Dissecting the Impact of Smoking, CMV and BMI on Immune Response: A Comprehensive Analysis

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The COVID-19 pandemic has accentuated the significant variability in immune responses among individuals and populations. This variability has resulted in a wide range of clinical outcomes following infection with SARS-CoV-2. Factors such as age, sex, and genetics have been identified as pivotal in influencing the body’s response to infections. Despite their known impact, these variables are often overlooked in the development of treatments and vaccines, highlighting a gap in our understanding and application of personalized medicine.

The Devastating Global Impact of Tobacco Use: Insights from the IHME Global Burden of Disease Study

The Institute for Health Metrics and Evaluation (IHME) conducts the Global Burden of Disease (GBD) study, a comprehensive research initiative that aims to quantify the health outcomes and risks across the globe. This effort synthesizes data from a vast array of sources, offering insights into mortality, health outcomes, and the impact of risk factors on global health. The GBD study’s latest findings, incorporating data up to 2019, provide a critical look at the state of global health before the onset of the COVID-19 pandemic, highlighting the immense challenge posed by non-communicable diseases (NCDs) and the risk factors contributing to global health loss​​​​.

A striking aspect of the GBD study’s findings is the catastrophic impact of tobacco use on global mortality. The IHME’s latest estimates, as reported in November 2023, indicate that tobacco use results in approximately 8.7 million premature deaths annually. This figure includes deaths directly attributable to smoking, which account for the majority, as well as those resulting from exposure to secondhand smoke and chewing tobacco. A significant portion of these deaths, 71%, occurs in men, underscoring the gender disparity in smoking-related mortality​​.

The distribution of smoking-related deaths varies significantly by age, predominantly affecting older populations. This trend is reflective of the cumulative impact of smoking over time, with death rates from smoking peaking in individuals older than 70 years, followed closely by those aged 50 to 69. Over the years, global smoking-related death rates have seen a decline in most countries, a testament to the effectiveness of tobacco control measures and public health interventions. However, the prevalence of smoking and its health consequences remains a significant concern, with approximately one in four adults worldwide using tobacco​​.

The disparities in smoking rates across different regions and among genders are notable. Smoking is more prevalent among men than women globally, with over one-third of men smoking compared to less than one in ten women. This gender disparity is pronounced, especially in Asia and Africa, where cultural and social factors contribute to lower smoking rates among women. Despite the overall decline in smoking rates, certain regions, including South-East Asia, the Pacific islands, and parts of Europe, continue to have high smoking prevalence​​.

The GBD study’s findings highlight the urgent need for robust public health strategies to combat the global tobacco epidemic. Efforts to reduce tobacco use and exposure to secondhand smoke can have profound health benefits, mitigating the risk of lung cancer, heart disease, and other smoking-related illnesses. The data underscore the importance of continuing and intensifying tobacco control measures, including pricing and taxation strategies, bans on tobacco advertising, and support for smoking cessation programs​​.

Data source: IHME, Global Burden of Disease (2019) – Note: Risk factors are not mutually exclusive: people may be exposed to multiple risk factors, and the number of deaths caused by each risk factor is calculated separately. OurWorldInData.org/causes-of-death | CC BY

The Milieu Intérieur Project: A Paradigm Shift

In response to this gap, the Milieu Intérieur (MI) project emerged as a revolutionary endeavor aiming to dissect the intricacies of the human immune system by examining the factors contributing to the variability of healthy immune responses. The project has meticulously assembled a cohort equilibrated in terms of age and sex, consisting of individuals with a homogeneous genetic background. This strategic composition facilitates the exploration of novel immune determinants beyond the well-documented age, sex, and genetic variants.

Advances and Discoveries

The MI project has made significant strides in advancing our understanding of immune homeostasis. By delving into the effects of variables such as age, sex, genetics, and cellular composition on immune-related gene expression, and investigating the influence of factors like CMV latent infection and smoking on leukocyte composition, the project has unveiled critical insights into the regulation of immune responses.

A noteworthy aspect of the project involves the measurement of cytokine protein secretion levels in response to immune stimulation. Utilizing Luminex technology, the project has analyzed the secretion of 13 cytokines following whole-blood stimulation with various immune agonists across a cohort of 1,000 donors. This has enabled a detailed characterization of immune response phenotypes, contributing valuable data to the field of immunology.

Collaborative Efforts and Global Impact

The MI project stands as a testament to the power of collaboration and innovation in science. Researchers are invited to access the MI data, biological samples, and methodologies, fostering a culture of open science and shared progress. The project’s contributions extend beyond academia, influencing medical practices and public health policies by challenging the conventional one-size-fits-all approach to patient care and drug development.

Recent publications under the project’s umbrella, such as those examining the impact of smoking on adaptive immunity and the role of Candida albicans intestinal carriage in healthy volunteers, further demonstrate the project’s commitment to exploring diverse facets of immune response variability.

The Road Ahead: Expanding Horizons

Looking forward, the MI project is poised to broaden its impact through initiatives like the 10-year follow-up assessment of its cohort, aiming to unravel the temporal variability of immune responses. Moreover, the project’s expansion into studying neonatal, pediatric, and elderly cohorts, alongside its efforts to incorporate diverse geographic populations through the Healthy Human Global Project, signifies a comprehensive approach to understanding human immunity.

The Milieu Intérieur project embodies a pioneering effort to map the complex landscape of human immune response variability. Through its ambitious studies, collaborative framework, and dedication to inclusivity, the project not only enriches our scientific knowledge but also paves the way for more personalized and effective medical interventions in the future.

The Immunomodulatory Effects of Smoking: Insights from a Novel Study on Immune Cell Phenotypes and Cytokine Responses

Recent studies have elucidated the complex interplay between lifestyle factors, infections such as cytomegalovirus (CMV), body mass index (BMI), and their collective impact on the immune system. By examining the associations among smoking, CMV serostatus, and BMI with immune cell phenotypes and cytokine responses, researchers are uncovering significant insights into immune system modulation.

Smoking and Its Immunological Footprint

Research has highlighted that smoking influences immune cell phenotypes, notably impacting natural killer (NK) cells. A study involving participants with varying smoking statuses demonstrated alterations in NK cell populations, particularly in CD57+ NK cells, natural killer group 2C (NKG2C)+ NK cells, and CD57+NKG2C+ NK cells among the total NK cell population. Smoking status was assessed alongside CMV serostatus, utilizing multi-parameter flow cytometry. This analysis sheds light on the nuanced ways in which smoking can modulate specific immune cell subsets, contributing to our understanding of its broader immunological implications​​.

The Role of CMV and BMI

CMV seropositivity and obesity have been independently associated with changes in immune cell dynamics and cytokine production. In a study focusing on the bone marrow’s (BM) microenvironment, it was found that increased BMI influenced the production of BM cytokines and reactive oxygen species (ROS), key elements in the maintenance of antigen-experienced adaptive immune cells. This work emphasizes how both BMI and CMV can significantly alter the immune landscape, particularly affecting cytokine expression and T cell functionality within the bone marrow​​.

Comprehensive Immune Profiling in the Framingham Heart Study

The Framingham Heart Study offspring participants have provided a rich dataset for analyzing circulating immune cell phenotypes in relation to age, sex, CMV exposure, and smoking status. The study identified distinct cellular differences with CMV exposure, including higher levels of Granzyme B+ cells, effector cells, and effector-memory re-expressing CD45RA (TEMRA) cells for both CD4+ and CD8+. Moreover, it was observed that current smokers exhibited lower pro-inflammatory CD8 cells, higher CD8 regulatory type cells, and altered B cell subsets, offering a detailed picture of how these factors intersect to shape the immune response​​.

Obesity’s Limited Impact on Cytokine Response in Critical Illness

In critically ill COVID-19 patients, an investigation into the relationship between BMI and immune response revealed that obesity did not significantly alter the disease course or cytokine profiles. This finding challenges assumptions about the role of obesity in modulating immune responses during severe infections, suggesting that factors beyond BMI might play more pivotal roles in determining the immune landscape during critical illness​​.

This body of research underscores the complexity of the immune system and the multifaceted ways in which environmental, infectious, and physiological factors interact to shape immune responses. It highlights the importance of considering a broad range of variables in the study of immunology and in the development of interventions aimed at modulating immune function.

The Persistent Effects of Smoking on the Immune System and Cytokine Secretion

Smoking has a profound impact on the immune system, influencing both innate and adaptive immune responses through its effects on cytokine secretion. The relationship between smoking and cytokine production reveals both short-term and long-term effects on immune function, highlighting the complexity of smoking’s biological impact.

Short-term and Long-term Effects on Immune Responses

Research has demonstrated that current smokers exhibit altered cytokine responses following immune stimulation. For instance, there is stronger induction of CXCL5 after E. coli stimulation and enhanced secretion of IL-2 and IL-13 after SEB stimulation, indicating that smoking affects both the innate and adaptive arms of the immune system. Interestingly, the effects of smoking on cytokine production vary depending on the duration and intensity of smoking history, with significant correlations observed in the number of years smoked and the total number of cigarettes consumed.

Past smokers, compared to current smokers, show no significant increase in CXCL5 secretion after innate immune stimulation but do exhibit increased secretion of IL-2 and IL-13 following adaptive immune stimulation. This suggests that the cessation of smoking may reverse some of the effects on innate immune responses while maintaining certain alterations in adaptive immune functions.

Impact on Immune Cells and Plasma Proteins

The association between smoking and cytokine levels also extends to specific subsets of circulating immune cells and soluble blood proteins. For example, the numbers of regulatory T cell subsets and B cells can modulate the effects of smoking on cytokine secretion during adaptive immune responses. Furthermore, levels of certain plasma proteins, such as carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6), have been found to influence the regulation of cytokines like CXCL5 in smokers, suggesting a complex interplay between smoking, soluble proteins, and immune cell populations.

Comprehensive Studies and Future Directions

Studies involving detailed assays and analyses, such as Luminex and MesoScale analysis of cytokines and chemokines, provide a deeper understanding of the multifaceted effects of smoking on the immune system. These investigations not only reveal the immediate effects of smoking on cytokine secretion but also pave the way for future research into how smoking-induced changes in the immune system contribute to the increased risk of diseases, including cancers and chronic inflammatory conditions.

The biological effects of smoking on cytokine secretion and immune function are significant and multifaceted, involving both immediate and long-term alterations in immune responses. The intricate relationship between smoking, cytokine production, immune cell populations, and plasma proteins underscores the importance of continued research in this area to better understand the implications for disease risk and potential therapeutic interventions​​.

The Persistent Impact of Smoking on Immune Responses through DNA Methylation

The intricate relationship between smoking and the immune system is increasingly being understood through the lens of epigenetics, particularly DNA methylation changes. Recent studies have provided compelling evidence that smoking induces significant alterations in the DNA methylation landscape, affecting both innate and adaptive immune responses. These modifications offer a potential mechanism through which smoking exerts long-term effects on human health, including its contribution to immune-related diseases.

DNA Methylation and Smoking: A Genome-wide Perspective

DNA methylation, a key epigenetic modification, plays a crucial role in regulating gene expression without altering the DNA sequence itself. It involves the addition of a methyl group to the cytosine residues at CpG sites, leading to changes in the chromatin structure and, consequently, gene expression. Smoking has been associated with widespread changes in DNA methylation across the genome. For instance, a genome-wide analysis revealed the presence of thousands of differentially methylated regions (DMRs) associated with smoking, with a mixture of hypermethylated and hypomethylated sites compared to non-smokers. These DMRs were found across various genomic locations, including promoter regions, exons, introns, and intergenic areas, highlighting the extensive impact of smoking on the genomic landscape​​.

The Role of Specific Genes and Pathways

The epigenetic changes induced by smoking are not random but rather target specific genes and pathways that are crucial for immune function. For example, genes related to the aryl hydrocarbon receptor repressor (AHRR), F2RL3, GPR15, RARA, and PRSS23 are among those showing significant DNA methylation changes in smokers. These genes play various roles in immune regulation, signaling pathways, and cellular responses to environmental stimuli. The hypomethylation observed in current smokers at these loci suggests an epigenetic mechanism for smoking-induced alterations in immune function. Moreover, the degree of methylation at these sites correlates with smoking behavior, such as the number of years smoked and the total number of cigarettes consumed, underscoring the dose-dependent nature of these epigenetic changes​​.

Epigenetic Mechanisms Mediating Immune Responses

The epigenetic modifications induced by smoking have far-reaching implications for immune cell function. DNA methylation affects the transcriptional programs of both innate and adaptive immune cells, influencing cell fate decisions, cytokine production, and the cells’ functional capacity upon antigenic exposure. This is particularly evident in the concept of ‘epigenetic memory,’ where stable and dynamic epigenetic states dictate cell differentiation and response patterns in memory T cells. Moreover, epigenetic reprogramming during primary innate immune responses enhances the cells’ reactivity to secondary challenges, a phenomenon known as ‘trained immunity’​​.

Implications for Health and Disease

The epigenetic changes induced by smoking contribute to the altered immune landscape in smokers, which may predispose individuals to various diseases, including cancers and autoimmune conditions. Understanding the specific pathways and genes affected by smoking-related DNA methylation changes is crucial for developing targeted interventions. This knowledge could lead to the identification of biomarkers for disease risk and the development of epigenetic therapies aimed at reversing the harmful effects of smoking on the immune system.

The persistent effect of smoking on adaptive immune responses is intricately linked to DNA methylation changes, highlighting the importance of epigenetics in mediating the long-term health consequences of smoking. These findings not only deepen our understanding of how smoking affects the immune system but also open new avenues for therapeutic interventions targeting the epigenetic modifications induced by smoking.


TABLE 1 – DNA methylation


DNA methylation is a fundamental epigenetic mechanism that influences gene expression patterns without altering the underlying DNA sequence. It involves the addition of a methyl group to cytosine residues, particularly at sites where cytosine is followed by guanine, known as CpG sites. This modification can affect the accessibility of DNA to transcriptional machinery, thereby influencing gene expression levels.

When it comes to smoking, which is a well-known environmental factor associated with various health issues, including cancer and cardiovascular diseases, it has been observed to induce widespread changes in DNA methylation patterns throughout the genome. This phenomenon has been extensively studied using genome-wide approaches, which allow researchers to analyze methylation status across the entire genome simultaneously.

One significant finding from these studies is the identification of thousands of regions in the genome where DNA methylation levels differ between smokers and non-smokers. These regions are termed differentially methylated regions (DMRs), and they represent sites where smoking has influenced the addition or removal of methyl groups compared to non-smokers.

The DMRs associated with smoking can be found in various genomic locations, including promoter regions, which are crucial for regulating gene expression, as well as exons, introns, and intergenic regions. This suggests that smoking-induced changes in DNA methylation are not confined to specific genomic regions but rather affect a wide array of genetic elements.

The impact of smoking on DNA methylation is complex and multifaceted. Some regions may experience hypermethylation, where there is an increase in methylation levels compared to non-smokers. In contrast, other regions may undergo hypomethylation, characterized by a decrease in methylation levels. These alterations in methylation status can lead to changes in the chromatin structure, affecting the accessibility of DNA to transcription factors and other regulatory proteins, ultimately influencing gene expression patterns.

The observed changes in DNA methylation associated with smoking have implications for various biological processes and disease susceptibility. For example, altered methylation patterns may affect the expression of genes involved in detoxification pathways, inflammation, and cell proliferation, which are relevant to the development of smoking-related diseases such as cancer.

In summary, DNA methylation plays a crucial role in mediating the effects of smoking on gene expression and cellular function. Genome-wide studies have provided valuable insights into the extent and nature of these methylation changes, highlighting the complex interplay between environmental factors like smoking and epigenetic regulation of gene expression.


The Complexity of Genetic Regulation: Exploring the Interplay Between Protein Quantitative Trait Loci (pQTLs) and Immune Responses


The intricate relationship between genetic variants and protein levels in response to specific stimuli is a burgeoning field of research, particularly in the context of immune responses and the development of diseases. Genome-wide association studies (GWAS) have played a pivotal role in identifying protein quantitative trait loci (pQTLs) that regulate protein expression in various conditions, including those induced by immune stimulation.

Recent studies have significantly advanced our understanding of how genetic variations influence cytokine levels in response to different stimuli. For instance, genome-wide mapping has revealed thousands of pQTL variant-protein interactions, emphasizing the complexity of genetic regulation on protein expression. These studies have identified both local and distant pQTL variants, with a significant number acting specifically on protein expression in response to particular conditions. Such findings underscore the importance of considering both the location and the context in which genetic variants exert their effects​​.

Moreover, the identification of shared loci with common diseases highlights the potential for pQTLs to inform our understanding of disease mechanisms and pathways. For example, certain variants within genes like Vitronectin (VTN) and ABO have been associated with a wide range of proteins, suggesting their involvement in cardiovascular diseases and other conditions. These associations provide insights into the underlying biological pathways that may contribute to disease susceptibility and progression​​.

Additionally, the study of cytokines and their genetic regulation has revealed a vast number of eQTLs targeting these critical immune mediators. The findings from such studies have implications for understanding the genetic basis of tissue-specific expression and the complex interplay between genetic variants and the immune system. For example, cytokine eQTL analysis has identified genes regulated by a large number of eSNPs, indicating the broad impact of genetic variation on cytokine expression​​.

The exploration of pQTLs and their effects on protein levels in various stimuli, including immune challenges, opens up new avenues for understanding the genetic basis of immune responses and their implications for health and disease. These insights not only enhance our comprehension of the genetic architecture of protein regulation but also pave the way for novel therapeutic strategies targeting specific genetic pathways involved in disease pathogenesis.

The Multifaceted Impact of Smoking on Cytokine Secretion and Immune Response

Smoking has a profound and complex effect on the human immune system, influencing cytokine secretion and altering immune cell responses in ways that can increase susceptibility to infections, chronic inflammation, and cancer. Recent studies have highlighted the intricate interplay between smoking and various components of the immune system, revealing both the immediate and persistent effects of tobacco exposure on cytokine levels, immune cell populations, and disease risk.

Immediate and Persistent Effects of Smoking

Smoking has been shown to significantly affect cytokine secretion, both directly and indirectly. One study found that smokers exhibit higher levels of pro-inflammatory cytokines such as IL-6, a key marker of chronic inflammation (CI), which plays a critical role in triggering the acute phase response and stimulating antibody production. This cytokine is also implicated in the increased lung cancer risk associated with smoking​​. Furthermore, smoking has been linked to changes in the composition of blood cells, including elevated levels of certain cancer risk biomarkers like CEA in smokers compared to non-smokers​​.

Interestingly, smoking not only induces an immediate response in the immune system but also leaves a lasting impact. For instance, incubating fresh whole blood from smokers without any exogenous stimulus led to an increase in several pro-inflammatory cytokines/chemokines, pointing towards a higher level of oxidative stress in smokers​​. This oxidative stress, a result of the reactive species generated by cigarette smoke, can overwhelm the body’s antioxidant defenses, potentially leading to chronic inflammation and increased cancer risk.

Altered Immune Responses and Disease Susceptibility

The literature also highlights how smoking skews immune responses, favoring the development of infections, lung disease, and cancer. Cigarette smoke has been shown to induce the release of interleukin-8 (IL-8) from human bronchial epithelial cells and inhibit the production of inflammatory cytokines by suppressing the activation of key transcription factors in bronchial epithelial cells​​. This suppression of the immune system’s ability to respond to infections and inflammation can lead to an increased risk of chronic obstructive pulmonary disease (COPD) and lung cancer.

Moreover, smoking affects the phagocytic ability of alveolar macrophages, impairing the body’s defense against pathogens like nontypeable Haemophilus influenzae, a common cause of bacterial infections in the lungs of individuals with COPD​​. This impairment further underscores the role of smoking in exacerbating lung diseases and highlights the importance of understanding the mechanisms by which smoking alters immune responses.

Comparison with Other Risk Factors

Comparing the effects of smoking with obesity on inflammatory biomarkers reveals that both conditions can elevate levels of CRP, a marker of inflammation, although the levels are higher in obesity. This comparison underscores the complex interactions between different risk factors and their collective impact on the immune system and disease risk​​.

Conclusion

The evidence clearly indicates that smoking has a multifaceted impact on the immune system, affecting cytokine secretion, altering immune cell functions, and increasing susceptibility to a range of diseases. The immediate and persistent effects of smoking on the immune system underscore the importance of smoking cessation for reducing disease risk and improving overall health. Future research into the transcriptional regulatory networks underlying these effects will be crucial for developing targeted interventions to mitigate the adverse health effects of smoking.


APPENDIX -1 Deaths by risk factor, 2019

The estimated annual number of deaths attributed to each risk factor. Estimates come with wide uncertainties, especially for countries with poor vital registration

Country/areaHigh blood pressuredeaths • 2019Diet high in sodiumdeaths • 2019Diet low in whole grainsdeaths • 2019Alcohol usedeaths • 2019Diet low in fruitsdeaths • 2019Unsafe water sourcedeaths • 2019Secondhand smokedeaths • 2019Low birth weightdeaths • 2019Child wastingdeaths • 2019Unsafe sexdeaths • 2019Diet low in nuts and seedsdeaths • 2019Indoor air pollutiondeaths • 2019Diet low in vegetableslow • 2019Smokingdeaths • 2019High blood sugardeaths • 2019Air pollution (outdoor & indoor)deaths • 2019Obesitydeaths • 2019Unsafe sanitationdeaths • 2019Drug usedeaths • 2019Low bone mineral densitydeaths • 2019Vitamin A deficiencydeaths • 2019Child stuntingdeaths • 2019Non-exclusive breastfeedingdeaths • 2019Iron deficiencydeaths • 2019Outdoor particulate matter pollutiondeaths • 2019Low physical activitydeaths • 2019No access to handwashing facilitydeaths • 2019High cholesteroldeaths • 2019
Afghanistan36,0171,42210,3355834,5833,7516,06222,13212,2857413,26928,1685,14810,30624,88837,03322,0482,5927006323933,0711,7637618,6794,1173,94119,746
Albania7,6092,4451,52073721747741063366379724514,4252,1582,2763,120113065010401,53231082,791
Algeria58,6021,91014,7721,2852,6482777,6707,0927459365,697662,74121,55538,97822,16236,087861,0301,3723681469421,6139,58032627,534
American Samoa87616282153330685510214950220000812031
Andorra10161940508006203106541458061200001113041
Angola17,6861,2892,01311,9061,57911,1431,63415,87610,76616,3834498,7261,3257,51110,75314,3846,9816,9515577183231,8241,6803915,5637967,0093,964
Antigua and Barbuda130112628618431240837130309101300003018237
Argentina59,0807,25811,34720,9622,1343158,5782,6621,5394,6615,3747083,08551,30639,51713,77836,676783,0621,572226734512,5901,08893322,649
Armenia7,7891,0622,44680231931,006133471721,03178294,8645,4423,2874,4635966507913,091596213,455
Australia25,4981,1505,1148,5762,457401,582376151512826131,50018,99917,6501,90718,71382,6732,18401411,7814,4009014,013
Austria19,7692,3892,9854,94466231,206905270504979912,31410,9102,6558,982859492000102,3892,258149,409
Azerbaijan23,8653,1687,0604,0441,393603,1381,6126743522,05666615612,49714,4348,64314,3335134712108119257,8601,3129211,918
Bahamas58647941463433317711692231554051024411917001199596164
Bahrain825322596931614826514402145451,2786381,1271281900016242285497
Bangladesh182,93720,99515,55910,14729,96928,15824,66439,2379,4154,34916,09494,78922,467105,712101,377173,51543,80318,7481,3842,204261,3511,0071,10673,97611,29715,54248,743
Barbados5553198126663291665330341576311754511413000017511512176
Belarus44,1872,40712,3919,8073,57442,435108367064,509961,03920,50911,3138,57019,272386239901428,4033,3962224,804
Belgium18,6551,9803,3467,2371,316281,360128343363437657219,61610,9133,7878,573178941,62100103,4912,559787,562
Belize301264812339284919881302513830012429847110131934412101
Benin7,3618027941,9719184,40865611,2117,1482,224499,8915441,9384,69612,2384,0723,338872904711,8587723092,3043253,6891,761
Bermuda1101025221008107416618710800230000821149
Bhutan70283105848475682143446503526533247766030758285005552707521336
Bolivia9,0921,4631,6043,0708244395802,7521,6141,697772,2769213,5299,3546,2558,9832302205104152139953,8856216383,394
Bosnia and Herzegovina10,6433,3061,6981,30374231,3106241658101,1482228,7009,0914,8375,845119013200103,62272255,102
Botswana2,5101653181,0314213984277444895,5801996362221,5882,2061,5962,137255230605586310942171392559
Brazil239,41630,81433,25077,47711,4884,30927,78821,52311,62122,82381614,01617,701170,120174,19960,915177,9402,4506,89212,135333821,14532543,57545,5596,10199,375
Brunei311706315481341822341262674174018701511000039352149
Bulgaria47,20914,9337,3438,1393,36193,023139405342,2691,81256320,63921,53011,01322,742163029205919,0722,4412219,141
Burkina Faso13,2331,2911,8696,8952,22312,9481,66018,75823,6613,6529824,3031,4872,9908,60027,7175,7989,8031587066423,6412,6384913,38433110,2092,051
Burundi6,7821,1029555,4003178,0973787,2637,6502,37947110,0047972,7793,68111,0141,8136,020812652281,4515082439771004,5671,512
Cambodia14,6273,7851,3199,6552,8361,3333,3744,3682,5451,70616614,0342,07916,45914,15517,6225,25579390896115379250813,4996811,2645,568
Cameroon18,6481,6551,9898,4201,20315,1301,36213,53715,07422,8393412,0689955,41411,63822,43313,52910,5313938436552,7302,97157910,2509349,3252,285
Canada41,7994,2969,22813,6223,645593,2437203161,02129682,25149,64630,7274,38129,814705,0623,96701633,7655,73011722,409
Cape Verde70964892048136437824811099371574874203422152301313194069217
Central African Republic4,8993555542,3585917,3663925,2967,1865,530136,9615701,9753,3127,9191,3255,5201772134271,2361,3331859311783,8661,095
Chad8,2528071,6153,3811,36326,4571,30115,82332,9494,64816519,0661,0182,9735,08221,7092,71419,9881753481,8315,6626,2817582,61426614,1412,066
Chile21,8012,8913,1438,5561,3891112,3254975751,40098433063911,17914,9336,24414,095601,78195802655,8081,2441116,462
China2,599,879855,385383,478514,659231,1203,270416,05434,44420,49774,85986,309363,02915,7062,418,6651,067,5541,848,274764,6981,90085,23889,857211,0481,6372021,423,633149,5317,575915,983
Colombia40,49910,4217,1127,5632,2025283,5563,4331,8244,7162,8342,4543,43517,29634,18015,71125,7301195071,3651701445313,0332,64857319,656
Comoros737124906852226743541996616552812503866463091728335303059310180203
Congo5,0913695621,8234901,5612971,8231,0154,074201,6385031,4333,0773,4703,0441,11714217565107209871,8032821,0011,252
Cook Islands427673080020132147445011000036012
Costa Rica4,8587277961,11316155322198373392221043462,1183,2251,0682,80451062810142938155601,841
Cote d’Ivoire16,1751,5242,0847,2321,3176,2142,35222,3158,03212,5614316,2621,3836,4819,52223,0538,1524,3115065841421,3421,2595456,7326825,8084,003
Croatia14,7184,4732,6422,92979581,5004221718221696759,6409,2873,3907,659113271200103,0721,04266,858
Cuba19,4381,8224,1124,5691,1131992,177128759893242001,01119,99015,6586,14411,920691952,00802775,8453,4014559,591
Cyprus1,835142393333102116020733281961,5351,6064588020309900004132102864
Czechia24,8178,7195,0586,7282,469572,3901001264651,929801,82320,71623,5556,60717,45346631,06800206,2552,9263316,349
Democratic Republic of Congo59,0472,5265,98415,6846,64629,1532,18536,75228,88513,46941858,0386,35315,71733,93969,50320,75020,6577692,5971,5704,1974,0732,26511,0602,64821,53513,181
Denmark8,6956471,7743,524504107188950207369236612,7285,2811,4674,128545856800101,2981,111303,793
Djibouti8281281279013926411651146095055201724914676583601871439449462445314228198
Dominica1531329321189312146411383711501300003319335
Dominican Republic15,5951,3352,7893,7222694509992,9216731,7661169391,3248,2029,3854,7669,134153244387223109383,7982,3704547,467
East Timor1,623341156266224185203462281191421,0271699281,0041,24325914135343512692105864418
Ecuador12,8471,9862,2953,9643312767241,7689802,1691,1114761,2204,80413,2874,76213,4549726980016568374,2361,0704265,117
Egypt164,7105,99833,3866,2073,9903,32219,6676,8398,9795429,6417349374,03299,35391,663130,3422,3931,6473,405271,0922,21510290,55923,5861,33888,183
El Salvador7,3981,0901,0822,3065532213743983781,096586185161,7057,1592,5745,2601321103611122561,9012782503,058
Equatorial Guinea7115169299349747403921,90118456192496486506345325111161239751108147
Eritrea3,9576984851,3455553,6213722,7883,3691,8131523,9364941,4652,4165,3361,6862,70880170724492491751,380652,388941
Estonia5,4181977891,19430212048288364401882,1961,3692073,026022354000016033642,314
Eswatini1,12874107620150396873812943,069174821043621,2038321,2802701163454370534493238209
Ethiopia41,7347,9936,49519,6027,70343,1741,78863,95839,22425,4183,19267,8274,8718,12325,73877,02014,96133,7021,1912,3681,3446,3193,6351,4558,95782727,5838,285
Fiji1,833274416107353683441176698143021669242,7406342,352293117035233026611865
Finland13,7999972,6172,6341,04614022761201,03828616,7639,0754175,581163874400003851,60496,984
France89,1706,30718,55942,1567,900884,0547084,6002,3283,557374,67680,34840,29514,33446,898365,2469,997016413,24514,76726237,831
Gabon1,805138182897511921174761521,1215691485241,4208951,30912744721123021821113185430
Gambia1,8011502095082604602249994281,06641,4931766119821,98785532244641144397548774443503
Georgia18,8022,4903,7702,2591,46271,578162262411,0391,5947597,17210,1044,7878,568630418703533,112936265,833
Germany224,49415,94133,59376,27912,9081068,0628926303,0204,569309,889143,642150,71329,252106,143515,3299,281015327,04120,21631494,572
Ghana26,8433,3793,43810,1549155,5991,23211,5476,06614,9955411,0652,1265,47717,72823,79217,7813,75460687413551859135612,5441,2755,7578,435
Greece29,0562,3597,4313,95867812,616125103585674127926,25815,9546,21913,080134456700205,7152,5896114,059
Greenland6071340601231410212742750075000065028
Grenada164133345811193144214551785412602400005122451
Guam3074963191644216611152615920936220095000031251155
Guatemala11,3081,7511,8265,8901,1452,0271,0312,5053,4411,7923715,2968623,78814,5069,0658,1741,18649257812574293723,7341721,0974,076
Guinea8,9958499891,8506535,5621,1989,5018,5014,6953913,7528334,2505,47616,2423,9103,8981613632521,4429965292,4553265,1072,353
Guinea-Bissau1,5061371585911721,0531431,4228991,03451,6391763018731,9986197594047951971013535555643400
Guyana1,478119216474164491171716921410551124231,4444661,129212235037441117550528
Haiti17,2471,2282,4174,2491,5103,5028425,9494,5245,57030512,1511,8743,11712,97714,0185,5922,483298255705221,0113501,8221,3762,4045,348
Honduras9,8851,4911,2242,7867477798171,4475114766993,8757934,2267,5255,7205,622473287242454136341,7832141613,636
Hungary34,37712,2097,2289,1152,780593,600112245303,3271,3471,05724,82322,6598,61720,490302231,06301216,9402,1931517,396
Iceland37437887133030426230293452281920402121000016561232
India1,471,889174,797258,257343,695256,232508,290240,098445,535118,28378,979164,172606,890134,0071,013,2821,121,9141,667,331579,108291,10372,903118,6821,50121,57517,97310,098979,68296,012173,939630,093
Indonesia477,72391,66838,67817,64446,15745,77452,55530,86131,56612,6031,81076,86735,542246,359259,251186,267186,65716,3626,01210,0532042,3442,646801106,71024,40410,170112,173
Iran99,9393,87629,0902,9762,00351110,6076,2546501,1543,471971,67239,92668,12143,20361,4151435,9803,048145922641,74214,44650452,530
Iraq55,7161,84511,8038174,4853826,6356,6208813546,172641,04025,19938,01625,62636,4811271,09877351221695525,3788,30811424,813
Ireland5,7863369541,543448143560811127322716,1843,6555522,977233320000105351,003182,738
Israel8,2556091,8696511841354217551180374406,1447,3842,4565,1341027334800212,2801,265242,906
Italy123,00111,91232,19430,3654,228478,3744635772,1715,4011213,93590,48995,75327,90264,136266,2927,590005224,66618,35414253,140
Jamaica3,8523316454182883234035866575321992211,7214,8131,1603,4341534690134938790611,090
Japan196,38538,08730,87747,79519,20654216,7963581,4704,49912,031953,448199,396101,14142,56551,82210310,5358,9210812539,69220,5362,36075,782
Jordan8,1682862,044186564291,0141,4331948417322974,7426,1763,1317,548412815311842133,0741,037493,663
Kazakhstan43,2434,9739,4559,5863,450293,5561,2653769142,9491,42437420,16422,69812,03922,828242,55241912863910,1332,69314116,202
Kenya27,2842,9232,72415,8623,07915,4051,83216,14212,36044,8901,12022,1092,15510,24613,98927,73915,02511,3675,5341,1444731,3612,1578255,49036010,8184,862
Kiribati177284420323452322430313328252284152229219212121819787
Kuwait2,53419161932173235719717231271251,5241,7871,5432,3170597601401,526484251,637
Kyrgyzstan7,8681,2492,9292,8621,087571,2219582503031,2021,4321895,0252,6844,1594,4795759510213345102,586583374,995
Laos8,1951,7996802,3817749141,3822,4481,4925571276,3326755,8486,4407,7663,52960915419620247233561,3762925202,792
Latvia9,3266371,8471,61481714961831596501043813,6902,9241,2344,366121111800101,1191,08475,030
Lebanon9,7573343,146262160401,35233947987610467,8117,1443,3826,165222911004823,3031,858506,121
Lesotho2,6601892031,6614881,2184821,01175810,173981,6332652,2172,5862,4992,32889334895169910230839129925386
Liberia2,9552593561,1813342,0601732,0861,6391,747962,7143066751,9463,3761,7191,41571103522312341746561501,247784
Libya8,6542852,126209428371,1612805116644683473,6635,8103,4456,2001326628606543,3681,280434,172
Lithuania12,4579372,6652,31098355762171881,020615624,9343,1241,3405,807333120000101,2641,633117,383
Luxembourg763561262805105047126003367656710335304152000091852326
Madagascar22,6653,5581,7724,1712,69515,6771,45713,14317,3383,9061,08621,4592,5735,4137,74323,7488,53212,1203284396883,0672,0384482,2462599,0034,485
Malawi11,1171,6508364,4151,1926,4726968,9785,69113,5177312,3791,1464,7466,61913,7174,5534,7962803911249475362661,3122084,5632,469
Malaysia41,0817,9086,5403,3882,7907265,9641,0664011,806831113,12424,58824,60910,96019,105801,3981,400025284210,5513,53947219,816
Maldives338666513329465787142322205240811103168011149294159
Mali11,2121,1161,4372,0711,41611,8811,23528,27728,5404,72225122,5801,1873,6027,43325,8725,3188,8191825136992,3691,8499003,2464037,7362,825
Malta84778242110570541019270205517001623690213100001471822471
Marshall Islands8314201014416848224135310436742410000129146
Mauritania2,6662364231653911,2792111,7571,0982232431,2082627031,3942,6281,75593281232098178981,411332794750
Mauritius2,7145324143403726393702412149141301,0413,6046212,23631193901116063324904
Mexico129,01913,03015,80649,8896,7372,39410,4589,8178,61910,8726,8429,8547,60548,393157,90848,332125,5919534,0095,0021624552214136,58211,9831,54452,139
Micronesia (country)178304423316387546448271672488021838400003224295
Moldova14,9977932,6423,8001,1525731114173201,4792827795,9214,4262,4196,769447311101712,102957416,482
Monaco88618152070020019748165003300001514045
Mongolia6,3188331,3013,3401,184365324021531836921,0096873,7661,1193,2683,58729415840192982,245178522,554
Montenegro2,2957033194926602449124102168131,7611,4537381,218022290000564931752
Morocco79,9042,55219,6471,1081,7869596,6164,7711,3131,5875,1331,6791,90721,38248,11729,24941,9203011,0301,720211273259427,06310,68363636,767
Mozambique22,2503,3102,0924,9252,9857,6381,33319,07210,59654,37530325,0172,1338,05812,14326,9217,7445,6948298282661,3921,5234921,8793096,3074,415
Myanmar85,79017,7747,52620,45212,2655,54110,88713,9076,1635,59913449,2235,89560,03968,00474,54431,1973,3555,8332,589596361,02629524,1693,8343,51522,312
Namibia2,4001502821,0343195512287854853,4651707751991,1501,8041,5911,559348155733366913789217359553
Nauru16233203211002111521501000001108
Nepal23,6973,1443,6406,8313,1024,7054,4368,3293,0302,0522,60621,6032,42934,20115,51342,1159,1452,6698981,5992632427230817,9481,5691,9719,470
Netherlands22,9411,6184,4437,5651,722101,79923413042457861,32831,53014,1014,97011,69266582,36500214,5691,716709,913
New Zealand5,9704301,3061,3524061334786169714533414,7923,4143343,62632713810011303918203,331
Nicaragua6,5479618141,7067091364845303279102801,7355781,6455,9732,7604,342851041960285161,0021911062,288
Niger10,6559901,3411,0411,57124,7161,42923,54137,1972,3192326,5077631,9825,72829,5053,66519,008734573,6479,6764,7718092,97139614,0122,510
Nigeria114,1258,03413,98145,8889,743157,2929,917187,666192,43768,152313128,2596,63717,35057,698197,56747,586103,24112,4633,9222,37243,32436,9254,30868,5335,34596,52129,796
Niue5110101000001361500000000102
North Korea50,37716,4926,4319,7936,2971199,8591,6047691,9634,22931,5153,01243,76422,08755,1548,4001022,1911,662673613221,5902,49016920,170
North Macedonia8,3942,6151,4019723982890100798142535515,3075,8613,3014,67611228401202,75144823,274
Northern Mariana Islands81131596112115058608117820320000107034
Norway6,7664541,5551,2634008431369415135714424,8184,7534542,78143857360000393934263,440
Oman2,9961087136778213052833010033661278122,3671,5762,41717213903421,553538231,909
Pakistan220,69824,19154,77818,21429,18265,45530,919209,47160,1514,50517,707116,09024,682134,289145,454235,657101,13530,8818,5833,30233911,2098,7563,646114,00816,29323,03389,731
Palau43710351111150053056549011000055023
Palestine3,8161431,181219329216156274541197281782,1853,9001,8482,8164486004731,792718392,108
Panama3,5065324168662821111982912207181061542811,1823,4858232,2645569101016298650129671,259
Papua New Guinea6,7271,2741,8755741,3612,6202,5813,9564,4633,56537211,1691,0137,15510,17112,3515,0081,984299352651,1434411761,1816161,3503,581
Paraguay6,5658179372,1333521126894143948461451,1935354,4115,7552,2844,8205019524211137181,0454801392,624
Peru19,0592,7122,9886,7401,4307321,1923,0021,5993,7601,1962,4391,4854,48913,28911,41414,355487547968311994668,9051,4921,5837,375
Philippines127,06028,26415,31639,8029,3796,65421,66920,87211,8387,2121,83742,67510,31795,58784,25374,78365,2001,9681,1742,3142851,8491,29227032,0192,7274,62251,846
Poland90,65621,62120,12926,3208,726767,7744861342,2149,1262,8081,82577,66962,95631,11957,514161,8262,912047227,7629,11812046,615
Portugal19,6371,3993,5807,2421,148241,771761307927823438712,13417,7392,41110,0912560074500202,0863,448938,628
Puerto Rico5,9765051,1701,38032168408921073164214942,7897,1464345,829410821900214271,155932,209
Qatar72631222751421177651228034188425459630395100115391633435
Romania94,37627,79712,93419,6015,119386,2434122571,9676,3372,43433838,99927,14017,13842,107242,26387002350314,5776,4857939,922
Russia557,78162,595115,639154,18147,58616135,6932,53088315,21443,5292,44827,048291,357196,91277,517283,79312126,4796,1630821602573,85941,346724332,217
Rwanda7,1591,2718655,223283,0555553,9713,1863,7022327,4687454,9594,5799,2863,0822,25982385495031021371,7581242,533928
Saint Kitts and Nevis10681626132754302172594128002200001112230
Saint Lucia276234486183161462145201062908519913700008040361
Saint Vincent and the Grenadines21518395610315118292417622366716212500006235465
Samoa3172070263976614821113943234341181282196110041372122
San Marino52410163030011024232726012000067022
Sao Tome and Principe1981728657963817171871844951409851702115272252
Saudi Arabia28,9951,1657,1317222,3141514,0377991236172,546371,82312,27119,54318,03628,039207222,33506112817,7956,14321817,926
Senegal11,5009831,3661,0421,4355,3481,5138,6723,8962,273549,0758513,1087,93112,4835,2653,82188432934416234243,3696613,1252,767
Serbia39,54511,6876,3625,0661,458143,480142196671,7861,9691,42524,35025,62512,66819,1614598414013110,6092,3751618,642
Seychelles178302057114196312301310612136881730000359361
Sierra Leone6,4715306781,9047153,2508325,6004,9402,999157,8135582,2252,4959,3712,0642,37270215617905313011,5422442,8531,554
Singapore3,475870674307180529626614018821132,8142,3501,3741,77711569100101,331373671,943
Slovakia15,9554,8523,4573,4931,33541,28010221246903347638,2257,0793,5738,779136637602303,4721,212169,003
Slovenia4,5861,3976241,115174134413164151621762,9802,0209402,6050169322000082329761,673
Solomon Islands9511762845920918327210710291621,2112321,0261,1921,32097014441263148111098242665
Somalia11,4981,9171,4979031,93314,4491,33914,22927,4004,15911527,5531,4965,2576,69328,3342,01710,8311454232,1834,0233,61379377014510,1922,378
South Africa61,4733,2915,24327,0608,3759,5067,29715,6337,157136,9783,7734,5903,90032,83654,45929,83055,3655,4015,4861,821748501,57129824,7805,9617,42814,727
South Korea37,14212,2525,98526,8924,4101384,0454191351,4211,485151,19951,57539,83223,11519,333252,2123,658013521,8375,40132315,522
South Sudan4,6977514945753915,9975237,8958,5354,456507,6784481,9192,6899,0882,4344,5541031751381,1379991511,390834,050934
Spain72,1062,91312,75319,3302,332525,6583593121,7631,7561782,14266,33154,53511,78542,038131,7242,78900518,8809,78316627,348
Sri Lanka29,9386,0514,2247,2963,8577483,0278622625471216,6432,35311,07131,71414,11415,9363762041,3021137147,2611,78431712,839
Sudan50,5011,73011,5814943,3945,4804,56818,9597,1613,6194,04211,3103,10716,14726,17728,16324,4424,1812,1679221569921,11345116,6348,8563,00320,203
Suriname829741262147429951132713264775451845308657101423015226111021339
Sweden19,5011,4954,1054,3401,225197398111029970231,15513,69211,9757588,795117341,23300106491,988409,414
Switzerland12,5719782,6803,938795567711778233313171510,2167,8411,6086,12926181,26800101,3741,809236,419
Syria25,5689468,3035671,487653,013840287121308181,85813,24017,99410,67116,0542029730715015710,4744,24112016,712
Taiwan25,6955,0055,03511,1921,417355,0302521351,14518549266826,64526,12212,52714,95792,2581,421013211,5833,1142419,262
Tajikistan13,0641,6493,5121,7321,5685501,3642,0201,7611811,6052,6072304,6348,0167,4554,6654654368512281308104,7584843225,675
Tanzania38,9448,0612,93319,2902,94913,2033,61632,24418,61426,7377739,1653,14417,91418,75745,49117,6059,4962,0191,2613053,4371,4121,2336,24664112,5458,651
Thailand69,03214,8948,06439,2234,3295,0109,4351,3691,24817,6111467,4496,46762,85965,17940,87843,87326010,6743,784242703132,2115,2133,04329,280
Togo5,7295036991,5688965,0385124,2093,9073,525195,0606302,2922,3946,7132,6183,5451461861454886311231,6192232,8231,653
Tokelau3010001000000130200000000001
Tonga1162024916226969231131001595211618300002017151
Trinidad and Tobago2,69720958639932317285113322701912201,0283,4488922,611430420031890580211,099
Tunisia19,6806925,281723795762,405738792684282133910,85914,6567,53012,00027393473071577,3371,60511510,680
Turkey109,1622,67028,8663,9411,35946914,6065,7691,1051,3751,08723632086,17072,36944,16680,1181081,3093,178348774041,52416,15892444,344
Turkmenistan11,3391,3553,0322,349748471,4767665562131,6955584,0444,7013,6086,87236545370567393,577590645,501
Tuvalu254514151120231728419010000023011
Uganda18,4532,9321,87715,3565239,1991,22424,87311,04920,0016823,0011,9706,27312,29027,6778,3936,8821418643831,9038314034,5863287,1453,090
Ukraine237,92613,63766,76544,74425,4884416,0788351685,48029,8832,7285,983113,38970,34446,129116,655319,3611,60201922942,91612,349272164,333
United Arab Emirates5,9832931,470553323269376571502602933,7264,2763,3617,62311,00836701123,2521,120273,910
United Kingdom87,7626,66820,84925,24210,067408,2771,3391621,95611,140125,936119,77775,45415,02656,21685,0144,9620211414,44914,33544448,028
United States495,20148,501102,247136,66340,17238235,5839,6065,89814,35411,02915027,977527,736439,37960,229393,859682104,73627,6810147511447,78737,147987226,343
United States Virgin Islands30626625791194414112010926732252047000031292128
Uruguay5,5277511,1831,68939657789122119362401534074,8643,2838203,22272432460231733428422,382
Uzbekistan62,4657,41620,1559,5625,139866,0784,2933,4621,3539,9433,16422822,19341,04330,09639,317893,04245214217374226,7492,81050037,741
Vanuatu5968610346535664573629936166247432416333401771542542422244
Venezuela43,1396,5435,6868,6212,5907733,7532,8631,0724,1334,257883,17116,76935,10812,61726,8192924991,1473661686312,3841,22144715,272
Vietnam158,37532,15511,91552,98415,1361,25119,0855,2861,5377,52176933,2476,12397,074106,47871,70137,9816059,6058,39072392463037,4575,5562,05340,603
Yemen30,5641,2419,0488613,6095,3514,46717,1737,4565523,6949,7093,62217,30614,46721,18411,7803,3945639232031,3161,98549811,2823,6702,19816,921
Zambia10,3401,8288736,8702,0565,9159198,2866,36419,582718,8221,2014,6736,35311,8266,0744,1333943981131,0897391772,9493293,9752,112
Zimbabwe12,2411,1401,4755,1561,9603,9141,6467,9465,80119,02525610,0191,3828,8389,79712,6676,4752,531963438815856312592,6073454,1133,571
Other
African Region (WHO)718,29971,73688,234270,44174,276492,20263,688670,297584,478596,45019,594656,08559,655236,433437,338897,242361,539347,98036,54326,56018,084107,06986,14620,497237,23536,619327,473178,229
East Asia & Pacific (WB)3,946,0961,131,168533,448810,626362,76274,574582,677122,95585,134143,571111,680640,57698,7423,390,9121,927,2192,489,6201,290,21828,579142,198138,4186938,1308,0312,0671,774,090234,42738,0611,349,535
Eastern Mediterranean Region (WHO)864,25849,264212,60635,71961,472100,378105,841312,037127,58019,81957,833195,04748,411403,946553,626594,627522,39255,12225,16919,5043,33422,14220,1846,517389,412108,81445,866419,130
England69,7385,56016,82020,1037,977326,5941,1661321,5619,23294,83296,05962,37513,11645,39063,6604,0190210312,64110,92636938,807
Europe & Central Asia (WB)2,343,457280,028507,361582,180171,2492,248169,04627,19317,29949,005164,44130,20881,1711,511,4531,217,981482,7911,233,8081,30384,34967,329191,1141,829193433,235215,3405,3291,207,305
European Region (WHO)2,360,893283,323510,860583,873171,8822,263170,52027,47517,35749,288164,64630,74681,2801,523,3271,231,884488,7021,243,9371,31584,75767,787191,1151,834195438,407217,2315,3571,213,928
G207,642,1541,501,9681,265,8051,763,418756,647576,491951,579587,210217,072401,652400,6111,088,390324,2066,077,1874,495,2254,334,0773,414,927319,677373,318348,9571,85426,67226,03312,1573,060,157596,373215,4973,102,459
High Income (WB)1,895,616226,977375,446555,459142,8852,356140,96120,10316,82045,51680,7606,25182,4711,733,6181,387,311361,4891,129,4891,285166,330105,094158205197323,644209,1446,838862,050
Latin America & Caribbean (WB)699,44891,077104,060221,48437,69817,74969,09564,20240,50572,99126,65959,31349,085390,430601,070234,047522,6739,52720,37529,8121532,3784,0901,389167,84379,32217,886281,121
Low Income (WB)483,18868,09162,740149,92957,969286,49949,653416,874369,034243,78117,749558,38549,194212,021279,885685,896185,480212,87612,57718,72516,35661,50944,08314,889121,23219,279195,082132,103
Lower Middle Income (WB)3,828,938474,684640,044729,523486,751908,433505,6651,126,580540,631366,587277,9801,323,285287,1802,200,1382,508,3713,192,3771,669,245528,022150,491171,9847,29598,85688,37725,5031,767,391249,160389,9951,523,401
Middle East & North Africa (WB)617,06422,743152,47917,79125,59811,55571,83755,15021,4257,96138,65712,02516,957268,382401,376292,068417,1566,73714,94616,0372662,9185,094963275,15391,1486,088320,092
Middle Income (WB)4,631,7391,114,910765,5211,005,865357,92332,326607,341138,60165,863327,645198,506424,335110,0873,543,8312,320,9412,428,7652,031,57214,054164,931141,8401853,6996,9721,7261,927,264353,21635,6681,876,967
North America (WB)537,11152,807111,500150,30743,82744138,83310,3276,21515,38311,32815930,234577,443470,19464,620423,753752109,80031,6510158111651,56142,8971,106248,801
Northern Ireland2,71519957367130112785055331401563,1511,7853291,53401421350000316551121,240
OECD Countries2,042,673232,971399,869591,738145,0134,808152,85033,51425,91054,27084,65915,72985,9091,807,1221,540,165411,0831,260,9422,293166,798108,04720334767336360,426222,1958,503912,849
Region of the Americas (WHO)1,230,167143,342214,301370,33281,18518,122107,49474,43246,60988,03737,94059,46978,798964,9141,063,762298,191940,26510,275130,06161,2341532,3924,1691,504218,938121,01518,897527,537
Scotland9,9994952,2723,1771,140491372162421,134161313,7558,1368186,390186452900107631,541355,168
South Asia (WB)1,966,216230,750346,964386,863327,040611,191309,319725,838203,46791,227204,033874,558191,1751,309,3991,441,5772,170,505771,593346,43184,716127,7802,28537,55029,78315,9391,201,872131,176218,769811,117
South-East Asia Region (WHO)2,394,045346,307342,705455,445362,548598,615355,276542,438171,058123,947189,418896,382212,4301,578,7521,686,7612,255,901918,795333,178100,177141,9681,82726,41523,09412,7021,264,076146,766208,756885,994
Sub-Saharan Africa (WB)721,69573,47486,540270,55476,955511,85461,924696,393618,295603,29218,055694,88261,517236,282431,231931,577351,910362,90637,82526,53320,420112,01690,72621,647233,02636,040340,341173,275
Wales5,3114151,1831,291649249252910045913346,8133,1587642,902134928000107291,317272,813
Western Pacific Region (WHO)3,252,290987,253470,827720,471292,55117,924497,73174,71645,049105,313105,110474,26347,4822,968,8251,507,3042,126,9171,015,7168,353117,002119,8984204,9844,2008961,584,921197,53220,9661,161,049
World10,845,5951,885,3561,844,8362,441,9741,046,0151,230,154

Data source: IHME, Global Burden of Disease (2019) – Note: Risk factors are not mutually exclusive: people may be exposed to multiple risk factors, and the number of deaths caused by each risk factor is calculated separately. OurWorldInData.org/causes-of-death | CC BY


APPENDIX – 2 – Smoking death rate in 1990 vs. 2019

Premature deaths attributed to smoking per 100,000 individuals.

Country/areaSmoking death rate in 1990deaths per 100,000 people • 1990Smoking death ratedeaths per 100,000 • 2019
Afghanistan75.881.7
Albania147.2102.6
Algeria143.976.3
American Samoa155.7116.8
Andorra116.074.1
Angola114.369.1
Antigua and Barbuda45.737.8
Argentina143.894.5
Armenia160.5117.7
Australia125.544.7
Austria106.767.9
Azerbaijan136.3145.3
Bahamas61.240.4
Bahrain212.482.7
Bangladesh200.886.4
Barbados46.232.0
Belarus159.0129.4
Belgium153.282.3
Belize61.752.8
Benin78.742.4
Bermuda93.546.0
Bhutan96.266.5
Bolivia98.543.0
Bosnia and Herzegovina159.9146.0
Botswana169.3123.0
Brazil179.873.1
Brunei249.6113.6
Bulgaria211.7148.8
Burkina Faso44.031.4
Burundi152.161.5
Cambodia222.0157.5
Cameroon61.646.2
Canada156.169.4
Cape Verde50.637.8
Central African Republic122.281.7
Chad66.656.1
Chile94.346.5
China216.5129.6
Colombia91.132.6
Comoros94.755.2
Congo97.358.8
Cook Islands146.886.9
Costa Rica79.341.4
Cote d’Ivoire76.760.9
Croatia208.2108.7
Cuba141.3103.8
Cyprus133.979.8
Czechia211.796.4
Democratic Republic of Congo77.643.5
Denmark210.0103.9
Djibouti105.289.9
Dominica64.145.6
Dominican Republic77.691.8
East Timor134.1127.8
Ecuador66.834.1
Egypt118.6125.6
El Salvador43.028.6
Equatorial Guinea105.143.2
Eritrea78.746.4
Estonia170.183.9
Eswatini103.868.3
Ethiopia66.721.2
Fiji204.4122.2
Finland123.953.7
France103.558.1
Gabon67.950.0
Gambia92.264.7
Georgia151.8122.6
Germany143.173.8
Ghana58.037.1
Greece137.4107.1
Greenland332.2193.3
Grenada72.749.0
Guam111.483.5
Guatemala76.736.6
Guinea70.379.3
Guinea-Bissau74.040.4
Guyana114.866.0
Haiti82.345.7
Honduras79.975.9
Hungary214.1131.2
Iceland133.759.6
India170.498.8
Indonesia125.1126.2
Iran99.857.4
Iraq163.1119.0
Ireland221.080.4
Israel118.951.7
Italy118.259.2
Jamaica62.357.7
Japan105.051.0
Jordan150.782.4
Kazakhstan158.8117.9
Kenya61.650.0
Kiribati407.6368.0
Kuwait88.061.7
Kyrgyzstan161.7114.6
Laos260.0150.4
Latvia167.996.6
Lebanon173.9150.7
Lesotho141.7174.9
Liberia58.234.2
Libya93.574.3
Lithuania145.389.1
Luxembourg143.465.6
Madagascar111.049.7
Malawi92.169.3
Malaysia139.899.8
Maldives219.177.6
Mali41.146.2
Malta127.858.4
Marshall Islands187.0151.8
Mauritania64.034.4
Mauritius143.461.2
Mexico95.543.9
Micronesia (country)283.0233.7
Moldova139.2102.5
Monaco122.4100.2
Mongolia191.5166.6
Montenegro160.7175.9
Morocco101.871.1
Mozambique84.773.3
Myanmar336.3147.4
Namibia154.091.6
Nauru291.4247.7
Nepal259.2186.8
Netherlands181.988.1
New Zealand156.759.3
Nicaragua56.442.0
Niger26.928.2
Nigeria34.021.6
Niue153.0117.4
North Korea137.9138.6
North Macedonia200.4170.2
Northern Mariana Islands164.6118.7
Norway118.149.0
Oman119.958.0
Pakistan182.6135.1
Palau185.9142.0
Palestine145.4102.5
Panama62.428.2
Papua New Guinea187.8161.8
Paraguay104.583.2
Peru30.514.0
Philippines158.0131.1
Poland214.4110.0
Portugal100.351.6
Puerto Rico68.537.6
Qatar108.575.1
Romania163.6108.6
Russia141.4124.7
Rwanda167.8101.3
Saint Kitts and Nevis64.739.3
Saint Lucia84.849.6
Saint Vincent and the Grenadines55.146.0
Samoa219.1165.5
San Marino92.562.0
Sao Tome and Principe36.545.4
Saudi Arabia74.164.3
Senegal69.141.7
Serbia175.1152.6
Seychelles135.1100.5
Sierra Leone108.062.6
Singapore133.537.2
Slovakia183.088.8
Slovenia127.368.9
Solomon Islands395.3328.8
Somalia113.577.2
South Africa142.975.4
South Korea151.459.4
South Sudan82.055.2
Spain120.267.6
Sri Lanka109.946.1
Sudan130.892.0
Suriname97.775.2
Sweden106.259.6
Switzerland112.354.9
Syria165.6115.5
Taiwan108.966.6
Tajikistan128.7102.6
Tanzania111.777.5
Thailand140.762.7
Togo103.266.5
Tokelau160.0111.2
Tonga162.7129.0
Trinidad and Tobago118.155.1
Tunisia119.790.6
Turkey182.799.2
Turkmenistan163.098.9
Tuvalu229.7165.9
Uganda64.648.3
Ukraine156.9152.2
United Arab Emirates128.095.0
United Kingdom195.390.2
United States160.092.5
United States Virgin Islands61.358.1
Uruguay136.091.6
Uzbekistan81.7109.8
Vanuatu191.7147.7
Venezuela109.558.9
Vietnam130.3109.9
Yemen176.6137.3
Zambia112.278.3
Zimbabwe146.7134.2
Other
African Region (WHO)82.951.5
East Asia & Pacific (WB)181.8111.7
Eastern Mediterranean Region (WHO)140.5102.1
England190.286.5
Europe & Central Asia (WB)153.195.3
European Region (WHO)153.095.1
G20163.098.2
High Income (WB)143.474.0
Latin America & Caribbean (WB)124.959.4
Low Income (WB)101.874.0
Lower Middle Income (WB)149.5101.3
Middle East & North Africa (WB)121.288.0
Middle Income (WB)177.5109.1
North America (WB)159.490.0
Northern Ireland200.692.2
OECD Countries144.173.7
Region of the Americas (WHO)145.574.8
Scotland239.9121.0
South Asia (WB)171.8100.5
South-East Asia Region (WHO)167.7100.8
Sub-Saharan Africa (WB)82.751.7
Wales199.997.5
Western Pacific Region (WHO)185.2111.7
World155.995.6

Data source: IHME, Global Burden of Disease (2019) Note: To allow comparisons between countries and over time this metric is age-standardized. – OurWorldInData.org/smoking | CC BY


reference link :

  • https://www.milieuinterieur.fr/en/about-us/the-milieu-interieur/
  • https://research.pasteur.fr/en/team/group-milieu-interieur/
  • https://www.milieuinterieur.fr/fr/news/the-milieu-interieur-project-and-covid-19/
  • https://www.nature.com/articles/s41598-020-76556-7
  • https://www.nature.com/articles/s41586-023-06968-8
  • https://pubmed.ncbi.nlm.nih.gov/36043705/
  • https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-021-01208-0
  • https://www.nature.com/articles/s41598-020-71018-6
  • https://www.nature.com/articles/s41467-021-27850-z
  • https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-020-00830-3
  • https://ourworldindata.org/smoking
  • https://www.healthdata.org/research-analysis/gbd
  • https://www.healthdata.org/research-analysis/gbd-research-library

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