Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case-control study

preprint OA: closed CC-BY-4.0
📄 Open PDF Full text JSON View at publisher

Abstract

Background Oesophageal carcinoma (OC) is a prominent cause of morbidity and mortality in low and middle-income countries yet little evidence exists about its contextual drivers. The objectives of this study were to assess the association between fermented milk (FM) ( mursik ) consumption and OC independent of known socio-demographic and lifestyle risk factors as well as to quantify its population impact among patients presenting to two referral hospitals in Nandi County, Kenya. Methods A hospital-based case-control study was employed to assess the FM-OC relationship among patients presenting to Kapsabet Surgical Care Centre and Kapsabet County Referral Hospital in Nandi County, Kenya for care between 23 rd November 2023 and 13 th January 2024. All 33 cases meeting specific eligibility criteria were prospectively recruited whilst 131 controls were simple randomly sampled and frequency-matched to the cases by hospital and day of presentation. A logistic regression model was fitted to assess the FM-OC association while adjusting for potential confounders. Subsequently, a population attributable fraction (PAF) for the association (along with its confidence interval) was estimated. Results A strong association between FM and OC was noted; the odds of OC among frequent and infrequent consumers of FM being over nine (OR 9.1, 95% CI: 3.1-26.6) and three (OR 3.2, 95% CI: 1.1-9.2) times higher, respectively, than non-consumers. This association was not substantially confounded by the studied socio-demographic and lifestyle factors. The PAF estimate for this association was 65.2% (95% CI: 40.1-90.7). Conclusions In this study setting, FM consumption was strongly associated with OC independent of other risk factors. This association registered a high PAF suggesting that up to 65% of OC in the population could be prevented if FM was not consumed. This finding calls for safe, community-owned alternatives for fermenting milk in order to mitigate the risk of OC in this population.
Full text 38,362 characters · extracted from preprint-html · click to expand
Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case-control study | 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 Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case-control study View ORCID Profile Rancy C. Mutai , View ORCID Profile Marshal M. Mweu doi: https://doi.org/10.1101/2025.04.26.25326497 Rancy C. Mutai 1 Department of Public and Global Health, Faculty of Health Sciences, University of Nairobi , Nairobi, Kenya Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rancy C. Mutai For correspondence: chepkoechrancy87{at}gmail.com Marshal M. Mweu 1 Department of Public and Global Health, Faculty of Health Sciences, University of Nairobi , Nairobi, Kenya Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Marshal M. Mweu Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background Oesophageal carcinoma (OC) is a prominent cause of morbidity and mortality in low and middle-income countries yet little evidence exists about its contextual drivers. The objectives of this study were to assess the association between fermented milk (FM) ( mursik ) consumption and OC independent of known socio-demographic and lifestyle risk factors as well as to quantify its population impact among patients presenting to two referral hospitals in Nandi County, Kenya. Methods A hospital-based case-control study was employed to assess the FM-OC relationship among patients presenting to Kapsabet Surgical Care Centre and Kapsabet County Referral Hospital in Nandi County, Kenya for care between 23 rd November 2023 and 13 th January 2024. All 33 cases meeting specific eligibility criteria were prospectively recruited whilst 131 controls were simple randomly sampled and frequency-matched to the cases by hospital and day of presentation. A logistic regression model was fitted to assess the FM-OC association while adjusting for potential confounders. Subsequently, a population attributable fraction (PAF) for the association (along with its confidence interval) was estimated. Results A strong association between FM and OC was noted; the odds of OC among frequent and infrequent consumers of FM being over nine (OR 9.1, 95% CI: 3.1-26.6) and three (OR 3.2, 95% CI: 1.1-9.2) times higher, respectively, than non-consumers. This association was not substantially confounded by the studied socio-demographic and lifestyle factors. The PAF estimate for this association was 65.2% (95% CI: 40.1-90.7). Conclusions In this study setting, FM consumption was strongly associated with OC independent of other risk factors. This association registered a high PAF suggesting that up to 65% of OC in the population could be prevented if FM was not consumed. This finding calls for safe, community-owned alternatives for fermenting milk in order to mitigate the risk of OC in this population. Introduction Gastrointestinal (GI) cancers constitute a major public health concern accounting for 26% of the global cancer incidence and 35% of all cancer-related deaths in 2018[ 1 ]. Of GI cancers, oesophageal carcinoma (OC) features prominently particularly in low and middle-income countries (LMICs) [ 2 ]. OC is a malignancy of the oesophagus typically characterised by dysphagia, odynophagia, unexplained weight loss, chest pain, worsening dyspepsia, and chronic cough[ 3 ]. In Sub-Saharan Africa, the highest incidence of OC is registered in the ‘oesophageal cancer corridor’ – an area stretching from Ethiopia to South Africa and traversing Kenya, Uganda, Tanzania and Malawi [ 4 ]. In Eastern Africa, OC incidence averages about 8.3 per 100,000 person-years [ 1 ]– Kenya recording an age-standardised incidence of 28.7 cases per 100,000 [ 5 ] and a case fatality rate of 99%[ 6 ]. Fermented milk (FM) (commonly known as mursik ) remains a favourite cultural beverage among the indigenous inhabitants of the Rift Valley region of Kenya [ 7 , 8 ]. It is prepared by boiling and fermenting fresh cow’s or goat’s milk for a period of 3-5 days, and thereafter, charcoal powder is added[ 7 , 8 ]. Despite the health benefits of fermented milk, its consumption has been linked to the occurrence of OC [ 9 ] ascribable to improper milk handling and fermentation processes which may introduce contaminants such as moulds that produce various mycotoxins[ 7 , 10 ]. These toxins may contribute to oesophageal carcinogenesis when ingested habitually[ 8 , 10 ]. Moreover, charcoal as a key ingredient is believed to harbour polycyclic aromatic hydrocarbons (PAHs)[ 11 ] that could catalyse the carcinogenicity of mursik . Besides FM, alcohol and tobacco use, biomass fuels, socio-demographic characteristics and hot beverage consumption are well-recognised risk factors for OC [ 9 , 12 – 17 ]. Alcoholic drinks may contain acetaldehydes and nitrosamines that are carcinogenic [ 9 , 18 ]. PAHs, aldehydes, and nitrosamines released during tobacco smoking may precipitate carcinogenesis[ 19 ]. In Kenya, wood fuel, ubiquitously used in rural households, is known to emit PAHs, benzene, arsenic, 1,3-butadiene and formaldehyde that can trigger oesophageal carcinogenesis[ 16 , 17 , 20 , 21 ]. The risk of OC increases with age, with individuals aged ≥50 years bearing a disproportionate risk [ 13 ]. OC is more common in males than females – attributable to higher rates of tobacco smoking and alcohol use among males[ 22 , 23 ]. Consumption of hot beverages >65 0 c could potentially be carcinogenic[ 24 ]. Hot drinks may instigate thermal injury of the oesophageal mucosa – a risk for OC[ 25 , 26 ]. Despite OC’s preponderance in LMICs, there is scarcity of evidence on its contextual drivers in endemic settings. Consequently, the objectives of this study were to quantify the association between FM consumption and OC independent of known risk factors as well as to estimate FM’s population impact among patients presenting to two referral hospitals in Nandi County, Kenya. An understanding of FM’s role in the occurrence of OC is critical to guiding policy development and informing the design of appropriate interventions for the control of OC in Kenya. Materials and Methods Study setting, design and population The study was carried out at Kapsabet Surgical Care Centre (KSCC) and Kapsabet County Referral Hospital (KCRH) situated in Kapsabet town, Nandi County within the Rift Valley region of Kenya. KSCC is a private hospital specialising in endoscopy and surgical care whereas KCRH is a state-run referral facility offering a range of preventive and curative services. Notably, the two hospitals serve a catchment population of ∼ 885,700 persons comprising majorly of Nandi natives of the Kalenjin community [ 27 ]. Of note, subsistence and commercial crop (tea and maize) and dairy farming are the economic mainstay of this region. A hospital-based case-control study design was employed in this study to evaluate the association between FM consumption and OC. The rationale for the choice of the design stems not only from its suitability for studying rare outcomes but also the ease and efficiency of recruitment of cases presenting to a hospital setting for care. Importantly, the study conformed to STROBE guidelines for reporting of case-control studies [ 28 ]. The study population comprised County-resident patients aged ≥18 years presenting to KSCC and KCRH for care between 23 rd November 2023 and 13 th January 2024 and who had consented to participate in the study. Critically-ill patients and those uninterviewable and/or unable to give consent were excluded from the study. Outcome definition Cases were eligible individuals attending the facilities with any suggestive symptoms: dysphagia, odynophagia, persistent coughing, chest pains and unexplained weight loss and had a confirmed diagnosis of OC during the study period. Controls were patients presenting to the same facilities as cases but with other conditions. Sample size and participant selection The size of the study sample was estimated as suggested by Kelsey et al . [ 29 ] for case control studies: Where Z α = 1.96 is the required value for a two-tailed 95% confidence level; Z β = -0.84 is the desired value for an 80% statistical power; n 1 is the number of cases; n 2 is the number of controls; r = 4 is the ratio of controls to cases; p 1 is the proportion of cases consuming FM; p 2 is the proportion of controls that consume FM – specified at 10.5% based on a previous study[ 9 ] and OR is the odds ratio for the FM-OC association (set at 3.72) informed by literature[ 9 ]. Given an anticipated non-response rate of 5%, the necessary sample was 164 subjects: 33 cases and 131 controls. All eligible cases were prospectively recruited over the study period within the facilities until the desired number was attained. Controls were simple randomly sampled from a sampling frame of patients admitted at the facilities’ medical and surgical wards and frequency-matched to cases by hospital and day of presentation. Study variables The primary exposure in this study was FM consumption. The other exposures considered included the participants’ sociodemographic characteristics (age, sex, education level, employment status and marital status), lifestyle factors (alcohol, tobacco use and beverage temperature) and cooking fuel. These variables were measured using an orally administered semi-structured questionnaire captured in both English and Swahili. Table 1 displays the assessment of these variables. View this table: View inline View popup Download powerpoint Table 1. Measurement of the study variables Ethical considerations Written permission to conduct the study was secured from the Kenyatta National Hospital-University of Nairobi Ethics and Research Committee (PF26/06/2023), the National Commission for Science, Technology and Innovation (NACOSTI/P/23/30502) and the Nandi County Health Services (Ref. No. CDH/NDI/2021/R.A/5). Furthermore, written informed consent was obtained from the participants prior to enlisting them in the study. In addition, the data collected were analyzed anonymously. Minimisation of biases Before data collection, two research assistants were trained on standardised interviewing techniques in order to limit interviewer bias during elicitation of information from respondents. Since differential recall of consumption habits (FM, alcohol and beverage) between cases and controls was likely, questioning on these related to recent consumption. Moreover, as the likelihood of altering consumption patterns by cases was probable, reverse causality was minimised by focusing on incident cases. Statistical analysis Upon data collection, the questionnaire responses were examined for completeness, after which qualitative variables were coded. Subsequently, the data were entered into a Microsoft Excel spreadsheet and cross-checked for accuracy. The dataset was then exported to R software v4.4.0 for cleaning and analysis. The R code for these analyses is available as supporting information[ 30 ]. For descriptive statistics, medians and ranges were computed for continuous variables whereas frequencies and percentages summarised categorical variables. A logistic regression model was fitted to evaluate the crude association between FM and OC. To evaluate the study covariates (age, sex, education level, employment status, marital status, alcohol, cooking fuel, tobacco and beverage temperature) as potential confounders of the FM–OC association, each of these factors was separately screened for its association with OC and FM using the Fisher’s exact test at P <0.05 (this two-stage testing process is synonymous with sequential screening where only variables associated with the outcome at P 65 years and cooking fuel was reclassified into two categories: biomass/kerosene and natural/biogas since there were no cases using kerosene. Qualifying covariates from this sequential screening were deemed potential confounders of the FM–OC relationship and thus included in a multivariable logistic regression model to adjust for their confounding effect. At this stage, only those variables that resulted in a >20% change in the coefficient for FM following a backward step-wise elimination procedure were considered important confounders and thus retained in the final model [ 31 ]. A population attributable fraction (PAF) – a measure quantifying the proportion of disease in the population that is preventable if the exposure were eliminated[ 31 ]– was computed from estimates of the final model [ 32 ]: Where: pd i reflects the proportion of cases consuming FM infrequently and frequently (non-baseline categories) and a OR i is the specific adjusted odds ratio for the non-baseline levels of FM. Estimation of PAF (along with its bootstrapped confidence interval) was realised using the graphPAF package [ 33 ]written in R software. Results Of the sample of 164 subjects, 160 (32 cases and 128 controls) gave consent to the study. Descriptive statistics for the study exposure variables are indicated in Table 2 . The respondents’ median age was 60 years (Range: 30-78) for cases and 50 years (Range: 21-98) for controls. On FM, 46.9% ( n = 15) of cases were frequent consumers compared with 14.8% ( n = 19) of controls. About 28.1% ( n = 9) of cases were frequent consumers of alcohol in comparison with 10.2% ( n = 13) of controls. View this table: View inline View popup Download powerpoint Table 2. Summary statistics for the socio-demographic and lifestyle characteristics of the respondents The crude association between FM and OC is captured in Table 3 . The odds of OC were approximately three (3.2; 95% CI: [1.1-9.2]) and nine (9.1; 95% CI: [3.1-26.6]) times higher amongst infrequent and frequent consumers, respectively, than non-consumers. View this table: View inline View popup Download powerpoint Table 3. Univariable analysis of the association between fermented milk consumption and oesophageal carcinoma among patients at KSCC and KCRH, Nandi County, Kenya The association between individual covariates and OC is presented in Table 4 . Notably, age group, education level, alcohol and tobacco were associated with OC at the 5% significance level. As such, these variables qualified for assessment of their association with FM. View this table: View inline View popup Download powerpoint Table 4. Association between individual covariates and oesophageal carcinoma among patients attending KSCC and KCRH, Nandi County, Kenya Table 5 presents the results for the association between qualifying covariates and FM. Importantly, only age group and alcohol were significantly associated with fermented milk ( p <0.05). Consequently, these variables were deemed potential confounders of the FM-OC association and were offered to a multivariable logistic regression model to adjust for their confounding effect. View this table: View inline View popup Download powerpoint Table 5. Association between qualifying exposures and fermented milk consumption among patients attending KSCC and KCRH, Nandi County, Kenya Results of the multivariable analysis of the FM-OC association are presented in Table 6 . Since alcohol and age group did not confound the FM-OC association (i.e. neither of the factors resulted in a >20% change in the coefficient for FM) the odds ratio for the unadjusted association was maintained and subsequently employed in the derivation of PAF. The PAF estimate for the FM-OC association was 65.2% (95% CI: 40.1-90.7). View this table: View inline View popup Download powerpoint Table 6: Multivariable analysis of the association between fermented milk and oesophageal carcinoma among patients at KSCC and KCRH, Nandi County, Kenya Discussion In this population, an analysis of the association between FM consumption and OC has demonstrated a robust relationship. The odds of OC were roughly three and nine times higher amongst infrequent and frequent consumers, respectively, than non-consumers; signifying a dose-response relationship. In particular, this association was not confounded by any of the examined covariates. Patel et al. [2013][ 9 ] corroborate this strong relationship – observing about four times higher odds of OC amongst mursik consumers. Importantly, markedly high concentrations of ethanol (>100mM) and acetaldehyde (>1800µM) have been detected previously in mursik [ 10 ] – carcinogenicity of acetaldehyde being exhibited in both animal and in vitro models at fairly low concentrations (100 µM) [ 34 , 35 ]Conceivably, recurrent exposure of the oesophageal mucosa to these mutagenic substances in mursik may explain its carcinogenicity. In Afghanistan, a linkage between consumption of fermented dairy products (cheese and yoghurt) and OC has been established[ 36 ]. As sterility during the traditional fermentation process is not guaranteed, contamination of mursik by fungal species of the genera Aspergillus, Penicillium and Fusarium is likely, with resultant production of mycotoxins [ 7 ]. Of these, aflatoxin is the predominant metabolite recovered from mursik [ 37 ]. Notably, aflatoxins have been implicated in oesophageal carcinogenesis [ 38 ]. Customarily, fermentation gourds for mursik are lined with specially ground fine charcoal that imparts a smoky flavour[ 39 ]. Nonetheless, charcoal could be a source of PAHs – potentially carcinogenic – spurring oesophageal carcinogenesis[ 11 ]. More so, charcoal-derived carcinogens have been pointed out as contributory to the high incidence of OC in Iran [ 40 ]. Despite our finding of a significant elevated risk of OC with FM consumption, some studies have posted contradictory findings[ 19 , 41 ]. In particular, Oncina-Cánovas et al. [ 41 ] report a protective association between consumption of fermented dairy products and OC. This divergence of observations across study contexts underscores the need to carefully examine the role played by disparate dairy fermentation processes in driving local and/or regional OC burdens. The PAF estimate of 65.2% for FM in this study implies that roughly two-thirds of OC in the study population could potentially be prevented if FM was not consumed. Irrefutably, FM as a singular factor is impactful in this population – contributing significantly to the OC burden in this setting. This highlights the necessity of raising awareness on general safety practices for preparing fermented milk. A few limitations are inherent in this study. Despite efforts to adjust the association for known confounders, the possibility of residual confounding persists. Other unmeasurable factors such as genetic predispositions and environmental exposures could still have influenced the observed relationship between FM and OC. Although the recruitment of controls from hospital settings not only affords convenience but also controls for potential differences in health-seeking behaviours between cases and controls, their utility may introduce selection bias. Hospitalised controls generally tend to have higher exposures compared to the general population that they represent. Consequently, for our study, this undertaking is likely to have weakened the FM-OC association. Conclusions This study has revealed a strong association between FM consumption and OC in this setting. This relationship was not confounded by any of the studied factors. The association yielded a high PAF implying that up to 65% of OC in the population could be prevented if FM was not consumed. This finding calls for dedicated campaigns to raise local awareness with a view to develop safe, community-acceptable fermentation processes to mitigate OC risk. Data Availability All relevant data are within the manuscript and its Supporting Information files. https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DC0IMK Acknowledgments The authors heartily thank the study participants, the administration and staff at KSCC and KCRH for making it possible to accomplish this research work. References 1. ↵ Arnold M , Abnet CC , Neale RE , Vignat J , Giovannucci EL , McGlynn KA , et al. Global Burden of 5 Major Types of Gastrointestinal Cancer . Gastroenterology . 2020 ; 159 : 335 - 349.e15 . doi: 10.1053/j.gastro.2020.02.068 OpenUrl CrossRef PubMed 2. ↵ Kamangar F , Nasrollahzadeh D , Safiri S , Sepanlou SG , Fitzmaurice C , Ikuta KS , et al. The global, regional, and national burden of oesophageal cancer and its attributable risk factors in 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017 . Lancet Gastroenterol Hepatol . 2020 ; 5 : 582 – 597 . doi: 10.1016/S2468-1253(20)30007-8 OpenUrl CrossRef PubMed 3. ↵ Ellis A , Risk JM , Maruthappu T , Kelsell DP . Tylosis with oesophageal cancer: Diagnosis, management and molecular mechanisms . Orphanet J Rare Dis . 2015 ; 10 : 4 – 9 . doi: 10.1186/s13023-015-0346-2 OpenUrl CrossRef PubMed 4. ↵ Schaafsma T , Wakefield J , Hanisch R , Bray F , Schüz J , Joy EJM , et al. Africa’s oesophageal cancer corridor: Geographic variations in incidence correlate with certain micronutrient deficiencies . PLoS One . 2015 ; 10 . doi: 10.1371/journal.pone.0140107 OpenUrl CrossRef 5. ↵ Asombang AW , Chishinga N , Nkhoma A , Chipaila J , Nsokolo B , Manda-Mapalo M , et al. Systematic review and meta-analysis of esophageal cancer in Africa: Epidemiology, risk factors, management and outcomes . World J Gastroenterol . 2019 ; 25 : 4512 – 4533 . doi: 10.3748/wjg.v25.i31.4512 OpenUrl CrossRef PubMed 6. ↵ Ministry of Health . Kenya-Cancer-Policy-2020. Afya House, Nairobi ; 2020 . 7. ↵ John MN , Joseph WM , Zacchaeus ON , Moses BS . Spontaneously fermented kenyan milk products: A review of the current state and future perspectives . African Journal of Food Science . 2017 ; 11 : 1 – 11 . doi: 10.5897/ajfs2016.1516 OpenUrl CrossRef 8. ↵ Kigen G , Busakhala N , Kamuren Z , Rono H , Kimalat W , Njiru E. Factors associated with the high prevalence of oesophageal cancer in Western Kenya: A review . Infectious Agents and Cancer . BioMed Central Ltd .; 2017 . doi: 10.1186/s13027-017-0169-y OpenUrl CrossRef 9. ↵ Patel K , Wakhisi J , Mining S , Mwangi A , Patel R. MTRH in the Rift Valley, Kenya, and Its Potential Risk Factors . Article ID . 2013 ; 2013 . doi: 10.1155/2013/503249 OpenUrl CrossRef 10. ↵ Nieminen MT , Novak-Frazer L , Collins R , Dawsey SP , Dawsey SM , Abnet CC , et al. Alcohol and acetaldehyde in African fermented milk mursik - A possible etiologic factor for high incidence of esophageal cancer in Western Kenya . Cancer Epidemiology Biomarkers and Prevention . 2013 ; 22 : 69 – 75 . doi: 10.1158/1055-9965.EPI-12-0908 OpenUrl Abstract / FREE Full Text 11. ↵ Liu G , Niu Z , Van Niekerk D , Xue J , Zheng L. Polycyclic aromatic hydrocarbons (PAHs) from coal combustion: Emissions, analysis, and toxicology . Rev Environ Contam Toxicol . 2008 ; 192 : 1 – 28 . doi: 10.1007/978-0-387-71724-1_1 OpenUrl CrossRef PubMed 12. ↵ Yang J , Liu X , Cao S , Dong X , Rao S , Cai K. Understanding Esophageal Cancer: The Challenges and Opportunities for the Next Decade . Front Oncol . 2020 ; 10 : 1 – 13 . doi: 10.3389/fonc.2020.01727 OpenUrl CrossRef PubMed 13. ↵ Odera JO , Odera E , Githang’a J , Walong EO , Li F , Xiong Z , et al. Esophageal cancer in Kenya . Am J Dig Dis (Madison) . 2017 ; 4 : 23 – 33 . OpenUrl PubMed 14. Arnal MJD , Arenas ÁF , Arbeloa ÁL. Esophageal cancer: Risk factors, screening and endoscopic treatment in Western and Eastern countries . World J Gastroenterol . 2015 ; 21 : 7933 – 7943 . doi: 10.3748/wjg.v21.i26.7933 OpenUrl CrossRef PubMed 15. Saadaat R , Abdul-Ghafar J , Hanifi AN , Khalid S , Khairy AL , Ibrahimkhil AS , et al. Risk factors associated with esophageal cancers, diagnosed at tertiary level in Afghanistan: a descriptive cross-sectional study . BMC Cancer . 2022 ; 22 : 1112 . doi: 10.1186/s12885-022-10228-9 OpenUrl CrossRef PubMed 16. ↵ Okello S , Akello SJ , Dwomoh E , Byaruhanga E , Opio CK , Zhang R , et al. Biomass fuel as a risk factor for esophageal squamous cell carcinoma: A systematic review and meta-analysis . Environ Health . 2019 ; 18 . doi: 10.1186/s12940-019-0496-0 OpenUrl CrossRef 17. ↵ Josyula S , Lin J , Xue X , Rothman N , Lan Q , Rohan TE , et al. Household air pollution and cancers other than lung: A meta-analysis . Environmental Health: A Global Access Science Source. BioMed Central Ltd .; 2015 . doi: 10.1186/s12940-015-0001-3 OpenUrl CrossRef PubMed 18. ↵ Yang CS , Chen XL . Research on esophageal cancer: With personal perspectives from studies in China and Kenya . Int J Cancer . 2021 ; 149 : 264 – 276 . doi: 10.1002/ijc.33421 OpenUrl CrossRef 19. ↵ Wang T , Zhu Y , Zheng Y , Cao Y , Xu Q , Wang X , et al. Dairy consumption and risk of esophagus cancer in the prostate, lung, colorectal, and ovarian cohort . Front Nutr . 2022 ; 9 . doi: 10.3389/fnut.2022.1015062 OpenUrl CrossRef 20. ↵ Gauggel-Lewandowski S , Heussner AH , Steinberg P , Pieterse B , Van Der Burg B , Dietrich DR . Bioavailability and potential carcinogenicity of polycyclic aromatic hydrocarbons from wood combustion particulate matter in vitro . Chem Biol Interact . 2013 ; 206 : 411 – 422 . doi: 10.1016/j.cbi.2013.05.015 OpenUrl CrossRef PubMed 21. ↵ Gustafson P , Barregard L , Strandberg B , Sällsten G. The impact of domestic wood burning on personal, indoor and outdoor levels of 1,3-butadiene, benzene, formaldehyde and acetaldehyde . Journal of Environmental Monitoring . 2007 ; 9 : 23 – 32 . doi: 10.1039/b614142k OpenUrl CrossRef PubMed 22. ↵ Nasrollahzadeh D , Kamangar F , Aghcheli K , Sotoudeh M , Islami F , Abnet CC , et al. Opium, tobacco, and alcohol use in relation to oesophageal squamous cell carcinoma in a high-risk area of Iran . Br J Cancer . 2008 ; 98 : 1857 – 1863 . doi: 10.1038/sj.bjc.6604369 OpenUrl CrossRef PubMed Web of Science 23. ↵ Liu CQ , Ma YL , Qin Q , Wang PH , Luo Y , Xu PF , et al. Epidemiology of esophageal cancer in 2020 and projections to 2030 and 2040 . Thoracic Cancer . John Wiley and Sons Inc ; 2023 . pp. 3 – 11 . doi: 10.1111/1759-7714.14745 OpenUrl CrossRef PubMed 24. ↵ Loomis D , Guha N , Hall AL , Straif K. Identifying occupational carcinogens: An update from the IARC Monographs . Occupational and Environmental Medicine . BMJ Publishing Group ; 2018 . pp. 593 – 603 . doi: 10.1136/oemed-2017-104944 OpenUrl Abstract / FREE Full Text 25. ↵ Luo H , Ge H. Hot Tea Consumption and Esophageal Cancer Risk: A Meta-Analysis of Observational Studies . Front Nutr . 2022 ; 9 : 1 – 10 . doi: 10.3389/fnut.2022.831567 OpenUrl CrossRef 26. ↵ Chen Y , Tong Y , Yang C , Gan Y , Sun H , Bi H , et al. Consumption of hot beverages and foods and the risk of esophageal cancer: A meta-analysis of observational studies . BMC Cancer . 2015 ; 15 . doi: 10.1186/s12885-015-1185-1 OpenUrl CrossRef PubMed 27. ↵ Kenya National Bureau of Statistics . Kenya population and housing census volume 1: Population by County and sub-County. Kenya National Bureau of Statistics . 2019 . Available: https://www.knbs.or.ke/?wpdmpro=2019-kenya-population-and-housing-census-volume-i-population-by-county-and-sub-county 28. ↵ von Elm E , Altman DG , Egger M , Pocock SJ , Gøtzsche PC , Vandenbroucke JP . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies . J Clin Epidemiol . 2008 ; 61 : 344 – 349 . doi: 10.1016/J.JCLINEPI.2007.11.008 OpenUrl CrossRef PubMed Web of Science 29. ↵ Kelsey L. Jennifer , Whittemore S. Alice , Evans S. Alfred , Thomson W. Douglas . Methods in Observational Epidemiology . Second Edition. New York : Oxford University Press, Inc .; 1996 . Available: https://books.google.co.in/books?id=Xnz6VgL22osC&printsec=frontcover&source=gbsgesummaryr&cad=0#v=onepage&q&f=false 30. ↵ Mutai R. Replication Data: Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case control study . DRAFT VERSION ed: Harvard Dataverse . 2025 ; 1 . doi: 10.7910/DVN/DC0IMK OpenUrl CrossRef 31. ↵ Dohoo IR , Martin W , Stryhn H. Methods in Epidemiologic Research. 1st Ed. Book . Charlottetown, P.E.I.: VER, Inc .; 2012 . Available: https://books.google.co.ke/books?id=2kQm1AEACAAJ 32. ↵ Rockhill B , Newman B , Weinberg C. Use and misuse of population attributable fractions . Am J Public Health . 1998 ; 88 : 15 – 19 . doi: 10.2105/AJPH.88.1.15 OpenUrl CrossRef PubMed Web of Science 33. ↵ Ferguson J , O’Connell M. Estimating and displaying population attributable fractions using the R package: graphPAF . Eur J Epidemiol . 2024 ; 39 : 715 – 742 . doi: 10.1007/s10654-024-01129-1 OpenUrl CrossRef PubMed 34. ↵ Lachenmeier DW , Sohnius EM . The role of acetaldehyde outside ethanol metabolism in the carcinogenicity of alcoholic beverages: Evidence from a large chemical survey . Food and Chemical Toxicology . 2008 ; 46 : 2903 – 2911 . doi: 10.1016/J.FCT.2008.05.034 OpenUrl CrossRef PubMed 35. ↵ Seitz HK , Stickel F. Molecular mechanisms of alcohol-mediated carcinogenesis . Nature Reviews Cancer . 2007 . pp. 599 – 612 . doi: 10.1038/nrc2191 OpenUrl CrossRef PubMed Web of Science 36. ↵ Eser S , Özgür S , Shayan NA , Abdianwall MH . Risk Factors Related to Esophageal Cancer, a Case-Control Study in Herat Province of Afghanistan . Arch Iran Med . 2022 ; 25 : 682 – 690 . doi: 10.34172/aim.2022.107 OpenUrl CrossRef PubMed 37. ↵ Talaam KK , Nga’ng’a ZW , Lang’at KB , Kirui MC , Gonoi T , Bii CC . The Presence of Mycotoxins in Kenya’s Kalenjin Traditional Fermented Milk “Mursik.” J Sci Res Rep . 2018 ; 21 : 1 – 8 . doi: 10.9734/jsrr/2018/7500 OpenUrl CrossRef 38. ↵ Ghasemi-Kebria F , Joshaghani H , Taheri NS , Semnani S , Aarabi M , Salamat F , et al. Aflatoxin contamination of wheat flour and the risk of esophageal cancer in a high risk area in Iran . Cancer Epidemiol . 2013 ; 37 : 290 – 293 . doi: 10.1016/J.CANEP.2013.01.010 OpenUrl CrossRef 39. ↵ Mureithi W , Den Biggelaar C , Wesakania EW , Kamau K , Gatundu C. MANAGEMENT OF TREES USED IN MURSIK (FERMENTED MILK) PRODUCTION IN TRANS-NZOIA DISTRICT, KENYA . J Ethnobiol . 2000 . 40. ↵ Hakami R , Javad M , Arash E , Farin K , Mahboob N , Akram P , et al. Dietary Intake of Benzo(a)pyrene and Risk of Esophageal Cancer in North of Iran . Nutr Cancer . 2008 ; 60 : 216 – 221 . doi: 10.1080/01635580701684831 OpenUrl CrossRef PubMed Web of Science 41. ↵ Oncina-Cánovas A , Torres-Collado L , García-de-la-Hera M , Compañ-Gabucio LM , González-Palacios S , Signes-Pastor AJ , et al. Association Between Dairy Products Consumption and Esophageal, Stomach, and Pancreatic Cancers in the PANESOES Multi Case–Control Study . Cancers (Basel) . 2024 ; 16 . doi: 10.3390/cancers16244151 OpenUrl CrossRef View the discussion thread. Back to top Previous Next Posted April 28, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case-control study Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case-control study Rancy C. Mutai , Marshal M. Mweu medRxiv 2025.04.26.25326497; doi: https://doi.org/10.1101/2025.04.26.25326497 Share This Article: Copy Citation Tools Association between fermented milk consumption and oesophageal carcinoma among patients presenting to two referral hospitals in Nandi County, Kenya: a case-control study Rancy C. Mutai , Marshal M. Mweu medRxiv 2025.04.26.25326497; doi: https://doi.org/10.1101/2025.04.26.25326497 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Epidemiology Subject Areas All Articles Addiction Medicine (569) Allergy and Immunology (863) Anesthesia (300) Cardiovascular Medicine (4442) Dentistry and Oral Medicine (444) Dermatology (383) Emergency Medicine (609) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1511) Epidemiology (15230) Forensic Medicine (30) Gastroenterology (1126) Genetic and Genomic Medicine (6610) Geriatric Medicine (668) Health Economics (998) Health Informatics (4542) Health Policy (1370) Health Systems and Quality Improvement (1613) Hematology (543) HIV/AIDS (1266) Infectious Diseases (except HIV/AIDS) (15923) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (147) Nephrology (668) Neurology (6607) Nursing (346) Nutrition (999) Obstetrics and Gynecology (1146) Occupational and Environmental Health (957) Oncology (3337) Ophthalmology (974) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (664) Pediatrics (1693) Pharmacology and Therapeutics (692) Primary Care Research (712) Psychiatry and Clinical Psychology (5448) Public and Global Health (9238) Radiology and Imaging (2202) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1196) Rheumatology (596) Sexual and Reproductive Health (714) Sports Medicine (530) Surgery (712) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a01b2b033de824f0',t:'MTc3OTc4MTYwNg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-05-26T02:00:01.498150+00:00
License: CC-BY-4.0