{"title":"利用调查逻辑回归分析加蓬、冈比亚、利比里亚、毛里塔尼亚和尼日利亚五个西非国家儿童(0-59 个月)营养不良的决定因素--来自人口与健康调查数据的启示。","authors":"Reshav Beni, Shaun Ramroop, Faustin Habyarimana","doi":"10.1186/s13690-024-01374-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Malnutrition is one of the most critical health challenges confronting public health agencies in developing nations. This study aimed to determine the scope and underlying factors contributing to malnutrition in West African countries, specifically Gabon, Gambia, Liberia, Mauritania, and Nigeria.</p><p><strong>Method: </strong>For this secondary data analysis, this study drew upon the demographic and health surveys (DHS) conducted within these West African nations. These surveys employed a complex sampling design involving a combination of stratification and cluster sampling in two stages, with varying probabilities of selection leading to weighted samples that effectively represented different components of the population. Given the intricacies of this sampling design, it is paramount to account for them when analyzing the survey data. To address this concern, this study applied a survey logistic regression model, which accommodates factors such as stratification, clustering, and sampling weights and departs from the assumption of independence inherent in the ordinary logistic regression model.</p><p><strong>Results: </strong>The outcomes of this model revealed several variables that emerged as statistically significant (p < 0.05) determinants of malnutrition. These influential factors encompass the region of the respondent, the current age of the mother, the highest level of education attained by the mother, the source of drinking water, the type of toilet facility, the household's wealth status, the age and gender of the child, and whether the child experienced a fever in the preceding two weeks.</p><p><strong>Conclusion: </strong>These findings demonstrate with poignant clarity the importance of primary health care interventions in the recognition and management of malnutrition. The countries of interest should invest in public health care interventions including community workshops and outreach programs. Workshops may occur at primary health care facilities during queue waits, or health workers may work with community leaders to perform workshops in areas of high foot traffic, such as places of worship, shopping hubs and collection points for financial aid or grants.</p>","PeriodicalId":48578,"journal":{"name":"Archives of Public Health","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373175/pdf/","citationCount":"0","resultStr":"{\"title\":\"Analyzing childhood (0-59 months) malnutrition determinants in five West African Countries of Gabon, Gambia, Liberia, Mauritania, and Nigeria using survey logistic regression-insights from DHS data.\",\"authors\":\"Reshav Beni, Shaun Ramroop, Faustin Habyarimana\",\"doi\":\"10.1186/s13690-024-01374-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Malnutrition is one of the most critical health challenges confronting public health agencies in developing nations. This study aimed to determine the scope and underlying factors contributing to malnutrition in West African countries, specifically Gabon, Gambia, Liberia, Mauritania, and Nigeria.</p><p><strong>Method: </strong>For this secondary data analysis, this study drew upon the demographic and health surveys (DHS) conducted within these West African nations. These surveys employed a complex sampling design involving a combination of stratification and cluster sampling in two stages, with varying probabilities of selection leading to weighted samples that effectively represented different components of the population. Given the intricacies of this sampling design, it is paramount to account for them when analyzing the survey data. To address this concern, this study applied a survey logistic regression model, which accommodates factors such as stratification, clustering, and sampling weights and departs from the assumption of independence inherent in the ordinary logistic regression model.</p><p><strong>Results: </strong>The outcomes of this model revealed several variables that emerged as statistically significant (p < 0.05) determinants of malnutrition. These influential factors encompass the region of the respondent, the current age of the mother, the highest level of education attained by the mother, the source of drinking water, the type of toilet facility, the household's wealth status, the age and gender of the child, and whether the child experienced a fever in the preceding two weeks.</p><p><strong>Conclusion: </strong>These findings demonstrate with poignant clarity the importance of primary health care interventions in the recognition and management of malnutrition. The countries of interest should invest in public health care interventions including community workshops and outreach programs. Workshops may occur at primary health care facilities during queue waits, or health workers may work with community leaders to perform workshops in areas of high foot traffic, such as places of worship, shopping hubs and collection points for financial aid or grants.</p>\",\"PeriodicalId\":48578,\"journal\":{\"name\":\"Archives of Public Health\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373175/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Public Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13690-024-01374-6\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Public Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13690-024-01374-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Analyzing childhood (0-59 months) malnutrition determinants in five West African Countries of Gabon, Gambia, Liberia, Mauritania, and Nigeria using survey logistic regression-insights from DHS data.
Background: Malnutrition is one of the most critical health challenges confronting public health agencies in developing nations. This study aimed to determine the scope and underlying factors contributing to malnutrition in West African countries, specifically Gabon, Gambia, Liberia, Mauritania, and Nigeria.
Method: For this secondary data analysis, this study drew upon the demographic and health surveys (DHS) conducted within these West African nations. These surveys employed a complex sampling design involving a combination of stratification and cluster sampling in two stages, with varying probabilities of selection leading to weighted samples that effectively represented different components of the population. Given the intricacies of this sampling design, it is paramount to account for them when analyzing the survey data. To address this concern, this study applied a survey logistic regression model, which accommodates factors such as stratification, clustering, and sampling weights and departs from the assumption of independence inherent in the ordinary logistic regression model.
Results: The outcomes of this model revealed several variables that emerged as statistically significant (p < 0.05) determinants of malnutrition. These influential factors encompass the region of the respondent, the current age of the mother, the highest level of education attained by the mother, the source of drinking water, the type of toilet facility, the household's wealth status, the age and gender of the child, and whether the child experienced a fever in the preceding two weeks.
Conclusion: These findings demonstrate with poignant clarity the importance of primary health care interventions in the recognition and management of malnutrition. The countries of interest should invest in public health care interventions including community workshops and outreach programs. Workshops may occur at primary health care facilities during queue waits, or health workers may work with community leaders to perform workshops in areas of high foot traffic, such as places of worship, shopping hubs and collection points for financial aid or grants.
期刊介绍:
rchives of Public Health is a broad scope public health journal, dedicated to publishing all sound science in the field of public health. The journal aims to better the understanding of the health of populations. The journal contributes to public health knowledge, enhances the interaction between research, policy and practice and stimulates public health monitoring and indicator development. The journal considers submissions on health outcomes and their determinants, with clear statements about the public health and policy implications. Archives of Public Health welcomes methodological papers (e.g., on study design and bias), papers on health services research, health economics, community interventions, and epidemiological studies dealing with international comparisons, the determinants of inequality in health, and the environmental, behavioural, social, demographic and occupational correlates of health and diseases.