B. Pham, Tess Aga, Rebecca Emori, Doris Manong, S. Maraga, Billiam Degemba, Vicky Gabe, Noel Berry, Michael Kobol, Lydia Kue, Nanim Ainui, Ronny Jorry, Vinson D Silas, Norah Abori, Gasowo S Jaukae, Guise Gende, Toan H Ha, A. Okely, William Pomat
{"title":"评估 COVID-19 和相关家庭社会经济因素对巴布亚新几内亚健康的影响:来自综合健康和流行病监测系统的证据","authors":"B. Pham, Tess Aga, Rebecca Emori, Doris Manong, S. Maraga, Billiam Degemba, Vicky Gabe, Noel Berry, Michael Kobol, Lydia Kue, Nanim Ainui, Ronny Jorry, Vinson D Silas, Norah Abori, Gasowo S Jaukae, Guise Gende, Toan H Ha, A. Okely, William Pomat","doi":"10.1136/bmjph-2023-000563","DOIUrl":null,"url":null,"abstract":"The COVID-19 pandemic had an unprecedented impact on the health and well-being of populations worldwide. Few studies have used household data to explore the health risks associated with COVID-19 in low-income and middle-income countries. This study assessed population vulnerability to COVID-19 by examining household socioeconomic factors related to COVID-19 health risks in Papua New Guinea (PNG).Using household socioeconomic surveillance data from 2020, encompassing 37 880 residents living within the catchment areas of the Comprehensive Health and Epidemiological Surveillance System, the study assessed COVID-19 health risks based on the socioeconomic demographic characteristics of the surveillance population. Multinomial logistic regression analyses were conducted to determine associated factors and to estimate predictors of COVID-19 health risks.Among the surveillance population, more than 9% reported experiencing COVID-19 health risks, including home-based quarantine (9.6%), centre-based quarantine (0.5%), positive COVID-19 test (0.1%), hospitalisation due to COVID-19 (0.3%) and death from COVID-19 (0.3%). People living in semimodern houses (OR 1.47 (95% CI 1.35 to 1.61)) (verse permanent houses), individuals living in houses with 1–2 bedrooms (OR 1.12 (95% CI 1.01 to 1.25)) (verse houses with 4+ bedrooms) and those belonging to the poorest wealth quintile (OR 1.16 (95% CI 1.024 to 1.314)) (verse the richest) were more susceptible to COVID-19 health risks. Protective factors against COVID-19 health risks included urban residence (OR 0.65 (95% CI 0.59 to 0.71)) (verse rurality), aged 0–4 years (OR 0.76 (95% CI 0.64 to 0.91)) (verse aged 55+ years), households with 7–8 members (OR 0.84 (95% CI 0.74 to 0.96)) (verse 10+ members), handwashing with soap (OR 0.3 (95% CI 0.28 to 0.33)) (verse without soap).The study provides insights into the susceptibility to COVID-19 health risks across socioeconomic groups in PNG. 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Multinomial logistic regression analyses were conducted to determine associated factors and to estimate predictors of COVID-19 health risks.Among the surveillance population, more than 9% reported experiencing COVID-19 health risks, including home-based quarantine (9.6%), centre-based quarantine (0.5%), positive COVID-19 test (0.1%), hospitalisation due to COVID-19 (0.3%) and death from COVID-19 (0.3%). People living in semimodern houses (OR 1.47 (95% CI 1.35 to 1.61)) (verse permanent houses), individuals living in houses with 1–2 bedrooms (OR 1.12 (95% CI 1.01 to 1.25)) (verse houses with 4+ bedrooms) and those belonging to the poorest wealth quintile (OR 1.16 (95% CI 1.024 to 1.314)) (verse the richest) were more susceptible to COVID-19 health risks. 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引用次数: 0
摘要
2019冠状病毒病大流行对全世界人民的健康和福祉产生了前所未有的影响。在低收入和中等收入国家,很少有研究使用家庭数据来探索与COVID-19相关的健康风险。本研究通过检查巴布亚新几内亚与COVID-19健康风险相关的家庭社会经济因素,评估了人口对COVID-19的脆弱性。该研究利用2020年以来的家庭社会经济监测数据,包括生活在健康和流行病学综合监测系统集水区的37880名居民,根据监测人群的社会经济人口统计学特征评估了COVID-19的健康风险。进行多项逻辑回归分析以确定相关因素并估计COVID-19健康风险的预测因子。在监测人群中,超过9%的人报告存在COVID-19健康风险,包括家庭隔离(9.6%)、中心隔离(0.5%)、COVID-19检测阳性(0.1%)、因COVID-19住院(0.3%)和因COVID-19死亡(0.3%)。居住在半现代房屋(OR 1.47 (95% CI 1.35至1.61))(相对于永久性房屋)、居住在1-2间卧室房屋(OR 1.12 (95% CI 1.01至1.25))(相对于4间以上卧室的房屋)和属于最贫穷财富五分之一(OR 1.16 (95% CI 1.024至1.314))(相对于最富有的房屋)的人更容易受到COVID-19健康风险的影响。预防COVID-19健康风险的保护因素包括城市居住(OR 0.65 (95% CI 0.59至0.71))(农村)、0-4岁(OR 0.76 (95% CI 0.64至0.91))(55岁以上)、7-8人家庭(OR 0.84 (95% CI 0.74至0.96))(10人以上)、用肥皂洗手(OR 0.3 (95% CI 0.28至0.33))(不使用肥皂)。该研究为巴布亚新几内亚社会经济群体对COVID-19健康风险的易感性提供了见解。这些发现对公共卫生政策和干预措施的制定具有启示意义,这些政策和干预措施可以外推到类似的环境中,以加强对未来突发公共卫生事件的防范。
Assessing health impact of COVID-19 and associated household socioeconomic factors in Papua New Guinea: evidence from the Comprehensive Health and Epidemiological Surveillance System
The COVID-19 pandemic had an unprecedented impact on the health and well-being of populations worldwide. Few studies have used household data to explore the health risks associated with COVID-19 in low-income and middle-income countries. This study assessed population vulnerability to COVID-19 by examining household socioeconomic factors related to COVID-19 health risks in Papua New Guinea (PNG).Using household socioeconomic surveillance data from 2020, encompassing 37 880 residents living within the catchment areas of the Comprehensive Health and Epidemiological Surveillance System, the study assessed COVID-19 health risks based on the socioeconomic demographic characteristics of the surveillance population. Multinomial logistic regression analyses were conducted to determine associated factors and to estimate predictors of COVID-19 health risks.Among the surveillance population, more than 9% reported experiencing COVID-19 health risks, including home-based quarantine (9.6%), centre-based quarantine (0.5%), positive COVID-19 test (0.1%), hospitalisation due to COVID-19 (0.3%) and death from COVID-19 (0.3%). People living in semimodern houses (OR 1.47 (95% CI 1.35 to 1.61)) (verse permanent houses), individuals living in houses with 1–2 bedrooms (OR 1.12 (95% CI 1.01 to 1.25)) (verse houses with 4+ bedrooms) and those belonging to the poorest wealth quintile (OR 1.16 (95% CI 1.024 to 1.314)) (verse the richest) were more susceptible to COVID-19 health risks. Protective factors against COVID-19 health risks included urban residence (OR 0.65 (95% CI 0.59 to 0.71)) (verse rurality), aged 0–4 years (OR 0.76 (95% CI 0.64 to 0.91)) (verse aged 55+ years), households with 7–8 members (OR 0.84 (95% CI 0.74 to 0.96)) (verse 10+ members), handwashing with soap (OR 0.3 (95% CI 0.28 to 0.33)) (verse without soap).The study provides insights into the susceptibility to COVID-19 health risks across socioeconomic groups in PNG. These findings have implications for development of public health policies and interventions that can be extrapolated to similar settings for enhancing preparedness for future public health emergencies.