NDLI: A distributional regression approach to modeling the impact of structural and intermediary social determinants on communities burdened by tuberculosis in Eastern Amazonia

Content Provider	Springer Nature : BioMed Central
Author	Giacomet, Clóvis Luciano Ramos, Antônio Carlos Vieira Moura, Heriederson Sávio Dias Berra, Thaís Zamboni Alves, Yan Mathias Delpino, Felipe Mendes Farley, Jason E. Reynolds, Nancy R. Alonso, Jonas Bodini Teibo, Titilade Kehinde Ayandeyi Arcêncio, Ricardo Alexandre
Abstract	Background Tuberculosis (TB) is a disease that is influenced by social determinants of health. However, the specific structural and intermediary determinants of TB in Eastern Amazonia remain unclear. Despite being rich in natural resources, the region faces significant challenges related to poverty, inequality, and neglected diseases. The objective of this study was to use mathematical modeling to evaluate the influence of structural and intermediary determinants of health on TB in Eastern Amazonia, Brazil. Methods This cross-sectional included all TB cases diagnosed and registered in the Notifiable Diseases Information System (SINAN) from 2001 to 2017. Data on social determinants were collected at the census tract level. The generalized additive model for location, scale, and shape (GAMLSS) framework was employed to identify the effect of social determinants on communities with a high TB prevalence. The Double Poisson distribution (DPO) was chosen, and inclusion of quadratic effects was tested. Results A total of 1730 individuals were diagnosed with TB and reported in SINAN during the analyzed period. The majority were female (59.3%), aged 31 to 59 years (47.6%), identified as blacks (67.9%), and had incomplete elementary education (46.6%). The prevalence of alcoholism was 8.6% and mental illness was 0.7%. GAMLSS analyses demonstrated that the risk of community incidence of TB is associated with the proportion of the population lacking basic sanitation, as well as with the age groups of 16–31 years and > 61 years. Conclusions The study highlights the strategic utility of GAMLSS in identifying high-risk areas for TB. Models should encompass a broader range of social determinants to inform policies aimed at reducing inequality and achieving the goals of the End TB strategy.
Related Links	https://archpublichealth.biomedcentral.com/counter/pdf/10.1186/s13690-023-01147-7.pdf
Ending Page	15
Page Count	15
Starting Page	1
File Format	HTM / HTML
ISSN	20493258
DOI	10.1186/s13690-023-01147-7
Journal	Archives of Public Health
Issue Number	1
Volume Number	81
Language	English
Publisher	BioMed Central
Publisher Date	2023-07-20
Access Restriction	Open
Subject Keyword	Public Health Medicine Health Policy Health Services Research Health Informatics Epidemiology Ecological studies Social determinants of health GAMLSS Medicine/Public Health
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health
Journal Impact Factor	3.2/2023
5-Year Journal Impact Factor	3.3/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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