Background: Papua New Guinea (PNG) is undergoing an epidemiological transition with increased mortality from NCDs. This study examined NCDs-attributed mortality and associated sociodemographic factors in PNG.
Method: Using WHO 2016 instrument, 926 verbal autopsy (VA) interviews were conducted in six major provinces from January 2018 to December 2020. InterVA-5 tool was used to assign causes of death (COD). Multivariable logistic regression analysis was performed to identify sociodemographic factors associated with mortalities from emerging and endemic NCDs.
Finding: NCDs accounted for 47% of the total deaths, including 20% of deaths attributed to emerging NCDs and 27% of deaths due to endemic NCDs. Leading CODs from emerging NCDs were identified including cardiac diseases, stroke, and diabetes. The risk of dying from emerging NCDs was significantly lower among populations under age 44y compared with population aged 75+y (OR: 0.14 [0.045-0.433]; p-value: 0.001). People living in urban areas were twice likely to die from emerging NCDs than those in rural areas (OR: 1.92 [1.116-3.31]; p-value: 0.018). People in Madang province were 70% less likely to die from emerging NCDs compared to those from East New Britain province (OR: 0.314 [0.135-0.73]; p-value: 0.007). Leading CODs from endemic NCDs included digestive neoplasms, respiratory neoplasms, and other neoplasms. Only children aged 0-4y had significant lower risk of dying from endemic NCDs compared to the population aged 75+y (OR: 0.114 [95% CI: 0.014-0.896]; p-value: 0.039).
Conclusion: Public health interventions are urgently needed, prioritizing urban population and those aged over 44y to reduce premature mortality from NCDs.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021879 | PMC |
http://dx.doi.org/10.1371/journal.pgph.0000118 | DOI Listing |
BMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
View Article and Find Full Text PDFFront Nutr
December 2024
Department of Nutrition and Food Sciences, Faculty of Agricultural and Food Sciences, American University of Beirut, Beirut, Lebanon.
Objective: This pilot study aims to assess the diet quality amongst Lebanese male university students using the Global Diet Quality Score (GDQS), identify its association with obesity, and determine the key drivers of consumption of foods associated with higher NCDs risk.
Methods: A cross-sectional survey was conducted using a convenience sampling approach, comprising 385 male students aged between 18 and 24 years at the American University of Beirut. Dietary data was collected using 24-h recall, where participants detailed all foods and beverages consumed in the past 24 h, including portion sizes.
Background: The COVID-19 pandemic has led to a significant shift in healthcare services, focusing on pandemic response and emergency preparedness. The Oman Ministry of Health implemented various measures to combat and control COVID-19. However, this shift disrupted routine outpatient appointments, particularly for chronic diseases such as diabetes mellitus (DM) and hypertension (HTN).
View Article and Find Full Text PDFLancet Oncol
December 2024
International Atomic Energy Agency, Vienna, Austria.
Global efforts to highlight cancer and non-communicable diseases (NCDs) as a growing burden were first raised in 2005 World Health Assembly Resolution 58.22 and reinforced with Resolution 70.12 and the Global NCD action plan in 2017.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Biostatistics, Amrita Institute of Medical Sciences Amrita Vishwa Vidyapeetham, Kochi, Kerala, India.
Background: Multimorbidity, the coexistence of two or more chronic conditions in an individual, has emerged as a significant public health challenge with profound economic implications, exerting substantial strain on healthcare systems and economies worldwide. This study aimed to estimate the prevalence of non-communicable diseases (NCD) related multimorbidity, catastrophic health expenditure (CHE), and associated factors among adults aged ≥40 years in Ernakulam district.
Methods: A community-based cross-sectional study was conducted among 420 individuals aged ≥40 years using population probability sampling.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!