Age-standardised trends in Incidence Rates of Noncommunicable diseases among Adults Aged 30 to 79 in Senegal from 2000 to 2019

Age-standardised trends in Incidence Rates of Noncommunicable diseases among Adults Aged 30 to 79 in Senegal from 2000 to 2019 | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Age-standardised trends in Incidence Rates of Noncommunicable diseases among Adults Aged 30 to 79 in Senegal from 2000 to 2019 Ngone Diaba Gaye , View ORCID Profile Mohamed B. Jalloh , Tiffany L. Gary-Webb , Mame Madjiguene Ka , Malick Anne , Ishta Madan , Ahmed Tamer Abdelnoor , John Tukakira , Damaris Kyem , Gurbinder Singh , Jennifer L. Carter , Elisabeth L.P. Sattler , Modou Jobe , View ORCID Profile Bamba Gaye doi: https://doi.org/10.1101/2025.09.26.25336768 Ngone Diaba Gaye 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 2 Ibra Mamadou Wane Medical Center, Department of Cardiac Rehabilitation , Dakar, Senegal Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mohamed B. Jalloh 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mohamed B. Jalloh Tiffany L. Gary-Webb 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 3 University of Pittsburgh , Pittsburgh, Pennsylvania, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mame Madjiguene Ka 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 4 Department of Cardiology, Principal Hospital of Dakar , Dakar, Senegal Find this author on Google Scholar Find this author on PubMed Search for this author on this site Malick Anne 5 Ministry of Health and Social Action , Dakar, Senegal Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ishta Madan 3 University of Pittsburgh , Pittsburgh, Pennsylvania, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ahmed Tamer Abdelnoor 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 6 Faculty of Medicine, Zagazig University , Zagazig, Egypt Find this author on Google Scholar Find this author on PubMed Search for this author on this site John Tukakira 3 University of Pittsburgh , Pittsburgh, Pennsylvania, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Damaris Kyem 3 University of Pittsburgh , Pittsburgh, Pennsylvania, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gurbinder Singh 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jennifer L. Carter 7 Nuffield Department of Population Health, University of Oxford , Oxford, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elisabeth L.P. Sattler 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 8 Department of Clinical and Administrative Pharmacy, Department of Nutritional Sciences, University of Georgia , Athens, Georgia , USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Modou Jobe 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 9 Medical Research Council Unit The Gambia at London School of Hygiene & Tropical Medicine , Atlantic Boulevard, Fajara, The Gambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bamba Gaye 1 Alliance for Medical Research in Africa (AMedRA) , Dakar, Senegal 10 Institute of Health and Development (ISED), Cheikh Anta Diop University , Dakar, Senegal 11 Department of Biomedical Informatics, Emory University School of Medicine , Atlanta, Georgia , USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Bamba Gaye For correspondence: m.bamba.gaye{at}gmail.com Abstract Full Text Info/History Metrics Data/Code Preview PDF ABSTRACT Introduction Non-communicable diseases (NCDs) represent a significant global health burden in sub-Saharan Africa (SSA). However, most SSA countries such as Senegal lack reliable data despite the need for surveillance of NCD trends to inform targeted preventive strategies. Methods We used publicly available data from the Global Burden of Disease Study (World Health Organization’s Health Inequality Data Repository). We used age-standardised regression to analyze the trends of NCDs (cancers, cardiovascular diseases, chronic respiratory diseases, diabetes, and chronic kidney diseases) incidence among adults in Senegal. Statistical analysis was performed using the Joinpoint Regression Program, Version 5.3.0.0 and data visualization was performed using R, version 4.4.0 Results NCD incidence rates in females were consistently higher than in males. Rates in females increased from 190,857 to 194,620 cases per 100,000 population between 2000 and 2019 (p-value 0.007) as compared to 160,623 to 163,800 cases per 100,000 population in males (p-value 0.002). Incidence rates were higher in females for neoplasm (p-value 0.03), chronic respiratory diseases (p-value 0.07), and diabetes and chronic kidney diseases (p-value 0.04), while cardiovascular disease incidence was higher in males (p-value 0.02). Conclusion There was a significant increase in age-standardized NCD incidence among adults in Senegal. When considering subtypes, all had increased incidence rates, except cardiovascular diseases which showed a significant decrease over time. A national NCD registry and targeted risk factor prevention programs are crucial to help tackle the NCD burden in Senegal. What is already known? Senegal is experiencing a shift towards a higher burden of NCD, with a probability of dying from NCD as high as 20% [95% CI: 11.9-28.8%] in 2019 according to WHO. Unfortunately, reliable epidemiological data and surveillance systems are lacking to inform appropriate prevention and resource allocation strategies. What does this study add? Overall, we observed a significant increasing trend in the age-standardized incidence of NCD during the study period, 2000-2019. There were differences between NCD subtypes, with neoplasm rates remaining constant throughout the study period while diabetes, chronic kidney disease and chronic respiratory disease were increasing. Incidence rates were consistently higher in females compared to males, especially for chronic respiratory disease, diabetes, and chronic kidney disease. What do the new findings imply? The overall non-significant increasing trend of NCD incidence rates in Senegal calls for the critical need to invest in robust surveillance systems such as NCD national registry and targeted risk factors prevention programs to tackle this growing burden. Discrepancies in the trends of some NCD subtypes may reflect reporting bias, which needs to be addressed by well-designed longitudinal cohort studies. INTRODUCTION Non-communicable diseases (NCDs), including cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes, account for most deaths worldwide, and their burden is rising fastest in low- and middle-income countries (LMICs). 1 Reliable data from LMICs are essential for prevention, service planning, and policy, yet many countries in sub-Saharan Africa (SSA) have limited vital registration, weak routine surveillance, and NCD indicators that are poorly integrated into national health information systems. 1 Senegal illustrates these challenges. Limited evidence from national risk factor surveys and facility-based series suggests increasing prevalence hypertension, diabetes, and selected cancers, 2 – 8 alongside exposure to tobacco use, physical inactivity 9 and diets high in sugars, salt, and saturated fats. 10 These changes plausibly reflect population growth and rapid urbanization. 6 According to the World Health Organization (WHO), NCDs were estimated to be the leading broad cause of death in Senegal in 2019 and the probability of dying from NCD was as high as 20% [95% CI: 11.9-28.8%]. 11 Structural barriers compound this mortality context, including late presentation, 7 , 12 rural–urban disparities in access, limited financial protection, constrained medicine availability, and suboptimal adherence. 7 , 13 , 14 Weak integration of NCD data into the national health information system remains a critical challenge, leading to fragmented and incomplete surveillance. Weak mortality and morbidity reporting, limited use of electronic health records, and inadequate funding for data infrastructure hinder effective disease monitoring and policy development. To tackle the burden of NCD, governments need surveillance systems and infrastructure to produce reliable data that can direct policies and legislations that will ultimately prevent the burden of NCD. 1 , 15 Timely, population-based estimates of incidence are needed to guide prevention and service delivery. We therefore examined age-standardised incidence rates (ASIR) among adults in Senegal from 2000 to 2019. We hypothesized that ASIR increased over time, reflecting demographic change, urbanization, and rising exposure to modifiable risk factors, with the aim of informing national strategies for NCD prevention, early detection, and treatment. MATERIALS AND METHODS Study design and data sources We conducted a secondary analysis of ASIR for Senegal using estimates from the Global Burden of Disease (GBD) 2019 study that we accessed via the WHO Health Inequality Data Repository (HIDR). 16 HIDR is a public catalogue of disaggregated health datasets (launched April 2023); some series originate from external sources and are not “WHO official estimates.” In our case, all ASIRs were Institute for Health Metrics and Evaluation (IHME)/GBD-2019 outputs retrieved through HIDR. Case definitions and cause hierarchy Outcomes followed the GBD cause hierarchy: Level-1 NCDs and Level-2 categories neoplasms, cardiovascular diseases, chronic respiratory diseases, and diabetes and kidney disease. GBD obtained incidence estimates by using a Bayesian meta-regression to synthesise several input sources, including surveys, censuses, vital statistics, and other health-related data sources. 17 For non-fatal outcomes, DisMod-MR 2.1 (GBD Bayesian disease model meta-regression platform) produces internally consistent incidence, prevalence, remission, and excess mortality estimates; cause-specific deaths are estimated with CODEm (Cause of Death Ensemble model). NCDs refer to noninfectious diseases 17 . Neoplasms refer to abnormal tissue growths, both benign and malignant. 17 Cardiovascular diseases are a group of disorders of the heart and blood vessels and include coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other conditions 17 . Chronic respiratory diseases affect the airways and other structures of the lungs and include chronic obstructive pulmonary disease, asthma, occupational lung diseases and pulmonary hypertension. 17 Senegal input data and provenance To enhance transparency, we enumerated all Senegal-specific input series contributing to these estimates (e.g., population-based surveys, registries, health-service data) using the GBD 2019 Data Input Sources tool. Where local data are sparse, GBD models borrow strength across space and time via a hierarchical “geographical cascade” and spatiotemporal Gaussian process regression, which we note as a limitation for country-level precision. ASIR were directly standardised to the GBD world standard population using 5-year age groups (both sexes, all ages) and reported per 100,000 population with 95% confidence intervals (CIs). This differs from WHO 2000–2025 weights; readers should interpret cross-study comparisons accordingly. We analysed the four quinquennial time points available in HIDR for Senegal (2005, 2010, 2015, 2019). Statistical analysis We used the Joinpoint Regression Program, Version 5.3.0.0 to analyze data and R, version 4.4.0 (R Foundation for Statistical Computing) for data visualization. We analyzed statistical significance of trends using an annual percent change (APC) and report the results. 18 Joinpoint regression uses the grid search method and segmented regression to model data. 19 It is able to handle correlated data by allowing specification of variance-covariance matrices to specify correlated data. Standard errors used in the analysis were back calculated from confidence intervals in the datasets using the method described by Julian PT Higgins and others. 20 Ethics, data, and code availability All data are publicly available (HIDR and IHME/ Global Health Data Exchange [GHDx]). No individual-level identifiers are present; institutional ethics review was not required. Analysis code and tidy datasets will be deposited in an open repository upon acceptance, and URLs to the HIDR dataset(s) and GBD query will be provided. RESULTS Overall, we found an increasing trend in NCD ASIR. Subgroup analysis revealed variations in ASIR trends by sex. Incidence rates in females were consistently higher than in males. Rates in females increased from 190,857 cases per 100,000 population [95% CI 180,864-201,390] in 2000 to 194,620 cases per 100,000 population in 2019 [95% CI 184,482-204,560] (p-value 0.007) with a 0.17 annual percent increase. In males, NCD ASIR increased from 160,623 cases per 100,000 population [95% CI 151,716-170,325] in 2000 to 163,800 cases per 100,000 population in 2019 [95% CI 155058-173,439] (p-value 0.002) with a 0.11 annual percent increase. There were differences in the trends by type of NCD. Rates of neoplasms were consistently higher in females compared to males ( Figure 1 ). The rate of neoplasms increased in females from 3,323 cases per 100,000 population [95% CI 2,705-4,093] in 2000 to 3,351 cases per 100,000 population [95% CI 2,722-4,130] in 2019 (p-value 0.03) with a 0.04 annual percent increase while it also increased slightly in males from 3,118 cases per 100,000 population [95% CI 2,562-3,806] in 2000 to 3,148 cases per 100,000 population [95% CI 2,593-3,838] in 2019 (p-value 0.03) with a 0.04 annual percent increase. Download figure Open in new tab Figure 1: Neoplasms ASIR by sex (per 100 000 population), stable over time (p-value for trend 0.08) and consistently higher in women ( Figure 2 ). Rates of cardiovascular disease were consistently higher in males compared to females. Incidence in males decreased from 652 cases per 100,000 population [95% CI 608-701] in 2000 to 631 cases per 100,000 population [95% CI 587-677] in 2019 (p-value 0.02) with a 0.18 annual percent decrease while it decreased from 598 cases per 100,000 population [95% CI 561-640] in 2000 to 584 cases per 100,000 population [95% CI 546-623] in 2019 in females (p-value 0.02) with a 0.12 annual percent decrease. Download figure Open in new tab Figure 2: Cardiovascular Disease ASIR by sex (per 100 000 population) slowly decreasing and consistently higher in male Incidence of chronic respiratory disease was consistently higher in females compared UJ to males increasing from 665 cases per 100,000 population [95% CI 579-772] in 2000 to 729 cases per 100,000 population [95% CI 632-850] in 2019 (p-value 0.07) with a 0.41 annual percent increase while from 578 cases per 100,000 population [95% CI 507-671] in 2000 to 629 cases per 100,000 population [95% CI 543-736] in 2019 (p-value 0.17) in males with 0.37 annual percent increase ( figure 3 ). Download figure Open in new tab Figure 3: Chronic Respiratory Disease ASIR by sex per 100 000 population) increasing over time (p-value for trend 0.08) and consistently higher in females Throughout 2000-2019, the incidence rates of diabetes and kidney diseases in females were higher than those of males ( Figure 4 ) and increased from 407 cases per 100,000 population [95% CI 382-434] in 2000 to 489 cases per 100,000 population [95% CI 455-525] in 2019 in females (p-value 0.04) with a 1.05 annual percent increase and from 397 cases per 100,000 population [95% CI 371-424] in 2000 to 464 cases per 100,000 population [95% CI 433-499] in 2019 in males (p-value 0.07) with a 0.85 annual percent increase. Figure 5 shows comparisons of trends of different NCD in Senegal. Download figure Open in new tab Figure 4: Diabetes and Chronic Kidney Disease ASIR by sex per 100 000 population) rising until 2015, followed by a decline, with rates remaining consistently higher in females Download figure Open in new tab Figure 5: Comparison of non-communicable diseases subtypes ASIR by sex (per 100 000 population) DISCUSSION Key findings We observed that NCD incidence in Senegal increased modestly between 2000 and 2019, with important variations by disease type and sex. Women experienced consistently higher overall NCD incidence than men throughout the study period, a pattern that held across most disease categories. The sex disparity was particularly pronounced for chronic respiratory diseases, where the rate of increase among women exceeded that of men. Cardiovascular disease presented a notable exception to this pattern, with men maintaining higher incidence rates despite declines in both sexes. While neoplasm incidence increased only marginally, diabetes and kidney disease showed the steepest rises among all NCD subtypes, suggesting an emerging epidemiological transition. These divergent trajectories across NCD subtypes and between sexes highlight the heterogeneous nature of the NCD epidemic in Senegal and underscore the need for targeted prevention strategies that account for both disease-specific and sex-specific risk factors. The observed increase in NCD incidence is concerning and mirrors regional and global patterns consistent with the ongoing epidemiological transition. In West Africa, Ghana and Nigeria have reported similar increases in hypertension and diabetes, attributed to urbanisation, sedentary lifestyles, and dietary change. 21 , 22 South Africa, with its high prevalence of obesity and smoking, has shown pronounced increases in NCD incidence rates. 23 Senegal reached its epidemiological transition in 2014 (the point at which deaths from NCD outweighed deaths from communicable diseases). 24 By 2019, deaths from NCD had risen to constitute almost half of all deaths. 24 Multiple forces likely contribute to these trends in Senegal, including urbanisation, lifestyle change, and population ageing. 25 , 26 The country is shifting from predominantly rural to increasingly urban settlements: in 1990, 77% of Senegalese lived in rural areas (vs 64.2% across lower-middle-income African countries), whereas by 2019 8.2 million people (52.3%) lived in rural areas (vs 50.4% average), with urban growth concentrated along the coastal zone, particularly Dakar. 24 Rapid urbanisation has been associated with insecurity and environmental risks (pollution, flooding, erosion). 24 Concurrently, cardiovascular risk factors, including hypertension, diabetes, smoking, physical inactivity, and high-sugar/high-fat diets, are rising. 5 , 7 , 27 Health-system constraints may amplify these patterns: limited access to high-quality care, rural–urban disparities, treatment costs, and low insurance coverage. 7 Incidence rates of cancers were consistently higher in females than males in our study. This pattern aligns with Global Cancer Observatory 2018 estimates for West Africa, which report higher age-standardised incidence in women than in men (122.0 vs 95.6 per 100,000) and a higher cumulative risk to age 75 (12.7% vs 10.1%). 28 Differences in exposures and screening access, including Breast Cancer Awareness Month (“Pink Month”), may influence detection and incidence. Projections indicate steep increases in cancer incidence across all ages in SSA from 2010 to 2030. 29 Additionally, cancers are one of the key NCD that contribute to high morbidity and mortality in SSA, including Senegal. 30 Mortality rates are reported to be high, with specific challenges in Africa related to late-stage cancer presentation, lack of awareness, and limited access to screening and treatment. 29 Despite the overall rise in NCDs, our CVD incidence estimates show a slight decline. Importantly, mortality trends do not necessarily track incidence, because they are influenced by case fatality, treatment access, and competing risks. Regional syntheses of CVD mortality and DALYs report large declines in many high- and some middle-income countries, whereas reductions in SSA have been smaller and uneven; in several analyses, absolute CVD deaths in SSA continued to grow as populations expanded and aged. 31 , 32 The epidemiological transition in SSA has accelerated markedly, with the proportion of total disability-adjusted life years (DALYs) attributable to NCDs rising from approximately 18.6% in 1990 to 29.8% in 2017, driven substantially by cardiovascular disease. 33 The absolute number of cardiovascular deaths in SSA increased by more than 50% during this period, with mortality occurring at younger ages than in other regions, thereby amplifying both disability burden and years of life lost. 34 , 35 These patterns underscore critical gaps in cardiovascular health that require comprehensive approaches encompassing prevention, service strengthening, and equitable access to quality care. In Senegal, nascent interventions show promise: cardiac rehabilitation services, established with the country’s first outpatient centre in 2019, and patient education initiatives launched in 2018 have demonstrated short-term improvements in risk factor control and health literacy, though population-level impact remains to be established. 36 , 37 The higher cardiovascular disease burden we observed among men aligns with regional patterns across SSA, where male predominance in cardiovascular incidence, DALYs, and mortality likely reflects both differential risk factor exposure, particularly tobacco use, and underlying biological susceptibilities. 38 The rising incidence of chronic respiratory diseases in Senegal, particularly among women, reflects distinctive exposure patterns in West African settings. Women’s higher disease burden likely stems from disproportionate exposure to household air pollution from cooking with biomass fuels, a finding corroborated by local data demonstrating female predominance and associations between poor household ventilation and obstructive lung disease. 39 These sex-specific patterns underscore the need for interventions targeting both household and ambient air pollution alongside tobacco control measures aligned with global evidence on respiratory disease prevention. 40 The chronic respiratory disease burden in LMICs is further complicated by the legacy effects of tuberculosis, HIV-related lung disease, rapid urbanisation, and emerging occupational hazards. 41 Across SSA, chronic respiratory diseases contribute substantially to mortality and disability-adjusted life years, with trajectories remaining concerning given persistent household air pollution exposure and incomplete implementation of tobacco control policies. 41 The temporal pattern we observed for diabetes and kidney disease, with increases until 2015 followed by slight reductions, reflects the complex and evolving epidemiology of metabolic diseases in transitional settings. 42 – 45 This trajectory parallels broader regional trends: countries with the highest malaria burden experienced rising age-standardised mortality from type 2 diabetes and chronic kidney disease between 1990 and 2019. 46 In Senegal, urban areas show particularly high diabetes prevalence, while health system constraints limit both prevention efforts and long-term disease management. 7 The ongoing nutrition transition associated with urbanisation, characterised by dietary shifts toward energy-dense, ultra-processed foods, continues to drive diabetes risk while simultaneously complicating dietary management for those with established disease. 8 , 47 Study limitations This study relies on model-based national estimates from GBD 2019 accessed via the WHO HIDR rather than raw, country-level case counts. Precision therefore reflects the availability, quality, and representativeness of Senegal-specific input data; where inputs are sparse, GBD’s spatiotemporal modelling borrows strength from regional neighbours, which can attenuate country-specific signals. We analysed ASIR that were directly standardised to the GBD world standard population; comparisons with studies using alternative standards (such as WHO 2000-2025) require caution, as absolute levels may differ even when trends align. Because the data are aggregated at population level, we lacked key covariates (socioeconomic status, treatment access, subnational risk factors), precluding individual-level inference and limiting our capacity to explain within-country heterogeneity. Heterogeneity in the underlying source mix (surveys, civil registration, registries, facility data) and temporal variation in ascertainment or coding may introduce inconsistencies across years and settings, including possible under-ascertainment in rural or underserved areas. Trend estimation is further constrained by the four quinquennial time points (2005, 2010, 2015, 2019) available in HIDR. With only four observations, joinpoint regression has low power to detect inflections (at most one joinpoint), so we emphasised the average annual percent change (AAPC) and provided a weighted log-linear sensitivity analysis. Uncertainty was handled by back-calculating standard errors from reported 95% uncertainty intervals; because GBD intervals arise from posterior draws and can be asymmetric, this approximation may misstate variability. Finally, there is no classical sample size for these estimates. Future work should prioritise routinely collected, high-quality primary data (registries, strengthened civil registration and vital statistics, and subnational surveillance), incorporate draw-level analyses to propagate uncertainty more faithfully, and use annual GBD series where possible to enhance temporal resolution. Linking modelled outcomes to subnational and socioeconomic covariates would improve interpretability and policy relevance, particularly for targeting NCD prevention and care. Implications for public health The present study highlights the critical need to have reliable epidemiological estimates of NCD to inform evidence-based prevention and control strategies. Accurate data allows policymakers to allocate resources effectively and empowers healthcare providers to deliver timely and appropriate interventions. Therefore, investing in robust surveillance systems and epidemiological research such as electronic health record and digital registries 48 and integrated disease surveillance and response 49 , is crucial to develop a comprehensive understanding of the NCD landscape and guide the implementation of effective prevention and control measures tailored to the needs of our population. Addressing the increasing challenge of NCD requires the implementation of comprehensive strategies. These strategies should prioritize targeted interventions and emphasize the importance of modifying risk factors, early detection, and ensuring equal access to healthcare services while integrating approaches that reflect local dietary habits, social structures, and cultural norms. Health campaigns should promote healthier adaptations of traditional Senegalese cuisine, such as reducing excessive oil, salt, and sugar in popular dishes like “thieboudienne”, while encouraging nutrient-dense local foods like millet, fonio, and leafy greens. Additionally, community-based physical activity programs should incorporate culturally relevant activities, such as traditional dance (sabar, mbalax) or walking groups making exercise more engaging and accessible. CONCLUSION Using harmonised, model-based estimates, we demonstrate that age-standardised incidence of NCDs in Senegal rose over the past two decades, with marked heterogeneity by sex and subtype. Neoplasms, chronic respiratory diseases, and diabetes with kidney disease increased, often disproportionately affecting women, while cardiovascular disease incidence declined modestly yet remained higher in men. These divergent trajectories and consistent sex differentials reveal that uniform NCD strategies fail to address the complex epidemiological reality in West African settings. Effective policy requires targeted, evidence-based interventions tailored to disease-specific and population-specific needs. For chronic respiratory diseases, this means accelerating adoption of clean cooking technologies and strengthening tobacco control. For diabetes and kidney disease, primary care systems must be equipped for early detection and long-term management within financially protected benefit packages. Cardiovascular prevention demands sex-responsive approaches that integrate risk factor control with accessible acute and post-acute care. Crucially, these interventions require robust surveillance infrastructure. Senegal and neighbouring countries need sustained investment in civil registration systems, disease-specific registries, and routine risk factor surveillance that generate open, analysable data with appropriate uncertainty quantification to track genuine epidemiological change. The distinction between mortality and incidence trends is critical: declining death rates may mask rising disease occurrence if improved treatment extends survival without preventing new cases. Only through integrated monitoring of incidence, mortality, and care quality, coupled with responsive health systems that link prevention, primary care, and specialist services, can Senegal effectively address its growing NCD burden while advancing health equity. This comprehensive approach offers the most promising pathway to altering the NCD trajectory across sub-Saharan Africa. Ethical approval N/A no human subjects involved. Author Contributions Conceptualization: N.D.G., M.B.J., M.M.K., J.T., T.L.G.-W., and B.G. Formal analysis: J.T., D.K., and B.G. Funding acquisition: T.L.G.-W. Supervision: T.L.G.-W. and B.G. Validation: T.L.G.-W. and B.G. Visualization: J.T. and B.G. Writing – original draft: N.D.G. and M.B.J. Writing – review & editing: All authors (N.D.G., M.B.J., T.L.G.-W., M.M.K., M.A., I.M., A.T.A., J.T., D.K., G.S., J.L.C., E.L.P.S., M.J., and B.G.). Funding No external funding Competing interests There are no competing interests for any author. Patient consent for publication Not required. Data availability statement Data are publicly available from the World Health Organization’s Health Inequality Data Repository (HIDR) Acknowledgments The authors would like to acknowledge financial support for this work from the University of Pittsburgh Office of The Vice Provost for Faculty Diversity and Development and the Center for African Studies. Footnotes ↵ # joint first authors This version of the manuscript has been revised to update formatting errors. 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