Datta Jayanta, Sinha Prasenjit
Department of Statistics, Tripura University, Suryamaninagar, Agartala, West Tripura, India.
Indian J Community Med. 2024 Jan-Feb;49(1):189-194. doi: 10.4103/ijcm.ijcm_1088_21. Epub 2024 Jan 12.
Accurate information on age is an essential prerequisite for demographic and epidemiological studies. This study analyzed the age data quality among the literate and illiterate (combined, rural, urban) population and examined the association between data quality and literacy.
Secondary data on age statistics and literacy were obtained from census 2011. We measured age data quality for literates and illiterates (combined, rural, urban) by transforming Whipple's index known as ABCC, abbreviated based on surnames of the developers A'Hearn, Baten, and Crayen (2009). Correlation tests between literacy and ABCC were performed. RStudio (Version 1.3.1073) was used.
Computed ABCC indices in majority states (union territories) for literates (data quality rough) were higher than illiterates (data quality very rough). Urban data among literates and rural data among illiterates were comparatively superior. Correlation between ABCC and literacy rates for (i) literate combined (R = 0.84, = 3.5e), (ii) literate rural (R = 0.8, = 1.1e), (iii) literate urban (R = 0.8, = 1e), (iv) illiterate combined (R = 0.54, = 9e), (v) illiterate rural (R = 0.48, = 0.0034), and (vi) illiterate urban (R = 0.73, = 6.4e) was significant. Age data quality for both literates and illiterates was poor. There was heaping at terminal digits "0" and "5" even among literates, which contradicts the theoretical expectation of quality data among literates.
Correlations between data quality and literacy were significant, with comparatively lower magnitude among illiterates, which indicates the role of literacy in yielding quality data. Awareness, training, ADHAAR-based enumeration, and digitization may be suggested for better age data.
准确的年龄信息是人口统计学和流行病学研究的重要前提。本研究分析了识字和不识字人群（包括农村、城市总体）的年龄数据质量，并检验了数据质量与识字率之间的关联。
年龄统计和识字率的二手数据取自2011年人口普查。我们通过转换以ABCC闻名的惠普尔指数来衡量识字者和不识字者（包括农村、城市总体）的年龄数据质量，该指数根据开发者A'Hearn、Baten和Crayen的姓氏缩写（2009年）。进行了识字率与ABCC之间的相关性检验。使用了RStudio（版本1.3.1073）。
大多数邦（中央直辖区）识字者（数据质量粗略）的计算ABCC指数高于不识字者（数据质量非常粗略）。识字者中的城市数据和不识字者中的农村数据相对较好。（i）识字者总体（R = 0.84，P = 3.5e）、（ii）农村识字者（R = 0.8，P = 1.1e）、（iii）城市识字者（R = 0.8，P = 1e）、（iv）不识字者总体（R = 0.54，P = 9e）、（v）农村不识字者（R = 0.48，P = 0.0034）和（vi）城市不识字者（R = 0.73，P = 6.4e）的ABCC与识字率之间的相关性显著。识字者和不识字者的年龄数据质量都很差。即使在识字者中，末位数字“0”和“5”也存在堆积现象，这与识字者中高质量数据的理论预期相矛盾。
数据质量与识字率之间的相关性显著，不识字者中的相关性相对较低，这表明识字率在产生高质量数据方面的作用。为了获得更好的年龄数据，建议提高意识、进行培训、基于AADHAAR进行人口普查以及数字化。
