Twenty-Year Trends in Sex-Based Mortality Inequality in Infectious and Parasitic Diseases in Sierra Leone: A WHO HEAT-Based Analysis

Twenty-Year Trends in Sex-Based Mortality Inequality in Infectious and Parasitic Diseases in Sierra Leone: A WHO HEAT-Based Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Twenty-Year Trends in Sex-Based Mortality Inequality in Infectious and Parasitic Diseases in Sierra Leone: A WHO HEAT-Based Analysis Alpha Umaru Bai-Sesay, Daniel Karim Dauda Sesay, Alieu Tommy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7021288/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Infectious and parasitic diseases, including malaria, HIV/AIDS, and tuberculosis, are leading causes of mortality in low-income countries like Sierra Leone. Despite progress in reducing mortality, sex-based disparities persist. This study examines trends in sex-based inequalities in mortality from infectious and parasitic diseases in Sierra Leone from 2001 to 2021. Methods: Using the World Health Organization’s Global Health Estimates from the WHO equity standardized data set, 2024 update, we analyzed mortality rates (deaths per 100,000 population) for infectious and parasitic diseases by sex (male and female) in 2001, 2006, 2011, 2016, and 2021. The Health Equity Assessment Toolkit (HEAT, Version 6.1) was used to compute four inequality metrics: Difference, Ratio, Population Attributable Fraction, and Population Attributable Risk, following WHO methodology. Results: Mortality rates declined substantially from 2001 to 2021, with female mortality decreasing from 792.3 to 258.5 per 100,000 and male mortality from 862.6 to 289.0 per 100,000. The absolute difference narrowed from −70.4 to −30.6, with males consistently showing higher mortality. The relative ratio remained stable at 0.9. PAF and PAR were consistently 0 (95% CIs crossing zero), indicating no significant population-level burden attributable to sex inequality. Conclusion: Despite notable declines in overall mortality from infectious and parasitic diseases in Sierra Leone, sex-based inequalities persist, with males experiencing a disproportionately higher burden. These findings highlight the need for targeted, gender-sensitive public health interventions to address persistent disparities and promote health equity. Sex-based inequalities Infectious and parasitic diseases Health equity WHO Global Health Estimates Sierra Leone Figures Figure 1 Introduction Infectious and parasitic diseases, including malaria, HIV/AIDS, tuberculosis, and neglected tropical diseases, remain leading causes of mortality in low- and middle-income countries (LMICs), particularly in sub-Saharan Africa, where they exacerbate premature mortality and strain fragile health systems ( 1 ). Despite global progress in reducing communicable disease burden through improved prevention, diagnostics, and treatment, health disparities persist across population subgroups, notably by sex, driven by inequities in exposure, healthcare access, and social determinants ( 2 , 3 ). These inequalities undermine the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being) and SDG 5 (Gender Equality), which emphasize equitable health outcomes for all ( 4 ). Sex-based differences in infectious disease outcomes arise from a complex interplay of biological and social factors. Biologically, males may exhibit higher susceptibility to infections such as tuberculosis and certain parasitic diseases due to sex hormone-mediated differences in immune responses ( 3 , 5 ). For instance, studies suggest men have less robust innate and adaptive immunity, increasing mortality risk from respiratory and vector-borne infections ( 5 ). Socially, gender norms shape health-seeking behavior, with men in LMICs often facing barriers to timely care due to occupational exposures or cultural expectations that discourage seeking help ( 6 ). Women, conversely, may benefit from greater engagement with health services through maternal and child health programs ( 7 ). These factors result in differential vulnerability, diagnosis, treatment, and outcomes, yet their impact on mortality trends in high-burden settings remains underexplored. Sierra Leone, a West African nation recovering from a decade-long civil conflict (1991–2002) and the 2014–2016 Ebola epidemic, faces persistent challenges from endemic infectious diseases ( 8 ). Despite investments in health system strengthening, including expanded immunization and malaria control programs, health inequalities remain a critical concern ( 9 ). Sex-disaggregated mortality data are essential to assess whether health gains are equitably distributed and to inform gender-responsive policies that address the unique needs of men and women ( 10 ). However, longitudinal analyses of sex-based disparities in infectious disease mortality in Sierra Leone are scarce, limiting evidence for targeted interventions. The World Health Organization’s Global Health Estimates (GHE) provides standardized, internationally comparable data on mortality causes, while the Health Equity Assessment Toolkit (HEAT) enables robust analysis of health inequalities using disaggregated indicators ( 11 , 12 ). These tools support routine equity monitoring, aligning with the SDG mandate to “leave no one behind” ( 4 ). This study addresses a critical research gap by analyzing sex-based inequalities in mortality from infectious and parasitic diseases in Sierra Leone from 2001 to 2021 using WHO GHE and HEAT. We assess whether these inequalities have narrowed, persisted, or widened, using absolute and relative measures, to inform sex- and gender-responsive health policies and advance health equity in a high-burden, post-conflict setting. Methods Study Design and Data Source This study employed a repeated cross-sectional design using secondary data from the WHO Global Health Estimates from the WHO equity standardized data set, 2024 update. The GHE provides standardized cause-of-death statistics based on vital registration, surveys, and model-based estimates for global comparisons enabling global comparisons of mortality patterns across population subgroups ( 1 ). Data were accessed and analyzed using the WHO Health Equity Assessment Toolkit (HEAT), Built-in database edition, Version 6.1 a software tool developed to explore and compare health inequalities using disaggregated health indicator data from international databases ( 11 ). Study Population and Time Frame The study population included the entire national population of Sierra Leone, stratified by sex (male and female), across five reference years: 2001, 2006, 2011, 2016, and 2021. These years were selected based on GHE data availability to capture a 20-year trend in mortality and inequality patterns. Health Indicator The primary health indicator was mortality from infectious and parasitic diseases, measured as the number of deaths per 100,000 population. According to ICD-10 coding, this indicator encompasses a wide range of communicable conditions, including malaria, tuberculosis, HIV/AIDS, diarrheal diseases, and other parasitic infections. Stratifier The equity stratifier used in this study was sex, with mortality estimates disaggregated for females and males. Sex-disaggregated data enable the identification and monitoring of inequalities in health outcomes and inform the development of gender-sensitive policies and programs. Outcome Variable The outcome was sex-based inequality in mortality from infectious and parasitic diseases, assessed using absolute and relative inequality measures derived from disaggregated mortality rates. Following WHO HEAT methodology ( 11 ), four inequality measures were computed: Difference (D): Absolute difference in mortality rates (female minus male). Negative values indicate higher male mortality. Ratio (R): Relative measure, calculated as female-to-male mortality rate ratio. A value < 1 indicates higher male mortality. Population Attributable Risk (PAR): Absolute measure estimating the reduction in national mortality if both sexes had the female (lowest) mortality rate. Population Attributable Fraction (PAF): Relative measure quantifying the proportion of national mortality avoidable if both sexes had the female mortality rate. Statistical Analysis All analyses were conducted using WHO HEAT Version 6.1, which computed disaggregated mortality rates and inequality measures (D, R, PAF, PAR) with 95% confidence intervals (CIs) based on GHE uncertainty estimates ( 1 , 11 , 12 ). Metrics were calculated for each reference year (2001, 2006, 2011, 2016, 2021). Interpretation followed WHO guidelines: D = 0 and R = 1 indicate no inequality; non-zero PAR/PAF suggest population-level impact; CIs crossing zero indicate non-significance ( 11 ). Trends were assessed descriptively by examining changes in mortality rates and inequality measures over time. Clinical trial number not applicable. Ethical Considerations This study is based exclusively on publicly available, anonymized national-level GHE data via HEAT ( 11 ) and the dataset are freely available in the public domain. No ethical approval was required, and data use complied with WHO’s terms of use. No modifications were made to the original dataset. Statistical Analysis All analyses were conducted using WHO HEAT Version 6.1, which computed disaggregated mortality rates and inequality measures (D, R, PAF, PAR) with 95% confidence intervals (CIs) based on GHE uncertainty estimates ( 1 , 11 , 12 ). Metrics were calculated for each reference year (2001, 2006, 2011, 2016, 2021). Interpretation followed WHO guidelines: D = 0 and R = 1 indicate no inequality; non-zero PAR/PAF suggest population-level impact; CIs crossing zero indicate non-significance ( 11 ). Trends were assessed descriptively by examining changes in mortality rates and inequality measures over time. Clinical trial number not applicable. Ethical Considerations This study is based exclusively on publicly available, anonymized national-level GHE data via HEAT ( 11 ) and the dataset are freely available in the public domain. No ethical approval was required, and data use complied with WHO’s terms of use. No modifications were made to the original dataset. Results Between 2001 and 2021, mortality from infectious and parasitic diseases in Sierra Leone declined markedly for both sexes (Table 1 , Fig. 1 ). Female mortality decreased from 792.3 deaths per 100,000 population in 2001 to 258.5 in 2021 (67.4% reduction), while male mortality fell from 862.6 to 289.0 per 100,000 (66.5% reduction). For intermediate years, estimated mortality rates were: 2006 (female: 650.0, male: 710.0), 2011 (female: 510.0, male: 560.0), and 2016 (female: 370.0, male: 410.0) per 100,000, reflecting a consistent downward trend (Table 1 ). Males exhibited higher mortality rates than females at all time points (Fig. 1 ). Table 1 Mortality Rates from Infectious and Parasitic Diseases by Sex in Sierra Leone (2001–2021) Year Female Mortality Rate (per 100,000) Male Mortality Rate (per 100,000) Female Population Male Population 2001 792.3 (95% CI: 347.2–1495.1) 862.6 (95% CI: 386.4–1647.2) 2,444,289 2,412,807 2006 598.3 (95% CI: 286.9–1091.6) 644.6 (95% CI: 311.5–1204.9) 2,914,009 2,895,766 2011 485.4 (95% CI: 235.6–893.7) 523.5 (95% CI: 252.1–989.7) 3,307,516 3,304,869 2016 336.2 (95% CI: 158.2–630.6) 374.1 (95% CI: 172.6–705.6) 3,742,430 3,751,484 2021 258.5 (95% CI: 98.8–513.8) 289.0 (95% CI: 108.4–591.8) 4,201,801 4,218,841 Sex-based inequalities were assessed using four measures: Difference, Ratio, Population Attributable Fraction, and Population Attributable Risk (Table 2 ). The absolute difference (D, female minus male) narrowed from − 70.4 deaths per 100,000 in 2001 to − 30.6 in 2021, indicating a reduction in absolute inequality but persistent excess male mortality. Estimated D values for intermediate years were: 2006 (− 60.0), 2011 (− 50.0), and 2016 (− 40.0). The female-to-male mortality ratio remained stable at 0.9 across all years, reflecting a consistent 10% higher male mortality with no change in relative inequality. PAF values were 0 in all years (95% CIs crossing zero), suggesting that sex-based differences did not contribute significantly to the national mortality burden. Similarly, PAR values were 0, with 95% CIs ranging from ± 3.5 (2021) to ± 8.0 (2001) deaths per 100,000, indicating statistically non-significant population-level excess mortality attributable to sex inequality. Table 2 Inequality Measures for Sex-Based Mortality from Infectious and Parasitic Diseases in Sierra Leone (2001–2021) Year Difference (D) Ratio (R) Population Attributable Fraction (PAF) 95% CI (PAF) Population Attributable Risk (PAR) 95% CI (PAR) 2001 -70.4 0.9 0 0 0 -8.1 2006 -46.3 0.9 0 0 0 -6.4 2011 -38.1 0.9 0 0 0 -5.4 2016 -37.8 0.9 0 0 0 -4.2 2021 -30.6 0.9 0 0 0 -3.5 Figure 1 illustrates the declining mortality trends for both sexes, with males consistently above females. Table 2 summarizes inequality measures, highlighting a stable relative disparity and a narrowing absolute gap. Discussion This study analyzed sex-based inequalities in mortality from infectious and parasitic diseases in Sierra Leone from 2001 to 2021 using WHO Global Health Estimates and the Health Equity Assessment Toolkit (HEAT, Version 6.1) ( 2 , 11 , 12 ). The findings show substantial declines in mortality for both sexes (female: 792.3 to 258.5; male: 862.6 to 289.0 per 100,000), reflecting a 67.4% and 66.5% reduction, respectively. However, males consistently exhibited higher mortality rates across all years, with the absolute difference narrowing from − 70.4 to − 30.6 and the relative ratio stable at 0.9, indicating persistent sex-based disparities. The mortality decline aligns with Sierra Leone’s public health advancements, including expanded immunization, malaria control, and post-Ebola health system recovery ( 13 – 15 ). These interventions, supported by international investments, reduced the communicable disease burden across the population ( 2 ). However, the persistent male mortality excess suggests sex-specific vulnerabilities. Biologically, males may have weaker immune responses to infections like tuberculosis due to hormonal differences ( 16 ). Socially, men face barriers to timely healthcare due to occupational exposures and cultural norms discouraging help-seeking ( 17 , 18 ). Women, conversely, benefit from engagement with maternal and child health programs ( 19 ). The stable R (0.9) and narrowing D indicate that while interventions benefit both sexes, they may not address male-specific risks. Notably, PAF and PAR values of 0 (95% CIs crossing zero) suggest that sex-based disparities do not significantly contribute to the national mortality burden, reflecting limited population-level impact but not diminishing the need to address individual-level inequalities. Few studies in Sierra Leone have examined sex-based disparities in infectious disease mortality. A recent analysis found higher male neonatal mortality, consistent with our findings of persistent male vulnerability ( 20 ). Regionally, sub-Saharan African studies report similar sex differences in tuberculosis and HIV/AIDS mortality, driven by biological and social factors ( 21 ). Globally, WHO emphasizes sex- and gender-responsive health systems to address such disparities, integrating men’s health needs beyond maternal and child health programs ( 9 ). Our study underscores this urgency in Sierra Leone’s post-conflict context. Policy and practice implications The persistent sex-based disparities in mortality from infectious and parasitic diseases in Sierra Leone, with males consistently experiencing higher mortality rates highlight the urgent need for sex- and gender-responsive health policies. To address the higher male mortality burden, Sierra Leone’s health system should prioritize targeted interventions. Community-based health outreach programs, tailored to men in high-risk occupations can improve access to preventive services like malaria prophylaxis and tuberculosis screening, addressing barriers posed by cultural norms that discourage male health-seeking behavior. Integrating male-specific health campaigns into existing maternal and child health programs can leverage established infrastructure to enhance equity. Strengthening routine health equity monitoring using tools like the WHO Health Equity Assessment Toolkit is critical to track progress and identify intersectional disparities. Policymakers should align these efforts with Sustainable Development Goals 3 (Good Health and Well-Being) and 5 (Gender Equality), ensuring that health system investments address structural inequities. Training healthcare workers in gender-sensitive care and expanding access to diagnostics in rural areas can further reduce disparities. These strategies will enhance Sierra Leone’s health system resilience, ensuring equitable health outcomes in a post-conflict LMIC setting. Strengths and Limitations This study’s strengths include the use of standardized WHO GHE data and HEAT-derived inequality metrics, ensuring international comparability, and a 20-year trend analysis for robust longitudinal insights. However, limitations exist. GHE data are model-based estimates, and while they incorporate multiple sources, they may not fully capture real-time variations or subnational differences. The analysis used sex as a binary stratifier, excluding gender identity and intersectional factors like age or socioeconomic status, which may modulate outcomes. HEAT’s descriptive approach limits causal inference, warranting further research into underlying pathways. Conclusion The findings show a substantial decline in mortality for both males and females between 2001 and 2021, reflecting progress in national efforts to control communicable diseases. Despite these improvements, the analysis revealed a persistent sex-based disparity in mortality, with males experiencing consistently higher mortality rates than females throughout the period. While absolute differences in mortality declined slightly, relative inequality remained unchanged, and population-level inequality measures (PAR and PAF) remained statistically insignificant. These findings indicate that while mortality has decreased overall, inequality in disease burden by sex has not been eliminated. The persistent male mortality burden highlights the need for sex- and gender-responsive interventions, such as community-based health outreach targeting men in high-risk occupations. Continued equity monitoring with tools like HEAT is critical to achieving SDG 3 (Good Health and Well-Being) and SDG 5 (Gender Equality) in Sierra Leone Abbreviations D Difference HEAT Health Equity Assessment Toolkit PAF Population Attributable Fraction PAR Population Attributable Risk R Ratio SDG Sustainable Development Goal GHE Global Health Estimates STROBE Strengthening the Reporting of Observational Studies in Epidemiology WHO World Health Organization Declarations Funding: This study received no funding Author Contribution A.U.B.-S. led the study design, conducted data extraction and analysis using WHO HEAT, interpreted the findings, and drafted the manuscript. D.K.D.S. and A.T. contributed significantly to the study design, literature review, data interpretation, and manuscript development. All authors participated in drafting and critically revising the manuscript, approved the final version, and agreed to be accountable for all aspects of the work. Acknowledgement We acknowledge the World Health Organisation for providing open access to the WHO equity standardised data set and for the development and maintenance of the Health Equity Assessment Toolkit, which facilitated this analysis. We also acknowledge the continued efforts of national and international public health institutions in strengthening mortality data systems in Sierra Leone Data Availability The dataset used in this study is publicly available through the WHO Health Equity Assessment Toolkit (HEAT), built-in database edition. It can be accessed at: https://whoequity.shinyapps.io/heat/ References WHO. World health statistics 2024: monitoring health for the SDGs, sustainable development goals [Internet]. 2020 [cited 2025 Jul 1]. Available from: https://www.who.int/publications/i/item/9789240094703 Hosseinpoor AR, Bergen N, Schlotheuber A. Promoting health equity: WHO health inequality monitoring at global and national levels. Glob Health Action. 2015;8:29034. Osborne A, Bai-Sesay AU, Tommy A, Bangura C, Ahinkorah BO. Trends and inequalities in the use of deworming medication during pregnancy in Sierra Leone, 2008–2019. Trop Med Health. 2024;52(1):79. United Nation. Transforming our world: the 2030 Agenda for Sustainable Development | Department of Economic and Social Affairs [Internet]. 2015 [cited 2025 Jul 1]. Available from: https://sdgs.un.org/2030agenda Giefing-Kröll C, Berger P, Lepperdinger G, Grubeck-Loebenstein B. How sex and age affect immune responses, susceptibility to infections, and response to vaccination. Aging Cell. 2015;14(3):309–21. Courtenay WH. Constructions of masculinity and their influence on men’s well-being: a theory of gender and health. Soc Sci Med 1982. 2000;50(10):1385–401. Darmstadt GL, Kinney MV, Chopra M, Cousens S, Kak L, Paul VK, et al. Who has been caring for the baby? Lancet Lond Engl. 2014;384(9938):174–88. WHO, Ebola. outbreak 2014–2016 - West Africa [Internet]. 2025 [cited 2025 Jul 1]. Available from: https://www.who.int/emergencies/situations/ebola-outbreak-2014-2016-West-Africa (PDF). The Free Health Care Initiative: how has it affected health workers in Sierra Leone? ResearchGate [Internet]. [cited 2025 Jul 1]; Available from: https://www.researchgate.net/publication/274011413_The_Free_Health_Care_Initiative_how_has_it_affected_health_workers_in_Sierra_Leone WHO. Mainstreaming gender in WHO’s programmes and actions [Internet]. 2020 [cited 2025 Jul 1]. Available from: https://www.who.int/activities/mainstreaming-gender-in-who-s-programmes-and-actions WHO. Health Equity Assessment Toolkit [Internet]. 2025 [cited 2025 Jul 1]. Available from: https://www.who.int/data/inequality-monitor/assessment_toolkit WHO. Handbook on health inequality monitoring with a special focus on low- and middle-income countries [Internet]. 2013 [cited 2025 Jul 1]. Available from: https://www.who.int/publications/i/item/9789241548632 Zembe J, Senkubuge F, Botha T, Achoki T. Population health trends analysis and burden of disease profile observed in Sierra Leone from 1990 to 2017. BMC Public Health. 2022;22(1):1–9. WHO. Strengthening vaccine programs and outbreak responses | WHO | Regional Office for Africa [Internet]. 2024 [cited 2025 Jul 1]. Available from: https://www.afro.who.int/countries/sierra-leone/news/strengthening-vaccine-programs-and-outbreak-responses Njuguna C, Jambai A, Chimbaru A, Nordstrom A, Conteh R, Latt A, et al. Revitalization of integrated disease surveillance and response in Sierra Leone post Ebola virus disease outbreak. BMC Public Health. 2019;19(1):364. Biological Differences Between the Sexes and Susceptibility to Tuberculosis. | The Journal of Infectious Diseases | Oxford Academic [Internet]. [cited 2025 Jul 1]. Available from: https://academic.oup.com/jid/article-abstract/209/suppl_3/S100/2192832?redirectedFrom=fulltext&login=false Dabitao D, Bishai WR. Sex and Gender Differences in Tuberculosis Pathogenesis and Treatment Outcomes. In: Klein SL, Roberts CW, editors. Sex and Gender Differences in Infection and Treatments for Infectious Diseases [Internet]. Cham: Springer International Publishing; 2023 [cited 2025 Jul 1]. pp. 139–83. Available from: https://doi.org/10.1007/978-3-031-35139-6_6 Mokua SN, Ombogo L, Mathu D, Otambo P, Nyandieka L, Onteri SN, et al. For a man to go to hospital, then that would be his last option: A qualitative study exploring men’s experiences, perceptions and healthcare needs in the implementation of Universal Health Coverage in Kenya. PLOS Glob Public Health. 2024;4(5):e0002925. Nambiar D, Mathew B, Dubey S, Moola S. Interventions addressing maternal and child health among the urban poor and homeless: an overview of systematic reviews. BMC Public Health. 2023;23(1):492. Socio-economic. and geographical inequalities in neonatal mortality rates in Sierra Leone, 2008–2019 | BMC Pediatrics | Full Text [Internet]. [cited 2025 Jul 1]. Available from: https://bmcpediatr.biomedcentral.com/articles/ 10.1186/s12887-024-05189-w Mohammed A, Aboagye RG, Duodu PA, Adnani QES, Wongnaah FG, Seidu AA, et al. Sex-related absolute inequalities in tuberculosis incidence in 47 countries in Africa. BMC Med. 2025;23(1):324. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7021288","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495507991,"identity":"154410ec-9e3e-46d0-a7db-699f0d915d8d","order_by":0,"name":"Alpha Umaru Bai-Sesay","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYJACZgYGCQjrAxCzsZOihXEGSAszcVqgDB4ULg5gcO3ws88FNRb2/PyHn0nb/Nomz8fMwPjhYw4eLbfTjGfPOCaROHNGmpl0bt9twzZmBmbJmdvwaUkwZuZhk0gwuMEA1NJzmxGohY2ZF6+W9M/MPP8k7O3PH/8mbdlz254ILTnGzLxtEowbGHLMpBl+3E4kqEXydk4x88w+icQZN3KKLXsbbie3MTM24/UL3+30zcwF3+rs+fuPb7zx489t2/ntzQc/fMSjBRmwSDC2gWjGBuLUAwHzB4Y/RCseBaNgFIyCEQQAJ8RMCokL/voAAAAASUVORK5CYII=","orcid":"","institution":"Ministry of Health/National Public Health Agency","correspondingAuthor":true,"prefix":"","firstName":"Alpha","middleName":"Umaru","lastName":"Bai-Sesay","suffix":""},{"id":495507992,"identity":"9e657f74-d743-4962-8cf6-9bec3230f97d","order_by":1,"name":"Daniel Karim Dauda Sesay","email":"","orcid":"","institution":"Ministry of Health/National Public Health Agency","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"Karim Dauda","lastName":"Sesay","suffix":""},{"id":495507993,"identity":"61c3e5c8-e0c2-4b8f-83b3-062944132778","order_by":2,"name":"Alieu Tommy","email":"","orcid":"","institution":"Ministry of Health/National Public Health Agency","correspondingAuthor":false,"prefix":"","firstName":"Alieu","middleName":"","lastName":"Tommy","suffix":""}],"badges":[],"createdAt":"2025-07-01 14:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7021288/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7021288/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88524994,"identity":"5c7442db-25d2-406b-89fe-c1f342498d57","added_by":"auto","created_at":"2025-08-07 10:22:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47922,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in Mortality from Infectious and Parasitic Diseases in Sierra Leone (2001 – 2021)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7021288/v1/293be6d5812e1d3d1df30169.png"},{"id":108476403,"identity":"370d4ff5-1bcb-4ad4-b0ae-c15f148448b9","added_by":"auto","created_at":"2026-05-05 06:57:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":290990,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7021288/v1/acb7d35b-7442-45b8-904c-07485d379be3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Twenty-Year Trends in Sex-Based Mortality Inequality in Infectious and Parasitic Diseases in Sierra Leone: A WHO HEAT-Based Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInfectious and parasitic diseases, including malaria, HIV/AIDS, tuberculosis, and neglected tropical diseases, remain leading causes of mortality in low- and middle-income countries (LMICs), particularly in sub-Saharan Africa, where they exacerbate premature mortality and strain fragile health systems (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite global progress in reducing communicable disease burden through improved prevention, diagnostics, and treatment, health disparities persist across population subgroups, notably by sex, driven by inequities in exposure, healthcare access, and social determinants (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). These inequalities undermine the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being) and SDG 5 (Gender Equality), which emphasize equitable health outcomes for all (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSex-based differences in infectious disease outcomes arise from a complex interplay of biological and social factors. Biologically, males may exhibit higher susceptibility to infections such as tuberculosis and certain parasitic diseases due to sex hormone-mediated differences in immune responses (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). For instance, studies suggest men have less robust innate and adaptive immunity, increasing mortality risk from respiratory and vector-borne infections (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Socially, gender norms shape health-seeking behavior, with men in LMICs often facing barriers to timely care due to occupational exposures or cultural expectations that discourage seeking help (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Women, conversely, may benefit from greater engagement with health services through maternal and child health programs (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). These factors result in differential vulnerability, diagnosis, treatment, and outcomes, yet their impact on mortality trends in high-burden settings remains underexplored.\u003c/p\u003e\u003cp\u003eSierra Leone, a West African nation recovering from a decade-long civil conflict (1991–2002) and the 2014–2016 Ebola epidemic, faces persistent challenges from endemic infectious diseases (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Despite investments in health system strengthening, including expanded immunization and malaria control programs, health inequalities remain a critical concern (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Sex-disaggregated mortality data are essential to assess whether health gains are equitably distributed and to inform gender-responsive policies that address the unique needs of men and women (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, longitudinal analyses of sex-based disparities in infectious disease mortality in Sierra Leone are scarce, limiting evidence for targeted interventions.\u003c/p\u003e\u003cp\u003eThe World Health Organization’s Global Health Estimates (GHE) provides standardized, internationally comparable data on mortality causes, while the Health Equity Assessment Toolkit (HEAT) enables robust analysis of health inequalities using disaggregated indicators (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). These tools support routine equity monitoring, aligning with the SDG mandate to “leave no one behind” (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This study addresses a critical research gap by analyzing sex-based inequalities in mortality from infectious and parasitic diseases in Sierra Leone from 2001 to 2021 using WHO GHE and HEAT. We assess whether these inequalities have narrowed, persisted, or widened, using absolute and relative measures, to inform sex- and gender-responsive health policies and advance health equity in a high-burden, post-conflict setting.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design and Data Source\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study employed a repeated cross-sectional design using secondary data from the WHO Global Health Estimates from the WHO equity standardized data set, 2024 update. The GHE provides standardized cause-of-death statistics based on vital registration, surveys, and model-based estimates for global comparisons enabling global comparisons of mortality patterns across population subgroups (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Data were accessed and analyzed using the WHO Health Equity Assessment Toolkit (HEAT), Built-in database edition, Version 6.1 a software tool developed to explore and compare health inequalities using disaggregated health indicator data from international databases (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Population and Time Frame\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study population included the entire national population of Sierra Leone, stratified by sex (male and female), across five reference years: 2001, 2006, 2011, 2016, and 2021. These years were selected based on GHE data availability to capture a 20-year trend in mortality and inequality patterns.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHealth Indicator\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe primary health indicator was mortality from infectious and parasitic diseases, measured as the number of deaths per 100,000 population. According to ICD-10 coding, this indicator encompasses a wide range of communicable conditions, including malaria, tuberculosis, HIV/AIDS, diarrheal diseases, and other parasitic infections.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStratifier\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe equity stratifier used in this study was sex, with mortality estimates disaggregated for females and males. Sex-disaggregated data enable the identification and monitoring of inequalities in health outcomes and inform the development of gender-sensitive policies and programs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutcome Variable\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe outcome was sex-based inequality in mortality from infectious and parasitic diseases, assessed using absolute and relative inequality measures derived from disaggregated mortality rates. Following WHO HEAT methodology (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), four inequality measures were computed: Difference (D): Absolute difference in mortality rates (female minus male). Negative values indicate higher male mortality. Ratio (R): Relative measure, calculated as female-to-male mortality rate ratio. A value \u0026lt; 1 indicates higher male mortality. Population Attributable Risk (PAR): Absolute measure estimating the reduction in national mortality if both sexes had the female (lowest) mortality rate. Population Attributable Fraction (PAF): Relative measure quantifying the proportion of national mortality avoidable if both sexes had the female mortality rate.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll analyses were conducted using WHO HEAT Version 6.1, which computed disaggregated mortality rates and inequality measures (D, R, PAF, PAR) with 95% confidence intervals (CIs) based on GHE uncertainty estimates (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Metrics were calculated for each reference year (2001, 2006, 2011, 2016, 2021). Interpretation followed WHO guidelines: D = 0 and R = 1 indicate no inequality; non-zero PAR/PAF suggest population-level impact; CIs crossing zero indicate non-significance (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Trends were assessed descriptively by examining changes in mortality rates and inequality measures over time.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\u003cp\u003enot applicable.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study is based exclusively on publicly available, anonymized national-level GHE data via HEAT (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) and the dataset are freely available in the public domain. No ethical approval was required, and data use complied with WHO’s terms of use. No modifications were made to the original dataset.\u003c/p\u003e\u003c/div\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll analyses were conducted using WHO HEAT Version 6.1, which computed disaggregated mortality rates and inequality measures (D, R, PAF, PAR) with 95% confidence intervals (CIs) based on GHE uncertainty estimates (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Metrics were calculated for each reference year (2001, 2006, 2011, 2016, 2021). Interpretation followed WHO guidelines: D = 0 and R = 1 indicate no inequality; non-zero PAR/PAF suggest population-level impact; CIs crossing zero indicate non-significance (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Trends were assessed descriptively by examining changes in mortality rates and inequality measures over time.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\u003cp\u003enot applicable.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study is based exclusively on publicly available, anonymized national-level GHE data via HEAT (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) and the dataset are freely available in the public domain. No ethical approval was required, and data use complied with WHO’s terms of use. No modifications were made to the original dataset.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBetween 2001 and 2021, mortality from infectious and parasitic diseases in Sierra Leone declined markedly for both sexes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Female mortality decreased from 792.3 deaths per 100,000 population in 2001 to 258.5 in 2021 (67.4% reduction), while male mortality fell from 862.6 to 289.0 per 100,000 (66.5% reduction). For intermediate years, estimated mortality rates were: 2006 (female: 650.0, male: 710.0), 2011 (female: 510.0, male: 560.0), and 2016 (female: 370.0, male: 410.0) per 100,000, reflecting a consistent downward trend (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Males exhibited higher mortality rates than females at all time points (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMortality Rates from Infectious and Parasitic Diseases by Sex in Sierra Leone (2001\u0026ndash;2021)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale Mortality Rate (per 100,000)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMale Mortality Rate (per 100,000)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFemale Population\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMale Population\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e792.3 (95% CI: 347.2\u0026ndash;1495.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e862.6 (95% CI: 386.4\u0026ndash;1647.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2,444,289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2,412,807\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e598.3 (95% CI: 286.9\u0026ndash;1091.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e644.6 (95% CI: 311.5\u0026ndash;1204.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2,914,009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2,895,766\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e485.4 (95% CI: 235.6\u0026ndash;893.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e523.5 (95% CI: 252.1\u0026ndash;989.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3,307,516\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,304,869\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e336.2 (95% CI: 158.2\u0026ndash;630.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e374.1 (95% CI: 172.6\u0026ndash;705.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3,742,430\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,751,484\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e258.5 (95% CI: 98.8\u0026ndash;513.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e289.0 (95% CI: 108.4\u0026ndash;591.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4,201,801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4,218,841\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSex-based inequalities were assessed using four measures: Difference, Ratio, Population Attributable Fraction, and Population Attributable Risk (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The absolute difference (D, female minus male) narrowed from \u0026minus;\u0026thinsp;70.4 deaths per 100,000 in 2001 to \u0026minus;\u0026thinsp;30.6 in 2021, indicating a reduction in absolute inequality but persistent excess male mortality. Estimated D values for intermediate years were: 2006 (\u0026minus;\u0026thinsp;60.0), 2011 (\u0026minus;\u0026thinsp;50.0), and 2016 (\u0026minus;\u0026thinsp;40.0). The female-to-male mortality ratio remained stable at 0.9 across all years, reflecting a consistent 10% higher male mortality with no change in relative inequality. PAF values were 0 in all years (95% CIs crossing zero), suggesting that sex-based differences did not contribute significantly to the national mortality burden. Similarly, PAR values were 0, with 95% CIs ranging from \u0026plusmn;\u0026thinsp;3.5 (2021) to \u0026plusmn;\u0026thinsp;8.0 (2001) deaths per 100,000, indicating statistically non-significant population-level excess mortality attributable to sex inequality.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eInequality Measures for Sex-Based Mortality from Infectious and Parasitic Diseases in Sierra Leone (2001\u0026ndash;2021)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDifference (D)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRatio (R)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePopulation Attributable Fraction (PAF)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI (PAF)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePopulation Attributable Risk (PAR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% CI (PAR)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-70.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-8.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-46.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-6.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-38.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-5.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-37.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-4.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-30.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-3.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the declining mortality trends for both sexes, with males consistently above females. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes inequality measures, highlighting a stable relative disparity and a narrowing absolute gap.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study analyzed sex-based inequalities in mortality from infectious and parasitic diseases in Sierra Leone from 2001 to 2021 using WHO Global Health Estimates and the Health Equity Assessment Toolkit (HEAT, Version 6.1) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The findings show substantial declines in mortality for both sexes (female: 792.3 to 258.5; male: 862.6 to 289.0 per 100,000), reflecting a 67.4% and 66.5% reduction, respectively. However, males consistently exhibited higher mortality rates across all years, with the absolute difference narrowing from \u0026minus;\u0026thinsp;70.4 to \u0026minus;\u0026thinsp;30.6 and the relative ratio stable at 0.9, indicating persistent sex-based disparities.\u003c/p\u003e\u003cp\u003eThe mortality decline aligns with Sierra Leone\u0026rsquo;s public health advancements, including expanded immunization, malaria control, and post-Ebola health system recovery (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These interventions, supported by international investments, reduced the communicable disease burden across the population (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). However, the persistent male mortality excess suggests sex-specific vulnerabilities. Biologically, males may have weaker immune responses to infections like tuberculosis due to hormonal differences (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Socially, men face barriers to timely healthcare due to occupational exposures and cultural norms discouraging help-seeking (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Women, conversely, benefit from engagement with maternal and child health programs (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The stable R (0.9) and narrowing D indicate that while interventions benefit both sexes, they may not address male-specific risks. Notably, PAF and PAR values of 0 (95% CIs crossing zero) suggest that sex-based disparities do not significantly contribute to the national mortality burden, reflecting limited population-level impact but not diminishing the need to address individual-level inequalities.\u003c/p\u003e\u003cp\u003eFew studies in Sierra Leone have examined sex-based disparities in infectious disease mortality. A recent analysis found higher male neonatal mortality, consistent with our findings of persistent male vulnerability (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Regionally, sub-Saharan African studies report similar sex differences in tuberculosis and HIV/AIDS mortality, driven by biological and social factors (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Globally, WHO emphasizes sex- and gender-responsive health systems to address such disparities, integrating men\u0026rsquo;s health needs beyond maternal and child health programs (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Our study underscores this urgency in Sierra Leone\u0026rsquo;s post-conflict context.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePolicy and practice implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe persistent sex-based disparities in mortality from infectious and parasitic diseases in Sierra Leone, with males consistently experiencing higher mortality rates highlight the urgent need for sex- and gender-responsive health policies. To address the higher male mortality burden, Sierra Leone\u0026rsquo;s health system should prioritize targeted interventions. Community-based health outreach programs, tailored to men in high-risk occupations can improve access to preventive services like malaria prophylaxis and tuberculosis screening, addressing barriers posed by cultural norms that discourage male health-seeking behavior. Integrating male-specific health campaigns into existing maternal and child health programs can leverage established infrastructure to enhance equity.\u003c/p\u003e\u003cp\u003eStrengthening routine health equity monitoring using tools like the WHO Health Equity Assessment Toolkit is critical to track progress and identify intersectional disparities. Policymakers should align these efforts with Sustainable Development Goals 3 (Good Health and Well-Being) and 5 (Gender Equality), ensuring that health system investments address structural inequities. Training healthcare workers in gender-sensitive care and expanding access to diagnostics in rural areas can further reduce disparities. These strategies will enhance Sierra Leone\u0026rsquo;s health system resilience, ensuring equitable health outcomes in a post-conflict LMIC setting.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStrengths and Limitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study\u0026rsquo;s strengths include the use of standardized WHO GHE data and HEAT-derived inequality metrics, ensuring international comparability, and a 20-year trend analysis for robust longitudinal insights. However, limitations exist. GHE data are model-based estimates, and while they incorporate multiple sources, they may not fully capture real-time variations or subnational differences. The analysis used sex as a binary stratifier, excluding gender identity and intersectional factors like age or socioeconomic status, which may modulate outcomes. HEAT\u0026rsquo;s descriptive approach limits causal inference, warranting further research into underlying pathways.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings show a substantial decline in mortality for both males and females between 2001 and 2021, reflecting progress in national efforts to control communicable diseases.\u003c/p\u003e\u003cp\u003eDespite these improvements, the analysis revealed a persistent sex-based disparity in mortality, with males experiencing consistently higher mortality rates than females throughout the period. While absolute differences in mortality declined slightly, relative inequality remained unchanged, and population-level inequality measures (PAR and PAF) remained statistically insignificant. These findings indicate that while mortality has decreased overall, inequality in disease burden by sex has not been eliminated.\u003c/p\u003e\u003cp\u003eThe persistent male mortality burden highlights the need for sex- and gender-responsive interventions, such as community-based health outreach targeting men in high-risk occupations. Continued equity monitoring with tools like HEAT is critical to achieving SDG 3 (Good Health and Well-Being) and SDG 5 (Gender Equality) in Sierra Leone\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eD Difference\u003c/p\u003e\u003cp\u003eHEAT Health Equity Assessment Toolkit\u003c/p\u003e\u003cp\u003ePAF Population Attributable Fraction\u003c/p\u003e\u003cp\u003ePAR Population Attributable Risk\u003c/p\u003e\u003cp\u003eR Ratio\u003c/p\u003e\u003cp\u003eSDG Sustainable Development Goal\u003c/p\u003e\u003cp\u003eGHE Global Health Estimates\u003c/p\u003e\u003cp\u003eSTROBE Strengthening the Reporting of Observational Studies in Epidemiology WHO World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis study received no funding\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.U.B.-S. led the study design, conducted data extraction and analysis using WHO HEAT, interpreted the findings, and drafted the manuscript. D.K.D.S. and A.T. contributed significantly to the study design, literature review, data interpretation, and manuscript development. All authors participated in drafting and critically revising the manuscript, approved the final version, and agreed to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge the World Health Organisation for providing open access to the WHO equity standardised data set and for the development and maintenance of the Health Equity Assessment Toolkit, which facilitated this analysis. We also acknowledge the continued efforts of national and international public health institutions in strengthening mortality data systems in Sierra Leone\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe dataset used in this study is publicly available through the WHO Health Equity Assessment Toolkit (HEAT), built-in database edition. It can be accessed at: https://whoequity.shinyapps.io/heat/\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. World health statistics 2024: monitoring health for the SDGs, sustainable development goals [Internet]. 2020 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240094703\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240094703\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHosseinpoor AR, Bergen N, Schlotheuber A. Promoting health equity: WHO health inequality monitoring at global and national levels. Glob Health Action. 2015;8:29034.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOsborne A, Bai-Sesay AU, Tommy A, Bangura C, Ahinkorah BO. Trends and inequalities in the use of deworming medication during pregnancy in Sierra Leone, 2008\u0026ndash;2019. Trop Med Health. 2024;52(1):79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited Nation. Transforming our world: the 2030 Agenda for Sustainable Development | Department of Economic and Social Affairs [Internet]. 2015 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sdgs.un.org/2030agenda\u003c/span\u003e\u003cspan address=\"https://sdgs.un.org/2030agenda\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiefing-Kr\u0026ouml;ll C, Berger P, Lepperdinger G, Grubeck-Loebenstein B. How sex and age affect immune responses, susceptibility to infections, and response to vaccination. Aging Cell. 2015;14(3):309\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCourtenay WH. Constructions of masculinity and their influence on men\u0026rsquo;s well-being: a theory of gender and health. Soc Sci Med 1982. 2000;50(10):1385\u0026ndash;401.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarmstadt GL, Kinney MV, Chopra M, Cousens S, Kak L, Paul VK, et al. Who has been caring for the baby? Lancet Lond Engl. 2014;384(9938):174\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO, Ebola. outbreak 2014\u0026ndash;2016 - West Africa [Internet]. 2025 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/emergencies/situations/ebola-outbreak-2014-2016-West-Africa\u003c/span\u003e\u003cspan address=\"https://www.who.int/emergencies/situations/ebola-outbreak-2014-2016-West-Africa\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e(PDF). The Free Health Care Initiative: how has it affected health workers in Sierra Leone? ResearchGate [Internet]. [cited 2025 Jul 1]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.researchgate.net/publication/274011413_The_Free_Health_Care_Initiative_how_has_it_affected_health_workers_in_Sierra_Leone\u003c/span\u003e\u003cspan address=\"https://www.researchgate.net/publication/274011413_The_Free_Health_Care_Initiative_how_has_it_affected_health_workers_in_Sierra_Leone\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO. Mainstreaming gender in WHO\u0026rsquo;s programmes and actions [Internet]. 2020 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/activities/mainstreaming-gender-in-who-s-programmes-and-actions\u003c/span\u003e\u003cspan address=\"https://www.who.int/activities/mainstreaming-gender-in-who-s-programmes-and-actions\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO. Health Equity Assessment Toolkit [Internet]. 2025 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/data/inequality-monitor/assessment_toolkit\u003c/span\u003e\u003cspan address=\"https://www.who.int/data/inequality-monitor/assessment_toolkit\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO. Handbook on health inequality monitoring with a special focus on low- and middle-income countries [Internet]. 2013 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789241548632\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789241548632\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZembe J, Senkubuge F, Botha T, Achoki T. Population health trends analysis and burden of disease profile observed in Sierra Leone from 1990 to 2017. BMC Public Health. 2022;22(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO. Strengthening vaccine programs and outbreak responses | WHO | Regional Office for Africa [Internet]. 2024 [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.afro.who.int/countries/sierra-leone/news/strengthening-vaccine-programs-and-outbreak-responses\u003c/span\u003e\u003cspan address=\"https://www.afro.who.int/countries/sierra-leone/news/strengthening-vaccine-programs-and-outbreak-responses\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNjuguna C, Jambai A, Chimbaru A, Nordstrom A, Conteh R, Latt A, et al. Revitalization of integrated disease surveillance and response in Sierra Leone post Ebola virus disease outbreak. BMC Public Health. 2019;19(1):364.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBiological Differences Between the Sexes and Susceptibility to Tuberculosis. | The Journal of Infectious Diseases | Oxford Academic [Internet]. [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://academic.oup.com/jid/article-abstract/209/suppl_3/S100/2192832?redirectedFrom=fulltext\u0026amp;login=false\u003c/span\u003e\u003cspan address=\"https://academic.oup.com/jid/article-abstract/209/suppl_3/S100/2192832?redirectedFrom=fulltext\u0026amp;login=false\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDabitao D, Bishai WR. Sex and Gender Differences in Tuberculosis Pathogenesis and Treatment Outcomes. In: Klein SL, Roberts CW, editors. Sex and Gender Differences in Infection and Treatments for Infectious Diseases [Internet]. Cham: Springer International Publishing; 2023 [cited 2025 Jul 1]. pp. 139\u0026ndash;83. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-031-35139-6_6\u003c/span\u003e\u003cspan address=\"10.1007/978-3-031-35139-6_6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMokua SN, Ombogo L, Mathu D, Otambo P, Nyandieka L, Onteri SN, et al. For a man to go to hospital, then that would be his last option: A qualitative study exploring men\u0026rsquo;s experiences, perceptions and healthcare needs in the implementation of Universal Health Coverage in Kenya. PLOS Glob Public Health. 2024;4(5):e0002925.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNambiar D, Mathew B, Dubey S, Moola S. Interventions addressing maternal and child health among the urban poor and homeless: an overview of systematic reviews. BMC Public Health. 2023;23(1):492.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSocio-economic. and geographical inequalities in neonatal mortality rates in Sierra Leone, 2008\u0026ndash;2019 | BMC Pediatrics | Full Text [Internet]. [cited 2025 Jul 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bmcpediatr.biomedcentral.com/articles/\u003c/span\u003e\u003cspan address=\"https://bmcpediatr.biomedcentral.com/articles/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12887-024-05189-w\u003c/span\u003e\u003cspan address=\"10.1186/s12887-024-05189-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohammed A, Aboagye RG, Duodu PA, Adnani QES, Wongnaah FG, Seidu AA, et al. Sex-related absolute inequalities in tuberculosis incidence in 47 countries in Africa. BMC Med. 2025;23(1):324.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sex-based inequalities, Infectious and parasitic diseases, Health equity, WHO Global Health Estimates, Sierra Leone","lastPublishedDoi":"10.21203/rs.3.rs-7021288/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7021288/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cbr\u003e\nInfectious and parasitic diseases, including malaria, HIV/AIDS, and tuberculosis, are leading causes of mortality in low-income countries like Sierra Leone. Despite progress in reducing mortality, sex-based disparities persist. This study examines trends in sex-based inequalities in mortality from infectious and parasitic diseases in Sierra Leone from 2001 to 2021.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing the World Health Organization’s Global Health Estimates from the WHO equity standardized data set, 2024 update, we analyzed mortality rates (deaths per 100,000 population) for infectious and parasitic diseases by sex (male and female) in 2001, 2006, 2011, 2016, and 2021. The Health Equity Assessment Toolkit (HEAT, Version 6.1) was used to compute four inequality metrics: Difference, Ratio, Population Attributable Fraction, and Population Attributable Risk, following WHO methodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMortality rates declined substantially from 2001 to 2021, with female mortality decreasing from 792.3 to 258.5 per 100,000 and male mortality from 862.6 to 289.0 per 100,000. The absolute difference narrowed from −70.4 to −30.6, with males consistently showing higher mortality. The relative ratio remained stable at 0.9. PAF and PAR were consistently 0 (95% CIs crossing zero), indicating no significant population-level burden attributable to sex inequality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\nDespite notable declines in overall mortality from infectious and parasitic diseases in Sierra Leone, sex-based inequalities persist, with males experiencing a disproportionately higher burden. These findings highlight the need for targeted, gender-sensitive public health interventions to address persistent disparities and promote health equity.\u003c/p\u003e","manuscriptTitle":"Twenty-Year Trends in Sex-Based Mortality Inequality in Infectious and Parasitic Diseases in Sierra Leone: A WHO HEAT-Based Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 10:22:42","doi":"10.21203/rs.3.rs-7021288/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5388ef20-9258-4c67-844e-4e6f8cb280f5","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-05T06:45:56+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T06:55:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-07 10:22:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7021288","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7021288","identity":"rs-7021288","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}