Discipline of Paediatrics, School of Clinical Medicine, University of New South Wales, Sydney, NSW, 2031, Australia.
School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, 2006, Australia.
Matern Child Health J. 2024 Oct;28(10):1677-1684. doi: 10.1007/s10995-024-03975-7. Epub 2024 Aug 23.
The prevalence of low birth weight (LBW) is an important indicator of child health and wellbeing. However, in many countries, decisions regarding care and treatment are often based on mothers' perceptions of their children's birth size due to a lack of objective birth weight data. Additionally, birth weight data that is self-reported or recorded often encounters the issue of heaping. This study assesses the concordance between the perceived birth size and the reported or recorded birth weight. We also investigate how the presence of heaped birth weight data affects this concordance, as well as the relationship between concordance and various sociodemographic factors.
We examined 4,641 birth records reported in the 2019 Bangladesh Multiple Indicator Cluster Survey. The sensitivity-specificity analysis was performed to assess perceived birth size's ability to predict LBW, while Cohen's Kappa statistic assessed reliability. We used the kernel smoothing technique to correct heaping of birth weight data, as well as a multivariable multinomial logistic model to assess factors associated with concordance.
Maternally-perceived birth size exhibited a low sensitivity (63.5%) and positive predictive value (52.6%) for predicting LBW, but a high specificity (90.1%) and negative predictive value (93.4%). There was 86.1% agreement between birth size and birth weight-based classifications (Kappa = 0.49, indicating moderate agreement). Smoothed birth weight data did not improve agreement (83.4%, Kappa = 0.45). Of the sociodemographic factors, early marriage was positively associated with discordance (i.e., overestimation).
An important consideration when calculating the LBW prevalence is that maternally perceived birth size is not an optimal proxy for birth weight. Focus should be placed on encouraging institutional births and educating community health workers and young mothers about the significance of measuring and recording birth weight.
低出生体重（LBW）的发生率是儿童健康和福祉的一个重要指标。然而，在许多国家，由于缺乏客观的出生体重数据，医疗决策往往基于母亲对子女出生大小的感知。此外，自我报告或记录的出生体重数据经常存在堆积问题。本研究评估了感知出生大小与报告或记录的出生体重之间的一致性。我们还研究了堆积出生体重数据的存在如何影响这种一致性，以及一致性与各种社会人口因素之间的关系。
我们分析了 2019 年孟加拉国多指标类集调查报告的 4641 份出生记录。我们进行了敏感性-特异性分析，以评估感知出生大小预测 LBW 的能力，同时使用 Cohen's Kappa 统计量评估可靠性。我们使用核平滑技术校正出生体重数据的堆积，使用多变量多项逻辑回归模型评估与一致性相关的因素。
母亲感知的出生大小对预测 LBW 的敏感性（63.5%）和阳性预测值（52.6%）较低，但特异性（90.1%）和阴性预测值（93.4%）较高。出生大小与基于出生体重的分类之间有 86.1%的一致性（Kappa=0.49，表明中度一致）。平滑后的出生体重数据并没有提高一致性（83.4%，Kappa=0.45）。在社会人口因素中，早婚与不一致（即高估）呈正相关。
在计算 LBW 发生率时，需要考虑到母亲感知的出生大小并不是出生体重的理想替代指标。应重点鼓励机构分娩，并教育社区卫生工作者和年轻母亲测量和记录出生体重的重要性。
