赞比亚卢萨卡大学教学医院妇女和新生儿医院的社会经济地位与不良分娩结果的关系

Agripa Lungu, L. Kasonka, B. Vwalika
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引用次数: 0

摘要

背景:在世界范围内,低社会经济地位通常与不良出生结局有关。在世界范围内,不良出生结局显著影响围产期发病率和死亡率,一些文献显示了相互矛盾的结果。在赞比亚的妇女和新生儿医院,这种关系在新生儿预后不良的妇女中尚不清楚;因此,这项研究是为了探索社会经济地位和不良出生结果之间的关系。方法:采用回顾性队列研究。检索2015年8月至2017年9月期间前瞻性收集的ZAPPS研究的次要数据。总共检索了1,450名参与者的信息,其中1,084条数据记录在排除不符合资格标准的数据后进行分析。社会经济地位是一个解释变量,使用14个变量的主成分分析得出的标准化财富分数来估计。富有的五分之一被进一步划分为贫穷和不贫穷。应答变量为低出生体重、早产和胎龄小。结果:本研究发现SGA、LBW和早产的发生率分别为164、124和13.5 / 1000活产。在生存分析中,与富裕母亲所生的婴儿(87.5%)相比,贫穷母亲所生的婴儿存活LBW的比例(82.9%)较低(p值= 0.189)。此外,与非贫困母亲所生的婴儿(85.8%)(p值= 0.032)相比,贫困母亲所生的婴儿(78.4%)比富裕母亲所生的婴儿(83.6%)(p值= 0.022)更低(79.1%),而贫困母亲所生的婴儿(78.4%)更低(p值= 0.022)。在多重Cox回归分析中,社会经济状况不是SGA的显著危险因素(aHR = 1.08;95%可信区间;p=0.099)、体重与早产(aHR = 1.17;95%可信区间;p = l.41)。然而,男婴(aHR = 1.80;95%可信区间;p=0.012)、孕期家庭暴力或虐待(aHR = 3.48;95% ci [1.59 - 7.34];p = 0.002)和产妇贫血(aHR = 2.1;95%可信区间;p = 0.019)是SGA的危险因素,而有过早产史(aHR = 2.02;95%可信区间;p = 0.002), HIV感染(aHR = 1.22;95%可信区间;p = 0.040)和贫血(aHR = 1.37;95%可信区间;P = 0.009)是早产的预测因子。结论:低社会经济地位与不良出生结局之间无统计学意义的关联,但怀孕男婴、HIV感染、贫血和先前早产与sgaa和早产显著相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of socioeconomic status with adverse birth outcomes at the Women and Newborn Hospital of the University Teaching Hospitals in Lusaka, Zambia
Background: Low socioeconomic status has generally been associated with adverse birth outcomes worldwide. Adverse birth outcomes significantly contribute to perinatal morbidity and mortality worldwide with some literatures showing conflicting results. At Women and New-born Hospital in Zambia, this relationship had remained unclear among women who experienced poor neonatal outcome; hence the study was done to explore this association between socioeconomic status and adverse birth outcomes. Methods: A retrospective cohort study was conducted. Secondary data from ZAPPS study that had been collected prospectively between August 2015 and September 201 7 was retrieved. Altogether, 1,450 participants' information was retrieved, out of which 1,084 data records were set out for analysis after excluding those not meeting eligibility criteria. Socioeconomic status was an explanatory variable which was estimated using the standardized wealth score derived from principal component analysis of 14 variables. The wealth quintiles were further categorised into poor and not poor. Response variables were low birth weight, preterm birth and small for gestation age. SPSS version 21 was used for data analysis and p value< 0.05 was significant  Results: This study found the incidences of SGA, LBW and preterm births to be 164, 124 and 13 5 per 1000 live births respectively. In survival analysis, the proportion of babies who survived LBW among mothers who were poor was lower (82.9%) compared to babies born to rich mothers (87.5%) (p-value = 0.189). Furthermore, the proportion of babies who survived SGA for the poor was lower (79 .1 % ) compared to babies born to none poor mothers (85.8%) (p-value = 0.032) and preterm birth for the poor (78.4%) compared to babies born to mothers who were rich (83 .6%) (p-value = 0.022). In multiple Cox regression analysis socioeconomic status was not a significant risk factor for SGA ( aHR = 1.08; 95% CI; p=0.099), LBW and preterm birth (aHR = 1.17; 95% CI; p= l.41). However, male babies (aHR = 1.80; 95% CI; p=0.012), domestic violence or abuse during pregnancy (aHR = 3.48; 95% CI [1.59 - 7.34]; p = 0.002) and maternal anaemia (aHR = 2.1; 95% CI; p = 0.019) were risk factors for SGA while prior preterm birth ( aHR = 2.02; 95% CI; p = 0.002), HIV infection (aHR = 1.22; 95% CI; p = 0.040) and anaemia (aHR = 1.37; 95% CI; p = 0.009) were predictors of preterm delivery.  Conclusion: There was no statistically significant association between low socioeconomic status and adverse birth outcomes although being pregnant with a male baby, HIV infection, anaemia and prior preterm birth were significantly associated with SGAand preterm.
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