绘制印度五岁以下儿童同时消耗和发育迟缓的地图:多层次分析
Bikash Khura1, Parimala Mohanty2, Aravind P Gandhi3
1International Institute for Population Sciences, Mumbai, India.
International journal of public health
|June 23, 2023
概括
印度五岁以下儿童的同时消耗和发育迟缓 (WaSt) 已经减少,但在男孩和出生次数较高的儿童中仍然较高. 母亲的教育和家庭财富显著降低了WaSt风险.
科学领域:
- 儿科和儿童健康 儿科和儿童健康
- 公共卫生和流行病学
- 营养科学 营养科学
背景情况:
- 同时消耗和衰减 (WaSt) 是五岁以下儿童严重营养不良的一种形式.
- 了解WaSt的趋势,模式和预测因素对于印度的有针对性的干预至关重要.
研究的目的:
- 检查印度五岁以下儿童同时消耗和衰老 (WaSt) 的共存形式,模式和预测因素.
- 用国家调查数据分析WaSt的趋势和关联.
主要方法:
- 利用印度国家家庭健康调查 (NFHS) 对五岁以下儿童的数据.
- 采用单变量分析,交叉表格和多层次二进制逻辑回归来确定关联.
- 结果呈现为调整后的几率比率 (aOR) 与95%的置信区间 (CI).
主要成果:
- 瓦斯特的患病率从8.7% (2005-06) 下降到5.2% (2019-20).
- 在6-18个月之间,WaSt达到峰值,男孩的患病率更高,出生顺序更高 (aOR=1.20),母亲教育程度更低 (aOR=0.63).
- 来自富裕家庭的儿童患WaSt的风险明显较低 (aOR=0.48).
结论:
- 同时消耗和衰老仍然是印度的一个重大公共卫生问题.
- 社会经济因素,包括母亲的教育和家庭财富,与西班牙人密切相关.
- 针对这些社会经济决定因素的有针对性的干预措施对于减少 WaSt.是必不可少的.
相关概念视频
Confounding in Epidemiological Studies
196
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
196
Strategies for Assessing and Addressing Confounding
122
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
122
Bias in Epidemiological Studies
375
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
375
Comparing the Survival Analysis of Two or More Groups
228
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
228
Longitudinal Studies
191
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
191
Statistical Methods for Analyzing Epidemiological Data
426
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
426


