align="char" char=".">.23<xref ref-type="fn" rid="tfn18" /> (.11)</td><td align="char" char=".">.21 (.11)</td><td align="char" char=".">.08 (.09)</td><td align="char" char=".">.19 (.12)</td><td align="char" char=".">.26<xref ref-type="fn" rid="tfn18" /> (.13)</td><td align="char" char=".">.26 (.24)</td><td align="char" char=".">−.09 (.07)</td><td align="char" char=".">.12 (.08)</td><td align="char" char=".">.00 (.20)</td></tr><tr><td align="left">(6)</td><td align="left">Father completed associate degree or above (1 = yes)</td><td align="char" char=".">−.02 (.13)</td><td align="char" char=".">−.02 (.14)</td><td align="char" char=".">−.04 (.11)</td><td align="char" char=".">−.03 (.14)</td><td align="char" char=".">−.10 (.16)</td><td align="char" char=".">−.04 (.29)</td><td align="char" char=".">−.03 (.09)</td><td align="char" char=".">−.05 (.10)</td><td align="char" char=".">.17 (.24)</td></tr><tr><td align="left">(7)</td><td align="left">Father lived at home for at least 6 months of the last year (1 = yes)</td><td align="char" char=".">−.00 (.14)</td><td align="char" char=".">−.12 (.15)</td><td align="char" char=".">−.12 (.12)</td><td align="char" char=".">−.21 (.16)</td><td align="char" char=".">−.25 (.17)</td><td align="char" char=".">.20 (.32)</td><td align="char" char=".">−.07 (.10)</td><td align="char" char=".">−.10 (.11)</td><td align="char" char=".">.52 (.26)</td></tr><tr><td align="left">(8)</td><td align="left">Number of adults in the household</td><td align="char" char=".">.02 (.06)</td><td align="char" char=".">.02 (.06)</td><td align="char" char=".">.01 (.05)</td><td align="char" char=".">.03 (.06)</td><td align="char" char=".">.06 (.07)</td><td align="char" char=".">.08 (.13)</td><td align="char" char=".">.04 (.04)</td><td align="char" char=".">.06 (.04)</td><td align="char" char=".">.03 (.10)</td></tr><tr><td align="left">(9)</td><td align="left">Number of siblings in the household</td><td align="char" char=".">−.28 (.17)</td><td align="char" char=".">−.40<xref ref-type="fn" rid="tfn18" /> (.18)</td><td align="char" char=".">−.30<xref ref-type="fn" rid="tfn18" /> (.14)</td><td align="char" char=".">−.39<xref ref-type="fn" rid="tfn18" /> (.19)</td><td align="char" char=".">−.39 (.21)</td><td align="char" char=".">−.43 (.38)</td><td align="char" char=".">−.05 (.12)</td><td align="char" char=".">−.16 (.13)</td><td align="char" char=".">.06 (.31)</td></tr><tr><td align="left">(10)</td><td align="left">Asset index (PCA score)</td><td align="char" char=".">.05 (.05)</td><td align="char" char=".">.07 (.06)</td><td align="char" char=".">.01 (.04)</td><td align="char" char=".">.08 (.06)</td><td align="char" char=".">.11 (.06)</td><td align="char" char=".">.10 (.12)</td><td align="char" char=".">−.01 (.04)</td><td align="char" char=".">.03 (.04)</td><td align="char" char=".">.00 (.10)</td></tr><tr><td align="left">(11)</td><td align="left">Observations</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td><td align="char" char=".">81</td></tr><tr><td align="left">(12)</td><td align="left">R<sup>2</sup></td><td align="char" char=".">.16</td><td align="char" char=".">.27</td><td align="char" char=".">.28</td><td align="char" char=".">.25</td><td align="char" char=".">.27</td><td align="char" char=".">.10</td><td align="char" char=".">.05</td><td align="char" char=".">.18</td><td align="char" char=".">.14</td></tr></tbody></table> </ephtml> </p> <ulist> <item>15 <emph>Note</emph>: Standard errors in parentheses. One unit increase [controls factor] is associated with 100 × beta percent change in home language environment outcomes.</item> <item>16 <emph>Source</emph>: Authors' survey.</item> <item>17 Abbreviations: CTS, the number of conversational turns within segments; NS, the number of segments; PCA, principal component analysis.</item> <item>18 * <emph>p</emph> < .05;</item> <item>19 ** <emph>p</emph> < .01.</item> </ulist> <p>Table 4 shows the results of multivariate multiple linear correlations between household characteristics and the HLE for the rural sample. Older children were significantly associated with higher CVC (<emph>p</emph> < .05). Boys were significantly associated with higher AWC (<emph>p</emph> < .05). Children whose mothers had a job had higher CTS initiated by the focus child (<emph>p</emph> < .05), while children whose fathers had completed an associate degree or above had higher NS initiated by a male adult (<emph>p</emph> < .05). Having more siblings in the household was significantly associated with lower AWC (<emph>p</emph> < .05) and lower CTC (<emph>p</emph> < .05).</p> <p>Table 5 shows the multivariate multiple linear regression results between household characteristics and the HLE for the peri‐urban sample. Similar to the rural sample, older children were significantly associated with higher CVC (<emph>p</emph> < .01). Higher child age was significantly associated with lower NS initiated by a female adult (<emph>p</emph> < .05) and NS initiated by a male adult (<emph>p</emph> < .05). In contrast with the rural sample, however, boys tended to have lower AWC (<emph>p</emph> < .05), CTC (<emph>p</emph> < .01), CVC (<emph>p</emph> < .01), and CTS initiated by the focus child (<emph>p</emph> < .01), and CTS initiated by a female adult (<emph>p</emph> < .01). Children whose mothers had a job had higher AWC (<emph>p</emph> < .05) and CTS initiated by a female adult (<emph>p</emph> < .05) while having more siblings in the household was significantly associated with lower CTC (<emph>p</emph> < .05), CVC (<emph>p</emph> < .05), and CTS initiated by the focus child (<emph>p</emph> < .05).</p> <hd id="AN0175750708-18">Associations between the HLE and language development</hd> <p>Finally, Table 6 presents multivariate multiple linear associations between the HLE and language development. We found strong positive correlations between HLE measures (AWC, CTC, CVC, CTS initiated by the focus child, and CTS initiated by a female adult) and CDI <emph>z</emph>‐scores. NS initiated by a male adult was negatively and insignificantly correlated with CDI. The same results were also found in the exclusively rural and exclusively peri‐urban samples, as shown in Table S4a,b, respectively.</p> <p>6 TABLE Correlations between adult word count (AWC), conversational turn count (CTC), child vocalization count (CVC), and initiation of conversational turns (CT) in audio segments and CDI in rural and peri‐urban samples.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Variables</th><th align="left">CDI <italic>z</italic>‐score</th></tr><tr><th align="left">(1)</th><th align="left">(2)</th><th align="left">(3)</th><th align="left">(4)</th><th align="left">(5)</th><th align="left">(6)</th><th align="left">(7)</th><th align="left">(8)</th><th align="left">(9)</th></tr></thead><tbody valign="top"><tr><td align="left">(1)</td><td align="left">lnAWC</td><td align="left">.64<xref ref-type="fn" rid="tfn24" /> (.16)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">(2)</td><td align="left">lnCTC</td><td align="left" /><td align="left">.61<xref ref-type="fn" rid="tfn24" /> (.13)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">(3)</td><td align="left">lnCVC</td><td align="left" /><td align="left" /><td align="left">.68<xref ref-type="fn" rid="tfn24" /> (.15)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">(4)</td><td align="left">ln(CTS initiated by the focus child)</td><td align="left" /><td align="left" /><td align="left" /><td align="left">.53<xref ref-type="fn" rid="tfn24" /> (.12)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">(5)</td><td align="left">ln(CTS initiated by a female adult)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left">.56<xref ref-type="fn" rid="tfn24" /> (.11)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">(6)</td><td align="left">ln(CTS initiated by a male adult)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left">.03 (.07)</td><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left">(7)</td><td align="left">ln(NS initiated by the focus child)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left">.21 (.21)</td><td align="left" /><td align="left" /></tr><tr><td align="left">(8)</td><td align="left">ln(NS initiated by a female adult)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left">.56<xref ref-type="fn" rid="tfn24" /> (.21)</td><td align="left" /></tr><tr><td align="left">(9)</td><td align="left">ln(NS initiated by a male adult)</td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left">−.12 (.09)</td></tr><tr><td align="left">(10)</td><td align="left">Controls</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td><td align="left">Yes</td></tr><tr><td align="left">(11)</td><td align="left">Observations</td><td align="left">158</td><td align="left">158</td><td align="left">158</td><td align="left">158</td><td align="left">158</td><td align="left">158</td><td align="left">158</td><td align="left">158</td><td align="left">158</td></tr><tr><td align="left">(12)</td><td align="left">R<sup>2</sup></td><td align="left">.38</td><td align="left">.40</td><td align="left">.39</td><td align="left">.39</td><td align="left">.41</td><td align="left">.31</td><td align="left">.31</td><td align="left">.34</td><td align="left">.32</td></tr></tbody></table> </ephtml> </p> <ulist> <item>20 <emph>Note</emph>: Standard errors in parentheses. 1% increase [home language environment outcomes] is associated with beta/100 SD change in CDI <emph>z</emph>‐score. Each regression equation controlled the characteristics of the child (including child's gender and age in months) and of households (including mother's age (in years), whether the mother had completed an associate degree or above, whether the mother had a job, whether the father had completed an associate degree or above, whether the father had lived at home for at least 6 months of the last year, the total number of adults in the household, and the total number of siblings of the focus child living in the household).</item> <item>21 Source: Authors' survey.</item> <item>22 Abbreviations: CDI, MacArthur–Bates Communicative Development Inventories; NS, the number of segments.</item> <item>23 * <emph>p</emph> < .05;</item> <item>24 ** <emph>p</emph> < .01.</item> </ulist> <hd id="AN0175750708-19">DISCUSSION</hd> <p>Developmental delays are a serious health issue for children under the age of 3 years in China, especially among low‐SES and rural populations (Emmers et al., [<reflink idref="bib26" id="ref155">26</reflink>]; Ma et al., [<reflink idref="bib54" id="ref156">54</reflink>]). New research that investigates how the HLE interacts with language development may be a key to improving ECD outcomes for children from low‐SES backgrounds, including peri‐urban children in rapidly urbanizing areas in LMICs. No previous study of language development in LMICs has systematically compared the HLE and language development outcomes of peri‐urban children with their rural peers. This study provides new insight by presenting the first‐ever quantification and objective comparison of the HLE, measured using LENA technology, and language development of children aged 18–24 months in two understudied populations in China.</p> <p>Three overarching takeaways are visible from our results. First, we found that a significant gap in HLE outcomes exists between children from peri‐urban and rural households. Significant differences in language development are also observed, with children from peri‐urban households showing significantly lower CDI scores and CVC. Second, we found that specific demographic characteristics (such as child age, child gender, maternal employment, and number of siblings) were positively correlated with measures of the HLE in both the rural and peri‐urban populations. Third, we found evidence of significant correlations between the HLE and language development in both the rural and peri‐urban populations. Ultimately, we found that despite enjoying various advantages including higher parental educational achievement, lower parental migration, and greater family assets, peri‐urban children both heard less and said less than their rural peers.</p> <p>Comparing the HLE and language development of children aged 18–24 months in peri‐urban China and those in rural China, we found that peri‐urban children hear significantly less adult speech and have significantly lower language development. As peri‐urban children appeared to be at a high risk of language delay despite having equal or higher SES than their rural peers, this suggests that other underlying factors besides SES contributed to their delayed language development. The CDI scores of the peri‐urban children indicated that they were at the greatest risk of language delay, as the full peri‐urban sample, top half, and bottom half were 17, 18, and 16 CDI points below the scores of the full rural sample, top half, and bottom half, respectively. The bottom half of the peri‐urban sample was particularly concerning, as peri‐urban children in the bottom half scored 16 out of 113, only half the score from children in the bottom half of the rural sample (32 out of 113). Supporting these findings, CVC, another indicator of language development, was lower for peri‐urban children than rural children across the full sample, as well as in the top half and bottom half of the sample. While these language development scores reveal concerning trends in both rural and peri‐urban households, the population most urgently in need of attention appears to be the bottom half of the peri‐urban sample. The poor language development of children in these populations is a significant problem that has gone largely uninvestigated up to this point.</p> <p>One possible explanation for the poor language development of peri‐urban children in comparison with rural children is the differences in the HLE of the two samples. In almost all measures of the HLE, we found that peri‐urban children were falling behind their rural peers. Peri‐urban children heard fewer adult words, had fewer conversations with adults, and made fewer vocalizations than rural children. In terms of AWC, peri‐urban children lagged behind their rural peers by 3429 words, on average, with this gap increasing to 3571 words when we focused on the lower half of AWC. The number of adult–child conversations was also significantly lower in peri‐urban households than in rural households (across the full sample and within the top and bottom halves of CTC). More specifically, children from peri‐urban households initiated 109 fewer conversational turns with adults, on average, than children from rural China, with an even larger gap between the two samples seen in the top half of these scores. This pattern also applied to CTS initiated by female adults, as peri‐urban female adults initiated significantly fewer conversational turns (<reflink idref="bib71" id="ref157">71</reflink>) than rural female adults. These findings suggest that peri‐urban caregivers, especially female caregivers, made fewer contributions to the HLE than rural caregivers. Furthermore, peri‐urban children made fewer vocalizations than rural children, especially among children who scored in the upper half of CTC for the two samples.</p> <p>One possible reason for the differences between the HLE of rural and peri‐urban households may be the unique challenges that urbanized farmers and rural migrants face in peri‐urban areas—challenges that are not faced in rural areas. For example, after having their property taken through forced land dispossession during the urbanization process, urbanized farmers are often forced to find non‐farming jobs they have no previous training for, or are forced to take on more low‐paying part‐time jobs to compensate for the reduction in income (Buckingham & Chan, [<reflink idref="bib10" id="ref158">10</reflink>]; Tong et al., [<reflink idref="bib79" id="ref159">79</reflink>]). Additionally, rural migrants who move to peri‐urban spaces seeking higher wages and better work are often met by social exclusion and discrimination in their new homes, which can lead to serious mental health issues; rural migrants may also suffer from a lack of permanent residency as they search for available housing, which may ultimately influence the quality of their child's home environment (Wang et al., [<reflink idref="bib82" id="ref160">82</reflink>]; Wong & Song, [<reflink idref="bib88" id="ref161">88</reflink>]). Whether they come from an urbanized farmer or a rural migrant background, all peri‐urban households must contend with the destabilization of rapidly transitioning from a rural to an urban environment. The specific impacts of this aspect of urbanization, including potential differences in the HLE and language development of recently urbanized versus more settled peri‐urban households, are a promising direction for future research.</p> <p>From these examples, it is clear that living in peri‐urban communities gives rise to additional challenges that rural households do not have to face on a regular basis. Thus, relative to their peri‐urban counterparts, caregivers in rural China may be able to devote more energy and time to conversations and positive interactions with their children, which may subsequently influence stronger language development. This may explain why children in peri‐urban China hear even less adult speech and produce even fewer vocalizations than those in rural China, where rates of developmental delay have already been identified as alarmingly high (Emmers et al., [<reflink idref="bib26" id="ref162">26</reflink>]; Ma et al., [<reflink idref="bib54" id="ref163">54</reflink>]). In other words, more attention should be given to the quality of the HLE and language development of young children in peri‐urban communities in China, through both policy interventions and research, as ECD is a serious and currently overlooked issue in these peri‐urban communities.</p> <p>Another finding of this study is that certain child and household characteristics were correlated with the HLE. First, we found that older children engaged in more conversations with adults, initiated more conversations with adults, and made more vocalizations than younger children. This result is consistent with previous research showing that increased age corresponds to increased numbers of adult–child conversations (Greenwood et al., [<reflink idref="bib37" id="ref164">37</reflink>]; Hart & Risley, [<reflink idref="bib39" id="ref165">39</reflink>]). Second, maternal employment also had a positive impact on the HLE. When the mother had a job, more adult words were spoken in the household, more conversations occurred between adults and children, and more conversations were initiated by both children and female adults. This result echoes findings from a previous study in the United States that found that, despite maternal employment having a neutral effect on cognitive outcomes, maternal employment had positive effects on language outcomes (Brooks‐Gunn et al., [<reflink idref="bib9" id="ref166">9</reflink>]). Third, the size of the household, specifically the number of siblings, negatively impacted the quality of the HLE, with more siblings associated with a decrease in conversational turns initiated by a male adult. For rural children, more siblings also correlated to a smaller number of adult words overheard in the household, as well as a smaller number of adult–child conversations, while for peri‐urban children, more siblings correlated to fewer child vocalizations. These findings reflect previous research that has shown that children with more siblings have lower levels of both word production and comprehension (Mayor et al., [<reflink idref="bib58" id="ref167">58</reflink>]). Finally, dividing households according to who acted as the primary caregiver, we found that households in which the grandmother was the primary caregiver had significantly higher AWC and CTC (but not CDI) than those in which the mother was the primary caregiver (Table S5). This finding of the potential positive impact of grandmothers on the HLE appears to contrast with Yue et al. ([<reflink idref="bib94" id="ref168">94</reflink>]), which found that grandmothers acting as primary caregivers to rural children under 3 years old was negatively associated with cognitive development, suggesting that the role of grandmothers in the HLE of rural and peri‐urban children requires further research.</p> <p>While child age, maternal employment, and household size had similar impacts on the HLE in both the rural and peri‐urban samples, the impact from child gender differed between samples. In the rural sample, being male was associated with higher AWC, CTC, CVC, and CTS initiated by the child. Conversely, in the peri‐urban sample, being male was associated with lower AWC, CTC, and CVC, as well as lower CTS initiated by the child and by a female adult. While the findings from the rural sample ran counter to most literature on child gender and the HLE, the findings from the peri‐urban sample were consistent with the international literature, which has shown that language development occurs earlier in girls than in boys, with girls producing more words and more diverse speech earlier than boys their same age (Adani & Cepanec, [<reflink idref="bib1" id="ref169">1</reflink>]; Bouchard et al., [<reflink idref="bib7" id="ref170">7</reflink>]).</p> <p>Finally, our results indicate that the HLE was strongly correlated with language development in both peri‐urban and rural households, indicating that the HLE may be an important target for future ECD interventions in these populations. In both rural and peri‐urban households, more adult speech and more linguistic interaction between the child and caregivers (i.e., higher AWC, CTC, CVC, and CTS initiated by a child, CTS initiated by a female adult, and NS initiated by a female adult) were positively associated with language development. Previous research in rural China confirms this finding (Ma et al., [<reflink idref="bib54" id="ref171">54</reflink>]), as does the general body of international LENA studies (d'Apice et al., [<reflink idref="bib21" id="ref172">21</reflink>]; d'Apice & von Stumm, [<reflink idref="bib22" id="ref173">22</reflink>]; Gilkerson et al., [<reflink idref="bib33" id="ref174">33</reflink>]; Romeo et al., [<reflink idref="bib68" id="ref175">68</reflink>]; Weisleder & Fernald, [<reflink idref="bib85" id="ref176">85</reflink>]).</p> <p>The results showed an unexpected negative association between NS initiated by a male adult and CDI scores, which was strongest among the rural sample. Within the rural sample, we also saw a positive association between paternal educational attainment and NS initiated by a male adult (<emph>p</emph> < .05), although less than 10% of fathers in the rural sample had an associate degree or above. Perhaps because the majority of rural fathers had low levels of educational attainment, higher counts of NS initiated by a male adult increased the negative impact of low paternal educational attainment, thus more heavily (negatively) influencing CDI outcomes. However, a recent systematic review on the accuracy of the LENA system identified that some LENA variables, such as number of segments, are not strong enough or valid enough to accurately measure the HLE (Cristia et al., [<reflink idref="bib17" id="ref177">17</reflink>]). Thus, this finding may not be of great concern. At the bottom line, these findings again indicate the need for future research to more deeply investigate factors that may influence the HLE, including the roles of caregivers.</p> <p>We acknowledge several limitations of this study. First, while LENA has been validated and confirmed reliable in Mandarin Chinese (Gilkerson et al., [<reflink idref="bib34" id="ref178">34</reflink>]; Ma et al., [<reflink idref="bib55" id="ref179">55</reflink>]) and used previously among children aged 0 through 3 years in China (Ma et al., [<reflink idref="bib54" id="ref180">54</reflink>]; Zhang, Xu, et al., [<reflink idref="bib102" id="ref181">102</reflink>]), other studies suggest that the accuracy of CTC (especially in the measures of initiated segments, etc.) is not fully reliable (Cristia et al., [<reflink idref="bib17" id="ref182">17</reflink>], [<reflink idref="bib18" id="ref183">18</reflink>]). In addition, no validation studies currently exist that focus on CTS initiated by a child, female adult, or male adult and NS initiated by a child, female adult, or male adult. Therefore, the data regarding CTS initiated by a child, female adult, or male adult and NS initiated by a child, female adult, or male adult should be interpreted conservatively. A second limitation is that we were only able to record 2 days of audio for each sample household compared to other LENA studies that have been able to conduct weekly or biweekly recordings (Suskind et al., [<reflink idref="bib75" id="ref184">75</reflink>]; Zhang, Xu, et al., [<reflink idref="bib102" id="ref185">102</reflink>]). To capture the most complete and accurate portrait possible of the HLE, future research should attempt to record on a weekly or biweekly schedule, as previous studies have successfully done. However, in the context of our own study, to accommodate for the shorter recording period, we confirmed with all caregivers that the 2 days of recording would be accurately representative of normal home life; if not, caregivers were instructed to record their HLE at the next opportunity to capture two normal days of their child's most typical at‐home experiences.</p> <p>The findings presented in this study reveal that urbanization can negatively impact the HLE among otherwise similar low‐SES populations, offering insight that can guide future research and policy on language development in LMICs. We show that children living in peri‐urban China lag significantly behind their rural peers, both in terms of the quality of the HLE and their level of language development. While children from both rural and peri‐urban China are at risk of developmental delay, peri‐urban children face the highest risk of delay and thus require immediate attention from policymakers and researchers. The number of peri‐urban households in China will only grow as the country's rate of urbanization continues to increase. As a result, the number of children at risk of language delay in peri‐urban populations in China will also continue to grow unless policy and research interventions are put into place. Using LENA technology to further study how the HLE and language development are related in peri‐urban regions across China, both practitioners and policymakers can develop more targeted interventions to improve language development in these vulnerable communities.</p> <hd id="AN0175750708-20">FUNDING INFORMATION</hd> <p>This study was supported by private gifts from individual donors. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p> <hd id="AN0175750708-21">DATA AVAILABILITY STATEMENT</hd> <p>The data, analytic code, and materials necessary to reproduce the analyses presented in this study are not publicly accessible but are available from the first author upon reasonable request. The analyses presented here were not pre‐registered.</p> <p>GRAPH: Appendix S1.</p> <ref id="AN0175750708-22"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref110" type="bt">1</bibl> <bibtext> Adani, S., & Cepanec, M. (2019). Sex differences in early communication development: Behavioral and neurobiological indicators of more vulnerable communication system development in boys. Croatian Medical Journal, 60 (2), 141 – 149. https://doi.org/10.3325/cmj.2019.60.141</bibtext> </blist> <blist> <bibl id="bib2" idref="ref90" type="bt">2</bibl> <bibtext> Alderman, H., & Fernald, L. (2017). The nexus between nutrition and early childhood development. Annual Review of Nutrition, 37 (1), 447 – 476. https://doi.org/10.1146/annurev‐nutr‐071816‐064627</bibtext> </blist> <blist> <bibl id="bib3" idref="ref3" type="bt">3</bibl> <bibtext> Attanasio, O. P. (2015). The determinants of human capital formation during the early years of life: Theory, measurement, and policies. Journal of the European Economic Association, 13 (6), 949 – 997. https://doi.org/10.1111/jeea.12159</bibtext> </blist> <blist> <bibl id="bib4" idref="ref105" type="bt">4</bibl> <bibtext> Bai, Y., Zhang, S., Wang, L., Dang, R., Abbey, C., & Rozelle, S. (2019). Past successes and future challenges in rural China's human capital. Journal of Contemporary China, 28 (120), 883 – 898. https://doi.org/10.1080/10670564.2019.1594102</bibtext> </blist> <blist> <bibl id="bib5" idref="ref112" type="bt">5</bibl> <bibtext> Bengoa, M., & Rick, C. (2020). Chinese hukou policy and rural‐to‐urban migrants' health: Evidence from matching methods. Eastern Economic Journal, 46 (2), 224 – 259. https://doi.org/10.1057/s41302‐019‐00158‐z</bibtext> </blist> <blist> <bibl id="bib6" idref="ref119" type="bt">6</bibl> <bibtext> Bland, D., & Hernández, M. (2016). Urban legend: China's tiered city system explained. South China Morning Post. https://multimedia.scmp.com/2016/cities/</bibtext> </blist> <blist> <bibl id="bib7" idref="ref170" type="bt">7</bibl> <bibtext> Bouchard, C., Trudeau, N., Sutton, A., Boudreault, M.‐C., & Deneault, J. (2009). Gender differences in language development in French Canadian children between 8 and 30 months of age. Applied PsychoLinguistics, 30 (4), 685 – 707. https://doi.org/10.1017/S0142716409990075</bibtext> </blist> <blist> <bibl id="bib8" idref="ref35" type="bt">8</bibl> <bibtext> Brainard, M. S., & Doupe, A. J. (2000). Auditory feedback in learning and maintenance of vocal behaviour. Nature Reviews Neuroscience, 1 (1), 31 – 40. https://doi.org/10.1038/35036205</bibtext> </blist> <blist> <bibl id="bib9" idref="ref166" type="bt">9</bibl> <bibtext> Brooks‐Gunn, J., Han, W.‐J., & Waldfogel, J. (2010). First‐year maternal employment and child development in the first seven years. Monographs of the Society for Research in Child Development, 75 (2), 7 – 9. https://doi.org/10.1111/j.1540‐5834.2010.00562.x</bibtext> </blist> <blist> <bibtext> Buckingham, W., & Chan, K. W. (2018). One city, two systems: Chengzhongcun in China's urban system. Journal of Contemporary China, 27 (112), 584 – 595. https://doi.org/10.1080/10670564.2018.1433576</bibtext> </blist> <blist> <bibtext> Busch, T., Sangen, A., Vanpoucke, F., & van Wieringen, A. (2018). Correlation and agreement between Language ENvironment Analysis (LENA™) and manual transcription for Dutch natural language recordings. Behavior Research Methods, 50, 1921 – 1932. https://doi.org/10.3758/s13428‐017‐0960‐0</bibtext> </blist> <blist> <bibtext> Canault, M., Le Normand, M.‐T., Foudil, S., Loundon, N., & Thai‐Van, H. (2016). Reliability of the Language ENvironment Analysis system (LENA™) in European French. Behavior Research Methods, 48 (3), 1109 – 1124. https://doi.org/10.3758/s13428‐015‐0634‐8</bibtext> </blist> <blist> <bibtext> Casillas, M., Brown, P., & Levinson, S. C. (2020). Early language experience in a Tseltal Mayan village. Child Development, 91 (5), 1819 – 1835. https://doi.org/10.1111/cdev.13349</bibtext> </blist> <blist> <bibtext> Casillas, M., Brown, P., & Levinson, S. C. (2021). Early language experience in a Papuan community. Journal of Child Language, 48 (4), Article 4 – Article 814. https://doi.org/10.1017/S0305000920000549</bibtext> </blist> <blist> <bibtext> Chang, S., He, W., Jia, F., & Chen, C. (2007). Analysis on the changes of nutritional status in China anemia status of children under 5 in China. Journal of Hygiene Research, 36 (2), 210 – 212.</bibtext> </blist> <blist> <bibtext> Chen, K., Liu, C., Liu, X., Wang, Z., Luo, R., Li, S., Yu, Y., & Alderman, H. (2021). Nutrition, cognition, and social emotion among preschoolers in poor, rural areas of south central China: Status and correlates. Nutrients, 13 (4), 1322. https://doi.org/10.3390/nu13041322</bibtext> </blist> <blist> <bibtext> Cristia, A., Bulgarelli, F., & Bergelson, E. (2020). Accuracy of the language environment analysis system segmentation and metrics: A systematic review. Journal of Speech, Language, and Hearing Research, 63 (4), 1093 – 1105. https://doi.org/10.1044/2020_JSLHR‐19‐00017</bibtext> </blist> <blist> <bibtext> Cristia, A., Lavechin, M., Scaff, C., Soderstrom, M., Rowland, C., Räsänen, O., Bunce, J., & Bergelson, E. (2021). A thorough evaluation of the Language Environment Analysis (LENA) system. Behavior Research Methods, 53 (2), 467 – 486. https://doi.org/10.3758/s13428‐020‐01393‐5</bibtext> </blist> <blist> <bibtext> Cunha, F., Gerdes, M., Hu, Q., & Nihtianova, S. (2023). Language environment and maternal expectations: An evaluation of the LENA start program. National Bureau of Economic Research, w30837. https://doi.org/10.3386/w30837</bibtext> </blist> <blist> <bibtext> Dailey, S., & Bergelson, E. (2022). Language input to infants of different socioeconomic statuses: A quantitative meta‐analysis. Developmental Science, 25 (3), e13192. https://doi.org/10.1111/desc.13192</bibtext> </blist> <blist> <bibtext> d'Apice, K., Latham, R., & Stumm, S. (2019). A naturalistic home observational approach to Children's language, cognition, and behavior. Developmental Psychology, 55, 1414 – 1427. https://doi.org/10.1037/dev0000733</bibtext> </blist> <blist> <bibtext> d'Apice, K., & von Stumm, S. (2020). The role of spoken language and literacy exposure for cognitive and language outcomes in children. Scientific Studies of Reading, 24 (2), 108 – 122. https://doi.org/10.1080/10888438.2019.1641505</bibtext> </blist> <blist> <bibtext> deMayo, B., Kellier, D., Braginsky, M., Bergmann, C., Hendriks, C., Rowland, C. F., Frank, M. C., & Marchman, V. A. (2021). Web‐CDI: A system for online administration of the MacArthur‐Bates Communicative Development Inventories. PsyArXiv. https://doi.org/10.31234/osf.io/8mjx9</bibtext> </blist> <blist> <bibtext> Demir‐Lira, Ö. E., Applebaum, L. R., Goldin‐Meadow, S., & Levine, S. C. (2019). Parents' early book reading to children: Relation to children's later language and literacy outcomes controlling for other parent language input. Developmental Science, 22 (3), e12764. https://doi.org/10.1111/desc.12764</bibtext> </blist> <blist> <bibtext> Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., Pagani, L. S., Feinstein, L., Engel, M., Brooks‐Gunn, J., Sexton, H., Duckworth, K., & Japel, C. (2007). School readiness and later achievement. Developmental Psychology, 43 (6), 1428 – 1446. https://doi.org/10.1037/0012‐1649.43.6.1428</bibtext> </blist> <blist> <bibtext> Emmers, D., Jiang, Q., Xue, H., Zhang, Y., Zhang, Y., Zhao, Y., Liu, B., Dill, S.‐E., Qian, Y., Warrinnier, N., Johnstone, H., Cai, J., Wang, X., Wang, L., Luo, R., Li, G., Xu, J., Liu, M., Huang, Y., ... Rozelle, S. (2020). Early childhood development and parental training interventions in rural China: A systematic review and meta‐analysis. BMJ Globalization and Health, 6 (8), e005578. https://doi.org/10.1136/bmjgh‐2021‐005578</bibtext> </blist> <blist> <bibtext> Fan, C. C., Sun, M., & Zheng, S. (2011). Migration and split households: A comparison of sole, couple, and family migrants in Beijing, China. Environment and Planning A: Economy and Space, 43 (9), 2164 – 2185. https://doi.org/10.1068/a44128</bibtext> </blist> <blist> <bibtext> Fenson, L., Marchman, V. A., Thal, D. J., Dale, P. S., Reznick, J. S., & Bates, E. (2007). MacArthur‐Bates Communicative Development Inventories (2nd ed.). Paul H. Brookes.</bibtext> </blist> <blist> <bibtext> Fernald, A., Marchman, V. A., & Weisleder, A. (2013). SES differences in language processing skill and vocabulary are evident at 18 months. Developmental Science, 16 (2), 234 – 248. https://doi.org/10.1111/desc.12019</bibtext> </blist> <blist> <bibtext> Firestone, R., Punpuing, S., Peterson, K. E., Acevedo‐Garcia, D., & Gortmaker, S. L. (2011). Child overweight and undernutrition in Thailand: Is there an urban effect? Social Science & Medicine, 72 (9), 1420 – 1428. https://doi.org/10.1016/j.socscimed.2011.03.003</bibtext> </blist> <blist> <bibtext> Frank, M. C., Braginsky, M., Yurovsky, D., & Marchman, V. A. (2021). Variability and consistency in early language learning: The Wordbank project. MIT Press.</bibtext> </blist> <blist> <bibtext> Gilkerson, J., & Richards, J. A. (2009). Impact of adult talk, conversational turns, and TV during the critical 0–4 years of child development. LENA Foundation technical report (2nd ed.). LENA Foundation. <ulink href="http://www.lena.org/wp‐content/uploads/2016/07/LTR‐01‐2%5fPowerOfTalk.pdf">http://www.lena.org/wp‐content/uploads/2016/07/LTR‐01‐2%5fPowerOfTalk.pdf</ulink></bibtext> </blist> <blist> <bibtext> Gilkerson, J., Richards, J. A., Warren, S. F., Oller, D. K., Russo, R., & Vohr, B. (2018). Language experience in the second year of life predicts language outcomes in late childhood. Pediatrics, 142 (4), e20174276. https://doi.org/10.1542/peds.2017‐4276</bibtext> </blist> <blist> <bibtext> Gilkerson, J., Zhang, Y., Xu, D., Richards, J. A., Xu, X., Jiang, F., Harnsberger, J., & Topping, K. (2015). Evaluating language environment analysis system performance for Chinese: A pilot study in Shanghai. Journal of Speech, Language, and Hearing Research, 58 (2), 445 – 452. https://doi.org/10.1044/2015_JSLHR‐L‐14‐0014</bibtext> </blist> <blist> <bibtext> Golinkoff, R. M., Hoff, E., Rowe, M. L., Tamis‐LeMonda, C. S., & Hirsh‐Pasek, K. (2019). Language matters: Denying the existence of the 30‐million‐word gap has serious consequences. Child Development, 90 (3), 985 – 992. https://doi.org/10.1111/cdev.13128</bibtext> </blist> <blist> <bibtext> Grantham‐McGregor, S., & Ani, C. (2001). A review of studies on the effect of iron deficiency on cognitive development in children. The Journal of Nutrition, 131 (2), 649S – 668S. https://doi.org/10.1093/jn/131.2.649S</bibtext> </blist> <blist> <bibtext> Greenwood, C. R., Thiemann‐Bourque, K., Walker, D., Buzhardt, J., & Gilkerson, J. (2011). Assessing children's home language environments using automatic speech recognition technology. Communication Disorders Quarterly, 32 (2), 83 – 92. https://doi.org/10.1177/1525740110367826</bibtext> </blist> <blist> <bibtext> Hamnett, C. (2020). Is Chinese urbanisation unique? Urban Studies, 57 (3), 690 – 700. https://doi.org/10.1177/0042098019890810</bibtext> </blist> <blist> <bibtext> Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experience of young American children. Paul H. Brookes Publishing.</bibtext> </blist> <blist> <bibtext> He, S., & Wang, K. (2016). China's new generation migrant workers' urban experience and well‐being. In D. Wang & S. He (Eds.), Mobility, sociability and well‐being of urban living (pp. 67 – 91). Springer. https://doi.org/10.1007/978‐3‐662‐48184‐4_4</bibtext> </blist> <blist> <bibtext> Heurlin, C. (2019). Unemployment among land‐losing farmers in China: Evidence from the 2010 census. Journal of Contemporary China, 28 (117), 434 – 452. https://doi.org/10.1080/10670564.2018.1542223</bibtext> </blist> <blist> <bibtext> Hoff, E. (2003). The specificity of environmental influence: Socioeconomic status affects early vocabulary development via maternal speech. Child Development, 74 (5), 1368 – 1378. https://doi.org/10.1111/1467‐8624.00612</bibtext> </blist> <blist> <bibtext> Huttenlocher, J., Haight, W., Bryk, A., Seltzer, M., & Lyons, T. (1991). Early vocabulary growth: Relation to language input and gender. Developmental Psychology, 27 (2), 236 – 248. https://doi.org/10.1037/0012‐1649.27.2.236</bibtext> </blist> <blist> <bibtext> Knudsen, E. I., Heckman, J. J., Cameron, J. L., & Shonkoff, J. P. (2006). Economic, neurobiological, and behavioral perspectives on building America's future workforce. Proceedings of the National Academy of Sciences of the United States of America, 103 (27), 10155 – 10162.</bibtext> </blist> <blist> <bibtext> Kolenikov, S., & Angeles, G. (2009). Socioeconomic status measurement with discrete proxy variables: Is principal component analysis a reliable answer? Review of Income and Wealth, 55 (1), 128 – 165. https://doi.org/10.1111/j.1475‐4991.2008.00309.x</bibtext> </blist> <blist> <bibtext> Krishnan, V. (2010). Constructing an area‐based socioeconomic index: A principal components analysis approach. Early Child Development Mapping Project.</bibtext> </blist> <blist> <bibtext> Le, T. H., Nakagawa, Y., & Kobayashi, Y. (2021). Conditions under which rural‐to‐urban migration enhances social and economic sustainability of home communities: A case study in Vietnam. Sustainability, 13 (15), 8326. https://doi.org/10.3390/su13158326</bibtext> </blist> <blist> <bibtext> Lee, V. E., & Burkam, D. T. (2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Economic Policy Institute.</bibtext> </blist> <blist> <bibtext> Li, N., & Placier, P. (2015). Migrant and non‐migrant families in Chengdu, China: Segregated lives, segregated schools. Social Sciences, 4 (2), 339 – 360. https://doi.org/10.3390/socsci4020339</bibtext> </blist> <blist> <bibtext> Li, S. (2010). The economic situation of rural migrant Workers in China. China Perspectives, 2010 (4), 4 ‐ 15. https://doi.org/10.4000/chinaperspectives.5332</bibtext> </blist> <blist> <bibtext> Liu, A., & Ye, Z. (2020). China statistical Yearbook‐2020. National Bureau of Statistics of China (NBS China). <ulink href="http://www.stats.gov.cn/tjsj/ndsj/2020/indexeh.htm">http://www.stats.gov.cn/tjsj/ndsj/2020/indexeh.htm</ulink></bibtext> </blist> <blist> <bibtext> Liu, S., Zhang, F., & Wu, F. (2022). Contrasting migrants' sense of belonging to the city in selected peri‐urban neighbourhoods in Beijing. Cities, 120, 103499. https://doi.org/10.1016/j.cities.2021.103499</bibtext> </blist> <blist> <bibtext> Lopez, L. D., Walle, E. A., Pretzer, G. M., & Warlaumont, A. S. (2020). Adult responses to infant prelinguistic vocalizations are associated with infant vocabulary: A home observation study. PLoS One, 15 (11), e0242232. https://doi.org/10.1371/journal.pone.0242232</bibtext> </blist> <blist> <bibtext> Ma, Y., Jonsson, L., Feng, T., Weisberg, T., Shao, T., Yao, Z., Zhang, D., Dill, S.‐E., Guo, Y., Zhang, Y., Friesen, D., & Rozelle, S. (2021). Variations in the home language environment and early language development in rural China. International Journal of Environmental Research and Public Health, 18 (5), 2671. https://doi.org/10.3390/ijerph18052671</bibtext> </blist> <blist> <bibtext> Ma, Y., Jonsson, L., Yao, Z., Zhang, X., Friesen, D., Medina, A., Rozelle, S., & Pappas, L. (2023). The home language environment in rural China: Variations across family characteristics. BMC Public Health, 23 (1), 354. https://doi.org/10.1186/s12889‐023‐15245‐2</bibtext> </blist> <blist> <bibtext> Macdonald, T., & Winklerprins, A. M. G. A. (2014). Searching for a better life: Peri‐urban migration in Western Para State, Brazil. Geographical Review, 104 (3), 294 – 309. https://doi.org/10.1111/j.1931‐0846.2014.12027.x</bibtext> </blist> <blist> <bibtext> Mandere, N. M., Ness, B., & Anderberg, S. (2010). Peri‐urban development, livelihood change and household income: A case study of peri‐urban Nyahururu, Kenya. Journal of Agricultural Extension and Rural Development, 2 (5), 73 – 83.</bibtext> </blist> <blist> <bibtext> Mayor, J., Arias‐Trejo, N., & Alva, E. A. (2018). The impact of household size on lexical typicality: An early link between language and social cognition? Frontiers in Psychology, 9, 1445. https://doi.org/10.3389/fpsyg.2018.01445</bibtext> </blist> <blist> <bibtext> McCartney, K. (1984). Effect of quality of day care environment on children's language development. Developmental Psychology, 20 (2), 244 – 260. https://doi.org/10.1037/0012‐1649.20.2.244</bibtext> </blist> <blist> <bibtext> McDade, T. W., & Adair, L. S. (2001). Defining the "urban" in urbanization and health: A factor analysis approach. Social Science & Medicine, 53 (1), 55 – 70. https://doi.org/10.1016/S0277‐9536(00)00313‐0</bibtext> </blist> <blist> <bibtext> Moeller, M. P., Hoover, B., Putman, C., Arbataitis, K., Bohnenkamp, G., Peterson, B., Lewis, D., Estee, S., Pittman, A., & Stelmachowicz, P. (2007). Vocalizations of infants with hearing loss compared with infants with Normal hearing: Part II—Transition to words. Ear and Hearing, 28 (5), 628 – 642. https://doi.org/10.1097/AUD.0b013e31812564c9</bibtext> </blist> <blist> <bibtext> Nauman, E., VanLandingham, M., Anglewicz, P., Patthavanit, U., & Punpuing, S. (2015). Rural‐to‐urban migration and changes in health among young adults in Thailand. Demography, 52 (1), 233 – 257. https://doi.org/10.1007/s13524‐014‐0365‐y</bibtext> </blist> <blist> <bibtext> Pae, S., Yoon, H., Seol, A., Gilkerson, J., Richards, J. A., Ma, L., & Topping, K. (2016). Effects of feedback on parent–child language with infants and toddlers in Korea. First Language, 36 (6), 549 – 569. https://doi.org/10.1177/0142723716649273</bibtext> </blist> <blist> <bibtext> Palmer, N. A., Perkins, D. D., & Xu, Q. (2011). Social capital and community participation among migrant workers in China. Journal of Community Psychology, 39 (1), 89 – 105. https://doi.org/10.1002/jcop.20419</bibtext> </blist> <blist> <bibtext> Prado, E. L., & Dewey, K. G. (2014). Nutrition and brain development in early life. Nutrition Reviews, 72 (4), 267 – 284. https://doi.org/10.1111/nure.12102</bibtext> </blist> <blist> <bibtext> Ramírez, N. F., Lytle, S. R., & Kuhl, P. K. (2020). Parent coaching increases conversational turns and advances infant language development. Proceedings of the National Academy of Sciences, 117 (7), 3484 – 3491. https://doi.org/10.1073/pnas.1921653117</bibtext> </blist> <blist> <bibtext> Ramírez‐Esparza, N., García‐Sierra, A., & Kuhl, P. K. (2014). Look who's talking: Speech style and social context in language input to infants are linked to concurrent and future speech development. Developmental Science, 17 (6), 880 – 891. https://doi.org/10.1111/desc.12172</bibtext> </blist> <blist> <bibtext> Romeo, R. R., Leonard, J. A., Robinson, S. T., West, M. R., Mackey, A. P., Rowe, M. L., & Gabrieli, J. D. E. (2018). Beyond the 30‐million‐word gap: Children's conversational exposure is associated with language‐related brain function. Psychological Science, 29 (5), 700 – 710. https://doi.org/10.1177/0956797617742725</bibtext> </blist> <blist> <bibtext> Rowe, M. L. (2008). Child‐directed speech: Relation to socioeconomic status, knowledge of child development and child vocabulary skill. Journal of Child Language, 35 (1), 185 – 205. https://doi.org/10.1017/s0305000907008343</bibtext> </blist> <blist> <bibtext> Rowe, M. L. (2012). A longitudinal investigation of the role of quantity and quality of child‐directed speech in vocabulary development. Child Development, 83 (5), 1762 – 1774. https://doi.org/10.1111/j.1467‐8624.2012.01805.x</bibtext> </blist> <blist> <bibtext> Sania, A., Sudfeld, C. R., Danaei, G., Fink, G., McCoy, D. C., Zhu, Z., Fawzi, M. C. S., Akman, M., Arifeen, S. E., Barros, A. J. D., Bellinger, D., Black, M. M., Bogale, A., Braun, J. M., Van Den Broek, N., Carrara, V., Duazo, P., Duggan, C., Fernald, L. C. H., ... Fawzi, W. (2019). Early life risk factors of motor, cognitive and language development: A pooled analysis of studies from low/middle‐income countries. BMJ Open, 9 (10), e026449. https://doi.org/10.1136/bmjopen‐2018‐026449</bibtext> </blist> <blist> <bibtext> Smith, N. R. (2014). Living on the edge: Household registration reform and peri‐urban precarity in China. Journal of Urban Affairs, 36 (Suppl. 1), 369 – 383. https://doi.org/10.1111/juaf.12107</bibtext> </blist> <blist> <bibtext> Song, Y., & Xie, Z. (2017). Impact of urban public resources on migration decision of rural children in China. Population Research, 41 (5), 52 – 62.</bibtext> </blist> <blist> <bibtext> Sperry, D. E., Sperry, L. L., & Miller, P. J. (2019). Reexamining the verbal environments of children from different socioeconomic backgrounds. Child Development, 90 (4), 1303 – 1318. https://doi.org/10.1111/cdev.13072</bibtext> </blist> <blist> <bibtext> Suskind, D. L., Leffel, K. R., Graf, E., Hernandez, M. W., Gunderson, E. A., Sapolich, S. G., Suskind, E., Leininger, L., Goldin‐Meadow, S., & Levine, S. C. (2016). A parent‐directed language intervention for children of low socioeconomic status: A randomized controlled pilot study. Journal of Child Language, 43 (2), 366 – 406. https://doi.org/10.1017/S0305000915000033</bibtext> </blist> <blist> <bibtext> Tacoli, C., McGranahan, G., & Satterthwaite, D. (2015). Urbanisation, rural–urban migration and urban poverty. Human Settlements Group, International Institute for Environment and Development.</bibtext> </blist> <blist> <bibtext> Tamis‐LeMonda, C. S., Bornstein, M. H., & Baumwell, L. (2001). Maternal responsiveness and children's achievement of language milestones. Child Development, 72 (3), 748 – 767. https://doi.org/10.1111/1467‐8624.00313</bibtext> </blist> <blist> <bibtext> Tardif, T., Fletcher, P., Liang, W., Zhang, Z., Kaciroti, N., & Marchman, V. A. (2008). Baby's first 10 words. Developmental Psychology, 44 (4), 929 – 938. https://doi.org/10.1037/0012‐1649.44.4.929</bibtext> </blist> <blist> <bibtext> Tong, W., Zhu, L., & Lo, K. (2019). Livelihood adaptation and life satisfaction among land‐lost farmers: Critiquing China's urbanisation‐driven land appropriation. Bulletin of Geography. Socio‐Economic Series, 46 (46), 149 – 161. https://doi.org/10.2478/bog‐2019‐0040</bibtext> </blist> <blist> <bibtext> Uccelli, P., Demir‐Lira, Ö. E., Rowe, M. L., Levine, S., & Goldin‐Meadow, S. (2019). Children's early decontextualized talk predicts academic language proficiency in midadolescence. Child Development, 90 (5), 1650 – 1663. https://doi.org/10.1111/cdev.13034</bibtext> </blist> <blist> <bibtext> Walker, D., Greenwood, C., Hart, B., & Carta, J. (1994). Prediction of school outcomes based on early language production and socioeconomic factors. Child Development, 65 (2), 606 – 621. https://doi.org/10.1111/j.1467‐8624.1994.tb00771.x</bibtext> </blist> <blist> <bibtext> Wang, L., Liang, W., Zhang, S., Jonsson, L., Li, M., Yu, C., Sun, Y., Ma, Q., Bai, Y., Abbey, C., Luo, R., Yue, A., & Rozelle, S. (2019). Are infant/toddler developmental delays a problem across rural China? Journal of Comparative Economics, 47 (2), 458 – 469. https://doi.org/10.1016/j.jce.2019.02.003</bibtext> </blist> <blist> <bibtext> Wang, Y., Williams, R., Dilley, L., & Houston, D. M. (2020). A meta‐analysis of the predictability of LENA™ automated measures for child language development. Developmental Review, 57, 100921. https://doi.org/10.1016/j.dr.2020.100921</bibtext> </blist> <blist> <bibtext> Weber, A., Fernald, A., & Diop, Y. (2017). When cultural norms discourage talking to babies: Effectiveness of a parenting program in rural Senegal. Child Development, 88 (5), 1513 – 1526. https://doi.org/10.1111/cdev.12882</bibtext> </blist> <blist> <bibtext> Weisleder, A., & Fernald, A. (2013). Talking to children matters: Early language experience strengthens processing and builds vocabulary. Psychological Science, 24 (11), 2143 – 2152. https://doi.org/10.1177/0956797613488145</bibtext> </blist> <blist> <bibtext> Werwach, A., Mürbe, D., Schaadt, G., & Männel, C. (2021). Infants' vocalizations at 6 months predict their productive vocabulary at one year. Infant Behavior and Development, 64, 101588. https://doi.org/10.1016/j.infbeh.2021.101588</bibtext> </blist> <blist> <bibtext> Winarso, H., Hudalah, D., & Firman, T. (2015). Peri‐urban transformation in the Jakarta metropolitan area. Habitat International, 49, 221 – 229. https://doi.org/10.1016/j.habitatint.2015.05.024</bibtext> </blist> <blist> <bibtext> Wong, D. F. K., & Song, H. X. (2008). The resilience of migrant Workers in Shanghai China: The roles of migration stress and meaning of migration. International Journal of Social Psychiatry, 54 (2), 131 – 143. https://doi.org/10.1177/0020764007083877</bibtext> </blist> <blist> <bibtext> Wood, C., Diehm, E. A., & Callender, M. F. (2016). An investigation of language environment analysis measures for Spanish–English bilingual preschoolers from migrant low‐socioeconomic‐status backgrounds. Language, Speech, and Hearing Services in Schools, 47 (2), 123 – 134. https://doi.org/10.1044/2015_LSHSS‐14‐0115</bibtext> </blist> <blist> <bibtext> World Bank. (2020). World Bank open data. https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS?most_recent_year_desc=false</bibtext> </blist> <blist> <bibtext> Wu, F., Zhang, F., & Webster, C. (2013). Informality and the development and demolition of urban villages in the Chinese peri‐urban area. Urban Studies, 50 (10), 1919 – 1934. https://doi.org/10.1177/0042098012466600</bibtext> </blist> <blist> <bibtext> Xu, D., Yapanel, U., & Gray, S. (2009). Reliability of the LENA™ language environment analysis system in young Children's natural home environment (LENA Foundation Technical Report LTR‐05‐02; p. 16). LENA Foundation.</bibtext> </blist> <blist> <bibtext> Xu, J. (1999). Snowball: An anthropological analysis of the Han people. Shanghai People's Press.</bibtext> </blist> <blist> <bibtext> Yue, A., Shi, Y., Luo, R., Chen, J., Garth, J., Zhang, J., Medina, A., Kotb, S., & Rozelle, S. (2017). China's invisible crisis: Cognitive delays among rural toddlers and the absence of modern parenting. The China Journal, 78, 50 – 80. https://doi.org/10.1086/692290</bibtext> </blist> <blist> <bibtext> Zangl, R., & Fernald, A. (2007). Increasing flexibility in Children's online processing of grammatical and nonce determiners in fluent speech. Language Learning and Development, 3 (3), 199 – 231. https://doi.org/10.1080/15475440701360564</bibtext> </blist> <blist> <bibtext> Zhan, S. (2011). What determines migrant workers' life chances in contemporary China? Hukou, social exclusion, and the market. Modern China, 37 (3), 243 – 285. https://doi.org/10.1177/0097700410379482</bibtext> </blist> <blist> <bibtext> Zhang, L., Wang, S. X., & Yu, L. (2015). Is social capital eroded by the state‐led urbanization in China? A case study on indigenous villagers in the urban fringe of Beijing. China Economic Review, 35, 232 – 246. https://doi.org/10.1016/j.chieco.2014.04.005</bibtext> </blist> <blist> <bibtext> Zhang, S., Shi, Y., Wang, L., Yang, N., Liu, B., Tang, R., & Bai, Y. (2020). Urbanization and human capital: Early childhood development in rural China. Journal of East China Normal University (Educational Sciences), 38 (6), 102 – 115. https://doi.org/10.16382/j.cnki.1000‐5560.2020.06.007</bibtext> </blist> <blist> <bibtext> Zhang, W. (2007). Alternation of [n] and [l] in Sichuan dialect, standard mandarin and English: A single‐case study. Leeds Working Papers in Linguistics and Phonetics, 12, 156 – 173.</bibtext> </blist> <blist> <bibtext> Zhang, X., Ma, Y., Feng, T., Zhang, V., Wu, X., Li, M., Li, Q., Thani, Z., Pappas, L., Dill, S.‐E., & Rozelle, S. (2023). The home language environment and early language ability in rural Southwestern China. Frontiers in Psychology, 13, 1010442. https://doi.org/10.3389/fpsyg.2022.1010442</bibtext> </blist> <blist> <bibtext> Zhang, Y., Wang, H., Wang, X., Liu, M., Wang, Y., Wang, Y., & Zhou, H. (2019). The association between urbanization and child height: A multilevel study in China. BMC Public Health, 19 (1), 569. https://doi.org/10.1186/s12889‐019‐6921‐z</bibtext> </blist> <blist> <bibtext> Zhang, Y., Xu, X., Jiang, F., Gilkerson, J., Xu, D., Richards, J. A., Harnsberger, J., & Topping, K. J. (2015). Effects of quantitative linguistic feedback to caregivers of young children: A pilot study in China. Communication Disorders Quarterly, 37 (1), 16 – 24. https://doi.org/10.1177/1525740115575771</bibtext> </blist> <blist> <bibtext> Zhu, Y. (2017). In situ urbanization in China: Processes, contributing factors, and policy implications. China Population and Development Studies, 1 (1), 45 – 66. https://doi.org/10.1007/BF03500917</bibtext> </blist> </ref> <aug> <p>By Yue Ma; Xinwu Zhang; Lucy Pappas; Andrew Rule; Yujuan Gao; Sarah‐Eve Dill; Tianli Feng; Yue Zhang; Hong Wang; Flavio Cunha and Scott Rozelle</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib26" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib24" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib44" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib29" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib39" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib42" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib43" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib70" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib77" firstref="ref10"></nolink> <nolink nlid="nl10" bibid="bib21" firstref="ref11"></nolink> <nolink nlid="nl11" bibid="bib22" firstref="ref12"></nolink> <nolink nlid="nl12" bibid="bib32" firstref="ref13"></nolink> <nolink nlid="nl13" bibid="bib84" firstref="ref15"></nolink> <nolink nlid="nl14" bibid="bib100" firstref="ref16"></nolink> <nolink nlid="nl15" bibid="bib33" firstref="ref17"></nolink> <nolink nlid="nl16" bibid="bib67" firstref="ref18"></nolink> <nolink nlid="nl17" bibid="bib85" firstref="ref19"></nolink> <nolink nlid="nl18" bibid="bib53" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib66" firstref="ref26"></nolink> <nolink nlid="nl20" bibid="bib37" firstref="ref28"></nolink> <nolink nlid="nl21" bibid="bib83" firstref="ref29"></nolink> <nolink nlid="nl22" bibid="bib86" firstref="ref30"></nolink> <nolink nlid="nl23" bibid="bib61" firstref="ref34"></nolink> <nolink nlid="nl24" bibid="bib25" firstref="ref36"></nolink> <nolink nlid="nl25" bibid="bib48" firstref="ref38"></nolink> <nolink nlid="nl26" bibid="bib80" firstref="ref39"></nolink> <nolink nlid="nl27" bibid="bib81" firstref="ref40"></nolink> <nolink nlid="nl28" bibid="bib23" firstref="ref41"></nolink> <nolink nlid="nl29" bibid="bib31" firstref="ref42"></nolink> <nolink nlid="nl30" bibid="bib55" firstref="ref43"></nolink> <nolink nlid="nl31" bibid="bib20" firstref="ref48"></nolink> <nolink nlid="nl32" bibid="bib35" firstref="ref49"></nolink> <nolink nlid="nl33" bibid="bib69" firstref="ref52"></nolink> <nolink nlid="nl34" bibid="bib89" firstref="ref54"></nolink> <nolink nlid="nl35" bibid="bib13" firstref="ref55"></nolink> <nolink nlid="nl36" bibid="bib14" firstref="ref56"></nolink> <nolink nlid="nl37" bibid="bib17" firstref="ref57"></nolink> <nolink nlid="nl38" bibid="bib71" firstref="ref59"></nolink> <nolink nlid="nl39" bibid="bib38" firstref="ref64"></nolink> <nolink nlid="nl40" bibid="bib41" firstref="ref65"></nolink> <nolink nlid="nl41" bibid="bib72" firstref="ref66"></nolink> <nolink nlid="nl42" bibid="bib40" firstref="ref67"></nolink> <nolink nlid="nl43" bibid="bib50" firstref="ref69"></nolink> <nolink nlid="nl44" bibid="bib49" firstref="ref70"></nolink> <nolink nlid="nl45" bibid="bib79" firstref="ref71"></nolink> <nolink nlid="nl46" bibid="bib96" firstref="ref72"></nolink> <nolink nlid="nl47" bibid="bib10" firstref="ref73"></nolink> <nolink nlid="nl48" bibid="bib56" firstref="ref74"></nolink> <nolink nlid="nl49" bibid="bib91" firstref="ref76"></nolink> <nolink nlid="nl50" bibid="bib47" firstref="ref77"></nolink> <nolink nlid="nl51" bibid="bib62" firstref="ref78"></nolink> <nolink nlid="nl52" bibid="bib73" firstref="ref79"></nolink> <nolink nlid="nl53" bibid="bib87" firstref="ref80"></nolink> <nolink nlid="nl54" bibid="bib52" firstref="ref82"></nolink> <nolink nlid="nl55" bibid="bib57" firstref="ref83"></nolink> <nolink nlid="nl56" bibid="bib64" firstref="ref84"></nolink> <nolink nlid="nl57" bibid="bib76" firstref="ref85"></nolink> <nolink nlid="nl58" bibid="bib30" firstref="ref87"></nolink> <nolink nlid="nl59" bibid="bib101" firstref="ref88"></nolink> <nolink nlid="nl60" bibid="bib60" firstref="ref89"></nolink> <nolink nlid="nl61" bibid="bib15" firstref="ref91"></nolink> <nolink nlid="nl62" bibid="bib16" firstref="ref92"></nolink> <nolink nlid="nl63" bibid="bib36" firstref="ref93"></nolink> <nolink nlid="nl64" bibid="bib65" firstref="ref94"></nolink> <nolink nlid="nl65" bibid="bib27" firstref="ref95"></nolink> <nolink nlid="nl66" bibid="bib97" firstref="ref96"></nolink> <nolink nlid="nl67" bibid="bib74" firstref="ref97"></nolink> <nolink nlid="nl68" bibid="bib51" firstref="ref98"></nolink> <nolink nlid="nl69" bibid="bib103" firstref="ref99"></nolink> <nolink nlid="nl70" bibid="bib90" firstref="ref100"></nolink> <nolink nlid="nl71" bibid="bib102" firstref="ref104"></nolink> <nolink nlid="nl72" bibid="bib82" firstref="ref106"></nolink> <nolink nlid="nl73" bibid="bib98" firstref="ref107"></nolink> <nolink nlid="nl74" bibid="bib143" firstref="ref108"></nolink> <nolink nlid="nl75" bibid="bib200" firstref="ref109"></nolink> <nolink nlid="nl76" bibid="bib300" firstref="ref111"></nolink> <nolink nlid="nl77" bibid="bib99" firstref="ref117"></nolink> <nolink nlid="nl78" bibid="bib93" firstref="ref122"></nolink> <nolink nlid="nl79" bibid="bib95" firstref="ref123"></nolink> <nolink nlid="nl80" bibid="bib11" firstref="ref126"></nolink> <nolink nlid="nl81" bibid="bib12" firstref="ref127"></nolink> <nolink nlid="nl82" bibid="bib63" firstref="ref129"></nolink> <nolink nlid="nl83" bibid="bib34" firstref="ref132"></nolink> <nolink nlid="nl84" bibid="bib19" firstref="ref134"></nolink> <nolink nlid="nl85" bibid="bib92" firstref="ref136"></nolink> <nolink nlid="nl86" bibid="bib28" firstref="ref139"></nolink> <nolink nlid="nl87" bibid="bib78" firstref="ref140"></nolink> <nolink nlid="nl88" bibid="bib45" firstref="ref143"></nolink> <nolink nlid="nl89" bibid="bib94" firstref="ref144"></nolink> <nolink nlid="nl90" bibid="bib58" firstref="ref152"></nolink> <nolink nlid="nl91" bibid="bib59" firstref="ref153"></nolink> <nolink nlid="nl92" bibid="bib46" firstref="ref154"></nolink> <nolink nlid="nl93" bibid="bib54" firstref="ref156"></nolink> <nolink nlid="nl94" bibid="bib88" firstref="ref161"></nolink> <nolink nlid="nl95" bibid="bib68" firstref="ref175"></nolink> <nolink nlid="nl96" bibid="bib18" firstref="ref183"></nolink> <nolink nlid="nl97" bibid="bib75" firstref="ref184"></nolink>
Header DbId: eric
DbLabel: ERIC
An: EJ1418608
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Associations between Urbanization and the Home Language Environment: Evidence from a LENA Study in Rural and Peri-Urban China
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Yue+Ma%22">Yue Ma</searchLink><br /><searchLink fieldCode="AR" term="%22Xinwu+Zhang%22">Xinwu Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Lucy+Pappas%22">Lucy Pappas</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2476-3286">0000-0002-2476-3286</externalLink>)<br /><searchLink fieldCode="AR" term="%22Andrew+Rule%22">Andrew Rule</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5674-8550">0000-0001-5674-8550</externalLink>)<br /><searchLink fieldCode="AR" term="%22Yujuan+Gao%22">Yujuan Gao</searchLink><br /><searchLink fieldCode="AR" term="%22Sarah-Eve+Dill%22">Sarah-Eve Dill</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9321-6606">0000-0002-9321-6606</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tianli+Feng%22">Tianli Feng</searchLink><br /><searchLink fieldCode="AR" term="%22Yue+Zhang%22">Yue Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Hong+Wang%22">Hong Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Flavio+Cunha%22">Flavio Cunha</searchLink><br /><searchLink fieldCode="AR" term="%22Scott+Rozelle%22">Scott Rozelle</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Child+Development%22"><i>Child Development</i></searchLink>. e74-e92 2024 95(2):e74-e92.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– 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="%22Rural+Urban+Differences%22">Rural Urban Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Family+Environment%22">Family Environment</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Usage%22">Language Usage</searchLink><br /><searchLink fieldCode="DE" term="%22Infants%22">Infants</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Language%22">Child Language</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Acquisition%22">Language Acquisition</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/cdev.14034
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0009-3920<br />1467-8624
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In low- and middle-income countries, urbanization has spurred the expansion of peri-urban communities, or urban communities of formerly rural residents with low socioeconomic status. The growth of these communities offers researchers an opportunity to measure the associations between the level of urbanization and the home language environment (HLE) among otherwise similar populations. Data were collected in 2019 using Language Environment Analysis observational assessment technology from 158 peri-urban and rural households with Han Chinese children (92 males, 66 females) aged 18-24 months in China. Peri-urban children scored lower than rural children in measures of the HLE and language development. In both samples, child age, gender, maternal employment, and sibling number were positively correlated with the HLE, which was in turn correlated with language development.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1418608
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1418608
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/cdev.14034
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: e74
    Subjects:
      – SubjectFull: Rural Urban Differences
        Type: general
      – SubjectFull: Family Environment
        Type: general
      – SubjectFull: Language Usage
        Type: general
      – SubjectFull: Infants
        Type: general
      – SubjectFull: Child Language
        Type: general
      – SubjectFull: Language Acquisition
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: Associations between Urbanization and the Home Language Environment: Evidence from a LENA Study in Rural and Peri-Urban China
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yue Ma
      – PersonEntity:
          Name:
            NameFull: Xinwu Zhang
      – PersonEntity:
          Name:
            NameFull: Lucy Pappas
      – PersonEntity:
          Name:
            NameFull: Andrew Rule
      – PersonEntity:
          Name:
            NameFull: Yujuan Gao
      – PersonEntity:
          Name:
            NameFull: Sarah-Eve Dill
      – PersonEntity:
          Name:
            NameFull: Tianli Feng
      – PersonEntity:
          Name:
            NameFull: Yue Zhang
      – PersonEntity:
          Name:
            NameFull: Hong Wang
      – PersonEntity:
          Name:
            NameFull: Flavio Cunha
      – PersonEntity:
          Name:
            NameFull: Scott Rozelle
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0009-3920
            – Type: issn-electronic
              Value: 1467-8624
          Numbering:
            – Type: volume
              Value: 95
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Child Development
              Type: main
ResultId 1